From 19c30904350ec6241652cd618ff9fc0e255c8515 Mon Sep 17 00:00:00 2001 From: Valentin Sulzer Date: Thu, 18 Nov 2021 18:45:15 -0500 Subject: [PATCH 1/8] #1810 allow strings for parameter sets --- CHANGELOG.md | 2 + benchmarks/time_setup_models_and_sims.py | 12 +- benchmarks/time_solve_models.py | 3 +- docs/tutorials/add-parameter-values.rst | 4 +- ...utorial 4 - Setting parameter values.ipynb | 861 ++++++------------ .../Tutorial 9 - Changing the mesh.ipynb | 2 +- examples/notebooks/batch_study.ipynb | 14 +- ...DFN-with-particle-size-distributions.ipynb | 4 +- examples/notebooks/models/MPM.ipynb | 2 +- ...ating_mechanical_models_Enertech_DFN.ipynb | 2 +- .../notebooks/models/compare-ecker-data.ipynb | 2 +- .../models/electrode-state-of-health.ipynb | 2 +- .../notebooks/models/lithium-plating.ipynb | 2 +- ...simulating-ORegan-2021-parameter-set.ipynb | 2 +- .../models/submodel_cracking_DFN_or_SPM.ipynb | 2 +- .../submodel_loss_of_active_materials.ipynb | 2 +- .../notebooks/models/thermal-models.ipynb | 2 +- .../using-model-options_thermal-example.ipynb | 2 +- .../parameterization/parameter-values.ipynb | 2 +- .../parameterization/parameterization.ipynb | 2 +- .../simulating-long-experiments.ipynb | 2 +- examples/scripts/DFN_size_distributions.py | 12 +- .../scripts/compare_lithium_ion_half_cell.py | 2 +- examples/scripts/compare_particle_models.py | 2 +- examples/scripts/cycling_ageing.py | 2 +- examples/scripts/nca_parameters.py | 2 +- examples/scripts/print_parameters.py | 2 +- .../lead_acid/base_lead_acid_model.py | 2 +- .../lithium_ion/Yang2017.py | 2 +- .../lithium_ion/base_lithium_ion_model.py | 4 +- .../effective_resistance_current_collector.py | 4 +- pybamm/parameters/parameter_values.py | 101 +- .../base_lithium_ion_tests.py | 27 +- .../test_basic_half_cell_models.py | 4 +- .../test_lithium_ion/test_dfn.py | 2 +- .../test_lithium_ion/test_mpm.py | 2 +- .../test_lithium_ion/test_thermal_models.py | 2 +- tests/unit/test_citations.py | 12 +- .../test_simulation_with_experiment.py | 18 +- .../test_lithium_ion/test_Yang2017.py | 3 +- .../test_lithium_ion/test_basic_models.py | 3 +- .../test_parameter_sets/test_LCO_Ai2020.py | 5 +- .../test_LCO_Ramadass2004.py | 8 +- .../test_parameter_sets/test_LFP_Prada2013.py | 2 +- .../test_LGM50_Chen2020.py | 2 +- .../test_LGM50_ORegan2021.py | 4 +- .../test_Landesfeind2019.py | 2 +- .../test_parameter_sets/test_NCA_Kim2011.py | 2 +- .../test_parameter_sets/test_NCO_Ecker2015.py | 2 +- .../test_NMChalfcell_Xu2019.py | 2 +- .../test_parameter_sets/test_OKane2020.py | 11 +- .../test_UMBL_Mohtat2020.py | 2 +- .../test_parameters/test_parameter_values.py | 25 +- tests/unit/test_plotting/test_quick_plot.py | 3 +- tests/unit/test_simulation.py | 2 +- tests/unit/test_solvers/test_casadi_solver.py | 113 ++- 56 files changed, 502 insertions(+), 819 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 14aa69e538..8b42d43b11 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -2,6 +2,7 @@ ## Features +- The name of a parameter set can be passed to `ParameterValues` as a string, e.g. `ParameterValues("Chen2020")` - Reformatted SEI growth models into a single submodel with conditionals ([#1808](https://github.com/pybamm-team/PyBaMM/pull/1808)) - Stress-induced diffusion is now a separate model option instead of being automatically included when using the particle mechanics submodels ([#1797](https://github.com/pybamm-team/PyBaMM/pull/1797)) - `Experiment`s with drive cycles can be solved ([#1793](https://github.com/pybamm-team/PyBaMM/pull/1793)) @@ -18,6 +19,7 @@ ## Breaking changes +- The `chemistry` keyword argument in `ParameterValues` has been deprecated. Use `ParameterValues(chem)` instead of `ParameterValues(chemistry=chem)` - Raise error when trying to convert an `Interpolant` with the "pchip" interpolator to CasADI ([#1791](https://github.com/pybamm-team/PyBaMM/pull/1791)) - Raise error if `Concatenation` is used directly with `Variable` objects (`concatenation` should be used instead) ([#1789](https://github.com/pybamm-team/PyBaMM/pull/1789)) - Made jax, jaxlib and the PyBaMM JaxSolver optional ([#1767](https://github.com/pybamm-team/PyBaMM/pull/1767)) diff --git a/benchmarks/time_setup_models_and_sims.py b/benchmarks/time_setup_models_and_sims.py index 7ce44d9c81..2aa2e7a421 100644 --- a/benchmarks/time_setup_models_and_sims.py +++ b/benchmarks/time_setup_models_and_sims.py @@ -19,7 +19,7 @@ def compute_discretisation(model, param): class TimeBuildSPM: def __init__(self): - self.param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + self.param = pybamm.ParameterValues("Marquis2019") def time_setup_SPM(self): self.model = pybamm.lithium_ion.SPM() @@ -29,7 +29,7 @@ def time_setup_SPM(self): class TimeBuildSPMe: def __init__(self): - self.param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + self.param = pybamm.ParameterValues("Marquis2019") def time_setup_SPMe(self): self.model = pybamm.lithium_ion.SPMe() @@ -39,7 +39,7 @@ def time_setup_SPMe(self): class TimeBuildDFN: def __init__(self): - self.param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + self.param = pybamm.ParameterValues("Marquis2019") def time_setup_DFN(self): self.model = pybamm.lithium_ion.DFN() @@ -52,7 +52,7 @@ class TimeBuildSPMSimulation: params = [False, True] def __init__(self): - self.param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + self.param = pybamm.ParameterValues("Marquis2019") def time_setup_SPM_simulation(self, with_experiment): self.model = pybamm.lithium_ion.SPM() @@ -72,7 +72,7 @@ class TimeBuildSPMeSimulation: params = [False, True] def __init__(self): - self.param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + self.param = pybamm.ParameterValues("Marquis2019") def time_setup_SPMe_simulation(self, with_experiment): self.model = pybamm.lithium_ion.SPMe() @@ -92,7 +92,7 @@ class TimeBuildDFNSimulation: params = [False, True] def __init__(self): - self.param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + self.param = pybamm.ParameterValues("Marquis2019") def time_setup_DFN_simulation(self, with_experiment): self.model = pybamm.lithium_ion.DFN() diff --git a/benchmarks/time_solve_models.py b/benchmarks/time_solve_models.py index 1cbfc47673..517238e324 100644 --- a/benchmarks/time_solve_models.py +++ b/benchmarks/time_solve_models.py @@ -9,8 +9,7 @@ def prepare_model(model): geometry = model.default_geometry # load parameter values and process model and geometry - chemistry = pybamm.parameter_sets.Marquis2019 - param = pybamm.ParameterValues(chemistry=chemistry) + param = pybamm.ParameterValues("Marquis2019") param.process_model(model) param.process_geometry(geometry) diff --git a/docs/tutorials/add-parameter-values.rst b/docs/tutorials/add-parameter-values.rst index ba69b9c2cb..63625044de 100644 --- a/docs/tutorials/add-parameter-values.rst +++ b/docs/tutorials/add-parameter-values.rst @@ -123,7 +123,7 @@ Then, to use these new parameters, use: .. code-block:: python - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.AuthorYear) + param = pybamm.ParameterValues("AuthorYear") Note that you can re-use existing parameter subsets instead of creating new ones (for example, you could just replace "experiment": "new_experiment_AuthorYear" with "experiment": "1C_discharge_from_full_Marquis2019" in the above dictionary). @@ -173,7 +173,7 @@ To test this, add something like the following test to one of the model test fil def test_my_new_parameters(self): model = pybamm.lithium_ion.DFN() - parameter_values = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.AuthorYear) + parameter_values = pybamm.ParameterValues("AuthorYear") modeltest = tests.StandardModelTest(model, parameter_values=parameter_values) modeltest.test_all() diff --git a/examples/notebooks/Getting Started/Tutorial 4 - Setting parameter values.ipynb b/examples/notebooks/Getting Started/Tutorial 4 - Setting parameter values.ipynb index effdc5193c..6011ef6d8f 100644 --- a/examples/notebooks/Getting Started/Tutorial 4 - Setting parameter values.ipynb +++ b/examples/notebooks/Getting Started/Tutorial 4 - Setting parameter values.ipynb @@ -54,60 +54,7 @@ "metadata": {}, "outputs": [], "source": [ - "chemistry = pybamm.parameter_sets.Chen2020" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This variable is a dictionary with the corresponding parameter subsets for each component." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'chemistry': 'lithium-ion',\n", - " 'cell': 'LGM50_Chen2020',\n", - " 'negative electrode': 'graphite_Chen2020',\n", - " 'separator': 'separator_Chen2020',\n", - " 'positive electrode': 'nmc_Chen2020',\n", - " 'electrolyte': 'lipf6_Nyman2008',\n", - " 'experiment': '1C_discharge_from_full_Chen2020',\n", - " 'sei': 'example',\n", - " 'citation': 'Chen2020'}" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "chemistry" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "More details on each subset can be found [here](https://github.com/pybamm-team/PyBaMM/tree/develop/pybamm/input/parameters).\n", - "\n", - "Now we can pass `'chemistry'` into `ParameterValues` to create the dictionary of parameter values" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "parameter_values = pybamm.ParameterValues(chemistry=chemistry)" + "parameter_values = pybamm.ParameterValues(\"Chen2020\")" ] }, { @@ -119,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -129,7 +76,6 @@ " 'Ambient temperature [K]': 298.15,\n", " 'Bulk solvent concentration [mol.m-3]': 2636.0,\n", " 'Cation transference number': 0.2594,\n", - " 'Cell capacity [A.h]': 5.0,\n", " 'Cell cooling surface area [m2]': 0.00531,\n", " 'Cell volume [m3]': 2.42e-05,\n", " 'Current function [A]': 5.0,\n", @@ -137,8 +83,8 @@ " 'EC initial concentration in electrolyte [mol.m-3]': 4541.0,\n", " 'Electrode height [m]': 0.065,\n", " 'Electrode width [m]': 1.58,\n", - " 'Electrolyte conductivity [S.m-1]': ,\n", - " 'Electrolyte diffusivity [m2.s-1]': ,\n", + " 'Electrolyte conductivity [S.m-1]': ,\n", + " 'Electrolyte diffusivity [m2.s-1]': ,\n", " 'Initial concentration in electrolyte [mol.m-3]': 1000.0,\n", " 'Initial concentration in negative electrode [mol.m-3]': 29866.0,\n", " 'Initial concentration in positive electrode [mol.m-3]': 17038.0,\n", @@ -161,245 +107,7 @@ " 'Negative current collector thickness [m]': 1.2e-05,\n", " 'Negative electrode Bruggeman coefficient (electrode)': 1.5,\n", " 'Negative electrode Bruggeman coefficient (electrolyte)': 1.5,\n", - " 'Negative electrode OCP [V]': ('graphite_LGM50_ocp_Chen2020',\n", - " array([[0. , 1.81772748],\n", - " [0.03129623, 1.0828807 ],\n", - " [0.03499902, 0.99593794],\n", - " [0.0387018 , 0.90023398],\n", - " [0.04240458, 0.79649431],\n", - " [0.04610736, 0.73354429],\n", - " [0.04981015, 0.66664314],\n", - " [0.05351292, 0.64137149],\n", - " [0.05721568, 0.59813869],\n", - " [0.06091845, 0.5670836 ],\n", - 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" 'Positive electrode exchange-current density [A.m-2]': ,\n", + " 'Positive electrode exchange-current density [A.m-2]': ,\n", " 'Positive electrode porosity': 0.335,\n", + " 'Positive electrode reaction-driven LAM factor [m3.mol-1]': 0.0,\n", " 'Positive electrode specific heat capacity [J.kg-1.K-1]': 700.0,\n", " 'Positive electrode thermal conductivity [W.m-1.K-1]': 2.1,\n", " 'Positive electrode thickness [m]': 7.56e-05,\n", " 'Positive particle radius [m]': 5.22e-06,\n", " 'Ratio of inner and outer SEI exchange current densities': 1.0,\n", - " 'Reference OCP vs SHE in the negative electrode [V]': nan,\n", - " 'Reference OCP vs SHE in the positive electrode [V]': nan,\n", " 'Reference temperature [K]': 298.15,\n", " 'SEI kinetic rate constant [m.s-1]': 1e-12,\n", " 'SEI open-circuit potential [V]': 0.4,\n", " 'SEI reaction exchange current density [A.m-2]': 1.5e-07,\n", - " 'SEI resistivity [Ohm.m]': 5000000.0,\n", - " 'Separator Bruggeman coefficient (electrode)': 1.5,\n", + " 'SEI resistivity [Ohm.m]': 200000.0,\n", " 'Separator Bruggeman coefficient (electrolyte)': 1.5,\n", " 'Separator density [kg.m-3]': 397.0,\n", " 'Separator porosity': 0.47,\n", @@ -699,10 +169,10 @@ " 'Total heat transfer coefficient [W.m-2.K-1]': 10.0,\n", " 'Typical current [A]': 5.0,\n", " 'Typical electrolyte concentration [mol.m-3]': 1000.0,\n", - " 'Upper voltage cut-off [V]': 4.4}" + " 'Upper voltage cut-off [V]': 4.2}" ] }, - "execution_count": 5, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -720,7 +190,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -728,8 +198,8 @@ "output_type": "stream", "text": [ "EC initial concentration in electrolyte [mol.m-3]\t4541.0\n", - "Electrolyte conductivity [S.m-1]\t\n", - "Electrolyte diffusivity [m2.s-1]\t\n", + "Electrolyte conductivity [S.m-1]\t\n", + "Electrolyte diffusivity [m2.s-1]\t\n", "Initial concentration in electrolyte [mol.m-3]\t1000.0\n", "Negative electrode Bruggeman coefficient (electrolyte)\t1.5\n", "Positive electrode Bruggeman coefficient (electrolyte)\t1.5\n", @@ -749,6 +219,75 @@ "To run a simulation with this parameter set, we can proceed as usual but passing the parameters as a keyword argument" ] }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "59900e1b574744e4828e53c79375a21d", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "interactive(children=(FloatSlider(value=0.0, description='t', max=3554.1817016731093, step=35.541817016731095)…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model = pybamm.lithium_ion.DFN()\n", + "sim = pybamm.Simulation(model, parameter_values=parameter_values)\n", + "sim.solve([0, 3600])\n", + "sim.plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Change individual components" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can replace individual components of the chemistry (such as the electrolyte or positive electrode). Care should be taken when doing so since some parameters may only be valid for certain combinataions of components. To replace an individual component, we first load the `chemistry` from the parameter sets" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "chemistry = pybamm.parameter_sets.Chen2020" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This variable is a dictionary with the corresponding parameter subsets for each component." + ] + }, { "cell_type": "code", "execution_count": 7, @@ -756,15 +295,132 @@ "outputs": [ { "data": { - "image/png": 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\n", "text/plain": [ - "
" + "{'chemistry': 'lithium_ion',\n", + " 'cell': 'LGM50_Chen2020',\n", + " 'negative electrode': 'graphite_Chen2020',\n", + " 'separator': 'separator_Chen2020',\n", + " 'positive electrode': 'nmc_Chen2020',\n", + " 'electrolyte': 'lipf6_Nyman2008',\n", + " 'experiment': '1C_discharge_from_full_Chen2020',\n", + " 'sei': 'example',\n", + " 'citation': 'Chen2020'}" ] }, - "metadata": { - "needs_background": "light" + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "chemistry" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "More details on each subset can be found [here](https://github.com/pybamm-team/PyBaMM/tree/develop/pybamm/input/parameters)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For example, we replace the electrolyte component as follows" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "chemistry[\"electrolyte\"] = \"lipf6_Valoen2005\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we can pass the updated `'chemistry'` into `ParameterValues` to create the dictionary of parameter values" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "parameter_values = pybamm.ParameterValues(chemistry)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this case this only changes the conductivity and diffusivity functions" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EC initial concentration in electrolyte [mol.m-3]\t4541.0\n", + "Electrolyte conductivity [S.m-1]\t\n", + "Electrolyte diffusivity [m2.s-1]\t\n", + "Initial concentration in electrolyte [mol.m-3]\t1000.0\n", + "Negative electrode Bruggeman coefficient (electrolyte)\t1.5\n", + "Positive electrode Bruggeman coefficient (electrolyte)\t1.5\n", + "Separator Bruggeman coefficient (electrolyte)\t1.5\n", + "Typical electrolyte concentration [mol.m-3]\t1000.0\n" + ] + } + ], + "source": [ + "parameter_values.search(\"electrolyte\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can run the simulation again with the updated parameters" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "e17db80b47e1436a8c3b15f3fd479ad3", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "interactive(children=(FloatSlider(value=0.0, description='t', max=3560.1058147685944, step=35.60105814768595),…" + ] }, + "metadata": {}, "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -792,7 +448,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -809,7 +465,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -825,20 +481,32 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "application/vnd.jupyter.widget-view+json": { + "model_id": "87a62972f4a140b199ac8e09a3a261de", + "version_major": 2, + "version_minor": 0 + }, "text/plain": [ - "
" + "interactive(children=(FloatSlider(value=0.0, description='t', max=1724.4256164479839, step=17.24425616447984),…" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -870,7 +538,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -896,20 +564,32 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 16, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "application/vnd.jupyter.widget-view+json": { + "model_id": "ee09003547434fb683ea65eb71023f4a", + "version_major": 2, + "version_minor": 0 + }, "text/plain": [ - "
" + "interactive(children=(FloatSlider(value=0.0, description='t', max=97.69494263343306, step=0.9769494263343306),…" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -935,7 +615,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -956,20 +636,32 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 18, "metadata": {}, "outputs": [ { "data": { - "image/png": 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" + "interactive(children=(FloatSlider(value=0.0, description='t', max=35.8755487989083, step=0.35875548798908297),…" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -998,7 +690,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -1010,7 +702,7 @@ "[3] Marc Doyle, Thomas F. Fuller, and John Newman. Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell. Journal of the Electrochemical society, 140(6):1526–1533, 1993. doi:10.1149/1.2221597.\n", "[4] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", "[5] Scott G. Marquis, Valentin Sulzer, Robert Timms, Colin P. Please, and S. Jon Chapman. An asymptotic derivation of a single particle model with electrolyte. Journal of The Electrochemical Society, 166(15):A3693–A3706, 2019. doi:10.1149/2.0341915jes.\n", - "[6] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", + "[6] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", "\n" ] } @@ -1022,9 +714,9 @@ ], "metadata": { "kernelspec": { - "display_name": "PyBaMM development (env)", + "display_name": "Python 3 (ipykernel)", "language": "python", - "name": "pybamm-dev" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -1036,7 +728,20 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, diff --git a/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb b/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb index 077ca6082e..786a7cf4db 100644 --- a/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb +++ b/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb @@ -201,7 +201,7 @@ "# choose model and parameters\n", "model = pybamm.lithium_ion.DFN()\n", "chemistry = pybamm.parameter_sets.Ecker2015\n", - "parameter_values = pybamm.ParameterValues(chemistry=chemistry)\n", + "parameter_values = pybamm.ParameterValues(chemistry)\n", "\n", "# choose solver \n", "solver = pybamm.CasadiSolver(mode=\"fast\")\n", diff --git a/examples/notebooks/batch_study.ipynb b/examples/notebooks/batch_study.ipynb index 363b46c1dd..d8529662b1 100644 --- a/examples/notebooks/batch_study.ipynb +++ b/examples/notebooks/batch_study.ipynb @@ -126,7 +126,7 @@ "source": [ "# passing parameter_values as a dictionary\n", "chen2020 = pybamm.parameter_sets.Chen2020\n", - "parameter_values = {\"Chen2020\": pybamm.ParameterValues(chemistry=chen2020)}\n", + "parameter_values = {\"Chen2020\": pybamm.ParameterValues(chen2020)}\n", "\n", "# creating a BatchStudy object and solving the simulation\n", "batch_study = pybamm.BatchStudy(models=models, parameter_values=parameter_values, permutations=True)\n", @@ -180,9 +180,9 @@ "\n", "# populating a dictionary with 3 same parameter values\n", "parameter_values = {\n", - " \"Chen2020_1\": pybamm.ParameterValues(chemistry=chen2020),\n", - " \"Chen2020_2\": pybamm.ParameterValues(chemistry=chen2020),\n", - " \"Chen2020_3\": pybamm.ParameterValues(chemistry=chen2020),\n", + " \"Chen2020_1\": pybamm.ParameterValues(chen2020),\n", + " \"Chen2020_2\": pybamm.ParameterValues(chen2020),\n", + " \"Chen2020_3\": pybamm.ParameterValues(chen2020),\n", "}\n", "\n", "# different values for \"Current function [A]\"\n", @@ -469,9 +469,9 @@ "# populating a dictionary with 3 same parameter values (Mohtat2020 chemistry)\n", "mohtat2020 = pybamm.parameter_sets.Mohtat2020\n", "parameter_values = {\n", - " \"Mohtat2020_1\": pybamm.ParameterValues(chemistry=mohtat2020),\n", - " \"Mohtat2020_2\": pybamm.ParameterValues(chemistry=mohtat2020),\n", - " \"Mohtat2020_3\": pybamm.ParameterValues(chemistry=mohtat2020),\n", + " \"Mohtat2020_1\": pybamm.ParameterValues(mohtat2020),\n", + " \"Mohtat2020_2\": pybamm.ParameterValues(mohtat2020),\n", + " \"Mohtat2020_3\": pybamm.ParameterValues(mohtat2020),\n", "}\n", "\n", "# different values for the parameter \"Inner SEI open-circuit potential [V]\"\n", diff --git a/examples/notebooks/models/DFN-with-particle-size-distributions.ipynb b/examples/notebooks/models/DFN-with-particle-size-distributions.ipynb index b0ed3811c6..a16cfa31f9 100644 --- a/examples/notebooks/models/DFN-with-particle-size-distributions.ipynb +++ b/examples/notebooks/models/DFN-with-particle-size-distributions.ipynb @@ -92,7 +92,7 @@ "outputs": [], "source": [ "# Base parameter set (no distribution parameters by default)\n", - "params = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019)\n", + "params = pybamm.ParameterValues("Marquis2019")\n", "\n", "# Add distribution parameters to the set, with default values (lognormals)\n", "params = pybamm.get_size_distribution_parameters(params)" @@ -379,7 +379,7 @@ "]\n", "\n", "# parameters\n", - "params = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019)\n", + "params = pybamm.ParameterValues("Marquis2019")\n", "params = pybamm.get_size_distribution_parameters(params) \n", "\n", "# define current function\n", diff --git a/examples/notebooks/models/MPM.ipynb b/examples/notebooks/models/MPM.ipynb index 653c1078ff..7822d7f917 100644 --- a/examples/notebooks/models/MPM.ipynb +++ b/examples/notebooks/models/MPM.ipynb @@ -449,7 +449,7 @@ "outputs": [], "source": [ "# Parameter set (no distribution parameters by default)\n", - "params = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019)\n", + "params = pybamm.ParameterValues("Marquis2019")\n", "\n", "# Extract the radii values. We will choose these to be the means of our area-weighted distributions\n", "R_a_n_dim = params[\"Negative particle radius [m]\"]\n", diff --git a/examples/notebooks/models/Validating_mechanical_models_Enertech_DFN.ipynb b/examples/notebooks/models/Validating_mechanical_models_Enertech_DFN.ipynb index 472f4aef2d..8486a4637f 100644 --- a/examples/notebooks/models/Validating_mechanical_models_Enertech_DFN.ipynb +++ b/examples/notebooks/models/Validating_mechanical_models_Enertech_DFN.ipynb @@ -78,7 +78,7 @@ "source": [ "# update parameters, making C-rate and input\n", "chemistry = pybamm.parameter_sets.Ai2020\n", - "param = pybamm.ParameterValues(chemistry=chemistry)\n", + "param = pybamm.ParameterValues(chemistry)\n", "capacity = param[\"Nominal cell capacity [A.h]\"]\n", "param.update({\n", " \"Current function [A]\": capacity * pybamm.InputParameter(\"C-rate\")\n", diff --git a/examples/notebooks/models/compare-ecker-data.ipynb b/examples/notebooks/models/compare-ecker-data.ipynb index 62b59e9a54..17ddb4cbeb 100644 --- a/examples/notebooks/models/compare-ecker-data.ipynb +++ b/examples/notebooks/models/compare-ecker-data.ipynb @@ -81,7 +81,7 @@ "\n", "# pick parameters, keeping C-rate as an input to be changed for each solve\n", "chemistry = pybamm.parameter_sets.Ecker2015\n", - "parameter_values = pybamm.ParameterValues(chemistry=chemistry)\n", + "parameter_values = pybamm.ParameterValues(chemistry)\n", "parameter_values.update({\"Current function [A]\": \"[input]\"})" ] }, diff --git a/examples/notebooks/models/electrode-state-of-health.ipynb b/examples/notebooks/models/electrode-state-of-health.ipynb index 37f01912ea..ce489139be 100644 --- a/examples/notebooks/models/electrode-state-of-health.ipynb +++ b/examples/notebooks/models/electrode-state-of-health.ipynb @@ -81,7 +81,7 @@ " \"Discharge at 1C until 2.8V\",\n", " \"Hold at 2.8V until C/50\",\n", "])\n", - "parameter_values = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Mohtat2020)\n", + "parameter_values = pybamm.ParameterValues("Mohtat2020")\n", "\n", "sim = pybamm.Simulation(spm, experiment=experiment, parameter_values=parameter_values)\n", "spm_sol = sim.solve()\n", diff --git a/examples/notebooks/models/lithium-plating.ipynb b/examples/notebooks/models/lithium-plating.ipynb index e03ffe07e6..4f260176b8 100644 --- a/examples/notebooks/models/lithium-plating.ipynb +++ b/examples/notebooks/models/lithium-plating.ipynb @@ -52,7 +52,7 @@ "\n", "# pick parameters\n", "chemistry = pybamm.parameter_sets.Chen2020_plating\n", - "parameter_values = pybamm.ParameterValues(chemistry=chemistry)\n", + "parameter_values = pybamm.ParameterValues(chemistry)\n", "#parameter_values.update({\"Reference temperature [K]\": 268.15})\n", "parameter_values.update({\"Ambient temperature [K]\": 268.15})\n", "#parameter_values.update({\"Initial temperature [K]\": 268.15})\n", diff --git a/examples/notebooks/models/simulating-ORegan-2021-parameter-set.ipynb b/examples/notebooks/models/simulating-ORegan-2021-parameter-set.ipynb index 977caf7c8f..25558bf97c 100644 --- a/examples/notebooks/models/simulating-ORegan-2021-parameter-set.ipynb +++ b/examples/notebooks/models/simulating-ORegan-2021-parameter-set.ipynb @@ -49,7 +49,7 @@ "model = pybamm.lithium_ion.DFN(options=options)\n", "\n", "# O'Regan 2021 parameter set\n", - "param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.ORegan2021)\n", + "param = pybamm.ParameterValues(\"ORegan2021\")\n", "\n", "# Choose CasADI fast (we do a short discharge so there are no events, if events are needed choose \"fast with events\")\n", "solver = pybamm.CasadiSolver(mode=\"fast\")" diff --git a/examples/notebooks/models/submodel_cracking_DFN_or_SPM.ipynb b/examples/notebooks/models/submodel_cracking_DFN_or_SPM.ipynb index d79736f897..ea77f1d9ca 100644 --- a/examples/notebooks/models/submodel_cracking_DFN_or_SPM.ipynb +++ b/examples/notebooks/models/submodel_cracking_DFN_or_SPM.ipynb @@ -67,7 +67,7 @@ "outputs": [], "source": [ "chemistry = pybamm.parameter_sets.Ai2020\n", - "param = pybamm.ParameterValues(chemistry=chemistry)\n", + "param = pybamm.ParameterValues(chemistry)\n", "## It can update the speed of crack propagation using the commands below:\n", "# param.update({\"Negative electrode Cracking rate\":3.9e-20*10})\n" ] diff --git a/examples/notebooks/models/submodel_loss_of_active_materials.ipynb b/examples/notebooks/models/submodel_loss_of_active_materials.ipynb index 26f781088a..b953b6692f 100644 --- a/examples/notebooks/models/submodel_loss_of_active_materials.ipynb +++ b/examples/notebooks/models/submodel_loss_of_active_materials.ipynb @@ -41,7 +41,7 @@ " }\n", ")\n", "chemistry = pybamm.parameter_sets.Ai2020\n", - "param = pybamm.ParameterValues(chemistry=chemistry)\n", + "param = pybamm.ParameterValues(chemistry)\n", "param.update({\"Negative electrode LAM constant proportional term [s-1]\": 1e-4/3600})\n", "param.update({\"Positive electrode LAM constant proportional term [s-1]\": 1e-4/3600})\n", "total_cycles = 2\n", diff --git a/examples/notebooks/models/thermal-models.ipynb b/examples/notebooks/models/thermal-models.ipynb index 53fbffe031..d9ffb759bb 100644 --- a/examples/notebooks/models/thermal-models.ipynb +++ b/examples/notebooks/models/thermal-models.ipynb @@ -260,7 +260,7 @@ "metadata": {}, "outputs": [], "source": [ - "parameter_values = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019)" + "parameter_values = pybamm.ParameterValues("Marquis2019")" ] }, { diff --git a/examples/notebooks/models/using-model-options_thermal-example.ipynb b/examples/notebooks/models/using-model-options_thermal-example.ipynb index 5431c386bc..c7488a93ac 100644 --- a/examples/notebooks/models/using-model-options_thermal-example.ipynb +++ b/examples/notebooks/models/using-model-options_thermal-example.ipynb @@ -83,7 +83,7 @@ "metadata": {}, "outputs": [], "source": [ - "param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019)\n", + "param = pybamm.ParameterValues("Marquis2019")\n", "param.update(\n", " {\n", " \"Total heat transfer coefficient [W.m-2.K-1]\": 1.0,\n", diff --git a/examples/notebooks/parameterization/parameter-values.ipynb b/examples/notebooks/parameterization/parameter-values.ipynb index ddc47738f3..992e981d70 100644 --- a/examples/notebooks/parameterization/parameter-values.ipynb +++ b/examples/notebooks/parameterization/parameter-values.ipynb @@ -129,7 +129,7 @@ ], "source": [ "print(\"Marquis2019 chemistry set is {}\".format(pybamm.parameter_sets.Marquis2019))\n", - "chem_parameter_values = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019)\n", + "chem_parameter_values = pybamm.ParameterValues("Marquis2019")\n", "print(\"Negative current collector thickness is {} m\".format(\n", " chem_parameter_values[\"Negative current collector thickness [m]\"])\n", ")" diff --git a/examples/notebooks/parameterization/parameterization.ipynb b/examples/notebooks/parameterization/parameterization.ipynb index 7785150c72..3aa9beb4db 100644 --- a/examples/notebooks/parameterization/parameterization.ipynb +++ b/examples/notebooks/parameterization/parameterization.ipynb @@ -2186,7 +2186,7 @@ ], "source": [ "chemistry = pybamm.parameter_sets.Chen2020\n", - "param_same = pybamm.ParameterValues(chemistry=chemistry)\n", + "param_same = pybamm.ParameterValues(chemistry)\n", "{k: v for k,v in param_same.items() if k in spm._parameter_info}" ] }, diff --git a/examples/notebooks/simulating-long-experiments.ipynb b/examples/notebooks/simulating-long-experiments.ipynb index c6a31ceda7..d8b18d5741 100644 --- a/examples/notebooks/simulating-long-experiments.ipynb +++ b/examples/notebooks/simulating-long-experiments.ipynb @@ -52,7 +52,7 @@ "metadata": {}, "outputs": [], "source": [ - "parameter_values = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Mohtat2020)\n", + "parameter_values = pybamm.ParameterValues("Mohtat2020")\n", "parameter_values.update({\"SEI kinetic rate constant [m.s-1]\": 1e-14})\n", "spm = pybamm.lithium_ion.SPM({\"SEI\": \"ec reaction limited\"})" ] diff --git a/examples/scripts/DFN_size_distributions.py b/examples/scripts/DFN_size_distributions.py index 3bba8e0219..99c67f47eb 100644 --- a/examples/scripts/DFN_size_distributions.py +++ b/examples/scripts/DFN_size_distributions.py @@ -10,17 +10,17 @@ models = [ pybamm.lithium_ion.DFN(options={"particle size": "distribution"}, name="MP-DFN"), pybamm.lithium_ion.MPM(name="MPM"), - pybamm.lithium_ion.DFN(name="DFN") + pybamm.lithium_ion.DFN(name="DFN"), ] # parameter set -params = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) +params = pybamm.ParameterValues("Marquis2019") # add distribution params (lognormals) with custom standard deviations params = pybamm.get_size_distribution_parameters(params, sd_n=0.2, sd_p=0.4) # discharge and relaxation: define current function -t_cutoff = 3450 # [s] +t_cutoff = 3450 # [s] t_rest = 3600 # [s] I_typ = params["Typical current [A]"] # current for 1C @@ -36,11 +36,7 @@ def current(t): solver = pybamm.CasadiSolver(mode="fast") sims = [] for model in models: - sim = pybamm.Simulation( - model, - parameter_values=params, - solver=solver - ) + sim = pybamm.Simulation(model, parameter_values=params, solver=solver) sims.append(sim) for sim in sims: diff --git a/examples/scripts/compare_lithium_ion_half_cell.py b/examples/scripts/compare_lithium_ion_half_cell.py index b6dcac3f3e..810091a7d2 100644 --- a/examples/scripts/compare_lithium_ion_half_cell.py +++ b/examples/scripts/compare_lithium_ion_half_cell.py @@ -19,7 +19,7 @@ ] chemistry = pybamm.parameter_sets.Xu2019 -param = pybamm.ParameterValues(chemistry=chemistry) +param = pybamm.ParameterValues(chemistry) # create and run simulations sims = [] diff --git a/examples/scripts/compare_particle_models.py b/examples/scripts/compare_particle_models.py index ac66580f6e..d780452004 100644 --- a/examples/scripts/compare_particle_models.py +++ b/examples/scripts/compare_particle_models.py @@ -20,7 +20,7 @@ ] # pick parameter values -parameter_values = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Ecker2015) +parameter_values = pybamm.ParameterValues("Ecker2015") # create and solve simulations sims = [] diff --git a/examples/scripts/cycling_ageing.py b/examples/scripts/cycling_ageing.py index 541ff49946..956a5c443e 100644 --- a/examples/scripts/cycling_ageing.py +++ b/examples/scripts/cycling_ageing.py @@ -11,7 +11,7 @@ } ) -param = pb.ParameterValues(chemistry=pb.parameter_sets.Mohtat2020) +param = pb.ParameterValues(pb.parameter_sets.Mohtat2020) experiment = pb.Experiment( [ diff --git a/examples/scripts/nca_parameters.py b/examples/scripts/nca_parameters.py index 39cc2019c4..a1e32f9402 100644 --- a/examples/scripts/nca_parameters.py +++ b/examples/scripts/nca_parameters.py @@ -4,7 +4,7 @@ model = pb.lithium_ion.DFN() chemistry = pb.parameter_sets.NCA_Kim2011 -parameter_values = pb.ParameterValues(chemistry=chemistry) +parameter_values = pb.ParameterValues(chemistry) sim = pb.Simulation(model, parameter_values=parameter_values, C_rate=1) sim.solve([0, 3600]) diff --git a/examples/scripts/print_parameters.py b/examples/scripts/print_parameters.py index 95013ee985..3e42a0944c 100644 --- a/examples/scripts/print_parameters.py +++ b/examples/scripts/print_parameters.py @@ -4,6 +4,6 @@ import pybamm parameters = pybamm.LithiumIonParameters() -parameter_values = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) +parameter_values = pybamm.ParameterValues("Marquis2019") output_file = "lithium_ion_parameters.txt" parameter_values.print_parameters(parameters, output_file) diff --git a/pybamm/models/full_battery_models/lead_acid/base_lead_acid_model.py b/pybamm/models/full_battery_models/lead_acid/base_lead_acid_model.py index cb693a7d67..637aecc656 100644 --- a/pybamm/models/full_battery_models/lead_acid/base_lead_acid_model.py +++ b/pybamm/models/full_battery_models/lead_acid/base_lead_acid_model.py @@ -39,7 +39,7 @@ def __init__(self, options=None, name="Unnamed lead-acid model", build=False): @property def default_parameter_values(self): - return pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Sulzer2019) + return pybamm.ParameterValues("Sulzer2019") @property def default_geometry(self): diff --git a/pybamm/models/full_battery_models/lithium_ion/Yang2017.py b/pybamm/models/full_battery_models/lithium_ion/Yang2017.py index 6479c627d8..3c7186e22f 100644 --- a/pybamm/models/full_battery_models/lithium_ion/Yang2017.py +++ b/pybamm/models/full_battery_models/lithium_ion/Yang2017.py @@ -16,4 +16,4 @@ def __init__(self, options=None, name="Yang2017", build=True): @property def default_parameter_values(self): - return pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020_plating) + return pybamm.ParameterValues("Chen2020_plating") diff --git a/pybamm/models/full_battery_models/lithium_ion/base_lithium_ion_model.py b/pybamm/models/full_battery_models/lithium_ion/base_lithium_ion_model.py index 2f1c505c0d..0c8d3af73d 100644 --- a/pybamm/models/full_battery_models/lithium_ion/base_lithium_ion_model.py +++ b/pybamm/models/full_battery_models/lithium_ion/base_lithium_ion_model.py @@ -47,9 +47,9 @@ def __init__(self, options=None, name="Unnamed lithium-ion model", build=False): @property def default_parameter_values(self): if self.half_cell: - return pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Xu2019) + return pybamm.ParameterValues("Xu2019") else: - return pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + return pybamm.ParameterValues("Marquis2019") @property def default_quick_plot_variables(self): diff --git a/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py b/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py index 5dcdf7760e..c270f2a12a 100644 --- a/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py +++ b/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py @@ -212,7 +212,7 @@ def V_cc_dim(t, z, y=None): @property def default_parameter_values(self): - return pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + return pybamm.ParameterValues("Marquis2019") @property def default_geometry(self): @@ -468,7 +468,7 @@ def V_cc_dim(t, y, z): @property def default_parameter_values(self): - return pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + return pybamm.ParameterValues("Marquis2019") @property def default_geometry(self): diff --git a/pybamm/parameters/parameter_values.py b/pybamm/parameters/parameter_values.py index 24d74e7bdb..76476967a4 100644 --- a/pybamm/parameters/parameter_values.py +++ b/pybamm/parameters/parameter_values.py @@ -48,10 +48,10 @@ class ParameterValues: 1 >>> file = "input/parameters/lithium_ion/cells/kokam_Marquis2019/parameters.csv" >>> values_path = pybamm.get_parameters_filepath(file) - >>> param = pybamm.ParameterValues(values=values_path) + >>> param = pybamm.ParameterValues(values_path) >>> param["Negative current collector thickness [m]"] 2.5e-05 - >>> param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + >>> param = pybamm.ParameterValues("Marquis2019") >>> param["Reference temperature [K]"] 298.15 @@ -64,25 +64,37 @@ def __init__(self, values=None, chemistry=None): raise ValueError( "Only one of values and chemistry can be provided. To change parameters" " slightly from a chemistry, first load parameters with the chemistry" - " (param = pybamm.ParameterValues(chemistry=...)) and then update with" + " (param = pybamm.ParameterValues(...)) and then update with" " param.update({dict of values})." ) if values is None and chemistry is None: raise ValueError("values and chemistry cannot both be None") # First load chemistry if chemistry is not None: + warnings.warn( + "The 'chemistry' keyword argument has been deprecated and will be " + "removed in a future release. Call `ParameterValues` with a " + "parameter set dictionary, or the name of a parameter set (string), " + "as the single argument, e.g. `ParameterValues('Chen2020')`.", + DeprecationWarning, + ) self.update_from_chemistry(chemistry) # Then update with values dictionary or file if values is not None: - # If base_parameters is a filename, load from that filename - if isinstance(values, str): - file_path = self.find_parameter(values) - path = os.path.split(file_path)[0] - values = self.read_parameters_csv(file_path) + if (isinstance(values, str) and hasattr(pybamm.parameter_sets, values)) or ( + isinstance(values, dict) and "chemistry" in values + ): + self.update_from_chemistry(values) else: - path = "" - # Don't check parameter already exists when first creating it - self.update(values, check_already_exists=False, path=path) + # If base_parameters is a filename, load from that filename + if isinstance(values, str): + file_path = self.find_parameter(values) + path = os.path.split(file_path)[0] + values = self.read_parameters_csv(file_path) + else: + path = "" + # Don't check parameter already exists when first creating it + self.update(values, check_already_exists=False, path=path) # Initialise empty _processed_symbols dict (for caching) self._processed_symbols = {} @@ -123,7 +135,7 @@ def items(self): def copy(self): """Returns a copy of the parameter values. Makes sure to copy the internal dictionary.""" - return ParameterValues(values=self._dict_items.copy()) + return ParameterValues(self._dict_items.copy()) def search(self, key, print_values=True): """ @@ -137,6 +149,9 @@ def update_from_chemistry(self, chemistry): """ Load standard set of components from a 'chemistry' dictionary """ + if isinstance(chemistry, str): + chemistry = getattr(pybamm.parameter_sets, chemistry) + base_chemistry = chemistry["chemistry"] # Load each component name @@ -159,40 +174,16 @@ def update_from_chemistry(self, chemistry): component_groups += ["lithium plating"] if "anode" in chemistry.keys(): - if "negative electrode" in chemistry.keys(): - raise KeyError( - "both 'anode' and 'negative electrode' keys provided in the " - "chemistry. The 'anode' notation will be deprecated in the next " - "release so 'negative electrode' should be used instead." - ) - else: - chemistry["negative electrode"] = chemistry["anode"] - warnings.warn( - "the 'anode' component notation will be deprecated in the next " - "release, as it has now been renamed to 'negative electrode'. " - "Simulation will continue passing the 'anode' component as " - "'negative electrode' (it might overwrite any existing definition " - "of the component).", - DeprecationWarning, - ) + raise KeyError( + "The 'anode' notation has been deprecated, " + "'negative electrode' should be used instead." + ) if "cathode" in chemistry.keys(): - if "positive electrode" in chemistry.keys(): - raise KeyError( - "both 'cathode' and 'positive electrode' keys provided in the " - "chemistry. The 'cathode' notation will be deprecated in the next " - "release so 'positive electrode' should be used instead." - ) - else: - chemistry["positive electrode"] = chemistry["cathode"] - warnings.warn( - "the 'cathode' component notation will be deprecated in the next " - "release, as it has now been renamed to 'positive electrode'. " - "Simulation will continue passing the 'cathode' component as " - "'positive electrode' (it might overwrite any existing definition " - "of the component).", - DeprecationWarning, - ) + raise KeyError( + "The 'cathode' notation has been deprecated, " + "'positive electrode' should be used instead." + ) for component_group in component_groups: # Make sure component is provided @@ -349,24 +340,10 @@ def check_parameter_values(self, values): "capacity [A.h]', and used to calculate current from C-rate." ) if "Cell capacity [A.h]" in values: - if "Nominal cell capacity [A.h]" in values: - raise ValueError( - "both 'Cell capacity [A.h]' and 'Nominal cell capacity [A.h]' " - "provided in values. The 'Cell capacity [A.h]' notation will be " - "deprecated in the next release so 'Nominal cell capacity [A.h]' " - "should be used instead." - ) - else: - values["Nominal cell capacity [A.h]"] = values["Cell capacity [A.h]"] - warnings.warn( - "the 'Cell capacity [A.h]' notation will be " - "deprecated in the next release, as it has now been renamed " - "to 'Nominal cell capacity [A.h]'. Simulation will continue " - "passing the 'Cell capacity [A.h]' as 'Nominal cell " - "capacity [A.h]' (it might overwrite any existing definition " - "of the component)", - DeprecationWarning, - ) + raise ValueError( + "The 'Cell capacity [A.h]' parameter has been deprecated, " + "'Nominal cell capacity [A.h]' should be used instead." + ) for param in values: if "surface area density" in param: raise ValueError( diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py index c251b45508..71a5c6bd75 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py @@ -15,12 +15,12 @@ def run_basic_processing_test(self, options, **kwargs): def test_basic_processing(self): options = {} # use Ecker parameters for nonlinear diffusion - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Ecker2015) + param = pybamm.ParameterValues("Ecker2015") self.run_basic_processing_test(options, parameter_values=param) def test_sensitivities(self): model = self.model() - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Ecker2015) + param = pybamm.ParameterValues("Ecker2015") modeltest = tests.StandardModelTest(model, parameter_values=param) modeltest.test_sensitivities( "Current function [A]", @@ -132,7 +132,7 @@ def test_irreversible_plating_with_porosity(self): "lithium plating": "irreversible", "lithium plating porosity change": "true", } - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020_plating) + param = pybamm.ParameterValues("Chen2020_plating") self.run_basic_processing_test(options, parameter_values=param) def test_reaction_limited(self): @@ -157,42 +157,35 @@ def test_ec_reaction_limited(self): def test_loss_active_material_stress_negative(self): options = {"loss of active material": ("none", "stress-driven")} - chemistry = pybamm.parameter_sets.Ai2020 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues("Ai2020") self.run_basic_processing_test(options, parameter_values=parameter_values) def test_loss_active_material_stress_positive(self): options = {"loss of active material": ("stress-driven", "none")} - chemistry = pybamm.parameter_sets.Ai2020 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues("Ai2020") self.run_basic_processing_test(options, parameter_values=parameter_values) def test_loss_active_material_stress_both(self): options = {"loss of active material": "stress-driven"} - chemistry = pybamm.parameter_sets.Ai2020 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues("Ai2020") self.run_basic_processing_test(options, parameter_values=parameter_values) def test_negative_cracking(self): options = {"particle mechanics": ("swelling and cracking", "none")} - chemistry = pybamm.parameter_sets.Ai2020 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues("Ai2020") self.run_basic_processing_test(options, parameter_values=parameter_values) def test_positive_cracking(self): options = {"particle mechanics": ("none", "swelling and cracking")} - chemistry = pybamm.parameter_sets.Ai2020 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues("Ai2020") self.run_basic_processing_test(options, parameter_values=parameter_values) def test_both_cracking(self): options = {"particle mechanics": "swelling and cracking"} - chemistry = pybamm.parameter_sets.Ai2020 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues("Ai2020") self.run_basic_processing_test(options, parameter_values=parameter_values) def test_both_swelling_only(self): options = {"particle mechanics": "swelling only"} - chemistry = pybamm.parameter_sets.Ai2020 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues("Ai2020") self.run_basic_processing_test(options, parameter_values=parameter_values) diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_basic_half_cell_models.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_basic_half_cell_models.py index 9c766ae134..9d41932edb 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_basic_half_cell_models.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_basic_half_cell_models.py @@ -17,7 +17,7 @@ def test_runs_Xu2019(self): # load parameter values chemistry = pybamm.parameter_sets.Xu2019 - param = pybamm.ParameterValues(chemistry=chemistry) + param = pybamm.ParameterValues(chemistry) param["Current function [A]"] = 2.5e-3 @@ -48,7 +48,7 @@ def test_runs_Chen2020(self): # load parameter values chemistry = pybamm.parameter_sets.Chen2020_plating - param = pybamm.ParameterValues(chemistry=chemistry) + param = pybamm.ParameterValues(chemistry) param["Current function [A]"] = 2.5 diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_dfn.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_dfn.py index 6112671f06..affbfd6073 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_dfn.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_dfn.py @@ -37,7 +37,7 @@ def positive_radius(x): class TestDFNWithSizeDistribution(unittest.TestCase): def setUp(self): - params = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + params = pybamm.ParameterValues("Marquis2019") self.params = pybamm.get_size_distribution_parameters(params) var = pybamm.standard_spatial_vars diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_mpm.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_mpm.py index 98d596dd00..0756253b69 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_mpm.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_mpm.py @@ -12,7 +12,7 @@ def test_basic_processing(self): options = {"thermal": "isothermal"} model = pybamm.lithium_ion.MPM(options) # use Ecker parameters for nonlinear diffusion - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Ecker2015) + param = pybamm.ParameterValues("Ecker2015") param = pybamm.get_size_distribution_parameters(param) modeltest = tests.StandardModelTest(model) modeltest.test_all() diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_thermal_models.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_thermal_models.py index 144e36e9dd..e80b9ecb57 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_thermal_models.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_thermal_models.py @@ -45,7 +45,7 @@ def test_consistent_cooling(self): var.z: 5, } chemistry = pybamm.parameter_sets.NCA_Kim2011 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues(chemistry) # high thermal and electrical conductivity in current collectors parameter_values.update( diff --git a/tests/unit/test_citations.py b/tests/unit/test_citations.py index 5e3a3ed7bf..8f31dcad60 100644 --- a/tests/unit/test_citations.py +++ b/tests/unit/test_citations.py @@ -196,23 +196,23 @@ def test_parameter_citations(self): citations = pybamm.citations citations._reset() - pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020) + pybamm.ParameterValues("Chen2020") self.assertIn("Chen2020", citations._papers_to_cite) citations._reset() - pybamm.ParameterValues(chemistry=pybamm.parameter_sets.NCA_Kim2011) + pybamm.ParameterValues("NCA_Kim2011") self.assertIn("Kim2011", citations._papers_to_cite) citations._reset() - pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + pybamm.ParameterValues("Marquis2019") self.assertIn("Marquis2019", citations._papers_to_cite) citations._reset() - pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Sulzer2019) + pybamm.ParameterValues("Sulzer2019") self.assertIn("Sulzer2019physical", citations._papers_to_cite) citations._reset() - pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Ecker2015) + pybamm.ParameterValues("Ecker2015") self.assertIn("Ecker2015i", citations._papers_to_cite) self.assertIn("Ecker2015ii", citations._papers_to_cite) self.assertIn("Zhao2018", citations._papers_to_cite) @@ -220,7 +220,7 @@ def test_parameter_citations(self): self.assertIn("Richardson2020", citations._papers_to_cite) citations._reset() - pybamm.ParameterValues(chemistry=pybamm.parameter_sets.ORegan2021) + pybamm.ParameterValues("ORegan2021") self.assertIn("ORegan2021", citations._papers_to_cite) def test_solver_citations(self): diff --git a/tests/unit/test_experiments/test_simulation_with_experiment.py b/tests/unit/test_experiments/test_simulation_with_experiment.py index 5b47b672b8..0575d743a4 100644 --- a/tests/unit/test_experiments/test_simulation_with_experiment.py +++ b/tests/unit/test_experiments/test_simulation_with_experiment.py @@ -168,13 +168,13 @@ def test_run_experiment_drive_cycle(self): "Run drive_cycle (W)", ) ], - drive_cycles={"drive_cycle": drive_cycle} + drive_cycles={"drive_cycle": drive_cycle}, ) model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, experiment=experiment) - self.assertIn(('drive_cycle', 'A'), sim.op_conds_to_model_and_param) - self.assertIn(('drive_cycle', 'V'), sim.op_conds_to_model_and_param) - self.assertIn(('drive_cycle', 'W'), sim.op_conds_to_model_and_param) + self.assertIn(("drive_cycle", "A"), sim.op_conds_to_model_and_param) + self.assertIn(("drive_cycle", "V"), sim.op_conds_to_model_and_param) + self.assertIn(("drive_cycle", "W"), sim.op_conds_to_model_and_param) def test_run_experiment_old_setup_type(self): experiment = pybamm.Experiment( @@ -218,7 +218,7 @@ def test_run_experiment_termination(self): termination="99% capacity", ) model = pybamm.lithium_ion.SPM({"SEI": "ec reaction limited"}) - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020) + param = pybamm.ParameterValues("Chen2020") param["SEI kinetic rate constant [m.s-1]"] = 1e-14 sim = pybamm.Simulation(model, experiment=experiment, parameter_values=param) sol = sim.solve(solver=pybamm.CasadiSolver()) @@ -240,7 +240,7 @@ def test_run_experiment_termination(self): termination="5.04Ah capacity", ) model = pybamm.lithium_ion.SPM({"SEI": "ec reaction limited"}) - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020) + param = pybamm.ParameterValues("Chen2020") param["SEI kinetic rate constant [m.s-1]"] = 1e-14 sim = pybamm.Simulation(model, experiment=experiment, parameter_values=param) sol = sim.solve(solver=pybamm.CasadiSolver()) @@ -298,12 +298,12 @@ def test_cycle_summary_variables(self): model = pybamm.lithium_ion.SPM() # Chen 2020 plating: pos = function, neg = data - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020_plating) + param = pybamm.ParameterValues("Chen2020_plating") sim = pybamm.Simulation(model, experiment=experiment, parameter_values=param) sim.solve(solver=pybamm.CasadiSolver("fast with events"), save_at_cycles=2) # Chen 2020: pos = function, neg = function - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020) + param = pybamm.ParameterValues("Chen2020") sim = pybamm.Simulation(model, experiment=experiment, parameter_values=param) sim.solve(solver=pybamm.CasadiSolver("fast with events"), save_at_cycles=2) @@ -354,7 +354,7 @@ def test_inputs(self): model = pybamm.lithium_ion.SPM() # Change a parameter to an input - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019) + param = pybamm.ParameterValues("Marquis2019") param["Negative electrode diffusivity [m2.s-1]"] = ( pybamm.InputParameter("Dsn") * 3.9e-14 ) diff --git a/tests/unit/test_models/test_full_battery_models/test_lithium_ion/test_Yang2017.py b/tests/unit/test_models/test_full_battery_models/test_lithium_ion/test_Yang2017.py index db23b3c0a1..b12294f205 100644 --- a/tests/unit/test_models/test_full_battery_models/test_lithium_ion/test_Yang2017.py +++ b/tests/unit/test_models/test_full_battery_models/test_lithium_ion/test_Yang2017.py @@ -13,8 +13,7 @@ def test_well_posed(self): def test_default_parameter_values(self): model = pybamm.lithium_ion.Yang2017() - chemistry = pybamm.parameter_sets.Chen2020_plating - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues("Chen2020_plating") for key, value in parameter_values.items(): if not isinstance(value, tuple): np.testing.assert_array_equal( diff --git a/tests/unit/test_models/test_full_battery_models/test_lithium_ion/test_basic_models.py b/tests/unit/test_models/test_full_battery_models/test_lithium_ion/test_basic_models.py index ae1c3e33c5..d8f8a97733 100644 --- a/tests/unit/test_models/test_full_battery_models/test_lithium_ion/test_basic_models.py +++ b/tests/unit/test_models/test_full_battery_models/test_lithium_ion/test_basic_models.py @@ -51,8 +51,7 @@ def test_basic_dfn_half_cell_simulation(self): model = pybamm.lithium_ion.BasicDFNHalfCell( options={"working electrode": "positive"} ) - chemistry = pybamm.parameter_sets.Chen2020_plating - param = pybamm.ParameterValues(chemistry=chemistry) + param = pybamm.ParameterValues("Chen2020_plating") param["Current function [A]"] = 2.5 sim = pybamm.Simulation(model=model, parameter_values=param) sim.solve([0, 100]) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_LCO_Ai2020.py b/tests/unit/test_parameters/test_parameter_sets/test_LCO_Ai2020.py index ec884d8036..65b9c1b597 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_LCO_Ai2020.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_LCO_Ai2020.py @@ -41,7 +41,7 @@ def test_load_params(self): def test_functions(self): root = pybamm.root_dir() - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Ai2020) + param = pybamm.ParameterValues("Ai2020") sto = pybamm.Scalar(0.5) T = pybamm.Scalar(298.15) @@ -86,8 +86,7 @@ def test_functions(self): self.assertAlmostEqual(param.evaluate(fun(*value[0])), value[1], places=4) def test_standard_lithium_parameters(self): - chemistry = pybamm.parameter_sets.Ai2020 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues("Ai2020") options = {"particle mechanics": "swelling and cracking"} model = pybamm.lithium_ion.DFN(options) sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_LCO_Ramadass2004.py b/tests/unit/test_parameters/test_parameter_sets/test_LCO_Ramadass2004.py index a3175b9f05..ee4e5be18e 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_LCO_Ramadass2004.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_LCO_Ramadass2004.py @@ -38,13 +38,12 @@ def test_load_params(self): ) ) self.assertAlmostEqual( - cell["Negative current collector thickness [m]"], - 1.7E-05 + cell["Negative current collector thickness [m]"], 1.7e-05 ) def test_functions(self): root = pybamm.root_dir() - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Ramadass2004) + param = pybamm.ParameterValues("Ramadass2004") sto = pybamm.Scalar(0.5) T = pybamm.Scalar(298.15) @@ -91,8 +90,7 @@ def test_functions(self): self.assertAlmostEqual(param.evaluate(fun(*value[0])), value[1], places=4) def test_standard_lithium_parameters(self): - chemistry = pybamm.parameter_sets.Ramadass2004 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues("Ramadass2004") model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) sim.set_parameters() diff --git a/tests/unit/test_parameters/test_parameter_sets/test_LFP_Prada2013.py b/tests/unit/test_parameters/test_parameter_sets/test_LFP_Prada2013.py index a59c23fb11..b0e06b069a 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_LFP_Prada2013.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_LFP_Prada2013.py @@ -27,7 +27,7 @@ def test_load_params(self): def test_standard_lithium_parameters(self): chemistry = pybamm.parameter_sets.Prada2013 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues(chemistry) model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_LGM50_Chen2020.py b/tests/unit/test_parameters/test_parameter_sets/test_LGM50_Chen2020.py index 35fcbcca19..76d49b1d2a 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_LGM50_Chen2020.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_LGM50_Chen2020.py @@ -41,7 +41,7 @@ def test_load_params(self): def test_standard_lithium_parameters(self): chemistry = pybamm.parameter_sets.Chen2020 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues(chemistry) model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_LGM50_ORegan2021.py b/tests/unit/test_parameters/test_parameter_sets/test_LGM50_ORegan2021.py index aab6106c7a..5b965cf62e 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_LGM50_ORegan2021.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_LGM50_ORegan2021.py @@ -52,7 +52,7 @@ def test_load_params(self): def test_functions(self): root = pybamm.root_dir() - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.ORegan2021) + param = pybamm.ParameterValues("ORegan2021") T = pybamm.Scalar(298.15) # Positive electrode @@ -128,7 +128,7 @@ def test_functions(self): def test_standard_lithium_parameters(self): chemistry = pybamm.parameter_sets.ORegan2021 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues(chemistry) model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_Landesfeind2019.py b/tests/unit/test_parameters/test_parameter_sets/test_Landesfeind2019.py index c80aed3edc..6c8f276d39 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_Landesfeind2019.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_Landesfeind2019.py @@ -82,7 +82,7 @@ def test_standard_lithium_parameters(self): for solvent in ["EC_DMC_1_1", "EC_EMC_3_7", "EMC_FEC_19_1"]: chemistry = pybamm.parameter_sets.Chen2020 chemistry["electrolyte"] = "lipf6_" + solvent + "_Landesfeind2019" - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues(chemistry) model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) sim.set_parameters() diff --git a/tests/unit/test_parameters/test_parameter_sets/test_NCA_Kim2011.py b/tests/unit/test_parameters/test_parameter_sets/test_NCA_Kim2011.py index 26143d727c..080dcdd45f 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_NCA_Kim2011.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_NCA_Kim2011.py @@ -42,7 +42,7 @@ def test_load_params(self): def test_standard_lithium_parameters(self): chemistry = pybamm.parameter_sets.NCA_Kim2011 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues(chemistry) model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_NCO_Ecker2015.py b/tests/unit/test_parameters/test_parameter_sets/test_NCO_Ecker2015.py index 9dc6f194c6..a6db637374 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_NCO_Ecker2015.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_NCO_Ecker2015.py @@ -44,7 +44,7 @@ def test_load_params(self): def test_standard_lithium_parameters(self): chemistry = pybamm.parameter_sets.Ecker2015 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues(chemistry) model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_NMChalfcell_Xu2019.py b/tests/unit/test_parameters/test_parameter_sets/test_NMChalfcell_Xu2019.py index 713a057b9a..f629435a10 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_NMChalfcell_Xu2019.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_NMChalfcell_Xu2019.py @@ -44,7 +44,7 @@ def test_load_params(self): def test_standard_lithium_parameters(self): chemistry = pybamm.parameter_sets.Xu2019 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues(chemistry) model = pybamm.lithium_ion.BasicDFNHalfCell({"working electrode": "positive"}) sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_OKane2020.py b/tests/unit/test_parameters/test_parameter_sets/test_OKane2020.py index ea7e151209..1e1180e6f2 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_OKane2020.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_OKane2020.py @@ -1,12 +1,12 @@ # -# Tests for Ai (2020) Enertech parameter set loads +# Tests for O'Kane (2020) parameter set # import pybamm import unittest import os -class TestAi2020(unittest.TestCase): +class TestOKane2020(unittest.TestCase): def test_load_params(self): Li_plating = pybamm.ParameterValues({}).read_parameters_csv( pybamm.get_parameters_filepath( @@ -15,13 +15,12 @@ def test_load_params(self): ) ) self.assertEqual( - Li_plating["Lithium metal partial molar volume [m3.mol-1]"], - "1.30E-05" + Li_plating["Lithium metal partial molar volume [m3.mol-1]"], "1.30E-05" ) def test_functions(self): root = pybamm.root_dir() - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020_plating) + param = pybamm.ParameterValues("Chen2020_plating") T = pybamm.Scalar(298.15) p = "pybamm/input/parameters/lithium_ion/lithium_platings/okane2020_Li_plating/" @@ -31,7 +30,7 @@ def test_functions(self): "plating_exchange_current_density_OKane2020.py": ([1e3, 1e4, T], 9.6485e-3), "stripping_exchange_current_density_OKane2020.py": ( [1e3, 1e4, T], - 9.6485e-2 + 9.6485e-2, ), } diff --git a/tests/unit/test_parameters/test_parameter_sets/test_UMBL_Mohtat2020.py b/tests/unit/test_parameters/test_parameter_sets/test_UMBL_Mohtat2020.py index 869ac6b5db..67e5962775 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_UMBL_Mohtat2020.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_UMBL_Mohtat2020.py @@ -43,7 +43,7 @@ def test_load_params(self): def test_standard_lithium_parameters(self): chemistry = pybamm.parameter_sets.Mohtat2020 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues(chemistry) model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_values.py b/tests/unit/test_parameters/test_parameter_values.py index 59e9ecad11..ad1fd020a5 100644 --- a/tests/unit/test_parameters/test_parameter_values.py +++ b/tests/unit/test_parameters/test_parameter_values.py @@ -10,7 +10,6 @@ import numpy as np import pandas as pd -import copy import pybamm import tests.shared as shared @@ -79,7 +78,7 @@ def test_repr(self): def test_update_from_chemistry(self): # incomplete chemistry with self.assertRaisesRegex(KeyError, "must provide 'cell' parameters"): - pybamm.ParameterValues(chemistry={"chemistry": "lithium_ion"}) + pybamm.ParameterValues({"chemistry": "lithium_ion"}) def test_update_from_chemistry_local(self): # Copy parameters @@ -87,14 +86,14 @@ def test_update_from_chemistry_local(self): subprocess.run(cmd) # Import parameters from chemistry - pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020) + pybamm.ParameterValues("Chen2020") # Clean up parameter files shutil.rmtree("lithium_ion") def test_update(self): # converts to dict if not - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020) + param = pybamm.ParameterValues("Chen2020") param_from_csv = pybamm.ParameterValues( "lithium_ion/negative_electrodes/graphite_Chen2020/parameters.csv" ) @@ -700,7 +699,7 @@ def test_process_complex_expression(self): scal2 = pybamm.Scalar(4) expression = (scal1 * (par1 ** var2)) / ((var1 - par2) + scal2) - param = pybamm.ParameterValues(values={"par1": 1, "par2": 2}) + param = pybamm.ParameterValues({"par1": 1, "par2": 2}) exp_param = param.process_symbol(expression) self.assertIsInstance(exp_param, pybamm.Division) # left side @@ -857,25 +856,25 @@ def some_function(self): self.assertEqual(df[1]["c"], "[data]some_data") def test_deprecate_anode_cathode(self): - chemistry = copy.deepcopy(pybamm.parameter_sets.Ecker2015) + chemistry = pybamm.parameter_sets.Ecker2015.copy() chemistry["anode"] = chemistry.pop("negative electrode") with self.assertWarnsRegex(DeprecationWarning, "anode"): - pybamm.ParameterValues(chemistry=chemistry) + pybamm.ParameterValues(chemistry) - chemistry = copy.deepcopy(pybamm.parameter_sets.Ecker2015) + chemistry = pybamm.parameter_sets.Ecker2015.copy() chemistry["cathode"] = chemistry.pop("positive electrode") with self.assertWarnsRegex(DeprecationWarning, "cathode"): - pybamm.ParameterValues(chemistry=chemistry) + pybamm.ParameterValues(chemistry) - chemistry = copy.deepcopy(pybamm.parameter_sets.Ecker2015) + chemistry = pybamm.parameter_sets.Ecker2015.copy() chemistry["anode"] = None with self.assertRaisesRegex(KeyError, "both 'anode' and 'negative"): - pybamm.ParameterValues(chemistry=chemistry) + pybamm.ParameterValues(chemistry) - chemistry = copy.deepcopy(pybamm.parameter_sets.Ecker2015) + chemistry = pybamm.parameter_sets.Ecker2015.copy() chemistry["cathode"] = None with self.assertRaisesRegex(KeyError, "both 'cathode' and 'positive"): - pybamm.ParameterValues(chemistry=chemistry) + pybamm.ParameterValues(chemistry) if __name__ == "__main__": diff --git a/tests/unit/test_plotting/test_quick_plot.py b/tests/unit/test_plotting/test_quick_plot.py index aca43c6e68..ce939f384f 100644 --- a/tests/unit/test_plotting/test_quick_plot.py +++ b/tests/unit/test_plotting/test_quick_plot.py @@ -482,8 +482,7 @@ def test_failure(self): pybamm.QuickPlot(1) def test_model_with_inputs(self): - chemistry = pybamm.parameter_sets.Chen2020 - parameter_values = pybamm.ParameterValues(chemistry=chemistry) + parameter_values = pybamm.ParameterValues("Chen2020") model = pybamm.lithium_ion.SPMe() parameter_values.update({"Electrode height [m]": "[input]"}) solver = pybamm.CasadiSolver(mode="safe") diff --git a/tests/unit/test_simulation.py b/tests/unit/test_simulation.py index 0df41e6ffc..d2c9a3e61a 100644 --- a/tests/unit/test_simulation.py +++ b/tests/unit/test_simulation.py @@ -298,7 +298,7 @@ def test_save_load(self): def test_load_param(self): # Test load_sim for parameters imports filename = f"{uuid.uuid4()}.p" - save_sim = f"import pybamm; model = pybamm.lithium_ion.SPM(); params = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Chen2020); sim = pybamm.Simulation(model, parameter_values=params); sim.solve([0, 3600]); sim.save('{filename}')" # noqa + save_sim = f"import pybamm; model = pybamm.lithium_ion.SPM(); params = pybamm.ParameterValues("Chen2020"); sim = pybamm.Simulation(model, parameter_values=params); sim.solve([0, 3600]); sim.save('{filename}')" # noqa subprocess.run([sys.executable, "-c", save_sim]) try: diff --git a/tests/unit/test_solvers/test_casadi_solver.py b/tests/unit/test_solvers/test_casadi_solver.py index c98d4f2e63..4678e7fec9 100644 --- a/tests/unit/test_solvers/test_casadi_solver.py +++ b/tests/unit/test_solvers/test_casadi_solver.py @@ -478,7 +478,7 @@ def test_dae_solver_algebraic_model(self): def test_interpolant_extrapolate(self): model = pybamm.lithium_ion.DFN() - param = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.NCA_Kim2011) + param = pybamm.ParameterValues("NCA_Kim2011") experiment = pybamm.Experiment( ["Charge at 1C until 4.6 V"], period="10 seconds" ) @@ -549,12 +549,11 @@ def test_solve_sensitivity_scalar_var_scalar_input(self): # Solve # Make sure that passing in extra options works - solver = pybamm.CasadiSolver( - mode="fast", rtol=1e-10, atol=1e-10 - ) + solver = pybamm.CasadiSolver(mode="fast", rtol=1e-10, atol=1e-10) t_eval = np.linspace(0, 1, 80) - solution = solver.solve(model, t_eval, inputs={"p": 0.1}, - calculate_sensitivities=True) + solution = solver.solve( + model, t_eval, inputs={"p": 0.1}, calculate_sensitivities=True + ) np.testing.assert_array_equal(solution.t, t_eval) np.testing.assert_allclose(solution.y[0], np.exp(0.1 * solution.t)) np.testing.assert_allclose( @@ -585,20 +584,22 @@ def test_solve_sensitivity_scalar_var_scalar_input(self): # Solve # Make sure that passing in extra options works - solver = pybamm.CasadiSolver( - rtol=1e-10, atol=1e-10 - ) + solver = pybamm.CasadiSolver(rtol=1e-10, atol=1e-10) t_eval = np.linspace(0, 1, 80) solution = solver.solve( - model, t_eval, inputs={"p": 0.1, "q": 2, "r": -1, "s": 0.5}, + model, + t_eval, + inputs={"p": 0.1, "q": 2, "r": -1, "s": 0.5}, calculate_sensitivities=True, ) np.testing.assert_allclose(solution.y[0], -1 + 0.2 * solution.t) np.testing.assert_allclose( - solution.sensitivities["p"], (2 * solution.t)[:, np.newaxis], + solution.sensitivities["p"], + (2 * solution.t)[:, np.newaxis], ) np.testing.assert_allclose( - solution.sensitivities["q"], (0.1 * solution.t)[:, np.newaxis], + solution.sensitivities["q"], + (0.1 * solution.t)[:, np.newaxis], ) np.testing.assert_allclose(solution.sensitivities["r"], 1) np.testing.assert_allclose(solution.sensitivities["s"], 0) @@ -659,10 +660,13 @@ def test_solve_sensitivity_vector_var_scalar_input(self): # Solve - scalar input solver = pybamm.CasadiSolver() t_eval = np.linspace(0, 1) - solution = solver.solve(model, t_eval, inputs={"param": 7}, - calculate_sensitivities=["param"]) + solution = solver.solve( + model, t_eval, inputs={"param": 7}, calculate_sensitivities=["param"] + ) np.testing.assert_array_almost_equal( - solution["var"].data, np.tile(2 * np.exp(-7 * t_eval), (n, 1)), decimal=4, + solution["var"].data, + np.tile(2 * np.exp(-7 * t_eval), (n, 1)), + decimal=4, ) np.testing.assert_array_almost_equal( solution["var"].sensitivities["param"], @@ -690,19 +694,24 @@ def test_solve_sensitivity_vector_var_scalar_input(self): # Solve # Make sure that passing in extra options works solver = pybamm.CasadiSolver( - rtol=1e-10, atol=1e-10, + rtol=1e-10, + atol=1e-10, ) t_eval = np.linspace(0, 1, 80) solution = solver.solve( - model, t_eval, inputs={"p": 0.1, "q": 2, "r": -1, "s": 0.5}, + model, + t_eval, + inputs={"p": 0.1, "q": 2, "r": -1, "s": 0.5}, calculate_sensitivities=True, ) np.testing.assert_allclose(solution.y, np.tile(-1 + 0.2 * solution.t, (n, 1))) np.testing.assert_allclose( - solution.sensitivities["p"], np.repeat(2 * solution.t, n)[:, np.newaxis], + solution.sensitivities["p"], + np.repeat(2 * solution.t, n)[:, np.newaxis], ) np.testing.assert_allclose( - solution.sensitivities["q"], np.repeat(0.1 * solution.t, n)[:, np.newaxis], + solution.sensitivities["q"], + np.repeat(0.1 * solution.t, n)[:, np.newaxis], ) np.testing.assert_allclose(solution.sensitivities["r"], 1) np.testing.assert_allclose(solution.sensitivities["s"], 0) @@ -767,15 +776,19 @@ def test_solve_sensitivity_scalar_var_vector_input(self): n = disc.mesh["negative electrode"].npts # Solve - constant input - solver = pybamm.CasadiSolver( - mode="fast", rtol=1e-10, atol=1e-10 - ) + solver = pybamm.CasadiSolver(mode="fast", rtol=1e-10, atol=1e-10) t_eval = np.linspace(0, 1) - solution = solver.solve(model, t_eval, inputs={"param": 7 * np.ones(n)}, - calculate_sensitivities=True) + solution = solver.solve( + model, + t_eval, + inputs={"param": 7 * np.ones(n)}, + calculate_sensitivities=True, + ) l_n = mesh["negative electrode"].edges[-1] np.testing.assert_array_almost_equal( - solution["var"].data, np.tile(2 * np.exp(-7 * t_eval), (n, 1)), decimal=4, + solution["var"].data, + np.tile(2 * np.exp(-7 * t_eval), (n, 1)), + decimal=4, ) np.testing.assert_array_almost_equal( @@ -783,7 +796,9 @@ def test_solve_sensitivity_scalar_var_vector_input(self): np.vstack([np.eye(n) * -2 * t * np.exp(-7 * t) for t in t_eval]), ) np.testing.assert_array_almost_equal( - solution["integral of var"].data, 2 * np.exp(-7 * t_eval) * l_n, decimal=4, + solution["integral of var"].data, + 2 * np.exp(-7 * t_eval) * l_n, + decimal=4, ) np.testing.assert_array_almost_equal( solution["integral of var"].sensitivities["param"], @@ -792,8 +807,9 @@ def test_solve_sensitivity_scalar_var_vector_input(self): # Solve - linspace input p_eval = np.linspace(1, 2, n) - solution = solver.solve(model, t_eval, inputs={"param": p_eval}, - calculate_sensitivities=True) + solution = solver.solve( + model, t_eval, inputs={"param": p_eval}, calculate_sensitivities=True + ) l_n = mesh["negative electrode"].edges[-1] np.testing.assert_array_almost_equal( solution["var"].data, 2 * np.exp(-p_eval[:, np.newaxis] * t_eval), decimal=4 @@ -828,12 +844,11 @@ def test_solve_sensitivity_then_no_sensitivity(self): # Solve # Make sure that passing in extra options works - solver = pybamm.CasadiSolver( - mode="fast", rtol=1e-10, atol=1e-10 - ) + solver = pybamm.CasadiSolver(mode="fast", rtol=1e-10, atol=1e-10) t_eval = np.linspace(0, 1, 80) - solution = solver.solve(model, t_eval, inputs={"p": 0.1}, - calculate_sensitivities=True) + solution = solver.solve( + model, t_eval, inputs={"p": 0.1}, calculate_sensitivities=True + ) # check sensitivities np.testing.assert_allclose( @@ -865,21 +880,24 @@ def test_solve_sensitivity_scalar_var_scalar_input(self): # Solve # Make sure that passing in extra options works - solver = pybamm.CasadiSolver( - mode="fast", rtol=1e-10, atol=1e-10 - ) + solver = pybamm.CasadiSolver(mode="fast", rtol=1e-10, atol=1e-10) t_eval = np.linspace(0, 1, 80) - solution = solver.solve(model, t_eval, inputs={"p": 0.1}, - calculate_sensitivities=True) + solution = solver.solve( + model, t_eval, inputs={"p": 0.1}, calculate_sensitivities=True + ) np.testing.assert_array_equal(solution.t, t_eval) np.testing.assert_allclose(solution.y[0], np.exp(0.1 * solution.t)) np.testing.assert_allclose( solution.sensitivities["p"], - np.stack(( - solution.t * np.exp(0.1 * solution.t), - 2 * solution.t * np.exp(0.1 * solution.t), - )).transpose().reshape(-1, 1), - atol=1e-7 + np.stack( + ( + solution.t * np.exp(0.1 * solution.t), + 2 * solution.t * np.exp(0.1 * solution.t), + ) + ) + .transpose() + .reshape(-1, 1), + atol=1e-7, ) np.testing.assert_allclose( solution["var2 squared"].data, 4 * np.exp(2 * 0.1 * solution.t) @@ -887,7 +905,7 @@ def test_solve_sensitivity_scalar_var_scalar_input(self): np.testing.assert_allclose( solution["var2 squared"].sensitivities["p"], (8 * solution.t * np.exp(2 * 0.1 * solution.t))[:, np.newaxis], - atol=1e-7 + atol=1e-7, ) def test_solve_sensitivity_algebraic(self): @@ -903,8 +921,9 @@ def test_solve_sensitivity_algebraic(self): # Make sure that passing in extra options works solver = pybamm.CasadiAlgebraicSolver(tol=1e-10) t_eval = np.linspace(0, 1, 80) - solution = solver.solve(model, t_eval, inputs={"p": 0.1}, - calculate_sensitivities=True) + solution = solver.solve( + model, t_eval, inputs={"p": 0.1}, calculate_sensitivities=True + ) np.testing.assert_array_equal(solution.t, t_eval) np.testing.assert_allclose(solution.y[0], 0.1 * solution.t) np.testing.assert_allclose( @@ -916,7 +935,7 @@ def test_solve_sensitivity_algebraic(self): np.testing.assert_allclose( solution["var squared"].sensitivities["p"], (2 * 0.1 * solution.t ** 2).reshape(-1, 1), - atol=1e-7 + atol=1e-7, ) From cc1b429ae2780a44054b2a57f48c189f833c9052 Mon Sep 17 00:00:00 2001 From: Valentin Sulzer Date: Thu, 18 Nov 2021 19:30:19 -0500 Subject: [PATCH 2/8] #1810 allow strings in var_pts and geometry --- benchmarks/time_solve_models.py | 11 +-- .../Tutorial 9 - Changing the mesh.ipynb | 20 ++--- .../expression_tree/broadcasts.ipynb | 6 +- ...ating_mechanical_models_Enertech_DFN.ipynb | 10 +-- .../compare-comsol-discharge-curve.ipynb | 2 +- .../notebooks/models/compare-ecker-data.ipynb | 10 +-- .../notebooks/models/pouch-cell-model.ipynb | 12 +-- ...simulating-ORegan-2021-parameter-set.ipynb | 2 +- .../spatial_methods/finite-volumes.ipynb | 2 +- examples/scripts/DFN_ambient_temperature.py | 3 +- examples/scripts/SPMe_SOC.py | 9 +- .../compare_comsol/compare_comsol_DFN.py | 3 +- .../scripts/compare_comsol/discharge_curve.py | 3 +- examples/scripts/compare_dae_solver.py | 3 +- examples/scripts/compare_lithium_ion_2D.py | 11 +-- examples/scripts/compare_spectral_volume.py | 3 +- examples/scripts/thermal_lithium_ion.py | 3 +- pybamm/geometry/battery_geometry.py | 32 +++---- pybamm/meshes/meshes.py | 17 +++- pybamm/meshes/one_dimensional_submeshes.py | 4 +- .../full_battery_models/base_battery_model.py | 21 +++-- .../lead_acid/base_lead_acid_model.py | 3 +- .../effective_resistance_current_collector.py | 16 ++-- .../test_asymptotics_convergence.py | 3 +- .../test_lead_acid/test_compare_outputs.py | 6 +- .../test_lead_acid/test_composite.py | 3 +- .../test_lead_acid/test_full.py | 6 +- .../test_lead_acid/test_loqs.py | 3 +- .../base_lithium_ion_tests.py | 22 +---- .../test_lithium_ion/test_compare_outputs.py | 26 ++---- .../test_lithium_ion/test_dfn.py | 25 +++--- .../test_lithium_ion/test_mpm.py | 6 +- .../test_lithium_ion/test_thermal_models.py | 11 +-- .../test_function_control.py | 3 +- .../test_solvers/test_external_variables.py | 3 +- tests/integration/test_solvers/test_idaklu.py | 21 +++-- .../integration/test_solvers/test_solution.py | 3 +- .../test_spectral_volume.py | 15 ++-- tests/shared.py | 24 +++-- .../test_geometry/test_battery_geometry.py | 9 +- tests/unit/test_meshes/test_meshes.py | 90 +++++++++++-------- .../test_meshes/test_scikit_fem_submesh.py | 64 ++++++------- tests/unit/test_models/test_base_model.py | 9 +- .../test_base_battery_model.py | 22 +++-- .../test_base_lead_acid_model.py | 8 +- .../test_effective_current_collector.py | 11 +-- tests/unit/test_plotting/test_quick_plot.py | 17 +--- tests/unit/test_simulation.py | 3 +- tests/unit/test_solvers/test_solution.py | 3 +- .../test_finite_volume/test_extrapolation.py | 7 +- .../test_scikit_finite_element.py | 6 +- .../test_spectral_volume.py | 15 ++-- 52 files changed, 266 insertions(+), 384 deletions(-) diff --git a/benchmarks/time_solve_models.py b/benchmarks/time_solve_models.py index 517238e324..add84173a1 100644 --- a/benchmarks/time_solve_models.py +++ b/benchmarks/time_solve_models.py @@ -14,16 +14,7 @@ def prepare_model(model): param.process_geometry(geometry) # set mesh - var = pybamm.standard_spatial_vars - var_pts = { - var.x_n: 20, - var.x_s: 20, - var.x_p: 20, - var.r_n: 30, - var.r_p: 30, - var.y: 10, - var.z: 10, - } + var_pts = {"x_n": 20, "x_s": 20, "x_p": 20, "r_n": 30, "r_p": 30, "y": 10, "z": 10} mesh = pybamm.Mesh(geometry, model.default_submesh_types, var_pts) # discretise model diff --git a/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb b/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb index 786a7cf4db..39fe6af065 100644 --- a/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb +++ b/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb @@ -100,11 +100,11 @@ "\n", "# create our dictionary \n", "var_pts = {\n", - " var.x_n: 10, # negative electrode\n", - " var.x_s: 10, # separator \n", - " var.x_p: 10, # positive electrode\n", - " var.r_n: 10, # negative particle\n", - " var.r_p: 10, # positive particle\n", + " "x_n": 10, # negative electrode\n", + " "x_s": 10, # separator \n", + " "x_p": 10, # positive electrode\n", + " "r_n": 10, # negative particle\n", + " "r_p": 10, # positive particle\n", "}" ] }, @@ -210,11 +210,11 @@ "solutions = []\n", "for N in npts:\n", " var_pts = {\n", - " var.x_n: N, # negative electrode\n", - " var.x_s: N, # separator \n", - " var.x_p: N, # positive electrode\n", - " var.r_n: N, # negative particle\n", - " var.r_p: N, # positive particle\n", + " "x_n": N, # negative electrode\n", + " "x_s": N, # separator \n", + " "x_p": N, # positive electrode\n", + " "r_n": N, # negative particle\n", + " "r_p": N, # positive particle\n", " } \n", " sim = pybamm.Simulation(\n", " model, solver=solver, parameter_values=parameter_values, var_pts=var_pts\n", diff --git a/examples/notebooks/expression_tree/broadcasts.ipynb b/examples/notebooks/expression_tree/broadcasts.ipynb index 08b447f376..f86e57e359 100644 --- a/examples/notebooks/expression_tree/broadcasts.ipynb +++ b/examples/notebooks/expression_tree/broadcasts.ipynb @@ -44,8 +44,8 @@ "source": [ "var = pybamm.standard_spatial_vars\n", "geometry = {\n", - " \"negative electrode\": {var.x_n: {\"min\": pybamm.Scalar(0), \"max\": pybamm.Scalar(1)}},\n", - " \"negative particle\": {var.r_n: {\"min\": pybamm.Scalar(0), \"max\": pybamm.Scalar(1)}},\n", + " \"negative electrode\": {"x_n": {\"min\": pybamm.Scalar(0), \"max\": pybamm.Scalar(1)}},\n", + " \"negative particle\": {"r_n": {\"min\": pybamm.Scalar(0), \"max\": pybamm.Scalar(1)}},\n", "}\n", "\n", "submesh_types = {\n", @@ -53,7 +53,7 @@ " \"negative particle\": pybamm.Uniform1DSubMesh,\n", "}\n", "\n", - "var_pts = {var.x_n: 5, var.r_n: 3}\n", + "var_pts = {"x_n": 5, "r_n": 3}\n", "mesh = pybamm.Mesh(geometry, submesh_types, var_pts)\n", "\n", "spatial_methods = {\n", diff --git a/examples/notebooks/models/Validating_mechanical_models_Enertech_DFN.ipynb b/examples/notebooks/models/Validating_mechanical_models_Enertech_DFN.ipynb index 8486a4637f..bcc6054c3c 100644 --- a/examples/notebooks/models/Validating_mechanical_models_Enertech_DFN.ipynb +++ b/examples/notebooks/models/Validating_mechanical_models_Enertech_DFN.ipynb @@ -87,11 +87,11 @@ "# update the mesh\n", "var = pybamm.standard_spatial_vars\n", "var_pts = {\n", - " var.x_n: 50,\n", - " var.x_s: 50,\n", - " var.x_p: 50,\n", - " var.r_n: 21,\n", - " var.r_p: 21,\n", + " "x_n": 50,\n", + " "x_s": 50,\n", + " "x_p": 50,\n", + " "r_n": 21,\n", + " "r_p": 21,\n", "}\n", "\n", "# define the simulation\n", diff --git a/examples/notebooks/models/compare-comsol-discharge-curve.ipynb b/examples/notebooks/models/compare-comsol-discharge-curve.ipynb index 31862c8601..0d7e369bbb 100644 --- a/examples/notebooks/models/compare-comsol-discharge-curve.ipynb +++ b/examples/notebooks/models/compare-comsol-discharge-curve.ipynb @@ -93,7 +93,7 @@ "\n", "# create mesh\n", "var = pybamm.standard_spatial_vars\n", - "var_pts = {var.x_n: 31, var.x_s: 11, var.x_p: 31, var.r_n: 11, var.r_p: 11}\n", + "var_pts = {"x_n": 31, "x_s": 11, "x_p": 31, "r_n": 11, "r_p": 11}\n", "mesh = pybamm.Mesh(geometry, model.default_submesh_types, var_pts)\n", "\n", "# discretise model\n", diff --git a/examples/notebooks/models/compare-ecker-data.ipynb b/examples/notebooks/models/compare-ecker-data.ipynb index 17ddb4cbeb..e681da01fc 100644 --- a/examples/notebooks/models/compare-ecker-data.ipynb +++ b/examples/notebooks/models/compare-ecker-data.ipynb @@ -100,11 +100,11 @@ "source": [ "var = pybamm.standard_spatial_vars\n", "var_pts = {\n", - " var.x_n: int(parameter_values.evaluate(model.param.L_n / 1e-6)),\n", - " var.x_s: int(parameter_values.evaluate(model.param.L_s / 1e-6)),\n", - " var.x_p: int(parameter_values.evaluate(model.param.L_p / 1e-6)),\n", - " var.r_n: int(parameter_values.evaluate(model.param.R_n_typ / 1e-7)),\n", - " var.r_p: int(parameter_values.evaluate(model.param.R_p_typ / 1e-7)),\n", + " "x_n": int(parameter_values.evaluate(model.param.L_n / 1e-6)),\n", + " "x_s": int(parameter_values.evaluate(model.param.L_s / 1e-6)),\n", + " "x_p": int(parameter_values.evaluate(model.param.L_p / 1e-6)),\n", + " "r_n": int(parameter_values.evaluate(model.param.R_n_typ / 1e-7)),\n", + " "r_p": int(parameter_values.evaluate(model.param.R_p_typ / 1e-7)),\n", "}" ] }, diff --git a/examples/notebooks/models/pouch-cell-model.ipynb b/examples/notebooks/models/pouch-cell-model.ipynb index 6f4150cd14..17ce645965 100644 --- a/examples/notebooks/models/pouch-cell-model.ipynb +++ b/examples/notebooks/models/pouch-cell-model.ipynb @@ -157,12 +157,12 @@ "var = pybamm.standard_spatial_vars\n", "npts = 16\n", "var_pts = {\n", - " var.x_n: npts,\n", - " var.x_s: npts,\n", - " var.x_p: npts,\n", - " var.r_n: npts,\n", - " var.r_p: npts,\n", - " var.z: npts,\n", + " "x_n": npts,\n", + " "x_s": npts,\n", + " "x_p": npts,\n", + " "r_n": npts,\n", + " "r_p": npts,\n", + " "z": npts,\n", "}" ] }, diff --git a/examples/notebooks/models/simulating-ORegan-2021-parameter-set.ipynb b/examples/notebooks/models/simulating-ORegan-2021-parameter-set.ipynb index 25558bf97c..ec4bf1167c 100644 --- a/examples/notebooks/models/simulating-ORegan-2021-parameter-set.ipynb +++ b/examples/notebooks/models/simulating-ORegan-2021-parameter-set.ipynb @@ -71,7 +71,7 @@ "outputs": [], "source": [ "var = pybamm.standard_spatial_vars\n", - "var_pts = {var.x_n: 30, var.x_s: 30, var.x_p: 30, var.r_n: 40, var.r_p: 40}\n", + "var_pts = {"x_n": 30, "x_s": 30, "x_p": 30, "r_n": 40, "r_p": 40}\n", "\n", "submesh_types = model.default_submesh_types\n", "submesh_types[\"negative particle\"] = pybamm.MeshGenerator(\n", diff --git a/examples/notebooks/spatial_methods/finite-volumes.ipynb b/examples/notebooks/spatial_methods/finite-volumes.ipynb index 73411ac0ed..3558253ba1 100644 --- a/examples/notebooks/spatial_methods/finite-volumes.ipynb +++ b/examples/notebooks/spatial_methods/finite-volumes.ipynb @@ -119,7 +119,7 @@ "}\n", "\n", "var = pybamm.standard_spatial_vars\n", - "var_pts = {var.x_n: 15, var.x_s: 10, var.x_p: 15, var.r_n: 10, var.r_p: 10}\n", + "var_pts = {"x_n": 15, "x_s": 10, "x_p": 15, "r_n": 10, "r_p": 10}\n", "mesh = pybamm.Mesh(geometry, submesh_types, var_pts)" ] }, diff --git a/examples/scripts/DFN_ambient_temperature.py b/examples/scripts/DFN_ambient_temperature.py index 5cf515e02d..7fa2cb31f3 100644 --- a/examples/scripts/DFN_ambient_temperature.py +++ b/examples/scripts/DFN_ambient_temperature.py @@ -30,8 +30,7 @@ def ambient_temperature(t): param.process_geometry(geometry) # set mesh -var = pybamm.standard_spatial_vars -var_pts = {var.x_n: 30, var.x_s: 30, var.x_p: 30, var.r_n: 10, var.r_p: 10} +var_pts = {"x_n": 30, "x_s": 30, "x_p": 30, "r_n": 10, "r_p": 10} mesh = pybamm.Mesh(geometry, model.default_submesh_types, var_pts) # discretise model diff --git a/examples/scripts/SPMe_SOC.py b/examples/scripts/SPMe_SOC.py index 0379253bd6..277365cf30 100644 --- a/examples/scripts/SPMe_SOC.py +++ b/examples/scripts/SPMe_SOC.py @@ -58,14 +58,7 @@ ) param.process_model(model) param.process_geometry(geometry) - s_var = pybamm.standard_spatial_vars - var_pts = { - s_var.x_n: 5, - s_var.x_s: 5, - s_var.x_p: 5, - s_var.r_n: 5, - s_var.r_p: 10, - } + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 5, "r_p": 10} # set mesh mesh = pybamm.Mesh(geometry, model.default_submesh_types, var_pts) # discretise model diff --git a/examples/scripts/compare_comsol/compare_comsol_DFN.py b/examples/scripts/compare_comsol/compare_comsol_DFN.py index 2320a1b435..1ebe6176bf 100644 --- a/examples/scripts/compare_comsol/compare_comsol_DFN.py +++ b/examples/scripts/compare_comsol/compare_comsol_DFN.py @@ -45,8 +45,7 @@ param.process_geometry(geometry) # create mesh -var = pybamm.standard_spatial_vars -var_pts = {var.x_n: 31, var.x_s: 11, var.x_p: 31, var.r_n: 11, var.r_p: 11} +var_pts = {"x_n": 31, "x_s": 11, "x_p": 31, "r_n": 11, "r_p": 11} mesh = pybamm.Mesh(geometry, pybamm_model.default_submesh_types, var_pts) # discretise model diff --git a/examples/scripts/compare_comsol/discharge_curve.py b/examples/scripts/compare_comsol/discharge_curve.py index 10da794bf7..7b12f4c759 100644 --- a/examples/scripts/compare_comsol/discharge_curve.py +++ b/examples/scripts/compare_comsol/discharge_curve.py @@ -30,8 +30,7 @@ param.process_geometry(geometry) # create mesh -var = pybamm.standard_spatial_vars -var_pts = {var.x_n: 31, var.x_s: 11, var.x_p: 31, var.r_n: 11, var.r_p: 11} +var_pts = {"x_n": 31, "x_s": 11, "x_p": 31, "r_n": 11, "r_p": 11} mesh = pybamm.Mesh(geometry, model.default_submesh_types, var_pts) # discretise model diff --git a/examples/scripts/compare_dae_solver.py b/examples/scripts/compare_dae_solver.py index 8b3a467a26..c98309a2ed 100644 --- a/examples/scripts/compare_dae_solver.py +++ b/examples/scripts/compare_dae_solver.py @@ -15,8 +15,7 @@ param.process_geometry(geometry) # set mesh -var = pybamm.standard_spatial_vars -var_pts = {var.x_n: 50, var.x_s: 50, var.x_p: 50, var.r_n: 20, var.r_p: 20} +var_pts = {"x_n": 50, "x_s": 50, "x_p": 50, "r_n": 20, "r_p": 20} mesh = pybamm.Mesh(geometry, model.default_submesh_types, var_pts) # discretise model diff --git a/examples/scripts/compare_lithium_ion_2D.py b/examples/scripts/compare_lithium_ion_2D.py index 4d92dd9430..f0fd4ba5da 100644 --- a/examples/scripts/compare_lithium_ion_2D.py +++ b/examples/scripts/compare_lithium_ion_2D.py @@ -34,16 +34,7 @@ for model in models: geometry = model.default_geometry param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = { - var.x_n: 10, - var.x_s: 10, - var.x_p: 10, - var.r_n: 10, - var.r_p: 10, - var.y: 10, - var.z: 10, - } + var_pts = {"x_n": 10, "x_s": 10, "x_p": 10, "r_n": 10, "r_p": 10, "y": 10, "z": 10} mesh = pybamm.Mesh(geometry, model.default_submesh_types, var_pts) disc = pybamm.Discretisation(mesh, model.default_spatial_methods) disc.process_model(model) diff --git a/examples/scripts/compare_spectral_volume.py b/examples/scripts/compare_spectral_volume.py index 537289938a..2259bc14d7 100644 --- a/examples/scripts/compare_spectral_volume.py +++ b/examples/scripts/compare_spectral_volume.py @@ -23,8 +23,7 @@ p.process_geometry(g) # set mesh -var = pybamm.standard_spatial_vars -var_pts = {var.x_n: 1, var.x_s: 1, var.x_p: 1, var.r_n: 1, var.r_p: 1} +var_pts = {"x_n": 1, "x_s": 1, "x_p": 1, "r_n": 1, "r_p": 1} # the Finite Volume method also works on spectral meshes meshes = [ pybamm.Mesh( diff --git a/examples/scripts/thermal_lithium_ion.py b/examples/scripts/thermal_lithium_ion.py index cd4c1fbdea..04c14bfaba 100644 --- a/examples/scripts/thermal_lithium_ion.py +++ b/examples/scripts/thermal_lithium_ion.py @@ -37,8 +37,7 @@ param.process_model(model) # set mesh -var = pybamm.standard_spatial_vars -var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 10, var.r_n: 10, var.r_p: 10} +var_pts = {"x_n": 10, "x_s": 10, "x_p": 10, "r_n": 10, "r_p": 10} # discretise models for model in models: diff --git a/pybamm/geometry/battery_geometry.py b/pybamm/geometry/battery_geometry.py index fe2a6bf5ac..14f6bd41b5 100644 --- a/pybamm/geometry/battery_geometry.py +++ b/pybamm/geometry/battery_geometry.py @@ -28,7 +28,6 @@ def battery_geometry( A geometry class for the battery """ - var = pybamm.standard_spatial_vars geo = pybamm.geometric_parameters l_n = geo.l_n l_s = geo.l_s @@ -38,43 +37,36 @@ def battery_geometry( l_n_l_s.print_name = "l_n + l_s" geometry = { - "negative electrode": {var.x_n: {"min": 0, "max": l_n}}, - "separator": {var.x_s: {"min": l_n, "max": l_n_l_s}}, - "positive electrode": {var.x_p: {"min": l_n_l_s, "max": 1}}, + "negative electrode": {"x_n": {"min": 0, "max": l_n}}, + "separator": {"x_s": {"min": l_n, "max": l_n_l_s}}, + "positive electrode": {"x_p": {"min": l_n_l_s, "max": 1}}, } # Add particle domains if include_particles is True: geometry.update( { - "negative particle": {var.r_n: {"min": 0, "max": 1}}, - "positive particle": {var.r_p: {"min": 0, "max": 1}}, + "negative particle": {"r_n": {"min": 0, "max": 1}}, + "positive particle": {"r_p": {"min": 0, "max": 1}}, } ) # Add particle size domains - if ( - options is not None and - options["particle size"] == "distribution" - ): + if options is not None and options["particle size"] == "distribution": R_min_n = geo.R_min_n R_min_p = geo.R_min_p R_max_n = geo.R_max_n R_max_p = geo.R_max_p geometry.update( { - "negative particle size": { - var.R_n: {"min": R_min_n, "max": R_max_n} - }, - "positive particle size": { - var.R_p: {"min": R_min_p, "max": R_max_p} - }, + "negative particle size": {"R_n": {"min": R_min_n, "max": R_max_n}}, + "positive particle size": {"R_p": {"min": R_min_p, "max": R_max_p}}, } ) if current_collector_dimension == 0: - geometry["current collector"] = {var.z: {"position": 1}} + geometry["current collector"] = {"z": {"position": 1}} elif current_collector_dimension == 1: geometry["current collector"] = { - var.z: {"min": 0, "max": 1}, + "z": {"min": 0, "max": 1}, "tabs": { "negative": {"z_centre": geo.centre_z_tab_n}, "positive": {"z_centre": geo.centre_z_tab_p}, @@ -82,8 +74,8 @@ def battery_geometry( } elif current_collector_dimension == 2: geometry["current collector"] = { - var.y: {"min": 0, "max": geo.l_y}, - var.z: {"min": 0, "max": geo.l_z}, + "y": {"min": 0, "max": geo.l_y}, + "z": {"min": 0, "max": geo.l_z}, "tabs": { "negative": { "y_centre": geo.centre_y_tab_n, diff --git a/pybamm/meshes/meshes.py b/pybamm/meshes/meshes.py index 87cf37ab3d..84e02771ee 100644 --- a/pybamm/meshes/meshes.py +++ b/pybamm/meshes/meshes.py @@ -26,8 +26,17 @@ class Mesh(dict): def __init__(self, geometry, submesh_types, var_pts): super().__init__() + + # Preprocess var_pts + var_pts_input = var_pts + var_pts = {} + for key, value in var_pts_input.items(): + if isinstance(key, str): + key = getattr(pybamm.standard_spatial_vars, key) + var_pts[key] = value + # convert var_pts to an id dict - var_id_pts = {var.id: pts for var, pts in var_pts.items()} + var_name_pts = {var.name: pts for var, pts in var_pts.items()} # create submesh_pts from var_pts submesh_pts = {} @@ -54,11 +63,13 @@ def __init__(self, geometry, submesh_types, var_pts): ) # skip over tabs key if var != "tabs": + if isinstance(var, str): + var = getattr(pybamm.standard_spatial_vars, var) # Raise error if the number of points for a particular # variable haven't been provided, unless that variable # doesn't appear in the geometry if ( - var.id not in var_id_pts.keys() + var.name not in var_name_pts.keys() and var.domain[0] in geometry.keys() ): raise KeyError( @@ -67,7 +78,7 @@ def __init__(self, geometry, submesh_types, var_pts): ) ) # Otherwise add to the dictionary of submesh points - submesh_pts[domain][var.id] = var_id_pts[var.id] + submesh_pts[domain][var.name] = var_name_pts[var.name] self.submesh_pts = submesh_pts # Input domain order manually diff --git a/pybamm/meshes/one_dimensional_submeshes.py b/pybamm/meshes/one_dimensional_submeshes.py index f4f0bdd66f..14f1de4bfc 100644 --- a/pybamm/meshes/one_dimensional_submeshes.py +++ b/pybamm/meshes/one_dimensional_submeshes.py @@ -90,7 +90,9 @@ class Uniform1DSubMesh(SubMesh1D): def __init__(self, lims, npts): spatial_var, spatial_lims, tabs = self.read_lims(lims) - npts = npts[spatial_var.id] + if isinstance(spatial_var, str): + spatial_var = getattr(pybamm.standard_spatial_vars, spatial_var) + npts = npts[spatial_var.name] edges = np.linspace(spatial_lims["min"], spatial_lims["max"], npts + 1) diff --git a/pybamm/models/full_battery_models/base_battery_model.py b/pybamm/models/full_battery_models/base_battery_model.py index 91260f2053..7b9ae079fa 100644 --- a/pybamm/models/full_battery_models/base_battery_model.py +++ b/pybamm/models/full_battery_models/base_battery_model.py @@ -446,21 +446,20 @@ def default_geometry(self): @property def default_var_pts(self): - var = pybamm.standard_spatial_vars base_var_pts = { - var.x_n: 20, - var.x_s: 20, - var.x_p: 20, - var.r_n: 20, - var.r_p: 20, - var.y: 10, - var.z: 10, - var.R_n: 30, - var.R_p: 30, + "x_n": 20, + "x_s": 20, + "x_p": 20, + "r_n": 20, + "r_p": 20, + "y": 10, + "z": 10, + "R_n": 30, + "R_p": 30, } # Reduce the default points for 2D current collectors if self.options["dimensionality"] == 2: - base_var_pts.update({var.x_n: 10, var.x_s: 10, var.x_p: 10}) + base_var_pts.update({"x_n": 10, "x_s": 10, "x_p": 10}) return base_var_pts @property diff --git a/pybamm/models/full_battery_models/lead_acid/base_lead_acid_model.py b/pybamm/models/full_battery_models/lead_acid/base_lead_acid_model.py index 637aecc656..8927d84d07 100644 --- a/pybamm/models/full_battery_models/lead_acid/base_lead_acid_model.py +++ b/pybamm/models/full_battery_models/lead_acid/base_lead_acid_model.py @@ -51,8 +51,7 @@ def default_geometry(self): @property def default_var_pts(self): # Choose points that give uniform grid for the standard parameter values - var = pybamm.standard_spatial_vars - return {var.x_n: 25, var.x_s: 41, var.x_p: 34, var.y: 10, var.z: 10} + return {"x_n": 25, "x_s": 41, "x_p": 34, "y": 10, "z": 10} @property def default_quick_plot_variables(self): diff --git a/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py b/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py index c270f2a12a..fdfc8a8779 100644 --- a/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py +++ b/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py @@ -221,7 +221,7 @@ def default_geometry(self): var = pybamm.standard_spatial_vars if self.options["dimensionality"] == 1: geometry["current collector"] = { - var.z: {"min": 0, "max": 1}, + "z": {"min": 0, "max": 1}, "tabs": { "negative": {"z_centre": param.centre_z_tab_n}, "positive": {"z_centre": param.centre_z_tab_p}, @@ -229,8 +229,8 @@ def default_geometry(self): } elif self.options["dimensionality"] == 2: geometry["current collector"] = { - var.y: {"min": 0, "max": param.l_y}, - var.z: {"min": 0, "max": param.l_z}, + "y": {"min": 0, "max": param.l_y}, + "z": {"min": 0, "max": param.l_z}, "tabs": { "negative": { "y_centre": param.centre_y_tab_n, @@ -248,8 +248,7 @@ def default_geometry(self): @property def default_var_pts(self): - var = pybamm.standard_spatial_vars - return {var.y: 32, var.z: 32} + return {"y": 32, "z": 32} @property def default_submesh_types(self): @@ -476,8 +475,8 @@ def default_geometry(self): var = pybamm.standard_spatial_vars geometry = { "current collector": { - var.y: {"min": 0, "max": param.l_y}, - var.z: {"min": 0, "max": param.l_z}, + "y": {"min": 0, "max": param.l_y}, + "z": {"min": 0, "max": param.l_z}, "tabs": { "negative": { "y_centre": param.centre_y_tab_n, @@ -496,8 +495,7 @@ def default_geometry(self): @property def default_var_pts(self): - var = pybamm.standard_spatial_vars - return {var.y: 32, var.z: 32} + return {"y": 32, "z": 32} @property def default_submesh_types(self): diff --git a/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_asymptotics_convergence.py b/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_asymptotics_convergence.py index 19b7bb3135..779606dece 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_asymptotics_convergence.py +++ b/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_asymptotics_convergence.py @@ -28,8 +28,7 @@ def test_leading_order_convergence(self): parameter_values.process_geometry(geometry) # Discretise (same mesh, create different discretisations) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 3, var.x_s: 3, var.x_p: 3} + var_pts = {"x_n": 3, "x_s": 3, "x_p": 3} mesh = pybamm.Mesh(geometry, full_model.default_submesh_types, var_pts) method_options = {"extrapolation": {"order": "linear", "use bcs": False}} diff --git a/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_compare_outputs.py b/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_compare_outputs.py index 430a0cc154..13f9cc3d89 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_compare_outputs.py +++ b/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_compare_outputs.py @@ -26,8 +26,7 @@ def test_compare_averages_asymptotics(self): param.process_model(model) # set mesh - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 10} + var_pts = {"x_n": 10, "x_s": 10, "x_p": 10} # discretise models for model in models: @@ -70,8 +69,7 @@ def test_compare_outputs_surface_form(self): param.process_model(model) # set mesh - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 5, var.x_s: 5, var.x_p: 5} + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5} # discretise models discs = {} diff --git a/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_composite.py b/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_composite.py index 8ca0247f48..cbcdfb076a 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_composite.py +++ b/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_composite.py @@ -42,8 +42,7 @@ def test_set_up(self): def test_basic_processing_1plus1D(self): options = {"current collector": "potential pair", "dimensionality": 1} model = pybamm.lead_acid.Composite(options) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 5, var.x_s: 5, var.x_p: 5, var.y: 5, var.z: 5} + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "y": 5, "z": 5} modeltest = tests.StandardModelTest(model, var_pts=var_pts) modeltest.test_all(skip_output_tests=True) diff --git a/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_full.py b/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_full.py index 5c4a4fdfb1..44f83b588f 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_full.py +++ b/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_full.py @@ -20,8 +20,7 @@ def test_basic_processing(self): def test_basic_processing_with_convection(self): options = {"thermal": "isothermal", "convection": "uniform transverse"} model = pybamm.lead_acid.Full(options) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 10} + var_pts = {"x_n": 10, "x_s": 10, "x_p": 10} modeltest = tests.StandardModelTest(model, var_pts=var_pts) modeltest.test_all(t_eval=np.linspace(0, 3600 * 10)) @@ -46,8 +45,7 @@ def test_set_up(self): def test_basic_processing_1plus1D(self): options = {"current collector": "potential pair", "dimensionality": 1} model = pybamm.lead_acid.Full(options) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 5, var.x_s: 5, var.x_p: 5, var.y: 5, var.z: 5} + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "y": 5, "z": 5} modeltest = tests.StandardModelTest(model, var_pts=var_pts) modeltest.test_all(skip_output_tests=True) diff --git a/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_loqs.py b/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_loqs.py index 56268c0eff..b28d9dc4bd 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_loqs.py +++ b/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_loqs.py @@ -63,8 +63,7 @@ def test_thermal(self): def test_basic_processing_1plus1D(self): options = {"current collector": "potential pair", "dimensionality": 1} model = pybamm.lead_acid.LOQS(options) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 5, var.x_s: 5, var.x_p: 5, var.y: 5, var.z: 5} + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "y": 5, "z": 5} modeltest = tests.StandardModelTest(model, var_pts=var_pts) modeltest.test_all(skip_output_tests=True) diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py index 71a5c6bd75..58159124fd 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py @@ -29,32 +29,14 @@ def test_sensitivities(self): def test_basic_processing_1plus1D(self): options = {"current collector": "potential pair", "dimensionality": 1} - var = pybamm.standard_spatial_vars - var_pts = { - var.x_n: 5, - var.x_s: 5, - var.x_p: 5, - var.r_n: 5, - var.r_p: 5, - var.y: 5, - var.z: 5, - } + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 5, "r_p": 5, "y": 5, "z": 5} model = self.model(options) modeltest = tests.StandardModelTest(model, var_pts=var_pts) modeltest.test_all(skip_output_tests=True) def test_basic_processing_2plus1D(self): options = {"current collector": "potential pair", "dimensionality": 2} - var = pybamm.standard_spatial_vars - var_pts = { - var.x_n: 5, - var.x_s: 5, - var.x_p: 5, - var.r_n: 5, - var.r_p: 5, - var.y: 5, - var.z: 5, - } + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 5, "r_p": 5, "y": 5, "z": 5} model = self.model(options) modeltest = tests.StandardModelTest(model, var_pts=var_pts) modeltest.test_all(skip_output_tests=True) diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_compare_outputs.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_compare_outputs.py index 7989c91833..85c3e2d604 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_compare_outputs.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_compare_outputs.py @@ -27,8 +27,7 @@ def test_compare_outputs_surface_form(self): param.process_model(model) # set mesh - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 5, var.x_s: 5, var.x_p: 5, var.r_n: 5, var.r_p: 5} + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 5, "r_p": 5} # discretise models discs = {} @@ -84,8 +83,7 @@ def test_compare_outputs_thermal(self): param.process_model(model) # set mesh - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 5, var.x_s: 5, var.x_p: 5, var.r_n: 5, var.r_p: 5} + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 5, "r_p": 5} # discretise models discs = {} @@ -119,8 +117,7 @@ def test_compare_particle_shape(self): ] # set same mesh for all models - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 5, var.x_s: 5, var.x_p: 5, var.r_n: 5, var.r_p: 5} + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 5, "r_p": 5} for model, param in zip(models, params): if model.name == "user": @@ -162,9 +159,7 @@ def test_compare_particle_shape(self): def test_compare_narrow_size_distribution(self): # The MPM should agree with the SPM when the size distributions are narrow # enough. - models = [ - pybamm.lithium_ion.SPM(), pybamm.lithium_ion.MPM() - ] + models = [pybamm.lithium_ion.SPM(), pybamm.lithium_ion.MPM()] param = models[0].default_parameter_values @@ -180,16 +175,7 @@ def test_compare_narrow_size_distribution(self): ) # set same mesh for both models - var = pybamm.standard_spatial_vars - var_pts = { - var.x_n: 5, - var.x_s: 5, - var.x_p: 5, - var.r_n: 5, - var.r_p: 5, - var.R_n: 5, - var.R_p: 5, - } + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 5, "r_p": 5, "R_n": 5, "R_p": 5} # solve models solutions = [] @@ -198,7 +184,7 @@ def test_compare_narrow_size_distribution(self): model, var_pts=var_pts, parameter_values=param, - solver=pybamm.CasadiSolver(mode="fast") + solver=pybamm.CasadiSolver(mode="fast"), ) solution = sim.solve([0, 3600]) solutions.append(solution) diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_dfn.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_dfn.py index affbfd6073..df47a3c7ec 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_dfn.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_dfn.py @@ -40,17 +40,16 @@ def setUp(self): params = pybamm.ParameterValues("Marquis2019") self.params = pybamm.get_size_distribution_parameters(params) - var = pybamm.standard_spatial_vars self.var_pts = { - var.x_n: 5, - var.x_s: 5, - var.x_p: 5, - var.r_n: 5, - var.r_p: 5, - var.R_n: 3, - var.R_p: 3, - var.y: 5, - var.z: 5, + "x_n": 5, + "x_s": 5, + "x_p": 5, + "r_n": 5, + "r_p": 5, + "R_n": 3, + "R_p": 3, + "y": 5, + "z": 5, } def test_basic_processing(self): @@ -91,13 +90,9 @@ def test_conservation_each_electrode(self): pybamm.lithium_ion.DFN(), pybamm.lithium_ion.DFN(options={"particle size": "distribution"}), ] - var = pybamm.standard_spatial_vars # reduce number of particle sizes, for a crude discretization - var_pts = { - var.R_n: 3, - var.R_p: 3, - } + var_pts = {"R_n": 3, "R_p": 3} solver = pybamm.CasadiSolver(mode="fast") # solve diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_mpm.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_mpm.py index 0756253b69..0f040924e4 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_mpm.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_mpm.py @@ -58,13 +58,9 @@ def test_conservation_each_electrode(self): # We test that the amount of lithium removed or added to each electrode # is the same as for the SPM with the same parameters models = [pybamm.lithium_ion.SPM(), pybamm.lithium_ion.MPM()] - var = pybamm.standard_spatial_vars # reduce number of particle sizes, for a crude discretization - var_pts = { - var.R_n: 3, - var.R_p: 3, - } + var_pts = {"R_n": 3, "R_p": 3} solver = pybamm.CasadiSolver(mode="fast") # solve diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_thermal_models.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_thermal_models.py index e80b9ecb57..8c249fad27 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_thermal_models.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_thermal_models.py @@ -34,16 +34,7 @@ def test_consistent_cooling(self): solutions = {} for model_name, model in models.items(): - var = pybamm.standard_spatial_vars - var_pts = { - var.x_n: 3, - var.x_s: 3, - var.x_p: 3, - var.r_n: 3, - var.r_p: 3, - var.y: 5, - var.z: 5, - } + var_pts = {"x_n": 3, "x_s": 3, "x_p": 3, "r_n": 3, "r_p": 3, "y": 5, "z": 5} chemistry = pybamm.parameter_sets.NCA_Kim2011 parameter_values = pybamm.ParameterValues(chemistry) diff --git a/tests/integration/test_models/test_submodels/test_external_circuit/test_function_control.py b/tests/integration/test_models/test_submodels/test_external_circuit/test_function_control.py index fa6cb7ed05..9454d6c738 100644 --- a/tests/integration/test_models/test_submodels/test_external_circuit/test_function_control.py +++ b/tests/integration/test_models/test_submodels/test_external_circuit/test_function_control.py @@ -70,8 +70,7 @@ def constant_voltage(variables): params[0].update({"Voltage function [V]": 4.08}, check_already_exists=False) # set parameters and discretise models - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 5, var.x_s: 5, var.x_p: 30, var.r_n: 10, var.r_p: 10} + var_pts = {"x_n": 5, "x_s": 5, "x_p": 30, "r_n": 10, "r_p": 10} for i, model in enumerate(models): # create geometry geometry = model.default_geometry diff --git a/tests/integration/test_solvers/test_external_variables.py b/tests/integration/test_solvers/test_external_variables.py index 270288c58c..98e842ac11 100644 --- a/tests/integration/test_solvers/test_external_variables.py +++ b/tests/integration/test_solvers/test_external_variables.py @@ -18,8 +18,7 @@ def test_on_dfn(self): param.process_model(model) param.process_geometry(geometry) inputs = {"Negative electrode conductivity [S.m-1]": e_height} - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 5, var.x_s: 5, var.x_p: 5, var.r_n: 10, var.r_p: 10} + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 10, "r_p": 10} spatial_methods = model.default_spatial_methods solver = pybamm.CasadiSolver() diff --git a/tests/integration/test_solvers/test_idaklu.py b/tests/integration/test_solvers/test_idaklu.py index 805c6ffbe1..78d078551e 100644 --- a/tests/integration/test_solvers/test_idaklu.py +++ b/tests/integration/test_solvers/test_idaklu.py @@ -20,7 +20,7 @@ def test_on_spme(self): np.testing.assert_array_less(1, solution.t.size) def test_on_spme_sensitivities(self): - param_name = 'Typical current [A]' + param_name = "Typical current [A]" param_value = 0.15652 model = pybamm.lithium_ion.SPMe() geometry = model.default_geometry @@ -35,7 +35,8 @@ def test_on_spme_sensitivities(self): t_eval = np.linspace(0, 3600, 100) solver = pybamm.IDAKLUSolver(rtol=1e-10, atol=1e-10) solution = solver.solve( - model, t_eval, + model, + t_eval, inputs=inputs, calculate_sensitivities=True, ) @@ -47,19 +48,19 @@ def test_on_spme_sensitivities(self): # evaluate the sensitivities using finite difference h = 1e-6 sol_plus = solver.solve( - model, t_eval, - inputs={param_name: param_value + 0.5 * h} + model, t_eval, inputs={param_name: param_value + 0.5 * h} ) sol_neg = solver.solve( - model, t_eval, - inputs={param_name: param_value - 0.5 * h} + model, t_eval, inputs={param_name: param_value - 0.5 * h} ) dyda_fd = (sol_plus.y - sol_neg.y) / h dyda_fd = dyda_fd.transpose().reshape(-1, 1) np.testing.assert_allclose( - dyda_ida, dyda_fd, - rtol=1e-2, atol=1e-3, + dyda_ida, + dyda_fd, + rtol=1e-2, + atol=1e-3, ) def test_set_tol_by_variable(self): @@ -92,13 +93,11 @@ def test_changing_grid(self): param.process_geometry(geometry) # Calculate time for each solver and each number of grid points - var = pybamm.standard_spatial_vars t_eval = np.linspace(0, 3600, 100) for npts in [100, 200]: # discretise var_pts = { - spatial_var: npts - for spatial_var in [var.x_n, var.x_s, var.x_p, var.r_n, var.r_p] + spatial_var: npts for spatial_var in ["x_n", "x_s", "x_p", "r_n", "r_p"] } mesh = pybamm.Mesh(geometry, model.default_submesh_types, var_pts) disc = pybamm.Discretisation(mesh, model.default_spatial_methods) diff --git a/tests/integration/test_solvers/test_solution.py b/tests/integration/test_solvers/test_solution.py index 1be3488680..b2442e8974 100644 --- a/tests/integration/test_solvers/test_solution.py +++ b/tests/integration/test_solvers/test_solution.py @@ -75,8 +75,7 @@ def test_append_external_variables(self): # solve model solver = model.default_solver - var = pybamm.standard_spatial_vars - Nr = model.default_var_pts[var.r_n] + Nr = model.default_var_pts["r_n"] T_av = 0 c_s_n_av = np.ones((Nr, 1)) * 0.6 diff --git a/tests/integration/test_spatial_methods/test_spectral_volume.py b/tests/integration/test_spatial_methods/test_spectral_volume.py index a8bc1e9e02..5424c00852 100644 --- a/tests/integration/test_spatial_methods/test_spectral_volume.py +++ b/tests/integration/test_spatial_methods/test_spectral_volume.py @@ -55,15 +55,14 @@ def get_mesh_for_testing( xn_pts, xs_pts, xp_pts = 40, 25, 35 else: xn_pts, xs_pts, xp_pts = xpts, xpts, xpts - var = pybamm.standard_spatial_vars var_pts = { - var.x_n: xn_pts, - var.x_s: xs_pts, - var.x_p: xp_pts, - var.r_n: rpts, - var.r_p: rpts, - var.y: ypts, - var.z: zpts, + "x_n": xn_pts, + "x_s": xs_pts, + "x_p": xp_pts, + "r_n": rpts, + "r_p": rpts, + "y": ypts, + "z": zpts, } return pybamm.Mesh(geometry, submesh_types, var_pts) diff --git a/tests/shared.py b/tests/shared.py index b4efb8f9df..8dc9688b7b 100644 --- a/tests/shared.py +++ b/tests/shared.py @@ -87,17 +87,16 @@ def get_mesh_for_testing( xn_pts, xs_pts, xp_pts = 40, 25, 35 else: xn_pts, xs_pts, xp_pts = xpts, xpts, xpts - var = pybamm.standard_spatial_vars var_pts = { - var.x_n: xn_pts, - var.x_s: xs_pts, - var.x_p: xp_pts, - var.r_n: rpts, - var.r_p: rpts, - var.y: ypts, - var.z: zpts, - var.R_n: Rpts, - var.R_p: Rpts, + "x_n": xn_pts, + "x_s": xs_pts, + "x_p": xp_pts, + "r_n": rpts, + "r_p": rpts, + "y": ypts, + "z": zpts, + "R_n": Rpts, + "R_p": Rpts, } return pybamm.Mesh(geometry, submesh_types, var_pts) @@ -123,7 +122,7 @@ def get_size_distribution_mesh_for_testing( Rpts=Rpts, zpts=zpts, geometry=geometry, - cc_submesh=cc_submesh + cc_submesh=cc_submesh, ) @@ -182,8 +181,7 @@ def get_unit_2p1D_mesh_for_testing(ypts=15, zpts=15, include_particles=True): ) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 3, var.x_s: 3, var.x_p: 3, var.y: ypts, var.z: zpts} + var_pts = {"x_n": 3, "x_s": 3, "x_p": 3, "y": ypts, "z": zpts} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), diff --git a/tests/unit/test_geometry/test_battery_geometry.py b/tests/unit/test_geometry/test_battery_geometry.py index 0243e00ccc..53abeb2f0d 100644 --- a/tests/unit/test_geometry/test_battery_geometry.py +++ b/tests/unit/test_geometry/test_battery_geometry.py @@ -10,7 +10,7 @@ def test_geometry_keys(self): for cc_dimension in [0, 1, 2]: geometry = pybamm.battery_geometry( options={"particle size": "distribution"}, - current_collector_dimension=cc_dimension + current_collector_dimension=cc_dimension, ) for domain_geoms in geometry.values(): all( @@ -20,20 +20,19 @@ def test_geometry_keys(self): geometry.print_parameter_info() def test_geometry(self): - var = pybamm.standard_spatial_vars geo = pybamm.geometric_parameters for cc_dimension in [0, 1, 2]: geometry = pybamm.battery_geometry( options={"particle size": "distribution"}, - current_collector_dimension=cc_dimension + current_collector_dimension=cc_dimension, ) self.assertIsInstance(geometry, pybamm.Geometry) self.assertIn("negative electrode", geometry) self.assertIn("negative particle", geometry) self.assertIn("negative particle size", geometry) - self.assertEqual(geometry["negative electrode"][var.x_n]["min"], 0) + self.assertEqual(geometry["negative electrode"]["x_n"]["min"], 0) self.assertEqual( - geometry["negative electrode"][var.x_n]["max"].id, geo.l_n.id + geometry["negative electrode"]["x_n"]["max"].id, geo.l_n.id ) if cc_dimension == 1: self.assertIn("tabs", geometry["current collector"]) diff --git a/tests/unit/test_meshes/test_meshes.py b/tests/unit/test_meshes/test_meshes.py index ff71555293..086aa4dd6b 100644 --- a/tests/unit/test_meshes/test_meshes.py +++ b/tests/unit/test_meshes/test_meshes.py @@ -58,8 +58,7 @@ def test_mesh_creation(self): geometry = pybamm.battery_geometry() param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 12, var.r_n: 5, var.r_p: 6} + var_pts = {"x_n": 10, "x_s": 10, "x_p": 12, "r_n": 5, "r_p": 6} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -101,8 +100,7 @@ def test_init_failure(self): with self.assertRaisesRegex(KeyError, "Points not given"): pybamm.Mesh(geometry, submesh_types, {}) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 12} + var_pts = {"x_n": 10, "x_s": 10, "x_p": 12} geometry = pybamm.battery_geometry(current_collector_dimension=1) with self.assertRaisesRegex(KeyError, "Points not given"): pybamm.Mesh(geometry, submesh_types, var_pts) @@ -110,8 +108,7 @@ def test_init_failure(self): # Not processing geometry parameters geometry = pybamm.battery_geometry() - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 12, var.r_n: 5, var.r_p: 6} + var_pts = {"x_n": 10, "x_s": 10, "x_p": 12, "r_n": 5, "r_p": 6} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -126,9 +123,8 @@ def test_init_failure(self): pybamm.Mesh(geometry, submesh_types, var_pts) # Geometry has an unrecognized variable type - var = pybamm.standard_spatial_vars geometry["negative electrode"] = { - var.x_n: {"min": 0, "max": pybamm.Variable("var")} + "x_n": {"min": 0, "max": pybamm.Variable("var")} } with self.assertRaisesRegex(NotImplementedError, "for symbol var"): pybamm.Mesh(geometry, submesh_types, var_pts) @@ -146,8 +142,7 @@ def test_mesh_sizes(self): param.process_geometry(geometry) # provide mesh properties - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 12, var.r_n: 5, var.r_p: 6} + var_pts = {"x_n": 10, "x_s": 10, "x_p": 12, "r_n": 5, "r_p": 6} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -160,20 +155,49 @@ def test_mesh_sizes(self): # create mesh mesh = pybamm.Mesh(geometry, submesh_types, var_pts) - var_id_pts = {var.id: pts for var, pts in var_pts.items()} + self.assertEqual(mesh["negative electrode"].npts, var_pts["x_n"]) + self.assertEqual(mesh["separator"].npts, var_pts["x_s"]) + self.assertEqual(mesh["positive electrode"].npts, var_pts["x_p"]) - self.assertEqual(mesh["negative electrode"].npts, var_id_pts[var.x_n.id]) - self.assertEqual(mesh["separator"].npts, var_id_pts[var.x_s.id]) - self.assertEqual(mesh["positive electrode"].npts, var_id_pts[var.x_p.id]) + self.assertEqual(len(mesh["negative electrode"].edges) - 1, var_pts["x_n"]) + self.assertEqual(len(mesh["separator"].edges) - 1, var_pts["x_s"]) + self.assertEqual(len(mesh["positive electrode"].edges) - 1, var_pts["x_p"]) - self.assertEqual( - len(mesh["negative electrode"].edges) - 1, var_id_pts[var.x_n.id] - ) - self.assertEqual(len(mesh["separator"].edges) - 1, var_id_pts[var.x_s.id]) - self.assertEqual( - len(mesh["positive electrode"].edges) - 1, var_id_pts[var.x_p.id] + def test_mesh_sizes_using_standard_spatial_vars(self): + param = pybamm.ParameterValues( + values={ + "Negative electrode thickness [m]": 0.1, + "Separator thickness [m]": 0.2, + "Positive electrode thickness [m]": 0.3, + } ) + geometry = pybamm.battery_geometry() + param.process_geometry(geometry) + + # provide mesh properties + var = pybamm.standard_spatial_vars + var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 12, var.r_n: 5, var.r_p: 6} + submesh_types = { + "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "positive particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), + } + + # create mesh + mesh = pybamm.Mesh(geometry, submesh_types, var_pts) + + self.assertEqual(mesh["negative electrode"].npts, var_pts[var.x_n]) + self.assertEqual(mesh["separator"].npts, var_pts[var.x_s]) + self.assertEqual(mesh["positive electrode"].npts, var_pts[var.x_p]) + + self.assertEqual(len(mesh["negative electrode"].edges) - 1, var_pts[var.x_n]) + self.assertEqual(len(mesh["separator"].edges) - 1, var_pts[var.x_s]) + self.assertEqual(len(mesh["positive electrode"].edges) - 1, var_pts[var.x_p]) + def test_combine_submeshes(self): param = pybamm.ParameterValues( values={ @@ -187,8 +211,7 @@ def test_combine_submeshes(self): param.process_geometry(geometry) # provide mesh properties - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 12, var.r_n: 5, var.r_p: 6} + var_pts = {"x_n": 10, "x_s": 10, "x_p": 12, "r_n": 5, "r_p": 6} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -218,8 +241,8 @@ def test_combine_submeshes(self): # test errors geometry = { - "negative electrode": {var.x_n: {"min": 0, "max": 0.5}}, - "negative particle": {var.r_n: {"min": 0.5, "max": 1}}, + "negative electrode": {"x_n": {"min": 0, "max": 0.5}}, + "negative particle": {"r_n": {"min": 0.5, "max": 1}}, } param.process_geometry(geometry) @@ -246,8 +269,7 @@ def test_ghost_cells(self): param.process_geometry(geometry) # provide mesh properties - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 12, var.r_n: 5, var.r_p: 6} + var_pts = {"x_n": 10, "x_s": 10, "x_p": 12, "r_n": 5, "r_p": 6} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -285,8 +307,7 @@ def test_mesh_coord_sys(self): geometry = pybamm.battery_geometry() param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 12, var.r_n: 5, var.r_p: 6} + var_pts = {"x_n": 10, "x_s": 10, "x_p": 12, "r_n": 5, "r_p": 6} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -305,12 +326,11 @@ def test_mesh_coord_sys(self): self.assertTrue(submesh.coord_sys in pybamm.KNOWN_COORD_SYS) def test_unimplemented_meshes(self): - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.y: 10} + var_pts = {"x_n": 10, "y": 10} geometry = { "negative electrode": { - var.x_n: {"min": 0, "max": 1}, - var.y: {"min": 0, "max": 1}, + "x_n": {"min": 0, "max": 1}, + "y": {"min": 0, "max": 1}, } } submesh_types = { @@ -337,8 +357,7 @@ def test_1plus1D_tabs_left_right(self): ) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 7, var.x_p: 12, var.z: 24} + var_pts = {"x_n": 10, "x_s": 7, "x_p": 12, "z": 24} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -374,8 +393,7 @@ def test_1plus1D_tabs_right_left(self): ) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 7, var.x_p: 12, var.z: 24} + var_pts = {"x_n": 10, "x_s": 7, "x_p": 12, "z": 24} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), diff --git a/tests/unit/test_meshes/test_scikit_fem_submesh.py b/tests/unit/test_meshes/test_scikit_fem_submesh.py index 207016bf1c..86e0fc1521 100644 --- a/tests/unit/test_meshes/test_scikit_fem_submesh.py +++ b/tests/unit/test_meshes/test_scikit_fem_submesh.py @@ -29,8 +29,7 @@ def test_mesh_creation(self): ) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 7, var.x_p: 12, var.y: 16, var.z: 24} + var_pts = {"x_n": 10, "x_s": 7, "x_p": 12, "y": 16, "z": 24} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -74,8 +73,7 @@ def test_init_failure(self): with self.assertRaises(KeyError): pybamm.Mesh(geometry, submesh_types, {}) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 10, var.y: 10, var.z: 10} + var_pts = {"x_n": 10, "x_s": 10, "x_p": 10, "y": 10, "z": 10} # there are parameters in the variables that need to be processed with self.assertRaisesRegex( pybamm.DiscretisationError, @@ -83,20 +81,20 @@ def test_init_failure(self): ): pybamm.Mesh(geometry, submesh_types, var_pts) - lims = {var.x_n: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}} + lims = {"x_n": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}} with self.assertRaises(pybamm.GeometryError): pybamm.ScikitUniform2DSubMesh(lims, None) lims = { - var.x_n: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, - var.x_p: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + "x_n": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + "x_p": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, } with self.assertRaises(pybamm.DomainError): pybamm.ScikitUniform2DSubMesh(lims, None) lims = { - var.y: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, - var.z: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + "y": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + "z": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, } npts = {var.y.id: 10, var.z.id: 10} var.z.coord_sys = "not cartesian" @@ -106,8 +104,7 @@ def test_init_failure(self): def test_tab_error(self): # set variables and submesh types - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 2, var.x_s: 2, var.x_p: 2, var.y: 64, var.z: 64} + var_pts = {"x_n": 2, "x_s": 2, "x_p": 2, "y": 64, "z": 64} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -143,8 +140,7 @@ def test_tab_error(self): def test_tab_left_right(self): # set variables and submesh types - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 2, var.x_s: 2, var.x_p: 2, var.y: 64, var.z: 64} + var_pts = {"x_n": 2, "x_s": 2, "x_p": 2, "y": 64, "z": 64} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -201,8 +197,7 @@ def test_mesh_creation(self): ) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 7, var.x_p: 12, var.y: 16, var.z: 24} + var_pts = {"x_n": 10, "x_s": 7, "x_p": 12, "y": 16, "z": 24} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -234,25 +229,24 @@ def test_mesh_creation(self): self.assertEqual(len(mesh[domain].edges), len(mesh[domain].nodes) + 1) def test_init_failure(self): - var = pybamm.standard_spatial_vars # only one lim - lims = {var.x_n: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}} + lims = {"x_n": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}} with self.assertRaises(pybamm.GeometryError): pybamm.ScikitChebyshev2DSubMesh(lims, None) # different coord_sys lims = { - var.r_n: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, - var.z: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + "r_n": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + "z": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, } with self.assertRaises(pybamm.DomainError): pybamm.ScikitChebyshev2DSubMesh(lims, None) # not y and z lims = { - var.x_n: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, - var.z: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + "x_n": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + "z": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, } with self.assertRaises(pybamm.DomainError): pybamm.ScikitChebyshev2DSubMesh(lims, None) @@ -281,8 +275,7 @@ def test_mesh_creation(self): ) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 7, var.x_p: 12, var.y: 16, var.z: 24} + var_pts = {"x_n": 10, "x_s": 7, "x_p": 12, "y": 16, "z": 24} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -316,25 +309,24 @@ def test_mesh_creation(self): self.assertEqual(len(mesh[domain].edges), len(mesh[domain].nodes) + 1) def test_init_failure(self): - var = pybamm.standard_spatial_vars # only one lim - lims = {var.x_n: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}} + lims = {"x_n": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}} with self.assertRaises(pybamm.GeometryError): pybamm.ScikitExponential2DSubMesh(lims, None) # different coord_sys lims = { - var.r_n: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, - var.z: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + "r_n": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + "z": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, } with self.assertRaises(pybamm.DomainError): pybamm.ScikitExponential2DSubMesh(lims, None) # not y and z lims = { - var.x_n: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, - var.z: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + "x_n": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + "z": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, } with self.assertRaises(pybamm.DomainError): pybamm.ScikitExponential2DSubMesh(lims, None) @@ -367,8 +359,7 @@ def test_mesh_creation(self): ) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 10, var.x_s: 7, var.x_p: 12, var.y: 16, var.z: 24} + var_pts = {"x_n": 10, "x_s": 7, "x_p": 12, "y": 16, "z": 24} y_edges = np.linspace(0, 0.8, 16) z_edges = np.linspace(0, 1, 24) @@ -406,8 +397,7 @@ def test_mesh_creation(self): self.assertEqual(len(mesh[domain].edges), len(mesh[domain].nodes) + 1) def test_exceptions(self): - var = pybamm.standard_spatial_vars - lims = {var.y: {"min": 0, "max": 1}} + lims = {"y": {"min": 0, "max": 1}} y_edges = np.array([0, 0.3, 1]) z_edges = np.array([0, 0.3, 1]) submesh_params = {"y_edges": y_edges, "z_edges": z_edges} @@ -415,7 +405,7 @@ def test_exceptions(self): # test not enough lims with self.assertRaises(pybamm.GeometryError): mesh(lims, None) - lims = {var.y: {"min": 0, "max": 1}, var.z: {"min": 0, "max": 1}} + lims = {"y": {"min": 0, "max": 1}, "z": {"min": 0, "max": 1}} # error if len(edges) != npts npts = {var.y.id: 10, var.z.id: 3} @@ -423,19 +413,19 @@ def test_exceptions(self): mesh(lims, npts) # error if lims[0] not equal to edges[0] - lims = {var.y: {"min": 0.1, "max": 1}, var.z: {"min": 0, "max": 1}} + lims = {"y": {"min": 0.1, "max": 1}, "z": {"min": 0, "max": 1}} npts = {var.y.id: 3, var.z.id: 3} with self.assertRaises(pybamm.GeometryError): mesh(lims, npts) # error if lims[-1] not equal to edges[-1] - lims = {var.y: {"min": 0, "max": 1}, var.z: {"min": 0, "max": 1.3}} + lims = {"y": {"min": 0, "max": 1}, "z": {"min": 0, "max": 1.3}} npts = {var.y.id: 3, var.z.id: 3} with self.assertRaises(pybamm.GeometryError): mesh(lims, npts) # error if different coordinate system - lims = {var.y: {"min": 0, "max": 1}, var.r_n: {"min": 0, "max": 1}} + lims = {"y": {"min": 0, "max": 1}, "r_n": {"min": 0, "max": 1}} npts = {var.y.id: 3, var.r_n.id: 3} with self.assertRaises(pybamm.DomainError): mesh(lims, npts) diff --git a/tests/unit/test_models/test_base_model.py b/tests/unit/test_models/test_base_model.py index 3b9a4fac0d..aadf02598f 100644 --- a/tests/unit/test_models/test_base_model.py +++ b/tests/unit/test_models/test_base_model.py @@ -647,18 +647,17 @@ def test_set_initial_conditions(self): self.assertEqual(model.initial_conditions[var_concat].value, 1) # Discretise - var = pybamm.standard_spatial_vars geometry = { - "negative electrode": {var.x_n: {"min": 0, "max": 1}}, - "separator": {var.x_s: {"min": 1, "max": 2}}, - "negative particle": {var.r_n: {"min": 0, "max": 1}}, + "negative electrode": {"x_n": {"min": 0, "max": 1}}, + "separator": {"x_s": {"min": 1, "max": 2}}, + "negative particle": {"r_n": {"min": 0, "max": 1}}, } submeshes = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), } - var_pts = {var.x_n: 10, var.x_s: 10, var.r_n: 5} + var_pts = {"x_n": 10, "x_s": 10, "r_n": 5} mesh = pybamm.Mesh(geometry, submeshes, var_pts) spatial_methods = { "negative electrode": pybamm.FiniteVolume(), diff --git a/tests/unit/test_models/test_full_battery_models/test_base_battery_model.py b/tests/unit/test_models/test_full_battery_models/test_base_battery_model.py index b3a84d5f93..210532a035 100644 --- a/tests/unit/test_models/test_full_battery_models/test_base_battery_model.py +++ b/tests/unit/test_models/test_full_battery_models/test_base_battery_model.py @@ -85,7 +85,6 @@ def test_summary_variables(self): model.summary_variables = ["bad var"] def test_default_geometry(self): - var = pybamm.standard_spatial_vars model = pybamm.BaseBatteryModel({"dimensionality": 0}) self.assertEqual( @@ -120,22 +119,21 @@ def test_default_submesh_types(self): ) def test_default_var_pts(self): - var = pybamm.standard_spatial_vars var_pts = { - var.x_n: 20, - var.x_s: 20, - var.x_p: 20, - var.r_n: 20, - var.r_p: 20, - var.y: 10, - var.z: 10, - var.R_n: 30, - var.R_p: 30, + "x_n": 20, + "x_s": 20, + "x_p": 20, + "r_n": 20, + "r_p": 20, + "y": 10, + "z": 10, + "R_n": 30, + "R_p": 30, } model = pybamm.BaseBatteryModel({"dimensionality": 0}) self.assertDictEqual(var_pts, model.default_var_pts) - var_pts.update({var.x_n: 10, var.x_s: 10, var.x_p: 10}) + var_pts.update({"x_n": 10, "x_s": 10, "x_p": 10}) model = pybamm.BaseBatteryModel({"dimensionality": 2}) self.assertDictEqual(var_pts, model.default_var_pts) diff --git a/tests/unit/test_models/test_full_battery_models/test_lead_acid/test_base_lead_acid_model.py b/tests/unit/test_models/test_full_battery_models/test_lead_acid/test_base_lead_acid_model.py index 1ec8763262..421fb07580 100644 --- a/tests/unit/test_models/test_full_battery_models/test_lead_acid/test_base_lead_acid_model.py +++ b/tests/unit/test_models/test_full_battery_models/test_lead_acid/test_base_lead_acid_model.py @@ -7,16 +7,14 @@ class TestBaseLeadAcidModel(unittest.TestCase): def test_default_geometry(self): - var = pybamm.standard_spatial_vars - model = pybamm.lead_acid.BaseModel({"dimensionality": 0}) self.assertEqual( - model.default_geometry["current collector"][var.z]["position"], 1 + model.default_geometry["current collector"]["z"]["position"], 1 ) model = pybamm.lead_acid.BaseModel({"dimensionality": 1}) - self.assertEqual(model.default_geometry["current collector"][var.z]["min"], 0) + self.assertEqual(model.default_geometry["current collector"]["z"]["min"], 0) model = pybamm.lead_acid.BaseModel({"dimensionality": 2}) - self.assertEqual(model.default_geometry["current collector"][var.y]["min"], 0) + self.assertEqual(model.default_geometry["current collector"]["y"]["min"], 0) def test_incompatible_options(self): with self.assertRaisesRegex( diff --git a/tests/unit/test_models/test_submodels/test_current_collector/test_effective_current_collector.py b/tests/unit/test_models/test_submodels/test_current_collector/test_effective_current_collector.py index 6af89f4369..90460719fb 100644 --- a/tests/unit/test_models/test_submodels/test_current_collector/test_effective_current_collector.py +++ b/tests/unit/test_models/test_submodels/test_current_collector/test_effective_current_collector.py @@ -44,16 +44,7 @@ def test_get_processed_variables(self): pybamm.current_collector.EffectiveResistance({"dimensionality": 2}), pybamm.current_collector.AlternativeEffectiveResistance2D(), ] - var = pybamm.standard_spatial_vars - var_pts = { - var.x_n: 5, - var.x_s: 5, - var.x_p: 5, - var.r_n: 5, - var.r_p: 5, - var.y: 5, - var.z: 5, - } + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 5, "r_p": 5, "y": 5, "z": 5} param = models[0].default_parameter_values meshes = [None] * len(models) for i, model in enumerate(models): diff --git a/tests/unit/test_plotting/test_quick_plot.py b/tests/unit/test_plotting/test_quick_plot.py index ce939f384f..3c116c20a8 100644 --- a/tests/unit/test_plotting/test_quick_plot.py +++ b/tests/unit/test_plotting/test_quick_plot.py @@ -310,8 +310,7 @@ def test_loqs_spme(self): param = model.default_parameter_values param.process_model(model) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 5, var.x_s: 5, var.x_p: 5, var.r_n: 5, var.r_p: 5} + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 5, "r_p": 5} mesh = pybamm.Mesh(geometry, model.default_submesh_types, var_pts) disc = pybamm.Discretisation(mesh, model.default_spatial_methods) disc.process_model(model) @@ -391,8 +390,7 @@ def test_plot_1plus1D_spme(self): param = spm.default_parameter_values param.process_model(spm) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 5, var.x_s: 5, var.x_p: 5, var.r_n: 5, var.r_p: 5, var.z: 5} + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 5, "r_p": 5, "z": 5} mesh = pybamm.Mesh(geometry, spm.default_submesh_types, var_pts) disc_spm = pybamm.Discretisation(mesh, spm.default_spatial_methods) disc_spm.process_model(spm) @@ -426,16 +424,7 @@ def test_plot_2plus1D_spm(self): param = spm.default_parameter_values param.process_model(spm) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = { - var.x_n: 5, - var.x_s: 5, - var.x_p: 5, - var.r_n: 5, - var.r_p: 5, - var.y: 5, - var.z: 5, - } + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 5, "r_p": 5, "y": 5, "z": 5} mesh = pybamm.Mesh(geometry, spm.default_submesh_types, var_pts) disc_spm = pybamm.Discretisation(mesh, spm.default_spatial_methods) disc_spm.process_model(spm) diff --git a/tests/unit/test_simulation.py b/tests/unit/test_simulation.py index d2c9a3e61a..59a5361f8a 100644 --- a/tests/unit/test_simulation.py +++ b/tests/unit/test_simulation.py @@ -157,8 +157,7 @@ def test_set_external_variable(self): model = pybamm.lithium_ion.SPMe(model_options) sim = pybamm.Simulation(model) - var = pybamm.standard_spatial_vars - Nr = model.default_var_pts[var.r_n] + Nr = model.default_var_pts["r_n"] T_av = 0 c_s_n_av = np.ones((Nr, 1)) * 0.5 diff --git a/tests/unit/test_solvers/test_solution.py b/tests/unit/test_solvers/test_solution.py index 3edf888f2f..7298de45e6 100644 --- a/tests/unit/test_solvers/test_solution.py +++ b/tests/unit/test_solvers/test_solution.py @@ -291,8 +291,7 @@ def test_solution_evals_with_inputs(self): param.update({"Negative electrode conductivity [S.m-1]": "[input]"}) param.process_model(model) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 5, var.x_s: 5, var.x_p: 5, var.r_n: 10, var.r_p: 10} + var_pts = {"x_n": 5, "x_s": 5, "x_p": 5, "r_n": 10, "r_p": 10} spatial_methods = model.default_spatial_methods solver = model.default_solver sim = pybamm.Simulation( diff --git a/tests/unit/test_spatial_methods/test_finite_volume/test_extrapolation.py b/tests/unit/test_spatial_methods/test_finite_volume/test_extrapolation.py index e3390e562c..2135b57592 100644 --- a/tests/unit/test_spatial_methods/test_finite_volume/test_extrapolation.py +++ b/tests/unit/test_spatial_methods/test_finite_volume/test_extrapolation.py @@ -387,10 +387,9 @@ def test_quadratic_extrapolate_left_right(self): ) def test_extrapolate_on_nonuniform_grid(self): - var = pybamm.standard_spatial_vars geometry = { - "negative particle": {var.r_n: {"min": 0, "max": 1}}, - "positive particle": {var.r_p: {"min": 0, "max": 1}}, + "negative particle": {"r_n": {"min": 0, "max": 1}}, + "positive particle": {"r_p": {"min": 0, "max": 1}}, } submesh_types = { @@ -399,7 +398,7 @@ def test_extrapolate_on_nonuniform_grid(self): } rpts = 10 - var_pts = {var.r_n: rpts, var.r_p: rpts} + var_pts = {"r_n": rpts, "r_p": rpts} mesh = pybamm.Mesh(geometry, submesh_types, var_pts) method_options = {"extrapolation": {"order": "linear", "use bcs": False}} spatial_methods = {"negative particle": pybamm.FiniteVolume(method_options)} diff --git a/tests/unit/test_spatial_methods/test_scikit_finite_element.py b/tests/unit/test_spatial_methods/test_scikit_finite_element.py index f0300468f9..06d028c931 100644 --- a/tests/unit/test_spatial_methods/test_scikit_finite_element.py +++ b/tests/unit/test_spatial_methods/test_scikit_finite_element.py @@ -252,8 +252,7 @@ def test_manufactured_solution_cheb_grid(self): ) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 3, var.x_s: 3, var.x_p: 3, var.y: 32, var.z: 32} + var_pts = {"x_n": 3, "x_s": 3, "x_p": 3, "y": 32, "z": 32} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), @@ -314,8 +313,7 @@ def test_manufactured_solution_exponential_grid(self): ) param.process_geometry(geometry) - var = pybamm.standard_spatial_vars - var_pts = {var.x_n: 3, var.x_s: 3, var.x_p: 3, var.y: 32, var.z: 32} + var_pts = {"x_n": 3, "x_s": 3, "x_p": 3, "y": 32, "z": 32} submesh_types = { "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), diff --git a/tests/unit/test_spatial_methods/test_spectral_volume.py b/tests/unit/test_spatial_methods/test_spectral_volume.py index a8ecefc03d..b8d31fc2bd 100644 --- a/tests/unit/test_spatial_methods/test_spectral_volume.py +++ b/tests/unit/test_spatial_methods/test_spectral_volume.py @@ -55,15 +55,14 @@ def get_mesh_for_testing( xn_pts, xs_pts, xp_pts = 40, 25, 35 else: xn_pts, xs_pts, xp_pts = xpts, xpts, xpts - var = pybamm.standard_spatial_vars var_pts = { - var.x_n: xn_pts, - var.x_s: xs_pts, - var.x_p: xp_pts, - var.r_n: rpts, - var.r_p: rpts, - var.y: ypts, - var.z: zpts, + "x_n": xn_pts, + "x_s": xs_pts, + "x_p": xp_pts, + "r_n": rpts, + "r_p": rpts, + "y": ypts, + "z": zpts, } return pybamm.Mesh(geometry, submesh_types, var_pts) From 9434eb9a4ad40bfa325b571f48c5c6add2173cab Mon Sep 17 00:00:00 2001 From: Valentin Sulzer Date: Fri, 19 Nov 2021 11:56:46 -0500 Subject: [PATCH 3/8] #1810 remove MeshGenerator and fix tests --- .../Creating Models/2-a-pde-model.ipynb | 2 +- .../3-negative-particle-problem.ipynb | 2 +- ...paring-full-and-reduced-order-models.ipynb | 2 +- .../Creating Models/5-half-cell-model.ipynb | 6 +- .../parameterization/parameterization.ipynb | 2 +- examples/scripts/SPM_compare_particle_grid.py | 4 +- pybamm/meshes/one_dimensional_submeshes.py | 14 +- pybamm/meshes/scikit_fem_submeshes.py | 34 ++--- .../full_battery_models/base_battery_model.py | 25 ++-- .../effective_resistance_current_collector.py | 4 +- .../test_spectral_volume.py | 2 +- tests/shared.py | 26 ++-- .../test_discretisation.py | 10 +- .../test_geometry/test_battery_geometry.py | 2 +- tests/unit/test_meshes/test_meshes.py | 120 +++++++++--------- .../test_one_dimensional_submesh.py | 36 ++---- .../test_meshes/test_scikit_fem_submesh.py | 67 +++++----- .../test_zero_dimensional_submesh.py | 2 +- tests/unit/test_models/test_base_model.py | 6 +- .../test_base_battery_model.py | 12 +- .../test_lead_acid/test_loqs.py | 6 +- .../test_parameters/test_parameter_values.py | 18 +-- tests/unit/test_simulation.py | 8 +- .../test_processed_symbolic_variable.py | 2 +- .../test_finite_volume/test_extrapolation.py | 2 +- .../test_scikit_finite_element.py | 12 +- .../test_spectral_volume.py | 4 +- 27 files changed, 204 insertions(+), 226 deletions(-) diff --git a/examples/notebooks/Creating Models/2-a-pde-model.ipynb b/examples/notebooks/Creating Models/2-a-pde-model.ipynb index aac4530852..0096893cd5 100644 --- a/examples/notebooks/Creating Models/2-a-pde-model.ipynb +++ b/examples/notebooks/Creating Models/2-a-pde-model.ipynb @@ -186,7 +186,7 @@ "outputs": [], "source": [ "# mesh and discretise\n", - "submesh_types = {\"negative particle\": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh)}\n", + "submesh_types = {\"negative particle\": pybamm.Uniform1DSubMesh}\n", "var_pts = {r: 20}\n", "mesh = pybamm.Mesh(geometry, submesh_types, var_pts)" ] diff --git a/examples/notebooks/Creating Models/3-negative-particle-problem.ipynb b/examples/notebooks/Creating Models/3-negative-particle-problem.ipynb index 725d52a9e0..32042e4e16 100644 --- a/examples/notebooks/Creating Models/3-negative-particle-problem.ipynb +++ b/examples/notebooks/Creating Models/3-negative-particle-problem.ipynb @@ -226,7 +226,7 @@ "metadata": {}, "outputs": [], "source": [ - "submesh_types = {\"negative particle\": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh)}\n", + "submesh_types = {\"negative particle\": pybamm.Uniform1DSubMesh}\n", "var_pts = {r: 20}\n", "mesh = pybamm.Mesh(geometry, submesh_types, var_pts)\n", "\n", diff --git a/examples/notebooks/Creating Models/4-comparing-full-and-reduced-order-models.ipynb b/examples/notebooks/Creating Models/4-comparing-full-and-reduced-order-models.ipynb index 37dc71c7b1..818511084a 100644 --- a/examples/notebooks/Creating Models/4-comparing-full-and-reduced-order-models.ipynb +++ b/examples/notebooks/Creating Models/4-comparing-full-and-reduced-order-models.ipynb @@ -251,7 +251,7 @@ "outputs": [], "source": [ "# mesh\n", - "submesh_types = {\"negative particle\": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh)}\n", + "submesh_types = {\"negative particle\": pybamm.Uniform1DSubMesh}\n", "var_pts = {r: 20}\n", "mesh = pybamm.Mesh(geometry, submesh_types, var_pts)\n", "\n", diff --git a/examples/notebooks/Creating Models/5-half-cell-model.ipynb b/examples/notebooks/Creating Models/5-half-cell-model.ipynb index fc9c82a537..c88b69404a 100644 --- a/examples/notebooks/Creating Models/5-half-cell-model.ipynb +++ b/examples/notebooks/Creating Models/5-half-cell-model.ipynb @@ -475,9 +475,9 @@ "outputs": [], "source": [ "submesh_types = {\n", - " \"separator\": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh),\n", - " \"positive electrode\": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh),\n", - " \"positive particle\": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh),\n", + " \"separator\": pybamm.Uniform1DSubMesh,\n", + " \"positive electrode\": pybamm.Uniform1DSubMesh,\n", + " \"positive particle\": pybamm.Uniform1DSubMesh,\n", "}\n", "var_pts = {x_s: 10, x_p: 20, r: 30}\n", "mesh = pybamm.Mesh(geometry, submesh_types, var_pts)\n", diff --git a/examples/notebooks/parameterization/parameterization.ipynb b/examples/notebooks/parameterization/parameterization.ipynb index 3aa9beb4db..8fb6ca343c 100644 --- a/examples/notebooks/parameterization/parameterization.ipynb +++ b/examples/notebooks/parameterization/parameterization.ipynb @@ -327,7 +327,7 @@ "metadata": {}, "outputs": [], "source": [ - "submesh_types = {\"negative particle\": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh)}\n", + "submesh_types = {\"negative particle\": pybamm.Uniform1DSubMesh}\n", "var_pts = {r: 20}\n", "mesh = pybamm.Mesh(geometry, submesh_types, var_pts)\n", "\n", diff --git a/examples/scripts/SPM_compare_particle_grid.py b/examples/scripts/SPM_compare_particle_grid.py index 7c15fbdf87..44a6f84edb 100644 --- a/examples/scripts/SPM_compare_particle_grid.py +++ b/examples/scripts/SPM_compare_particle_grid.py @@ -31,8 +31,8 @@ # set mesh submesh_types = models[0].default_submesh_types particle_meshes = [ - pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - pybamm.MeshGenerator(pybamm.Chebyshev1DSubMesh), + pybamm.Uniform1DSubMesh, + pybamm.Chebyshev1DSubMesh, pybamm.MeshGenerator(pybamm.Exponential1DSubMesh, submesh_params={"side": "right"}), ] meshes = [None] * len(models) diff --git a/pybamm/meshes/one_dimensional_submeshes.py b/pybamm/meshes/one_dimensional_submeshes.py index 14f1de4bfc..095b5c7f9d 100644 --- a/pybamm/meshes/one_dimensional_submeshes.py +++ b/pybamm/meshes/one_dimensional_submeshes.py @@ -68,6 +68,10 @@ def read_lims(self, lims): raise pybamm.GeometryError("lims should only contain a single variable") ((spatial_var, spatial_lims),) = lims.items() + + if isinstance(spatial_var, str): + spatial_var = getattr(pybamm.standard_spatial_vars, spatial_var) + return spatial_var, spatial_lims, tabs @@ -90,8 +94,6 @@ class Uniform1DSubMesh(SubMesh1D): def __init__(self, lims, npts): spatial_var, spatial_lims, tabs = self.read_lims(lims) - if isinstance(spatial_var, str): - spatial_var = getattr(pybamm.standard_spatial_vars, spatial_var) npts = npts[spatial_var.name] edges = np.linspace(spatial_lims["min"], spatial_lims["max"], npts + 1) @@ -158,7 +160,7 @@ def __init__(self, lims, npts, side="symmetric", stretch=None): spatial_var, spatial_lims, tabs = self.read_lims(lims) a = spatial_lims["min"] b = spatial_lims["max"] - npts = npts[spatial_var.id] + npts = npts[spatial_var.name] coord_sys = spatial_var.coord_sys # Set stretch if not provided @@ -236,7 +238,7 @@ class Chebyshev1DSubMesh(SubMesh1D): def __init__(self, lims, npts, tabs=None): spatial_var, spatial_lims, tabs = self.read_lims(lims) - npts = npts[spatial_var.id] + npts = npts[spatial_var.name] # Create N Chebyshev nodes in the interval (a,b) N = npts - 1 @@ -279,7 +281,7 @@ def __init__(self, lims, npts, edges=None): raise pybamm.GeometryError("User mesh requires parameter 'edges'") spatial_var, spatial_lims, tabs = self.read_lims(lims) - npts = npts[spatial_var.id] + npts = npts[spatial_var.name] # check that npts + 1 equals number of user-supplied edges if (npts + 1) != len(edges): @@ -338,7 +340,7 @@ class SpectralVolume1DSubMesh(SubMesh1D): def __init__(self, lims, npts, edges=None, order=2): spatial_var, spatial_lims, tabs = self.read_lims(lims) - npts = npts[spatial_var.id] + npts = npts[spatial_var.name] # default: Spectral Volumes of equal size if edges is None: diff --git a/pybamm/meshes/scikit_fem_submeshes.py b/pybamm/meshes/scikit_fem_submeshes.py index df8e403dbf..8490018fd2 100644 --- a/pybamm/meshes/scikit_fem_submeshes.py +++ b/pybamm/meshes/scikit_fem_submeshes.py @@ -83,6 +83,10 @@ def read_lims(self, lims): # get spatial variables spatial_vars = list(lims.keys()) + for i, var in enumerate(spatial_vars): + if isinstance(var, str): + spatial_vars[i] = getattr(pybamm.standard_spatial_vars, var) + # check coordinate system agrees if spatial_vars[0].coord_sys != spatial_vars[1].coord_sys: raise pybamm.DomainError( @@ -172,7 +176,7 @@ def __init__(self, lims, npts): ) else: edges[var.name] = np.linspace( - lims[var]["min"], lims[var]["max"], npts[var.id] + lims[var.name]["min"], lims[var.name]["max"], npts[var.name] ) super().__init__(edges, coord_sys, tabs) @@ -233,14 +237,14 @@ def __init__(self, lims, npts, side="top", stretch=2.3): ) elif var.name == "y": edges[var.name] = np.linspace( - lims[var]["min"], lims[var]["max"], npts[var.id] + lims[var.name]["min"], lims[var.name]["max"], npts[var.name] ) elif var.name == "z": - ii = np.array(range(0, npts[var.id])) - a = lims[var]["min"] - b = lims[var]["max"] + ii = np.array(range(0, npts[var.name])) + a = lims[var.name]["min"] + b = lims[var.name]["max"] edges[var.name] = (b - a) * ( - np.exp(-stretch * ii / (npts[var.id] - 1)) - 1 + np.exp(-stretch * ii / (npts[var.name] - 1)) - 1 ) / (np.exp(-stretch) - 1) + a super().__init__(edges, coord_sys, tabs) @@ -289,10 +293,10 @@ def __init__(self, lims, npts): ) else: # Create N Chebyshev nodes in the interval (a,b) - N = npts[var.id] - 2 + N = npts[var.name] - 2 ii = np.array(range(1, N + 1)) - a = lims[var]["min"] - b = lims[var]["max"] + a = lims[var.name]["min"] + b = lims[var.name]["max"] x_cheb = (a + b) / 2 + (b - a) / 2 * np.cos( (2 * ii - 1) * np.pi / 2 / N ) @@ -344,28 +348,28 @@ def __init__(self, lims, npts, y_edges=None, z_edges=None): for var in spatial_vars: # check that npts equals number of user-supplied edges - if npts[var.id] != len(edges[var.name]): + if npts[var.name] != len(edges[var.name]): raise pybamm.GeometryError( """User-suppled edges has should have length npts but has length {}. Number of points (npts) for variable {} in domain {} is {}.""".format( - len(edges[var.name]), var.name, var.domain, npts[var.id] + len(edges[var.name]), var.name, var.domain, npts[var.name] ) ) # check end points of edges agree with spatial_lims - if edges[var.name][0] != lims[var]["min"]: + if edges[var.name][0] != lims[var.name]["min"]: raise pybamm.GeometryError( """First entry of edges is {}, but should be equal to {} for variable {} in domain {}.""".format( - edges[var.name][0], lims[var]["min"], var.name, var.domain + edges[var.name][0], lims[var.name]["min"], var.name, var.domain ) ) - if edges[var.name][-1] != lims[var]["max"]: + if edges[var.name][-1] != lims[var.name]["max"]: raise pybamm.GeometryError( """Last entry of edges is {}, but should be equal to {} for variable {} in domain {}.""".format( - edges[var.name][-1], lims[var]["max"], var.name, var.domain + edges[var.name][-1], lims[var.name]["max"], var.name, var.domain ) ) diff --git a/pybamm/models/full_battery_models/base_battery_model.py b/pybamm/models/full_battery_models/base_battery_model.py index 7b9ae079fa..3494594803 100644 --- a/pybamm/models/full_battery_models/base_battery_model.py +++ b/pybamm/models/full_battery_models/base_battery_model.py @@ -465,24 +465,21 @@ def default_var_pts(self): @property def default_submesh_types(self): base_submeshes = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle size": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive particle size": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, + "negative particle": pybamm.Uniform1DSubMesh, + "positive particle": pybamm.Uniform1DSubMesh, + "negative particle size": pybamm.Uniform1DSubMesh, + "positive particle size": pybamm.Uniform1DSubMesh, } if self.options["dimensionality"] == 0: - base_submeshes["current collector"] = pybamm.MeshGenerator(pybamm.SubMesh0D) + base_submeshes["current collector"] = pybamm.SubMesh0D elif self.options["dimensionality"] == 1: - base_submeshes["current collector"] = pybamm.MeshGenerator( - pybamm.Uniform1DSubMesh - ) + base_submeshes["current collector"] = pybamm.Uniform1DSubMesh + elif self.options["dimensionality"] == 2: - base_submeshes["current collector"] = pybamm.MeshGenerator( - pybamm.ScikitUniform2DSubMesh - ) + base_submeshes["current collector"] = pybamm.ScikitUniform2DSubMesh return base_submeshes @property diff --git a/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py b/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py index fdfc8a8779..0f61502c66 100644 --- a/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py +++ b/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py @@ -218,7 +218,6 @@ def default_parameter_values(self): def default_geometry(self): geometry = {} param = self.param - var = pybamm.standard_spatial_vars if self.options["dimensionality"] == 1: geometry["current collector"] = { "z": {"min": 0, "max": 1}, @@ -253,7 +252,7 @@ def default_var_pts(self): @property def default_submesh_types(self): if self.options["dimensionality"] == 1: - return {"current collector": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh)} + return {"current collector": pybamm.Uniform1DSubMesh} elif self.options["dimensionality"] == 2: return { "current collector": pybamm.MeshGenerator(pybamm.ScikitUniform2DSubMesh) @@ -472,7 +471,6 @@ def default_parameter_values(self): @property def default_geometry(self): param = self.param - var = pybamm.standard_spatial_vars geometry = { "current collector": { "y": {"min": 0, "max": param.l_y}, diff --git a/tests/integration/test_spatial_methods/test_spectral_volume.py b/tests/integration/test_spatial_methods/test_spectral_volume.py index 5424c00852..072005ac35 100644 --- a/tests/integration/test_spatial_methods/test_spectral_volume.py +++ b/tests/integration/test_spatial_methods/test_spectral_volume.py @@ -46,7 +46,7 @@ def get_mesh_for_testing( "positive particle": pybamm.MeshGenerator( pybamm.SpectralVolume1DSubMesh, {"order": order} ), - "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), + "current collector": pybamm.SubMesh0D, } if cc_submesh: submesh_types["current collector"] = cc_submesh diff --git a/tests/shared.py b/tests/shared.py index 8dc9688b7b..5016c966bb 100644 --- a/tests/shared.py +++ b/tests/shared.py @@ -71,14 +71,14 @@ def get_mesh_for_testing( param.process_geometry(geometry) submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle size": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive particle size": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, + "negative particle": pybamm.Uniform1DSubMesh, + "positive particle": pybamm.Uniform1DSubMesh, + "negative particle size": pybamm.Uniform1DSubMesh, + "positive particle size": pybamm.Uniform1DSubMesh, + "current collector": pybamm.SubMesh0D, } if cc_submesh: submesh_types["current collector"] = cc_submesh @@ -112,7 +112,7 @@ def get_size_distribution_mesh_for_testing( rpts=10, Rpts=10, zpts=15, - cc_submesh=pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + cc_submesh=pybamm.Uniform1DSubMesh, ): options = {"particle size": "distribution"} geometry = pybamm.battery_geometry(options=options, current_collector_dimension=1) @@ -130,7 +130,7 @@ def get_1p1d_mesh_for_testing( xpts=None, rpts=10, zpts=15, - cc_submesh=pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + cc_submesh=pybamm.Uniform1DSubMesh, ): geometry = pybamm.battery_geometry(current_collector_dimension=1) return get_mesh_for_testing( @@ -184,9 +184,9 @@ def get_unit_2p1D_mesh_for_testing(ypts=15, zpts=15, include_particles=True): var_pts = {"x_n": 3, "x_s": 3, "x_p": 3, "y": ypts, "z": zpts} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, "current collector": pybamm.MeshGenerator(pybamm.ScikitUniform2DSubMesh), } diff --git a/tests/unit/test_discretisations/test_discretisation.py b/tests/unit/test_discretisations/test_discretisation.py index 20481d4154..fdc0f109f8 100644 --- a/tests/unit/test_discretisations/test_discretisation.py +++ b/tests/unit/test_discretisations/test_discretisation.py @@ -119,7 +119,7 @@ def test_adding_1D_external_variable(self): x = pybamm.SpatialVariable("x", domain="test", coord_sys="cartesian") geometry = {"test": {x: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}}} - submesh_types = {"test": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh)} + submesh_types = {"test": pybamm.Uniform1DSubMesh} var_pts = {x: 10} mesh = pybamm.Mesh(geometry, submesh_types, var_pts) @@ -178,8 +178,8 @@ def test_concatenation_external_variables(self): } submesh_types = { - "test": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "test1": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "test": pybamm.Uniform1DSubMesh, + "test1": pybamm.Uniform1DSubMesh, } var_pts = {x: 10, y: 5} mesh = pybamm.Mesh(geometry, submesh_types, var_pts) @@ -1324,9 +1324,7 @@ def test_bc_symmetry(self): } # mesh - submesh_types = { - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh) - } + submesh_types = {"negative particle": pybamm.Uniform1DSubMesh} var_pts = {r: 20} mesh = pybamm.Mesh(geometry, submesh_types, var_pts) diff --git a/tests/unit/test_geometry/test_battery_geometry.py b/tests/unit/test_geometry/test_battery_geometry.py index 53abeb2f0d..d001558023 100644 --- a/tests/unit/test_geometry/test_battery_geometry.py +++ b/tests/unit/test_geometry/test_battery_geometry.py @@ -14,7 +14,7 @@ def test_geometry_keys(self): ) for domain_geoms in geometry.values(): all( - self.assertIsInstance(spatial_var, pybamm.SpatialVariable) + self.assertIsInstance(spatial_var, str) for spatial_var in domain_geoms.keys() ) geometry.print_parameter_info() diff --git a/tests/unit/test_meshes/test_meshes.py b/tests/unit/test_meshes/test_meshes.py index 086aa4dd6b..c42497f8f2 100644 --- a/tests/unit/test_meshes/test_meshes.py +++ b/tests/unit/test_meshes/test_meshes.py @@ -16,9 +16,7 @@ def test_mesh_creation_no_parameters(self): "negative particle": {r: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}} } - submesh_types = { - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh) - } + submesh_types = {"negative particle": pybamm.Uniform1DSubMesh} var_pts = {r: 20} # create mesh @@ -61,12 +59,12 @@ def test_mesh_creation(self): var_pts = {"x_n": 10, "x_s": 10, "x_p": 12, "r_n": 5, "r_p": 6} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, + "negative particle": pybamm.Uniform1DSubMesh, + "positive particle": pybamm.Uniform1DSubMesh, + "current collector": pybamm.SubMesh0D, } # create mesh @@ -90,12 +88,12 @@ def test_mesh_creation(self): def test_init_failure(self): geometry = pybamm.battery_geometry() submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, + "negative particle": pybamm.Uniform1DSubMesh, + "positive particle": pybamm.Uniform1DSubMesh, + "current collector": pybamm.SubMesh0D, } with self.assertRaisesRegex(KeyError, "Points not given"): pybamm.Mesh(geometry, submesh_types, {}) @@ -111,12 +109,12 @@ def test_init_failure(self): var_pts = {"x_n": 10, "x_s": 10, "x_p": 12, "r_n": 5, "r_p": 6} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, + "negative particle": pybamm.Uniform1DSubMesh, + "positive particle": pybamm.Uniform1DSubMesh, + "current collector": pybamm.SubMesh0D, } with self.assertRaisesRegex(pybamm.DiscretisationError, "Parameter values"): @@ -144,12 +142,12 @@ def test_mesh_sizes(self): # provide mesh properties var_pts = {"x_n": 10, "x_s": 10, "x_p": 12, "r_n": 5, "r_p": 6} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, + "negative particle": pybamm.Uniform1DSubMesh, + "positive particle": pybamm.Uniform1DSubMesh, + "current collector": pybamm.SubMesh0D, } # create mesh @@ -179,12 +177,12 @@ def test_mesh_sizes_using_standard_spatial_vars(self): var = pybamm.standard_spatial_vars var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 12, var.r_n: 5, var.r_p: 6} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, + "negative particle": pybamm.Uniform1DSubMesh, + "positive particle": pybamm.Uniform1DSubMesh, + "current collector": pybamm.SubMesh0D, } # create mesh @@ -213,12 +211,12 @@ def test_combine_submeshes(self): # provide mesh properties var_pts = {"x_n": 10, "x_s": 10, "x_p": 12, "r_n": 5, "r_p": 6} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, + "negative particle": pybamm.Uniform1DSubMesh, + "positive particle": pybamm.Uniform1DSubMesh, + "current collector": pybamm.SubMesh0D, } # create mesh @@ -271,12 +269,12 @@ def test_ghost_cells(self): # provide mesh properties var_pts = {"x_n": 10, "x_s": 10, "x_p": 12, "r_n": 5, "r_p": 6} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, + "negative particle": pybamm.Uniform1DSubMesh, + "positive particle": pybamm.Uniform1DSubMesh, + "current collector": pybamm.SubMesh0D, } # create mesh @@ -310,12 +308,12 @@ def test_mesh_coord_sys(self): var_pts = {"x_n": 10, "x_s": 10, "x_p": 12, "r_n": 5, "r_p": 6} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, + "negative particle": pybamm.Uniform1DSubMesh, + "positive particle": pybamm.Uniform1DSubMesh, + "current collector": pybamm.SubMesh0D, } # create mesh @@ -333,9 +331,7 @@ def test_unimplemented_meshes(self): "y": {"min": 0, "max": 1}, } } - submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh) - } + submesh_types = {"negative electrode": pybamm.Uniform1DSubMesh} with self.assertRaises(pybamm.GeometryError): pybamm.Mesh(geometry, submesh_types, var_pts) @@ -360,10 +356,10 @@ def test_1plus1D_tabs_left_right(self): var_pts = {"x_n": 10, "x_s": 7, "x_p": 12, "z": 24} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "current collector": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, + "current collector": pybamm.Uniform1DSubMesh, } # create mesh @@ -396,10 +392,10 @@ def test_1plus1D_tabs_right_left(self): var_pts = {"x_n": 10, "x_s": 7, "x_p": 12, "z": 24} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "current collector": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, + "current collector": pybamm.Uniform1DSubMesh, } # create mesh diff --git a/tests/unit/test_meshes/test_one_dimensional_submesh.py b/tests/unit/test_meshes/test_one_dimensional_submesh.py index 59d8013419..7356da95f6 100644 --- a/tests/unit/test_meshes/test_one_dimensional_submesh.py +++ b/tests/unit/test_meshes/test_one_dimensional_submesh.py @@ -33,9 +33,7 @@ def test_symmetric_mesh_creation_no_parameters(self): "negative particle": {r: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}} } - submesh_types = { - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh) - } + submesh_types = {"negative particle": pybamm.Uniform1DSubMesh} var_pts = {r: 20} # create mesh @@ -189,9 +187,7 @@ def test_mesh_creation_no_parameters(self): "negative particle": {r: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}} } - submesh_types = { - "negative particle": pybamm.MeshGenerator(pybamm.Chebyshev1DSubMesh) - } + submesh_types = {"negative particle": pybamm.Chebyshev1DSubMesh} var_pts = {r: 20} # create mesh @@ -215,23 +211,21 @@ def test_exceptions(self): submesh_params = {"edges": edges} mesh = pybamm.MeshGenerator(pybamm.UserSupplied1DSubMesh, submesh_params) - x_n = pybamm.standard_spatial_vars.x_n - # error if npts+1 != len(edges) - lims = {x_n: {"min": 0, "max": 1}} - npts = {x_n.id: 10} + lims = {"x_n": {"min": 0, "max": 1}} + npts = {"x_n": 10} with self.assertRaises(pybamm.GeometryError): mesh(lims, npts) # error if lims[0] not equal to edges[0] - lims = {x_n: {"min": 0.1, "max": 1}} - npts = {x_n.id: len(edges) - 1} + lims = {"x_n": {"min": 0.1, "max": 1}} + npts = {"x_n": len(edges) - 1} with self.assertRaises(pybamm.GeometryError): mesh(lims, npts) # error if lims[-1] not equal to edges[-1] - lims = {x_n: {"min": 0, "max": 10}} - npts = {x_n.id: len(edges) - 1} + lims = {"x_n": {"min": 0, "max": 10}} + npts = {"x_n": len(edges) - 1} with self.assertRaises(pybamm.GeometryError): mesh(lims, npts) @@ -279,23 +273,21 @@ def test_exceptions(self): submesh_params = {"edges": edges} mesh = pybamm.MeshGenerator(pybamm.SpectralVolume1DSubMesh, submesh_params) - x_n = pybamm.standard_spatial_vars.x_n - # error if npts+1 != len(edges) - lims = {x_n: {"min": 0, "max": 1}} - npts = {x_n.id: 10} + lims = {"x_n": {"min": 0, "max": 1}} + npts = {"x_n": 10} with self.assertRaises(pybamm.GeometryError): mesh(lims, npts) # error if lims[0] not equal to edges[0] - lims = {x_n: {"min": 0.1, "max": 1}} - npts = {x_n.id: len(edges) - 1} + lims = {"x_n": {"min": 0.1, "max": 1}} + npts = {"x_n": len(edges) - 1} with self.assertRaises(pybamm.GeometryError): mesh(lims, npts) # error if lims[-1] not equal to edges[-1] - lims = {x_n: {"min": 0, "max": 10}} - npts = {x_n.id: len(edges) - 1} + lims = {"x_n": {"min": 0, "max": 10}} + npts = {"x_n": len(edges) - 1} with self.assertRaises(pybamm.GeometryError): mesh(lims, npts) diff --git a/tests/unit/test_meshes/test_scikit_fem_submesh.py b/tests/unit/test_meshes/test_scikit_fem_submesh.py index 86e0fc1521..91c2899da8 100644 --- a/tests/unit/test_meshes/test_scikit_fem_submesh.py +++ b/tests/unit/test_meshes/test_scikit_fem_submesh.py @@ -32,9 +32,9 @@ def test_mesh_creation(self): var_pts = {"x_n": 10, "x_s": 7, "x_p": 12, "y": 16, "z": 24} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, "current collector": pybamm.MeshGenerator(pybamm.ScikitUniform2DSubMesh), } @@ -55,16 +55,16 @@ def test_mesh_creation(self): for domain in mesh: if domain == "current collector": # NOTE: only for degree 1 - npts = var_pts[var.y] * var_pts[var.z] + npts = var_pts["y"] * var_pts["z"] self.assertEqual(mesh[domain].npts, npts) else: self.assertEqual(len(mesh[domain].edges), len(mesh[domain].nodes) + 1) def test_init_failure(self): submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, "current collector": pybamm.MeshGenerator(pybamm.ScikitUniform2DSubMesh), } geometry = pybamm.battery_geometry( @@ -96,20 +96,23 @@ def test_init_failure(self): "y": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, "z": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, } - npts = {var.y.id: 10, var.z.id: 10} - var.z.coord_sys = "not cartesian" + npts = {"y": 10, "z": 10} + z = pybamm.SpatialVariable("z", domain="not cartesian") + lims = { + "y": {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + z: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}, + } with self.assertRaises(pybamm.DomainError): pybamm.ScikitUniform2DSubMesh(lims, npts) - var.z.coord_sys = "cartesian" def test_tab_error(self): # set variables and submesh types var_pts = {"x_n": 2, "x_s": 2, "x_p": 2, "y": 64, "z": 64} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, "current collector": pybamm.MeshGenerator(pybamm.ScikitUniform2DSubMesh), } @@ -143,9 +146,9 @@ def test_tab_left_right(self): var_pts = {"x_n": 2, "x_s": 2, "x_p": 2, "y": 64, "z": 64} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, "current collector": pybamm.MeshGenerator(pybamm.ScikitUniform2DSubMesh), } @@ -200,9 +203,9 @@ def test_mesh_creation(self): var_pts = {"x_n": 10, "x_s": 7, "x_p": 12, "y": 16, "z": 24} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, "current collector": pybamm.MeshGenerator(pybamm.ScikitChebyshev2DSubMesh), } @@ -223,7 +226,7 @@ def test_mesh_creation(self): for domain in mesh: if domain == "current collector": # NOTE: only for degree 1 - npts = var_pts[var.y] * var_pts[var.z] + npts = var_pts["y"] * var_pts["z"] self.assertEqual(mesh[domain].npts, npts) else: self.assertEqual(len(mesh[domain].edges), len(mesh[domain].nodes) + 1) @@ -278,9 +281,9 @@ def test_mesh_creation(self): var_pts = {"x_n": 10, "x_s": 7, "x_p": 12, "y": 16, "z": 24} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, "current collector": pybamm.MeshGenerator( pybamm.ScikitExponential2DSubMesh ), @@ -303,7 +306,7 @@ def test_mesh_creation(self): for domain in mesh: if domain == "current collector": # NOTE: only for degree 1 - npts = var_pts[var.y] * var_pts[var.z] + npts = var_pts["y"] * var_pts["z"] self.assertEqual(mesh[domain].npts, npts) else: self.assertEqual(len(mesh[domain].edges), len(mesh[domain].nodes) + 1) @@ -366,9 +369,9 @@ def test_mesh_creation(self): submesh_params = {"y_edges": y_edges, "z_edges": z_edges} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, "current collector": pybamm.MeshGenerator( pybamm.UserSupplied2DSubMesh, submesh_params ), @@ -391,7 +394,7 @@ def test_mesh_creation(self): for domain in mesh: if domain == "current collector": # NOTE: only for degree 1 - npts = var_pts[var.y] * var_pts[var.z] + npts = var_pts["y"] * var_pts["z"] self.assertEqual(mesh[domain].npts, npts) else: self.assertEqual(len(mesh[domain].edges), len(mesh[domain].nodes) + 1) @@ -408,25 +411,25 @@ def test_exceptions(self): lims = {"y": {"min": 0, "max": 1}, "z": {"min": 0, "max": 1}} # error if len(edges) != npts - npts = {var.y.id: 10, var.z.id: 3} + npts = {"y": 10, "z": 3} with self.assertRaises(pybamm.GeometryError): mesh(lims, npts) # error if lims[0] not equal to edges[0] lims = {"y": {"min": 0.1, "max": 1}, "z": {"min": 0, "max": 1}} - npts = {var.y.id: 3, var.z.id: 3} + npts = {"y": 3, "z": 3} with self.assertRaises(pybamm.GeometryError): mesh(lims, npts) # error if lims[-1] not equal to edges[-1] lims = {"y": {"min": 0, "max": 1}, "z": {"min": 0, "max": 1.3}} - npts = {var.y.id: 3, var.z.id: 3} + npts = {"y": 3, "z": 3} with self.assertRaises(pybamm.GeometryError): mesh(lims, npts) # error if different coordinate system lims = {"y": {"min": 0, "max": 1}, "r_n": {"min": 0, "max": 1}} - npts = {var.y.id: 3, var.r_n.id: 3} + npts = {"y": 3, "r_n": 3} with self.assertRaises(pybamm.DomainError): mesh(lims, npts) diff --git a/tests/unit/test_meshes/test_zero_dimensional_submesh.py b/tests/unit/test_meshes/test_zero_dimensional_submesh.py index df663bdf06..2645913482 100644 --- a/tests/unit/test_meshes/test_zero_dimensional_submesh.py +++ b/tests/unit/test_meshes/test_zero_dimensional_submesh.py @@ -10,7 +10,7 @@ def test_exceptions(self): def test_init(self): position = {"x": {"position": 1}} - generator = pybamm.MeshGenerator(pybamm.SubMesh0D) + generator = pybamm.SubMesh0D mesh = generator(position, None) mesh.add_ghost_meshes() diff --git a/tests/unit/test_models/test_base_model.py b/tests/unit/test_models/test_base_model.py index aadf02598f..c56d2802f3 100644 --- a/tests/unit/test_models/test_base_model.py +++ b/tests/unit/test_models/test_base_model.py @@ -653,9 +653,9 @@ def test_set_initial_conditions(self): "negative particle": {"r_n": {"min": 0, "max": 1}}, } submeshes = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "negative particle": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "negative particle": pybamm.Uniform1DSubMesh, } var_pts = {"x_n": 10, "x_s": 10, "r_n": 5} mesh = pybamm.Mesh(geometry, submeshes, var_pts) diff --git a/tests/unit/test_models/test_full_battery_models/test_base_battery_model.py b/tests/unit/test_models/test_full_battery_models/test_base_battery_model.py index 210532a035..33239fb73e 100644 --- a/tests/unit/test_models/test_full_battery_models/test_base_battery_model.py +++ b/tests/unit/test_models/test_full_battery_models/test_base_battery_model.py @@ -88,32 +88,32 @@ def test_default_geometry(self): model = pybamm.BaseBatteryModel({"dimensionality": 0}) self.assertEqual( - model.default_geometry["current collector"][var.z]["position"], 1 + model.default_geometry["current collector"]["z"]["position"], 1 ) model = pybamm.BaseBatteryModel({"dimensionality": 1}) - self.assertEqual(model.default_geometry["current collector"][var.z]["min"], 0) + self.assertEqual(model.default_geometry["current collector"]["z"]["min"], 0) model = pybamm.BaseBatteryModel({"dimensionality": 2}) - self.assertEqual(model.default_geometry["current collector"][var.y]["min"], 0) + self.assertEqual(model.default_geometry["current collector"]["y"]["min"], 0) def test_default_submesh_types(self): model = pybamm.BaseBatteryModel({"dimensionality": 0}) self.assertTrue( issubclass( - model.default_submesh_types["current collector"].submesh_type, + model.default_submesh_types["current collector"], pybamm.SubMesh0D, ) ) model = pybamm.BaseBatteryModel({"dimensionality": 1}) self.assertTrue( issubclass( - model.default_submesh_types["current collector"].submesh_type, + model.default_submesh_types["current collector"], pybamm.Uniform1DSubMesh, ) ) model = pybamm.BaseBatteryModel({"dimensionality": 2}) self.assertTrue( issubclass( - model.default_submesh_types["current collector"].submesh_type, + model.default_submesh_types["current collector"], pybamm.ScikitUniform2DSubMesh, ) ) diff --git a/tests/unit/test_models/test_full_battery_models/test_lead_acid/test_loqs.py b/tests/unit/test_models/test_full_battery_models/test_lead_acid/test_loqs.py index eb29f0f68f..1706a0fe27 100644 --- a/tests/unit/test_models/test_full_battery_models/test_lead_acid/test_loqs.py +++ b/tests/unit/test_models/test_full_battery_models/test_lead_acid/test_loqs.py @@ -29,7 +29,7 @@ def test_default_geometry(self): ) self.assertTrue( issubclass( - model.default_submesh_types["current collector"].submesh_type, + model.default_submesh_types["current collector"], pybamm.SubMesh0D, ) ) @@ -58,7 +58,7 @@ def test_well_posed_1plus1D(self): ) self.assertTrue( issubclass( - model.default_submesh_types["current collector"].submesh_type, + model.default_submesh_types["current collector"], pybamm.Uniform1DSubMesh, ) ) @@ -79,7 +79,7 @@ def test_well_posed_2plus1D(self): ) self.assertTrue( issubclass( - model.default_submesh_types["current collector"].submesh_type, + model.default_submesh_types["current collector"], pybamm.ScikitUniform2DSubMesh, ) ) diff --git a/tests/unit/test_parameters/test_parameter_values.py b/tests/unit/test_parameters/test_parameter_values.py index ad1fd020a5..7e22b8aaa8 100644 --- a/tests/unit/test_parameters/test_parameter_values.py +++ b/tests/unit/test_parameters/test_parameter_values.py @@ -122,10 +122,6 @@ def test_update(self): def test_check_parameter_values(self): # Cell capacity [A.h] deprecated with self.assertRaisesRegex(ValueError, "Cell capacity"): - pybamm.ParameterValues( - {"Cell capacity [A.h]": 1, "Nominal cell capacity [A.h]": 1} - ) - with self.assertWarnsRegex(DeprecationWarning, "Cell capacity"): pybamm.ParameterValues({"Cell capacity [A.h]": 1}) # Can't provide a current density of 0, as this will cause a ZeroDivision error with self.assertRaisesRegex(ValueError, "Typical current"): @@ -858,22 +854,12 @@ def some_function(self): def test_deprecate_anode_cathode(self): chemistry = pybamm.parameter_sets.Ecker2015.copy() chemistry["anode"] = chemistry.pop("negative electrode") - with self.assertWarnsRegex(DeprecationWarning, "anode"): + with self.assertRaisesRegex(KeyError, "anode"): pybamm.ParameterValues(chemistry) chemistry = pybamm.parameter_sets.Ecker2015.copy() chemistry["cathode"] = chemistry.pop("positive electrode") - with self.assertWarnsRegex(DeprecationWarning, "cathode"): - pybamm.ParameterValues(chemistry) - - chemistry = pybamm.parameter_sets.Ecker2015.copy() - chemistry["anode"] = None - with self.assertRaisesRegex(KeyError, "both 'anode' and 'negative"): - pybamm.ParameterValues(chemistry) - - chemistry = pybamm.parameter_sets.Ecker2015.copy() - chemistry["cathode"] = None - with self.assertRaisesRegex(KeyError, "both 'cathode' and 'positive"): + with self.assertRaisesRegex(KeyError, "cathode"): pybamm.ParameterValues(chemistry) diff --git a/tests/unit/test_simulation.py b/tests/unit/test_simulation.py index 59a5361f8a..df10bd76f0 100644 --- a/tests/unit/test_simulation.py +++ b/tests/unit/test_simulation.py @@ -2,7 +2,6 @@ import numpy as np import pandas as pd import os -import subprocess import sys import unittest import uuid @@ -297,8 +296,11 @@ def test_save_load(self): def test_load_param(self): # Test load_sim for parameters imports filename = f"{uuid.uuid4()}.p" - save_sim = f"import pybamm; model = pybamm.lithium_ion.SPM(); params = pybamm.ParameterValues("Chen2020"); sim = pybamm.Simulation(model, parameter_values=params); sim.solve([0, 3600]); sim.save('{filename}')" # noqa - subprocess.run([sys.executable, "-c", save_sim]) + model = pybamm.lithium_ion.SPM() + params = pybamm.ParameterValues("Chen2020") + sim = pybamm.Simulation(model, parameter_values=params) + sim.solve([0, 3600]) + sim.save(filename) try: pkl_obj = pybamm.load_sim(os.path.join(filename)) diff --git a/tests/unit/test_solvers/test_processed_symbolic_variable.py b/tests/unit/test_solvers/test_processed_symbolic_variable.py index 46a50446c8..5f6ee9921f 100644 --- a/tests/unit/test_solvers/test_processed_symbolic_variable.py +++ b/tests/unit/test_solvers/test_processed_symbolic_variable.py @@ -280,7 +280,7 @@ def test_1D_different_domains(self): geometry = pybamm.Geometry( {"line": {x: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}}} ) - submesh_types = {"line": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh)} + submesh_types = {"line": pybamm.Uniform1DSubMesh} var_pts = {x: 10} mesh = pybamm.Mesh(geometry, submesh_types, var_pts) disc = pybamm.Discretisation(mesh, {"line": pybamm.FiniteVolume()}) diff --git a/tests/unit/test_spatial_methods/test_finite_volume/test_extrapolation.py b/tests/unit/test_spatial_methods/test_finite_volume/test_extrapolation.py index 2135b57592..7b990133a4 100644 --- a/tests/unit/test_spatial_methods/test_finite_volume/test_extrapolation.py +++ b/tests/unit/test_spatial_methods/test_finite_volume/test_extrapolation.py @@ -16,7 +16,7 @@ def errors(pts, function, method_options, bcs=None): domain = "test" x = pybamm.SpatialVariable("x", domain=domain) geometry = {domain: {x: {"min": pybamm.Scalar(0), "max": pybamm.Scalar(1)}}} - submesh_types = {domain: pybamm.MeshGenerator(pybamm.Uniform1DSubMesh)} + submesh_types = {domain: pybamm.Uniform1DSubMesh} var_pts = {x: pts} mesh = pybamm.Mesh(geometry, submesh_types, var_pts) diff --git a/tests/unit/test_spatial_methods/test_scikit_finite_element.py b/tests/unit/test_spatial_methods/test_scikit_finite_element.py index 06d028c931..b4fad0bef0 100644 --- a/tests/unit/test_spatial_methods/test_scikit_finite_element.py +++ b/tests/unit/test_spatial_methods/test_scikit_finite_element.py @@ -255,9 +255,9 @@ def test_manufactured_solution_cheb_grid(self): var_pts = {"x_n": 3, "x_s": 3, "x_p": 3, "y": 32, "z": 32} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, "current collector": pybamm.MeshGenerator(pybamm.ScikitChebyshev2DSubMesh), } mesh = pybamm.Mesh(geometry, submesh_types, var_pts) @@ -316,9 +316,9 @@ def test_manufactured_solution_exponential_grid(self): var_pts = {"x_n": 3, "x_s": 3, "x_p": 3, "y": 32, "z": 32} submesh_types = { - "negative electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "separator": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), - "positive electrode": pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + "negative electrode": pybamm.Uniform1DSubMesh, + "separator": pybamm.Uniform1DSubMesh, + "positive electrode": pybamm.Uniform1DSubMesh, "current collector": pybamm.MeshGenerator( pybamm.ScikitExponential2DSubMesh ), diff --git a/tests/unit/test_spatial_methods/test_spectral_volume.py b/tests/unit/test_spatial_methods/test_spectral_volume.py index b8d31fc2bd..b002f88ae0 100644 --- a/tests/unit/test_spatial_methods/test_spectral_volume.py +++ b/tests/unit/test_spatial_methods/test_spectral_volume.py @@ -46,7 +46,7 @@ def get_mesh_for_testing( "positive particle": pybamm.MeshGenerator( pybamm.SpectralVolume1DSubMesh, {"order": order} ), - "current collector": pybamm.MeshGenerator(pybamm.SubMesh0D), + "current collector": pybamm.SubMesh0D, } if cc_submesh: submesh_types["current collector"] = cc_submesh @@ -77,7 +77,7 @@ def get_1p1d_mesh_for_testing( xpts=None, rpts=10, zpts=15, - cc_submesh=pybamm.MeshGenerator(pybamm.Uniform1DSubMesh), + cc_submesh=pybamm.Uniform1DSubMesh, ): geometry = pybamm.battery_geometry(current_collector_dimension=1) return get_mesh_for_testing( From cc6aea8e752c1a7c65a3fe4100823333dd15b4bf Mon Sep 17 00:00:00 2001 From: Valentin Sulzer Date: Fri, 19 Nov 2021 16:13:21 -0500 Subject: [PATCH 4/8] #1810 fix examples --- .../Creating Models/2-a-pde-model.ipynb | 25 +- .../3-negative-particle-problem.ipynb | 25 +- ...paring-full-and-reduced-order-models.ipynb | 27 +- .../Creating Models/5-half-cell-model.ipynb | 71 +- .../Tutorial 9 - Changing the mesh.ipynb | 73 +- examples/notebooks/batch_study.ipynb | 430 +-- .../expression_tree/broadcasts.ipynb | 25 +- ...DFN-with-particle-size-distributions.ipynb | 35 +- examples/notebooks/models/MPM.ipynb | 81 +- examples/notebooks/models/SPM.ipynb | 345 +- ...ating_mechanical_models_Enertech_DFN.ipynb | 15 +- .../compare-comsol-discharge-curve.ipynb | 11 +- .../notebooks/models/compare-ecker-data.ipynb | 42 +- .../models/electrode-state-of-health.ipynb | 6 +- .../notebooks/models/lithium-plating.ipynb | 5 +- .../notebooks/models/pouch-cell-model.ipynb | 42 +- ...simulating-ORegan-2021-parameter-set.ipynb | 20 +- .../models/submodel_cracking_DFN_or_SPM.ipynb | 11 +- .../submodel_loss_of_active_materials.ipynb | 15 +- .../notebooks/models/thermal-models.ipynb | 41 +- .../using-model-options_thermal-example.ipynb | 19 +- .../parameterization/parameter-values.ipynb | 6 +- .../parameterization/parameterization.ipynb | 7 +- .../simulating-long-experiments.ipynb | 3051 ++++++++--------- .../spatial_methods/finite-volumes.ipynb | 6 +- 25 files changed, 2231 insertions(+), 2203 deletions(-) diff --git a/examples/notebooks/Creating Models/2-a-pde-model.ipynb b/examples/notebooks/Creating Models/2-a-pde-model.ipynb index 0096893cd5..bc0577e801 100644 --- a/examples/notebooks/Creating Models/2-a-pde-model.ipynb +++ b/examples/notebooks/Creating Models/2-a-pde-model.ipynb @@ -176,7 +176,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We then create a mesh using the `pybamm.MeshGenerator` class. As inputs this class takes the type of mesh and any parameters required by the mesh. In this case we choose a uniform one-dimensional mesh which doesn't require any parameters. " + "We then create a uniform one-dimensional mesh with 20 points. " ] }, { @@ -246,12 +246,12 @@ "name": "stderr", "output_type": "stream", "text": [ - "2021-01-24 19:28:37,091 - [WARNING] processed_variable.get_spatial_scale(518): No length scale set for negative particle. Using default of 1 [m].\n" + "2021-11-19 15:31:50,774 - [WARNING] processed_variable.get_spatial_scale(520): No length scale set for negative particle. Using default of 1 [m].\n" ] }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -313,7 +313,7 @@ "text": [ "[1] Joel A. E. Andersson, Joris Gillis, Greg Horn, James B. Rawlings, and Moritz Diehl. CasADi – A software framework for nonlinear optimization and optimal control. Mathematical Programming Computation, 11(1):1–36, 2019. doi:10.1007/s12532-018-0139-4.\n", "[2] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", - "[3] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", + "[3] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", "[4] Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, and others. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17(3):261–272, 2020. doi:10.1038/s41592-019-0686-2.\n", "\n" ] @@ -326,7 +326,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -340,7 +340,20 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, diff --git a/examples/notebooks/Creating Models/3-negative-particle-problem.ipynb b/examples/notebooks/Creating Models/3-negative-particle-problem.ipynb index 32042e4e16..137571dc79 100644 --- a/examples/notebooks/Creating Models/3-negative-particle-problem.ipynb +++ b/examples/notebooks/Creating Models/3-negative-particle-problem.ipynb @@ -57,8 +57,6 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[33mWARNING: You are using pip version 21.0.1; however, version 21.1.2 is available.\n", - "You should consider upgrading via the '/home/user/Documents/PyBaMM/env/bin/python3.8 -m pip install --upgrade pip' command.\u001b[0m\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } @@ -265,12 +263,12 @@ "name": "stderr", "output_type": "stream", "text": [ - "2021-05-27 10:32:57,012 - [WARNING] processed_variable.get_spatial_scale(471): No length scale set for negative particle. Using default of 1 [m].\n" + "2021-11-19 15:29:22,931 - [WARNING] processed_variable.get_spatial_scale(520): No length scale set for negative particle. Using default of 1 [m].\n" ] }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -337,7 +335,7 @@ "text": [ "[1] Joel A. E. Andersson, Joris Gillis, Greg Horn, James B. Rawlings, and Moritz Diehl. CasADi – A software framework for nonlinear optimization and optimal control. Mathematical Programming Computation, 11(1):1–36, 2019. doi:10.1007/s12532-018-0139-4.\n", "[2] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", - "[3] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", + "[3] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", "[4] Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, and others. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17(3):261–272, 2020. doi:10.1038/s41592-019-0686-2.\n", "\n" ] @@ -350,7 +348,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -364,7 +362,20 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, diff --git a/examples/notebooks/Creating Models/4-comparing-full-and-reduced-order-models.ipynb b/examples/notebooks/Creating Models/4-comparing-full-and-reduced-order-models.ipynb index 818511084a..d724b48cf4 100644 --- a/examples/notebooks/Creating Models/4-comparing-full-and-reduced-order-models.ipynb +++ b/examples/notebooks/Creating Models/4-comparing-full-and-reduced-order-models.ipynb @@ -52,8 +52,6 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[33mWARNING: You are using pip version 21.0.1; however, version 21.1.2 is available.\n", - "You should consider upgrading via the '/home/user/Documents/PyBaMM/env/bin/python3.8 -m pip install --upgrade pip' command.\u001b[0m\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } @@ -294,14 +292,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "2021-05-27 10:31:08,618 - [WARNING] processed_variable.get_spatial_scale(471): No length scale set for negative particle. Using default of 1 [m].\n", - "2021-05-27 10:31:08,729 - [WARNING] processed_variable.get_spatial_scale(471): No length scale set for negative particle. Using default of 1 [m].\n" + "2021-11-19 15:29:38,512 - [WARNING] processed_variable.get_spatial_scale(520): No length scale set for negative particle. Using default of 1 [m].\n", + "2021-11-19 15:29:38,541 - [WARNING] processed_variable.get_spatial_scale(520): No length scale set for negative particle. Using default of 1 [m].\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "28d9f238e5364c4588a39b0984631dee", + "model_id": "c7ec6d3f5bf14206a6ec219f10583c46", "version_major": 2, "version_minor": 0 }, @@ -397,7 +395,7 @@ "text": [ "[1] Joel A. E. Andersson, Joris Gillis, Greg Horn, James B. Rawlings, and Moritz Diehl. CasADi – A software framework for nonlinear optimization and optimal control. Mathematical Programming Computation, 11(1):1–36, 2019. doi:10.1007/s12532-018-0139-4.\n", "[2] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", - "[3] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", + "[3] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", "[4] Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, and others. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17(3):261–272, 2020. doi:10.1038/s41592-019-0686-2.\n", "\n" ] @@ -410,7 +408,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -424,7 +422,20 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, diff --git a/examples/notebooks/Creating Models/5-half-cell-model.ipynb b/examples/notebooks/Creating Models/5-half-cell-model.ipynb index c88b69404a..542c5f9d51 100644 --- a/examples/notebooks/Creating Models/5-half-cell-model.ipynb +++ b/examples/notebooks/Creating Models/5-half-cell-model.ipynb @@ -55,7 +55,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 19, "id": "short-tension", "metadata": {}, "outputs": [ @@ -63,8 +63,6 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[33mWARNING: You are using pip version 21.0.1; however, version 21.1.2 is available.\n", - "You should consider upgrading via the '/home/user/Documents/PyBaMM/env/bin/python3.8 -m pip install --upgrade pip' command.\u001b[0m\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } @@ -88,7 +86,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 20, "id": "catholic-condition", "metadata": {}, "outputs": [], @@ -106,7 +104,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 21, "id": "compound-equity", "metadata": {}, "outputs": [], @@ -125,7 +123,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 22, "id": "square-brief", "metadata": {}, "outputs": [], @@ -151,7 +149,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 23, "id": "sealed-catholic", "metadata": {}, "outputs": [], @@ -183,7 +181,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 24, "id": "legendary-cycling", "metadata": {}, "outputs": [], @@ -218,7 +216,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 25, "id": "valuable-graphics", "metadata": {}, "outputs": [], @@ -239,7 +237,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 26, "id": "chicken-sweden", "metadata": {}, "outputs": [], @@ -259,7 +257,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 27, "id": "asian-wesley", "metadata": {}, "outputs": [], @@ -303,7 +301,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 28, "id": "certified-species", "metadata": {}, "outputs": [], @@ -338,7 +336,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 29, "id": "joint-dover", "metadata": {}, "outputs": [], @@ -380,7 +378,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 30, "id": "metric-wrong", "metadata": {}, "outputs": [], @@ -417,7 +415,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 31, "id": "industrial-stable", "metadata": {}, "outputs": [], @@ -450,7 +448,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 32, "id": "southwest-reset", "metadata": {}, "outputs": [], @@ -469,7 +467,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 33, "id": "occupied-danish", "metadata": {}, "outputs": [], @@ -511,7 +509,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 34, "id": "fiscal-radio", "metadata": {}, "outputs": [], @@ -532,7 +530,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 35, "id": "architectural-means", "metadata": {}, "outputs": [ @@ -540,16 +538,16 @@ "name": "stderr", "output_type": "stream", "text": [ - "2021-05-27 12:38:45,268 - [WARNING] processed_variable.get_spatial_scale(471): No length scale set for positive electrode. Using default of 1 [m].\n", - "2021-05-27 12:38:45,312 - [WARNING] processed_variable.get_spatial_scale(471): No length scale set for separator. Using default of 1 [m].\n", - "2021-05-27 12:38:45,376 - [WARNING] processed_variable.get_spatial_scale(471): No length scale set for positive electrode. Using default of 1 [m].\n", - "2021-05-27 12:38:45,426 - [WARNING] processed_variable.get_spatial_scale(471): No length scale set for positive electrode. Using default of 1 [m].\n" + "2021-11-19 15:30:23,304 - [WARNING] processed_variable.get_spatial_scale(520): No length scale set for positive electrode. Using default of 1 [m].\n", + "2021-11-19 15:30:23,328 - [WARNING] processed_variable.get_spatial_scale(520): No length scale set for separator. Using default of 1 [m].\n", + "2021-11-19 15:30:23,367 - [WARNING] processed_variable.get_spatial_scale(520): No length scale set for positive electrode. Using default of 1 [m].\n", + "2021-11-19 15:30:23,395 - [WARNING] processed_variable.get_spatial_scale(520): No length scale set for positive electrode. Using default of 1 [m].\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1a7c0c34430c4d3b813e1cdd66b5e316", + "model_id": "1d57bc29107d47838633a27df1b920cc", "version_major": 2, "version_minor": 0 }, @@ -563,10 +561,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 17, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } @@ -606,7 +604,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 36, "id": "laden-replica", "metadata": {}, "outputs": [ @@ -616,7 +614,7 @@ "text": [ "[1] Joel A. E. Andersson, Joris Gillis, Greg Horn, James B. Rawlings, and Moritz Diehl. CasADi – A software framework for nonlinear optimization and optimal control. Mathematical Programming Computation, 11(1):1–36, 2019. doi:10.1007/s12532-018-0139-4.\n", "[2] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", - "[3] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", + "[3] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", "\n" ] } @@ -636,7 +634,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -650,7 +648,20 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, diff --git a/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb b/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb index 39fe6af065..a35c147988 100644 --- a/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb +++ b/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb @@ -64,13 +64,15 @@ { "data": { "text/plain": [ - "{SpatialVariable(-0x79e01bfb9d7cff2b, x_n, children=[], domain=['negative electrode'], auxiliary_domains={'secondary': \"['current collector']\"}): 20,\n", - " SpatialVariable(0x5f7f85ca4693341d, x_s, children=[], domain=['separator'], auxiliary_domains={'secondary': \"['current collector']\"}): 20,\n", - " SpatialVariable(0x37d11455e5eb3c11, x_p, children=[], domain=['positive electrode'], auxiliary_domains={'secondary': \"['current collector']\"}): 20,\n", - " SpatialVariable(-0x773a2c9b6fa4664d, r_n, children=[], domain=['negative particle'], auxiliary_domains={'secondary': \"['negative electrode']\", 'tertiary': \"['current collector']\"}): 30,\n", - " SpatialVariable(-0x4452c7ad5cc40f52, r_p, children=[], domain=['positive particle'], auxiliary_domains={'secondary': \"['positive electrode']\", 'tertiary': \"['current collector']\"}): 30,\n", - " SpatialVariable(0x2002988a67d25c74, y, children=[], domain=['current collector'], auxiliary_domains={}): 10,\n", - " SpatialVariable(0x5fffa46b605e5d31, z, children=[], domain=['current collector'], auxiliary_domains={}): 10}" + "{'x_n': 20,\n", + " 'x_s': 20,\n", + " 'x_p': 20,\n", + " 'r_n': 20,\n", + " 'r_p': 20,\n", + " 'y': 10,\n", + " 'z': 10,\n", + " 'R_n': 30,\n", + " 'R_p': 30}" ] }, "execution_count": 3, @@ -95,16 +97,13 @@ "metadata": {}, "outputs": [], "source": [ - "# get the spatial variables used in pybamm\n", - "var = pybamm.standard_spatial_vars \n", - "\n", "# create our dictionary \n", "var_pts = {\n", - " "x_n": 10, # negative electrode\n", - " "x_s": 10, # separator \n", - " "x_p": 10, # positive electrode\n", - " "r_n": 10, # negative particle\n", - " "r_p": 10, # positive particle\n", + " \"x_n\": 10, # negative electrode\n", + " \"x_s\": 10, # separator \n", + " \"x_p\": 10, # positive electrode\n", + " \"r_n\": 10, # negative particle\n", + " \"r_p\": 10, # positive particle\n", "}" ] }, @@ -123,7 +122,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 5, @@ -151,7 +150,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c3d04e4275094bc9886db1f774f07c4d", + "model_id": "897f0b16157c4d4683006a7a4beeb748", "version_major": 2, "version_minor": 0 }, @@ -161,6 +160,16 @@ }, "metadata": {}, "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -201,7 +210,7 @@ "# choose model and parameters\n", "model = pybamm.lithium_ion.DFN()\n", "chemistry = pybamm.parameter_sets.Ecker2015\n", - "parameter_values = pybamm.ParameterValues(chemistry)\n", + "parameter_values = pybamm.ParameterValues(chemistry=chemistry)\n", "\n", "# choose solver \n", "solver = pybamm.CasadiSolver(mode=\"fast\")\n", @@ -210,11 +219,11 @@ "solutions = []\n", "for N in npts:\n", " var_pts = {\n", - " "x_n": N, # negative electrode\n", - " "x_s": N, # separator \n", - " "x_p": N, # positive electrode\n", - " "r_n": N, # negative particle\n", - " "r_p": N, # positive particle\n", + " \"x_n\": N, # negative electrode\n", + " \"x_s\": N, # separator \n", + " \"x_p\": N, # positive electrode\n", + " \"r_n\": N, # negative particle\n", + " \"r_p\": N, # positive particle\n", " } \n", " sim = pybamm.Simulation(\n", " model, solver=solver, parameter_values=parameter_values, var_pts=var_pts\n", @@ -238,7 +247,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "824a23adfb0e4858a9648b116faf0521", + "model_id": "e3b4ea06bd624d9eb817153870514a28", "version_major": 2, "version_minor": 0 }, @@ -252,7 +261,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 9, @@ -286,10 +295,12 @@ "[2] Marc Doyle, Thomas F. Fuller, and John Newman. Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell. Journal of the Electrochemical society, 140(6):1526–1533, 1993. doi:10.1149/1.2221597.\n", "[3] Madeleine Ecker, Stefan Käbitz, Izaro Laresgoiti, and Dirk Uwe Sauer. Parameterization of a Physico-Chemical Model of a Lithium-Ion Battery: II. Model Validation. Journal of The Electrochemical Society, 162(9):A1849–A1857, 2015. doi:10.1149/2.0541509jes.\n", "[4] Madeleine Ecker, Thi Kim Dung Tran, Philipp Dechent, Stefan Käbitz, Alexander Warnecke, and Dirk Uwe Sauer. Parameterization of a Physico-Chemical Model of a Lithium-Ion Battery: I. Determination of Parameters. Journal of the Electrochemical Society, 162(9):A1836–A1848, 2015. doi:10.1149/2.0551509jes.\n", - "[5] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", - "[6] Scott G. Marquis, Valentin Sulzer, Robert Timms, Colin P. Please, and S. Jon Chapman. An asymptotic derivation of a single particle model with electrolyte. Journal of The Electrochemical Society, 166(15):A3693–A3706, 2019. doi:10.1149/2.0341915jes.\n", - "[7] Giles Richardson, Ivan Korotkin, Rahifa Ranom, Michael Castle, and Jamie M. Foster. Generalised single particle models for high-rate operation of graded lithium-ion electrodes: systematic derivation and validation. Electrochimica Acta, 339:135862, 2020. doi:10.1016/j.electacta.2020.135862.\n", - "[8] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", + "[5] Alastair Hales, Laura Bravo Diaz, Mohamed Waseem Marzook, Yan Zhao, Yatish Patel, and Gregory Offer. The cell cooling coefficient: a standard to define heat rejection from lithium-ion batteries. Journal of The Electrochemical Society, 166(12):A2383, 2019.\n", + "[6] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", + "[7] Scott G. Marquis, Valentin Sulzer, Robert Timms, Colin P. Please, and S. Jon Chapman. An asymptotic derivation of a single particle model with electrolyte. Journal of The Electrochemical Society, 166(15):A3693–A3706, 2019. doi:10.1149/2.0341915jes.\n", + "[8] Giles Richardson, Ivan Korotkin, Rahifa Ranom, Michael Castle, and Jamie M. Foster. Generalised single particle models for high-rate operation of graded lithium-ion electrodes: systematic derivation and validation. Electrochimica Acta, 339:135862, 2020. doi:10.1016/j.electacta.2020.135862.\n", + "[9] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", + "[10] Yan Zhao, Yatish Patel, Teng Zhang, and Gregory J Offer. Modeling the effects of thermal gradients induced by tab and surface cooling on lithium ion cell performance. Journal of The Electrochemical Society, 165(13):A3169, 2018.\n", "\n" ] } @@ -301,7 +312,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -315,7 +326,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.12" }, "toc": { "base_numbering": 1, diff --git a/examples/notebooks/batch_study.ipynb b/examples/notebooks/batch_study.ipynb index d8529662b1..76323600c7 100644 --- a/examples/notebooks/batch_study.ipynb +++ b/examples/notebooks/batch_study.ipynb @@ -21,7 +21,15 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], "source": [ "%pip install pybamm -q # install PyBaMM if it is not installed\n", "import pybamm\n", @@ -47,7 +55,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d8386d45232642dc8b60557abb3f3c36", + "model_id": "11ef47538e7b48a389a158a757004dfe", "version_major": 2, "version_minor": 0 }, @@ -61,7 +69,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 2, @@ -101,12 +109,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "df30b96e9e6f49b8933e6b992c11773f", + "model_id": "d0189a6cb4b74295a8c0477d9f88eb99", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "interactive(children=(FloatSlider(value=0.0, description='t', max=3566.800904290021, step=35.66800904290021), …" + "interactive(children=(FloatSlider(value=0.0, description='t', max=3567.8551657209678, step=35.67855165720968),…" ] }, "metadata": {}, @@ -115,7 +123,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 3, @@ -125,8 +133,7 @@ ], "source": [ "# passing parameter_values as a dictionary\n", - "chen2020 = pybamm.parameter_sets.Chen2020\n", - "parameter_values = {\"Chen2020\": pybamm.ParameterValues(chen2020)}\n", + "parameter_values = {\"Chen2020\": pybamm.ParameterValues(\"Chen2020\")}\n", "\n", "# creating a BatchStudy object and solving the simulation\n", "batch_study = pybamm.BatchStudy(models=models, parameter_values=parameter_values, permutations=True)\n", @@ -153,7 +160,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0ba1d7339bc54133ae8b997ed08162d9", + "model_id": "11b054dc030f4b98998ec440b887f1d2", "version_major": 2, "version_minor": 0 }, @@ -167,7 +174,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 4, @@ -180,9 +187,9 @@ "\n", "# populating a dictionary with 3 same parameter values\n", "parameter_values = {\n", - " \"Chen2020_1\": pybamm.ParameterValues(chen2020),\n", - " \"Chen2020_2\": pybamm.ParameterValues(chen2020),\n", - " \"Chen2020_3\": pybamm.ParameterValues(chen2020),\n", + " \"Chen2020_1\": pybamm.ParameterValues(\"Chen2020\"),\n", + " \"Chen2020_2\": pybamm.ParameterValues(\"Chen2020\"),\n", + " \"Chen2020_3\": pybamm.ParameterValues(\"Chen2020\"),\n", "}\n", "\n", "# different values for \"Current function [A]\"\n", @@ -224,212 +231,212 @@ "name": "stderr", "output_type": "stream", "text": [ - "2021-10-16 01:20:49,651 - [NOTICE] simulation.solve(809): Cycle 1/10 (32.710 ms elapsed) --------------------\n", - "2021-10-16 01:20:49,654 - [NOTICE] simulation.solve(843): Cycle 1/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:49,864 - [NOTICE] simulation.solve(843): Cycle 1/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:49,901 - [NOTICE] simulation.solve(843): Cycle 1/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:50,008 - [NOTICE] simulation.solve(843): Cycle 1/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:50,058 - [NOTICE] simulation.solve(843): Cycle 1/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:50,276 - [NOTICE] simulation.solve(809): Cycle 2/10 (657.744 ms elapsed) --------------------\n", - "2021-10-16 01:20:50,277 - [NOTICE] simulation.solve(843): Cycle 2/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:50,446 - [NOTICE] simulation.solve(843): Cycle 2/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:50,468 - [NOTICE] simulation.solve(843): Cycle 2/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:50,556 - [NOTICE] simulation.solve(843): Cycle 2/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:50,573 - [NOTICE] simulation.solve(843): Cycle 2/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:50,628 - [NOTICE] simulation.solve(809): Cycle 3/10 (1.009 s elapsed) --------------------\n", - "2021-10-16 01:20:50,629 - [NOTICE] simulation.solve(843): Cycle 3/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:50,949 - [NOTICE] simulation.solve(843): Cycle 3/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:50,975 - [NOTICE] simulation.solve(843): Cycle 3/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:51,066 - [NOTICE] simulation.solve(843): Cycle 3/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:51,083 - [NOTICE] simulation.solve(843): Cycle 3/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:51,137 - [NOTICE] simulation.solve(809): Cycle 4/10 (1.519 s elapsed) --------------------\n", - "2021-10-16 01:20:51,138 - [NOTICE] simulation.solve(843): Cycle 4/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:51,310 - [NOTICE] simulation.solve(843): Cycle 4/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:51,333 - [NOTICE] simulation.solve(843): Cycle 4/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:51,421 - [NOTICE] simulation.solve(843): Cycle 4/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:51,439 - [NOTICE] simulation.solve(843): Cycle 4/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:51,495 - [NOTICE] simulation.solve(809): Cycle 5/10 (1.877 s elapsed) --------------------\n", - "2021-10-16 01:20:51,497 - [NOTICE] simulation.solve(843): Cycle 5/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:51,666 - [NOTICE] simulation.solve(843): Cycle 5/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:51,690 - [NOTICE] simulation.solve(843): Cycle 5/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:51,776 - [NOTICE] simulation.solve(843): Cycle 5/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:51,794 - [NOTICE] simulation.solve(843): Cycle 5/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:51,849 - [NOTICE] simulation.solve(809): Cycle 6/10 (2.231 s elapsed) --------------------\n", - "2021-10-16 01:20:51,850 - [NOTICE] simulation.solve(843): Cycle 6/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:52,025 - [NOTICE] simulation.solve(843): Cycle 6/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:52,050 - [NOTICE] simulation.solve(843): Cycle 6/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:52,146 - [NOTICE] simulation.solve(843): Cycle 6/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:52,164 - [NOTICE] simulation.solve(843): Cycle 6/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:52,218 - [NOTICE] simulation.solve(809): Cycle 7/10 (2.600 s elapsed) --------------------\n", - "2021-10-16 01:20:52,218 - [NOTICE] simulation.solve(843): Cycle 7/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:52,389 - [NOTICE] simulation.solve(843): Cycle 7/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:52,412 - [NOTICE] simulation.solve(843): Cycle 7/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:52,501 - [NOTICE] simulation.solve(843): Cycle 7/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:52,516 - [NOTICE] simulation.solve(843): Cycle 7/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:52,571 - [NOTICE] simulation.solve(809): Cycle 8/10 (2.953 s elapsed) --------------------\n", - "2021-10-16 01:20:52,572 - [NOTICE] simulation.solve(843): Cycle 8/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:52,743 - [NOTICE] simulation.solve(843): Cycle 8/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:52,769 - [NOTICE] simulation.solve(843): Cycle 8/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:52,862 - [NOTICE] simulation.solve(843): Cycle 8/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:52,881 - [NOTICE] simulation.solve(843): Cycle 8/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:52,936 - [NOTICE] simulation.solve(809): Cycle 9/10 (3.318 s elapsed) --------------------\n", - "2021-10-16 01:20:52,937 - [NOTICE] simulation.solve(843): Cycle 9/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:53,117 - [NOTICE] simulation.solve(843): Cycle 9/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:53,139 - [NOTICE] simulation.solve(843): Cycle 9/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:53,233 - [NOTICE] simulation.solve(843): Cycle 9/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:53,251 - [NOTICE] simulation.solve(843): Cycle 9/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:53,309 - [NOTICE] simulation.solve(809): Cycle 10/10 (3.691 s elapsed) --------------------\n", - "2021-10-16 01:20:53,310 - [NOTICE] simulation.solve(843): Cycle 10/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:53,485 - [NOTICE] simulation.solve(843): Cycle 10/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:53,505 - [NOTICE] simulation.solve(843): Cycle 10/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:53,599 - [NOTICE] simulation.solve(843): Cycle 10/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:53,619 - [NOTICE] simulation.solve(843): Cycle 10/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:53,689 - [NOTICE] simulation.solve(938): Finish experiment simulation, took 4.071 s\n", - "2021-10-16 01:20:55,999 - [NOTICE] simulation.solve(809): Cycle 1/10 (30.949 ms elapsed) --------------------\n", - "2021-10-16 01:20:56,000 - [NOTICE] simulation.solve(843): Cycle 1/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:56,201 - [NOTICE] simulation.solve(843): Cycle 1/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:56,239 - [NOTICE] simulation.solve(843): Cycle 1/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:56,353 - [NOTICE] simulation.solve(843): Cycle 1/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:56,404 - [NOTICE] simulation.solve(843): Cycle 1/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:56,629 - [NOTICE] simulation.solve(809): Cycle 2/10 (660.465 ms elapsed) --------------------\n", - "2021-10-16 01:20:56,630 - [NOTICE] simulation.solve(843): Cycle 2/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:56,804 - [NOTICE] simulation.solve(843): Cycle 2/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:56,827 - [NOTICE] simulation.solve(843): Cycle 2/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:56,926 - [NOTICE] simulation.solve(843): Cycle 2/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:56,944 - [NOTICE] simulation.solve(843): Cycle 2/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:57,003 - [NOTICE] simulation.solve(809): Cycle 3/10 (1.034 s elapsed) --------------------\n", - "2021-10-16 01:20:57,004 - [NOTICE] simulation.solve(843): Cycle 3/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:57,198 - [NOTICE] simulation.solve(843): Cycle 3/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:57,222 - [NOTICE] simulation.solve(843): Cycle 3/10, step 3/5: Charge at 1 A until 4.1 V\n" + "2021-11-19 15:27:32,325 - [NOTICE] simulation.solve(850): Cycle 1/10 (24.445 ms elapsed) --------------------\n", + "2021-11-19 15:27:32,326 - [NOTICE] simulation.solve(884): Cycle 1/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:32,488 - [NOTICE] simulation.solve(884): Cycle 1/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:32,518 - [NOTICE] simulation.solve(884): Cycle 1/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:32,606 - [NOTICE] simulation.solve(884): Cycle 1/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:32,648 - [NOTICE] simulation.solve(884): Cycle 1/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:32,824 - [NOTICE] simulation.solve(850): Cycle 2/10 (523.340 ms elapsed) --------------------\n", + "2021-11-19 15:27:32,824 - [NOTICE] simulation.solve(884): Cycle 2/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:32,963 - [NOTICE] simulation.solve(884): Cycle 2/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:32,979 - [NOTICE] simulation.solve(884): Cycle 2/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:33,051 - [NOTICE] simulation.solve(884): Cycle 2/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:33,064 - [NOTICE] simulation.solve(884): Cycle 2/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:33,110 - [NOTICE] simulation.solve(850): Cycle 3/10 (809.460 ms elapsed) --------------------\n", + "2021-11-19 15:27:33,111 - [NOTICE] simulation.solve(884): Cycle 3/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:33,247 - [NOTICE] simulation.solve(884): Cycle 3/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:33,265 - [NOTICE] simulation.solve(884): Cycle 3/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:33,338 - [NOTICE] simulation.solve(884): Cycle 3/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:33,351 - [NOTICE] simulation.solve(884): Cycle 3/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:33,398 - [NOTICE] simulation.solve(850): Cycle 4/10 (1.097 s elapsed) --------------------\n", + "2021-11-19 15:27:33,398 - [NOTICE] simulation.solve(884): Cycle 4/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:33,536 - [NOTICE] simulation.solve(884): Cycle 4/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:33,553 - [NOTICE] simulation.solve(884): Cycle 4/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:33,625 - [NOTICE] simulation.solve(884): Cycle 4/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:33,638 - [NOTICE] simulation.solve(884): Cycle 4/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:33,685 - [NOTICE] simulation.solve(850): Cycle 5/10 (1.384 s elapsed) --------------------\n", + "2021-11-19 15:27:33,685 - [NOTICE] simulation.solve(884): Cycle 5/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:33,947 - [NOTICE] simulation.solve(884): Cycle 5/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:33,965 - [NOTICE] simulation.solve(884): Cycle 5/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:34,037 - [NOTICE] simulation.solve(884): Cycle 5/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:34,051 - [NOTICE] simulation.solve(884): Cycle 5/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:34,099 - [NOTICE] simulation.solve(850): Cycle 6/10 (1.798 s elapsed) --------------------\n", + "2021-11-19 15:27:34,100 - [NOTICE] simulation.solve(884): Cycle 6/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:34,240 - [NOTICE] simulation.solve(884): Cycle 6/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:34,257 - [NOTICE] simulation.solve(884): Cycle 6/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:34,339 - [NOTICE] simulation.solve(884): Cycle 6/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:34,353 - [NOTICE] simulation.solve(884): Cycle 6/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:34,401 - [NOTICE] simulation.solve(850): Cycle 7/10 (2.101 s elapsed) --------------------\n", + "2021-11-19 15:27:34,402 - [NOTICE] simulation.solve(884): Cycle 7/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:34,540 - [NOTICE] simulation.solve(884): Cycle 7/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:34,557 - [NOTICE] simulation.solve(884): Cycle 7/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:34,629 - [NOTICE] simulation.solve(884): Cycle 7/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:34,645 - [NOTICE] simulation.solve(884): Cycle 7/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:34,694 - [NOTICE] simulation.solve(850): Cycle 8/10 (2.393 s elapsed) --------------------\n", + "2021-11-19 15:27:34,694 - [NOTICE] simulation.solve(884): Cycle 8/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:34,834 - [NOTICE] simulation.solve(884): Cycle 8/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:34,851 - [NOTICE] simulation.solve(884): Cycle 8/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:34,924 - [NOTICE] simulation.solve(884): Cycle 8/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:34,937 - [NOTICE] simulation.solve(884): Cycle 8/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:34,985 - [NOTICE] simulation.solve(850): Cycle 9/10 (2.684 s elapsed) --------------------\n", + "2021-11-19 15:27:34,985 - [NOTICE] simulation.solve(884): Cycle 9/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:35,123 - [NOTICE] simulation.solve(884): Cycle 9/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:35,141 - [NOTICE] simulation.solve(884): Cycle 9/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:35,216 - [NOTICE] simulation.solve(884): Cycle 9/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:35,229 - [NOTICE] simulation.solve(884): Cycle 9/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:35,277 - [NOTICE] simulation.solve(850): Cycle 10/10 (2.976 s elapsed) --------------------\n", + "2021-11-19 15:27:35,278 - [NOTICE] simulation.solve(884): Cycle 10/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:35,415 - [NOTICE] simulation.solve(884): Cycle 10/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:35,433 - [NOTICE] simulation.solve(884): Cycle 10/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:35,508 - [NOTICE] simulation.solve(884): Cycle 10/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:35,522 - [NOTICE] simulation.solve(884): Cycle 10/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:35,569 - [NOTICE] simulation.solve(990): Finish experiment simulation, took 3.268 s\n", + "2021-11-19 15:27:37,125 - [NOTICE] simulation.solve(850): Cycle 1/10 (24.831 ms elapsed) --------------------\n", + "2021-11-19 15:27:37,125 - [NOTICE] simulation.solve(884): Cycle 1/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:37,287 - [NOTICE] simulation.solve(884): Cycle 1/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:37,316 - [NOTICE] simulation.solve(884): Cycle 1/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:37,405 - [NOTICE] simulation.solve(884): Cycle 1/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:37,444 - [NOTICE] simulation.solve(884): Cycle 1/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:37,780 - [NOTICE] simulation.solve(850): Cycle 2/10 (679.526 ms elapsed) --------------------\n", + "2021-11-19 15:27:37,780 - [NOTICE] simulation.solve(884): Cycle 2/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:37,920 - [NOTICE] simulation.solve(884): Cycle 2/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:37,936 - [NOTICE] simulation.solve(884): Cycle 2/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:38,012 - [NOTICE] simulation.solve(884): Cycle 2/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:38,025 - [NOTICE] simulation.solve(884): Cycle 2/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:38,072 - [NOTICE] simulation.solve(850): Cycle 3/10 (971.448 ms elapsed) --------------------\n", + "2021-11-19 15:27:38,072 - [NOTICE] simulation.solve(884): Cycle 3/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:38,210 - [NOTICE] simulation.solve(884): Cycle 3/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:38,227 - [NOTICE] simulation.solve(884): Cycle 3/10, step 3/5: Charge at 1 A until 4.1 V\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-10-16 01:20:57,316 - [NOTICE] simulation.solve(843): Cycle 3/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:57,332 - [NOTICE] simulation.solve(843): Cycle 3/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:57,386 - [NOTICE] simulation.solve(809): Cycle 4/10 (1.417 s elapsed) --------------------\n", - "2021-10-16 01:20:57,387 - [NOTICE] simulation.solve(843): Cycle 4/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:57,563 - [NOTICE] simulation.solve(843): Cycle 4/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:57,585 - [NOTICE] simulation.solve(843): Cycle 4/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:57,672 - [NOTICE] simulation.solve(843): Cycle 4/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:57,689 - [NOTICE] simulation.solve(843): Cycle 4/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:57,744 - [NOTICE] simulation.solve(809): Cycle 5/10 (1.775 s elapsed) --------------------\n", - "2021-10-16 01:20:57,744 - [NOTICE] simulation.solve(843): Cycle 5/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:57,916 - [NOTICE] simulation.solve(843): Cycle 5/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:57,939 - [NOTICE] simulation.solve(843): Cycle 5/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:58,028 - [NOTICE] simulation.solve(843): Cycle 5/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:58,045 - [NOTICE] simulation.solve(843): Cycle 5/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:58,099 - [NOTICE] simulation.solve(809): Cycle 6/10 (2.131 s elapsed) --------------------\n", - "2021-10-16 01:20:58,100 - [NOTICE] simulation.solve(843): Cycle 6/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:58,278 - [NOTICE] simulation.solve(843): Cycle 6/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:58,301 - [NOTICE] simulation.solve(843): Cycle 6/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:58,396 - [NOTICE] simulation.solve(843): Cycle 6/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:58,415 - [NOTICE] simulation.solve(843): Cycle 6/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:58,472 - [NOTICE] simulation.solve(809): Cycle 7/10 (2.504 s elapsed) --------------------\n", - "2021-10-16 01:20:58,473 - [NOTICE] simulation.solve(843): Cycle 7/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:58,642 - [NOTICE] simulation.solve(843): Cycle 7/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:58,666 - [NOTICE] simulation.solve(843): Cycle 7/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:58,758 - [NOTICE] simulation.solve(843): Cycle 7/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:58,776 - [NOTICE] simulation.solve(843): Cycle 7/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:58,831 - [NOTICE] simulation.solve(809): Cycle 8/10 (2.862 s elapsed) --------------------\n", - "2021-10-16 01:20:58,832 - [NOTICE] simulation.solve(843): Cycle 8/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:59,006 - [NOTICE] simulation.solve(843): Cycle 8/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:59,032 - [NOTICE] simulation.solve(843): Cycle 8/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:59,129 - [NOTICE] simulation.solve(843): Cycle 8/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:59,147 - [NOTICE] simulation.solve(843): Cycle 8/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:59,210 - [NOTICE] simulation.solve(809): Cycle 9/10 (3.242 s elapsed) --------------------\n", - "2021-10-16 01:20:59,211 - [NOTICE] simulation.solve(843): Cycle 9/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:59,382 - [NOTICE] simulation.solve(843): Cycle 9/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:59,404 - [NOTICE] simulation.solve(843): Cycle 9/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:59,494 - [NOTICE] simulation.solve(843): Cycle 9/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:59,512 - [NOTICE] simulation.solve(843): Cycle 9/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:59,570 - [NOTICE] simulation.solve(809): Cycle 10/10 (3.601 s elapsed) --------------------\n", - "2021-10-16 01:20:59,570 - [NOTICE] simulation.solve(843): Cycle 10/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:20:59,751 - [NOTICE] simulation.solve(843): Cycle 10/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:20:59,774 - [NOTICE] simulation.solve(843): Cycle 10/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:20:59,873 - [NOTICE] simulation.solve(843): Cycle 10/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:20:59,894 - [NOTICE] simulation.solve(843): Cycle 10/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:20:59,953 - [NOTICE] simulation.solve(938): Finish experiment simulation, took 3.984 s\n", - "2021-10-16 01:21:02,384 - [NOTICE] simulation.solve(809): Cycle 1/10 (31.196 ms elapsed) --------------------\n", - "2021-10-16 01:21:02,384 - [NOTICE] simulation.solve(843): Cycle 1/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:21:02,602 - [NOTICE] simulation.solve(843): Cycle 1/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:21:02,639 - [NOTICE] simulation.solve(843): Cycle 1/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:21:02,751 - [NOTICE] simulation.solve(843): Cycle 1/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:21:02,799 - [NOTICE] simulation.solve(843): Cycle 1/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:21:03,037 - [NOTICE] simulation.solve(809): Cycle 2/10 (684.004 ms elapsed) --------------------\n", - "2021-10-16 01:21:03,038 - [NOTICE] simulation.solve(843): Cycle 2/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:21:03,219 - [NOTICE] simulation.solve(843): Cycle 2/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:21:03,244 - [NOTICE] simulation.solve(843): Cycle 2/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:21:03,344 - [NOTICE] simulation.solve(843): Cycle 2/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:21:03,362 - [NOTICE] simulation.solve(843): Cycle 2/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:21:03,418 - [NOTICE] simulation.solve(809): Cycle 3/10 (1.065 s elapsed) --------------------\n", - "2021-10-16 01:21:03,419 - [NOTICE] simulation.solve(843): Cycle 3/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:21:03,596 - [NOTICE] simulation.solve(843): Cycle 3/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:21:03,620 - [NOTICE] simulation.solve(843): Cycle 3/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:21:03,711 - [NOTICE] simulation.solve(843): Cycle 3/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:21:03,727 - [NOTICE] simulation.solve(843): Cycle 3/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:21:03,782 - [NOTICE] simulation.solve(809): Cycle 4/10 (1.430 s elapsed) --------------------\n", - "2021-10-16 01:21:03,784 - [NOTICE] simulation.solve(843): Cycle 4/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:21:03,965 - [NOTICE] simulation.solve(843): Cycle 4/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:21:03,987 - [NOTICE] simulation.solve(843): Cycle 4/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:21:04,084 - [NOTICE] simulation.solve(843): Cycle 4/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:21:04,102 - [NOTICE] simulation.solve(843): Cycle 4/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:21:04,154 - [NOTICE] simulation.solve(809): Cycle 5/10 (1.802 s elapsed) --------------------\n", - "2021-10-16 01:21:04,155 - [NOTICE] simulation.solve(843): Cycle 5/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:21:04,328 - [NOTICE] simulation.solve(843): Cycle 5/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:21:04,354 - [NOTICE] simulation.solve(843): Cycle 5/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:21:04,452 - [NOTICE] simulation.solve(843): Cycle 5/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:21:04,469 - [NOTICE] simulation.solve(843): Cycle 5/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:21:04,526 - [NOTICE] simulation.solve(809): Cycle 6/10 (2.174 s elapsed) --------------------\n", - "2021-10-16 01:21:04,527 - [NOTICE] simulation.solve(843): Cycle 6/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n" + "2021-11-19 15:27:38,298 - [NOTICE] simulation.solve(884): Cycle 3/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:38,314 - [NOTICE] simulation.solve(884): Cycle 3/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:38,362 - [NOTICE] simulation.solve(850): Cycle 4/10 (1.261 s elapsed) --------------------\n", + "2021-11-19 15:27:38,362 - [NOTICE] simulation.solve(884): Cycle 4/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:38,501 - [NOTICE] simulation.solve(884): Cycle 4/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:38,517 - [NOTICE] simulation.solve(884): Cycle 4/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:38,589 - [NOTICE] simulation.solve(884): Cycle 4/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:38,604 - [NOTICE] simulation.solve(884): Cycle 4/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:38,650 - [NOTICE] simulation.solve(850): Cycle 5/10 (1.549 s elapsed) --------------------\n", + "2021-11-19 15:27:38,650 - [NOTICE] simulation.solve(884): Cycle 5/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:38,788 - [NOTICE] simulation.solve(884): Cycle 5/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:38,806 - [NOTICE] simulation.solve(884): Cycle 5/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:38,877 - [NOTICE] simulation.solve(884): Cycle 5/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:38,892 - [NOTICE] simulation.solve(884): Cycle 5/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:38,940 - [NOTICE] simulation.solve(850): Cycle 6/10 (1.840 s elapsed) --------------------\n", + "2021-11-19 15:27:38,941 - [NOTICE] simulation.solve(884): Cycle 6/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:39,081 - [NOTICE] simulation.solve(884): Cycle 6/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:39,099 - [NOTICE] simulation.solve(884): Cycle 6/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:39,174 - [NOTICE] simulation.solve(884): Cycle 6/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:39,191 - [NOTICE] simulation.solve(884): Cycle 6/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:39,236 - [NOTICE] simulation.solve(850): Cycle 7/10 (2.136 s elapsed) --------------------\n", + "2021-11-19 15:27:39,237 - [NOTICE] simulation.solve(884): Cycle 7/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:39,381 - [NOTICE] simulation.solve(884): Cycle 7/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:39,399 - [NOTICE] simulation.solve(884): Cycle 7/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:39,473 - [NOTICE] simulation.solve(884): Cycle 7/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:39,487 - [NOTICE] simulation.solve(884): Cycle 7/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:39,532 - [NOTICE] simulation.solve(850): Cycle 8/10 (2.432 s elapsed) --------------------\n", + "2021-11-19 15:27:39,533 - [NOTICE] simulation.solve(884): Cycle 8/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:39,676 - [NOTICE] simulation.solve(884): Cycle 8/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:39,693 - [NOTICE] simulation.solve(884): Cycle 8/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:39,767 - [NOTICE] simulation.solve(884): Cycle 8/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:39,781 - [NOTICE] simulation.solve(884): Cycle 8/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:39,829 - [NOTICE] simulation.solve(850): Cycle 9/10 (2.729 s elapsed) --------------------\n", + "2021-11-19 15:27:39,829 - [NOTICE] simulation.solve(884): Cycle 9/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:39,972 - [NOTICE] simulation.solve(884): Cycle 9/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:39,989 - [NOTICE] simulation.solve(884): Cycle 9/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:40,065 - [NOTICE] simulation.solve(884): Cycle 9/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:40,078 - [NOTICE] simulation.solve(884): Cycle 9/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:40,126 - [NOTICE] simulation.solve(850): Cycle 10/10 (3.025 s elapsed) --------------------\n", + "2021-11-19 15:27:40,126 - [NOTICE] simulation.solve(884): Cycle 10/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:40,271 - [NOTICE] simulation.solve(884): Cycle 10/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:40,288 - [NOTICE] simulation.solve(884): Cycle 10/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:40,362 - [NOTICE] simulation.solve(884): Cycle 10/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:40,376 - [NOTICE] simulation.solve(884): Cycle 10/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:40,422 - [NOTICE] simulation.solve(990): Finish experiment simulation, took 3.322 s\n", + "2021-11-19 15:27:42,083 - [NOTICE] simulation.solve(850): Cycle 1/10 (25.393 ms elapsed) --------------------\n", + "2021-11-19 15:27:42,083 - [NOTICE] simulation.solve(884): Cycle 1/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:42,249 - [NOTICE] simulation.solve(884): Cycle 1/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:42,280 - [NOTICE] simulation.solve(884): Cycle 1/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:42,370 - [NOTICE] simulation.solve(884): Cycle 1/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:42,413 - [NOTICE] simulation.solve(884): Cycle 1/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:42,591 - [NOTICE] simulation.solve(850): Cycle 2/10 (533.619 ms elapsed) --------------------\n", + "2021-11-19 15:27:42,591 - [NOTICE] simulation.solve(884): Cycle 2/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:42,732 - [NOTICE] simulation.solve(884): Cycle 2/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:42,749 - [NOTICE] simulation.solve(884): Cycle 2/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:42,824 - [NOTICE] simulation.solve(884): Cycle 2/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:42,838 - [NOTICE] simulation.solve(884): Cycle 2/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:42,883 - [NOTICE] simulation.solve(850): Cycle 3/10 (825.928 ms elapsed) --------------------\n", + "2021-11-19 15:27:42,884 - [NOTICE] simulation.solve(884): Cycle 3/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:43,025 - [NOTICE] simulation.solve(884): Cycle 3/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:43,042 - [NOTICE] simulation.solve(884): Cycle 3/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:43,118 - [NOTICE] simulation.solve(884): Cycle 3/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:43,131 - [NOTICE] simulation.solve(884): Cycle 3/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:43,177 - [NOTICE] simulation.solve(850): Cycle 4/10 (1.120 s elapsed) --------------------\n", + "2021-11-19 15:27:43,177 - [NOTICE] simulation.solve(884): Cycle 4/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:43,321 - [NOTICE] simulation.solve(884): Cycle 4/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:43,340 - [NOTICE] simulation.solve(884): Cycle 4/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:43,418 - [NOTICE] simulation.solve(884): Cycle 4/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:43,433 - [NOTICE] simulation.solve(884): Cycle 4/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:43,481 - [NOTICE] simulation.solve(850): Cycle 5/10 (1.424 s elapsed) --------------------\n", + "2021-11-19 15:27:43,481 - [NOTICE] simulation.solve(884): Cycle 5/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:43,623 - [NOTICE] simulation.solve(884): Cycle 5/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:43,641 - [NOTICE] simulation.solve(884): Cycle 5/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:43,717 - [NOTICE] simulation.solve(884): Cycle 5/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:43,732 - [NOTICE] simulation.solve(884): Cycle 5/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:43,779 - [NOTICE] simulation.solve(850): Cycle 6/10 (1.722 s elapsed) --------------------\n", + "2021-11-19 15:27:43,780 - [NOTICE] simulation.solve(884): Cycle 6/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-10-16 01:21:04,704 - [NOTICE] simulation.solve(843): Cycle 6/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:21:04,728 - [NOTICE] simulation.solve(843): Cycle 6/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:21:04,818 - [NOTICE] simulation.solve(843): Cycle 6/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:21:04,834 - [NOTICE] simulation.solve(843): Cycle 6/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:21:04,888 - [NOTICE] simulation.solve(809): Cycle 7/10 (2.536 s elapsed) --------------------\n", - "2021-10-16 01:21:04,889 - [NOTICE] simulation.solve(843): Cycle 7/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:21:05,061 - [NOTICE] simulation.solve(843): Cycle 7/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:21:05,084 - [NOTICE] simulation.solve(843): Cycle 7/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:21:05,172 - [NOTICE] simulation.solve(843): Cycle 7/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:21:05,192 - [NOTICE] simulation.solve(843): Cycle 7/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:21:05,246 - [NOTICE] simulation.solve(809): Cycle 8/10 (2.893 s elapsed) --------------------\n", - "2021-10-16 01:21:05,246 - [NOTICE] simulation.solve(843): Cycle 8/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:21:05,418 - [NOTICE] simulation.solve(843): Cycle 8/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:21:05,441 - [NOTICE] simulation.solve(843): Cycle 8/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:21:05,531 - [NOTICE] simulation.solve(843): Cycle 8/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:21:05,548 - [NOTICE] simulation.solve(843): Cycle 8/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:21:05,602 - [NOTICE] simulation.solve(809): Cycle 9/10 (3.250 s elapsed) --------------------\n", - "2021-10-16 01:21:05,603 - [NOTICE] simulation.solve(843): Cycle 9/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:21:05,777 - [NOTICE] simulation.solve(843): Cycle 9/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:21:05,800 - [NOTICE] simulation.solve(843): Cycle 9/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:21:05,901 - [NOTICE] simulation.solve(843): Cycle 9/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:21:05,918 - [NOTICE] simulation.solve(843): Cycle 9/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:21:05,979 - [NOTICE] simulation.solve(809): Cycle 10/10 (3.627 s elapsed) --------------------\n", - "2021-10-16 01:21:05,979 - [NOTICE] simulation.solve(843): Cycle 10/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", - "2021-10-16 01:21:06,161 - [NOTICE] simulation.solve(843): Cycle 10/10, step 2/5: Rest for 1 hour\n", - "2021-10-16 01:21:06,183 - [NOTICE] simulation.solve(843): Cycle 10/10, step 3/5: Charge at 1 A until 4.1 V\n", - "2021-10-16 01:21:06,272 - [NOTICE] simulation.solve(843): Cycle 10/10, step 4/5: Hold at 4.1 V until 50 mA\n", - "2021-10-16 01:21:06,290 - [NOTICE] simulation.solve(843): Cycle 10/10, step 5/5: Rest for 1 hour\n", - "2021-10-16 01:21:06,346 - [NOTICE] simulation.solve(938): Finish experiment simulation, took 3.995 s\n" + "2021-11-19 15:27:43,921 - [NOTICE] simulation.solve(884): Cycle 6/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:43,938 - [NOTICE] simulation.solve(884): Cycle 6/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:44,019 - [NOTICE] simulation.solve(884): Cycle 6/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:44,036 - [NOTICE] simulation.solve(884): Cycle 6/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:44,084 - [NOTICE] simulation.solve(850): Cycle 7/10 (2.027 s elapsed) --------------------\n", + "2021-11-19 15:27:44,084 - [NOTICE] simulation.solve(884): Cycle 7/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:44,229 - [NOTICE] simulation.solve(884): Cycle 7/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:44,247 - [NOTICE] simulation.solve(884): Cycle 7/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:44,321 - [NOTICE] simulation.solve(884): Cycle 7/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:44,335 - [NOTICE] simulation.solve(884): Cycle 7/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:44,381 - [NOTICE] simulation.solve(850): Cycle 8/10 (2.324 s elapsed) --------------------\n", + "2021-11-19 15:27:44,382 - [NOTICE] simulation.solve(884): Cycle 8/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:44,747 - [NOTICE] simulation.solve(884): Cycle 8/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:44,764 - [NOTICE] simulation.solve(884): Cycle 8/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:44,839 - [NOTICE] simulation.solve(884): Cycle 8/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:44,853 - [NOTICE] simulation.solve(884): Cycle 8/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:44,901 - [NOTICE] simulation.solve(850): Cycle 9/10 (2.843 s elapsed) --------------------\n", + "2021-11-19 15:27:44,901 - [NOTICE] simulation.solve(884): Cycle 9/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:45,041 - [NOTICE] simulation.solve(884): Cycle 9/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:45,059 - [NOTICE] simulation.solve(884): Cycle 9/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:45,136 - [NOTICE] simulation.solve(884): Cycle 9/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:45,152 - [NOTICE] simulation.solve(884): Cycle 9/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:45,198 - [NOTICE] simulation.solve(850): Cycle 10/10 (3.141 s elapsed) --------------------\n", + "2021-11-19 15:27:45,199 - [NOTICE] simulation.solve(884): Cycle 10/10, step 1/5: Discharge at C/10 for 10 hours or until 3.3 V\n", + "2021-11-19 15:27:45,342 - [NOTICE] simulation.solve(884): Cycle 10/10, step 2/5: Rest for 1 hour\n", + "2021-11-19 15:27:45,359 - [NOTICE] simulation.solve(884): Cycle 10/10, step 3/5: Charge at 1 A until 4.1 V\n", + "2021-11-19 15:27:45,436 - [NOTICE] simulation.solve(884): Cycle 10/10, step 4/5: Hold at 4.1 V until 50 mA\n", + "2021-11-19 15:27:45,450 - [NOTICE] simulation.solve(884): Cycle 10/10, step 5/5: Rest for 1 hour\n", + "2021-11-19 15:27:45,497 - [NOTICE] simulation.solve(990): Finish experiment simulation, took 3.440 s\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f2b139e02ff5491081de37e4257a7391", + "model_id": "36b493a7e09c4a42a5f24d787a9e23c6", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "interactive(children=(FloatSlider(value=0.0, description='t', max=155.67614578899756, step=1.5567614578899756)…" + "interactive(children=(FloatSlider(value=0.0, description='t', max=155.71556450330675, step=1.5571556450330675)…" ] }, "metadata": {}, @@ -438,7 +445,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 5, @@ -469,9 +476,9 @@ "# populating a dictionary with 3 same parameter values (Mohtat2020 chemistry)\n", "mohtat2020 = pybamm.parameter_sets.Mohtat2020\n", "parameter_values = {\n", - " \"Mohtat2020_1\": pybamm.ParameterValues(mohtat2020),\n", - " \"Mohtat2020_2\": pybamm.ParameterValues(mohtat2020),\n", - " \"Mohtat2020_3\": pybamm.ParameterValues(mohtat2020),\n", + " \"Mohtat2020_1\": pybamm.ParameterValues(\"Mohtat2020\"),\n", + " \"Mohtat2020_2\": pybamm.ParameterValues(\"Mohtat2020\"),\n", + " \"Mohtat2020_3\": pybamm.ParameterValues(\"Mohtat2020\"),\n", "}\n", "\n", "# different values for the parameter \"Inner SEI open-circuit potential [V]\"\n", @@ -514,7 +521,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -592,7 +599,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -606,7 +613,20 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.0" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, diff --git a/examples/notebooks/expression_tree/broadcasts.ipynb b/examples/notebooks/expression_tree/broadcasts.ipynb index f86e57e359..966d897b9b 100644 --- a/examples/notebooks/expression_tree/broadcasts.ipynb +++ b/examples/notebooks/expression_tree/broadcasts.ipynb @@ -44,8 +44,8 @@ "source": [ "var = pybamm.standard_spatial_vars\n", "geometry = {\n", - " \"negative electrode\": {"x_n": {\"min\": pybamm.Scalar(0), \"max\": pybamm.Scalar(1)}},\n", - " \"negative particle\": {"r_n": {\"min\": pybamm.Scalar(0), \"max\": pybamm.Scalar(1)}},\n", + " \"negative electrode\": {var.x_n: {\"min\": pybamm.Scalar(0), \"max\": pybamm.Scalar(1)}},\n", + " \"negative particle\": {var.r_n: {\"min\": pybamm.Scalar(0), \"max\": pybamm.Scalar(1)}},\n", "}\n", "\n", "submesh_types = {\n", @@ -53,7 +53,7 @@ " \"negative particle\": pybamm.Uniform1DSubMesh,\n", "}\n", "\n", - "var_pts = {"x_n": 5, "r_n": 3}\n", + "var_pts = {var.x_n: 5, var.r_n: 3}\n", "mesh = pybamm.Mesh(geometry, submesh_types, var_pts)\n", "\n", "spatial_methods = {\n", @@ -264,7 +264,7 @@ "output_type": "stream", "text": [ "[1] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", - "[2] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", + "[2] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", "\n" ] } @@ -276,7 +276,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -290,7 +290,20 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, diff --git a/examples/notebooks/models/DFN-with-particle-size-distributions.ipynb b/examples/notebooks/models/DFN-with-particle-size-distributions.ipynb index a16cfa31f9..c37a02a640 100644 --- a/examples/notebooks/models/DFN-with-particle-size-distributions.ipynb +++ b/examples/notebooks/models/DFN-with-particle-size-distributions.ipynb @@ -34,8 +34,6 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[33mWARNING: You are using pip version 21.1.2; however, version 21.2.3 is available.\n", - "You should consider upgrading via the '/home/user/PyBaMM/.tox/dev/bin/python -m pip install --upgrade pip' command.\u001b[0m\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } @@ -92,7 +90,7 @@ "outputs": [], "source": [ "# Base parameter set (no distribution parameters by default)\n", - "params = pybamm.ParameterValues("Marquis2019")\n", + "params = pybamm.ParameterValues(\"Marquis2019\")\n", "\n", "# Add distribution parameters to the set, with default values (lognormals)\n", "params = pybamm.get_size_distribution_parameters(params)" @@ -120,7 +118,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 4, @@ -145,7 +143,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fe7860b9192848bab44903e273a83031", + "model_id": "15600ad8e80a4c87aba6ca5566c7e318", "version_major": 2, "version_minor": 0 }, @@ -159,7 +157,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 5, @@ -197,7 +195,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -379,7 +377,7 @@ "]\n", "\n", "# parameters\n", - "params = pybamm.ParameterValues("Marquis2019")\n", + "params = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019)\n", "params = pybamm.get_size_distribution_parameters(params) \n", "\n", "# define current function\n", @@ -408,7 +406,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -475,7 +473,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -489,7 +487,20 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.9" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, diff --git a/examples/notebooks/models/MPM.ipynb b/examples/notebooks/models/MPM.ipynb index 7822d7f917..834c7d0b40 100644 --- a/examples/notebooks/models/MPM.ipynb +++ b/examples/notebooks/models/MPM.ipynb @@ -97,8 +97,6 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[33mWARNING: You are using pip version 21.1.2; however, version 21.1.3 is available.\n", - "You should consider upgrading via the '/home/user/PyBaMM/.tox/dev/bin/python -m pip install --upgrade pip' command.\u001b[0m\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } @@ -255,19 +253,19 @@ "name": "stdout", "output_type": "stream", "text": [ - "negative electrode is of type Generator for Uniform1DSubMesh\n", - "separator is of type Generator for Uniform1DSubMesh\n", - "positive electrode is of type Generator for Uniform1DSubMesh\n", - "negative particle is of type Generator for Uniform1DSubMesh\n", - "positive particle is of type Generator for Uniform1DSubMesh\n", - "negative particle size is of type Generator for Uniform1DSubMesh\n", - "positive particle size is of type Generator for Uniform1DSubMesh\n", - "current collector is of type Generator for SubMesh0D\n", + "negative electrode is of type Uniform1DSubMesh\n", + "separator is of type Uniform1DSubMesh\n", + "positive electrode is of type Uniform1DSubMesh\n", + "negative particle is of type Uniform1DSubMesh\n", + "positive particle is of type Uniform1DSubMesh\n", + "negative particle size is of type Uniform1DSubMesh\n", + "positive particle size is of type Uniform1DSubMesh\n", + "current collector is of type SubMesh0D\n", "x_n has 20 mesh points\n", "x_s has 20 mesh points\n", "x_p has 20 mesh points\n", - "r_n has 30 mesh points\n", - "r_p has 30 mesh points\n", + "r_n has 20 mesh points\n", + "r_p has 20 mesh points\n", "y has 10 mesh points\n", "z has 10 mesh points\n", "R_n has 30 mesh points\n", @@ -277,7 +275,7 @@ ], "source": [ "for k, t in model.default_submesh_types.items():\n", - " print(k,'is of type',t.__repr__())\n", + " print(k,'is of type',t.__name__)\n", "for var, npts in model.default_var_pts.items():\n", " print(var,'has',npts,'mesh points')" ] @@ -298,12 +296,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b66ea72826fe48e69565e67441ebc889", + "model_id": "f79e30dbc81445a09cc42f3d8f6565fd", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "interactive(children=(FloatSlider(value=0.0, description='t', max=3580.9687331142236, step=35.809687331142236)…" + "interactive(children=(FloatSlider(value=0.0, description='t', max=3581.95943869543, step=35.8195943869543), Ou…" ] }, "metadata": {}, @@ -312,7 +310,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 7, @@ -351,7 +349,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -408,7 +406,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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Kijs1pj3mHkk2Df/1ZIlMvyXp+xHx6Ezb2kR77T6fn1y5x6ibYWNkfWJS51SiyzJF+XHM+sQxzmRinal6qaOmdYkO2fpEh2wq0SPbd4/7hh2/oFoM+yTZXVKWkk1E+xkbR/lfFRGrJe1MFttui4hryjbW+A6ZmQ1OEKyP2rkYVzE9O/huPDPT/IlkN68OYIWkO4F9yZJGmpnV1mP8ggoxLD94PBEgv/TizvxBRLTu3nC/pEvIToGWdsh8DZmZJU0l/uviemAfSc9VdieC48hOTxbdDbQugN0FeCGwss8fwcxmqR7iF1SIYZK218Y7rZwEXBMRj+Z3T9gmX2Yr4I1kCbtLeYTMzEplR5j1LumKiAlJpwJXAnOB8yJimaRT8vJzgI8D50u6mez0wIeqzkgyM0vpJX5B5Rj2IuCLkibJ7vbyvrz6LsAl2aAZ84ALIuKK1PbcITOzUgGsr3Yk2bl+xOXA5W3vnVN4vprsyNHMrK96jV9QKYZdS5Y3s73eSuCAmWzLHTIzKxXApHMVmlkDNS1+uUNmZqWCYH3tye9mZqPTtPjlDpmZlQuYbE48MzPbqGHxyx2ymRqnXGPDzieWyu81gBxezEmsc16iLJUXbF693GapepH47OntJfLxzEskT0x+vv4mqQ2UzBtkNpulc3+Vp1tI1XsqUS91gXpqJGh9olPyVJTHk/VRHtueivLuw7pkvfJEyOtJxHXuS5R11rT45Q6ZmZUK0skazczGVdPilztkZlYqgHVOV2hmDdS0+OUOmZmVCmB94pSGmdm4alr8cofMzEoFYrJBR5hmZi1Ni1/ukJlZqaYdYZqZtTQtfrlDZmYJYrJBAc3MbKNmxS93yMysVHbrkdRUdDOz8dS0+DVrO2RK5QWrqym5xmrnDKtZb17iZ5bKJ5Yoq50XbH7Ndc5PbS+RTyxRL5lrLFGWqjeVaEsdEc06wjTrt7q5xp6OifJ6yTxkqbLyv++nErm/npgqz/2VyguWyjX2+NRmiXoLyssSbXliqrweLEuUdda0+DVrO2Rm1l3TjjDNzFqaFr/cITOzUoFYnzhKNjMbV02LX80ZyzOzkZgMlT7MzMZZr/FL0iJJt0taIem0DuU7SLpE0k2SfiLpJVXrtmtO19HMhq5pR5hmZi29xi9Jc4GzgDcAq4DrJV0WEbcWFvsIsDQi3ixp33z5wyvWncYjZGZWKoBJ5pQ+uqlwdPlBSUvzxy2SJiU9axCfxcxml17jF3AwsCIiVkbEOuAi4Ni2ZfYDvg0QEbcBe0napWLdadwhM7NS2RHm3NJHSuEI8SiyoHW8pP2mrT/ijIg4MCIOBD4MfC8iHhrMpzGz2aSX+JXbFbin8HpV/l7RjcBbACQdDOwJ7Fax7jQ+F2FmpSLoZdr4hiNEAEmtI8SyIfvjgQvrbszMrKhC/FooaUnh9eKIWFx43elCs2h7/UngTElLgZuBnwETFetO4w6ZmZVqHWEmpAJapyPEQzqtRNKWwCLg1B6aa2a2QYX4tSYiDkqUrwJ2L7zeDVg9bRsRjwInAkgScGf+2LJb3XbukI2DQSR/VaJe3eSvySSuiZ9SKlFrap2pJK6JsqlkvUSi1gWpJK6JsvmpxLA1E7wm65UWMZmoV0ePAW0mR4jHAD/06UobhUEkf30qUe+pKB8oeSIxovN4IolrKqnq44lErakEr08kytL1yrf3xGR5vbWJsjoqxK9urgf2kfRc4F7gOOCE4gKStgeeyK8TOwm4JiIeldS1bruhXkNW4QLf7SR9XdKNkpZJOnGY7TOzZ+rhotiuR5cFxzHmpysdv8yap5eL+iNigmzU/kpgOfDliFgm6RRJp+SLvQhYJuk2sutl/yRVN7W9oY2QVZwC+kfArRFxjKSdgNslfSnveZrZkPV4hFnpCFHSdsBrgXfW3dCgOX6ZNU8fRsiIiMuBy9veO6fw/Fpgn6p1U4Z5yrLKBb4BbJOfh90aeIjs4jgzG4EApmpe1B8RE5JaR4hzgfNaR5d5eSuovRm4KiIe70OTB8Xxy6xheolfozDMDlmVC3w/B1xGdlpjG+DtEc+806qkk4GTATZny4E01syym/P2coTZ7egyf30+cH7tjQzHQOLXHrv6Ml6zQek1fg3bMLuOVS7wPRJYCjwHOBD4nKRtn1EpYnFEHBQRB83X5v1up5kVTMac0scsMpD4tdOOzfnHwqyJmhS/htmiKhf4nghcHJkVZFNH9x1S+8ysTR8SK24qHL/MGqZp8WuYHbINF/hKWkB2ge9lbcvcDRwOkN964IXAyiG20cwKAhoV0AbI8cusYZoWv4Z2AUPFC3w/Dpwv6WayUwQfiog1w2qjmU0XiKnob26zJnL8MmuepsWvoV5RWmH66GrgjcNsU0fJpKqJLzeR4FWpZKypstQ6U+1MJI1Nbi9ZljiiSCV/XZBKDFv+E0wlf02tM5ngtWZi2FTC1VQS18kFqXqlRV22V14vVVZHBGN5JDkKjYlfNmOp5K/JskRC2UEkf32sZqLWx6a2KC+bLL8O+7Gp8rK1iXrJsonypLFPTpaX1dG0+OUpPmaW1KQjTDOzoibFL3fIzKxUPxIrmpmNQtPilztkZlYqS6zYnCNMM7OWpsUvd8jMLEFMNOgI08xso2bFL3fIzKxUBKyfak5AMzNraVr8cofMzEo1bdq4mVlL0+KXO2RmViqAiTG8xYiZWTdNi1/ukA1LIp9YUirvWc2caMlcY6n8ZfNS+cRq5igbQK6xyc1S9VI5wxLrTKTHSeUaq5uHbBBldU01KKCZlZlK5AxLlaVzjZWXPZ0YmambayyVT+zRZD6x8nq/niwvWztRvs5HJxL1EgFz7frydT4x0f8A1qT41ZyWmtnQRYiJmFP6MDMbV/2IX5IWSbpd0gpJp3Uo307S1yXdKGmZpBMLZXdJulnSUklLum3LI2RmltSkazDMzIp6iV+S5gJnAW8AVgHXS7osIm4tLPZHwK0RcYyknYDbJX0pItbl5a+regs1d8jMrFQAE1MeCTOz5ulD/DoYWBERKwEkXQQcCxQ7ZAFsI0nA1sBDwESdjTnSmlmpoLch/27D/fkyh+VD+sskfa/vH8LMZqUK8WuhpCWFx8ltq9gVuKfwelX+XtHngBcBq4GbgT+J2HBxYQBXSbqhw7qfwSNkZlYu6g/5Vxnul7Q9cDawKCLulrRz7402M6NK/FoTEQclyjtVbr9r/JHAUuD1wN7AtyR9PyIeBV4VEavzuPYtSbdFxDVlG/MImZmVag35lz262DDcn19P0RruLzoBuDgi7gaIiPv7/RnMbHbqMX5BdiC5e+H1bmQjYUUnksWwiIgVwJ3AvgARsTr///3AJWQxsZQ7ZGZWqpVYsexBesi/ynD/C4AdJF2dD+u/e7CfyMxmiwrxq5vrgX0kPVfSAuA44LK2Ze4GDgeQtAvwQmClpK0kbZO/vxXwRuCW1MZ8ytLMkibT14qlhvyrDPfPA15OFtC2AK6VdF1E/HzGDTUza9MlfiVFxISkU4ErgbnAeRGxTNIpefk5wMeB8yXdTBbzPhQRayQ9D7gku9afecAFEXFFanvukPWRUglXkxXLe+pSYp2p5K+JZKzJ5K91680rL0smf51fXm8qUZZK4lo7+etm5fUmynM1dtleol4iB2Ldev1ODBs9XENGteH+VWSduseBxyVdAxwAuENmfTWZSOI6Ge3HCRutT9RbX16NpxI3tX5qqvyf3scTiWFTZXWTv/56YsvSskcTiWEfSyR4XZsImGvXlwe3J/ucGLbH+JWvIy4HLm9775zC89Vko1/t9VaSxbLKfMrSzBLE5NSc0kcXVYb7LwVeI2mepC2BQ4Dlff8YZjYL9RS/hs4jZGZWKqB24Koy3B8RyyVdAdwETAHnRkTyOgszsyp6iV+j4A6ZmZWLbNi/dvUuw/356zOAM+pvxcysgx7j17C5Q2ZmpYLeLoo1MxuVpsUvd8jMLKHy9HAzszHTrPjlDpmZJU1NNSegmZkVNSl+uUNmZqUiIBp0hGlm1tK0+OUO2bCkcpTNSfxgUmWpPGR1yxLtjLplqRxlibKpZK6xRD6x+Ym8YIPINZaoN5nKGZaqVzcP2YL+X8E62aAjTJvdpijPGTb1jJzEVcvKrU/8Y7+ORB6yKP8jTpU9NpnI/ZUoG0SusUdTecgSucaeSOUhW9/nRIo0K365Q2ZmpQIx1aBp42ZmLU2LX0NtqaRFkm6XtELSaSXLHCZpqaRlkr43zPaZ2TNF4jGbOH6ZNU+T4tfQRsgkzQXOAt5AdruU6yVdFhG3FpbZHjgbWBQRd0vaeVjtM7MOAqJBQ/6D4vhl1kANi1/DHCE7GFgRESsjYh1wEXBs2zInABdHxN0AEXH/ENtnZh1EqPQxizh+mTVQk+LXMDtkuwL3FF6vyt8regGwg6SrJd0g6d2dViTpZElLJC1ZH08NqLlmFmTTxsses8hA4tcDD04OqLlm1rT4NcyL+jt9+vbTuPOAlwOHA1sA10q6LiJ+Pq1SxGJgMcC2c3Ycx1PBZpuGAMbwSHIEBhK/Djpgc8cvs0FpWPwa5gjZKmD3wuvdgNUdlrkiIh6PiDXANcABQ2qfmXUQU+WPWcTxy6yBeo1f3SbzSNpO0tcl3ZhP5jmxat12w+yQXQ/sI+m5khYAxwGXtS1zKfAaSfMkbQkcAiwfYhvNbBoRU+WPWcTxy6xxeotfhck8RwH7AcdL2q9tsT8Cbo2IA4DDgH+UtKBi3WmGdsoyIiYknQpcCcwFzouIZZJOycvPiYjlkq4AbiLLx3duRNwyrDZWkkqqOmypZLPJxLCJenNTZYl1ppK/JpLbTqUSwya2NzUvUZZK4ppKqppKKJtI1Fo7+WsqEW3N5K9T8/t8Bqxhma4HZZOJX7NYKmnsZCIJwrpIlKWSv06V//OaSv76RCJopMsSCVcTQerxREbstamyASR/fXpdn7skvcevDZN5ACS1JvPcWlgmgG0kCdgaeAiYIDsg61Z3mqEmho2Iy4HL2947p+31GcAZw2yXmSW4QwY4fpk1Ujp+LZS0pPB6cX6NZ0unyTyHtK3jc2Sj5auBbYC3R8SUpCp1p3GmfjNL28QuO5e0Y0Q8OOp2mNkQpOPXmog4KFFeZTLPkcBS4PXA3sC3JH2/Yt1panXI8qG39fnL+yLif9dZj5mNuQB6uFZM0iLgTLLTfOdGxCfbyg8ju/bqzvytiyPir2tvsHt7vgrcL2nbvD3fHdS2zGzEeoxfVJvMcyLwyYgIYIWkO4F9K9adpu4I2bURcSZkR5s112FmDZC4hCapSnb73Pcj4nd7amR1t0XEn+ftOwtwh8xsE1Y3fuU2TOYB7iWbzHNC2zJ3k6W6+b6kXYAXAiuBRyrUnaZuh+xYSVPAle05dsxsE1P/CLPKBbHDtkjSQ8CNZBfemtmmrIcRsiqTeYCPA+dLupnsNOWH8rQ3dKqb2l7dDtm7yPLr/J6kvSPipJrrMbNxFqD6+caqXtT6Skk3kg3nf6Bb0OrRIuAVwKuAnST9S0S8Z4DbM7NR6S1+ZavoMpknIlYDb6xaN6VWhywi7iUbgqu8ITNrIvUyS6nKRa0/BfaMiLWSjga+BuxTt7XdRMQDZHHLsctsk9c1fo2VrolhJb1L0gOSVkl6T/7eoZL+RtINg2+imY3UVOKRz1IqPIpTxrte1BoRj0bE2vz55cB8SQv70WzHLjPrEr/GSpURso8CR5PNgjpV0rfIZhBcCLx/cE2bPZRK1JpM8JooSyRjTSZ/Ta4zkfw1kcQ1UkljEwleI5GoNZkYNlWWWmcqGWviLyWRjzGZULZ28tdEWSwYQJSpf1Fs1wtiJf0G8KuICEkHkx0k9islhWPXLDOZuB/OZOLq7qnEjzz1F7U+ymPb+lTS2ERi2KcSgeGpKA9ETySCzeOJLNRPTCQSvE4k2pIoe3qivJ3r1pfvl4mJ8rLaGpS2p0qHbG1EXA8g6WPAr4AXRMQjg2yYmY2BANW8KLbiBbFvBf5Q0gTwJHBcPn28Hxy7zGazHuLXKFTpkP2GpJOB2/PHKgc0s1mkh+5RhQtiP0eW6XoQHLvMZrtNbITsr4D9gXcALyW7Z9N/Aj8DfhYRFwywfWY2YmpQQGvj2GU2yzUpfnXtkLVdpIuk3ciC3EvJ7mLuoGa2qeo90/XIOHaZzXINi19dO2SSXglc17quIyJWkc2e8rRxs9mgQUeYRY5dZtak+NU17QXwHuCnki6S9N58VpSZzRKaKn+MOccus1muSfGryinLUwAk7Us2zH++pO3I7gF3BfDDiJgcaCvNbHQadIRZ5NhlZk2KX5Uz9UfEbcBtwGckbQG8Dngb8GngoME0r2Hq5gyru84BtCVSZalcY6kcZYmcaKmyqWRus9KidM6wVFkqL1jNsmQ75ydyHyXKkrnG+pyHTA2bNt5Jh9j1Nhy7rCCVo2yy4w0nWmWJPGRRnlNrfSIwpHKUPZ0INk8m8pA9PZnYXqIsmU8skTPs6fXl9VK5xibXVzlpV13T4lfde1l+gezGvEF2tGlmm6oGHWFW8K/AA8B2wAdH3BYzG7QGxa+6HbJrI+JMAEk79rE9ZjZmxvFaix7cHhF/DiDpLHxAabZJa1L8qtshO1bSFHBlRPy8nw0yszESzcrjU8EiSQ8BN5KN8pvZpqph8avSCVtJcyR9pPDWu4A7gN+TdO5AWmZm46FBN+dt1yF2LQKWA68CdpL0L6NpmZkNRY/xS9IiSbdLWiHptA7lH5S0NH/cImlS0rPysrsk3ZyXLem2rUojZBExJekI4O/y1/eS3SzY+XzMNnFNOsJs1yF2PUAWtxy7zGaBXuKXpLnAWcAbyHIYXi/psoi4tbVMRJwBnJEvfwzwvyLiocJqXhcRa6psbyZTGn4m6a8k9XcahJmNt0g8msGxy2y26i1+HQysiIiVEbEOuAg4NrH88cCFdZs6kwC1O3AcsFrSpZI+LultdTdsZg0QzUqsWMKxy2w26j1+7QrcU3i9Kn/vGSRtSXZJxFent4CrJN0g6eRuG5tJHrL/lm90M+DFZPeDOxj4j6rrMLMGas5IWEeOXWazWDp+LWy7tmtx2z1wOyUxK1vjMWTJpounK18VEasl7Qx8S9JtEXFNWWNmPMsyIp4Gfpo/bJSSyV8Tg5+peolkrMl6NZO/xrx6iWhTSWOTCWXLcxISiV2WSvCaWmcqEW2kkr8mykiUaV6fE8PSqJGwJMeuTd9U4l/fdFm59VEeT9Yngsa6RNBIJ40tL3sqkRj26USweWqyvN66qUSC10TS2HWTiQSvk+X7ZTKRGHZqos+JYekav9ZERCo59CqyEfaW3YDVJcseR9vpyohYnf//fkmXkB0IlnbIhnpNRbfZCoXlXpHPVHjrMNtnZm3yaeNlj9nE8cusYXqPX9cD+0h6rqQFZJ2uy9oXym/J9lrg0sJ7W0napvUceCNwS2pjdfOQzViV2QqF5T4FXDmstplZwiYyQtYLxy+zhuohfkXEhKRTyf6e5wLnRcQySafk5efki74ZuCoiHi9U3wW4RNmZpXnABRFxRWp7Q+uQUZitACCpNVvh1rbl/pjsorhXDLFtZlail1OWkhYBZ5IFs3Mj4pMly70CuA54e0R8pf4WB8bxy6yBer3kIiKekSan0BFrvT4fOL/tvZXAATPZ1jBPWXadrSBpV7Ke5rQP207SyZKWSFqyPp7qe0PNLJeaMt5lyL8wqnQUsB9wvKT9SpYb91GlgcSvBx6c7HtDzSzXQ/wahWF2yKrMVvgs8KGISEapiFgcEQdFxEHztXm/2mdmHfQwbbxqDp/WqNL9fW14fw0kfu20Y2JGiJn1rElpe4Z5yrLKbIWDgIvyc64LgaMlTUTE14bSQjN7hi4Xv6amjXcaVTpk2ro3jiq9nvE+zef4ZdZATZp8NMwO2YbZCmS3XToOOKG4QEQ8t/Vc0vnANxzMzEYo6HZRbGra+IxGlZRKqzJ6jl9mTdM9fo2VoXXIZjBbYfQSebOGvr05NfOJ1d1eMrdZKtdYebVUPrFkveQ665Wl8oINoizmJXIfpT5Dop7mlkeYOYl6dYjOvaqKNplRpUbFr03c1AD+hZ1MXFA0mbiyZzIRpKYS9ermIUvlGkuVpXKNpfKJTSTyiU0k6k1NJfJETiYiSqJeHT3Gr6Eb5ghZpdkKhfffO4w2mVlaD9dabFKjSo5fZs0zjteKlRlqh8zMGqhmQPOokpmNnDtkZrZJ6DEjv0eVzGxkGnZHEXfIzCypSUP+ZmZFTYpf7pCZWVqDjjDNzKZpUPxyh8zMykWzjjDNzDZoWPxyh8zM0hp0hGlmNk2D4pc7ZGZWSjTrCNPMrKVp8csdsmEZp2SzKankr4kEr7WTxibamUz+WjdpbOIj1E02W7eMuankr/XK5s7r882qAzTVoENMsxLJ5K81f+Kp5K/rEn/866L8n971iQSvE4kErxOJoDgxlUhSm1hnMvFtIonrZCKhbCTqpcpqaVj8cofMzJKaNG3czKyoSfErMc5gZpYN+Zc9zMzGWa/xS9IiSbdLWiHptA7lH5S0NH/cImlS0rOq1G3nDpmZpUXiYWY2znqIX5LmAmcBRwH7AcdL2m/a6iPOiIgDI+JA4MPA9yLioSp127lDZmblwiNkZtZQvcevg4EVEbEyItYBFwHHJpY/HriwZl13yMysnMiuwSh7mJmNqwrxa6GkJYXHyW2r2BW4p/B6Vf7eM7clbQksAr4607otvqjfzJKaNEvJzKyoS/xaExEHpap3eK9shccAP4yIh2rUBdwhM7OUAPU5k4aZ2VD0Hr9WAbsXXu8GrC5Z9jg2nq6caV3AHbJmG0Cusbr1UvnEkvVSecFSOcqSuc0SZXVzmyXbWX7QkypL5SFLlc1JlaW2V5cHyKwhpuj/hY1TiT/+yY6DIK16iRxeiXWuTwSp1Pbq5iibTOQom0zkBUt9hmQ+sVQw7XceMug1fl0P7CPpucC9ZJ2uE9oXkrQd8FrgnTOtW+QOmZmVa1hiRTOzDXqMXxExIelU4EpgLnBeRCyTdEpefk6+6JuBqyLi8W51U9tzh8zMknzxvpk1Va/xKyIuBy5ve++cttfnA+dXqZviWZZmVqp1L7i608YrJFU8VtJNeVLFJZJePYCPYWazUK/xa9g8QmZm5SKyRw2FxIhvILvA9XpJl0XErYXFvg1cFhEhaX/gy8C+PbbazKyn+DUK7pCZWVIPR5IbEiMCSGolRtzQIYuItYXlt8JTCMysj8ZxJKyMO2RmVi5Ak8k+0kJJSwqvF0fE4vx5p8SIh7SvQNKbgU8AOwO/01uDzcxy3ePXWHGHzMzS0vEslVixUmLEiLgEuETSbwMfB46YaRPNzDpqTn/MHTIzS+th2viMEiNGxDWS9pa0MCLW1N2omVlLk9L2uEPWT3NqTlpNJWodQBLXlKi7veQ6E2W1k7HWSxqbyKuYrlezLJ3AtjxQKDFXW3PKL4qYkyirq4dp410TI0p6PnBHflH/y4AFwIP1W2vWX6lkrJOphKuJwJAqSyVcTSV/Tdcr314k6k2l6iWSuCYTwyZC1CCu92pS2p6hpr2oMAX+HfkU+Jsk/UjSAcNsn5lNpzyxYtkjJSImgFZixOXAl1tJFVuJFYHfA26RtJRsRubbI8ZzWpTjl1mz9BK/RmFoI2QVp8DfCbw2Ih6WdBSwmA4XAZvZEPVw1NotqWJEfAr4VP0tDIfjl1lDeZZlR1WmwP+osPx1ZNecmNmo+NZJLY5fZk3TsPg1zFOWnabA75pY/n3ANzsVSDo5z+q9ZH081ccmmtl05cP9TQp0fTCQ+PXAg5N9bKKZTdes+DXMEbJKU+ABJL2OLKB1vI1KnudoMcC2c3Ycv71qtikZz0u6hm0g8eugAzb3zjUbpAbFr2F2yCpNgc9vn3IucFREeLaV2Sg1LLHiADl+mTVNw+LXME9ZbpgCL2kB2RT4y4oLSNoDuBh4V0T8fIhtM7MykXjMHo5fZk3UoPg1tBGyiJiQ1JoCPxc4rzUFPi8/B/gosCNwtrJ8WBOJLOBmNgSaatA0pQFx/DJrpl7jl6RFwJlkf/fnRsQnOyxzGPBZYD7Z3Utem79/F/AYMEmFeDDUxLAVpsCfBJw0zDbNlOomfx0jdZO/JuulVlk312wqiWvN7Q0iaWw6oWziMCy1OxP15iTK5qa2V0fQqGnjg7QpxK/ZbCoxJDKIn/hkKuFqzYSyU4mgkSxLtGUykcQ1VS+VUDY5+pSs1+fE5D3GryrpbiRtD5wNLIqIuyXt3Laa11W984gz9ZtZKREeITOzRupD/Oqa7obs7iMXR8TdABFxf92NNX+4x8wGJ4DJKH+YmY2r7vFrYSsFTf44uW0NVdLdvADYQdLVkm6Q9O62FlyVv9++7mfwCJmZJalB08bNzIq6xK81Xa7rqpLuZh7wcuBwYAvgWknX5RN7XhURq/PTmN+SdFtEXFO2MXfIzCwhwKcszayReo5fVdLdrCLr2D0OPC7pGuAA4OcRsRqy05iSLiE7BVraIfMpSzMrF2SJFcseZmbjqvf41TXdDXAp8BpJ8yRtSXb/2uWStpK0DYCkrYA3ArekNuYRMjNLalJiRTOzol7iV5V0NxGxXNIVwE1kczrPjYhbJD0PuCRPgTMPuCAirkhtzx0yM0vzSJiZNVWP8atbupv89RnAGW3vrSQ7dVmZO2Q2Xc2T2MkcZXNSCbcSeW7q5hobo7xnyVxjybKa+ctS9eqIgElfQ2bWSSr3V8pk3Zxhydxmfc7hRbovky5L5S8rr9fv8NW0+OUOmZml+aJ+M2uqBsUvX9RvZuUCmIryRxeSFkm6XdIKSad1KH+HpJvyx48kzWiI38ysVI/xa9g8QmZmCQFTk7VqVrntCHAn8NqIeFjSUcBisllKZmY9qh+/RsEdMjMr1zrCrKfrbUci4keF5a8jy/NjZta73uLX0LlDZmZp6WswFkpaUni9OCIW58873XYkNfr1PuCbtdpoZtZJg64hc4fMzBK6JlBM3Xqkym1HsgWl15F1yF49s/aZmZVpVgJrd8jMrFwAk7Wvwahy2xEk7Q+cCxwVEQ/W3ZiZ2TS9xa+hc4fMzBJ6yuOz4bYjwL1ktx05obiApD2Ai4F35TfjNTPrE+chMxtfg0goW9cAkr/2PzEsRNQLaFVuOwJ8FNgRODu/xchE4hSomZVIJYZNJWqtm9y2EXqIX6PgDpmZpfVwhNnttiMRcRJwUu0NmJmleITMzDYJEY2apWRmtkHD4pc7ZGaWFA26KNbMrKhJ8csdMjNLaNa0cTOzjZoVv3wvSzMr15o2XvYwMxtXfYhf3e7Hmy9zmKSlkpZJ+t5M6hZ5hMzMSkVEo4b8zcxaeo1fVe7HK2l74GxgUUTcLWnnqnXbeYTMzJJiKkofZmbjrMf4teF+vBGxDmjdj7foBODiiLgbICLun0HdaRo/QvZYPLTmW+sv/MWo29HBQmDNqBtRgdvZX+Pczj1nWuExHr7yP6e+vDCxyLh+1ka44aan18x99n+NY/yC8f4tF7md/TWu7RxE/No8cS9eqHY/3hcA8yVdDWwDnBkRX6xYd5rGd8giYqdRt6ETSUuakODS7eyvprSzqohYNOo2bMrGNX5Bc37Lbmd/NaWdVfQhflW5H+884OXA4cAWwLWSrqtY9xkrMjMzM7PpqtyPdxWwJiIeBx6XdA1wQMW60/gaMjMzM7Nn2nA/XkkLyO7He1nbMpcCr5E0T9KWZKcll1esO41HyAZncfdFxoLb2V9NaadZN035Lbud/dWUdg5clfvxRsRySVcANwFTwLkRcQtAp7qp7SkalDTNzMzMbFPkU5ZmZmZmI+YOmZmZmdmIuUPWo263RshvqfDr/LYKSyV9dETtPE/S/ZJuKSmXpH/KP8dNkl427Dbm7ejWzpHvT0m7S/qupOX5rTL+pMMyY7E/zVIcv/qrCfErb4dj2DiKCD9qPsgu1LsDeB6wALgR2K9tmcOAb4xBW38beBlwS0n50cA3yXKnHAr8eEzbOfL9CTwbeFn+fBvg5x2+97HYn374UfZw/BpJO8dlfzqGjeHDI2S9mfGtEUYlIq4BHkoscizwxchcB2wv6dnDad1GFdo5chFxX0T8NH/+GNkU513bFhuL/WmW4PjVZ02IX+AYNq7cIetNp1sjtP+oAV4p6UZJ35T04uE0bcaqfpZxMDb7U9JewG8CP24ratL+tNnJ8Ws0xmp/OoaND+ch602VWyP8FNgzItZKOhr4GrDPoBtWw4xv8zAiY7M/JW0NfBV4f0Q82l7coco47k+bvRy/hm+s9qdj2HjxCFlvut4aISIejYi1+fPLyW5CmrrZ6ajM+DYPozAu+1PSfLJA9qWIuLjDIo3YnzarOX4N2TjtT8ew8eMOWW+63hpB0m9IUv78YLJ9/uDQW9rdZcC785k1hwK/joj7Rt2oduOwP/Ptfx5YHhGfLlmsEfvTZjXHryEbl/3pGDaefMqyB1HhtgrAW4E/lDQBPAkcFxFDH/aVdCHZDJ+FklYBfwXML7TzcrJZNSuAJ4ATh93Giu0ch/35KuBdwM2SlubvfQTYo9DOsdifZmUcv0bSzrHYnziGjSXfOsnMzMxsxHzK0szMzGzE3CEzMzMzGzF3yMzMzMxGzB0yMzMzsxFzh8xsxLrdkLjG+iYLNy++rHsNM7N6HL/6x7MszUZM0m8Da8nuG/eSPqxvbURs3XvLzMzSHL/6xyNkZiPW6YbEkvaWdIWkGyR9X9K+I2qemVkpx6/+cYfMNpD0B5J+md/49g5J765QZy9JTxaSC/bahi3yoep1Y3qLlmFZDPxxRLwc+ABw9gzqbi5piaTrJL1pIK0zG0OOYWPD8asGZ+q3ov2B0yPinPy2HpcDX6xQ746IOLAfDYiIJ4EDJd3Vj/U1kbIb/v4W8B/5XVYANsvL3gL8dYdq90bEkfnzPSJitaTnAd+RdHNE3DHodpuNAcewEXP8qs8dMit6KfCV/PmdwLo6K5F0NfAHEXG7pB2B70XESyTtBVwB/AA4FLgR+ALwMWBn4B0R8ZOePsGmYQ7wSKd/IPKbAHe6EXBxmdX5/1fm38VvArMioNms5xg2eo5fNfmUpRW9FLg9v/HsqcCf11zP84H/yp/vD9zcVnZm/v6+wAnAq8mGtT9Sc3ublIh4FLhT0tsguxGwpAOq1JW0g6TW0ehCsnvW3TqwxpqNF8ewEXP8qs8dMgNA0u7ANmRD/PeTBZjza6xnT7Lh56n8rf2BmwqL3BkRN+fly4Bv5zfXvRnYq/YHaLD8hsTXAi+UtErS+4B3AO+TdCPZfjq24upeBCzJ630X+GREzJqAZrOXY9hoOH71j09ZWsv+wDUR8XpJOwC3AK+UdDfwr8BlwKER8fYu6zmQ6cHr5cC/F14/XXg+VXg9xSz9PUbE8SVFi2qs60dkowRms01ZDFtBdprxSuCFwFsLna1ODsQxrDLHr/7xCJm1vBT4GUBEPAxcAPwOcADwtYj4DDBRYT0HAJsDSNqH7Mjo5mQNM7PelcWwVwAXRsSHyUbOduyyHscwGwl3yKxlQzDLfR04miw4XZm/VyWL8IHAnHzI+aPAcuA9/WummVlHZTHsFWQX3wNsFxEPdFnPgTiG2Qg4U78lSToPOAl4FnBaRHygrXwv4ButDM356YHfjIjHetzuXcBBEbGml/WY2eyWX+O0hux04lci4ttt5XvhGGZjYNad77aZiYjfz5+uIZtF1G4S2C5PqvgaYKqXQCZpC7ILROeTXZNhZtaLiYj440S5Y5iNBY+QmZmZmY2YryEzMzMzGzF3yMzMzMxGzB0yMzMzsxFzh8zMzMxsxNwhMzMzMxsxd8jMzMzMRswdMjMzM7MRc4fMzMzMbMT+PxRBEI7syKh5AAAAAElFTkSuQmCC\n", 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" ] @@ -449,7 +447,7 @@ "outputs": [], "source": [ "# Parameter set (no distribution parameters by default)\n", - "params = pybamm.ParameterValues("Marquis2019")\n", + "params = pybamm.ParameterValues(\"Marquis2019\")\n", "\n", "# Extract the radii values. We will choose these to be the means of our area-weighted distributions\n", "R_a_n_dim = params[\"Negative particle radius [m]\"]\n", @@ -505,12 +503,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8b545ec433484ec1b738983bb0d90b80", + "model_id": "ef24b8d5c32e4fa19f8665f56d2d1864", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "interactive(children=(FloatSlider(value=0.0, description='t', max=3511.0164027810006, step=35.11016402781001),…" + "interactive(children=(FloatSlider(value=0.0, description='t', max=3511.9522766513314, step=35.11952276651331),…" ] }, "metadata": {}, @@ -519,7 +517,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 12, @@ -548,7 +546,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -624,7 +622,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9e0887e23c884591bdd97caac3e670d5", + "model_id": "78a1747658144f7c86c975c70290a56b", "version_major": 2, "version_minor": 0 }, @@ -638,7 +636,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 15, @@ -749,7 +747,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ca33360fe25f423fbae0fe20bad989e1", + "model_id": "fbc7fc1fe7434b48bbcb69376b28f58a", "version_major": 2, "version_minor": 0 }, @@ -763,7 +761,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 18, @@ -813,7 +811,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4cfa09f7cdac41cfac0c38ab4be1cf38", + "model_id": "1af4a9e7a8c34514829081483c00f571", "version_major": 2, "version_minor": 0 }, @@ -827,7 +825,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 19, @@ -867,7 +865,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "462351065ca445868719ac5a85a66cf7", + "model_id": "0f7e454c447545d69e8dae1f8e2b1900", "version_major": 2, "version_minor": 0 }, @@ -881,7 +879,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 20, @@ -940,8 +938,8 @@ "[5] Toby L. Kirk, Colin P. Please, and S. Jon Chapman. Physical modelling of the slow voltage relaxation phenomenon in lithium-ion batteries. Journal of The Electrochemical Society, 168(6):060554, jun 2021. URL: https://doi.org/10.1149/1945-7111/ac0bf7, doi:10.1149/1945-7111/ac0bf7.\n", "[6] Scott G. Marquis, Valentin Sulzer, Robert Timms, Colin P. Please, and S. Jon Chapman. An asymptotic derivation of a single particle model with electrolyte. Journal of The Electrochemical Society, 166(15):A3693–A3706, 2019. doi:10.1149/2.0341915jes.\n", "[7] Peyman Mohtat, Suhak Lee, Jason B Siegel, and Anna G Stefanopoulou. Towards better estimability of electrode-specific state of health: decoding the cell expansion. Journal of Power Sources, 427:101–111, 2019.\n", - "[8] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", - "[9] Robert Timms, Scott G. Marquis, Valentin Sulzer, Colin P. Please, and S. Jon Chapman. Asymptotic Reduction of a Lithium-ion Pouch Cell Model. Submitted for publication, 2020. arXiv:2005.05127.\n", + "[8] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", + "[9] Robert Timms, Scott G Marquis, Valentin Sulzer, Colin P. Please, and S Jonathan Chapman. Asymptotic Reduction of a Lithium-ion Pouch Cell Model. SIAM Journal on Applied Mathematics, 81(3):765–788, 2021. doi:10.1137/20M1336898.\n", "[10] Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, and others. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17(3):261–272, 2020. doi:10.1038/s41592-019-0686-2.\n", "\n" ] @@ -961,7 +959,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -975,7 +973,20 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.9" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, diff --git a/examples/notebooks/models/SPM.ipynb b/examples/notebooks/models/SPM.ipynb index 118fb7bf4c..36b0a17083 100644 --- a/examples/notebooks/models/SPM.ipynb +++ b/examples/notebooks/models/SPM.ipynb @@ -238,25 +238,29 @@ "name": "stdout", "output_type": "stream", "text": [ - "negative electrode is of type Generator for Uniform1DSubMesh\n", - "separator is of type Generator for Uniform1DSubMesh\n", - "positive electrode is of type Generator for Uniform1DSubMesh\n", - "negative particle is of type Generator for Uniform1DSubMesh\n", - "positive particle is of type Generator for Uniform1DSubMesh\n", - "current collector is of type Generator for SubMesh0D\n", + "negative electrode is of type Uniform1DSubMesh\n", + "separator is of type Uniform1DSubMesh\n", + "positive electrode is of type Uniform1DSubMesh\n", + "negative particle is of type Uniform1DSubMesh\n", + "positive particle is of type Uniform1DSubMesh\n", + "negative particle size is of type Uniform1DSubMesh\n", + "positive particle size is of type Uniform1DSubMesh\n", + "current collector is of type SubMesh0D\n", "x_n has 20 mesh points\n", "x_s has 20 mesh points\n", "x_p has 20 mesh points\n", - "r_n has 30 mesh points\n", - "r_p has 30 mesh points\n", + "r_n has 20 mesh points\n", + "r_p has 20 mesh points\n", "y has 10 mesh points\n", - "z has 10 mesh points\n" + "z has 10 mesh points\n", + "R_n has 30 mesh points\n", + "R_p has 30 mesh points\n" ] } ], "source": [ "for k, t in model.default_submesh_types.items():\n", - " print(k,'is of type',t.__repr__())\n", + " print(k,'is of type',t.__name__)\n", "for var, npts in model.default_var_pts.items():\n", " print(var,'has',npts,'mesh points')" ] @@ -296,6 +300,8 @@ "macroscale is discretised using FiniteVolume method\n", "negative particle is discretised using FiniteVolume method\n", "positive particle is discretised using FiniteVolume method\n", + "negative particle size is discretised using FiniteVolume method\n", + "positive particle size is discretised using FiniteVolume method\n", "current collector is discretised using ZeroDimensionalSpatialMethod method\n" ] } @@ -401,50 +407,52 @@ "\t- x_p\n", "\t- x_p [m]\n", "\t- Sum of electrolyte reaction source terms\n", - "\t- Sum of negative electrode electrolyte reaction source terms\n", "\t- Sum of positive electrode electrolyte reaction source terms\n", - "\t- Sum of x-averaged negative electrode electrolyte reaction source terms\n", "\t- Sum of x-averaged positive electrode electrolyte reaction source terms\n", "\t- Sum of interfacial current densities\n", - "\t- Sum of negative electrode interfacial current densities\n", "\t- Sum of positive electrode interfacial current densities\n", - "\t- Sum of x-averaged negative electrode interfacial current densities\n", "\t- Sum of x-averaged positive electrode interfacial current densities\n", - "\t- r_n\n", - "\t- r_n [m]\n", + "\t- Sum of negative electrode electrolyte reaction source terms\n", + "\t- Sum of x-averaged negative electrode electrolyte reaction source terms\n", + "\t- Sum of negative electrode interfacial current densities\n", + "\t- Sum of x-averaged negative electrode interfacial current densities\n", "\t- r_p\n", "\t- r_p [m]\n", + "\t- r_n\n", + "\t- r_n [m]\n", + "\t- Current density variable\n", "\t- Total current density\n", "\t- Total current density [A.m-2]\n", "\t- Current [A]\n", "\t- C-rate\n", "\t- Discharge capacity [A.h]\n", "\t- Porosity\n", - "\t- Negative electrode porosity\n", "\t- Separator porosity\n", "\t- Positive electrode porosity\n", - "\t- X-averaged negative electrode porosity\n", "\t- X-averaged separator porosity\n", "\t- X-averaged positive electrode porosity\n", + "\t- Negative electrode porosity\n", + "\t- X-averaged negative electrode porosity\n", "\t- Leading-order porosity\n", - "\t- Leading-order negative electrode porosity\n", "\t- Leading-order separator porosity\n", "\t- Leading-order positive electrode porosity\n", - "\t- Leading-order x-averaged negative electrode porosity\n", "\t- Leading-order x-averaged separator porosity\n", "\t- Leading-order x-averaged positive electrode porosity\n", + "\t- Leading-order negative electrode porosity\n", + "\t- Leading-order x-averaged negative electrode porosity\n", "\t- Porosity change\n", - "\t- Negative electrode porosity change\n", "\t- Separator porosity change\n", "\t- Positive electrode porosity change\n", - "\t- X-averaged negative electrode porosity change\n", "\t- X-averaged separator porosity change\n", "\t- X-averaged positive electrode porosity change\n", - "\t- Leading-order x-averaged negative electrode porosity change\n", + "\t- Negative electrode porosity change\n", + "\t- X-averaged negative electrode porosity change\n", "\t- Leading-order x-averaged separator porosity change\n", "\t- Leading-order x-averaged positive electrode porosity change\n", + "\t- Leading-order x-averaged negative electrode porosity change\n", "\t- Negative electrode active material volume fraction\n", "\t- X-averaged negative electrode active material volume fraction\n", + "\t- Negative electrode capacity [A.h]\n", "\t- Negative particle radius\n", "\t- Negative particle radius [m]\n", "\t- Negative electrode surface area to volume ratio\n", @@ -455,6 +463,7 @@ "\t- X-averaged negative electrode active material volume fraction change\n", "\t- Positive electrode active material volume fraction\n", "\t- X-averaged positive electrode active material volume fraction\n", + "\t- Positive electrode capacity [A.h]\n", "\t- Positive particle radius\n", "\t- Positive particle radius [m]\n", "\t- Positive electrode surface area to volume ratio\n", @@ -463,52 +472,52 @@ "\t- X-averaged positive electrode surface area to volume ratio [m-1]\n", "\t- Positive electrode active material volume fraction change\n", "\t- X-averaged positive electrode active material volume fraction change\n", - "\t- Negative electrode volume-averaged velocity\n", "\t- Positive electrode volume-averaged velocity\n", - "\t- Negative electrode volume-averaged velocity [m.s-1]\n", "\t- Positive electrode volume-averaged velocity [m.s-1]\n", - "\t- Negative electrode volume-averaged acceleration\n", + "\t- Negative electrode volume-averaged velocity\n", + "\t- Negative electrode volume-averaged velocity [m.s-1]\n", "\t- Positive electrode volume-averaged acceleration\n", - "\t- Negative electrode volume-averaged acceleration [m.s-1]\n", "\t- Positive electrode volume-averaged acceleration [m.s-1]\n", - "\t- X-averaged negative electrode volume-averaged acceleration\n", "\t- X-averaged positive electrode volume-averaged acceleration\n", - "\t- X-averaged negative electrode volume-averaged acceleration [m.s-1]\n", "\t- X-averaged positive electrode volume-averaged acceleration [m.s-1]\n", - "\t- Negative electrode pressure\n", + "\t- Negative electrode volume-averaged acceleration\n", + "\t- Negative electrode volume-averaged acceleration [m.s-1]\n", + "\t- X-averaged negative electrode volume-averaged acceleration\n", + "\t- X-averaged negative electrode volume-averaged acceleration [m.s-1]\n", "\t- Positive electrode pressure\n", - "\t- X-averaged negative electrode pressure\n", "\t- X-averaged positive electrode pressure\n", + "\t- Negative electrode pressure\n", + "\t- X-averaged negative electrode pressure\n", "\t- Separator pressure\n", "\t- X-averaged separator pressure\n", - "\t- Negative electrode transverse volume-averaged velocity\n", "\t- Separator transverse volume-averaged velocity\n", "\t- Positive electrode transverse volume-averaged velocity\n", - "\t- Negative electrode transverse volume-averaged velocity [m.s-2]\n", "\t- Separator transverse volume-averaged velocity [m.s-2]\n", "\t- Positive electrode transverse volume-averaged velocity [m.s-2]\n", - "\t- X-averaged negative electrode transverse volume-averaged velocity\n", "\t- X-averaged separator transverse volume-averaged velocity\n", "\t- X-averaged positive electrode transverse volume-averaged velocity\n", - "\t- X-averaged negative electrode transverse volume-averaged velocity [m.s-2]\n", "\t- X-averaged separator transverse volume-averaged velocity [m.s-2]\n", "\t- X-averaged positive electrode transverse volume-averaged velocity [m.s-2]\n", "\t- Transverse volume-averaged velocity\n", "\t- Transverse volume-averaged velocity [m.s-2]\n", - "\t- Negative electrode transverse volume-averaged acceleration\n", + "\t- Negative electrode transverse volume-averaged velocity\n", + "\t- Negative electrode transverse volume-averaged velocity [m.s-2]\n", + "\t- X-averaged negative electrode transverse volume-averaged velocity\n", + "\t- X-averaged negative electrode transverse volume-averaged velocity [m.s-2]\n", "\t- Separator transverse volume-averaged acceleration\n", "\t- Positive electrode transverse volume-averaged acceleration\n", - "\t- Negative electrode transverse volume-averaged acceleration [m.s-2]\n", "\t- Separator transverse volume-averaged acceleration [m.s-2]\n", "\t- Positive electrode transverse volume-averaged acceleration [m.s-2]\n", - "\t- X-averaged negative electrode transverse volume-averaged acceleration\n", "\t- X-averaged separator transverse volume-averaged acceleration\n", "\t- X-averaged positive electrode transverse volume-averaged acceleration\n", - "\t- X-averaged negative electrode transverse volume-averaged acceleration [m.s-2]\n", "\t- X-averaged separator transverse volume-averaged acceleration [m.s-2]\n", "\t- X-averaged positive electrode transverse volume-averaged acceleration [m.s-2]\n", "\t- Transverse volume-averaged acceleration\n", "\t- Transverse volume-averaged acceleration [m.s-2]\n", + "\t- Negative electrode transverse volume-averaged acceleration\n", + "\t- Negative electrode transverse volume-averaged acceleration [m.s-2]\n", + "\t- X-averaged negative electrode transverse volume-averaged acceleration\n", + "\t- X-averaged negative electrode transverse volume-averaged acceleration [m.s-2]\n", "\t- Negative particle concentration\n", "\t- Negative particle concentration [mol.m-3]\n", "\t- X-averaged negative particle concentration\n", @@ -602,14 +611,18 @@ "\t- Ambient temperature\n", "\t- Inner SEI thickness\n", "\t- Inner SEI thickness [m]\n", - "\t- X-averaged inner SEI thickness\n", - "\t- X-averaged inner SEI thickness [m]\n", "\t- Outer SEI thickness\n", "\t- Outer SEI thickness [m]\n", + "\t- X-averaged inner SEI thickness\n", + "\t- X-averaged inner SEI thickness [m]\n", "\t- X-averaged outer SEI thickness\n", "\t- X-averaged outer SEI thickness [m]\n", + "\t- SEI thickness\n", + "\t- SEI thickness [m]\n", "\t- Total SEI thickness\n", "\t- Total SEI thickness [m]\n", + "\t- X-averaged SEI thickness\n", + "\t- X-averaged SEI thickness [m]\n", "\t- X-averaged total SEI thickness\n", "\t- X-averaged total SEI thickness [m]\n", "\t- X-averaged negative electrode resistance [Ohm.m2]\n", @@ -617,9 +630,10 @@ "\t- X-averaged inner SEI concentration [mol.m-3]\n", "\t- Outer SEI concentration [mol.m-3]\n", "\t- X-averaged outer SEI concentration [mol.m-3]\n", - "\t- Negative SEI concentration [mol.m-3]\n", + "\t- SEI concentration [mol.m-3]\n", "\t- X-averaged SEI concentration [mol.m-3]\n", "\t- Loss of lithium to SEI [mol]\n", + "\t- Loss of capacity to SEI [A.h]\n", "\t- Inner SEI interfacial current density\n", "\t- Inner SEI interfacial current density [A.m-2]\n", "\t- X-averaged inner SEI interfacial current density\n", @@ -632,50 +646,31 @@ "\t- SEI interfacial current density [A.m-2]\n", "\t- X-averaged SEI interfacial current density\n", "\t- X-averaged SEI interfacial current density [A.m-2]\n", - "\t- Inner positive electrode SEI thickness\n", - "\t- Inner positive electrode SEI thickness [m]\n", - "\t- X-averaged inner positive electrode SEI thickness\n", - "\t- X-averaged inner positive electrode SEI thickness [m]\n", - "\t- Outer positive electrode SEI thickness\n", - "\t- Outer positive electrode SEI thickness [m]\n", - "\t- X-averaged outer positive electrode SEI thickness\n", - "\t- X-averaged outer positive electrode SEI thickness [m]\n", - "\t- Total positive electrode SEI thickness\n", - "\t- Total positive electrode SEI thickness [m]\n", - "\t- X-averaged total positive electrode SEI thickness\n", - "\t- X-averaged total positive electrode SEI thickness [m]\n", - "\t- X-averaged positive electrode resistance [Ohm.m2]\n", - "\t- Inner positive electrode SEI concentration [mol.m-3]\n", - "\t- X-averaged inner positive electrode SEI concentration [mol.m-3]\n", - "\t- Outer positive electrode SEI concentration [mol.m-3]\n", - "\t- X-averaged outer positive electrode SEI concentration [mol.m-3]\n", - "\t- Positive SEI concentration [mol.m-3]\n", - "\t- X-averaged positive electrode SEI concentration [mol.m-3]\n", - "\t- Loss of lithium to positive electrode SEI [mol]\n", - "\t- Inner positive electrode SEI interfacial current density\n", - "\t- Inner positive electrode SEI interfacial current density [A.m-2]\n", - "\t- X-averaged inner positive electrode SEI interfacial current density\n", - "\t- X-averaged inner positive electrode SEI interfacial current density [A.m-2]\n", - "\t- Outer positive electrode SEI interfacial current density\n", - "\t- Outer positive electrode SEI interfacial current density [A.m-2]\n", - "\t- X-averaged outer positive electrode SEI interfacial current density\n", - "\t- X-averaged outer positive electrode SEI interfacial current density [A.m-2]\n", - "\t- Positive electrode SEI interfacial current density\n", - "\t- Positive electrode SEI interfacial current density [A.m-2]\n", - "\t- X-averaged positive electrode SEI interfacial current density\n", - "\t- X-averaged positive electrode SEI interfacial current density [A.m-2]\n", + "\t- Lithium plating concentration\n", + "\t- Lithium plating concentration [mol.m-3]\n", + "\t- X-averaged lithium plating concentration\n", + "\t- X-averaged lithium plating concentration [mol.m-3]\n", + "\t- Lithium plating thickness\n", + "\t- Lithium plating thickness [m]\n", + "\t- X-averaged lithium plating thickness [m]\n", + "\t- Loss of lithium to lithium plating [mol]\n", + "\t- Loss of capacity to lithium plating [A.h]\n", + "\t- Lithium plating interfacial current density\n", + "\t- Lithium plating interfacial current density [A.m-2]\n", + "\t- X-averaged lithium plating interfacial current density\n", + "\t- X-averaged lithium plating interfacial current density [A.m-2]\n", "\t- Electrolyte tortuosity\n", - "\t- Negative electrolyte tortuosity\n", "\t- Positive electrolyte tortuosity\n", - "\t- X-averaged negative electrolyte tortuosity\n", "\t- X-averaged positive electrolyte tortuosity\n", + "\t- Negative electrolyte tortuosity\n", + "\t- X-averaged negative electrolyte tortuosity\n", "\t- Separator tortuosity\n", "\t- X-averaged separator tortuosity\n", "\t- Electrode tortuosity\n", - "\t- Negative electrode tortuosity\n", "\t- Positive electrode tortuosity\n", - "\t- X-averaged negative electrode tortuosity\n", "\t- X-averaged positive electrode tortuosity\n", + "\t- Negative electrode tortuosity\n", + "\t- X-averaged negative electrode tortuosity\n", "\t- Separator volume-averaged velocity\n", "\t- Separator volume-averaged velocity [m.s-1]\n", "\t- Separator volume-averaged acceleration\n", @@ -691,16 +686,30 @@ "\t- Pressure\n", "\t- Negative particle flux\n", "\t- X-averaged negative particle flux\n", + "\t- Negative effective diffusivity\n", + "\t- Negative effective diffusivity [m2.s-1]\n", + "\t- X-averaged negative effective diffusivity\n", + "\t- X-averaged negative effective diffusivity [m2.s-1]\n", + "\t- Negative electrode SOC\n", "\t- Negative electrode volume-averaged concentration\n", "\t- Negative electrode volume-averaged concentration [mol.m-3]\n", "\t- Total lithium in negative electrode [mol]\n", "\t- Positive particle flux\n", "\t- X-averaged positive particle flux\n", - "\t- Total lithium in electrolyte [mol]\n", + "\t- Positive effective diffusivity\n", + "\t- Positive effective diffusivity [m2.s-1]\n", + "\t- X-averaged positive effective diffusivity\n", + "\t- X-averaged positive effective diffusivity [m2.s-1]\n", + "\t- Positive electrode SOC\n", "\t- Positive electrode volume-averaged concentration\n", "\t- Positive electrode volume-averaged concentration [mol.m-3]\n", "\t- Total lithium in positive electrode [mol]\n", - "\t- Total concentration in electrolyte [mol]\n", + "\t- Porosity times concentration\n", + "\t- Separator porosity times concentration\n", + "\t- Positive electrode porosity times concentration\n", + "\t- Negative electrode porosity times concentration\n", + "\t- Total lithium in electrolyte\n", + "\t- Total lithium in electrolyte [mol]\n", "\t- Ohmic heating\n", "\t- Ohmic heating [W.m-3]\n", "\t- X-averaged Ohmic heating\n", @@ -730,12 +739,25 @@ "\t- Current collector current density\n", "\t- Current collector current density [A.m-2]\n", "\t- Leading-order current collector current density\n", - "\t- SEI interfacial current density\n", - "\t- SEI interfacial current density [A.m-2]\n", - "\t- SEI interfacial current density per volume [A.m-3]\n", + "\t- X-averaged negative electrode SEI interfacial current density\n", + "\t- Negative electrode SEI interfacial current density\n", + "\t- X-averaged positive electrode SEI interfacial current density\n", + "\t- Positive electrode SEI interfacial current density\n", + "\t- Negative electrode lithium plating reaction overpotential\n", + "\t- X-averaged negative electrode lithium plating reaction overpotential\n", + "\t- Negative electrode lithium plating reaction overpotential [V]\n", + "\t- X-averaged negative electrode lithium plating reaction overpotential [V]\n", + "\t- X-averaged negative electrode lithium plating interfacial current density\n", + "\t- X-averaged positive electrode lithium plating interfacial current density\n", + "\t- Negative electrode lithium plating interfacial current density\n", + "\t- Positive electrode lithium plating interfacial current density\n", "\t- X-averaged negative electrode total interfacial current density\n", "\t- X-averaged negative electrode total interfacial current density [A.m-2]\n", "\t- X-averaged negative electrode total interfacial current density per volume [A.m-3]\n", + "\t- SEI film overpotential\n", + "\t- X-averaged SEI film overpotential\n", + "\t- SEI film overpotential [V]\n", + "\t- X-averaged SEI film overpotential [V]\n", "\t- Negative electrode exchange current density\n", "\t- X-averaged negative electrode exchange current density\n", "\t- Negative electrode exchange current density [A.m-2]\n", @@ -746,20 +768,16 @@ "\t- X-averaged negative electrode reaction overpotential\n", "\t- Negative electrode reaction overpotential [V]\n", "\t- X-averaged negative electrode reaction overpotential [V]\n", - "\t- Negative electrode surface potential difference\n", "\t- X-averaged negative electrode surface potential difference\n", - "\t- Negative electrode surface potential difference [V]\n", "\t- X-averaged negative electrode surface potential difference [V]\n", - "\t- SEI film overpotential\n", - "\t- X-averaged SEI film overpotential\n", - "\t- SEI film overpotential [V]\n", - "\t- X-averaged SEI film overpotential [V]\n", "\t- Negative electrode open circuit potential\n", "\t- Negative electrode open circuit potential [V]\n", "\t- X-averaged negative electrode open circuit potential\n", "\t- X-averaged negative electrode open circuit potential [V]\n", "\t- Negative electrode entropic change\n", + "\t- Negative electrode entropic change [V.K-1]\n", "\t- X-averaged negative electrode entropic change\n", + "\t- X-averaged negative electrode entropic change [V.K-1]\n", "\t- X-averaged positive electrode total interfacial current density\n", "\t- X-averaged positive electrode total interfacial current density [A.m-2]\n", "\t- X-averaged positive electrode total interfacial current density per volume [A.m-3]\n", @@ -773,20 +791,16 @@ "\t- X-averaged positive electrode reaction overpotential\n", "\t- Positive electrode reaction overpotential [V]\n", "\t- X-averaged positive electrode reaction overpotential [V]\n", - "\t- Positive electrode surface potential difference\n", "\t- X-averaged positive electrode surface potential difference\n", - "\t- Positive electrode surface potential difference [V]\n", "\t- X-averaged positive electrode surface potential difference [V]\n", - "\t- Positive electrode SEI film overpotential\n", - "\t- X-averaged positive electrode SEI film overpotential\n", - "\t- Positive electrode SEI film overpotential [V]\n", - "\t- X-averaged positive electrode SEI film overpotential [V]\n", "\t- Positive electrode open circuit potential\n", "\t- Positive electrode open circuit potential [V]\n", "\t- X-averaged positive electrode open circuit potential\n", "\t- X-averaged positive electrode open circuit potential [V]\n", "\t- Positive electrode entropic change\n", + "\t- Positive electrode entropic change [V.K-1]\n", "\t- X-averaged positive electrode entropic change\n", + "\t- X-averaged positive electrode entropic change [V.K-1]\n", "\t- Negative electrode interfacial current density\n", "\t- X-averaged negative electrode interfacial current density\n", "\t- Negative electrode interfacial current density [A.m-2]\n", @@ -805,52 +819,6 @@ "\t- Exchange current density\n", "\t- Exchange current density [A.m-2]\n", "\t- Exchange current density per volume [A.m-3]\n", - "\t- Negative electrode oxygen interfacial current density\n", - "\t- X-averaged negative electrode oxygen interfacial current density\n", - "\t- Negative electrode oxygen interfacial current density [A.m-2]\n", - "\t- X-averaged negative electrode oxygen interfacial current density [A.m-2]\n", - "\t- Negative electrode oxygen interfacial current density per volume [A.m-3]\n", - "\t- X-averaged negative electrode oxygen interfacial current density per volume [A.m-3]\n", - "\t- Negative electrode oxygen exchange current density\n", - "\t- X-averaged negative electrode oxygen exchange current density\n", - "\t- Negative electrode oxygen exchange current density [A.m-2]\n", - "\t- X-averaged negative electrode oxygen exchange current density [A.m-2]\n", - "\t- Negative electrode oxygen exchange current density per volume [A.m-3]\n", - "\t- X-averaged negative electrode oxygen exchange current density per volume [A.m-3]\n", - "\t- Negative electrode oxygen reaction overpotential\n", - "\t- X-averaged negative electrode oxygen reaction overpotential\n", - "\t- Negative electrode oxygen reaction overpotential [V]\n", - "\t- X-averaged negative electrode oxygen reaction overpotential [V]\n", - "\t- Negative electrode oxygen open circuit potential\n", - "\t- Negative electrode oxygen open circuit potential [V]\n", - "\t- X-averaged negative electrode oxygen open circuit potential\n", - "\t- X-averaged negative electrode oxygen open circuit potential [V]\n", - "\t- Positive electrode oxygen interfacial current density\n", - "\t- X-averaged positive electrode oxygen interfacial current density\n", - "\t- Positive electrode oxygen interfacial current density [A.m-2]\n", - "\t- X-averaged positive electrode oxygen interfacial current density [A.m-2]\n", - "\t- Positive electrode oxygen interfacial current density per volume [A.m-3]\n", - "\t- X-averaged positive electrode oxygen interfacial current density per volume [A.m-3]\n", - "\t- Positive electrode oxygen exchange current density\n", - "\t- X-averaged positive electrode oxygen exchange current density\n", - "\t- Positive electrode oxygen exchange current density [A.m-2]\n", - "\t- X-averaged positive electrode oxygen exchange current density [A.m-2]\n", - "\t- Positive electrode oxygen exchange current density per volume [A.m-3]\n", - "\t- X-averaged positive electrode oxygen exchange current density per volume [A.m-3]\n", - "\t- Positive electrode oxygen reaction overpotential\n", - "\t- X-averaged positive electrode oxygen reaction overpotential\n", - "\t- Positive electrode oxygen reaction overpotential [V]\n", - "\t- X-averaged positive electrode oxygen reaction overpotential [V]\n", - "\t- Positive electrode oxygen open circuit potential\n", - "\t- Positive electrode oxygen open circuit potential [V]\n", - "\t- X-averaged positive electrode oxygen open circuit potential\n", - "\t- X-averaged positive electrode oxygen open circuit potential [V]\n", - "\t- Oxygen interfacial current density\n", - "\t- Oxygen interfacial current density [A.m-2]\n", - "\t- Oxygen interfacial current density per volume [A.m-3]\n", - "\t- Oxygen exchange current density\n", - "\t- Oxygen exchange current density [A.m-2]\n", - "\t- Oxygen exchange current density per volume [A.m-3]\n", "\t- Negative electrode potential\n", "\t- Negative electrode potential [V]\n", "\t- X-averaged negative electrode potential\n", @@ -880,10 +848,10 @@ "\t- X-averaged positive electrolyte potential [V]\n", "\t- X-averaged electrolyte overpotential\n", "\t- X-averaged electrolyte overpotential [V]\n", - "\t- Gradient of negative electrolyte potential\n", "\t- Gradient of separator electrolyte potential\n", "\t- Gradient of positive electrolyte potential\n", "\t- Gradient of electrolyte potential\n", + "\t- Gradient of negative electrolyte potential\n", "\t- Electrolyte current density\n", "\t- Electrolyte current density [A.m-2]\n", "\t- Negative electrolyte current density\n", @@ -894,6 +862,28 @@ "\t- X-averaged electrolyte ohmic losses\n", "\t- X-averaged concentration overpotential [V]\n", "\t- X-averaged electrolyte ohmic losses [V]\n", + "\t- Negative electrode surface potential difference\n", + "\t- Negative electrode surface potential difference [V]\n", + "\t- Negative electrode oxygen interfacial current density\n", + "\t- X-averaged negative electrode oxygen interfacial current density\n", + "\t- Negative electrode oxygen interfacial current density [A.m-2]\n", + "\t- X-averaged negative electrode oxygen interfacial current density [A.m-2]\n", + "\t- Negative electrode oxygen interfacial current density per volume [A.m-3]\n", + "\t- X-averaged negative electrode oxygen interfacial current density per volume [A.m-3]\n", + "\t- Negative electrode oxygen exchange current density\n", + "\t- X-averaged negative electrode oxygen exchange current density\n", + "\t- Negative electrode oxygen exchange current density [A.m-2]\n", + "\t- X-averaged negative electrode oxygen exchange current density [A.m-2]\n", + "\t- Negative electrode oxygen exchange current density per volume [A.m-3]\n", + "\t- X-averaged negative electrode oxygen exchange current density per volume [A.m-3]\n", + "\t- Negative electrode oxygen reaction overpotential\n", + "\t- X-averaged negative electrode oxygen reaction overpotential\n", + "\t- Negative electrode oxygen reaction overpotential [V]\n", + "\t- X-averaged negative electrode oxygen reaction overpotential [V]\n", + "\t- Negative electrode oxygen open circuit potential\n", + "\t- Negative electrode oxygen open circuit potential [V]\n", + "\t- X-averaged negative electrode oxygen open circuit potential\n", + "\t- X-averaged negative electrode oxygen open circuit potential [V]\n", "\t- Positive electrode potential\n", "\t- Positive electrode potential [V]\n", "\t- X-averaged positive electrode potential\n", @@ -912,14 +902,40 @@ "\t- Local voltage [V]\n", "\t- Terminal voltage\n", "\t- Terminal voltage [V]\n", + "\t- Positive electrode surface potential difference\n", + "\t- Positive electrode surface potential difference [V]\n", + "\t- Positive electrode oxygen interfacial current density\n", + "\t- X-averaged positive electrode oxygen interfacial current density\n", + "\t- Positive electrode oxygen interfacial current density [A.m-2]\n", + "\t- X-averaged positive electrode oxygen interfacial current density [A.m-2]\n", + "\t- Positive electrode oxygen interfacial current density per volume [A.m-3]\n", + "\t- X-averaged positive electrode oxygen interfacial current density per volume [A.m-3]\n", + "\t- Positive electrode oxygen exchange current density\n", + "\t- X-averaged positive electrode oxygen exchange current density\n", + "\t- Positive electrode oxygen exchange current density [A.m-2]\n", + "\t- X-averaged positive electrode oxygen exchange current density [A.m-2]\n", + "\t- Positive electrode oxygen exchange current density per volume [A.m-3]\n", + "\t- X-averaged positive electrode oxygen exchange current density per volume [A.m-3]\n", + "\t- Positive electrode oxygen reaction overpotential\n", + "\t- X-averaged positive electrode oxygen reaction overpotential\n", + "\t- Positive electrode oxygen reaction overpotential [V]\n", + "\t- X-averaged positive electrode oxygen reaction overpotential [V]\n", + "\t- Positive electrode oxygen open circuit potential\n", + "\t- Positive electrode oxygen open circuit potential [V]\n", + "\t- X-averaged positive electrode oxygen open circuit potential\n", + "\t- X-averaged positive electrode oxygen open circuit potential [V]\n", + "\t- Oxygen interfacial current density\n", + "\t- Oxygen interfacial current density [A.m-2]\n", + "\t- Oxygen interfacial current density per volume [A.m-3]\n", + "\t- Oxygen exchange current density\n", + "\t- Oxygen exchange current density [A.m-2]\n", + "\t- Oxygen exchange current density per volume [A.m-3]\n", "\t- X-averaged open circuit voltage\n", "\t- Measured open circuit voltage\n", "\t- X-averaged open circuit voltage [V]\n", "\t- Measured open circuit voltage [V]\n", "\t- X-averaged reaction overpotential\n", "\t- X-averaged reaction overpotential [V]\n", - "\t- X-averaged SEI film overpotential\n", - "\t- X-averaged SEI film overpotential [V]\n", "\t- X-averaged solid phase ohmic losses\n", "\t- X-averaged solid phase ohmic losses [V]\n", "\t- X-averaged battery open circuit voltage [V]\n", @@ -933,7 +949,21 @@ "\t- Change in measured open circuit voltage [V]\n", "\t- Local ECM resistance\n", "\t- Local ECM resistance [Ohm]\n", - "\t- Terminal power [W]\n" + "\t- Terminal power [W]\n", + "\t- LAM_ne [%]\n", + "\t- LAM_pe [%]\n", + "\t- LLI [%]\n", + "\t- Loss of active material in negative electrode [%]\n", + "\t- Loss of active material in positive electrode [%]\n", + "\t- Loss of lithium inventory [%]\n", + "\t- Loss of lithium inventory, including electrolyte [%]\n", + "\t- Total lithium [mol]\n", + "\t- Total lithium in particles [mol]\n", + "\t- Total lithium lost [mol]\n", + "\t- Total lithium lost from particles [mol]\n", + "\t- Total lithium lost from electrolyte [mol]\n", + "\t- Total lithium lost to side reactions [mol]\n", + "\t- Total capacity lost to side reactions [A.h]\n" ] } ], @@ -975,7 +1005,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1034,7 +1064,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6951e504f62142baab46cc55542f2d0f", + "model_id": "d0efa462d5f34b83b235bb2ea110e66b", "version_major": 2, "version_minor": 0 }, @@ -1083,7 +1113,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0922b30728f5443db458dac815259893", + "model_id": "3a8dd8ff8d38408496b78180138260a7", "version_major": 2, "version_minor": 0 }, @@ -1143,7 +1173,7 @@ "[1] Joel A. E. Andersson, Joris Gillis, Greg Horn, James B. Rawlings, and Moritz Diehl. CasADi – A software framework for nonlinear optimization and optimal control. Mathematical Programming Computation, 11(1):1–36, 2019. doi:10.1007/s12532-018-0139-4.\n", "[2] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", "[3] Scott G. Marquis, Valentin Sulzer, Robert Timms, Colin P. Please, and S. Jon Chapman. An asymptotic derivation of a single particle model with electrolyte. Journal of The Electrochemical Society, 166(15):A3693–A3706, 2019. doi:10.1149/2.0341915jes.\n", - "[4] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", + "[4] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", "\n" ] } @@ -1155,7 +1185,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1169,7 +1199,20 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, diff --git a/examples/notebooks/models/Validating_mechanical_models_Enertech_DFN.ipynb b/examples/notebooks/models/Validating_mechanical_models_Enertech_DFN.ipynb index bcc6054c3c..1229d09341 100644 --- a/examples/notebooks/models/Validating_mechanical_models_Enertech_DFN.ipynb +++ b/examples/notebooks/models/Validating_mechanical_models_Enertech_DFN.ipynb @@ -77,8 +77,7 @@ ], "source": [ "# update parameters, making C-rate and input\n", - "chemistry = pybamm.parameter_sets.Ai2020\n", - "param = pybamm.ParameterValues(chemistry)\n", + "param = pybamm.ParameterValues(\"Ai2020\")\n", "capacity = param[\"Nominal cell capacity [A.h]\"]\n", "param.update({\n", " \"Current function [A]\": capacity * pybamm.InputParameter(\"C-rate\")\n", @@ -87,11 +86,11 @@ "# update the mesh\n", "var = pybamm.standard_spatial_vars\n", "var_pts = {\n", - " "x_n": 50,\n", - " "x_s": 50,\n", - " "x_p": 50,\n", - " "r_n": 21,\n", - " "r_p": 21,\n", + " var.x_n: 50,\n", + " var.x_s: 50,\n", + " var.x_p: 50,\n", + " var.r_n: 21,\n", + " var.r_p: 21,\n", "}\n", "\n", "# define the simulation\n", @@ -324,7 +323,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, diff --git a/examples/notebooks/models/compare-comsol-discharge-curve.ipynb b/examples/notebooks/models/compare-comsol-discharge-curve.ipynb index 0d7e369bbb..4987acc5ef 100644 --- a/examples/notebooks/models/compare-comsol-discharge-curve.ipynb +++ b/examples/notebooks/models/compare-comsol-discharge-curve.ipynb @@ -92,8 +92,7 @@ "param.process_geometry(geometry)\n", "\n", "# create mesh\n", - "var = pybamm.standard_spatial_vars\n", - "var_pts = {"x_n": 31, "x_s": 11, "x_p": 31, "r_n": 11, "r_p": 11}\n", + "var_pts = {\"x_n\": 31, \"x_s\": 11, \"x_p\": 31, \"r_n\": 11, \"r_p\": 11}\n", "mesh = pybamm.Mesh(geometry, model.default_submesh_types, var_pts)\n", "\n", "# discretise model\n", @@ -115,7 +114,7 @@ "outputs": [ { "data": { - "image/png": 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\n", "text/plain": [ "
" ] @@ -220,7 +219,7 @@ "[2] Marc Doyle, Thomas F. Fuller, and John Newman. Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell. Journal of the Electrochemical society, 140(6):1526–1533, 1993. doi:10.1149/1.2221597.\n", "[3] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", "[4] Scott G. Marquis, Valentin Sulzer, Robert Timms, Colin P. Please, and S. Jon Chapman. An asymptotic derivation of a single particle model with electrolyte. Journal of The Electrochemical Society, 166(15):A3693–A3706, 2019. doi:10.1149/2.0341915jes.\n", - "[5] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", + "[5] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", "\n" ] } @@ -232,7 +231,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -246,7 +245,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.12" }, "toc": { "base_numbering": 1, diff --git a/examples/notebooks/models/compare-ecker-data.ipynb b/examples/notebooks/models/compare-ecker-data.ipynb index e681da01fc..f0f732e8e2 100644 --- a/examples/notebooks/models/compare-ecker-data.ipynb +++ b/examples/notebooks/models/compare-ecker-data.ipynb @@ -80,8 +80,7 @@ "model = pybamm.lithium_ion.DFN()\n", "\n", "# pick parameters, keeping C-rate as an input to be changed for each solve\n", - "chemistry = pybamm.parameter_sets.Ecker2015\n", - "parameter_values = pybamm.ParameterValues(chemistry)\n", + "parameter_values = pybamm.ParameterValues(\"Ecker2015\")\n", "parameter_values.update({\"Current function [A]\": \"[input]\"})" ] }, @@ -100,11 +99,11 @@ "source": [ "var = pybamm.standard_spatial_vars\n", "var_pts = {\n", - " "x_n": int(parameter_values.evaluate(model.param.L_n / 1e-6)),\n", - " "x_s": int(parameter_values.evaluate(model.param.L_s / 1e-6)),\n", - " "x_p": int(parameter_values.evaluate(model.param.L_p / 1e-6)),\n", - " "r_n": int(parameter_values.evaluate(model.param.R_n_typ / 1e-7)),\n", - " "r_p": int(parameter_values.evaluate(model.param.R_p_typ / 1e-7)),\n", + " var.x_n: int(parameter_values.evaluate(model.param.L_n / 1e-6)),\n", + " var.x_s: int(parameter_values.evaluate(model.param.L_s / 1e-6)),\n", + " var.x_p: int(parameter_values.evaluate(model.param.L_p / 1e-6)),\n", + " var.r_n: int(parameter_values.evaluate(model.param.R_n_typ / 1e-7)),\n", + " var.r_p: int(parameter_values.evaluate(model.param.R_p_typ / 1e-7)),\n", "}" ] }, @@ -168,7 +167,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -233,9 +232,11 @@ "[2] Marc Doyle, Thomas F. Fuller, and John Newman. Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell. Journal of the Electrochemical society, 140(6):1526–1533, 1993. doi:10.1149/1.2221597.\n", "[3] Madeleine Ecker, Stefan Käbitz, Izaro Laresgoiti, and Dirk Uwe Sauer. Parameterization of a Physico-Chemical Model of a Lithium-Ion Battery: II. Model Validation. Journal of The Electrochemical Society, 162(9):A1849–A1857, 2015. doi:10.1149/2.0541509jes.\n", "[4] Madeleine Ecker, Thi Kim Dung Tran, Philipp Dechent, Stefan Käbitz, Alexander Warnecke, and Dirk Uwe Sauer. Parameterization of a Physico-Chemical Model of a Lithium-Ion Battery: I. Determination of Parameters. Journal of the Electrochemical Society, 162(9):A1836–A1848, 2015. doi:10.1149/2.0551509jes.\n", - "[5] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", - "[6] Giles Richardson, Ivan Korotkin, Rahifa Ranom, Michael Castle, and Jamie M. Foster. Generalised single particle models for high-rate operation of graded lithium-ion electrodes: systematic derivation and validation. Electrochimica Acta, 339:135862, 2020. doi:10.1016/j.electacta.2020.135862.\n", - "[7] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", + "[5] Alastair Hales, Laura Bravo Diaz, Mohamed Waseem Marzook, Yan Zhao, Yatish Patel, and Gregory Offer. The cell cooling coefficient: a standard to define heat rejection from lithium-ion batteries. Journal of The Electrochemical Society, 166(12):A2383, 2019.\n", + "[6] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", + "[7] Giles Richardson, Ivan Korotkin, Rahifa Ranom, Michael Castle, and Jamie M. Foster. Generalised single particle models for high-rate operation of graded lithium-ion electrodes: systematic derivation and validation. Electrochimica Acta, 339:135862, 2020. doi:10.1016/j.electacta.2020.135862.\n", + "[8] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", + "[9] Yan Zhao, Yatish Patel, Teng Zhang, and Gregory J Offer. Modeling the effects of thermal gradients induced by tab and surface cooling on lithium ion cell performance. Journal of The Electrochemical Society, 165(13):A3169, 2018.\n", "\n" ] } @@ -247,7 +248,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -261,9 +262,22 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, "nbformat_minor": 2 -} \ No newline at end of file +} diff --git a/examples/notebooks/models/electrode-state-of-health.ipynb b/examples/notebooks/models/electrode-state-of-health.ipynb index ce489139be..4b6ecc0ece 100644 --- a/examples/notebooks/models/electrode-state-of-health.ipynb +++ b/examples/notebooks/models/electrode-state-of-health.ipynb @@ -51,7 +51,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "78bde48e716c491dacc055847b13bb53", + "model_id": "0edfe2b03a894ade9ddf7e21240eaad4", "version_major": 2, "version_minor": 0 }, @@ -65,7 +65,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 2, @@ -81,7 +81,7 @@ " \"Discharge at 1C until 2.8V\",\n", " \"Hold at 2.8V until C/50\",\n", "])\n", - "parameter_values = pybamm.ParameterValues("Mohtat2020")\n", + "parameter_values = pybamm.ParameterValues(\"Mohtat2020\")\n", "\n", "sim = pybamm.Simulation(spm, experiment=experiment, parameter_values=parameter_values)\n", "spm_sol = sim.solve()\n", diff --git a/examples/notebooks/models/lithium-plating.ipynb b/examples/notebooks/models/lithium-plating.ipynb index 4f260176b8..29b946e420 100644 --- a/examples/notebooks/models/lithium-plating.ipynb +++ b/examples/notebooks/models/lithium-plating.ipynb @@ -51,8 +51,7 @@ "model2 = pybamm.lithium_ion.DFN(options={\"lithium plating\": \"irreversible\"})\n", "\n", "# pick parameters\n", - "chemistry = pybamm.parameter_sets.Chen2020_plating\n", - "parameter_values = pybamm.ParameterValues(chemistry)\n", + "parameter_values = pybamm.ParameterValues(\"Chen2020_plating\")\n", "#parameter_values.update({\"Reference temperature [K]\": 268.15})\n", "parameter_values.update({\"Ambient temperature [K]\": 268.15})\n", "#parameter_values.update({\"Initial temperature [K]\": 268.15})\n", @@ -555,7 +554,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.6" + "version": "3.8.12" }, "toc": { "base_numbering": 1, diff --git a/examples/notebooks/models/pouch-cell-model.ipynb b/examples/notebooks/models/pouch-cell-model.ipynb index 17ce645965..a0be651d88 100644 --- a/examples/notebooks/models/pouch-cell-model.ipynb +++ b/examples/notebooks/models/pouch-cell-model.ipynb @@ -45,8 +45,6 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[33mWARNING: You are using pip version 21.0.1; however, version 21.1.3 is available.\n", - "You should consider upgrading via the '/home/user/Documents/PyBaMM/env/bin/python3.8 -m pip install --upgrade pip' command.\u001b[0m\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } @@ -77,16 +75,7 @@ "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/user/Documents/PyBaMM/pybamm/models/full_battery_models/base_battery_model.py:303: UserWarning: 1+1D Thermal models are only valid if both tabs are placed at the top of the cell.\n", - " warnings.warn(\n" - ] - } - ], + "outputs": [], "source": [ "cc_model = pybamm.current_collector.EffectiveResistance({\"dimensionality\": 1})\n", "dfn_av = pybamm.lithium_ion.DFN({\"thermal\": \"x-lumped\"}, name=\"Average DFN\")\n", @@ -154,15 +143,14 @@ "metadata": {}, "outputs": [], "source": [ - "var = pybamm.standard_spatial_vars\n", "npts = 16\n", "var_pts = {\n", - " "x_n": npts,\n", - " "x_s": npts,\n", - " "x_p": npts,\n", - " "r_n": npts,\n", - " "r_p": npts,\n", - " "z": npts,\n", + " \"x_n\": npts,\n", + " \"x_s\": npts,\n", + " \"x_p\": npts,\n", + " \"r_n\": npts,\n", + " \"r_p\": npts,\n", + " \"z\": npts,\n", "}" ] }, @@ -562,7 +550,7 @@ "outputs": [ { "data": { - "image/png": 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EQRAEQSgpRMQIgiAIgiAIglBSiIgRBEEQBEEQBKGkaNcihojKieh9IvpJFmWIiG4horlE9BQR1Wjn7yGi2e3FJyK6j4heJKKFRHRZlmWvJKL5RPQCEQ3Uzl1DRB+0B5+K0J8ORPQ8Ec0jov8Q0YlZlG2VZ6kYfXLKXktEH+XYptZ6vl8kon87v29pqU9EdD4RLXfsvUhEssyuIAiC0O5p1yIGwLcBLMmyzAkAOjLzJAAPAZjuniCiQ9HyJSyLzadvMPPRAMYD+A4RdUlSiIiGA5jMzEcAuBrAb5RzvQEMbUc+FZs/TQC+xcwTAZwE4KYsyrbWs1SMPgHAHwEck22hVn6+AeCrzHw0M38vHz4BuNOxdzQzf9JC3wRBEASh6Gm3IoaIOgM4EcCjSlo5Ef0fEc1x3hiPNRQ9CsBTzud/OMcuPwXw6/bkEzPvcT5WAVgJYKfj13VE9JLzxvikCJ+edmy8DOAwzafr2otPRehPIzOvcA4bAFiOPwV7lorRJ8evNa4vKoV8vgEwgAedaMrkPPl0rnN9ryWidvvvuiAIgiC4tOcvu/9B+G3wNwB8wMzHAJgK4EZDuR4ANjmfNwPoDgBEdDSA9wCsbWc+gYgeBrAMwDxmbiaiKQC6M/NRAI4F8CsiohifACDt2DoQQGdmfqs9+VRs/ijcCGCG87ngz1IR++RRBPfuq07E6jwAfyKiLi3xCcDfAYyALXIGADirBb4JgiAIQklQVmgH8gkRfRfAaQCWA+jBzD8novOVLIcAmOB0GACg2omOuG+BfwJgI/zhK9XwOw0/BnAGshzaUuQ+fcDM32TmrxJRRwAvE9FMx6ejiOhFp0glgB5EdDeAzgBu1XwCgGbn99UAfpaNP8XoU7H5Y/KJiH4KYCsz/8XJUvBnqRh9MmQp+L0DAGb+mIjeBDCkJT4xsydsiOhB2MPz7svWR0EQBEEoKZi53f0AOA7AvwE8C+Bt2G9zTwbwHQCXKfkqDGVPBHCH8/lM2OPOuwB4w7H3EoD1AK5qBz6RWx/sqNxcAIMAfAHAHzL4NALAc87nCQAedD67bXwWwA4AN5eyT8Xmj2L7uwDuBUBKWsGepWL1ybE5EMBs5bjQz3dX53MXAIsB1LTQp25KnusBfCeX6yQ/8iM/8iM/8lNKP8TMaM84UY9+zPxLIioHcAuAYc7phcz8P1r+lJPnUABbAZzLzBuU8wMB/B8zH1fqPjl1P+8cVgB4iJlvcs79EsBE2OP3VzHzOYbyPwUwBcAe2JPfl2nnP2DmIaXsU7H545TpBWAN7A51k5N8LGyRVahnqeh8csp+F3Y0ZwSA1wF8m5k/LPDz/R/Y84bKAdzAzDOdczn5RES/gv2SpAnAUqeNjdn4JQiCIAilRrsXMYIgCIIgCIIgtC/a88R+QRAEQRAEQRDaISJiBEEQBEEQBEEoKUTECIIgCIIgCIJQUoiIEQRBEARBEAShpBARIwiCIAiCIAhCSdGuNrsUBEEQhL2R+vr6DshyY1hBEIQiZzeATbW1tcallGWJZUEQBEEoYerr6zsMGjTo0U6dOvUttC+CIAj5wrKsxm3btr3x8ccff6e2tnaPfl4iMQCI6EJmvqPQfqiIT8kQnzJTbP4A4lNSitEnoSjp1qlTp76VlZWyyakgCO2KVCo15uOPP+4Be0Pt4LkC+FOMXFhoBwyIT8kQnzJTbP4A4lNSitEnQRAEQSg4ImIEQRAEQciK+fPndxg9evTwurq6YePHjx/67rvvVgDAzp076ZRTThlUW1s77JRTThm0c+dOAoClS5dWjB8/fujo0aOH//jHP+5TWO+FXJk7d27HI4444sBx48YNveiii/oBgGVZOO+88/avra0ddswxxwxZu3ZtGgDWrl2bPuaYY4bU1tYOO++88/a3LKuwzgtZM3HixAO7d+9+2PTp0/d107K93/Pmzes4evTo4Ycffvjwm2++uUc+/dtr58RQx94MazcAApp3A+kqLQOpB3rphPmCyaQchkpR8NhqbEC6vEO0S4YaM50H2Es0eUoRB+7HPXsaUFHRIZAY0WKjL35+Mto3ZY607/xnV0MDqjp0MJ+PMB5KUpw11hfjR9CEnWvnzp3o2LFjyNfIshGVZ+tL1DXfvmMnunTqGGmUlOciU/2x9zXqWlP435it2xpQ3aVD5ueAFP8S+xJuT/ieAwAH0jdt2YXu1VXas+3XHa5POWeoJOwHh30hQ5qbj4D1G/egZ01F0FdSbSnXxvAHXP/WjueYeYruudC+qK+v3/fggw9+ti2Hk61cubKsS5cuVvfu3a2ZM2dW/+1vf6t54oknls+YMWOfdevWlf3ud79bc/nll+/bq1evpunTp6876aSTBn/3u9/9bMqUKdsnTJgw9Lbbblt5+OGH72orf4WWs2vXLpo8efKQp59++sPu3bt7iuSRRx7p+tBDD3V/6KGHPrr11lt7vPvuu1V//OMfP/nOd77Td+TIkQ2XXHLJxq9+9asDp02btvG0007bWsg2CNnx4Ycflj/99NNdV61aVTFjxow1QPb3e/To0cMfeOCBZQMHDmwcPXr08Jdeeum9ffbZpzmpD7t37y5ftGjRlNra2tBwsr13Toy1G+h3NEAp+wfk/IaTRgBSynk4x24+NW/KP+emeb1N8pLLCEiD7d9OWhpAipwfp0PiHZNdC5GfTu5vp3zK6eQR+ecBBI49t4i94xT5+dw00spTqHwwb+7lKWjDzWMsT8Hyqk2iQPlg/cE6/PJkaAN5nVDfJ7+8d97LQ1q7XB91Xw11KfUE22++JkRsvq4xaV6bvTQOX8NAeY64X5wxbyjNqS9Yl1Y/2HmGw+lu/lD5UF1aXhjSvHzshZzd47BfTjoMaeT7mySv//fKxnS7rOXY1WySpdVjOXbUdMtJt3/7acpFS9ktTvX5T08IQivQv3//JvdzVVWVVVZWxgAwd+7czj/+8Y8/BYBTTz11829+85s+06dPX/fOO+90mDJlynYAOOGEEzbPnj27sypiFi5cWPXNb35zYGVlpVVZWckvv/zy+23dJiGef/3rX506depkTZ06dfDOnTtTV1999eopU6ZsnzNnTpeTTjppCwBMmzZt8/HHH38gALzyyitdrrnmmk8B4OSTT948Z86cLqqIWblyZdlXvvKVA9LpNDMzPfvss+/X1NRIuKaIOOCAA0IvRrK531/84he37dy5MzV8+PA9ADBu3LjtL7/8cqepU6d6z8FTTz3V5YorrujXsWPH5v3333/PI488siKpf3uviBEEQRCEdsaIEQcftGHDhrx8t/fo0aNp8eJF78bl2bp1a+rnP/953zvvvHMFAGzcuLGsZ8+ezU755k2bNpUBADN774K6devW/Omnn5ardp566qnqs88+e/3ll1++vrk58UtaAcD9J159UMOm7Xm55x26d246659XG+/5qlWrKhYvXtzxrbfeemfLli3pyZMnD/3www/f2bhxY1lNTY13z7ds2ZIGgM2bN5f16NGjGQC6d+/uPQsuc+bM6Tx+/Pjtt9566ycy1Cw5zU8dfhB2b8xP/72ypil90uuxf+M62dzvtWvXlnXt2tX7g+7WrVvz+vXrA74/8sgj3a655ppPvvKVr2zN9m9f5sQIgiAIgpA1u3fvpi996UuDf/jDH35aW1u7C7A7Lxs2bEgDwMaNG9Pdu3dvAgByQ4kAtmzZkq6pqWlSbV1yySXr33vvvapTTjll0M9+9jOZM1OE9OzZs6m2tnZ7TU2NNWjQoMaampqmNWvWlHXv3r1p06ZN3j2vrq5uBoDq6uqmjRs3uh1c71lwOf3007eUl5fzl770pUHf+973+u7Zs4fCtQrFRjb3u1evXk1bt25Nu2W3bNmS7tmzZ+A5+MlPfvLpE0880e2UU04ZdPPNN2c1ekAiMYIgCILQTsgUOckXzc3N+MpXvjLo5JNP3nzOOedsdtMnTZq07cknn6yeMGFCw5NPPlk9adKk7QBw0EEHNTz//POdjj/++B2zZs2qvvnmmz9W7VVVVfEdd9yxCgAmTJgwdMGCBVvGjh3b0BZtKXWiIif55qijjtpx9dVX921sbMT27dtTGzZsKO/du3fT0Ucfve3xxx/vfs4552x+5JFHqidMmLANACZMmLDtkUceqb7ooos2PvPMM9VTp07dpNpramqiG2+8cTUATJs2bcBjjz3W9cwzz9zSFm0pZbKNnOSbbO53x44duWPHjtb7779f0b9//8YFCxZ0/u1vf7tatde7d+/me++9d6VlWRg0aNDB55133sakwwpFxAiCIAiCkBX33ntv9zlz5lSvW7eu/MEHH+wxYsSInffcc8/Hl1xyyfqvfe1rA2tra4ftt99+e2bOnLkCAH73u9+t+vrXvz7wRz/6Ueq4447bMnr06MCk/v/7v/+r+etf/9qDiNCrV6/GQw89VCb9Fxk9e/Zsvuiii9aOHz9+WGNjI/3iF79YVVZWhqlTp279xz/+0a22tnZYly5dmh988MHlAPDzn//80zPOOGPQn//8530OOuighlNPPTUwqf+ZZ57pMmPGjD7pdBoVFRXW8ccfv70wLROiOOOMMwYsXLiw8549e+i1117rOHv27A+zvd833XTTymnTpg1mZnzzm9/8TJ/Uf+211/Z+4YUXujIzJk2atDWbeVF77+pkVd1YJvYHJ3PLxH7VJ5nYLxP728XE/npmroPQrinE6mSCIAhtQdzqZDInRhAEQRAEQRCEkkJEjCAIgiAIgiAIJYWIGEEQBEEQBEEQSgoRMYIgCIIgCIIglBQiYgRBEARBEARBKClExAiCIAiCIAiCUFKIiBEEQRAEISfeeuutyrKystHPPfdcZwDYuXMnnXLKKYNqa2uHnXLKKYN27txJALB06dKK8ePHDx09evTwH//4x30K67WQC5Zl4dxzz+0/atSo4QcffPCI22+/vcZNP++88/avra0ddswxxwxZu3ZtGgDWrl2bPuaYY4bU1tYOO++88/a3rMTbfwhCIkTECIIgCIKQEz/72c/2Gzt2rLdJ4a233tpz2LBhu+rr65cOHTp016233toTAH74wx/2u/rqq1e/9tprS15++eWur7/+elXhvBZyob6+vmrp0qVVb7zxxpK5c+cu/eUvf7kfADz22GNdGxoaUvX19UunTp266ZprrukDANdcc02f0047bWN9ff3SnTt3ph977LGuhW2B0N4QESMIgiAIQta88MILnXr37t2477777nHT5s6d2/nLX/7yZgA49dRTN8+dO7czALzzzjsdpkyZsh0ATjjhhM2zZ8/urNpauHBh1ahRo4aPGzdu6JFHHnlgGzZDSEj//v0by8vLeffu3bRly5Z0dXV1MwDMmTOny0knnbQFAKZNm7b5lVde6QIAr7zySpfTTz99CwCcfPLJm+fMmdNFtbdy5cqyurq6YePGjRs6duzYYRs3bpQ+qZAVZYV2oGDs3vIcPvx7z7aoip3fjc6PIAhCG7G+0A4Ibcv5h1990NaNO/Ly3d61plPT3a9f/W7U+V/+8pf7PvDAA8svueSS/d20jRs3lvXs2bMZAHr06NG8adOmMgBgZnLzdOvWrfnTTz8tV2099dRT1Wefffb6yy+/fH1zc3M+3N9r+Ph7Zx7UvG1LXu55ukt10/63PGC85/vss0/z4MGDdw8ePPjghoaG1M033/wRYN/zmpoa755v2bIlDQCbN28u69GjRzMAdO/e3XsWXObMmdN5/Pjx22+99dZPZKiZkAt7rYhh5imF9kEQBEEQSpEHH3ywevTo0Tv69OkTUBzdu3dv3rBhQxoANm7cmO7evXsTABCR+z4PW7ZsSdfU1DSp5S655JL1V1111b6nnHLKoEMOOaThV7/61adt0Q4hOU888UTXNWvWlH/00Udvb9iwIX3EEUcMnzp16pbu3bs3bdq0ybvnboSmurq6aePGjemePXs2b9682XsWXE4//fQtb7zxRscvfelLg/r167fn97///eqqqio21S0IJvZaESMIgiAI7Y24yEk+ef311zvMmzevy6RJkzovXbq0wwcffFA1aNCgZZMmTdr25JNPVk+YMKHhySefrJ40adJ2ADjooIMann/++U7HH3/8jlmzZlXffPPNH6v2qqqq+I477lgFABMmTBi6YMGCLWPHjm1oi7aUOlGRk3zDzOjWrVtzWVkZunXrZjU2NlJTUxMdffTR2x5//PHu55xzzuZHHnmkesKECdsAYMKECdseeeSR6osuumjjM888Uz116tRNqr2mpia68cYbVwPAtGnTBjz22GNdzzzzzC1t0RahfUDMInoFQRAEoVSpr6/f9+CDD362srKyICOWp06dOvDCCy9cf8IJJ2zfvn07fe1rXxu4evXqiv3222/PzJkzV3Ts2JHffffdiq9//esDGxsbU8cdd9yWGTNmrFFt3HjjjT3/+te/9iAi9OrVq/Gxxx5bLm/li4umpiZMmzZt4IoVKyp3796dOuOMMzb85Cc/+ay5uRnnn39+/3fffbdDly5dmh988MHlffr0af7000/TZ5xxxqBt27alDzrooIa77757ZTqd9uzNnDmzesaMGX3S6TQqKiqsxx9/fNk+++wjYwmFALt37y5ftGjRlNra2jX6ORExgiAIglDCFFrECIIgtBZxIkZWghAEQRAEQRAEoaQQESMIgiAIgiAIQkkhIkYQBEEQBEEQhJJCVicTBEEQhNJm844dOz4B0LfQjgiCIOQLy7Iat23b9l8AG0znZWK/IAiCIJQ49fX1HQB0K7QfgiAIeWQ3gE21tbVGsSIiRhAEQRAEQRCEkkLmxAiCIAiCIAiCUFKIiBEEQRAEQRAEoaQQESMIgiAIgiAIQkkhIkYQBEEQBEEQhJJCRIwgCIIgCIIgCCWFiBhBEARBEARBEEoKETGCIAiCIAiCIJQUBRUxRPQcEa0jop84x+cS0QIiepmIHiSiSid9IBG9QETziehKpfwUIvq383NCodohCIIgCIIgCELbUdDNLomoH4DjAPRj5l8S0WAAHzFzMxHNALCUme8kogcB3MbMc4loNoDvAngfwOsAjnTMvQRgNDM3F6ApgiAIgiAIgiC0EWWFrJyZVxGRerxMOb0bQJPzeRQzz3U+Pw3gKAAMYDkzbwYAIloBYAiApa3rtSAIgiAIgiAIhaSgIiYKIhoOYAqASU6SOuxtM4A+AHoA2KSl17SBe4IgCIIgCIIgFJCiEzHOELN7AJzBzLucZEvJUg1go/PTzZAeZ/tCABfaB+lalHfOj9MAQN5/kmZOmDXfNtu2btI/U2YvKEPVUTbjIHBymwmbTZTFVU+YMZXpwqgfNaNRRZP6GTSnVxY8NLXHdC8ytds9TdSCaxRRLkXx99wrTgARx5nybaaS2mSkKMFQXWKkU/4/byHT6m0gS6mbo7IBAF5ftH09M++T2QGhvdCzZ08eOHBgod0QBEHIO/X19cbvtKISMUTUE8CjAC5i5g+VU28S0QRmfgXAiQAuhT0nZhARdXXyDALwQZx9Zr4DwB0AQJXdGP2OyqfzACVdJyGFZD3vFJDKZNNVBWXK57j8ZUA6iU0CKJ3IJqXL/c6o2Tuk7JqRTiMyr0s5GJXak2mySwDKU2y87Hr+MmJURDztgY40gLJAPg7lc6koA9IRqiPeZpSfjMpyiuyk6x3+snS0OlGTO1RSMMVwS1Nk35tUKsOzSUCagKrKcL6ASHWqLC8DUoZ8uhAoL0fo/uh5XLFRWRFqijF/h6pGlKWj63WPKcWoLG8G6fdauWxusU5Vu5BOK/4AANjLT7D/bNNpC5VlTYArZMjOp5lFKtWILp13O0ccFFTKtbTbvRvptAXvnY4ivIjcNADM6Dpk3kcQ9ioGDhyIhQsXFtoNQRCEvENExu+0gooYIvozgAkAKomoDsAqAH0B3OjMlbmPme8EcAWAO4moAsA/mXmxU/4KAM855q4o3KT+LKIbeTfHCPW0WkzLberFPItsOBlTTi9PWlpSG0nennPAt7D1DK4nsGk4bzjNiPeXObkfUcEVHYuBdPTpgAkigJlCPqptYbYTokSte11iBa120xmaJjAZ1pOUehQd4dtkABYCAiag95T8tlAh5bR/kokDbWNmMPw0MtxochLtf+vcz74fzP47DGYCg8CwwteMAPs1gZ0j3/8cCYIgCEKuzLt0CkYNXYiq6gbs2tIBb7xXh4k3PZsX24We2P8tQ/J3DfmWATjGkP4MgGdawbWEtKS3ENG7banJjDayrCBBz90NhBjFg2ZKNclavrhqvA6i8jY7stIWEI67RA8zyklIJE3PcC+TXCsXBiWy6S9UGL7pITGSw6Nrumd6TUbR5fbLKfgM6flNQteLZmg2g3W6csM8VEz3j7xKCKmQ+HGfF0cWsXKtXAFGbporYEiJunh3yynAXkFm9u6RHX301R25Q9KIAFZH3wqCIAhCYZh36RTUjliAVz/6MkZ9+Vd449arMG7EE5h36ZS8CJmiGk5WOrTCq858mSyCt7BJOu1u108XQOY389FREVY7iQnrTCYAks2RSKQbY3zS0/138hkqSCoiKJdHggyfNBRhEWeFLXjD/VgTEAHBQQgLDlOdhuiPW8YbVahVkI2IZFVoQKnPYIcAsBeZ0Z/RYGQGAChFgUiJeX6LLu/9NDUCp4oZVxDBjQbFTqwSBEEQhLZh1NCFePWjLwPWHvCDo3HgGf/Eqw8CdUOfzIt9ETFZUcTixSWXMU+RhrK3majDyH4nMb5sZiGR9Fyy+vRITFg8ZbIRb9NMQLhF+ZlALan1pLTE7B4J/4Z71VL4eiLm2D8RnayWSekno4tGVhE1DC8Qoclg1MvHtuhixGgCZQiZasH1wY2puEPE2E1jgFKs/Vm5V9ocRXEjNuzYJ8dJe9geAyl2IkoAZXm3BUEQBKE1qKpuQJ8Vr2LIYSsAAG/f/XPUXXEnqmbNzIv9pDPRBQDB4R3aT4KFiIL4Q0Eif3L1i+OMsv163PjDyk8m59RhLsGOZJyX6ht31s5ZSpozyMbtBkb+ZKwPmgjQzocutZfIoTyh/KZLG/Gja0K97YlueYK+qRrN8Tv1GSwHQiKqV1qnXk8I5U5WjRpNcG2yfhKZr4ma3WQzMc4D6dlQ/QECfxIE8sQNvHkq4fvp2SNXzDjixc1jEWApEsZ9ThR76h2wI47+cDf3b84P5hDY8v9iBEEQBKGQzPnJtwEGDhy1Ak0N5Zj3zjQcecPfsfDG6di1pUNe6pBITIvJtcsQfA9rNpe1MjIXDVWThc8Zs3J2XjpvuJXDUDXu+kt639roikE/qlfWPZe2ACsd0V83lA/mCrfQFV3qW4BsnwST36ohk71kvvv5LLfznVV0IxwfcA8YACzbbiqm8caIFJt9ZAYsR0dTSvvLoGD+qLuiDgMLaPV0OKYW8M3wLMIRCK5QYOVhYlepBvwKShhfvMBbGMB7pliJzJDdbstipFLuCwHbeX2omR0JI/+FAfltthcbsA8sS6lUEARBEArAy5edjImHz7G/0y3g1UVHou6qGXjxygswbsATqF88FhPzUI+ImJzIJD7yY7LFGG2qXe8ElUZoLb0aS/mcQPcEMulv1FUBwtBtBjtoel1xdat2k13uzJ1BtYOd3K4Zgt0JTUfcnnhZFQ8rjqoCISJ33En7fiid6KghXLFV6Hmcm6zbzCqg4hj17DnHqogL1cvx0SrvlBIBsUMxdkXefBT4Q7nCz6zWFsVR0s4GtYvrnDuh3wrbDPjuKiYRMYIgCELbs/LN19H88DQcMeYTcDOw+v1eWLFhEGqHv4KqWQNQ16+DLWDaw+pkpYupk5Bt91XLnw+TOrHRmKgMCV6p61Yo2GkzRVE8U5p4MXlk8sTveGoxlgz21HrjIhvBczEd2gjUbiSRuf2Z0KWD2heliNuTLax06t1lfz3TmdWN0VdvOWW30WrxGFOqUCE3wOGkWepwKVO0xGQvzl/tWgaiM0olbkTDaxsFy9k+KMO6LDuFUlr9AZt2A1mZ7+JpD2dVMbftbu3krcms/NafdVLioOxvhJl4j1pBEARByBMv/r+pOOLw55A6iLFnWyUWbrgAk35+PfZX8nQG8hKBcRERU9Rk6o3ovcUEPXqkEL8ppxYT4SQ2w8Tpp6T98dCwI6iRGT81VrwY/NHr0EVO0uWDM+4yrwqnhDajlFYospHFvYgSi96HCIGXtU1VVyYUL5oboYZaikCKutZh8RDjpFOHKjbDsT1NIAfssPJfTcipNr2IEEO3F2q303B2oi9ulMvfj4eVpZhd/xS70JeGFhUjCIIgtA1NjY347+XH4YjahUilgd1bK7Fh3CxMOryu1esWEZMXcuk0ZBh8lMik24lRREmL+y/5sal31AKd5gw29VMGj7J+I5+pA+xGKFKBHrhfS5LhUZE2IzRjRpuGE15nOeGIoZAJU0fa8dPf7DL62SSonWuzbXUhA6Ml5ZwroKLyuDedHbvpKE2d4cZ4ekQVbaz6FyOG1RvlLqmsrmbhzEnxbDIcR5WVxiKEorpnjH3MXrr/m8DMIKQANEN9LpVYT/KHQhAEQRDywGsP3oM+H/wMY8eth9WUwqKFB2DYL1/B/h07tkn9ImJaRJ7eeOZNeCC3nnESmxlEh7EjqtWoDt+JCDjoNUd5lFNEIspmOGKTbDhZzIv+kEiIImf3W9hfNd1SVm+QgUxBDlaMmoIYuuiIewYCjir5rSzEm/5Mep81m6wa1RwIDHlzTxNAUfvDKFEVb/aZoa2eXU55lZJjN+ikD8OCxWwLbfJ9cSv2jmVOjCAIgtDKvHTpF3FE3YugwUDDpg5YRNMx/obpbeqDiJicaUHv2TTBwWiOkGyAe0S+fGisBDaSdu5d1GFhbn79ioRtsPEo02aXqq0MWkyxS8ajqPyZbCbqrCvpoaFVhgLZ2AycSeJwApuJpbC62SWiH1N1uJjRtkGcm/Q6GRPMYib429llhYM2SH9Qdf9IXdI4OOfF0xNe9MeZ66JGWQIRF9VH90nww1reamlew8m/dk4l6maagiAIgpBv9jTsxKIrj8IRde+CUraA2X7sSxg/fGSb+yIiJmtaoYfQGp2OvNik+MktXmKmGEp05MQkYIJED/OJgmHeAClbseV1CmPKJbGpW4gVIKa39qqRmIsVlyXJNTQNngv04SMMhoQDzPncx0mPapj8MG1OGue3vYGk2Sf92XN9YJh9IDUThc8H8/rzUoLKh8FQhpkBzv4yhJQjNBQtErBIoQ0v7Qzs7EtDXhl1Hg3DXjwASjRHEARBEPLHvD/8CiObb8FhY7aheU8aC14fh4l/eB6dC+SPiJjEZOgYZPmGO4nJnGhTm27nCoFx/dG5g5ENXfro4oMCueJt6l4FpjHAHAGIJ7Mgy+elTmQrh+fLvhZu1zep+Qg56QgFexUt32bsCEbt70KXvO5jYxJK2US5Aks+pyLunha18z5y8EnzIkbkrLTH7lwpX9a6z5257Yo9cvKTImac3TLJ2xvGbQMDsDSbvlcEbbNL8ufhWI5vflRGEARBEPLHi5eehIlj5oAI2La2E1b0mYGJfzi/oD6JiElMVMegBV3ZjFGO1rCZtAuu9SaNNvUJxslc03+r5ZtjbEVFOfR0tRPoDcZpRmhRtkzyKOijL8CsUK6kNoP+qWUsLSGba2CyT4Cyy3ywYMhGKCF4VVV/mRHcFCjCRpSg0YcSOoEENLP9j5EuCtzF8aKeWtOwQrbMeQLRF4MxvZ3qULJmb5iZH/HwTbh7xBgGI7rlWJEWjvjgZgJSsCftE2tiBkGbZEdYAnkUm54fDDRLIEYQBEFoAfMunYJRQxeiqroBu7ZUYfvmTpg4ZgMAYNvaLmg69RWMGji4wF6aR920GUT0HBGtI6KfOMdERLcQ0VwieoqIapz0Gud4rnPeeclJo4loPhG9QkTnt7H3iO8ZZknUq+O828yRyGE1dqKVoLokssn9UfvKudpk7TMjl0sSXcriXG1mqDHCoNrWbOpkxaY2cinn51a1GXke0RGw0HVzIils5SYM4fqjGGXLsan5yeqHDNfa0SxKFAWABW0hMFVikddu0+X10gieEds/8ofQOZGaUNsc8ePlcQ78+US5P+WCIAiCANgCpnbEAixcdQpeevdMpMubsc/ADbAa05j31qnodtmn6FkEAgYosIgB8A0A/6McnwCgIzNPAvAQAHeZg+kAZjrpnZx8AHALgLMBHA3g+0TUvS2ctmHkvdMQMmfqvpHhJxubVtQJM0k6ulrQJig+/HpMNZlaoXYJzR4mv+6mXF5p7TIG52EkvDZZ2cyM24l3O99GoZCr8GBbeOkrfIVvceYYldqp18WDminuCgbuuRv1oKCPmaNGYb9c4REgRsyom0yqVajRIO/+slKW4W12aXZSfxgAJgus7B2jzn9x57yw61Tozij1BJ49C8GNNEXECIIgCLkxauhCvPrRl0Hb1+Cogx5ARadG7NzUAY0N5Tj6t38ttHsBCipimHmVlnQUgKecz/9wjo3pRFQJoBMzL2fmPQDmAhjbKo66rzoDP6ngDwxpUT9GIaL9qJtMBmiBaIosFmMzgVYzJVtwxUywE+eSRIbpkRQ32sNKySTRH+/Nt24/rrMcZScDrWWT9QI5ChkXy9Cpz2bekP44uFGUJHiRAyVa4QkENZLCgGUF/YyLUpF+oKhgt5guDFkpYv9WhIxiVF09Tf9zYCu67QQ4k+6dv4jANWY7oEK6X2QLmoiXGf68F+WVgauqRMAIgiAILaCqugEHVr2AieNfBhjY8FF37Pj8PFR23VVo10IUOhKj0wPAJufzZgBuZKXGOXbTa5y8m+HjpkdCRBcS0UIiWghrTw7uJYx+JKYlHQ61w5JPf5L0EuMx9CG9dNNvU3mTR6Z30nE2AvkNGT0fjRGKoIWk3UPdpic+DBht6nkVNwId3SweHVM0Q50g7vkZ75lfnOzOfsCuq73dCJKjOI3CSFEB7sfA1VYjKU4UxL0/MZfH/Iwa0tz7A/af0fDTavBZ/aD45woczybbQtte7ti9EAiINrdw0LXgamPupqIAnBXHyLDymH0n7NO2Ixz5AkQQBEEQonnz/40CAPQZsg4NmzrgP59ehl5XrMKSv8zAri0dCuucgWITMRsBdHM+V8MXNJucYzd9o5ZXTY+Eme9g5jpmrkOqIgu38ilcdLstrS5h9zpXmwnK6adNHiXtc/udSrNNPTqTxJ+otGg/M4SeYjBGKLI0E4q66OezcM0kNLw6dJumjBGpXnTIMxBOM7Vd9yeqmVGBBdVeqG0mf3394B3r0R57CJ9lFEOKNnCiM65oIMWeLkUAZoY6gNKor5wxdET+T8qtJ+CnLUyIyBk2xkGb7n9YXX5ZyCdR8zK1PFOI6N/OzwlK+pXO3M0XiGigk1ZFRPc79u4noion/TtE9B4RfdBmjRMEYa/nk7ffwvKfDMHBde8DAJobCf/96HiMOu9SvHjlBRg34Am88V5dgb0MU2wi5iUAX3A+f8E5NqYz8y4AO4ioPxGVA5gIYEHruNVGwzRaQyuFbGZZQRb6KPhjXzN/lL+/+pIaTFDfxPt7l5vrcHO7/wPM82zMZZOhdQ8DNkwv+ZOQNFoUyJ9BR2Vj01vcN8Nj7AuEYCZzBzxR0CNgKi5iQtopUhK9yfW6SDI3I9iRj3CSAkmsPKUGe1ob/FGl9gdvEr83GceLwwTnDLmRGqc8iJQISzDN/3EHZlqwLPbteRfIj8S4y5xTaEKQkAei5mUCAIgoDWAGgBOdnxlElCai4QAmM/MRAK4G8BunyPkAljj2ljrHAPAogLbfMU4QhL2WFy7/Grq/cjT6H7QGe7ZXoH7BKCx4fSLGDHweVbMGoK7fk6hfPBYTb3q20K6GKOgSy0T0ZwATAFQSUR2ArwA4iYjmAtgK4Fwn6wwA9xLRxQDeAjDLSf8BgL/B/jb/IzNvQqvRiq83W0O4FMxWss0p1SFEpKWFq82tU2aKEJnSw2VYO462ncRmJr/UdDUS5eUzVZJFhdk/DmT4pMFKPzrOinJeXS6ZtDzu3JBM/sbd04DwURIz3cMQjlhKecIiOr++UWVQovvHtvAgZ78Z//my280R5dVa2Y7GuEeOeVIb7u4bo68lLuSDowD81vnsztdUv9GHAFjOzJsBgIhWOGlHAXgaAJj5ZSK6XbE3Q7E3HcD/MvNap3xrtUMQBAEAsHHlR0g/NhZHHr4dRMDKxfuhw5lPYNyFwfconWFHCYqRgooYZv6WIfkSQ74NAL5oSF8I4IicKg+8rk2SWf2dR4r9uyrLXnrUpoomcaALAVPXizJWHi1wAqIoInJgtqZ7Fi4T96I/uYcGWwn9jEIVh0AyYZDJnlves+V1vBWxE1VBMFsYx9mUnhZXTLNpEsHGiEqk0aBo82xQMEoYKk5wYjjBxOA1d26osvcLmLyNLsmJrPhLJFta82xhYw9fY8+em5+dMXxMjJTnT7H/o1KSmOZlqqjzOdU8PQCsVtLThvwme4kgogsBXAgA/fv3z8WEIAh7IS9ddwVqu/4ZHXo1gBl4bcHBGHPTq4V2K2tks8usyNQjy8Fe1CTcllQT62ZSQWboJUZVx/6O5kmuUFQUw8rgXbaXJJCfw+Xj7WWO/qgd3mQ2kxElCLK4Y9q15ZBRCn1Q8Uur+QIxAgqXyCSYIgWe+2dgsKkLGjKkqZ89z5WTRh2uPd6Ba6fbZ+fZdCpn8gUIiLxBjUYB5doKGGWw5Vxbp0vLzlg++w28upmmEsnx1IstXlLexXCGr1nsDHGT4WS54AwJm2849TT8eZmbYZ5/GTVHU09vNuQ32UsEM98B4A4AqKurkxsvCEIsny37ELvvPQ5HDFkHSjE+/aAnVve/AmNuuqjQruWEiJisUb8nWtplNZTXe965kk83E0RjspF3eqv0svb7aLNIyMZ+4M28BXA6G3te9x+m+8DwV8vK1seou+qmW+68CcP5uEiD6Za7K48lla56LtY/kL3ssWUBqZSxiDF6AyAwKT8kYNm+R0Tw9nFUMT2Canv1zTzdCfuc8n0I2FAOWLPlCl52f5N/zGDAYlBKva4BTzyhxfD1hHodPX+InWvJSKedk15DgsPK7FXdbfFCTgJ7ed0ojS2GWN8ISEgEMzcDGG86R0SdYc/HfMD5/ZiW5X0Ag4ioq3M8CMAHsIN4NwG4iYgmAHjTOf+SY+cNBOd/CoIgtAqv3Po71Ha8FmVDm9HcmMKrrx+NSb9/Cn0L7VgLkMHTLYL9n3wFaBSTeTMasKlvdpmABD11V3iYu/v2T9wbeoJ5Yn+cvTibptxAVq3OnJsS5coKy/I72bEre2WJt/QxlEcrR4OuOMm08lo218Qdncbw/VTdTOKue930zS7Vtrt+BUSF5qsq+AgGWyBtbxhVypA3oMsUpSPXoLNsWkB0qeEoZyybm8bOhQlEnwjK0D7lry/b5fCEJMwAcJYzX7MRzrxMIrqJiPZxBNAVAJ5zfq5g5mZmXgxgHhHNB/ArAFc69u4GcIhj7xDnGET0VSKaDWA/IprtCB9BEISc2dOwE//9wecwpus1KKtqRlNDGV5ddxkm/f6pzIWLHInEtJgWdS1zLJ9DmcgiCcMsMbbcN9XeW3XndyqQOSz09OhAlCfByAoFuoxJrqAeEXDLMfyIR5IrmlQwtcRmqO3+y/a8aFpW+rnexPVQ3ZmvaiAqpKgCiltiTkGv1xUv6v41prxx3XMyHWjhK/f+BGx5YsJ/trwiqp/eZ/ajM5aTP2Wqn5SPDPb+MpwszEDKTnPbzl4JZx6MYWhY0H81euNIqHy9UBE8YuZlXqp8fgbAM4Y81wK4VktrAPA1Q96HATzcco8FQRCAF37yHUwY+ABGj2uE1ZjCwv/WoXbG85hUXl5o1/KCiJgWk0AERJJrbyOHOjMWiRqwY+zlhiDD56BFp2OWoYz+21QHA0h5VtmYJymsNTtY3q8xG7uqzbhyxnMRDWfbjeilg3OoRxUOFMiY2XhUDm/DR/LriBJqxnTtfrhRlLCPBl+MoY/4Ogh6lRzMHKqP/V/an4oqYN2haN7GNNqfkSJvlEn69u/gEDzyh+15SzLr8UX1uSAJxAiCIOylzLt0CkYNXYiq6gY07izHkcMbQSlg99YKLO36e4y78YJCu5hXRMTkhVZ49ZnIZJZiJiubToEkb9UTpLt9PlNURM+bisij5gsN/8mQP9N5Xczo7/yzudKqTfXNv05c5CmqTa6fqYQd1ZCJCJsMf9mkTLbcneRN0S09OkNRRt3hXRSvFdwBr26XXW23MfIS47snYMj/7IrDUIxHedDce2H/DkYC4aR5QtcNjKQJUCMvbHoOnNiickKPvLjD9mwXVAGjuqkqcInECIIg7I3Mu3QKakcswKuLxuKg/d5BjwEbwQxsX9cJ6XPeweE1+xTaxbwjIqZFtLS3YHhP3RodkGx6ex4c+JUkChP7hh1+ZznKnLEzm4kEfsURPXAqLJei2pXcZrLyAR0VJYBiREyuj1B4s0ulc52wjiiXQ+UziU7NFVdIRDU7KghjrEaPlLEyNFH/c1T1geIHOYWN0RsnqmJBWZrZZJdUAeNuWKlLf/83w5nYT4rvpNhzP3Bw2JogCILQ/hk19L/Y9FlnTBw/F0TAjg2dsOiDkTh02Nvo3A4FDCAiJkfypTTI+DHfptvCTlDAmDv+UVEUijgXJOJMFjowibhgw6e4MklsJhUA7rmAzQjVl0QoGM/ECSND2CqTr5lwq/OaQWE3nP585j1tNN9Vm2qkL2g4+voHf9te+sPAnOJKnQH/SP1tjpAQfGHIDKTd5Y8N7QyJnEArbSOWBaRTqth0Ns9UHhYyGRMEQRDaNQvvvROjqnehQ7ddYAY2fNQdnS96C4c2WaiaNaDQ7rUaImKyJp8dBHVsS5GS1Yg1jsyqdmTVNLeUuWOpOhDvnilN7d+Z3srHN8nt2oZrMAmzOJuZRn6RdmC0qd8HQ0Wmdsf5FWlAuSOqUIjtdCdRjmS41xHtMC0xncnvqI3qPYETZVB7l+BebyYA+oT9ULmgJLfbZAsPb5UyZ4iY5TQ45eQJ+qUKIH1IGSlnKFDGYgDMSKUY5NoUESMIgrBXsOGTj7Hzz0fisEHrQATs2lKJ/y47Dkf/7iEAwItXXoC6fh3QucB+thayxHJiTF1DhVwm02bVU0tiDxndTF6h8ro4vhcXeDPsdrSg/bDSO1fFC5TPbPis29F/MvVLWU9ITNALk/183bpAFKGFFQbaTXCiFMkeTjJ88o44aDNqzlCMUe/Qi1JAt4lARCb+DmhPAiG4lHJWapKU/8LfeFOx6eckcGB5MDI8x4o9gvf34LWbAbYIYLusv7yybUG9LgCBmZzFDfyhZN6cI8e6ukSzSBhBEIT2z0vXXYXOzx6M/YZ+BqSA1e/1RiplAeWdsX3derx45QUYN+AJvPFeXaFdbTUkEpMYfRBUnk2q5Go+KtTRkkpibdrdbwqlmAM4JvGi04xwfz2Xy6F3LGGF39TH2w1GItQok9q5ziXiYbqklpaQIGgQa9vr2MLrC0fbCCUEx22pARr3WobmjxjEisk507VjBpotoCxtGO1G0REmVfR60Rj9BultMNj385DnJAOBoWT6amNBe25URYlEku+X305XqXk12deSnSiKcqFdUeYJFzgCKuCHb9N9WpmBZlExgiAI7ZZP3nkXW+85HUccuhyUgr3vy+qv48irb8K8S6egbuiTqJo1E3X9OqB+8VhMvOnZQrvcaoiIyYlQVytH4aHZMXYmWwtDG6LIkE3tM6ZCZ3wTmWSgqYPqltMlRTbo4im7WxVdp6V0UPPZbwzsDaNguj6J7CkF4oRHNngd9AjBlcS/gDghv926iEvqZiBARLA3pHQeSH2vGVIO1P1f9Dq9KSyKmFE3QvIlhPqU+rFIo4+uYbckwxsCRq4d5SFg78IoS30zQd0wMxAdkzWWBUEQ2iX1P6jDoXVL0GcUo2lXGf777kR87rdP4si0vRSoKlg6A5hYID/biqITMWR/m98CoBa2fzcAeBDAzQBGAdgC4Fxm3khENQDuBVAN4A0A32duq2/wfERmtHKhV/SZuvoZMEZR1DWTcuvWh6qhKItul0x5Q63VZoripLQ0/xwpNoI2Y/1D8FJ4n2M7ywkeI61jrNvMKYJkwdsXxChmWvioudcipbadAr/g3z0z7n6Wbr85IGi0xse5G9wPRfGRDT5qvkba9AxqJ9zoiknMBC4Eh+4fKwmBZbPZj5aYwzvadSTLjtkE2hVcScyN0fjzWpSGKMsvq5ufMhhgSxmSJyJGEAShPbFkzr/Q8cULMWrcpwCAbWs7Y+vExzDxgiMK7FlhKToRA2AkgJHM/Dki6gJbnGwC0JGZJxHRuQCmA/ix83smM99HRHcBOAFAAeJmWUQ18lIXcqsv0s0MNhPoNd20Scyog3By6uBrNsPOZWlPGW6VaS50Un/VDnimpyIbmyDkLYri2mQgsNN83L4vRhva+aSiSz2vl9ejHt6+OE6nPeoVRSDyoWoINzhBftRD9UEXuO5KY6TZ0ZsRiBQ6RijghB514YAIca2wc18D826UDSspMKaNtKhRpDwXBEEQ2gG7du7Eez8Zj2EjP0LZsCbs3laBRUuGY+yN/0a3QjtXBBTjxP7VAPYQUTmALgA2AjgKwFPO+X84x4hJLxGy7XQQtO6aIT3uJ5XhR8tPhp+QTbNHplZGea+2IlPrXXsWwl242HIRxj2bbA8Pi/Imm7rcjq1nM0b4hWxG3VrFJid1JsJkIF0RCr5J0yfFHeWCql1pUv2Mu0FOf17t0weCGQGj9o+F4PA9QHueMvxpkFaG1TqcMxThMKnJTmWkHAciUM7DacsgCyDnQpBf3HdRiSy6dhwj9lwY/wLY503/XNvxSQr9jQqCIAilzIK7/wy+ry9G1n2IdGUT3ntrEPZ88S2MvfHfhXataCjGSMwmAO8DeA9AJwDfAvBFJx0ANgPo7nyucY7d9Jo4w0R0IYALAQBlHfLkbks6DBl61onrydCjzcnF5L1k04t3U5VqZ9nU14wqp3pEMceZfEtqM2nbjW00nMt5Y8oW3PKQCc0x3U91I1JVnEa6Y7j4XsRIOzaVV0WPsTKD3wRdaMZDQFBsqPaUNLZcWRz2RRXAQdHkrDbGbgjGXzIZ5G92GSfcXTGoDh3zBKK2Aad9fyxvvk3ATc8/t0ESkREEQShVdm7ejHd/dgIOr30XqS4WrMYU/vP2MZh0/ZOFdq3oKEYRczyAvgCGwJ7rMhfALMCLnFXDFzSbnOPNzu+NcYaZ+Q4AdwAAVXVr4Td9K7ztjDVp6h5nKNiGL2TDIkTvEgdTGcEwYDJXw7csSsjk2nQOlA4e5UrO/sXc8tjoSsiMsoKcLjQS+hM6T+ZDPZ/Xx4dyrwxljRtdqmkGR2PvveZQuMPv20g5KWy430Z/HFXiSj1vkWVtuJjrt+onwa7Qn7/iRlrUG6PcMWr228sMe1lmdrK6HnCgQbJNjCAIQukw79IpGDV0IaqqG9C4owxllRYOH2/BakrhjfpDMeLnz2DSed0zG9oLKcbhZARgEzM3A9gGoALAbABfcM5/AcBLzueXItLbwMV8oIxTSWzSNOSlmN68Zh7r5A4dStaBDo37CZ3NhNphzeQdaUdRu27oNuMwDcmKsulel0AZUyUJnhejsKDMRe29RwytUsq6w8FCc9r1IlrkgykwSiwY6VAS3aFVmXzXR3oFRlMptqLCIcYOv2NUHz0ZGU3RGwJXEgUlPYPAKUXRAc6cGF38qE+X7zizL7QCbVcVIImKEQRBKBXmXToFtSMW4L/LjsX7bwxAeacmpMst7NlejiWd/oTa3/8bHbuKgImiGCMxswF8jYjmAaiEvVLZPwF8gYjmAtgK4Fwn7wwA9xLRxQDegh2xaUViOgdJxjaZ7OW7v5HRXv47OBzoN8VtthcUbLoQcGflBMVNvL/Gzjb07p/fKQ6WjfTQeKSWi+oX53p11X5wS2wGBAL5qd5d0SIxRh9MoRLVP7ezrN5rCmWPdF5dyS44F8QpEmUrwmf3NztGA3NU9Lwm20pm9T54IoGBtHcNgivuBaWKkyPwfLtqzB9LyV4eBrH692MhMCxNaRm5w9cCN8/2kJ1xa+p+MoIgCELxM2roQnz0YS+MGzIblV13oWlXGhtWd0PXmu04ZOrZhXav6Ck6EeNEYM43nLrEkHcD7PkybUROSiWzSROhamLfd4ftZepJ5hHT23FjutZZDc3LQFDMxNWR1B+OSI+3GR1bIS1HPkRMyGaMkYRPgX0t2VnVS7dJ4fxBzG/z3Q69cVhYlB5X/mT0+ILqZ1SkhLWy+m/3QPXJ9TPgd0S50EcK31uCNheHWMljHoamGrY1jNoQe84MMQFp/1gVQL5NZVimp86cif+eQVuksmWLHZYllgVBEIqe+bfdgHHdGnDgqI8BAJ+81wf44n2oOXkoqmYNKLB3pUHRiZjiJ6JLlJNOMIiifOmNQE8s6cwHk5HMZVTxoXdQ1b6p97Zc80avRR0ilMt4R2MXztn4MNkV8HOx8t+QSY7se2fvn27XIAqixJkpzc1rOaIjyqZugJXPqh0vnQDLcqbBKyIpElVfa8JCLdpsAWnL9lEXu6YqQsPt3F9OOxnwNruM2+jSrcCTIexHVtwln92IkV2EAYthXCgM8AWOcuF0Xz1bxPa1dPYGIjcs42XUWqqcZ3ezSzjixn1SmZ2FCgRBEIRiZOVrr2P7A+dg7GErQARYzYT/vv45TLjheQDAi1degLp+HdC5wH6WAiJiWkTce/4kmF49R52OEhQZ6tX7M6TbiSqfRfecggIl2NkOd6iiOuemF/KWkkeXFtlccdZ+ux1d85VI2An0Ora+zYgsibEsIO2oQbXz3CKjThlXHBrvrCFEEfdkuL+9/UxMBQzXOImPbqFsBaznl3b7QvvPaD75zwIbz7tpri1PLHkGVHVG3t+D0Yq2trRXp6t8SFmhTPGE9XW1lZtoD2mzlFMiYgRBEIqNnVu3Ys11Y9B/xCdIjWY0707j4/d7onffDdhTtT+2r1uPhTdOx7gBT6B+8VhMLLTDJUBWIoaIvpMg2w5mvidHf4RY1M5JvtZkyDVKE7RgihIEO3L63IHMnWS9DjfaQzE2k6Iu9xzeGT4Uf4j0S7fplkgndCzTNQlszpinKB0rNygw/yQQokgWgVOjFsywN8802gximvcSWMmMtWiPJhiNNvUPQR2gbShpel/gPlnaZpfOZ2MkzHkwQ/eHdJ8Y9r4x6t8HB4Z+2WLLl1JqhEWtNHif7N/+8tYiYFoDIqoBcC/sVTDfAPB95uBa1kQ0BcDPncOrmfk5J/1K2MOedwO4gJlXEFEVgDsB9AewEsA3mHkXET0Me3XONIA/MfPdrd02QRBanxeu+REO73wPBh6yDczAZ8t7oPkLj2Lg18dg3qVTUDf0SVTNmom6fh1sAXNTAfZtL0GyjcRcCyDTQtVHAhAR02roHew89Wzzbi8sZmLnDmRh048maJ28XG0qUY+wmMnNvqV0OLNqb0TkRR0qlS1RReLbneyJCOVxxUyM6Io6RapBxailCAW9/YYAkjGDHoFyu58p0tug3W9djKhj1zRV4wpi274jR9xGaaJNFU2qKFEjQq6dVMpVKO6eMsqeNo4Vb4UzItkmpnWYDmAmM99HRHcBOAGA18sgojTshWaOdJJeIqLZAA4EMJmZjyCiIwH8BsAZsOd9LmHms4joZ87x/wK4kpnfd0TOIiJ6kJl3tU0TBUHIN3P/cD2G7vgDjjxgIygFbFvXCYs+mYiJMx7z8qiCpTMgEZgsyFbEvMbMX4/LQETPt8CfEiV/Hf9oc5Fd0RbYbIE9zbTp3b1JbmUTfYlDG1wT61vSCoKbM4atZzU0ymjTcN5w2kszlAsM30pAVHDFjWq5BwxknIviBTgonDnUp4+4QYGoi5JgbI+mPBjwRmKF8hsMeKKIFDNqFMr10zJEMFy/tPzuJpe+R+5J9u0xwClGYOUygwB11znzIy6KGHHzkC1k7M9BUR0Snm4kJs//HAkAgKMA/Nb5/A/nWH1VOgTAcmbeDABEtMJJOwrA0wDAzC8T0e2KvRmKvekA/peZ33fS9gBoRj7e0giC0OZsXb8BS67+Aj73uUWgfYDGnWWof/9ojPvlI5hYXl5o99oNWYkYZj5eTyOiCgA1zPxpVJ72S0t7C4YubKTJuN5wjB9t0KGJGEkTOnbf/OtvxaPKJa48+1ORhLuI0dGjrIVEtukxtzyu7vA5RQU4h3qMyeuAqz3/OJsRj22opCIikjhvFJ2K4PEHUEWLv8CzGPGQBZ9XV26wMdKlP9v+ZpfKRpdeRvd5oUD0TBVQXkTJi6woyzKTujUpKz8AM8NyFh6wFxbwPVMjMfaay3sfTvTiGNgbI9uXnPmBPJmvgb2pMpzfNdr5HvA3YVbz9ACwWklPG/Kb7F0B4EFm3h3nFBFdCOBCAOjfv39sAwRBaBuev+xsjB88C7UTdoAtYMvaLtg6biaO+OZRhXat3ZHTxH4iehDAt2G/LXoTQE8i+jUzX59P54qTfKoCMn6MxjDWJoHp3Ekeewh2IKPeFgfT1DIUk9/PbUg1vuGO9zEZyYa+5RKdiRMv/jv5gBuJFJ/RbkLntPf/GfNThF8hYeHcH1ZOmgSvab8Yo5MUPFTtpNQD93eMTVO6OgfJEyyItsPkz6MJehRc5QwAKKUOMVPtBVsS3nvGxlv0QbGZctYjZyeKQ0CCJePaLc8CeA5B0ZAYZ0jYfMOpp2ELjmrYgqMawEYtz0bY4snFzaOnNxvyB+wR0bkADgXwtUw+M/MdAO4AgLq6OonaCEIBefE3V2NczR8wecweAMD6j2qw7sBf4uD/d17oLYWQH3JdnWwYM28hotMAvADg/wH4D4C9QMTkE0MPPJuyWrTAI9Zk63RwKKFwAQzzEwx5dDGUDabha0k3uwyfje/eJ7GZqRUBARflZ5SYMdQTiEZEjC4KiKSQljYmRkZTyHRsPAgmq+UCwtZUXwyZygaetwwPp5eP7RFzcSLIPhcUIGodbkzFjZKwk2YHUfRNLf0Ykz60jZxGEak27bwWA8TszJtxbe61ImYrM1+Xa2Fnj7LxpnNE1BnAFwA84Px+TMvyPoBBRNTVOR4E4APY2vomADcR0QTYL/0A4CXHzhvO75ecer4E4EwApzDvpSE1QSgB5l06BaOGLkRVdQN2banC1nVdcMTA9UiVM6xmwqvvTMHE3zyC3oV2tJ2Tq4hxB/QdBeAZZt5JRO38H9wMHYNsX8lH9qiyMhD8HNfbanEd0dhv24PdsdAbeQCg4BvmKBnmDzlLUn9YIkTVkZxo2WGKHrUJCSvTr6c9cZ2jr6VRfJifJ1ckeLvNG2yGBJhyA0jL44ku5YLq985k01RXIOqR9c2hoA3XDwL0Fc0I/maSxHYkJhB10a2qwsMbFuZUAoDTit+wBU/gusCdqG+rKnX1tpSibv15M7qw2qsgIvobgEVwLgwz/zpPtmcAuJeILgbwFoBZToU3AfgVM68joitgR4IA4ApHFC0monlENB/2yIVvOOfvBnAXEc0FsArA1530+wEsATDL+Tf1LGb+JE9tEAQhD8y7dApqRyzAv5d9Eb2bXsOQkR+j94HrYDUTlrxxAPp89++YeM6gQru5V5CriHmXiP4JYASAHxNRhzz6VKRkMZQrW3Mqka+xE9QZ6WKC1/h5wu1DRtUY1+yo+Q7Zeq3XwYA9eVtblTrabvj9uDq8TB04ZIyaZOlfKD3m7X8m+7pf7maXgUhUjOZlw4F+b9zFsVizafRNSVSXtVZPMdtDpbzoB4J2jREmzdfAUtQcrIu0vFF/Yqx/cKJYrk/2tXSMB/xSoyr+8swMBLeQ8YSGf2HZAizLjaTAEyxE7ssB9tpFKQ4siODtLQOAyPLa3axvlLP3oI8EyNuFYOYNsJdJ1tMvVT4/A+AZQ55rYa/sqaY1wDBcjJllfztBKHJGDV2I+rcOxqhBs1G931YAwKZVXdGhyx6MnPFWgb3bu8h1s5HzANwO4Bhm3gF7UuKP8+ZVKdJSfWB8e9yC7+DIoklt6l2/eCzoC7+6dbmDaIJRGL25pg6q+pPkTBTqW/LkpTKXcAVCPruMXmfeYDSqA58EZt/f6EzBD6ZHMhBxiPAzJ5xOOWs2s4l6eYEJV3xEXEtdqFE4NWiXfTFiuVEUSy0bfJL9yEvYP/I+2Eb16Jedh5QHy/GO7f+EbHqRMUVe771rLE9h5peY+SUALwM4sdAOCYLQvnj+R99CVXUDxn+uHtX7bUXjjnK8unA8qr7+Niq7ymrobU1OkRjnLdITyvEnAPaikLfeSWilyIwxmqKeyFBv4uBRru/9nWrIV8PBt+zuIrLBxhmHASnHurJ2+3NuB0/tdCaNfJiiM2qEgkJnE2B4ix9tM2uTweiCKUMOhp2+cHDud+hxiq6EYbg/yg3KalNOJeri7VnjnLJY6/Qr9WcwF+m494wp18IvqD6xEZEgcqUC+4sVWE60xKj2ghKHyULguWUAKVv6u0MydR+jWuxHe9yQk6WscGYssjcwzv3AzExE4+IyC4IgJOXtp59Bz9cuwjGHbgAR0LSrDK+9NxFjrn0MEyoq8eKVF6CuXwdIKLVtySoSQ0ST85EngY1aIppFRHOIaAbZ3EJEc4noKWf3ZBBRjXM81zlfoK/vEnjzGRsyyD5GkV11ehwmt05+0MtcZYJmk/0OdBzZ1JZvm+rS1IHCLcCLzASGRWl5MtnQ8nhRlAziWV2JzBh8VMpb7EenogjYUQ/U4ITJT6VKo8OqHc3RkD0L3srGrkAhuALHcn7sRD2ips5z8YbBMTnDzxzprizF7M5JCkjnUNpeySYiOpuIBhPRWQC2FNohQRBKm8VzXsDr36/FsM/OQK8DNgAMbFvbGVYTYXe6N3Zt2YYXr7wA4wY8gTfeqyu0u3sd2Q4nu4GIOhBRx6gfAL9viUPOvjO/ATCVmY9h5umwd0fuyMyTADwEe2MwwN9FeRKATk6+dozem8qy05Ko45t9RyiTWb1Pm2vcR43auP3aJJ7qb/ONNp1OfZSX2VyVkM2Iuo029QiJ5opRKCT0x5iu2PJNxgytgjp8yc8d6ozH3SC2+/PquVAwIxh+s4crsvnyhA/CmTw9okZ4dB8iHFaHk9m2KDDXxd7vBf58HAuOaFfUV4Roc6+nL+xsH4hY2fjSDbHo8U5P4tjxSX8DGsOF2Cs4F8A+AC53fp9TWHcEQShVNq9Zi2VXHYgDPzkZh45fAkpbWPLWEKyv/Q+6XbYW9YvHo67fk6iaNQB1/Z5E/eKxmHjTs5kNC3kl2+FkhwLYDvO3pNvl+LSFPn3OqeMBIuoE4OewV0F7yjn/DwAXO5+PQvwuyq1MK3QWIk3G1ZWhR5uTm8l7yXrHMipNjU4YR98Y0jPVp2+JYarX/RwXp1MFEikdz6R+qOi6JW6KQs5PUMLbExqVRMFDNykYOSKjbyGRoUcnnDT1fkeVDywKYKrM4DdBFZqZIejiw7fpii4CwFZIzQQ/KgLEF03BFcdcV+389gR8C85bIr2tUJ9F32pgo0vn4rk2GfA2u0ypwkyx4x3vpXNinPmZNxbaD0EQSpeG7Tvxyv+cjvEH/wcDRjaAGdjyaRdsHXMfRp7r7+WuCpbOACYWwFchSxHDzLkuBJAN+wE4DMAoAF0A/AvAXAR3N+7ufM60i3Ir0UpvOmPNRnX/Ywq24QvZsAgxTEL2zoTLZHbVHCdgRmjVsSgHY4Ii4cyhmnInizsWFgoRmROVN6VqQkOtJo5YQROXrlx0NVqjl/GHSUXYNlwL0+UhPSEVkSf0211jLFoIeyunBUQEKUJGj5AoUTPy26k+8OoeMHYm1wc3QzN8OKhRyI4I2c+/Uwnz3jwnRhAEISeam5ux8AcTMGr0Ehw9qQkAsHZ5DyzDKZh41a2yWWWRkusSy63JRgCvMPNWAFuJaD2ANIK7G7uCZhPid1EOQEQXArgQAFBWDKtCu2/8s+l16O/Q9TTtVJvCxqOkHWDzuXDH0pQ3qc04KRhdko2p+plMwYS4fOqL+ZCPpkoSNMCYxRAV0POS6SqZBEaSi6ndJGWEWKDNutlsfGdA6cwrJiNEkRrdMP7pqe1SBYfZJe3IFzR2XEUV3+S0QYveUNBGUBQpzyCHrw07/3GXaLbH6rU/FUNE1QCGOodLne+HuPw9AfwMwMPMPLe1/RMEoXR5/uorcFjF/aibsAEAsHNTByzBdzDmql9gvwL7JsRTjCLmVQDXElEZgA4AegG4DsCXYK+I5u1uDH/X46hdlAMw8x0A7gAAquqW5Wv2DB2D5K/5FZMt6WxkG33JovfrkaxR7PWb7O5XVGCEQ915vxa1cxus1fQpWDpJHzpZtEf3Knubud7ROEEW1dk3Ebh2XqdfHaakpofrCV1tgzN2NEHb7DJKMGh9arUOb0iX4o/+J5GpyWo5dTU3NhRUhU3wI4Xrchy1YAuklNe+4Ip74egNBa+FF15ynlN2nlgGKLA3DJw5MJbx+XdXQwuuXWL5Ni1496b9SRgA9kusM2FfhpsAxIoY2C+0/gA7qi8IgoB5l07BqKELUVXdgF1bOmDZ+/ui337rccyQraAUsGtLJd77cDBG/e6/GNMOXwa1R9pieFhWMPNmALcAeBHAbAA/AvBPAI3O7sZnAfidk30GgLOc9EY4uyi3kmfI1/CikEn9x0Pv2obeYYfzRbqYi+/J/ohNb7qNtVHwvLu3jNr0ZqWs3mLTDxB9GdU6kMFmuAXRqDaT+qhb1293wE+3M+oJBt9QEjHmvZPnYMdet6muEBa8lv4Ud3XvFnehAiviBlGmC6DYUO01W34+/cqzK0jUOgzXUt2zx3I79Vqe0F3VfAw8N44N189mS/GTLLDzP7ckK6V9gaMMJ7MI7P647W92lIlz95nZ2+zSt+//laRS6j1lwFnBzE4jR8xQVvOGSoiBsIcXd3E+hyCic53ftQAeBnAoM8e+2BIEYe9g3qVTUDtiARauOgWv0Z+xdX0nHFS3DNV9t6KxoRwL356Mym+sweHXL0TBFroVsqYYIzFg5vsA3KclX2LIZ9xFuXVRe3AK+XjmQzZyCe8g2FsLFc//H6ceSVHT4zrdJomWyWYSjPktgNOIjRSZLUT3CNXVsvJ5VfXoRXZeabbgd8ozvqVn9YMhOqH453bQ9YUVkqI/2c0MpB1n9TlOSasI7GYPR4S4c2I0kUShA3OdpNi062Bnbxi1HAUKuvvImPz27DoOMAOWRUil4Ezsh6PaOGDAFUNeEhP8JZvJieK4kZ12qWLeAFDhfH4zIs95AO4F8H0A34G9GMzjre6ZIAhFz6ihC/Gft8eiT+WrOGD3I0gPaYbVRLAswvbj/otxgw4stItCDhSliCkN9I5CHrqxsSajelwZ6g0JGm/NpAzls2iP0mHTO6fqELKoDr9eNrOYCdvM5LXqV+YrmbATqHYylTRdnGUDW/DeuANmMZPTo0ZR19JkL1rAqOkExU+9AAXzZkS5QW4kIZ1l2712mW6fI7xIu2fkpNmfbfGgP6fq0DRvHxdAWflMqTBQif6iw4mukFqHHzJiZ8k2W5AYJKtaTyCCZGl+tz8Rw8xbADyfIVsnIvoCgK3MvJaIdraBa4IgFDmLnpuN4dUNmPS5uSACrCbCkrcORNdpf8S+7x6PfUTAlCwZX0oTUTURjXF+uraFU0IcLYhRGPs2kYNtcjYbtOj7adJoSfup7sCaTDYjMRhVWx08nbsgVfebyWQlyR1Uh3IFCrRAM6tDuQJBhBY8TnZEIZlvrnBwBZ8nFrTH0N3oMrAxZcQNDwVG3B/HpjfwizV7msvuPB9S7Tj+qtGcgD1lo0tzWxkgZ1iYI0Tc/7Jj17TRpe+n9nSSK1QUTwJRtL2WbwMYAeBqIqqCHZURBGEv5YXrf4W3LzsEQ1d/xfv3e8f6Tlg18GGM/M0b+PDh/8OuLcWwyJOQK0kiMd2Q3YRKITHZDhczvJ3N70CmnGzG5fYt+qsu5RhIMER7KPh2GuYWZBQKxnx63Ca5n4A/5Ert/CaqNya0FIjOZOFWlMlAJIXU6+p2sc0RGXWzS1bSPHucQBBpw7QCIkQ950aQHJv6W5f4iJI5zfVTjcLYRxFKxPFJD/OoQZewTXffFivgR1CDkuYeO+10PCJb0NgbX9oXgww33x9OZhdqn6PJwhBRf9gbHncDsBDAvcysbrZ8ZyH8EgShsPz3bw+h/7LLceTADaD9AKsphfUra9C1Zite+/Qk1I0YgxevvADjBjxhb1JZaIeFnEkysX8gMkyo3LvJISISKJvUZFQdCaMoWbmZXWQmSjCYqoxyQX15nsSjKA91G7rsi2tV8Hxu0amQn9qb/6Q24i6GHrGIQxUGuo+6n3ooI/b+afWHIhwR7c4oOlTzmpO6zUy2CPDmtJByHLJpAeSu9AUErr0eNbL3hXH/59jXlkKz/WRnmFfIpJ/mDBsjIkfsElKk5FUiMbaY8YeOBWwqis/ztx1DRO6r05kAdsBeAOZAAK8S0YiCOSYIQkH51+9/i6X/cxBG7fkGeg6yl0ve8HE3bKydg94//hj1734Odf2eRNWsAajr96QtYG5qw/3RhbyTJBLzBjJPqNwLyUdPwRCJiTQbFyWJ8aWNOjSk/VZ7inp0Qh8ZpeeLJrhIc6b8eic3u0uRORKT1F6ccItMzxAUi6s7fM5JUWzqrfOiKF7lQSuZNLXJnp7PlKYnGYUJKx+VDFFxzFhxQ+Fke5tLO8JhXFCBg+V8URPcB0a9cd4ZNyqlZiPXBikRFt9G0H9ftFjuggKAs/iBn1ONxESObWs/rCKijwDsD+DPAF6HvRDMobBHC5xQONcEQWhrXv7T/+Kw3T/HUX22g/YFmveksfitYaj+yg3Y/6yjvXyqYOkMSASmHZBRxCScULkXkU9VYOhRZSThkK+CvY3Vh7qEP6sd3pQhX1g2+PMI9HwWO6taKf30qA561FwVtY9pv+325xlkEiC5DMCLs+n6Yox4mC5mJtsJHQsPUIo3ThEND5VT1pFg5XEPiFhXFCT4c9DPqW6QkkEJTmQlItVIT0rxKcoOkyZkFM9U8W7bIKSIDffRXD6YyY++eDZJEUQgeAsGpIpu5fx80xPASABPA6iFPRfmQADvATiAiM4DsICZFxfORUEQWpvZM36LwZvuwudGfIJUtT0cd+WSfdH9W8/i4POHFNo9oQ3IaXUyIprOzDPy7UzxE9O9inot3AKT8Zi660lstra6iegAIxhHMXmuR2fI8ClcW5Tk0dZgM3RCjZ3SSO+CZYyRg1ib0QRsJfQzCr3t+jWNs+nn1R5mzSd3s8vAvQ5mT0Zk9CE7O+rdir5zQZFjthC8Xs7WK4G5OEE/zbX4CwCQX6c3od826m50GXSUYd7s0pkTw45NT7iwvZwyA0i5sSRtE9J2CNtrSC8ionkA5jHzJc7myIcAeAbAEQAuBXB44bwUBCEf/Pb0a9FU/zG6pglbmxlltftj1AGbMan/3Ti67y5QP6BpVxneeedA9DjjDxh01hGFdlloQ3JdYvkM2BtNehDRz5j5Fy13qZjJ5b17BnveBAiNjFXEvJYPCapc/U2ozLRsUaWYwp1M/diNzrTkCsd1ZJOTuXSxdRVVfwJRqJw6tu44qKA993Pi6IZB3OjRBHV8YVQbMtVlilAk8dctHKhXF1FsB5TciAe7E++dB9oV58Zn27Wl7f3ClnNH0q7fjg1y75jqgztZXxFIzM4ePY5dJjCzM7+mZU9+CfEDAI8R0WUAXoO9Mtl/mPnCwrolCEI++O3p12JC+XMY/T9LUdllJ/Zsq8SeHZXo3HsrKGWPnH377YMwbPpTGFXTu9DuCgUgq3EHRPQjIvo3gD5EdAERjXLegAHAafl3r1jRZgfnjOE9edSrc+9EZIYgrPzk7G+yjq9qnQ1pqjU25M9UVm95pqvAhh8oi0Rl+lFzBnavV34s+JtdJrMX759rU3XSnzvhG3I/Rg1A0q+du5O9ao9U+5qfdnmn3QxvEQFvqWfYczMsdjr7yg9laLy6tLOl2mR7s0u2/DrU28DKjy5OvGvHfltNyx6Hngf1Wuvn3TY7qyKrxwwGsX2F2GjReWIo+Kdnt5PAFvlp7rW0nM0xSbkgwScNRJa3FLN7Q/17oohNBpqtQAvbLcy8npmPBHAZgHcB3AXgrNaoi4hqiOgpIppLRLeQYUtvIppCRP92fk5Q0q8kovlE9AIRDXTSqojofsfe/c6S0CCi3xHRS0S0gIh+1xptEYRSYUL5c6g7+l18uHwwGneWo6LLbnTZdyusxjQWvTkCWye9gVG/+S86iIDZa8l28PTvAXwP9tdoHYDbAawnohUAVufXtVJA6Wzk67W8sacFU0KONpPaieoqR1cRnk5s7jrq/Vu9z0uG0lE2c4gvZNmq+NyRtytHLHcet9uXVWjJI+aKh1g/DfWZ6gwEADI0PKvr4vbvOZCUWLqTU2Fg70lVF5j88v50g89noH7NnsWkiSTVgi0ATf4SXKHH3o8aQWJW/gLcsWyubQZAVtgmwZHZMQ9OO4eZ5zPzzcx8DzO31gaX0wHMZOZJADpBWzyAiNKwRyec6PzMIKI0EQ0HMJmZjwBwNYDfOEXOB7DEsbfUOQaAq5j5KGYeC2AsEY1spfYIQlGz8dPPUHfUIuzZUY6DDl2Eik6N4GbC8g8PRGNDOQ777ULUDJBNKvd2shIxzNzEzAsBnMDM32HmcbAnWR4F4Iut4WDxkzAyYiTbzobeXc6i7oxZs4z0qF4pb/R1ucKKPWOnzrWhlNPzqV00QFneNhsfo2xqUY84m+FXr/m3GWq72ifN7fYEyrpRC9ffUCTFP5MYL/Jh8DNquV9PCLm/tL63GqkJ1BXjh/HSGASNm1cJanil1c0uCfCjQIq/nvIhp90WI3DaZJMAJgvszHlh1yFnHxlvo0v3b8ZTPIpl13fyzbP7P0+gmldYE1rMUQCecj7/wzlWGQJgOTNvZubNAFY4aUfBXoAAzPwygMPi7DHzHgAgonIA27FXvhwU9maWzluAj356ALo8PxgVnRvRudd27NrSAYvfHILGU5bj5a3fQGX1rkK7KRQJOS1jw8yLlM9NzPwRMzfnz61SoiXv4XPtjeZARjdNGXLvDZniL3ofN1ebtqChgM1cUYdJhW1FC7CkNuMw2owIfegRimwcMmVVh3aZ2535kdHPe+22lBMGA+q+K3rUQzfKbEen4vbGCdhRDwwPmi6YXDETbJWaWbfDnl9q7pBAcnUOuULFFz76U6VO0menoZ59dvPYitAfxaT9dZFqU1RMK1ADYLPzebNzrNIDwCbl2M2jp6cN+QP2iOgWAMsAfApgS5xTRHQhES0kooXr1q1L1BBBKEaev+FGvHPZIRi49Hj0G/EpUmmG1URY9PJQPLjiFxh05St44NePovfif2D31o6FdlcoEnKd2C8EaIVOQ6bX/gCiYxdJbZrI0mZMTrW75R5nypsUtwuX6QGm0AfzeXXn+mAtwU9J/FRtMqJXvM1o03DC9TMV0aFPYMKrO6UcRJkLiQw410hZpcHUDo67QRy+L5ERlJR/yPB7gKEyGW6M9+wxPCHhttuVbFH2SC1D5OX3sjnLLAcEUpoQGGBJUS6qwiQsy73FBNi9Y80IiBe1dfpOnkJWOEPC5htOPQ1bcFTDFhzVADZqeTYC6KYcu3n09GZD/oA9Zv6es1jBowCmwF5xzQgz3wHgDgCoq6uTmy+UFE1NTXj2+1/HsYc9hWN67wH1Aaxmwsr3+mBN1RQcPqoGQ0ffhpVPPoF7xr2G/YesxORTFgL9Lym060KRULQihoiGAngHwDEAFgK4E0B/ACsBfIOZdzmTJO8CUAngaWb+dRt72cLyfhcqs9mIvN65GHJyM/n3IUX81s970QnWxYK5XFaVZ3fKQ7+qWhcykBrVrow2Yy5lrI8xtzxrmwaloSdZcEWC2161c52MOGEWuCYRnfpIMePkTzpnnZSfOCcJ/nAw73KrAkYRWaScd4VHKBboRVWcFc0A45BC367/V2PnUxSW5jCzBctdlYx0X9kTVHvbnJh84YwmGG86R0SdAXwBwAPO78e0LO8DGEREXZ3jQQA+gK08bwJwExFNgL9h9EuOnTec3y859VQx8y5mbiKiHQBaa46PIBSMZa+9jWW3/RCjhy/CiRPtYCNbwOJFQ9HvW3/FoHNGYpCTt+FZ4Pgv/xllHeajqaELuN8l6DDl2sI5LxQVRStiAPwUzj/s8CdBnkVEP3OO/xf2JMmfM/NcIppNRI8x85LWdy1fkRcyfowmqouYIczQBgQFjP6mOHigL2EbF6HxMXfMLHZeeht8MVnIVE849hJfJonNpOLHPRewGXHLEwkA0xk1qqBVkczD+Bx6Oltwdpd3qo5oh7/3Se4izPusPVhR1z/4277yjGDkhThcIHAYiMwEnxlXi7jiPU1OtMS1ozz4+vQX8p4E1a6zF4wXNfT3oSHlfFv+3e9FzABwLxFdDOAtALMAgIhuAvArZl5HRFcAeM7Jf4UjihYT0Twimg9gD4BvOOfvBnAXEc0FsArA1530+4moB4ByAHOZ+cVWb5kgtBFv/OM5dJn/fQw4eBUGHGunbd/QCe+vHoFhP3wQB5+9b6iMLVhs0VLMHVahMBTlM0FE42CPB3ZD70fB35fmH7BXivlfAKOYea6T/rSTr5VFTD57CIYeZeJyqi+miQc5O9UCzBELL02ZM6CXMncslUJZemGyl42Y8Lu28V38JDaTtICUD0ab+i03VBSVJVbwKBfLz2+QB7pfuv5OIiTJr867HxHtyLQgQig/+2LJeB5hAWVyNiA+KNqmn58DR3abnHktUIaZEWA5H1LOeLqgXxxhE/5wM1ZWPiO7BnvYHiOddutEYHiakB+YeQMMi9cw86XK52dgGPrFzH4vzE9rAPA1Q96peXBXEArKvEunYNTQhaiqbsCuLR3w/pK+6FjRiIMO+gTpQ5vADOzaUokPyr+HQ797Nerk3ywhR4pSxAC4Cvabqd87x1GTINUuxmYAfeKMEtGFAOyN0Mo6ZOlShj+yJK/kww5lWSDKF71HGVcm//9YsDc8jCIvAwPQdzhX83pDb+C/e/bfkEeTaWq/aYhQMuLtmkRRS8hoK2FlutBw4wuRm10axYf5efLEhdPpNtkMPZkG+7r0ThGcjRt9n736zF4H6nLvr7o6WspQ0H9O9RPBVntD3UjZC0iJkNjn3SFo5P3Xb5Nij/y/Ca+Ms9wZkV2Xv5GlL0RUK+yOwYS62aXrl53bsuBsdJn5b0IQBKG1mHfpFNSOWIB/LzsZOzbuwfFj/4lDxn0AIsBqTOHDxQPRMOybOOziy7yl+gQhV4pOxBDRFwEsZOYNyhvFqEmQ6tYkpsmWAdRJkFTVLctv+uAb17wQ5QGFPiSvM9LNXFRWsjJ6jkxXytRsV7w0wywQcvE88FkZ1pTMJml2/O6pOsAnFz/19hO0PXZiohCZ7Kt+qSukkeFRir43yn1nv83eeddZzWbGtrP52jUz0GwB6bShiClKEvDV+a0KFA7PnYl8kgMijTwn1WFlgC8aYBQaTgRElTCk+OXa98ZRsn9NLYCZQcTKMDH1LvhLJlOKNT98m54fzGiWl5qCIBSIw4ctwLqPu6Guz3PodNg2APaw4qbdaTSf9BaG9hpYWAeFdkVOSyy3MqMAHE1EzwI4HsD1ABbDnvwIKJMgAbzpTJYE7A3GXm4bF1tp+Fao997CN6rG4tk4miwvQ93HRU31f0JDZAzW9bf0YaHAhp/kZF8ivpS3Q3zWNjPUyDDOzTZ14BPZQ4KNLgNG/Y5x1BPgjGLKG25EwrQ0ddKoF2uPhbt3jepn6H6x/nz5dQLw96VU67AQVp2Kp37kJeYZJ/fvQo3EOOfcjWncdrDfNs+eMrFMjY75TgqCILQNWzduxj++fR5WXzMQlV13o+9Ba9Gp9zZs/awL6pedjG1HvYt0ZTM6ioAR8kzRRWKY+VcAfgUARHQ3gP8DUA/zJMgrANxJRBUA/snMi9vQU+VzK0VmjIImy3f/ITcthLWryUYWbdKGANlJfiSDvDfVZstqWdPbdr+supZT9gIm9FmLHgT9SmA/8BY/ic3MsOUvyWxc9jnXR03tF7M23CpLm4H7w34aQ/HVD+REm9dvtBL1YNg+hsrG+Bp4dvTbx5p/apVemt0K/TlVo0Gs2nHEBYXWu4540onBsLRnxFdD7I1jY21eC3vlTY1lMMCWH7Gh7P42BEEQcuGZH1+OuuoH0bHLLnzhqAYA9r+JDZur8OmA32PImedjLIAXr7wAdf06oHNh3RXaIUUnYlSY+Xzl0DQJchnsJZgLTGxXrZXqyqG+SDejBFJys3rpYJo66CZzTaZzYcno/jf3DpvXIYV5DkUmn+JsGjvgLbDpvnHPunCMTQZAKaXLrdnM9FSr59WX/6od41La6nnNJ1VUqFEUXdiFbKq2VA3hBiec+6ELQz0y464KRpodvRnq882WYtPUNnf/lpC4YNsv0v3y58FQ4IKo184UjRTxIghC67J22SrU//oHGNXvNXz+4M+8Ydqb1lTjoz1HY9fatRg94nWsmv8y+ow9CQtvnI5xA55A/eKxmFhY14V2SFGLmPZPtuInWibkh9xsxkkq1vLE5U3a6Q9GZ5L5Z8qsJrlzKHwxo/SAkfzKqJ1694191PoNRptRYSpoHd0s+qux19sQoVCvrn6dycvrn3dxr5039CnmodAFhx5FIS3RvT+Ry2ln8VC5YsZvi51KwTFiAX/1ysgzEHwu3aFn3qwXV7iQZsKr0/kUuBn+PBhmZ5gZuRdUv/n+amVt9h5FEIS9CmbG01f9BEfU3IXuPXbghMn2wrGNu9LYsakTPqr+Dkb/8Kfo6eSfd+kU1A19ElWzZqKuXwdbwNz0bOEaILRbRMS0mJb0HCLKGpMzyYTcqmqRTYNpMqR5VmPMxpVTvTLJuKS+mezpeTix5WQ2c5meEBYV2nlOfjsDL+5VQaSddzdnTCupMXrKqCK9iJF6HFE+YxuhBS4cu+qE/SSCUp2c7+qEQGGGs9mlFSyoflQjMe5nZ48W8pY8UwWvu9klewM3Tb6S45w6dMxNC4zTgxuVIjCs8N+K46Qn/GROjCAIWaIvi/zGe3XoesL/YO3Dv8FhByzFlBEbQGn7n5d1q7pjTcXJOOx7f0BVugI9NFuqYOkMSARGaDVExORMK7z2jDUZFwvIRgy1DmEREh465nb1TAPikrka7pz5HW+zP9nCgdLBo1zryOKO+efC4+cSlTeKR7eDqzxCwRbq5cIKJWQ3IiKi52PDqnCmssaNLuPEh9FLJUuUQ1o9DHeGmDtzy1BEeWDVqIcr9bwhjdpwMVVPBJ51dwgfuQLGXV7ZNa4sX03NSkmGvVcMO9fU9UCJ+DAgc2IEQcgGd1nkVz/6Mg7/ynV4/WfTcMQR80Ab52LkcXae3dsrsPrjXmiq+zGGT/96/H4WgtBGiIjJmrYWLzoJBjYVdFhJ5g5UYPgNkrgbbTNJU+M77Ka8YQHWEptRZU3p6jv9QBRFL5igwgz9+Bi/InaVUcQPJWx4YCK98jmlFqVg3sz3R7GppKvihZTErEWoqydSBpuxRvy750gN+HvDACBy5vYoURtSRYdbXpf7Thn2y7Jyisipx1V7mXboFARBUBg1dCFefW0Uend6Fc33jMbEozZ7c/W2b+iIVZ0uxEHf/AWGpEyvDAWhcIiIyYqY7lW201sSmExONm9e869wgpsIRm6rGJjYr3ridtfcjm24fxzns7ntukAy7QBvjlronpnLEIL2M9uMJiA2EvoZhdpudRK4fley6thrwsAOHjhDoQwFVRumP4uUeo4M9ybCVpy/avc/qiBFpKtKSxVDqozwh4W5Syi7d1W/u6SJMTd8o4gPLw+DWP370Ya1KS0jUnahCahbthcWIAT+BgVBEDKx4LHnsO0f1+Oo4xow8chXvX9DGrZU4YNPhuPgEW+g+nvrUF1YNwUhEnlllxX5HqbBfk9J/wlB2o9+Ls7NZPGOXDG9HY9qgt7BZe3YtI+iWk/cVdDz6XWYykfbjL/X2dhMimeTgj9qRCGbdgfmjxhsUqRN56ppJxgIrOhGWmHd34AiNSf5fkY0jsmJ4Cg+620N+ai13fg8Rl1Xp75AfrbteTaJFZsU/bwrvhETiH2v7f1m/LvFzJ7ACfrsW055F91Ot635Mo4tOBdLhpMJgmDmrefno/47o7Hrju4YtfU0HH38K3bUpZmwfX0nvL35InS6aD02W8Owa0uHQrsrCLFIJCZrMkxWaCn5MhlwM5dBT66RzGVMg2HU0qSdh3Ks5jMNpMnlchi7cBbAqWzs+Z3JqE6hFe7n5+6fbpfi7ZpsmK6tviFnrK+s2iBPxwRsE2BZttiMEhIBVIGhCQu1SLMFpC273UzBZybCVbPfSlSQ3XtOwTKkGQiIFrXNrDyXng1bzUSO2HIEjn7hjP4R29fSAtJptyFKhEd3FKSc9+fwgNRha+wsVCAIgmDz30efQtOzv0TfXhswbPBnKJvYBACwmgkfvd8PDbs6YPDAj/D6pyeh7rIr8NJV35BlkYWSQERMi9BedWeNoUykRkomKIyEBE0SO9l1z6OEhzqELKojrZdR+39uGb/PGOygJfVQH/yTXJrFYOoctxDLAtIpeB3znB4rA6x0pjMJJPdsRl2iiIcoP7Ny3xUTzoOUbdM94aPdOqXfHxDSurimwNlgHtUWg7ywDClDxBl2xCXKcTfSoy677IoPy4IzyV/ZG4adeTVkixNQcAU1CjRYOSerkwnCXs/yN5di0U0/xcG9Xsfhh6wGHWOnW40prPqwNzY09MUhP30Ggzt0ASDLIguliYiYFtOSXma2wkQfxJQFGbPn3g6m4LjEYCcxOPwlqsZMLXO7aCmoszs4Z2nniS6KqjNzhzbOZtJxmnHXBPD7oy3eB8QUEVE7wlA/J4/AeXfXco5TQZtRlkwbXqpzqwKbZyqZ4rrnoaiQGt5zCqv3XI0u+UUcIeGkm/IA7D3z9kaXHNoPyBUivk8MhhW4GMQMTikinwFKeTEVe8K+YaWxYGRJid44oihfwlcQhOJGXxb5tcWjYO3Yg7rR72Lfyib0P74RgP3v1O5tlVi8/lgcPv1uDCjvhAGaLVkWWShFRMS0mJa8h29JmSzrzZg9n/EEk8XoJWyztelHfJTlbXO1Fxuh8Lu6WUlNVkRXTEHjKWOP349Q+G/fk/sTlZU5rt3JnohQHlbEiNax1/0xCjjNoOsj2J0TEm0v6tqZ6vAifKRXyYYCKv4DEwi66ALJHQ1GzhOriTb3b4LgXiN3OBgCwoWZkEq5cSJ3SWb36fI9V5dolkCMILR/3GWR5y85AXs2bsZhA5dgwtj/gNL+vyWfreyBz8qPxsiLbkDHTj1RW2CfBSHfiIjJC63w6jNkMrIr2gKbcfaStykqp0luZcqbFFZ+4srGdnB1mwFjweuaq8Rz57cY64uw6blhKOd2UFMJb3vcU5NSDhhap9xQ1hMfFM6s3wd2bg5r7fdsaI2P0grqQ2PBb3eSPw9PG5BiRo1sKX6GxLDrlzYUzd3kMuCkt7cL/MBIWhUbCApQz6QjTgKro2nRP7KFDLwaWMmrkgKIQZpgEgSh/fGfh5/F6BGvYsvaLjh69D8CwsVqJCx/vz96fP0B7HvWKOxbYF8FoTUREdMiWtpbMHTBYyMlOdSXs4vJxZH+Zj2q8+t1lmEebhUncjJWnt2pSMJdxKhOY8vvfkZBF3PL4962G4twOIMuonwRF5ZXSduql4x6JqKmjkT57oo69pOSC64oR5WGc1R+k7DzIkyuoFHHvimdCecwNNTMrYdUAUNOFEdVOxz4zcyw2FmVLKUYAwKRGGeMmyAI7YSdW3fguWuvxyH0APYf9ilGpy2ku1jYp8sGMANNu8qw+KPR6H/279B1wVEY+st3C+2yILQJRSdiiOhwALcCaAbQBOCbAFYDuBNAfwArAXyDmXcR0UAAdwGoBPA0M/+6jbzMv50WRUmiXkO3PXqnLqqjqr9oD0sGnYgzWejA7GRgsmFkSWwmFT/udTAGhPQ2ZnXLw2cCUZNQWuarpEY5kvjAzsk4sZFxwQGtPlV4+EMMVaMZ6gz8tq88K4IpIKopohy5UsaV5+45fw6YF+1J2cMfTZt6knohoM4f0+0qNkHaEDunXNwYRkEQSoI3nnkRu/8+Hfvv+xm6dGvAyYdt915eWE2E5j0pvPfegRh+xdOo7LIvRgF48coLUNevAzoX0nFBaEOKcZ+YNQCmMPORAK4HcA2A8wEsYeZJAJY6xwDwGwA/Z+YjAEwmouGt714+OwhRY2OSlGPtWCHWXut0cHzxwl7nT3+D7e7YHooAGLzzbbDXITR5bpI26tXx7ER0ZuM7/uaz6pkkNjPFtKI6y4Hz+i03YGq3+tn4w0HxZOcPL8LgRh9UP70oAGCONrhOaT4GzmsXzGsD+TYDP0kaHjQZEDuhfWy0+lW/3SF2sapTq9yet+LWaxd262QAlnt1KehXcICkJlyciA0zKTZtGxYDlsVgJ1yV+1IXQhxEVENETxHRXCK6hSj8GoGIphDRv52fE5T0K4loPhG94Lx4AxFVEdH9jr37iahKs/UiEf1fqzdMaHPmXToF2//YE033d8L2P/bEvEunAACam5vx98suw7/Om4xVPxmC4Z98CXVHvYPeQ9ehY6/t2LmlI95fcgDe+Pg0lJ29GQveOAIHDFiBedddhe3r1uPFKy/AuAFP4I336grcQkFoO4pOxDDzp8y8zTncDTsacxSAp5y0fzjHADCKmec6n59W0luB+C5vNlNTfHNRvbKkBrTPkS5m8L2F+EObfNmh9xKd0foBT3QZFtGFi/0xtSqqjixbFVs631c0o72EFQba7XTaOe4qmDrw+vOkik9PrJiFZaY+v35vAjYVsRI4n8EeoJRRxYdOpLFAqwObazIjMHSPQGByZq44zoefY8UeKWLGSWMG2CKAnY0yGbZA8Y161wUg75z7T4brl/rX5pc3/00ILWY6gJnOi7ROAE5QTxJRGsAMACc6PzOIKO28WJvsvGi7GvaLNyD6xRyI6CQA2yC0O9zJ+AtXnYJdn/8I//lgCmpH/gef/HwwGu/sgZPG3IGjT3gV+x60BumqZjRsqcLyJf3QMHEeul6yDsN/8RZqf3QPKFWGiTc9i/rFY1HX70lUzRqAun5PyrLIwl5H0Q0ncyGiTgB+CeAbAG4CsMk5tRlAjfNZFWGbAfRpPY9M8YI8mdOh0Idkdeo2ST/R+t0bV6iYalTT48qnDOWy9SF0bCG0QWG8XdJs+cPLDC/+E9o0+xdKi9G2meyrfnkdemh6mQK/ov1QAoWsJjlTLlizGamf3bIc9tFNtxxHWfeNgvnVOgLiwfXVcVafMxT516v657ZUaaw7VM3f+NK/+2rkiuELioDfrLbTbZwyRd+yIykpZ8UCV8iQK1RIGX6miBcQe6LF/q/llW82LMsstJijAPzW+ey+SFN7i0MALGfmzQBARCuctKNgv2ADM79MRLcr9mYo9qYD+F8iSgG4BMAfAJzWSm0RCsSooQsxd8EYdMJi0EPDMfGgRpR3bEKfYWsB2JtPrl3ZEw2DzsUBZ0xH5/LOGBJjT5ZFFvZ2ilLEEFE5gJkAfsvM7xLRRgDdnNPVADY6n9UZrGp6lN0LAVwIACjr0AIPDUM2ctIHih1j+dYYGpLUZnb1+vu46HX51uKEiX5s0mO6rPDKadEEHe8NOCULaAQ7+9EdQkvpoObrLrmbXbrCw+hXrFdmopdTNhm1n5G4NjEAYrOfuRIQIgpJzau3y53fzqmwzcBfAPuRJbNTwefBYiBt+cfexpSejPF9iXzG3foC98IVI453ysVg77Ol+E22GPIEDsFXl+amCC2iBvaLMiD4Is2lB/wXbWqeHrDndLqkDflVe+cBeAzAriROqd9p/fv3T1JEaEM2r9+MF67/Iw617kGv/Taj4z4NmHz0/MBqYpvXdkV1r63YPPJh9DjsRPSTjZ4EITFFJ2KcN1F/BfAEMz/hJL8E4AsA3nB+v+Skv0lEE5j5Fdgh/EvjbDPzHQDuAACq6tbCr/p8RGa0nlXM6ejYRgyJXWzZP5rqZpdBL8nr2kW5QoZy+hhH9923HaEJlkga+VCjBiZfKFQiAabbp2jSXK5qQKiYOvUtfNTcqELKZFMP1STwEY49t++d1T42epSG/M/uYUrPl9SkIRynCy6vyoAS5tDl8AIopMgV11fLjpbEhaF8OxYCzy0DID+CYkd9yKvL3BDfFz9KxQBbiqARFZMLzpCw+YZTT8MWHNWwBYfphZn6og1KHj292ZC/GsBGZ17MWQCmIOFLdfU7ra6uTm58gVm36lPM/8n/w+F9FyCdstBtn+045eAdgVEAe3aVY/WafbFjT2cM+NZdePv2G1BX+SR6jvpC4RwXhBKl6EQMgK8A+CKA3kR0NoC3YYfa7yKiuQBWAfi6k/cKAHcSUQWAfzLz4kI43DoRkzzXZdJAoZORGRKZN0UKtG5ci2pR+sqemGHiUL3Z2I69LDnA2qWMs5u0TrWDn1BnJLLJACgVHU3KdC31axcVSdExrc7lltfb5w4zi9roUrUT0CLuZ8cnV8QG5reQ/0z5RexCAVuG+6i2nRUjxuvpCBWExAXbfinizfOLg2LG3ZsnKG5Y+az+FnKBmZsBjDedI6LOsF+gPeD8fkzL8j6AQUTU1TkeBOAD2Dr8JgA3EdEEAG86500v5gbBFjZPwY7M7EtE32RmmeBfYOZdOgWjhi5EVXUDdm3pgDfeq8PEm57FsjeWYMkNP8T+XVehuutO9NhvE046viHwb+COTR2xfWtHrNvZF7t2pnHo0Hfw8a7xqLtsBhbeOB3jBjxhz2UpXPMEoWQpOhHDzI8AeMRw6muGvMsAHNPqTrUa2Xa547pSORQ3kn23PlPUQW1lXN5sXt77YiZ5mTgyia5sUDv1DCAVsXyG8UpniLp4Hd0sXIu93kqEwr9P0c8lAcoQKni5AT+64y0pHFWxQayEghmeUfuX5aSllUyR182Q7j1/atM4mJFg3l8lsDEnuXnZSwuIFnbuu7vZpaZogm4Gh+x5+8RAv3aOGqMU/Bf5qj1/BTSh1ZgB4F4iuhjAWwBmAQAR3QTgV8y8joiuAPCck/8KRxQtJqJ5RDQfwB7YczwB4G5oL+aYeReAOsfu0QDOFgFTeNzJ+K9+9GV07jsNqfk/wpjaf2PT9fuiT+ddGDBlj5eXGdi5uQqNuyuwcsdoHPbDu9C1Y290BbCfYq9u6JOomjUTdf06yGR8QWgBxPoM2L0EqurG6Hd00tyZzxEQmjkeibZTXWR1pPSAM73eLo85p34oi+5V64VSyTRuOu3XbXqr734uByOdhjcsx+Si7SGj0lC1yXZ5igMduCi7ZcQoK0smoMrLtDfxEVSmgVTEnhx657Q84lIGSzMqy8kf6kXReVMElJUZLqSWlwBUVZovkC9IbNJpIJ3yl1UwXkuy5+xUlKfN/mkulZcDKYqwpyRUlIevUeAeeHYZVZWhpoTqBYCOVY0oS0Wf955DslBV2Rz4MwncAvL1S8cOu5FOqWmu+lKGiREjnWZUlDd6dejzbtxhckRN6Nplt+OPu4afkpf8shUVe5BONyrLTQeFlDesjS10OWBePTPLWqt7EXV1dbxw4cJCu9FuWPrvN7DkT7/E8RNnY/1HPVFZ2YSageuRKvP/jtkCmveUYcv6ztgx5GIM+OJ3kKrUp0sJgtBSiMj4nVZ0kZjSoJVeecaajYuQZBJDrU+43x0tjtU5Lnr5aDj0ieAMQYrQZIne1BvLGV/V50wWdyxIzC1PIsZ8M8obf3fuiqGKBFI9I3H59DkpapmoIWZemuFaRMWLdPETKKYd+8+hP3PLJMCB4NwY/xqqUZng8+L6HYhEuhfas2UfEKk3RrljpEZeOGjTE4fs1x0XAROEvYjfnn4tmuo/Rtc0YWszo6x2f/zooZ8a8772z5ex5m+/Q58On6Cqogm9em/GwH23YMiUJgBA35FrANiipWlXGh+t7IvBB65E6vQ1KKvoil5t1ipBEFRExBQUpWeWuONhmr9i6GznpSOTy/yb6I5/RIAhstOo2svkRdIOeHaD5czXN1t7+hWJEzXusK5APlMlCRpgvN4xj5pfTUSr9AhF0sYrhdRhgCFhodgxmjT47rmgiVlPyGT40zJ2+HVlFyewQkrZfV7ZkSKsmCTn/4ogJ4Qm4gdfBPjPoLrggeomQEh5NkTFCMJvT78WE8qfw+j/WYrKLjuxe1tHvDZ3GH5zmoVjzz8G62deh6H7LkPj7nLs03sLDtpnGw6b0hiwYTUDzbvTQIqx7MPB2O+M36DL0KNRVtYBq6+8APttWYfOFV0jPBAEoS0QEZMVMZ2DXPr7Leps5Bp9yabOZHlZ6TcxKHIH1ahNF/XITPBSmj6pHhp2lw+c939nd7XjozChjrhWXy4kEXmZCMwV8jrwypt9LRKj1xO62rqwIDeaYBuKinDE+a52wv2hUcr5TGLGYMvdQ8X7bChIagH1IwVbrQogC3ZTU177/BX37DboIpu0a+EckxpFca4bsb1Mtff3wwAsw/PPfsQmcPOc4WdsL83tjhKV7S6FvZ0J5c+h7uh3sXTTV7F6/kcYc9DbGHfcmzh8+1KUr7kRZSdqgqWJ0NhQhu2bO2Jd1RQM/MLXUdV/PChd4c+J+evDqLtsDBbeeIlMxheEIkFETFbkolQymIsiVE3CWEP28/JbTOTb8YiM+lpKbj5LO07amY+7jEmiINlZDK4LlYvgMPmk2oyLHmRlX6nItExzXBDClBCIeugGonxWEx0DlpLM7n8iVKa++WXUs8aKT6yMrtKaECxvqk/xSV0EoDnQeNbuPztxl6BZtQjYkT2OWLH3GCJwGgAsbdU01b4yj4YU35xNetxtMwkEtmyHrVR+hkEKQiF44LSLMXzHUlRX7caWXZVY0mkYznzkT8a8O7Zux9x7Hsfmt95Cxx1L0L/6YwwZuQrjT9iFpp0VGNnrARxyor9gR4fKnWhuTKFhcxV2NVRgNU/EsLOmo6L34ShPlaEKQE+tjok3PSuT8QWhSBERkzURXaJ8iIZ8Co9MSiKxkcz59UiKXjpJh1zP59rMPoISkd+C02FMYi+qq6yZ5Nz8y4Qa2YryKmk31b2OFocjHsbMMXWq/rmrhUWsa5DIL7VoM9ubSLpRFIPmSmbTMcyAt9ll3EaXURV4gkSJ7gBOtMeCP7dFN+AKkIhr7U19ccQMM2BZhFQKzsR+s1/sqBffd/KcIyJlSBpjb12sRSh9HjjtYkzoNQ/Vo7eiS8eN2LazBjWvrcO9nz8XHXszBnd+B3t2l6F7l53oVrMdNQM34LgaC3RM2FZF193Yvb0COzdVwmpK44NV/TF27FsoP3cLKiiFzggLlihUwdIZCTfxEQSh1RER0yIi3/G23FzIZI7v/kMuWkg2pT6L7jn50QTdojqELFOExSRazGImbDPqWC0RekMeWTZhJ1CLLAFh8ZHtU2FZ9upfsXuu5PKoUdS1NNmk2GrU++j5aSqQg152Iw2M4HLKSWzqwsMzzf7zqS4l7V0LCj4foeeU/HvszksJ1BMI+5AiYMJimIkDc2DcZZ1ZUT7mUaZaeEm5iQx7E03fbxExQtsStY9KEtZ+9CnefHIWNr1Zj4l9X0TNyLVY/f4+SPXpiHSqAX3Hb8AZYz5CqqLZ+LfBFrBpbVds3dkdO1P7obkRGNKnHi8/MxqfDPsqvnbVOfjbr+7Dvh8+ht3DO6JT4lVEBUEodkTElBxuByWHf4iNgZWWjz/TzQYt+tIh6dAu49t/+MOQQquHJQkYRQwdck8FT6uSLDssp1gqU9TD7FK426uKmTyFfFhpeGD+SSBEkSwC590Jtn+UFZq9OnRUwRN4brRhau5Gl6T4GRVkMAZGlNuob3bpz+FSi5BSlAPO6Z0nVj+w4f6o7fPEhxUQRITwZpfBjS51Nab6wgg8o97NEAEjJKMlwkO34+6jUvdVZwPHEU/gpUuOw9b9TsWeJfPQ3MjoiG3oUrEVBw1fgY5dG7BtfWdUddyDLh1349geu8DH+H8LBxy2KlAHp5uxa2sl2Eph9fr9kB50LPY/8kuo2G8UqKIbeiIYVWl49qc4+ou3YfaTadwzbiH2H7ISk09ZCPS/JPcLJghC0SEipuTIFE/IldyjSnHRDz+PshRt1jUEO6l+55mcN9vhOrMNAoTL6Nc5uZ+A/8Ze7YAnqjdC2bgRCiDaXiafQsdqVMHgRPy11PKoIkHt1EfpIU2w6H5559wIkmNTl+5Jrp0pyRVM6mpwsfc6SiSoz55qk93J+1Yon/8s61Pw2Wmn4hHbQ8XsIWPkTPAP+kBQhpMRRQo9QXCJEh7zLp2Cz13/FDas3oC1K1Zj48rV2LZmHXYsfhWVu9eiIdUbZU1bUWFtwYh+H4ItQt3I1Vj9fm8MwDykHh6G0fuUoXlPGhPG/wfg/yA1yPxAVtU0eJ/t/VbSSFc2Y/UHvbGDasDNzSgfdgqWLtyGKaNvR+eLNwIAhiVoX4cp16LhWeD4L/8ZZR3mo6mhC7jfJegw5dp8XD5BEIoEETF5IV9CIs5cEqmQrc0osu8FmYYpRfUp4/qamVqZScLFHWeKL3DMUVJCfuZgxhU/kec5+e00BVdMcpUZieaiuJ10/WKGIhxuoMC0gaXhIBSBghLAUGxGCquoiI/jJ6nHmk07QKIN1dI/uteGSLHrOuSIadd3BpgZDMt/rg0Pn7s3DCkXNChg3BXHfGESsBlw0pP1ef/nSGh/jBq6EAveGo2hPeYg/ehQjOpeiT3bKzHu8PlovKsnajo2ouvOClCKQftYSO1nHsrlMmCUHzlx9qIFsy1M2AK2buyELQ09sSfVA817dqG5vAcGn3oxOvc/DKjqDUpXoAzAxj/1xZ6PuuGdjidhyjWX4dmf34hRO1/E1m3dkO0WkrZgsUWLdHQEoX0if9s5k4+egqlnk0XeJL60QYcmWrxw8Jj9QTAmMZPEVX1J22yuSm7xpWgVkrWQyCY9Q0gpru7wOU29ULh1aoffdFUziYas7kfSx1Ux6vbT2U8K5TcK6YiHIPi8umuLsbGjpj/b/tAxQiokftznk7zoGWkX24/OuQKG/M0+Sd2alJUfZ3EG10ZK8YwBSinG2V+NSRBMVFU3gPqMRO8D/g3AngTvkiq3n590hz1obixD0+4ypJvtZ3TThq5obK5Ak1WJrlWb0LCrEj17b8JHK/vD2ucwNO1uRK8Jp+CDfz6Fw/rMQufvbACA0HCvKLqdeCPSZd/DIfP/gbXfmoVDuu7GPkd8gi7H35LvSyAIQjtAREzW5FMVxLyKNpLFkK8CvY3VJxXHRV0Y/vCgeHfDQsLtsKpRidjOM2XUBRnrDNlEtjbj87p944AQSBpyirKb0LHgDIuInUbUxzXCr1A5ZR0JdbnkwD0jtWMfr+Oj5qaQW01IcWQnItWIkidYXB8N5dmNzISel2BkBgAoRcFISegme1ZNNQWedVbEDHkX0akzJROXhXh2bekA7PgMK9Pfx66tW1Ezcjw+ev5xjOz1Ijpe8AFQ1hnpdAXKtXJ9DLb8oWljUHfZTfbQtAHP5bSPSmrg6ehyPNB5vxnA1reBrsNAI29BauDpObZUEIT2jIiYrGgFZZCzSbWrGz1OP48VZkDtAptrNQ5j0tKC/btkgihJJzUuX3TpsJDJpCWMHeMENXm/IzrLSdSSWk9KSYwTkupj5F8jLZ5iEhf66Sg9Hhd1yVAm6f1Sn6Wo668ETzLacq83O8I3chlpfeK9Y0Hd+NUWQuz5wSB7q5nQXi7usTmK4kZs2LGvLtFsjztjJ6JUsPcXQgnxxnt1GDPiObz65pdRd5kzJ2bAi7bwqMxu4Fa+91FJDTwdENEiCEICSl7EENH5AC6E3Qv4HjO/1nq1xfQkc+o9+GPqQ2S0pXfR43xp5W6NNonDdCnsZnKgw6l6xnrewNlMlcefybb1tv+ZIzFt3llM0AF3cb23N0hUhygltRkOe3i3mdzrEy5suu964CEQTSDfpukxjnPR9BcQsJkUCl4dL2LkipHAMDx7/gsAkDOJyDTE0TsmW7ikXEOuTcupMx2sg4gQXJacvPOkLGLBzEFxxeTNoZElloVM5Ft4yD4qgiAUgpIWMUTUHcD3AYwH0BfAfWiTfz9z7R67hMaThE95B0mGhsT0ACOqySd6TEiNYegdzajulXouat5MVDPM78O1+RPOZpdJxAeFauPQJ4Y9R0H/A2qJ7PLSYyIRcfZNt9xiX3yQdjI6akTqgfFaWgx7KJNiM1Pb/cnpwfrtDR/tqRyhzS4pmN98V4LDwNwHiJV7HvnnEGyqd0DwNQeTn85g74TvV1CC++LFD9Z415WVyAzZ19GyGCknMsPOigjB5a7d+0fKMtTkb2pJBHe/GctSKhWEGER4CIJQ6pS0iAEwFsBcZt4DYDkRdSGiSmbenalgy8glcpK9yRZjtJk0ZOR2/ZI55g6CCUquYEwlSvpFiRWzmIkfYhbnrS60MpO5M9hSOavjbnZpMhrVgU9CYMnnyEzqh8jYjddJh2IziqTXhZ2bzE71GefHRNXFin8w+8h6flJTzTY9scOOs46aIOViuFfNJMADbVEc9fWGJp0DF8IZNqasTOaVCjhoKU4KgiAIQvum1EVMDwCblOPNAGoArDFlJqILYQ89A4Dt+PDvS1vVu9zoCWB9oZ3IBiv4OdL/VlaW+aTk7oGBUm9DqfsPFLYNAwpUr1Ag6uvr1xPRR0pSqf0NlZq/QOn5LP62LuJv62H8Tit1EbMRQDfluNpJM8LMdwC4o5V9ahFEtJCZ6wrtR66Uuv+AtKEYKHX/gfbRBqF0YOZ91ONSe/5KzV+g9HwWf1sX8bftKfW1OF8FMJGIyomoP4DtrT+UTBAEQRAEQRCEQlLSkRhm3kREfwTwEuyB4T8osEuCIAiCIAiCILQyJS1iAICZ7wJwV6H9yCNFPdwtAaXuPyBtKAZK3X+gfbRBKF1K7fkrNX+B0vNZ/G1dxN82hlhWshEEQRAEQRAEoYQo9TkxgiAIgiAIgiDsZYiIEQRBEARBEAShpBARIwiCIAiCIAhCSSEipoAQ0eFENJ+IXiaiF4hoMBFVEdH9RDTX+V1VaD8zQURDiaiRiCaWqP+1RDSLiOYQ0QyyucVpw1NEVFNoH+Nw/L2ViP5NRP8loq+VQhuI6DkiWkdEP3GOjT4TUY1zPNc5r29cXxAM/p9LRAucv+cHiajSSR/o/H3PJ6IrC+u1sDdAROcT0SvOMze60P7olOp3X6l915XSd1spfI+V4ndWe/+eEhFTWNYAmMLMRwK4HsA1AM4HsISZJwFY6hwXOz+Fvcw1UGL+E1EFgN8AmMrMxzDzdAAnAOjotOEhANML6WMCRgIYycyfAzAZwC9RGm34BoD/UY6jfJ4OYKaT3snJVwzo/s8D8Dnn73klgLOd9N8A+DkzHwFgMhENb1s3hb0JIuoO4PsAjob9DN5cUIfMlOp3X8l815Xgd1spfI+V4ndWu/6eEhFTQJj5U2be5hzuBtAE4CgATzlp/3COixYiGgfgUwCrnKSS8h/A5wBsB/CA8xZiEkqvDasB7CGicgBdAGxECbSBmVdpSVE+F2VbdP+ZeRkzNzuH7t8zAIxi5rnO56dRJP4L7ZaxAOYy8x5mXg6gi/u2tVgoxe++EvyuK7XvtqL/HivF76z2/j0lIqYIIKJOsN86/A5ADwCbnFObARRNuDeCq2AreJdS838/AIcBOAvAOQD+DKAngm3oXhDPkrMJwPsA3gPwBuxnSb8Pxd4GINrnGufYTS/qZ8p5gzUFwEwnSf13djOK3H+h5FH/joAifuZK7Luv1L7rSu27rRS/x0r2O6u9fE+V/GaXpY7z1mEmgN8y87tEtBFAN+d0Ney3EUUJEX0RwEJm3qAM+SwZ/x02AniFmbcC2EpE6wGkEWzDpoiyxcLxAPoCGALb37kAZqG02gCEnx3X503O8WYU+TNFRP0A3APgDGbe5SRbSpai9l9oF6h/R0CRPnOl9N1Xot91pfbdVorfYyX5ndWevqckElNAiCgF4K8AnmDmJ5zklwB8wfn8Bfjjb4uRUQCOJqJnYf8DdD2AxSgd/wHgVQBDiaiMiLoA6AXgUZRWGwjAJidEvA1ABYDZKK02ANHPfkn8TRBRT9jPzkXM/KFy6k0imuB8PhHAy23unLA38SqAiURUTkT9AWxn5t2FdkqlBL/7RqH0vutK7butFL/HSu47q719TxEzF9qHvRYiOg3A3QAWOklvw54QdheAfrDH3n5dUcpFCxHdDeD/ANSjxPwnonMAfBtAOezhAn8HcAuAQwFsBXAuM28onIfxEFEawJ2w32BVArgPwK0o8jYQ0Z8BTIDt8yIAX4HBZyLqAeBeAF0BvAXge8xsma22HQb/VwH4MoAPnCz3MfOdRDQY9v2pAPBPZv5lAdwV9iKI6AIA3wTAAH7AzAszFGlTSvm7r5S+60rpu60UvsdK8TurvX9PiYgRBEEQBEEQBKGkkOFkgiAIgiAIgiCUFCJiBEEQBEEQBEEoKUTECIIgCIIgCIJQUoiIEQRBEARBEAShpBARIwiCIAiCIAhCSSEiRhAEQRAEQRCEkkJEjCAIgiAIgiAIJUVZoR0QhFKAiLrB3rV5BYDNzLy5gO4IgiAIQk7I95nQXpBIjCAkYyyAcwBcCmBYYV0RBEEQhJyR7zOhXSAiRhAEQRAEQRCEkkJEjCAkYwGA+wDcBGBpVCYiYiJ6i4iOa01niGg2EW0kou+2Zj2CIAhCu0O+z4R2ATFzoX0QhHYDETGALsy8vQ3quhvAQma+tbXrEgRBEPYu5PtMKHYkEiMICkR0PxG94fysIqIP82CTiegqIvovES0jomOJ6Doiep2IFhHRiGzyCYIgCEIm5PtMaO+IiBEEBWY+i5lHAfgagE0AzsqT6c3MPAbAjwD8HcB8Zj4cwL0ArsohnyAIgiBEIt9nQntHRIwgaBDR4QAeBnA2M/8nT2ZnOr9fA8DM/JRzXA9gSA75BEEQBCEW+T4T2jMiYgRBgYg+B/st0VRmfjOPpnc5v5sB7FbSmxHcrylpPkEQBEGIRL7PhPaOiBhBcCCiYwH8L4CTmTlyxRZBEARBKGbk+0zYGxAlLAg+DwHYDuAJIgKATcx8TGFdEgRBEISske8zod0jSywLQh6RJSkFQRCE9oB8nwnFjgwnE4T8shbA/LbYHAzAUQB2tGY9giAIwl6LfJ8JRY1EYgRBEARBEARBKCkkEiMIgiAIgiAIQkkhIkYQBEEQBEEQhJJCRIwgCIIgCIIgCCWFiBhBEARBEARBEEoKETGCIAiCIAiCIJQUImIEQRAEQRAEQSgpRMQIgiAIgiAIglBSiIgRBEEQBEEQBKGkEBEjCIIgCIIgCEJJISJGEARBEARBEISSQkSMIAiCIAiCIAglhYgYQRAEQRAEQRBKChExgiAIgiAIgiCUFCJiBEEQBEEQBEEoKUTECIIgCIIgCIJQUoiIEQRBEARBEAShpBARIwiCIAiCIAhCSSEiRhAEQRAEQRCEkkJEjCAIgiAIgiAIJYWIGEEQBEEQBEEQSgoRMYIgCIIgCIIglBQiYgRBEARBEARBKClExAiCIAiCIAiCUFKIiBEEQRAEQRAEoaQQESMIgiAIgiAIQkkhIkYQBEEQBEEQhJJCRIwgCIIgCIIgCCWFiBhBEARBEARBEEqKskI7QEQdADwLYDIzNxvOXw/gGWZ+oc2dE4QipL6+viOA6kL7IRQlW2pra3cW2om9majvNCK6G8BTzPwIET0I4KfM/H6B3BSEokG+04QYYr/TCi5iAFwA4DGTgHG4BcCfAYiIEfZ6Vq1adcHw4cO/VVZW1rHQvgjFR1NT085Vq1b9uV+/fncV2pe9mEzfaQDwJwDTAXyrbVwShOJEvtOEODJ9pxEzt7VPQQeIXgFwJjOvIKIfATgbgAXgn8z8YydPPYAvMvOnBXRVEApKfX19x+HDh/+rU6dO5YX2RSheduzY0bhkyZJjJSJTGNzvNAAfwX4JdzyAjwHsAXCXE4lJAfgQwIHM3FQwZwWhgMh3mpCEuO+0gs6JIaIKAIMdAXMigC8BGMfMhwGYoWR9DcARhfBREIqIanlbJWTCeUZkaEYBUL/TAJwKYBiAgwCcC2CCm4+ZLQAfADisAG4KQrEg32lCRuK+0wo9sb8ngM3O5+MA/IWZdwIAM29U8n0GYL+2dU0QBEEQskL9TjsSwN+YuZmZVyM8JFq+1wRBEFpAoUVMA4CqBPmqnLyCIAiCUKwk/U4D5HtNEAShRRRUxDDzJgBpIqoC8DyArxNRRwAgohol61AAiwrgoiAIgiAkQvtOexnANCJKE9G+AI7Rssv3miAIQgsodCQGAGYBmMjMzwJ4EsBCInoDwOUAQETlAIYAWFgwDwVBwMSJEw/s3r37YdOnT983X+WXLl1a0bVr11Hjxo0bethhhw2fPHnykNdffz3pm+yiI6o9Tz31VJd99tnn0LFjxw4bO3bssNtuu61m6dKlFURUe99993Vzy/fv3/9g9/Nf/vKX7nV1dcPGjBkzbMyYMcMee+yxrgDw6quvdjjyyCMPHDt27LDDDz98+NVXX927AE0VopkFYCKAxwG8D+BdAPcC+LebgYh6A2iQxWoEoXDId1pmiv07rRiWWL4NwGUAZjPzbwD8Rjt/EoBHZAUXQSgs99xzz4qnn36666pVqyqi8kydOnXgr3/969XDhg3bk7T8wQcfvPOVV155DwBmz57dadq0aYPffPPNxR06dCjs0ok5YmrPddddt2ry5MlbZs6c+ZGbb+nSpRWDBg3adf311/c566yzNqdS/jul2bNnd7r99tv3+de//vV+dXW1tW3bttT8+fM7btiwIX3OOecMevzxxz8cOXLkbsuy8Pjjj3ctQDOFaG4DcBkzzwbw3Yg8ZwK4ve1cEgRBR77TklHM32kFj8Qw82sA5hBROiJLGYDft6FLgiAYOOCAAxpbu/xxxx23Y/jw4Q1z585tFyvWuO1ZsGCBsT19+vRpPOSQQ3bef//93dT0O++8s+ePfvSjT6urqy0A6NKlizVlypTtDz/8cPUJJ5ywZeTIkbsBIJVKYerUqVtbvSFCYhJ8pwH25P972sYjQRBMyHda9hTbd1oxRGLAzJEbszHzw23piyCUCiNGjDhow4YNefkb7tGjR9PixYvfzYetltKvX789K1eurACwI182e/XqdejQoUMb5s2b9z4AzJkzp+O0adOGnHHGGetvvvnm1QBw3XXX7XPjjTfue8MNN6w8++yzNwP2W7i5c+d2XbBgweKBAwfm9IXXr1+/PQceeODuu+66q9fYsWOHAcCf//znFVVVVQwA11xzzZqvfOUrB5x11lmb3TKffPJJxcCBA0Nv/j7++OOK/fffP5QuFBdx32nO+b+0lS+CUAq01+8zIP/faYX8PnPbUyzfaUUhYgRBKF02bNiQPvHEE4cAwLJly6pOP/30qsrKSj755JM3/fSnP/0sW3urVq2q+PKXv7w5744WiFWrVlV06dKl2RR6B+y3eYceeujOv/71r93cc3379t2zfPnyisMPP3yXamv//fffs2jRog5t5rwgCMJehnynxVNM32kiYgShRCmWN009evRoXrBgwVIgfvxwEubMmdNxyZIlHSZNmpTX3eY/++yzt9TjY445ZqeedsUVV6y74oor1qlpjz766IqW1Ou257zzztuwYsWKyqh8V1999ZpTTz31APf4G9/4xvqrrrqq77HHHru9urra2r59O82fP7/TV7/61S033HBDn3feeWe9G35//PHHu5566qkypEwQhJKlWL7PgOL/TivU9xn+f3v3HR5VnTVw/HsIKfSEkFBCILSACEiJKIhSBMS6imVFWbvoqthWxcK+otiWVVnFsqCiiIJgXxFUBCmCIgGkSG+h9xAChNTz/jGTMQnJpM1kZpLzeZ77ZO6de++clJmTc3/l4n85zYoYY0yJXH/99c0TExNrZ2RkyPLly2v++OOPWzxx/Jo1a2qec8458enp6dXq16+fNWXKlK2BOgASCv9+9u3bF+zumFatWmV27tz55Lx58+qCo9/xzp07D1544YVtRASAJ598cm9kZGT2pEmTtt19993N0tPTq2VmZsqVV155xIoYY4wpHctpJePPOU1UA/bnakyVsmzZssYdOnT4LjQ0tFyDEU3llp6eHrxmzZpB3bp12+vrWIwxpiiW00xJuMtpPp+dzBhjjDHGGGNKw4oYY4wxxhhjTECxIsYYY4wxxhgTUKyIMSZwpGRlZXl01i5T+Tj/RlJ8HYcxxhTDcpoplrucZgP7jQkgu3btui0iIuLO6tWrV4q7/xrPysrKOpmcnPxO06ZN3d5s0Rhj/IHlNONOcTnNihhjAsyyZctqAvV8HYfxSyndunWzK5vGmIBhOc244TanWRFjjDHGGGOMCShVekyMiHwvIgdFZGQ5ztFPROY5lxUissyTMRpjjDEl4Ymc5jzPRSIyR0R+EpGHPRWfMcZ4UnVfB+BjtwP9gaZlPYGqzgXmAojIY1TxwtAYY4zPlDuniUgDYDhwsapmeCowY4zxtCr9D7eq7sq7LiL1RGS68wrUXBFpXcpT3gBM8VyExhhjTMl4KKddChwB/ici34nImV4J1hhjyqlKFzGFeAL4QlUvBB4CXirpgSLSCUhR1R3eCs4YY4wphbLktCZAa+AKYAQwwXvhGWNM2VX17mQFdQR6i8jdzvUsABEZBQwquLOqnptndSjwkbcDNMYYY0qoLDntCDDX2ZVspYhEV1CsxhhTKlbE5PcH8IuqfgkgIiEAqjoKGFXUQSJSDRgMJHg/RGOMMaZEypLT5gFjnfvHYjdONcb4qSpdxIjIO0BPIFREEoCbgf+KyHBAgG+Bl0twqj7ASlU96qVQjTHGGLc8kdNUdYNzts0FQDDwgJfDNsaYMrH7xBhjjDHGGGMCig3sN8YYY4wxxgQUK2KMMcYYY4wxASWgx8SIiADjgG44vpdXVXVqSY5t0KCBxsXFeTE6Y4zxjWXLlh1S1Shfx2EqjuU0Y0xlVVROC+giBjgTOFNVe4hIHeB3oERFTFxcHImJid6MzRhjfEJEknwdg6lYltOMMZVVUTkt0LuT7QEyRCQYqINjfntjjDHG74jI9yJyUERGFvJcmIh8LCILnV/DfBGjMcYEikAvYpKBTcBGHK0wz7nbWUSGiUiiiCQePHiwAsIzxhhjXG4HHi3iuVuA9ap6PrDBuW6MMaYIgV7EDABigNZAO+AFEQktamdVnaCqCaqaEBVV+u7iqsq0adPYtGlTmQM2xhhTNanqLjdP9wZmOB9/41w3xhhThEAvYgRIVtVsIBUIAYK89WI7d+7k+uuvZ/jw4a5t69ev57333iMpybqgG2OMKbNIHL0LAI4C9Ys7oDy9C/bv38+IESOYNGlSqQM1xhh/EOhFzI9ANRH5GVgMjFPVk956sdDQUEaPHs3f/vY317YZM2Zwxx13MGfOHNe2yZMn88Ybb3Ds2DFvhWKMMaZyOQKEOx/XowRjPMvTuyAtLY0xY8bw1VdflTZOY4zxCwE9O5mzBeaWinq9hg0bMnJk/vGYgwYNQkTo06ePa9u4ceNYunQpN910U26c3HHHHXTv3p277rqrosI1xhgTOOYDl+AY33mJc91rmjRpwvfff49Ny2yMCVQBXcT4gw4dOtChQ4d82958803WrVtH3bp1AdixYwcTJ05kz549riJm8eLFfPDBB9x333106tSpwuM2xhhTsUTkHaAnECoiCcAoYICq/hv4AJgoIguBXcCt3owlJCSEgQMHevMljDHGq6yI8YKzzz6bs88+27UeExPDihUryM7Odm1bvHgx77zzDuecc46riMnMzCQ4OLjC4zXGGON9qnpnIZt/dz6XBgyp0ICMMSaAWRFTAapXr07nzp3zbRs+fDhxcXFcdNFFgKPL2bnnnktsbCyfffYZ1avbr8YYY4z33HXXXSxatIgVK1bYBTRjTMAJ9IH9ASs0NJRrrrmGOnXqAHD48GGOHTvGiRMnXAXMwYMH+eOPP3wZpjHGmEpq37597Ny5kwMHDvg6FGOMKTUrYvxEgwYN2LhxI9OmTXNte+edd+jQoYNNgWmMMcbjJk2aRHJyMjExMb4OxRhjSs2KGD8iItSv/+etAdq3b0/v3r0ZNGiQa9tzzz3HnDlzUFVfhGiMMaaSCA8Pp1o1+zfAGBOY/GLghYj8VoLdDqrqpV4Pxo9ceeWVXHnlla71LVu28M9//pOEhASWLl0KOMbSiIiPIjTGmKqlsuWrkydPsmXLFjp27OjrUIwxplT8oogBIoA73DwvwJsVFIvfat68OTNnziQoKMi1bcKECXz22We8+uqrloSMMcb7KlW+6tChAwcPHiQ5OdkmlDHGBBR/+cR6XVXd3thLRP5bUcH4q+rVq3PxxRfn27Zo0SJ+/PFHatSo4dr27rvv0rlzZxISEio6RGOMqewqVb4aPHgwqamppKamEhER4etwjDGmxMQfxlaISDNV3VGRr5mQkKCJiYkV+ZJes3btWtq3bw84ZjmLjo6mQ4cOrFy5EnB0F1BVatWq5cswjTEVRESWqapdxfACX+SrkqhMOc0YY/IqKqf5y4i+1SIyW0SGiEior4MJNLkFDDimbn733XcZMWKEa9u0adOIjIxk8uTJvgjPGGP8loi0d7cUcojlK2OM8QP+UsQ0AT4G7gb2iMibItLNxzEFpNq1a3Prrbdyww03uLapKo0bN85X7Dz44IM8+eSTnDp1yhdhGmOMv/gWmOH8uhpYBPzsfPxtIftXuny1dOlSbrnlFjZt2uTrUIwxpsT8oohR1ROq+oGq9gbOAZKBL0RkpYjc7+PwAt5tt93G1q1b6dq1KwAZGRm8++67fPzxx4SGOi4kpqam8umnn5KSkuLLUI0xpkKpagtVbYmjkLleVSNUtT7wV+CbQvavdPkqMTGRSZMmMX36dF+HYowxJeYXRUxeqrpZVUcClwHpwFgfh1QpiIhrKuaQkBCSkpL47LPPXNtmz57Nddddx6hRo3wYpTHG+MwFqvpp7oqqfgZc4O6AypKv/vrXvzJz5kwee+wxX4dijDEl5vHZyURkjLvnVbXIT0kRqQcMAW4FYoGPgJs8GqABIDIyksjISNd6u3bt+Mc//sHVV1/t2jZ69Ghq1arF3XffTc2aNX0RpjHGVBQRkfNVdaFz5TzcXOirTPmqfv36p818aYwx/s4bUyyfcH5tBfQGvnCuXwUUOi2liAzEkQguAeYCzwPfqmq2F+IzhWjfvj0vv/yya/3UqVO88sorhISEcO+99wKOsTWA3VzTGFMZ3QtMFZHcHFYDR5GST2XOV1lZWfz0008MGDDA16EYY0yxPN6dTFWfUdVngKZAV1V9SFUfArrhuFpVmLFAItBGVa9S1f9VhoQQyMLCwlizZg1TpkxxjZuZO3cunTt35ocffvBxdMYY41nOFpiWwDXOpbWqLipk10qbr4YOHcrAgQNZtKiwb9sYY/yLN2922UhVD+euqOphEWlU2I6qeqYX4zBl1LRpU5o2bepa/+WXX1i1alW+lpiDBw8SFRXli/CMMcbTzgfOUNU3RCRaRMJVdWPeHSpzvrr55pvJysoiJibG16EYY0yxvDmw/w8ReVdEejiXCcDawnYUkWKnRCnJPsa7Ro4cyebNm7nwwgsBxyxnHTp0oH///q6uZsYYE4hE5HHgaeAB56YQYGIh+1XafHXxxRfz2WefERcX5+tQjDGmWN5sibkdR0J4w7k+F3ikiH17FzchANDFU4GZsmvVqpXr8b59+4iPjycuLs7VOrN9+3YyMjKIj4/3VYjGGFMWQ4AE4DcAVd0lInUL2a9K5KvNmzdTo0YNa5UxxvgtrxUxqnoM+EcJd3+rBPv8txzhGC9o1qwZCxcuJDMz07XtpZdeYvz48Xz//fcMHDjQh9EZY0yppKlqZoGJSwprYq70+Wr16tX07NmTs88+mzlz5thkLsYYv+S1IkZEooFXgWaqeoGIdAJ6quppH+7OiQBMgAoODnY97tWrF1u2bKF3796AY0azJUuWcO655/oqPGOMKYmdItILUBGpBjwJ/FFwp6qQr9q3b0+PHj249tprrYAxxvgtb46JeQf4GQh3rq8H7vHi6xk/MHToUGbPnu2a0WzWrFn06NHDbqJmjPF3w4H/AzoAJ3HcIuBBT7+IiNwiIotFZJGIdC3wXEsRWSAi80TkJxFpWtR5vCkoKIhZs2Zx5513urbl5OT4IhRjjCmSN4uYGGerSzaAqmYA9ilYxURHR9OjRw8GDx7s2pa3+5kxxvgDVd2nqgNxXHhroKoDVPWAJ19DRCKA+4E+wFDg9QK73AO8p6p9gEk4CiufCAoKcj0eO3YsgwcPJjk52VfhGGPMabw5sD8r74qIhAMeb5cWkfb82Uc5FIhX1Ug3h5gKlJCQwKJFi1xdEo4fP07nzp25+eab+ec//+nj6IwxxkFELimwDpACrFHVFA+9THdgofOi3jYRqSMioaqa7nz+D/7svRABeLSIKovMzEymTZvGxo0bOXHiBBEREb4OyRhjAO8WMV+IyHigjojcguMK02nTVeYSkSBgqap2LWqfwqjqWhxXtRCR64B+ZQ3YeEfePtWrV6/myJEjHDlyxIcRGWPMaf4JnA2scq53dD6OEZE7VHVG7o5lzVdAJJC3OeMoUB/Y61z/EfheRG7HcVGuu7uTicgwYBg4JlrxhuDgYObNm8e6detc9w3bvHkzWVlZtGvXziuvaYzxD/PmzSM5OZm//OUvVKvmzc5bZeO1iFR1DLAAWAZcAryuqq+52T8bOC4iYeV42aHAR+U43nhZjx492LJlC08//bRr2wsvvMC3335r95oxxvjSZuAcVe3qLE7OAdYBfYHn8u5Yjnx1hD9bWgDqObfl+hcwUlU7AaOAF9ydTFUnqGqCqiZ486bDYWFhdOny56zR9913H+3bt2fZsmVee01jjG9lZGTw0EMPMXjwYD788ENfh1Mob7bEoKofAx+X4pANwAIR+Qw4nuc8xU5pKSKRQDtgkZt9vH7VyhQvb3eEXbt28X//93/ExMSwceNG14QAxhhTwc5SVdd/5aq6XEQ6quo6KXyKrrLkqyXAcyISDDQGjufpSgaOLteHnI8P4Gil8SuqypAhQ6hTpw5duzoaotLS0njrrbe48cYbadSokY8jNMZ4QkhICF9++SW//PILQ4YM8XU4hfLmFMufcvoc+ynAL8AHqlrYIP/qOPoEn5FnW0kvz/8V+FTdXM5X1QnABICEhAS77O8HmjZtys8//0xqaqqrgFm9ejXh4eHExsb6ODpjTBVyUkSGqOpUABEZAqQ5nyssX5Q6X6lqsoi8Bcx37vuAiHQGBqjqv3G0+IwXkSwgGLirHN+PV4gIN998MzfffLNr2xdffMEjjzzC9u3bGTdunA+jM8Z4UlxcHHFxcb4Oo0jirS48IjIOx92Ppzo3/RVYC8QCG1X1fg+/3iLgDlVdV5L9ExISNDEx0ZMhGA/IyckhISGBdevWsX79epo3b+7rkIwJOCKyTFUTfB1HIBGRM4DJwJnOTX8ANwPbcdzjbLaPQisRX+a0PXv2MGnSJC677DI6duwIwBNPPEFoaCiPPvootWrV8klcxpiymTx5Mjk5OVx77bXUrFmTlJQUPvroI26++WZq165d4fEUldO8WcQswHF1Kd25HoZj0GI/4HdVbV/IMYKju1d/56YfgHfdta44j2sJTC9N0rYixj9lZWXx1ltvsWLFCt5//33A0S9TRPLdVNMYUzQrYspOROoAqGpqMfuVKV95iz/ltPT0dBo3bkxoaCg7duwgODjYNebRbp5pjP9r27Yt27Zt49ChQ9StW5eHHnqI//znP3z++ef5bplRUYrKad4cE9MQyMiznolj7v0MEUkv4pgxQBfgfef6zUAbwO2dElV1K45WHxPgqlevzv3352+kGzt2LO+//z5Tpkxx9cE2xhhPE5F6QFsgLPefbVVdUMTuZcpXVUFoaCibNm1i/fr1rotPP/zwAyNGjOCVV17hwgsv9HGExhh3xo8fz549e6hbty4AQ4YMoV69epx11lk+jiw/bxYx84FvRWSyc/1GYKGI1AaKKmIuArqqahaAiEzHMbtZlU8KVVlSUhL79+8nOjra16EYYyopEfkr8DKO+7PsBloDK4GirpxYvnIjMjKS8847z7W+ePFiVq5cmW+a1rS0NGrUqOGL8IwxbvTp0yffevfu3ene3e2M7z7hzUmf7wVmAdc4l++Be1T1uKqeW8QxQv6BkYoXbpBpAstbb73Fhg0bXPco2LVrF7/99puPozLGVDJPAt2ATaraFhgELHWzv+WrUnjmmWfYuHGj65+jU6dO0bp1a+68807fBmaMCVjevE9MpqqOU9Wrncs4Vc0s5rDvgVkicoOI3AB8C3znrRhN4MhthVFVbr/9dnr06MHPP//s46iMMZVIlqoewNlDwTmQ/2w3+1u+KqU2bdq4xsRs3bqVkJCQfGMdd+/eTUpKiq/Cq1KOHDnChAkTeOedd1zbvvjiCyIiIhg7dqxr25IlS/jyyy85evSoD6I0vnDfffcxcOBA9u3bl2/7ihUruOyyy3j33Xd9FNnpvFbEiEh1ERkmIm+JyMTcpZjDHgO+AAY7ly+BEd6K0QQeEeHee+/lqquuokePHr4OxxhTeaQ7B+tvEpHhInI54G4aHstX5dC+fXs2b97MSy+95No2cuRIoqOj7SaaFSA1NZW///3vTJ482bWtZs2a1KtXj5o1a7q2vfvuuwwePJhVq1a5tu3atctuTl2J/fbbb8ybN4/69fPfpiooKIhvv/2WhQsX+iiy03lzTMx45/n7Am8DNwBFDZBERIKAr1X1MuC/XozLBLgrrriCK664wrX+5ZdfsnbtWkaMGEH16l69f6sxpvIaCdTFUYi8DdQD7ilsR8tXnhEUFOQaOAzQunVrOnbs6JqmOSsri549e3LJJZcwatQoH0VZORw+fJjRo0fzxBNP0LBhQ5o3b87HH39M+/Z/ThQ7aNAgtm/fnu+466+/nqioKM455xwAMjMz6dSpE61bt2bJkiU221wltGTJEpKTkwkJCcm3vUOHDqxbt462bdv6KLLTeXNMTHdVvRk4qqovAr34c/7906hqNhBZxJ2RjSlUTk4OTz75JE8//TTr1pXoFkHGGJOPsyhpraopqrpJVfur6tmq+mNh+1u+8o6nnnqKxMRE1z9P69evZ8WKFWzevNm1z+zZs7n++uutO3Epvfnmm7z22muMGTPGte3666+nU6dObo+78MILeeGFF1w3oz506BDnnnsuXbp0cRUwv/76K0888QSbNm3y3jdgKoyInNYKA1CtWjXatWvnV4WrNy9b597pOFtEaqpqiogUN73Ur8CXIjIFOJ67UVVneitIE9iqVavGTz/9xLx581xX706dOkVwcDBBQUE+js4YEwhUNVtEhgETSnGY5Ssv69ChA8nJyfnGycydO5dp06YxZMgQ17a7776bbdu2MWXKFCIjIwHH+JpGjRpV6TyQmZnpGnP0+OOPExERwe23316uczZu3JiZM2fm6042efJk3nrrLc455xzatGkDwObNm4mLi7PeEQHm2LFj5OTkEB4eXuQ+qamppKSkuCZb8iVvtsQcEZEIHAMdZ4nI5zimrXSnM44m/L8DjzqXR7wYo6kEGjVqxPXXX+9af+ihh+jbty979uzxYVTGmADzk4hcU4r9O2P5yutq165NTEyMa/3ZZ59lxYoV9O3b17UtMTGR+fPnu/7xSk9Pp2nTpvmmeN64cSMjR45kwYI/e7WnpKSQmppaKcd3/Pbbb7Rv354ff3Q0JoaEhDB8+PB8413KI+/V+Oeee44PPviAiy66CHD0kOjTpw8tWrQgOzvbI69nKsakSZOIiIhw3Wy8oNWrVxMeHs7IkSMrOLLCebOIuVRVk4GngHeAn4Cri9rZ2Zw/VVX7Flj6eTFGU8lkZmayefNmdu/ena+vtTHGFOMWYLqInBCRAyJyUEQOFLaj5SvfCQ4OpnPnzvk+35cuXcqOHTtcrS6pqalcdtll9OrVy7XPypUref755/N1Q3vuueeoW7cu8+bNc2276667uOSSS8jMdEymmpWVxejRo/n4449d++zbt4/p06ezZs0a17bdu3ezfPnyfK1GR48eJTk5mZycHM/9AEroxIkTbNmyJV/R5i0RERHcfPPNrnv+HD9+nH79+jFgwADX72T16tXcdNNNLF3qbtZy42sNGjTg/PPPL3LcS3x8PAkJCbRu3bqCIyuCqnp8AYKAGWU4LtEb8RS2dOvWTU3llJOTo7t373atr1mzRnfs2OHDiIypWBX5WVpZFqB5YYub/f3qZ2w5zb19+/bpjBkzdMOGDa5tr7/+uvbq1UvXrl3r2ta+fXsNCQnRnJwcVVU9duyYAtq7d2/XPt99950C+uSTT7q2jRw5UgGdMWOGa1u/fv0U0CNHjri2RUVF6QUXXOBaT0lJ0Y8//lg3b95c7u8xKSlJ09PTXevr168v9zk95amnnlJAP/jgA9e2Q4cOuX7OxrhT1OetV1pi9M9Bj6U9f2mb8405jYjQpEkTwDE+5tprr6Vjx47s3l1cb0ZjTFWlqklAMhCpqkm5i5tDLF8FkIYNG3LppZcSHx/v2jZ8+HAWLlzIGWec4dq2fPlydu7c6eouFRoayhdffMHTTz/t2qd169a8+OKLDBw40LWtW7du3H777TRv3ty1rUuXLvTr14+wsDDXtvr16+eb9Wn58uXceOONvPrqq65tu3fv5vDhw6X6/ubPn0/Hjh3zdfPxp1mkRo0axaxZsxg8eDDguIB+/vnn07lzZzIyMnwcnQlU4ihwvHBikbFAC6DEgx5F5CAQiWNSgBM474isqsVNCFBqCQkJmpiY6OnTGj+TnZ3Nf/7zHzZs2MCECaUZs2tM4BKRZaqa4Os4AomIXILj1gDZqhonIgnA06p6eRH7V1i+KgnLaYFp69atfPLJJ3Tv3p3+/fsD8Pe//513332XefPm5RvXU1Du/28iQnJyMl27duWBBx7gwQcfrIjQy+XYsWNcc801VK9enZkzHf8WHjhwgGXLljFo0CC/mgGrqlBVJk2aRLt27Tj33HOL3O/IkSP873//o3Hjxq5xUN5WVE7zZhHzUyGbVd30GRaR5oVtL+ZqWJnYB37V9fbbb9OiRQsGDRrk61CM8QorYkpPRJYClwOzVLWLc9taVW1fxP4Vlq9KwnJa5fHqq68ydepUFi5cSFhYGDk5OVx11VX07dvXVaDMmDGD4cOH88EHH9C7d28AMjIyTru3h7/LyspyzWD29NNP8+yzz/Lmm29yzz2F3qLJeNGBAwdo2LAh/fv3Z/bs2UXut27dOtq3b89VV13FF198USGxFZXTvDb3nar2LX6v045JEpG6OObrX+6FsEwVl5yczCOPPEJISAjbtm1zO42gMaZqUdV9Ba4Ap7vZ1/KV8YqHH36Yhx9+2LW+cuVK/ve//xESEuIqYk6cOMHu3bv5448/XEVMoBUwQL4pmAcNGsTatWvzzTa6bNkyunbtai0zFSAkJISxY8fSqFEjt/u1bduWMWPG5Js4w1e82RIjwG1AG1V9XETigCaqutjNMaVqzi8Pu2pVdf30008cP36cyy/3+J+VMX7BWmJKT0TmAkNwtMR0FZE+OPJPoRfkKjJflYTltMpt586dpKWlucb0HD9+nKysrEp9IW758uV069aNG2+8kY8++sjX4RgfKiqneXOK5VeBC4ErneupwH+KOeYZ4GwcgytR1USglXfCM1VV3759XQVMTk4O9957L7///rtvgzLG+NoTwCyghYjMAz7G/X1fLF+ZChMbG5tvUoLatWtX6gIGHC0Dffv25brrrvN1KMZPebOI6QvciGPQI6p6GAhze4Rjv30FNhXZnG9MeX3//fe89dZb+ZrujTFVj6ouwZG3bgDGAGeq6rJijrF8ZYyXdOjQgTlz5rguOmZlZdG/f3+mT5/u48gqp/fff5/hw4ezY8eOYvddt24dl1xyCf/6178qILKiebOIOaV5+qo5p1surlNjqog0BNR5TB/gqJfiM4aLL76YKVOm8OGHH/o6FGOMD4nIP4G6qjpLVWeq6tFiDrF8ZYyXiYhrPMxvv/3G/PnzmTp1Kt4aClGVffvtt7zxxhukpxd/LaZ27drMmjWLJUuWVEBkRfNmEbNaRG7EMTwmDngbWFjMMY9TuuZ8Y8ptyJAhNG3aFIC9e/dy1VVXsWvXLh9HZYypYHWBX0XkRxG5UUSK6zlQpnwlIreIyGIRWSQiXQt5foQzhnkiUuRsnsZUNT179uS3335j/PjxrsImJSXFx1FVHq+99hoLFizId6+jojRt2pStW7fy+eefV0BkRfNmEfMw0AdoDCxxvtaj7g5Q1d8oZXO+MZ709ttv89VXXzFp0iRfh2KMqUCq+ijQDHgNuApIEpHxbvYvdb4SkQjgfhy5cSjweoHnLwbqqWp/Ve2jqnPL/h0ZU/l06dKF6GjHrZg2btxIy5YtGTdunI+jqhxiYmI4//zzSzTLnYjQokULn88a580pllOBO51LaY5LwXF1y5gKN2rUKOLj4xkyZIivQzHGVDBVzQa+EZFtOFpVbgPucrN/afNVd2ChqmYA20SkjoiEqmpu/43rgGQRmQPsAe5zvoYxpoBdu3aRk5NDUFCQr0Opso4dO0Z6ejpRUVE+eX2vtcSIyBYReUpEmnrrNYzxtGrVqjF06FDXh+LMmTO59tprOXbsmI8jM8Z4k4jUF5H7RGQZ8DmwEWjp4ZeJxDmbmdNRoH6e9SZAjqpeiKMHwxPuTiYiw0QkUUQSDx486OFQjfFv/fr1Y/369fz97393bTtx4oQPIwpcW7ZsITY2lqeeeqrEx8ybN4969erx0ksveTEy97zZnewKIAJYIiKzReSGEvQxNsZvqCpjx47lyy+/ZM2aNb4OxxjjXRuATsD9qtpWVV9Q1Z0efo0jQHie9XrObXmf/875+DtnPEVS1QmqmqCqCb66EmqMLzVs2NDVpWnixIl06NCBtWvX+jiqwHP48GFOnjxJWlpaiY8588wz6datG7GxsV6MzD1vdif7A3hEREYAFwN3AG+Q/6qTMX5LRPjmm29YuHAhPXv2BByFja/7gBpjvKKZqpY8g5fNEuA5EQnGMV70eJ6uZADzgATgR+fXzV6Ox5hKY/369Rw6dIjMzExfhxJwunfvzuHDh8nOzi7xMVFRUfj6BrvebInJ1Q7HIMazgeIGPUaLyEcissC53klE7i7mmG4i8oOI/CQiYzwVtDEAYWFhDBgwwLV+//338/DDD9uHpDGVjKqmichAEXlMRP4vdylq/7LkK1VNBt4C5gNTgQdFpLOI5E568wHQXkR+wjEe5wUPfGvGVAljxozhjz/+4KyzzgKwaZjLINDGF3lzTMz9zr7FX+BoIj9XVQcUc9g7wM/82dy+HrjHzWuEAC8BV6tqX1V9rNyBG1OE5ORkvvnmG77++mvrd2tMJSMiLwEjcMysGYMj98S7OaRU+SqXqk5U1Z6qep6qJqrq76r6b+dz6ap6kzOfDSzkZprGGDeaNWsGQHZ2NjfccANvvvmmjyMKDElJSRw4cKDUhd/+/fuZOHEiixcv9lJk7nmzJaYjpe9bHKOq/wWyAZwzuOS42b8HcByYIiJzReT8ckdtTBEiIiJYtmwZM2bMIDw8HHDcQdgYUylcClwE7FfVu4BuuO/+XNp8ZYypIFu2bOG7777jvffeIyMjw9fh+L0777yThg0bUtoJQtauXcvtt9/ORx995KXI3PPmmJhSTa3slO8/QhEJB9wNQGgCnAV0BuoAc0TkDC2ilBSRYcAw+LNaN6Y0IiMjiYyMBByzoPTq1YvLL7+cZ555xsbKGBPYTqlqloioiASr6u5iZtcsbb4yxlSQ+Ph4Fi5cSFRUVInue1LVnXPOOQQFBZV6quSEhATGjBlDv36+uS+v14oYEYnFcQOwswDXrGSq6m7Kyi+cNxerIyK34Gian+hm/yPAYlU9BhwTkUNAFHCgsJ1VdQIwASAhIcE6S5pyWbduHXv27GHHjh1WwBgT+FJFpCawGJgkInsBdwP9S5uvjDEVqEOHDq7H+/fv58UXX+Sll14iLMwmyi1o9OjRZTquTp06PPqo2/vYe5U3u5NNxDHDCsCNOPoOu70NuqqOARbgmADgEuB1VX3NzSFLgHgRqS4idYBo4HB5AzemJBISElizZg3/+c9/XNsWL15sg/6NCUxDcLSuPAKsBRS4tqidy5CvjDE+8vjjj/Paa6/xzjvv+DoU40HeLGIaqOp7QLaq/gLcguODvkgi0k9VP1bVv6rqdar6kYgU2UalqkeBcTimpfwRGOG847IxFSIqKso1PmbNmjX07duXyy67zGZFMSbAqOp+Vc1Q1ZPANFV9RFV3FLV/afOVMcZ3Xn/9dV588UXuvfdeX4fid3bt2sX48ePLfD+8X375hUGDBjF58mQPR1Y8bxYxuSOpjotIMyAYR1cvd14u4TYXVZ2sqr1U9RxV/bIMcRrjEQ0aNODiiy/m5ptvtu5lxgS2aSXYp9T5yhjjG3Xq1OHxxx+nWjXHv70///wzO3YUeY2iSvn111+5++67+eKLL8p0vKry/fffs2TJEg9HVjyvjYkBFohIfRxz4i8D0oFPC9tRRFrjmMqyrojkba2pB9T0YozGeEyjRo348ss/6+icnBweeeQR7rrrLtq2bevDyIwxpVTkVQjLV8YEtm3btnHxxRcTGRnJunXrqFGjhq9D8qkuXbrwxhtvcO6555bp+ISEBLZv3+6TCbO8OTtZ7kifySIyH6irqkW1VZ2Ho7tZQyDvCKFjwD+8FaMxnpa3Beabb75h7NixrFu3jlmzZvkwKmNMKS1y85zlK2MCWFxcHPfddx+tWrWq8gUMQKtWrcrVzS4kJITmzZt7MKKSk4rouy8i/1DVV0qw3y2q+oHXA8IxO1liYmJFvJSpolSV999/nz59+tCypWNSvoyMDJvu0XidiCxT1QRfxxGIRCRKVYu9WUJF5quSsJxmTNlt27aNFi1a+DqMgJaSkoKqusYJe1JROc2bY2LyurGE+x0QkUsKLl6NzBgvERFuu+02VwGzb98+2rRpw/jx430cmTGmIBE5R0SSgOXO9QQRmeDmEMtXxlQC48aNo127dvzvf//zdSg+cfvtt/Pggw+W6xxTpkwhPDyc999/3zNBlZA3x8TkVdJRznmb5sNw3MRyOTDT0wEZU9FWrlzJ4cOH2b9/v69DMcac7lXgYuBjAFVNFBF3twWwfGVMJdCsWTPCw8Np3bq1r0OpcCdPnuTDDz8kNDSUadOmERYWRv/+/XnmmWdo0qRJic9z5pln0r17dyIiIrwY7ekqqjvZQFX9oQzHtQceVdVbPR2TNb0bX9i+fTsxMTEEBwcDsGDBAs4//3ybzcx4lHUnKz0RWaqqZ4vIClXt4tzmelyC472Wr0rCcpoxZXfixAlq1arlehwUFFRpb4qZlZXFzz//zCeffMInn3xCSkoK4JhhNS0tjRMnTtCgQQO+/fZbunfv7uNoHXzSnUxELhSR+1T1BxFpKCLxpTleVdcCXb0UnjEVLi4uzlXAzJo1i969e9u89cb4h3QRqY3jJpe5Rcmpkh5s+cqYwJVbwGRnZ3PDDTfQr18/Dh065OOoyicnJ4cjR47w+++/8/XXX/PCCy9w5ZVX0rhxY/r27cv48eMREe6++24WL17MgQMHOHLkCKNGjeLQoUP07duXuXPn+vrbcMtr3clE5HEcN7dsDLyB4z4xE4Febo7J25+4GnA2YLc/N5VSq1atOP/88xk6dKivQzHGwPPAD0ATEfkAGAQU+ea0fOUZ2dnZZGcXfY9qd71FyvpcQSLiag1397Wo57xJVVFVMjMzSU9PP23JyMhARAgJCSE0NJSQkJDTlqCgoHLHmpOTQ2pqar6fa95zFvdYRAgKCnItufdr8TRVJT09nVOnTpGWlsbJkyfzfU1LSyM7O9v1cy24nDp1il27dpGamsr3339PcHBwkfuWZMnJySnX8blLeno6aWlpru+rsK8nTpzg+PHjpKamcvz4cU6cOFHo+6BevXrccMMNXH311Vx88cX5ZmgLCQnh6aefpkWLFtx6661cfvnlzJw5k969exf7s9+zZw/ffvstCQkJdOlSogbscvPmmJghQALwG4Cq7hKRusUck7ePcRawGbjWO+EZ41vx8fHMnz/f9SF/8uRJrrjiCoYPH85f/vIXH0dnTNWiqrNEZANwEY5xnM+p6mY3hwR0vlJV5syZQ4sWLThy5Ag///wzmzdvZu/evRw8eND1j1HukpOT4zou7zmKUtQ/tdnZ2WRkZLj+Cc89b2VQ0mII/ixO3D32ZFy1a9cmPDyciIgIwsPDXY/r1q1LvXr1qFu3Ljk5ORw/fpyUlBQOHDjAwYMHOXDgAAcOHODQoUMe/13lLWoKFjiFbSvs55SZmZnv7ykz03PXEQLxAmOtWrWoU6cOjRo1ok6dOoSHh9OsWTOaN29Oq1at6N69O/Hx8a4icvTo0YwbN46pU6dy4YUXus5z0003Ua1aNW666SYuvfRSZs6cyQUXXOD2tX/99VeGDRvGiBEjKkURk6aqmQWqf7fvTFXt68V4jPE7ed8fP/zwA3PmzOGMM86wIsaYCiYiUcAuVX3buR7ibrrlQM9XX3/9NVdddZXbfUJCQggLCyM0NJSgoCDX9sJaJwpT2D/j1atXp1atWvlaDapXd/+viLvXKOtzeWPM+49xUV89uU9RrTsFH+ddDw4OJjQ09LQld8r+3FaZwpb09HRSU1M5evQou3fvLlUxUr16daKioujQoQP169fP14LirqAtuJ6Tk+NqdSvpkpWVRXp6OtnZ2eTk5BT6M6pevTo1a9YkIiLitJ9NrVq1qFGjBjVr1qRmzZrUqFGDGjVquFqmSrIcP36ccePG0aFDB6688kqqVatW4mM9uYSFhbmWGjVqFPo1LCws3/u0JHL3L2xa5KFDh5Kdnc2tt97KgAEDGDNmDPfcc4+rS3xBF1xwAWPGjGHQoEGn/e737t3Lpk2b6N69OzVreu6ewF4b2C8inwKvAa/jaJF5EmivqjcUsq/baSlV1eOzvdggSOOPVqxYQePGjWnUqBEAL7/8MmeddRb9+/e3wf+mxGxgf+mJyBKgr6qedK7XAuao6rkF9qvwfFUSpc1pmZmZtGrVip07d9K3b1/++te/0qFDB5o0aUJ0dDQ1atTwWpcf4zuqyvHjx0lOTubo0aMcO3aMlJQUUlJSCAoKonbt2tStW5fo6GiioqIIDw+v0n8H69at49JLL2XIkCE8//zzvg7Ha/IW1wV9/vnn3HTTTZw8eZIzzjiDu+++m4EDBxIeHu4qnnJycti5cyc7duwgKSmJzZs3s2nTJjZt2sTmzZtJS0sDYMmSJWWaLKConObNIqYR8CHQB8gBFgI3quqBQvb9yc2pVFX7eTo+K2KMv9u9ezfNmzenSZMmbN682W6SaUrMipjSE5HfVbVzCbZVeL4qibLktLVr17J69Wquu+46u0hiTBGOHj1KnTp1XK0Wu3btomnTpj6OqmIlJSXx+OOP88knn5TquKCgIOLi4mjTpg1t2rTh3nvvpW3btqV+/aJymte6k6nqPmCgiNQEqqnqcTf7BnSzvDHeEBMTw9y5c0lNTXUVMEuXLiUnJ4dzzjnHx9EZU/nk7T4mItEUMoNnZcpX7du3p3379r4Owxi/lrer1axZs/jLX/7CG2+8wbBhw3wXlAekpqayYsUKzjzzTCIjI93u27x5c6ZOncqoUaP47LPPWL58eb4xc6pK06ZNqVmzJr/++is9e/bkiSeeyDcjqzd49WaXItIKaAVUzzOYzW1Tu4hcBPR3rv6gqrO9GaMx/izvQDpVZfjw4SxZsoRVq1bRsWNHH0ZmTKXzOrBIRD50rt8EvOjugLLkKxG5BRiGY4zocFVdXsg+z+DouVD17r5njB8TEerVq1em1gR/k5iYSL9+/Rg+fDivv/56iY5p27YtTz31VJHP79y5k2bNmtGpUyfatGnjqVCL5M0plscANwMbgNz5ExU3dzMWkUedx0x1bnpVRCap6sveitOYQDJy5Ehmz57tKmDS0tLYunUrZ555po8jMyawqepEEdmK49YAAHeq6vyi9i9LvhKRCOB+4FwgBphMgdsOiEhDoFT3VDPGVIxBgwaxfft2131lMjIySEpKqpB/2D2tQYMG3HPPPfTv37/4nUsoNjaWpKQkYmNjPXZOd7w5JmYTcFbuIMkSHrMKOE9VU53rdYBFqtrJ0/HZmBhTGbzyyis8+uijTJw4kVtuucXX4Rg/YWNivK8s+crZcnOJqj7gXF8JdFfV9Dz7vAFMAL4oTUuM5TRjKt4DDzzAxIkTmTFjRonupWLKpsLHxAA7gIxSHiO5CQFAVVPFRhsaU6SWLVvSsWNHBg4c6Np29OjRQqdLNMYUTUTqASOAzkBY7nY3A/XLkq8igeQ860eB+sBeZwxtgNqquspSnzH+78wzz6Rp06bWvbuAI0eOcPDgQa93u/PmvHn/AL4RkYdF5J7cpZhjlorI+yLS07m8B9ilJWOKcNVVV/H777/TpEkTALZs2UJMTAzPPvusjyMzJuBMxNH1OR54x/n4Nzf7lyVfHQHC86zXc27LNQoYXdKARWSYiCSKSOLBg4XezsYY40XDhg1j1apV1K9fH4CtW7eyd+9eH0dVMiNHjuSDDz7w+Hn37NlDVFQU99xT3L/85efNIuZxoDGOq1pnO5fiujcMB/bjGGD5OnAQuM97IRoT+PJesU1KSiIiIoKGDRu6tqWnpxd2mDEmv9aq+k/gpKpOBS4D3N2iuiz5agnQS0SCRaQZcDxvVzKgJfCmiHwHNBYRt6NtVXWCqiaoakJUVFQxL22M8Ybc2bdOnjzJlVdeSdeuXdm9e7ePo3Lv2LFjPP/887z99tseP3eTJk247LLL6Nmzp8fPXZA3u5N1A+K1FINuVPUEjuLHGFMG/fr1Y/Pmza6bk6kqvXv3pkmTJkyZMoWwsLBizmBMlZVbTGSISH0c3b6KrAzKkq9UNVlE3gLm45jo5gER6QwMUNV/q2qP3H1FZLOq3l/K78EY4yOhoaH85S9/Ydu2ba7eEf4qLCyMefPmkZmZ6ZXzf/311145b0HeLGI2ArWAIu8PU5CIPAy8p6opzmkuuwP3q+oPXorRmEonb6Fy6NAhjh07Ru3atV3bs7OzqVatmt3czpj8NjqLlynArzjGqywrauey5itVnYij61pevxeyn02vbEwACQoKYvTo0eTk5Ljy69KlSznrrLP87mbVISEhlWIiAm92JzsGLBOR10VkTO5SzDG3OBNCX6AhcBvwghdjNKZSi4qKYs2aNfnusjt27Fh69erFH3/84cPIjPEvqjpUVY+o6qs4cs+zwFA3h1i+MsacJrcnRGJiIhdccAFXXXUV3poJ2J99+OGHPPjgg159DW8WMetxXNE6DJzIs7iTez+ZvsDHqroY78ZoTKVXrVo1GjRo4FpftmwZy5Ytcw1EBKrkB6wxBYlIAxG5DMfg+19VNcvN7pavjDFFat26NT179mTo0KF+1/OhT58+XHLJJV7N/e+99x6vvfYaO3fu9NpreK07mao+U4bD0kRkBDAEON85XaV/tcEZE+CmTp3Ktm3baNy4MQCbN2/miiuu4LnnnmPw4ME+js4Y3xCRwTjuz7IMEGCiiAxT1a+KOMTylTGmSOHh4cyePdvVMgOOqYfzXkD0hczMTLZt20ZERIRXi6vnn3+e0NBQr44P8ngRIyLXquqnRU2nrKpvuTn8FuAeYISq7hORVsDHJXjNNByzvgBMVtX3Shm2MVVKixYtXI/nzp3L+vXrOXz4sA8jMsbnngd6qupGcN2z5X/AV0XsfwtlyFfGmKojbwHz3HPP8fbbbzNnzhzatWvns5iCg4PZvn07R44cKX7ncujVq5dXzw/eaYkZBHyKY0rlgty2WzmTx4MiUltEaqvqFuDFErzmblXtU+pIjTEMGzaMPn360Lx5c8DRtezyyy/nvPPOY8SIEfk+hI2pxE7lFjAAqrrJeYGsUOXIV8aYKigjI4OsLHc9VCuOiBAZGVkhr3X8+HFEhFq1ann83N7476QLgKreWshym7sDRaSdiCwFDgEHReQ3ESnJ7T4bich8EflCROLK/y0YU7XEx8cTGhoKwKZNm5gzZw4//fSTq4DJycnxZXjGVISvReQpEWkkIo1F5EngKxGpISI1C+5cjnxljKmCnn32WdasWePTVhiA+fPnk5KSUiGvNX36dKKjo/nwww+9cn5/u8T6ATAOqAHUxHEDsUklOC5OVXsD44Eiu5LZ3Y2NKV58fDxJSUm8+eabrm2jR4+mR48erF692oeRGeNV/weMBvYAu4DngFE4JqRJLWT/DyhbvjLGVFG5N6U9deoUTzzxBKmphX20eM/+/fvp27cvAwYMqJDX69Spk1fHAHmjO1lHETlQyHYBVFWj3RxbW1XzlmsfOQdOuqWqh5xfvxeRN93sNwHHwE0SEhJsOiZjihAdHU109J9v1Q0bNrBs2TLXZAAAv/76K927d7fuZqZSUNVqACISAfQBtqrqSjeHlClfGWPMv//9b1566SVOnDjB66+/XmGvm5WVxQMPPECbNm0q5PXatWvHjh07vPZ/gjeKmI3AJWU8dpmI9FLVnwFE5Dwg0d0BIlIbSFPVbBHphKNp3xjjQVOmTOGVV15xTdW8fv16evToweDBg/n88899HJ0xZSciHwH/VtWVzptdrsRxn7MGIvKUqr5bxKGlzlfGGAPw2GOPkZmZyaOPPlqhrxsTE8PYsWMr9DW9eaHTG0VMuqomleYAZ79ixTE95QIR2eR8qjWwqpjD2wPjRSTVeY67ShmvMaYE8rbCqCrXXXcdl1zy5/WKL7/8kpSUFK677jpq1jxtCIEx/qprnhaXvwHrVHWgiDQFZgD5iphy5itjjCE0NJRnn33W12FUmJkzZzJ37lxefvllj57XG0VMRhmOeaSsL6aqv+GcTMAYUzHOOOMMpk2blm/bM888w8qVK+nTpw9xcXGAo9jxt5t8GVPAqTyPewFfAqjqLhEprNtxmfOVMcYUtGLFCh577DE++eQTr84YNn36dL788kueeuopOnTo4LXXKUxu609qaip16tTx2Hk9XsSo6rllOGa+p+MwxlSsyZMns2DBAlcBs2fPHvr168cjjzzCHXfc4dvgjHFDRJoAyTjGwjyd56mwgvtavjLGeNKnn37Kjz/+yLRp07jnnkJvsegRs2bN4pNPPqnwLmzgaIkJDg72+Hm90RJTZiJSDxgBdCZP8lDVfr6KyRhTMh07dqRjx46u9V9++YUtW7bku4lmYmIiYWFhtG/f3iYEMP7iReB3HL0IflbVtQAici6wo6iDLF8ZYzxh1KhRnHfeeVx66aVefZ333nuPG264gS5dKr7zkjcKGPC/KZYnAtlAPPCO8/FvPo3IGFMmV199Nbt37+auu/4cpvbYY4/RsWNH9uzZ49q2aNEijh8/7osQjUFVPwU6AZcBg/M8tQO4082hlq+MMeUWEhLi9QIGHAPsBwwYUKm6ePtbEdNaVf8JnFTVqTiSygU+jskYU0bR0dGEh4e71q+99lruvPNOmjZtCsDBgwfp1asXF198sWufI0eOsHPnzooO1VRhqrpPVX9XVc2zbY+qFtkSg+UrY4wHZWVl8corr/Dwww979Ly///4777//fqW8abW/FTHpzq8ZzqkuM4AoH8ZjjPGgv//970yYMMG1np6ezl133cU111zj2jZ16lSaNWuWb799+/aRlZVVobEaUwzLV8YYj8nIyODNN9/kvffew5M3ZH/ooYe47bbb+PHHHz12Tn/hV2NigI3OZDAF+BU4CizzaUR55OTkWD9+H8jJySE7O9trfSqN7zRt2pT//ve/+bY1bNiQfv36cfbZZ7u2XX/99SQmJrJjxw7X3X89PcuJMaXk1/nKGBNYatasybRp02jcuDFRUZ67HjJ+/HgmT57MgAEDPHZOfyF5Ws/9ioj0AsKB71TV45dgExISNDGx5PclU1Xq1KlDnTp1aNiwIY0aNXL7tX79+lWu4MnIyGDnzp0kJSWRlJTEnj17OHnyJOnp6Zw6dYr09HS3j4t6LjMzE4CwsDDCw8NdS0RERInX69WrV+WLIFUlLS2NlJQU13Ls2LFi17Ozs6lRowY1atQgLCysXI+jo6OpXbt2qWO//fbb2bhxIwsXLgRg//79NG7cmL/97W9MmjQJcLTqBAcHB+z7Lisri6ysLDIyMjhw4AB79+6lZcuWxMTElPpcIrJMVRO8EKYphLfzVUmUNqcZY0ygKCqn+VtLjEvuXZD9RVpaGq1atWL//v2sXr2alStXut2/evXqREdH06hRoyILnTZt2tCkSZOAGWR17NgxV4GyY8cO1+Pc9b1791Keojg0NNS11KhRg/DwcNd6UFAQqampHD16lO3bt3Pq1KniT1hArVq1iIiIIDIykjZt2tCuXTvXEh8fH7BX9TMzM9m+fTsbN25k48aNbNiwgT179pxWlBw7dswvumRFRkYSFxdHixYtiIuLy7c0b9680CLnvffey7d+4MABunXr5hpbAzBhwgRGjhzJpEmTuPLKKwFHYR0SEuLV7yevTZs2sX37ds4++2zXWKC3336bDRs2cMcdd7B//36SkpJ44YUXqFu3Ll26dGH//v1s3LiRTZs2ERQURHZ2tut8b7zxBvfee2+FxW/Kxt/ylTEmsG3fvp0RI0bw8ssvExsbW+rjN27cyJNPPsk777xDRESEFyL0D35bxPibmjVrugqX7OxsDh06xL59+9i/f7/br8uXL3d73sjISM4666x8yxlnnEFoaGhFfFsuqsqhQ4fYtm1bvuIkb5Fy9OjRIo+PjIykS5cuNG/enObNm9OsWTNiY2OpXbu2qxAJCwvLV6jkXQ8JCSlVMXfq1CmOHj2ab0lOTi7RtqKK0JiYGNq2besqbHIfN23a1OdX91WVvXv35itUch9v3bq1yOJERKhbty716tUjJiaGevXqudZzl+LWg4KCSEtLIy0tjVOnTrkeF1wv6nHu+smTJ9m/fz/bt29n+fLlLFtWeM+bBg0a5Cts8hY7zZs3p1atWnTs2JGlS5fmOy47O5tatWrl+8AfMGCA631Yq1Yt135BQUGl+vlnZWWxceNGcnJyXDcJW7BgAU8//TQ33ngjnTt3ZvXq1bz22musXLmSrl27kpmZyf79+zlw4AAAr7322mnnXbFihetxUFAQkZGRtGvXjujoaBo0aMCZZ55ZqjiNMcYEvq+//prp06cTFxfHv/71r1If/8Ybb/D5558zYMCAfDOEVjZ+253M2yqq6T0zM5ODBw+eVtzs3buXtWvXsnLlytMGcFWvXp0zzjjjtOImOjq6XLGcPHmSbdu2sW3bNrZu3Xra1xMnThR6XLVq1YiJiXEVJ7mFSu6SW6wEioyMDLZu3cr69etZv349GzZscD0urFCrWbMm8fHxpxU38fHx1KxZ06OxpaSkuIqTgsVKYb+f0NBQ2rRpQ3x8PG3btiU+Pp74+HhiY2MJDw+nVq1aPi/ACpOens6OHTvYvn17oUveKZgLioqKchU3rVq1olWrVrRs2ZJWrVoRExNDtWrVEBFUlf79+7Nnzx7WrVsHwN69e2nTpg3Dhg3j1VdfBRwFyt69e2nQoAE1atQA4JlnnuGPP/5g+vTpgGPGtMjISM4991yeeOIJVq1axezZs1mwYEGRcQYFBREdHU3NmjUJDw+nbdu2NG7cmOjoaOrWrUtsbCyNGzemYcOGREVFebTFyLqT+S8RuQUYBigwXFWX53nuMeBqIAtYDtyvJUzS1p3MmMojKyuLTz75hCFDhpT4oltmZqar2/ypU6f47LPPuPHGGwOmt487ReU0K2J8TFXZt28fq1atYuXKla5l/fr1+bqVADRq1IhOnTrlK2zatm3r+qPNzs5m165dhRYo27ZtY//+/YXGEBQURLNmzWjRooXrqnfeYiUmJqZKjCdRVQ4ePHhaYbNhwwa2bdtW6PSEUVFRBAUFuT4kRMS1lHY9JSXFddU+LxEhLi7utEIlt1jxxyKlvE6dOuW2yNm7d2+hx4WEhNCiRQtXUdOqVStatGhB69atadmyJatXr+baa6/lhhtu4MUXXwQcLSQPPvggc+fOpW/fvgD06tWLRYsW8corr7Bp0yZWrlzJ0qVLT2vxCg4Opn379px11ll06tSJDh06EBsbS8OGDYmIiPDZ78aKGP8kIhHAHOBcIAaYrKq98jzfRlU3OR9PB8ar6pySnNtfcpoxxvNU1W0xMmHCBJ544glmzJhBjx49KjCyimFFTAH+/oF/6tQpV0tN3iU5OTnffiEhIbRr144TJ06QlJRUZLeiqKgoWrZs6SpUch+3bNmS2NhYqle3noXunDp1is2bN7uKm9yvu3btQlVdY4EKe1zS9dwWn4LFSsuWLQkLCyskqqorLS2N7du3s2XLFrZs2cLWrVtdj7dt20Z6enqhxzVp0oRWrVoRFxdHmzZtaNWqFfPnzycxMZFOnTpx5MgRVq1axfbt2087NjY2lk6dOtGpUyc6duxIp06diI+P98sC34oY/yQiFwGXqOoDzvWVQHdVPe0PVkQmA++q6vySnNvfc5oxpvRUlc8//5zXX3+djz/+mNjYWFcrTVZWFrfccgsAM2bM4KabbmL06NGVchylFTEFBOIHvqqya9eu0wqbTZs2UaNGjXzFScHHgdTdy5jyyMnJYffu3fkKm7yFzpEjR9wenzvmJrdQyS1aAmlwpBUx/klEbgDiVXWUc30+cL2q7i2wX2/gn8AA605mTNV1/Phxhg4dytdff822bduIi4tDValXrx7169d3XXDLzs4mMzOz0l7wDLjZyczpRITY2FhiY2O57LLLXNszMjIIDg6uFP0ejSmvatWqud4nvXv3Pu35o0eP5itqkpKSXF01O3XqRIsWLSplFz3jF47gmIo5Vz3nNhcR6QS8BFxeXAEjIsNwjK+hWbNmHg3UGON7tWvX5quvvmLlypWu6fZFhHHjxrnumQaOYQGlnbCmMrCWGGOMqWSsJcY/OcfEzAZ6AI2BKQXGxLQGPgGuVtWk0pzbcpoxprIqKqfZ5UZjjDGmAqhqMvAWMB+YCjwoIp1F5FHnLv/B0VIzSUTmicilPgnUGGMCgHUnM8YYYyqIqk4EJhbY/LvzuctOO8AYY0yhrCXGGGOMMcYYE1Cq7JgYETkI5O1z3AA45KNwyirQYrZ4vcvi9a5Aire5qkb5OghTcQrJaSUVSH/XBVnsvhPI8VvsvlGe2AvNaVW2iClIRBIDbSBsoMVs8XqXxetdgRavMSURyH/XFrvvBHL8FrtveCN2605mjDHGGGOMCShWxBhjjDHGGGMCihUxf5rg6wDKINBitni9y+L1rkCL15iSCOS/a4vddwI5fovdNzweu42JMcYYY4wxxgQUa4kxxhhjjDHGBBQrYowxxhhjjDEBxYoYY4wxxhhjTECxIgYQkVtEZLGILBKRrr6OpzAi0sUZ3wIRmSsiLUUkTEQ+FpGFzq9hvo6zIBGJF5FMEenl7/GKSDcR+UFEfhKRMeIwzhnvDBGp7+sYczlje0NEfhGRpSIyxB/jFZHvReSgiIzME/dpMYpIfef6Qufz4ifx3iQivznfd5+ISKhze5zzfbhIRJ70RazGlEdly3v++p4sSQ7049hLlBP95fM7T9wlzo/+Ent5c6WIdHX+/SwWkVt8HHup8qaIDHL+rn4RkYtK9eKqWqUXIAJYDoQALYCffR1TEXE2Auo4H18CTAbuBv7p3PZ/wN2+jrOQuCcDPwK9/Dle5+9/du7P2LltEPCe8/FNwEu+jjNPbB2An5yP6wBb/DFeoClwCzDS3c8UeAn4m/PxRGCQn8TbEghyPh4D3O58/AlwvvPxj0A7X/+sbbGlpEtlzHv++p4sSQ70x9hLkxP95fM7T5wlzo/+Ent5cyWwyPleDnG+tyN8GHuJ8yYQBKwCwp3LytxjS7JYSwx0BxaqaoaqbgPq5FaN/kRV96lqqnM1HcgCegMznNu+ca77DRE5B9gH7HJu8ud4ewDHgSnOKwXn49/x7gEyRCQYx4f0EfwwXlXdVWBTUTH6RewF41XVraqa7VzNfd8BdFbVhc7H3+IHP2tjSqEy5j2/e0+WIgf6XeyULif6xed3HqXJj34Re3lypfO9W0tVt6lqBrAQx3u8QpQzb7YGtqnqUVU9Cmx3bisRK2IgEkjOs34U8Hk3nKKISC3gOeDf5I/9KP4X91M4rhrk8ud4mwBnATcCfwPeARqQP94In0RWuGRgE7AR+B3H30TBn68/xZurqBjrO9dzt/vT3wYi0g7HlbFpzk15PzuP4mfxGlOMypj3/PE9WdIc6I+xlyYn+tvnd2nyo7/Fnqs08Ubm2ZZ3u0+VMG+W67OoerkirByO4GjCylXPuc3vOK8qTAP+paprRSRv7H4Vt4hcCiSq6uE8XUz9Nl4csSxW1WPAMRE5hKOZM9z5fD3yv9F8bQAQg+OKRT0cV15+wH/jzVXwbyA3xmTn+lH87G9DRJoCk4DrVfWUc3NOnl38Kl5jSqAy5j2/ek+WMgf6VexOpcmJ/vb5XZr86G+x5ypNrvS793Mp8ma5YreWGFgC9BKRYBFpBhxX1XRfB1WQiFQDPgK+UtWvnJvn4+gnjPPrfB+EVpTOQB8R+Q7HB8rLwDr8N94lQLyIVBeROkA08Dn+G68Ayc4m21Qc/WB/xH/jzVXU36xf/i2LSAMcfwd3q+qWPE+tFJGezscXAwsqPDhjyq4y5j1/e092puQ50N9ih9LlRH/7/C5NfvS32HOVOFc6i4QTItLMWfT3An6ryGDzKmXe3AS0EJG6IlIXx7iezSV+LecAmypNRG4D7gAUeEBVE30c0mlE5BrgAyA3ttXAYzgGdjXF0ef21jwVr98QkQ+Ad4Fl+HG8IvI34C4gGEcXgK+BcUAn4Bhwk6oe9l2EfxKRIOA9HFeaQnEMHn0DP4tXRN4BeuKIcQ0wmEJiFJFI4EOgLo5BfsNVNafws1ZovLuAK/nzQ3Wyqr4nIi1x/PxDgFmq+lxFx2pMeVS2vOfP78nicqC/xl7SnOgvn9+5SpMf/SX28uZKEUkAXsNRwL2rqhN9GHup8qaIXAL807nvaFWdWeLXtiLGGGOMMcYYE0isO5kxxhhjjDEmoFgRY4wxxhhjjAkoVsQYY4wxxhhjAooVMcYYY4wxxpiAYkWMMcYYY4wxJqBYEWOMMcYYY4wJKFbEGGOMMcYYYwJKdV8HYEwgEJFwHHdg3g4cVdWjPgzHGGOM8QrLdyZQWEuMMSXTHfgb8CDQ1rehGGOMMV5j+c4EBCtijDHGGGOMMQHFihhjSuY3YDLwH2BDUTuJiIrIKhHp781gRORHETkiIvd583WMMcZUXiISLCKPF9js0Xxn+cp4i6iqr2MwptIQEQXqqOrxCnitD4BEVX3D269ljDGm8hGRBOANVT23DMeWON9ZvjLeYC0xxuQhIh+LyO/OZZeIbPHAOVVEnhKRpSKyVUQuFJEXRWSFiKwRkTNKs58xxhhTXiLSEfgfEOfMeQVbZEp7vpoi8qmIrBWRlSIy3TORGlM4K2KMyUNVb1TVzsAQIBm40UOnPqqqZwMjgK+BRaraBfgQeKoM+xljjDFlpqqrceSZkaraWVVfKucpLwLqqmp7VT0LuKvcQRrjhhUxxhQgIl2AT4Ghqvqrh047zfl1OaCqOsO5vgxoXYb9jDHGmPLqhiPfeMJK4AwReVNErgXSPXReYwplRYwxeYhIDxytHler6koPnvqU82s2+T/Ys8l/v6aS7meMMcaUmYgE45hCeY0nzqeqW4EzgdlAf2CliIR54tzGFMaKGGOcRORC4L/A5apa5IwsxhhjTCUQA6SoaoYnTiYiTYFsVf0KeAiIAup74tzGFMaKGGP+NB0IB75yDnL8ycfxGGOMMd6yC1jvnDhmlAfO1xH4RURW4pim+UVV3eOB8xpTKJti2RgPsimWjTHGVAU2xbLxNWuJMcaz9gOLKuJml0Bv4IQ3X8cYY4wpQonyneUr4y3WEmOMMcYYY4wJKNYSY4wxxhhjjAkoVsQYY4wxxhhjAooVMcYYY4wxxpiAYkWMMcYYY4wxJqBYEWOMMcYYY4wJKFbEGGOMMcYYYwKKFTHGGGOMMcaYgGJFjDHGGGOMMSagWBFjjDHGGGOMCShWxBhjjDHGGGMCyv8D7UcThTnkMDIAAAAASUVORK5CYII=\n", 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\n", 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\n", + "image/png": 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\n", 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" ] @@ -671,7 +659,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -725,7 +713,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -811,8 +799,8 @@ "[2] Marc Doyle, Thomas F. Fuller, and John Newman. Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell. Journal of the Electrochemical society, 140(6):1526–1533, 1993. doi:10.1149/1.2221597.\n", "[3] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", "[4] Scott G. Marquis, Valentin Sulzer, Robert Timms, Colin P. Please, and S. Jon Chapman. An asymptotic derivation of a single particle model with electrolyte. Journal of The Electrochemical Society, 166(15):A3693–A3706, 2019. doi:10.1149/2.0341915jes.\n", - "[5] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", - "[6] Robert Timms, Scott G. Marquis, Valentin Sulzer, Colin P. Please, and S. Jon Chapman. Asymptotic Reduction of a Lithium-ion Pouch Cell Model. Submitted for publication, 2020. arXiv:2005.05127.\n", + "[5] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", + "[6] Robert Timms, Scott G Marquis, Valentin Sulzer, Colin P. Please, and S Jonathan Chapman. Asymptotic Reduction of a Lithium-ion Pouch Cell Model. SIAM Journal on Applied Mathematics, 81(3):765–788, 2021. doi:10.1137/20M1336898.\n", "\n" ] } @@ -831,7 +819,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -845,7 +833,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.11" + "version": "3.8.12" }, "toc": { "base_numbering": 1, diff --git a/examples/notebooks/models/simulating-ORegan-2021-parameter-set.ipynb b/examples/notebooks/models/simulating-ORegan-2021-parameter-set.ipynb index ec4bf1167c..b1ce095e5b 100644 --- a/examples/notebooks/models/simulating-ORegan-2021-parameter-set.ipynb +++ b/examples/notebooks/models/simulating-ORegan-2021-parameter-set.ipynb @@ -70,8 +70,7 @@ "metadata": {}, "outputs": [], "source": [ - "var = pybamm.standard_spatial_vars\n", - "var_pts = {"x_n": 30, "x_s": 30, "x_p": 30, "r_n": 40, "r_p": 40}\n", + "var_pts = {\"x_n\": 30, \"x_s\": 30, \"x_p\": 30, \"r_n\": 40, \"r_p\": 40}\n", "\n", "submesh_types = model.default_submesh_types\n", "submesh_types[\"negative particle\"] = pybamm.MeshGenerator(\n", @@ -109,7 +108,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f3b237091d394796927a29926d0a67ac", + "model_id": "7e9913de41054c7cb71be948ebf63375", "version_major": 2, "version_minor": 0 }, @@ -123,7 +122,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 4, @@ -179,6 +178,19 @@ "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, diff --git a/examples/notebooks/models/submodel_cracking_DFN_or_SPM.ipynb b/examples/notebooks/models/submodel_cracking_DFN_or_SPM.ipynb index ea77f1d9ca..f0425407ed 100644 --- a/examples/notebooks/models/submodel_cracking_DFN_or_SPM.ipynb +++ b/examples/notebooks/models/submodel_cracking_DFN_or_SPM.ipynb @@ -66,8 +66,7 @@ "metadata": {}, "outputs": [], "source": [ - "chemistry = pybamm.parameter_sets.Ai2020\n", - "param = pybamm.ParameterValues(chemistry)\n", + "param = pybamm.ParameterValues(\"Ai2020\")\n", "## It can update the speed of crack propagation using the commands below:\n", "# param.update({\"Negative electrode Cracking rate\":3.9e-20*10})\n" ] @@ -88,7 +87,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "52f025d6be294882b5d4f9eedb474c34", + "model_id": "58a6cbde1d01456aba4d5b4977c28720", "version_major": 2, "version_minor": 0 }, @@ -127,7 +126,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1a4c62376c474449863e4837e971c34a", + "model_id": "508090de19594b48ad2a202c4df9b12e", "version_major": 2, "version_minor": 0 }, @@ -194,7 +193,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "70f30cf8e80d4a7a9c671844decddcdb", + "model_id": "4046d2be6c1a45f28233574c852cf6ca", "version_major": 2, "version_minor": 0 }, @@ -260,7 +259,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, diff --git a/examples/notebooks/models/submodel_loss_of_active_materials.ipynb b/examples/notebooks/models/submodel_loss_of_active_materials.ipynb index b953b6692f..737707aa02 100644 --- a/examples/notebooks/models/submodel_loss_of_active_materials.ipynb +++ b/examples/notebooks/models/submodel_loss_of_active_materials.ipynb @@ -40,8 +40,7 @@ " \"loss of active material\":\"stress-driven\",\n", " }\n", ")\n", - "chemistry = pybamm.parameter_sets.Ai2020\n", - "param = pybamm.ParameterValues(chemistry)\n", + "param = pybamm.ParameterValues(\"Ai2020\")\n", "param.update({\"Negative electrode LAM constant proportional term [s-1]\": 1e-4/3600})\n", "param.update({\"Positive electrode LAM constant proportional term [s-1]\": 1e-4/3600})\n", "total_cycles = 2\n", @@ -81,7 +80,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -125,7 +124,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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jdbPUZLqHQsIZQ7ty2uAuvLdsC//4YCW/fnURU2fmMenY3pw/MsskNdWTYgcV0Sj9O7fgwUtH8JOCIqbOXMk/PsjjidlruHh0NleP72mSmtKEZO76PqA5cDHwe6ARsDsFMhkSoKwiwvRFm/n3p2tZuGE3LTIzuOKoHK44MofsdvWzplUlHBLT59chVJUZS7Zw37sryNu6hyO6t+b+i444pC1hfYmWb6owMaLpjAl3cpC9B8rpXEvpn/oSCgmnDOrMyQM7MWvFNqZ+sJLb31jMP2au5IqjcvjBmB60SpEy7HeKS8sSypivCwM6t+ShS0eyvKCIR2at4t+freXJz9Yy8Yhu/Ph7vejXqUVKvteQGMnc9YeACFaf+d8DxcCrwKgUyGWohoqIMu3rjdz//krW7SihZ/vm3Pn9QZw7MovD6hmkXx0mRtQZPl+9gynvLOer9bvp1aE5j/xgJKcM6uRYTFssJkbUE5hwJwepiGiDteoUEY4b0JFj+3fgs1U7eOSjVfx5xgoe/DCPC3K7c/W4no4bBPzOnv3ltMhMrRI/oHNL7r9oOL88pT+Pf7KGF+dt4NUv8zlhQEcmHdub3B7OeBENyZGM5jJGVUeIyFcAqrpLRBwNtBCRCcDfsXoRP66qU6rsF3v/aVg9ka9U1S9rGisibYEXgRxgLXCBLfto4LHoqYE7VPV1J6/HSVSVdxYX8Nf3vmXl1j0c3qUlj102khMP75TyyTcUEhNrWA+WbS7i3neW8+GKbXRqmcmUc4Zw3sislCY7hCqz5s19S2NMuJODRFQrPQENhYgwrk97xvVpz7LNRTz+yRqe/XwdT89Zy4TBnfnh0b0Ykd2mQWXyKsWl5WTXMzY+UbLaNOOO7w/i5hP68vScdTz52RrOf2QOw7Nbc+VROUwY3LleSVOG5EhGES0TkTCgACLSActC6gj2uR/Esg7kA/NEZJqqLo057FSgr/0agx1PVcvYycBMVZ0iIpPtz78GFgO5qlpu/wB8LSJvqWq5U9fkBKrKrBXb+Mt7K1i8sYjeHZrz4CUjOHVw5wZb/YdETKxhHSgoLOW+d1fw6pf5tMjM4NcTBnDlUTlJl2KqCyHTWckLmHAnB4kohFy0Jx/epSV/uWAYt0zoz5OfreXZueuYvqiAoVmtuGR0NmcO60rzFHmt/EBxaXnKXPPV0aZ5Y24+sS/XHtOLlxds4F+z13DzCwtpf1hjLhzVnUvG9KCbiSNNOcnc9anA60BHEbkbOA+4zUFZRgN5qroaQEReACYCsYroROBptbSiuSLS2lYic2oYOxE41h7/FDAL+LWqxjYVboKtYKcLqsrHK7czdeZKFqzbRfe2TfnL+cM4a3i3Bq9jZ7Lmk2PP/nIe+2gVj32ymkgEfnR0L64/tneDZmpGja3Gkp3WmHAnB4lEtHIB5iadWjbh1xMGcONxfXj1y3yenbueya8t4q7/LeOs4V25ZHQPBlbTTz3IFJeWudZWtWnjMJcfacX4zs7bzjNz1/HwrFU8PGsVxw/oxA/GZnN03w6mhmyKSFgRVdVnRWQBcAKWK/ssVV3moCzdgA0xn/M5NHs03jHdahnbSVU3A6jqZhHpGD1IRMYATwA9gMvSwRoaiSjvL9vCAx/m8U1+IV1bNeGuswZzQW5318qEmBjRxCiviPDygnz+8u63bN+znzOHdeWWU/rXuxRTXTCdlTxBysOdgkSFalopCs0zM7j8yBwuG9uDBet28dzn63lpfj7/mbueI7q35qJR3TljWNeUxfZ7CVVlz/5y1/8tQiHhmH4dOKZfB/J3lfD8F+t54YsNvL9sC11bNeG8kVmcn9vdlTndzyR01+3YzCxVXQ4sT5Es8WaQqr+i1R2TyNhDD1D9HBgkIocDT4nI26paeohgItcC1wJkZ2fXdto6sbvkAC/Pz+c/n69j3Y4Surdtyp/OGcK5I9yvUxcbb9hQ4QBeQtXqYPWn6ctZuXUPI3u04Z+Xj2S4i7Fh0Vg5EyOa1qQ03CloVEQaPkY0EUSE3Jy25Oa05bdnDuTVLzfywheWlfTOt5Zy+tAuXDiqe6ATZUoOVBDRunVVShVZbZrxq1MGcPMJ/Xh/2RZenLeBf3yYx9QP8jiqdzsuHNWdUwZ1NmW7HCChu66qKiJvACNTKEs+0D3mcxawKcFjGtcwdouIdLGtoV2ArVW/WFWXicheYDAwP87+x7ATm3Jzcx39ZV+8sZCn56zlzYWb2F8eIbdHG35+Uj9OH9IlbTp3hGKsa6G4On8wicbvPvzRKr5Ys5Ocds145AcjOGVQZ9d/UEyMqCdIdbhToFDF9eeuNlo3a8w143ty9bgcFm7YzUvzN/DW15t5ZUE+vdo35/zc7pw7ohsdU1yGKt3YX26tv9JRqWucEeK0IV04bUgXNu3ex6sL8nlpwQZufmEhLZtkMPGIblw4qjuDu7VyW1TPkszyY66IjFLVeSmSZR7QV0R6AhuBi4BLqhwzDbjRjgEdAxTaCua2GsZOA64Apth/3wSwj91gJyv1APpjZdWnnLKKCO8u2cKTn61h3tpdNG0U5pwRWVw2Nj1jh8IxXXrSZ73qHrtLDjDt6008O3c9K7YU06VVE+44cyCXjOnhuvU6SjRpw8T2pie2l+ljIJXhToGiIqKkydq9VkSE4dltGJ7dhtvPGMj0RQW8NH8D97yznPveXcGJh3fkbxceQbPGwZhxoyFE6e5w69q6KT85oS83HNeHuat38NL8Dbw0fwPPzF3HwC4t+fP5QxnU1SikyZLM//LjgB+LyDpgL9bEqao61AlBbIXwRmAGVgmmJ1R1iYhMsvc/AkzHKt2Uh1W+6aqaxtqnngK8JCLXAOuB8+3t44HJIlKG5Q67XlW3O3Et1bFjz35emLeB/8xdx+bCUrLbNuO20w/n/NzutGqavkWQo0aGIIcblpZVMHvldt78ehMzlhRwoDzCoK4t+esFwzhjaNe0UUCjmM5K6U3Uy6SqI0lduFOgSLcY0URp1jiD80Zmcd7ILNZs38s/PljJa19uZNXWvQzJCoZSE1VE092iHSUUEo7q056j+rTnzpIy3vx6I799cwkzl201imgdSEYRXYxVPimKAPc6KYyqTsdSNmO3PRLzXoEbEh1rb9+BZXGouv0Z4Jl6ipwQywuK+Ncna3jz600cKI8wvk97/jBxMMcN6OiJiTMc0MSXsooIM5YU8N+vN/PRt9vYV1ZBq6aNuGR0NueNzEprV0zY9Jr3Aqn2MgWKdMmarw892zfnjKFdeO3LjYF6dqOX6sX716pZIy4b24PfvrnEeKDqSDKKaB9VXRe7QUQGOCyPryjcV8ZvXl/Ef7/ZTNNGYS7IzeKKI3Po67F2YqHKdpHBesju+u9Snpqzjk4tMzl3ZDdOHtiZsb3apZ31Mx4HOyu5K4ehRlLqZQoaEfW+IgoQtuNqgjTfesU1Xx0iYleXCc49c5JaFVERuQ64HuglIt/E7GoBfJoqwfzAv2av4X+LNnPjcX340dG9PNuDuDJrPkDPWCSi/G/RZiYM6sxDl47wXLWAkMma9wKn1n6IIVGsGFFvPafxCAdw4R/xsEU0SjgklAfonjlJIqad54AzsZJ+zox5jVTVH6RQNk+jqrzx1UaO6t2OX57S37NKKMRY1wL0kC3ZVMT2PQc4ZXDqW6imglBAwyk8xvWqui72hbXodxQRmSAiK0Qkz+4uV3W/iMhUe/83IjKitrEi0lZE3hORlfbfNvb2diLyoYjsEZEHqnzPSBFZZJ9rqjgcEBhRbysyUSrDagI030Z/W7x8+8IhCdRvpJPUqoiqaqGqrlXVi6tMmjsbQkCvsmrbXtbvLOH0IV3dFqXehEPBU2q+WGv99x7Xu73LktSNIP6YeZCT4mxz1Eoa0/74VGAgcLGIDIzzndHWydditU6ubWy0dXJfYKb9GaAUuB34ZRxxHrbPH/2uCQ5cYiUR9U7WfE0E8dn1coxolLAYi2hdSfixFZHzRaSF/f42EXktduVs+C77DlQA0KFFpsuS1J+o4SJIwfOlZdb9a5nG1QxqwlQ6SF9E5DoRWQQMsC2Q0ddaYJHDX1fZOllVDwDR9sexVLZOVtW5QLR1ck1jJ2K1TMb+exaAqu5V1dlYCmnsNXcBWqrqHDvp9OnoGKeo8EGyEgQz0bAyRtTDC4lwyLTCrivJ3PbbVbVYRMYDp2BNPg+nRizvE51EfLFCrywF5LIgDUjUxeLVmLMg/ph5iGi405t8N9xphKpe6vB3VdcWOZFjahr7ndbJQEdqpps9viY56kVE/dH57aBFNDhNtg4mK3n3/hlFtO4koyZV2H9PBx5W1TexOhoZ4hCdRMJeXuLZROf2ID1kXg+eNzGi6Us03Al4Ddhpx4ZeBjwuIsMd/roGb51cDzmsA0WuFZH5IjJ/27ZtCX9Burb4TJaMSkXUZUEakOh865U6ovEIh0Jm4V9HktGSNorIo8AFwHQRyUxyfKCITiJ+mBhDAYwRrfB4ORGTNe8J4nmZHqllTLLUp3VyTWO32O72qNv9kNbJcb4jqxY5AKulsqrmqmpuhw4dajntQSKKLyyiB8vlBUcTVY/Pt2B5PysqzHxbF5JRJC/A6lw0QVV3A22BX6VCKD9QXmkR9fCTZXNQqXFZkAZEVRHx7grd1BH1BA3hZapsnSwijbHaH0+rcsw04HI7e34sduvkWsZGWydDTOvk6rDPVywiY+1s+ctrG5MM0QWXD6ZbMsLBtYh61QMFkGEsonUm4YL2qlqC5UqKft4MbE6FUH4gqrT5QRGNxrkGySIaUW+7+YKYeetBol6mE4F7UuFlcqF1MnbSVUugsYicBZysqkuB64AngabA2/bLESpj8j38zEaJKmPlAVr5e72gPViJVma+rRvJdFYyJIGfkpVCAcyar4h4e3UuJkbUC1yAVcLoPlXdbbu4HfcyNWTrZHtfTjXb5wODE5U7GaIKgB9c8xkBDIXyWq/5eGSEQkYRrSNGEU0R/kpWimbNB+chU1XPlxKBYFU68BrGy+QcfqhDGSX67JYHKN7QD/cvJMYiWlc8/FOb3vgqWUmCF7Pk9ZqElZUOjCZqCAB+8kAFsYGIH1zzxiJadxLpNV9M/DIbguXVaem4VD4gahH1slUtSjBjRL29iDDlmwxBotI17+FnNkqlRTRASo0fkpVCptd8nalVEVXVFg0hiN+IWg8zfKCJVnZWCtBDFrGz5r2KKd9kCBJeb0ARS6VFNEDP7sEYUZcFqQcZITEL/zqSlJYkIm1EZLSIHBN9OSmMiEwQkRUikicik+PsFxGZau//JrbFaHVjRaStiLwnIivtv23s7SeJyAIRWWT/Pd7Ja/GVqyiInZVUPf2jdtC957IghkMQkWIRKYrzKhaRIrfl8yJ+6MwTJSwBtIj6YCFhLKJ1J5le8z8EPsYq5XGn/fcOpwQRkTDwIHAqMBC4WEQGVjnsVKCv/boWu8VoLWMnAzNVtS8w0/4MsB04U1WHYNXBe8apawGfJSvZlxCkeEPfxIiaiTHtUNUWqtoyzquFCXWqG5UNKDysyEQJh4PogbL+ennOzQhJoKzYTpKMlnQzMApYp6rHAcOBxPuv1c5oIE9VV6vqAeAFYGKVYyYCT6vFXKC1XfKkprETsTqWYP89C0BVv1LVaGePJUATu46fI/gxWSlIbgevd2kREUSCVenAi6TayxQUIj6ab8MBDYUCb7vmwyKBqv3qJMmUbypV1VLrB04yVXW5iPR3UJZuwIaYz/nAmASO6VbL2E52WRRUdbOIdIzz3ecCX6nq/niCici1WBZYsrOzE7qYyk4f3jeIBjLeMBJRT2dwgnXfgmTF9hq2l+lmrHaXC4GxwBzA0TChIOCrUKhoM4oAPbt+CK0IhyRQiwcnSeaxzReR1sAbwHsi8ibV9AquI/H+B1a9q9Udk8jY+F8qMgi4B/hxdcfUpfdxNFbED8lKQYw39HpnJbBW6EG6Zx4k1V6mwBBdJHu5IHqUaEH7IPUt90Md0YywsYjWlWRafJ5tv71DRD4EWgHvOChLPtA95nMWhyq61R3TuIaxW0Ski20N7QJsjR4kIlnA68DlqrrKkauwORiz5ORZ3UECGG9Yoer5HzWRYFmxPUiqvUyBIWpR8/riEYJuEXVZkHpgeaDclsKb1ElNUtWPVHWaHY/pFPOAviLSU0QaAxcB06ocMw243M6eHwsU2m73msZOw0pGwv77JoBt3f0fcKuqfurgdQBQYQeJ+sIiGsjOSt7O4ARL/iDF9XqQVHuZAkOFD7Kuo4hI4Lr0RC/Vy4v/jJBUJikbkiORgvazVXV8nML2jha0V9VyEbkRKxs/DDyhqktEZJK9/xGsnsenAXlACXBVTWPtU08BXhKRa4D1wPn29huBPsDtInK7ve1kVa20mNaH6MrIDyv0UABX6BV+iRE182La0gBepsBQmXXt9YfWJhywUkC+sIiGJFBtWZ0kkYL24+23D6vqLbH7ROReJ4VR1elYymbstkdi3itwQ6Jj7e07gBPibL8LuKueIleLL5OVAvSMRVQ9/6MWkmBVOvAyqvqR2zJ4GT8oMrGEA1YKSH2QrGQK2tedZNSkE+Nsm+CUIH7DT8lK0ck9SBNjRL1dRxSsFbqZGNMPEZlt/61a2N4UtK8jla55jz+zUaxSQMF5dqMebS/Puaagfd1JxDV/HXA90FtEvonZ1QL4LFWCeZ2Ij5KVDmbNB+chi0S8b12xsuaDc8+8QtTLZNonO0dlr3mvP7Q2QSsF5Ic6oqagfd1JRE16DjgTK8nnzJjXSFW9NIWyeZoKX1lEg1lg2curc7AC/02MaPoiIvckss1QO+qjmHwIoiJq/fXynBs0K7aT1KolqWqhqq5V1YtVdV3Ma2dDCOhVov8h/bBAD2yMqIcnRbCKewep0oEHOSnOtlMbXAof4KdyeWC1hg5Scqj64P4FLa7XSRKuI2q3vzwXyIkdp6q/d14s7xPtzOPlchRRopNDkNy8ER+Ub7Ky5oNzz7xCTLhTLxPu5AyVrnkfzLdgLSKDVNDeFxZREyNaZ5Jp8fkmUAgsAOK2wjQcpDyivnDLw0F3V5AUUb+UbzLzYlryHPA28Cdgcsz2YuNpqhuVBe29/tDaZATMIuqHqgembnPdSUYRzVJVkyWfIFb5H7elcAYJaoyol2dFLEu2mRjTD1UtBApF5CrgHGK8TCJivEx1IOKzrPlQKHjzLXjbg2gsonUnGVXpMxEZkjJJfEZFxPu9yqNErQxB0ml8ESNqsubTnTeAiUA5sDfmZUiSCh8oMrFkhEKBUkT90Gs+aAlmTpKMRXQ8cJWIrMZyzUc7Kw1NiWQepyKivnETRS8jSA9ZJOJ964qJEU17GsTLJCITgL9jdZ17XFWnVNkv9v7TsDrWXamqX9Y0VkTaAi9iWXPXAheo6i57363ANUAFcJOqzrC3zwK6APvsr3ask120DqWf5twgPbu+cM2b+bbOJKOImmzOJPCXIhrAGFFVT9e0A6umYoBumRf5TESGqOqiVH2BiISBB7Ey9POBeSIyTVWXxhx2KtDXfo0BHgbG1DJ2MjBTVaeIyGT7869FZCBwETAI6Aq8LyL9VLXC/q5LVXW+09dZURkj6vSZ3SFoFlFfJCuFjSJaV5J5bNcDRwNXqOo6rL7znVIilQ+oUCXskyDRUAAL2qt6fyERNKuKBxkPfCkiK0TkGxFZVCWL3glGA3mqulpVDwAvYIUDxDIReFot5gKtRaRLLWMnAk/Z758CzorZ/oKq7lfVNUCefZ6U4ocYw1iC1qXnYAMY794/YxGtO8lYRB8CIsDxwO+BYuBVYFQK5PI8FRXqm9V5OIB1RCsiSmaGdydFiGbNB+imeY+G8DJ1AzbEfM7HsnrWdky3WsZ2UtXNAKq6WUQ6xpxrbpxzRfm3iFRg/XbcpQ4VuvVbslLQ+parD1zzGSEJVKUDJ0lGVRqjqjcApQB2PFDjlEjlAyrUP8lKgYwRVW+vzsEooh6gIbxM8f4TV/1PUd0xiYxN5vsuVdUhWNd8NHBZ3BOIXCsi80Vk/rZt22r5OovKXvMef2ajBM8iav31sms+GgplitonTzKKaJkdM6QAItIBy0JqiENFRAmHvftQxRKqzJoPzgNmZc27LUX9sOrauS2FoQYeAo4ELrY/F2PFZDpJPtA95nMWsCnBY2oau8V232P/jSYdVTtGVTfaf4uxaqnGddmr6mOqmququR06dEjgEmOTXTz+0NoErW+5X3rNA8YqWgeSUUSnAq8DnUTkbmA28EcnhRGRCXa8VJ4dAF91v4jIVHv/NyIyoraxItJWRN4TkZX23zb29nYi8qGI7BGRB5y8DvBX+aag9pr3+v0zMaJpT0N4meYBfUWkp4g0xkokmlblmGnA5fb8OhYotN3uNY2dBlxhv78Cq+FJdPtFIpIpIj2xEqC+EJEMEWkPICKNgDOAxU5dZKVFzUfhUOWR4Nh5okq3lxcSUYONmXOTJ+EYUVV9VkQWACfYm85S1WVOCdLQ2Z1Yk//twGD75SgVPkh2iRLMGFHvJz6EAhZn5kFS7mVS1XIRuRGYgVWC6QlVXSIik+z9jwDTsUo35WGVb7qqprH2qacAL4nINVghBufbY5aIyEvAUqz6qDeoaoWINAdm2EpoGHgf+KdT11nhsxjRoNWk9INrPsMoonUmmV7zP6+y6VQROQpYoKoLHZClMkPT/r5ohmasIlqZ3QnMFZFodmdODWMnAsfa458CZgG/VtW9wGwR6eOA7IdgJSt596GKRQLYa97KmndbivphYkTTnqiXqaPtZToPuM3pL1HV6VjKZuy2R2LeK3BDomPt7Ts4aJSouu9u4O4q2/YCI5OVPVH8kHUdSzgk7C+vqP1An+CHOqJRJTpIsb1OkUzWfK79esv+fDqW62aSiLysqvfWU5aGzu5MKRU+6MwTJbi95r19/8IiBMi75zmqeJkEh71MQaKy17zHn9ko4ZBQEZzpttIi6mUvVNQiGqTYXqdIRhFtB4xQ1T0AIvI74BXgGGABUF9FtKGzOxNGRK4FrgXIzs5OaExFRMnwS7JSZYyoy4I0IH7oNS9iAufTHVVdDix3Ww6vE52bvL54jGK55oMz4fqhfFPUA2ososmTjCKaDRyI+VwG9FDVfSKy3wFZ6pPd2biGsVtEpIttDY3N7kwYVX0MeAwgNzc3of9lvkpWCqRr3vs/auGQUBak1YPHiBPuBFCIc+FOgaEy2cXj4TRRLEXUbSkaDj9UPYg2sAnS76RTJPPYPocVl/k72xr6KfC8HYS+tOahCdHQ2Z0pxQ8WtSiVLT4DtNKz6sC6LUX9ML3m055cYBIHw4uuxYpn/6eI3OKiXJ7jYItPjz+0NlaXnuBoon5IVormFBiLaPIkkzX/BxGZjtWWToBJMT2DL62vIA2d3QkgImuBlkBjETkLOLlKln6dKa/QypgRrxPErPmID2J8Q6aOaLqT6nCnwOC7GNGA9S33Qx3RSotogO6bUyTjmkdVF2BNkCnBhezOnHqIWyN+SlaKXkaQ4g0jEe9n4IbEuInSnFSHOwWG6I+/l5NdYgla33I1FtFAk0z5pkzgXKxSSZXjVPX3zovlfSIRJbORPwKWRISQmM5KXiNsyjelO9FwpzexvExn4my4U2DwW4vPoPUtP1jQ3mVB6kHUIhqkBYRTJGMRfRM7kB4wq/VaKI8oTT28uqtK0OINKyLerwMrEqyEB69RJdwJ4MdOhjsFiWipI7+45kMhoSJA9Zt8ESMawA6ETpGMIpqlqhNSJonPiPiosxIEL94wot5384VDwbJiew3by9QfaI41F58mIqcZL1PyVJb/8YcTKngWUV/EiBpFtK4k89h+JiJDUiaJz/BTshIEL97QH73mg2XF9iBvYnV+Kwf2xrwMSVJR6dr19jMbJRSwFp+qioi3F/9GEa07yVhExwNXisgaLNe8YOUPDU2JZB7HD1nXsVhdeoLzgPkhRtT0mk97jJfJIfxWvikjYIpoxAd1myt7zZs5N2mSUURPTZkUPsRPnZXAtq4F6AGriKinV+cQ7TXvthSGGvhMRIao6iK3BfE6Eb9ZREUClX3tCw9UpUXUBOYnSzJ1RNeJSBugL9AkZtc6x6XyAX7oVR5LKCQESA9F1fvWlXDAwik8iPEyOcTBZBd35XCKjFDQPFDejg+FGIuo0UOTJpnyTT8EbsZqn7kQGAvMAY5PiWQep8JvyUoSrNgXayHhthT1w8SIpj3Gy+QQfivfFA4FyyKqPghli8pfbiyiSZNMstLNwChgnaoeBwwHtqVEKh/gh/I/sYQDFm/ohxatQbNiew1VXQcUAZ2AHjEvQ5JEfJDsEksg51uP37poKJ7RQ5MnmRjRUlUtFRFEJFNVl4tI/5RJ5nEqIt6PeYlFAlYc3Q/JZkGzYnsN42VyDr/Nt0GziPohWclYROtOMhbRfBFpDbwBvGd3A9mUCqH8gO8soiKBWulF1PvFsYNmVfEgxsvkEH5QZGLJCIVQhfKABBxGLdpeppFtES0LUCMCp0gmWels++0dIvIh0Ap4OyVS+QC/KaIZYWF/eYXbYjQYfogRzQiF2F8ejB8yj2K8TA5hhdK4LYVzdG6VCcDmwlK6t23msjSpRxXPh0J1bmnlcG8u3OeyJN4j4UdXRO6JvlfVj1R1GnBXSqTyAX5LVurWuin5u4LxgB3s0uLt+9etTVMK95VRVFrmtiiG+Bgvk0P4zTWf3bY5AOt2lLgsScPgh1CoDi0yadIoFJh75iTJrCFPirPNZH1Wg98sojntmrN2RzCavvih7zFATjvLkrJuu5kY0xFVPVtVd6vqHcDtwL+wOi0ZksQPyYWxZEef3Z3BmHP94IESEbLbNjOKaB2oVREVketEZBHQX0S+iXmtAb5xUhgRmSAiK0QkT0Qmx9kvIjLV3v+NiIyobayItBWR90Rkpf23Tcy+W+3jV4jIKU5ei99W6Dntm7N9zwGKA2Bd80spmJz2llVlTUAWEF7DeJmcI+Kzus2dWzahcTjE+p3BUGqsOqLev3/ZbZuzISD3zEkSsYg+B5wJTLP/Rl8jVfUHTgkiImHgQSwr60DgYhEZWOWwU7EK6vcFrgUeTmDsZGCmqvYFZtqfsfdfBAwCJgAP2edxBP9ZRO0VegBWe9EEH6/Piz1s997a7UYRTVMaxMuULgt8ERkpIovsfVPFQc3Db6FQ4ZCQ1bYp6wMw30K0jqjbUtSfHu2asX5nSWV4lyExalVEVbVQVdeq6sWqui7mtdNhWUYDeaq6WlUPAC9wqJtqIvC0WswFWotIl1rGTgSest8/BZwVs/0FVd2vqmuAPPs8jhDx2cQYta6tDoBSE1VEvW7Rbto4TOeWTVgTgHvmJRrYy5ROC/yH7fNHv2uCU9dZEfF+KE1Vcto1Z9HGQsoCkDnvhxhRsAw2+8oqWF5Q7LYoniKZOqKpphuwIeZzPjAmgWO61TK2k6puBlDVzSLSMeZcc+OcyxHKfWYR7dm+OW2bN2bK9GXMXb2DFpkZVkNCm/6dWnDOiCz3BHQQv8SIAozMacNbX28iJELb5o2+E0d3WOMMfnRML5o0cswRYEiM57AqjvwJW4GzKU7lAh9ARKKL9KUxx1Qu8IG5IhJd4OfUMHYicKw9/ilgFvBrYhb4wBoRyQNGi8haoKWqzrHP9TSWUcCRyiuqSthHWfMAl47J5pqn5vOzFxcyplc7mjUKV3ppMjPCnHB4R988u34pv3XakC7c9+63/OzFhVw4qjuHZWZU6gEicGSv9nRu1aSWswSPdFJE4/0vrGrfru6YRMbW5fusA0WuxVrJk52dXctprUmxUThEIx/NjE0ahXnyqlHc9sZiZiwuYM/+8sp95RElIyS+UUSjMaJ+SH740zlDKCuP8Nmq7ewqOVDZaSmiSlmFMjKnDUf1bu+ukAFDVQuBQuDiBvi6dFngl9nvq24/hGTnW4gmu3j/eY3lhMM7ce0xvXjys7X895vNh+x/8JIRnD60iwuSOY8f6ogCtDssk3vOHcptbyzmzreWHrL/vJFZ3Hf+MBckS2+S6TUvwKVAL1X9vYhkA51V9QuHZMkHusd8zuLQUibVHdO4hrFbRKSLPVl2AbYm8X0AqOpjwGMAubm5tQZ/iAjf3uW/ggJDs1oz7cbxh2y/b8YKHv5olQsSpYbK8k0+mBhbNmnEY5fnHrJ9wbqdnPvwHMpN8WW/ky4L/ITPlex8C/DrUwdw0wH/1Tn+v9MO5xcn96NwXxn77OvbtLuUi/85l5ID5bWM9g7qE4sowITBnTlpYCcK95Wxd395ZajX5U98UXkPDd8lGZPdQ8CRHFzFF2PFDznFPKCviPQUkcZYcUbTqhwzDbjcDq4fCxTaq/Kaxk4DrrDfXwG8GbP9IhHJFJGeWDFLTinVgcJvrST9kjVfE9E8kQoTVO936rPAr2nsFnthT4IL/Hz7fU1y1Jn2h2X6tvB7ZkaYji2a0KNdc3q0a15Z2slPXdP80Gs+lnBIaNu8Md3bNqu8b00ywr76nXSSZBTRMap6A1AKoKq7sCyRjqCq5cCNwAxgGfCSqi4RkUkiMsk+bDqwGiux6J/A9TWNtcdMAU4SkZVYWapT7DFLgJew4p3eAW5QVbNcqQNRF7ZfMgWjc4UfyolURzQRyy/3zFAtabHAt89XLCJjbe/a5TFjDEmQEYr2NPfPs+uXGNGaCIXEV/fMSZKJES2zsx8VQEQ6AI6m86nqdCxlM3bbIzHvFbgh0bH29h3ACdWMuRu4ux4iGzg4gVRElIyw9ycTv2TN18TBe+ayIAGmAcKdUNVyEYku0sPAE9EFvr3/Eax58zSsBX4JcFVNY+1TTwFeEpFrgPXA+faYJSISXeCX890F/nXAk0BTrCQl0yK6DkSf3YiPlBq/xIjWREZIfGXFdpJkFNGpwOtARxG5GzgPuC0lUhk8RdSF7Zd5MeKjGNHqiPblNhOjqzyEtZg/Hvg9VrjTq8AoJ78kXRb4qjofGJyM7IZD8aNFVH1SvqkmjEW0ehJWRFX1WRFZgDX5CHCWqi5LmWQGzxCdP/yi1Pgpa746/GhV8SBjVHWEiHwFVriT7QI3GKolOi/5Kd4wEvF3TD7YFlEf3TMnSSZr/mfAy6rqZIKSwQdEXdh+UUSjl+HnFbrfrNgeJeXhTgb/keFHRVTV1zH5YP1OlkfM4x2PZJKVWgIzROQTEblBRDqlSiiDt4iNEfUDB7PmXRYkhUSNDyZr3lWi4U6d7HCn2cAf3RXJkO5EF5F+enatZCW3pUgt4ZBg9ND4JOOavxO4U0SGAhcCH4lIvqqemDLpDJ4g5DPr2sEYUf/OjCGTNZ8OdAT+DAzFhDsZEqRSEfVRDeAgxIiGQ8L+clOYJx51sflsBQqAHVgTqSHgRFeyfol/8VOLz+rwmxXbo7QEHsEqi6SA0+09DT4k7MMawH6rIxqPcEjw0drBURJWREXkOhGZBcwE2gM/UtWhqRLM4B0Oxhv64ykLgkXUxIi6j6reqaqDsDLWu2J5md53WSxDmhMKCeKzJiIR9XfdZrAVUeObj0sy5Zt6AD9V1YUpksXgUfzWpScI5ZvEZ1Zsj2O8TIakCIv4TBENiEXU6KFxSSZGdHIqBTF4l4NdelwWxCGCUL7Jb1ZsLyIi12HF23cAXsHyMi11VyqDF7CUGv88u37qNV8d1uLBaKLxqFURFZHZqjpeRIqxy4xEd2HVQm6ZMukMnqAyA9snE2MQyjeFfGbF9ijGy2SoE35TRCNBSFYK++ueOUmtiqiqjrf/tki9OAYvEvKZdS0Y5ZtMjKjbGC+Toa6EfdalJwgtPv0WTuEkySQr3ZPINkPwONilx2VBHCKqUPs5eN5vlQ68hIjMtv8Wi0hRzKtYRIrcls+Q/oR91rc8EgDXfEZIjAeqGpKx+ZwUZ9upTgli8C5hn/Utj15H2McTo4kRdY9YL5Oqtox5tTChToZEyPCZRVRVCfnYAwWW59BPtV+dpNZbb5dtWgT0F5FvYl5rgEWpF9GQ7vgt3jAIdUTF1BF1HeNlMtSVkPirb3lFxP8xosYiWj2JrEGeA84Eptl/o6+RqnppCmUzeAS/dek5mDXvsiApJGoR9ckt8yrGy2SoE36ziAahjmjIZwlmTlLrT62qFqrqWlW9GCgCOmFlew4WkWOcEEJE2orIeyKy0v7bpprjJojIChHJE5HJiYwXkVvt41eIyCkx2+8WkQ0isseJawgyB7v0uCyIQwShoL3pNe8etXiZvnFbPkP6Ewr5yyKqAagjmmEU0WpJJlnph8DHwAzgTvvvHQ7JMRmYqap9sTo3HZJNKiJh4EEsi8FA4GIRGVjTeHv/RcAgYALwkH0egLeA0Q7JH2h8FyNqK9RhH8+MB7Pm/XHPwFOJVzV5mX7gpmAGb+BHi6ifF/5gXZ+f7pmTJON8vBkYBaxT1eOA4cA2h+SYCDxlv38KOCvOMaOBPFVdraoHgBfscTWNnwi8oKr7VXUNkGefB1Wdq6qbHZI/0Pgt3rDM1kR9rIfGVDrwxz2riCgn/u0jHv9ktdui1Eqsl0lV18W8TK95Q0KEfBZvGITOShk+s2I7STKKaKmqlgKISKaqLgf6OyRHp6hSaP+N1+auG7Ah5nO+va2m8TWNMTiE3zorfbpyO43CQq/2h7ktSsrwW6/5uat3sHrbXjq3auK2KLVSTfmmYlO+yZAoGT7LwA5CjKjfar86STK95vNFpDXwBvCeiOwCNiU6WETeBzrH2fWbRE8RZ1ttd7UuYw49ici1wLUA2dnZyQ73PdGkHj+s0MsrIryxcBPHD+hIm+aN3RYnZfitG9arX+bTokkGJx7eyW1RasU0CTHUl5D4yyIahBhRv9V+dZJkes2fbb+9Q0Q+BFoB7yQx/sTq9onIFhHpoqqbRaQLsDXOYflA95jPWRxUhKsbX9OYhFHVx4DHAHJzc83/pCr4Kd5w/rpdbN+zn4lH+NtwLiKI+KPSQVlFhPeWbmHCoM40aRSufUCaICLnA++oarGI3AaMAP6gql+5LJohzcnwWbvIiKqvY/LBWERrIplkpZ9HX8BIoA9wmYgc4YAc04Ar7PdXAG/GOWYe0FdEeopIY6wkpGm1jJ8GXCQimSLSE+gLfOGAvIYY/BRvOHPZFhqHQxzTr4PboqQcv1hV5q3ZSXFpOScNTH9raBVut5XQ8cApWPHtjzh1cpeqkYwUkUX2vqli+1tF5EoR2SYiC+3XD526ziDit3aRQXHNq/rjd9JpkokRzQUmYcVYdsNyVR8L/FNEbqmnHFOAk0RkJVZtvSkAItJVRKYDqGo5cCNWtv4y4CVVXVLTeHv/S8BSLOvtDapaYZ/7XhHJB5qJSL6I3FHPawgsfoo3fH/ZVsb2bsdhmclErXiTsIgv7tl7y7bQOCPE+L7t3RYlWSrsv6cDD6vqm4CT8SBuVCN5GOu3oa/9mhDzdS+q6hH263EHrzNwhH1WCshKVvK5Iuqzxi9OksyvbTtghKruARCR3wGvAMcAC4B76yqEqu4AToizfRNwWszn6cD0RMfb++4G7o6z/Ragvgq0ARCfxBuu2raHNdv3ctW4HLdFaRBEvL86V1XeX7aF8X3a06yx5xYPG0XkUeBE4B4RySQ540BtTMQyFoBlbZ0F/LrKMZXVSABEJFqNZGkN4yurkQBrRCQPGC0ia4GWqjrHPtfTWBVM3nbwmgz4TxFV9XeVEoBw+GB1GQ9FEDUIyUx62cCBmM9lQA9V3Qfsd1Qqg6cI+6Sz0vtLtwBwggcSXpzAD8HzK7fuYcPOfZxweLxCG2nPBVgengmquhtoC/zKwfM3dDWSbvb7eOcCONcu3P+KiMTG7huSxG+KaKAsoj66b06RjAnhOWCuiETjL88EnheR5lirZ0NACYX84XKYtWIbAzq3oFvrpm6L0iCERDzfDevD5VZe4gkDvLd4UNUSEVkFnGLHWX6iqu8mc440q0ZS07neAp5X1f0iMgnLwnp83JObKiW1Eg4JZV5/eGOIqOJzPbQyhM3rv5OpIGGLqKr+AfgRsBsoBCap6u9Vda/pOR9sDmbNuyxIPThQHuHL9bs4snc7t0VpMELi/UoHX6zZSa/2zT1RP7QqInIz8CyWpbEj8B8R+Uky51DVE1V1cJzXm9jVROzvqnM1kjjjqxuTb78/5FyqusN25QP8EyvhtbprekxVc1U1t0MH/ycN1oVwKOSrDOxIxP+dlSoVUR/Vf3WKZLLmBTgcaKWq9wNbRcS0yDRUxvZ4Od5w0cZC9pdHGJ3T1m1RGoyQx13zkYgyf90uRnn3nl0DjFHV36rqb4GxWIt9p2jQaiS2+75YRMbavxeXR8dEFVqb72MlnBrqSNgH8d2xBKGOaIbPLKIfrtjK03PWOhJqkEyM6EPAkcDF9udirGxLQ8A5mDXv3Qds3lqru2Kud5WapLGy5r17z1Zu3UPhvjJG9fTsPRMOZs5jv3fy57jBq5EA1wGPY7VTXsXBRKWbRGSJiHwN3ARc6eB1Bg4/WUQPlEfYVVLGYZmN3BYlpVSGsPnkvj33+Xoe/2SNI/Vfk4kRHaOqI0TkKwBV3WWvoA0BJ+SDIOx5tou3Q4tMt0VpMMTjMaJf2IuHUTlxy2N6gX8Dn4vI6/bns4B/OXVyl6qRzAcGx9l+K3BrEuIbaiAc8o9F9Ov83ewrq2BML88uKBMiw0eKaHlFhLmrd3DG0C61H5wAySiiZXatOAUQkQ6Ah3/GDE7h9RjRqIt3wqB4OR/+JRzydqWDeWt20rFFJtltm7ktSp1Q1b+KyCxgPJYl9CrTVcmQCBmhEOURf/z8fpq3nZDA2J7+js/3g8EmypJNRRSXlnNkb2dqNyejiE4FXgc6isjdwHnAbY5IYfA00V7zXnXzfru12Osu3joR8nh3lvlrdzKqZ1tPd2RR1S+BL92Ww+AtrPhut6Vwhs9X72Rg15a0auZv13xG2D+K6NzVOwAY65AVO5le88+KyAIsV40AZ6mqCTg3VNZH86oi+tX63QDk9vCsi7dOhDzcWamgsJRNhaX8yMP3TESaANdjWUQVmI3VYanUVcEMaU9GSHxhEa2IKF/n7+b8kVm1H+xxohZRP8T2frV+N9ltm9GxhTPVSpJqRaKqy4HljnyzwTeIx10OyzYXcVhmhmddvHUlFPLu4mHZ5iIABnVt5bIk9eJprKTPf9ifLwaeAc53TSKDJwiJ4AM9lG+3FFNyoILh2d5dUCZKhu069OqcG8vCDbsZ7aAHMWFF1G4/dy6QEztOVX/vmDQGTxLNmvPq87VscxEDOreozGoMCl7Oml9qK6IDurRwWZJ60V9Vh8V8/tDOKjcYasQvFtGFG3YDcET31q7K0RCE7RC2co/XEd1cuI+ColKGZ7d27JzJlG96E6vHcDmwN+ZlCDhR/c2LFlFVZfnmYg7v0tJtURocL8eILi8oplvrprRs4um4sq9EZGz0g4iMAT51UR6DRwiFvF3xIspX63fRplkjerTzvzcq7BOL6EI7lM1JK3YyrvksVZ3g2DcbfEPIwzGi+bv2Uby/3OuWtToRComnrdg+WDyMAS4XkfX252xgmYgsAlRVh7onmiGdyQgJFT6wiH61fjdHdG/t6YTDRKm0iHp08R/lqw27aRwOcbiDv5nJKKKficgQVV3k2LcbfEHIwwXto7GGPlBqkiYk3rRil5ZVsHrbHk4b7PlyW2Zhb6gT4ZB3vRlRikrLyNu2hzOHdXVblAYhahH1+n1buH43g7q1JDMj7Ng5k3HNjwcWiMgKEflGRBaJyDdOCCEibUXkPRFZaf+Na/MVkQn29+eJyORExovIrfbxK0TkFHtbMxH5n4gst7t9THHiOoJK2MN1RJcXFCMC/TsF0CLq0RjRlVv2EFEY4PHFg6quq+nltnyG9MUPiug3GwpRxdFYw3Qm7PGkXrAK2X+zcbfjMb3JKKKnYvUUPhk4EzjD/usEk4GZqtoXmGl//g52Mf0HbTkGAheLyMCaxtv7LwIGYVkfHrLPA3Cfqg4AhgPjRORUh64lcHg5RnTZ5iJ6tG1G88ykCkj4Aq8qokG2YhsMYCuiHnx2Y4k+x4O9XfkiYaL1tr34Oxll7Y69lJZFHL9nCSuiKV61TwSest8/hdXqriqjgTxVXa2qB4AX7HE1jZ8IvKCq+1V1DVb/49GqWqKqH9rXdQCroLT/C5mliFBl1rz3HjCfxBrWibBHi2Iv3VxE00ZhegSs3JbBEMUPFtHlBcV0bJFJm+bB6BSe4QPX/IqCPQD07+ysBzFdzECdVHUzgKpuFpGOcY7pBmyI+ZyPFexf0/huwNwqY7rFnlREWmNZdv9e34sIKl5tXVZaVsG6nSWcNbxb7Qf7EK/GiK7cWky/Tod5ttyWiPy8pv2q+teGksXgTcIerngR5dstxY4rNOlMNFnJy5bsFQVFhAT6dDzM0fM2mCIqIu8D8bILfpPoKeJsq+2O1jhGRDKA54Gpqrq62pOIXAtcC5CdnV27pAHDqzGi63aUoAo92zd3WxRXsNoEeuymAWu27WVML0/3pY7++vYHRgHT7M9nAh+7IpHBU0S9GarqyYzzioiycmsxl47p4bYoDcbBZCXvVjtYsaWYnPbNadLIuUQlSEARdWr1rqon1vAdW0Ski23N7AJsjXNYPtA95nMWsMl+X934msYAPAasVNX7a5H9MftYcnNzvffLnWLEo73m12y3yuD2au/s6s4reDFGtLSsgk2FpZ5ePKjqnQAi8i4wQlWL7c93AC+7KJrBI0SbiFREtLKHuZfYsLOE0rJIoJJEDyYruSxIPfh2yx4GpMCKnUiMaAv7lQtch+Xa7gZMwkoacoJpwBX2+yuwiudXZR7QV0R6ikhjrCSkabWMnwZcJCKZItITK9nqCwARuQtoBfzUoWsILF7tNb92h6WI5rQPZqxh2INtAg/eM+8qojFkAwdiPh/A6lxnMNRIVBH1ak3K5QXFAPQLlGs+qoh6bNK1KS2rYO2OvfRLweKhVotoA63epwAvicg1wHrsXssi0hV4XFVPU9VyEbkRmAGEgSdUdUlN41V1iYi8BCzF6gh1g6pWiEgWVkjAcuBL27XxgKo+7tD1BIqQR1d6a7btpf1hjWnh7e48dUbEe/FKa20rds92vlBEnwG+EJHXsUKGzsbqP28w1EjYw7WbwYoPBejXKTjeqIOKqMuC1JGVW/ag6nyiEiQXI5qy1buq7gBOiLN9E3BazOfpwPREx9v77gburrItn/jxo4Y6EPKqa37HXnL8odDUiXBIOFDurVlxzfYSwB9WbFW9W0TeBo62N12lql+5KZPBG2R43CK6Yksx2W2b0axxuuRLp56DVmxvzblRVtiLB7cVUbN6N8SlssWnxybF/J0ljO3t6aSXeuHFGNH1O0to29wfVmyxXDEDgVaq+nsRyRaR0ar6hduyGdIbr865Ub4tKE6Jized8YMVu3FGKCVl85KpI3o3cBWwC9iNtXr/o+MSGTxHZRC2hx6wsooIBUWlZLVu6rYorhEKCRXeuWUAbNy9j27+uWcPAUcCF9ufi7GadhgMNRJNUPKiRbS8IsKa7XvpGyC3PMRYsb026dqs3FJMr/bNyQgn0wcpMRI+Y5XV+9+BHSIy2nGJDJ4jWj3ES3NiQWEpEYVubXyj1CRNSLzXhGDjrhKy/HPPxqjqDUApgKruAoJR3dtQL7xsEd20u5TyiPolzjthQh63iK7bWZKyULZkVFuzejfERUQIibcmxfxd+wDo1tr7sYZ1xWtFsVXVbxbRMrvlsAKISAfAmwFkhgbFyzGi63dacd7dA9YZzcv3LBJR8nfuo0e71NyzZBRRs3o3VIvX4g037rYVUf9Y15JGxFstPnfuPUBpWcRP92wq8DrQUUTuBmYDjoU7iUhbEXlPRFbaf9tUc9wEEVkhInkiMjmR8SJyq338ChE5JWb73SKyQUT2VPmOTBF50R7zuYjkOHWdQSQUU0fUa6zbaVW+SJVSk6542YpdUFTKgYpIyhYPySiiZvVuqBYr3tA7D9hG2yLatXUTlyVxj3DIW5PiQSu2PxRRVX0WuAX4E7AZOEtVnSxoPxmYqap9gZn25+9gz+kPAqdihV5dLCIDaxpv778IGARMAB6yzwPwFhAvZOsaYJeq9gH+BtzjyBUGlAwPK6Lrd5bQOByiU8tgzb1etohGrdjpYBFN6erd4G2seEO3pUicjbtL6NAik8wMZ1uVeQmvWbE3+dCKrarLVfVBVX1AVZc5fPqJwFP2+6eAs+IcMxrIU9XVqnoAeMEeV9P4icALqrpfVdcAefZ5UNW5qrq5FlleAU4QL/amTBMqa1J66PmNsn6HFecdvYag4GUr9vodliKanSKLaMLlm1T1WRFZgFWvU7BW705PnAaP4rV4w4Ki/XRpFawVeVW8ZsUuKCoFoEsrfyii1bRPLgQWqOpCB76iU1QptNsfd4xzTDdgQ8znfGBMLeO7AXOrjOlWiyyV32M3JykE2gHbk7geg03Yy0rNzhKyA+aWB+9bscMhoWuKvFFJVZNV1eVY3YgMhu/gNevalsLSQE6GsYREPGXFLigqpXE4RJtm3q8hapNrv96yP5+O1cp4koi8rKr31nYCEXkf6Bxn128SlCGeWaq2/xUpHSMi1wLXAmRnZ9dy2mDS3C4EX1xa5rIkyaGqrN9RwsgeccOVfU1mRohwSCguLXdblKRZt7OErq2b0CgFpZsgCUW0AVbvBg8TComn4g23FJcyqmfwJsNYwuKt1fnWov10bJmJjzy67bDaJu8BEJHfYbmtjwEWALUqoqp6YnX7RGSLiHSxrZldgK1xDssHusd8zgI22e+rG1/TmOqIjskXkQygFbCzmmt6DHgMIDc31zv/QRuQaAmz/F37GNnDZWGSYHdJGcX7y1Pm4k1nMsIhurRqQv6uErdFSZr1O0vo0TZ15baSUW9zgUlYLpZuWCvWY4F/isgtzotm8BLhkHcysEvLKthdUkbngAXLVyUU8pYVu6Cw1G/3rGrb5DKgh6ruA/Y7cP5pwBX2+yuAN+McMw/oKyI9RaQxVhLStFrGTwMusjPhewJ9gdq6QcWe6zzgA/VaEds0IquNpcht2OktpWbdztTGGqY73ds0Y4OddOkl1u/Ym9JyW8kootHV+y9U9RdYimkHrNX7lSmQzeAhQuKdwPmtRdZvfEd/KTVJExLvWbF9lmn7HDBXRH5nW0M/BZ4XkebAUgfOPwU4SURWAifZnxGRriIyHax4TeBGYAawDHhJVZfUNN7e/5It4zvADapaYZ/7XhHJB5qJSL6I3GGf619AOxHJA35OnAx+Q+I0bRymQ4vMymxmr3Aw+zpYxeyjdG/b1HP3rKi0jF0lZSktt5VMjGi1q3cRcWL1bvAwVryhN5SaLcVW0ovPlJqkCXusjuiWwlK+16+D22I4hqr+wVYIx2PFUE5S1fn27ksdOP8OrOTSqts3AafFfJ4OTE90vL3vbuDuONtvwSpJVXV7KXB+EuIbaqF7m6Zs2Okt69r6HVYN0e5t/ZFwmCzd2zRjW/F+SssqaNLIGxVbUp0xD8kpotHVe9Q9cybOrt4NHibkoaz5aBkgn7l5kyYU8o4Vu7i0jL0HKvx4z1YDYaAJlhXxGFX92GWZDB6ge9tmLFi3y20xkmLDzn20PyyTZo2TypP2DVH3dv6uEvp0bOGyNIkRjWlNC0U01at3g7fxQoxo/q4Snv18PQ/PWoUIdA56+SYPWLH37i/njYUbeeSjVQApKx/iBiLyQ+BmrGSfhcBYYA5wvItiGTxCz/bNeevrTZ5qe7u5qDTQZfN6trdCEuat3eUZRXRzoeVBTOXvZbK5+KuxJsovsVfvTgjhUiu6d0TkaxFZIiKPxHQGMdQBSdNe86rKp3nbufbp+Rxz74c8+tEqTh7YiaeuGk2rpr4pA1Qn0tmKvWb7Xn7/1lLG/mkmv3l9MS2bNOIPZw3mlEHxKhV5lpuBUcA6VT0OGA5sc1ckg1c4P7c74ZBw7zvL0/Y5rsqWQt/FeSfF0KxWDOnWiodm5bFz74HaB6QBBUWlNAoLbZulrqN7MuWbUrl6j7aSm2IrmJOBX1f5/mgrupOwSoHME5Fpqrq0uvFVWtF1Bd4XkX52YP0Fqlpkd/d4BSt+6QUHriWQhNMsA3vP/nJe+zKfp+esI2/rHto2b8yk7/Xm0rE9PGM9SDXpZsWuiCizVmzlqTnr+PjbbWSEhNOGdOGKo3IYkd3aT2WbopSqaqmIICKZqrpcRPq7LZTBG3Rr3ZQfH9ObBz7MY+mmIq44KodzRnRLa7d3QVGwy+aJCLeeNoArn5jH8X+ZxcWjs/lBmv8mbSkspWOLJpWdoVJBMv9jo6v3uap6nIgMAO50SI6JWKWgwGoDN4sqiigxregARCTaim5pDeMrW9EBa+yMzdHAHFUtso/PABpTe0FmQw2ERKhIg3/BvK17eGbOWl79ciN79pczNKsVfzl/GKcP7eKZ4PCGIl2s2LtLDvDy/HyembuO9TtL6Ngik5+d2I+LR3f3e2WDfBFpDbwBvCciu6i9HqfBUMkvT+nPgC4teHjWKm57YzH3vLOc80ZmcdnYHvTqcJjb4n2H0rIKCveZsnlH9W7PGzeM4+8zv+XRj1bx6EerOGlgJy4bm8O4Pu3SbsG9pWh/ysPYklFEU7l6d6UVnYjMwFJM38ayihrqSEhwzSJaEVFmLtvC03PWMTtvO43DIc4Y2oXLj8rhiO6tXZHJC4Rd7oa1ZFMhz8xZxxsLN1JaFmF0TltumdCfUwZ1TlkHj3TB9sTcpKq7gTtE5EOsIu/vuCqYwXOcMbQrpw/pwoJ1u3hqzjr+M3cd//50LUf3bc9lY3tw/ICOZKTB87SlyFQriTKwa0sevSyX/F0l/Gfuel6ct54ZS7bQq0NzLhvbg3NGZKVN6NiWolIO79Iypd+RjCJar9V7OraiU9VTRKQJ8CxWiMF7cU9iWs7Vihs1KXeXHOCFeRt4Zs46Nu7eR+eWTfjlyf24aHQ27Q/LbFBZvIgbvebLKiK8s7iAp+esZd7aXTRpFOLs4d24bGwOA7umdrJLJ1RVReQNYKT9+SN3JTJ4GREhN6ctuTlt2Vp8OC9+sYHnvljPtc8soGurJlw6tgcXjuru6rxY0ABJL14jq00zJp86gJ+e2Jfpizbz9Jx13PnWUu59ZwVnDe/G5Uf2SLkSWBOqSkFRKcf2j2cbdI6EFFEnVu/p2orOtvJOw3Ljx1VETcu52mnIGNFV2/bwxOw1vPplPqVlEcb2asttpx/OSQM7pcXK3yuEGrCOaGFJGc/PW89Tn61lc2Ep2W2bcdvph3P+yO608k/v+GSZKyKjVHWe24IY/EPHFk34yQl9ue7Y3ry/bCvPzF3Ln2es4O8zV3LWEV25enxPBnRueOWmwLaIBt01H48mjcKcMyKLc0ZksSi/kGfmruW1L/N5/ov1HNmrHdeM78nxAzqmNE4zHsX7yyk5UEGnlqldwCSkiDbA6j3a/m0KCbSiAzZiJSFdUsv4acBzIvJXrGSlvsAXInIY0MJWXDOwijt/4vA1BQoRoSKSuvOrKp+t2sG/Zq/hg+VbaRwOMdGeVN1cMXqZUAPEiK7dvpd/f7qGlxfkU3KggiN7teMPEwe7MqmmIccBk0RkLbAXy4OjqjrUVakMviAjHGLC4M5MGNyZvK17ePKzNbyyIJ+X5uczro+l3Bzbr+Gew6hr3udx3/VmSFYr7j1vGP932uG8MG8DT322lh8+PZ+cds24alxPzhuZRfPMhklI29JAVuxkriaVq/cpwEsicg2wHrsDh4h0BR5X1dNUtVxEoq3owsATVVrRHTJeVZeISLQVXTl2Kzq7CP80Ecm0z/UB8EgKriswhEOkpCZlJKLMWFLA1A/yWLa5iHbNG3PzCX35wdgedGhh3O/1IZVW7KWbipg6cyUzlhaQERK+P6wbV4/PYVDXVin5Po9yqtsCGIJBn46HcddZQ/jlyf15/gtLubn6yfn0bN+cq8blcO6I1Cs3BYX7adooTMsm6ZvVn060bmZVerlmfE/eWVzAv2av4XfTlnDfuyu4eHQ2lx/Zg6w2qSsyDwet2KmO603mf0TKVu8N3YpOVbdgVQAwOISVNe+cUqOqvLO4gL/PXMnygmJ6tW/OvecO5ftHdDXZ7w4htmteVR3L1Fy2uYi/v7+Sd5YU0KJJBjcc24fLj+pBxxbGChKH9VjNQHqp6u9FJBsrjn6du2IZ/ErrZo257tje/PDonrxtKze/fXMJ982wlJsrjspJWdOILUWldG7VJO2ywtOdRuEQZw7rypnDuvLl+l08MXsN/7JfEwZ15urxOYzIbpOSf9fKuN40UkTN6t1QLU7GG67etof/e30Rc1fvpFf75tx/4RGcOawrYePKdZSwPXGpWqWc6sOe/eXcN2MFT81Zy2GZGdx8Ql+uHt8zbTI/05SHgAhWouTvgWLgVcwi2ZBiGoVDfH9YV84c2oUv1+/midlr+Ocnq3l89hpOHdyZq8f3ZES2s/U+C4pKUx5r6HdGZLdhxCVt2Lh7H0/PWcvzn6/nf4s2M6x7a64el8NpQ7o4WnFka/F+IL1c82b1bqgWJ+IN95dX8Mis1Tz4YR5NGoX449lDuHBUd6OApojoP2uFKqG4BSYS490lBfxu2hIKikq5bGwPfnFS/yAnICXDGFUdISJfAajqLhFJXfsSg6EKIsLIHm0Y2aMN+btKeHrOOp7/Yj3//WYzI3u04Rcn9eOoPu0d+a4tRaXk9ghuMXsn6da6Kbeeejg3Hd+X177M54lP13LzCwuZ8vZyrj+uDxfmdqdxRv0V0oLCUlo1bZRyL2QyiqhZvRuqpb7xhvPW7uTW1xaRt3UPZw7ryu1nHG7cuSkmmqRQ1/tWUFjK76YtZsaSLfTv1IIHLx3huBXF55TZHeMUQEQ6YM2xBkODk9WmGf932uHcfEJfXp6/gUc/Xs0lj3/O2F5t+cXJ/RmV07bO51ZVthbtp5Mp3eQozTMzuOzIHC4d04NZ327lwQ9Xcfsbi3n0o1XcdEJfzhnerV6VZAqKShukykEyiqhZvRuqRerYt7ywpIwp7yzj+S820K11U/591SiOS3HNMoNFyPbHR5JUfSoiyrOfr+Ped1ZQVhHhlgn9+dHRvXxfhD4FTAVeBzqKyN3AecBt7opkCDrNMzO4clxPLhqdzfNfrOfBD1dx/iNzOKZfB35xUj+G1aFJyM69BzhQETGlm1JEKCQcP6ATx/XvyEffbuOv733LLa98w8OzVnHzCX3rHNq2pai0QRYPySiiZvVuqJZwkoqoqvLfbzZz51tL2VVygGuP6cVPT+yb1n2S/UZUb0zGIrpscxG3vraIhRt2c3Tf9tx11mB6tGueIgn9jao+KyILsBItBThLVZe5LJbBAFi1La8a15OLRmXzzNy1PDxrFRMf/JRTBnXi1xMGJNVC1NQQbRhEhGP7d+R7/Trw/rKt/OXdFfz0xYU8PGsVk08bwLH9OiSV1FRQWMqAzi1SKLFFMr/6ZvVuqJZQCA4k2Gx+a3Ep//faYt5ftoWhWa146upRpqyPC0QtoolUOyiriPDAB3k8+GEeLZs24m8XDuOsI7qZDNh6ICI/A15W1QfdlsVgqI6mjcNce0xvLhnTgydmr+HRj1Yxc9nHXDomm5tO6Eu7BLo1Vbb3NK75BkFEOGlgJ04Y0JHpizdz34wVXPXveYzr045bTz2cwd1q/70tr4iwfc/+BmnJmrAialbvhpoIJdC3XFV565vN/PbNxew7UMFtpx/OVeN6mmQkl4gqolqLX2N5QRG/eOlrlmwq4qwjuvK7MwfRprmJynGAlsAMEdkJvAC8YpeWMxjSjsMyM7jphL5cPDqb+9//lv98vp7XvtzIpGOtWpc1JbQUFFrZ16bPfMMSCglnDO3KyQM78+zn65g6cyVnPjCbs4d345cn96+xVNe2PfuJaMPcs4QVUbN6N9REo3CI0rLqNZode/Zz2xuLeXtxAcOzW3Pf+cPonYRrx+A8jcKWIlpaXkErDs1yL6+I8OjHq7n//W9p2aQRj/xgJBMGd25oMX2Lqt4J3CkiQ4ELgY9EJL+mdsgGg9t0aJHJ3WcP4apxPZny9nL+PGMF/5m7jl+e3J+zh3eL26mpoKgUEehompC4QuOMEFeN68k5I7J4eNYqnvh0Df/7ZjNXj+/J9cf2pkWTQ+f/hqohCpBMdkF09f6JiNwgIp1SJZTBe2S3bcb6HXvjdld6Z/FmTv7bx8xctpXJpw7glUlHGSU0Deje1urKsXb73kP25W0t5txH5vDnGSs4eWBn3v3ZMUYJTR1bgQJgB2Ay9QyeoE/Hw3j8ilxeuHYsHVtk8ouXv+bcRz5j8cbCQ47dWlRKu+aZJqHRZVo1bcTkUwfwwS++x2lDuvDwrFUc/5ePeOOrjYf8dm8papgaopCEIqqqd6rqIOAGrL7tH4nI+ymTzOApenc8jL0HKiqD0gF2lxzgpue/YtJ/vqRr66b896bxTPpeb+OKTxP6dLQWA3nb9lRuq4goj328itOmzmbdjr384+LhPHjpiITiwAzJISLXicgsYCbQHviR6TNv8Bpje7Xj9evHcd/5w9iws4QzH5jNbW8sYnfJgcpjCopK6dzKzCHpQlabZvztwiN484ZxdG3VhJ++uJALH5vL8oKiymO2NFB7T0jOIhrFrN4Nh9C7g5U5nbfVUmpmLtvCSX/7mOmLNvPzk/rx2vVH0a9T6rPvDInTtVVTmjYKs2qrZRFds30vFz46hz9OX873+nXg3Z8dw5nDurospa/pAfxUVQep6u9UdamTJxeRtiLynoistP/GLfIqIhNEZIWI5InI5ETGi8it9vErROSUmO13i8gGEdlT5TuuFJFtIrLQfv3QyWs1uEsoJJw3MouZvziWK47M4bnP13PcfbN44Yv1RCJKQWHD1KM0JMew7q15/fpxTDlnCCu3FHP61Nnc+dYSikrLKCgqpVFYaNcA+QDJxIhehxXH1AF4BWv17ujEafAuUevagnW7eOOrTbz6ZT4DOrfgyatMRny6EgoJvTo0Z8WWIv796RrueWc5jcMhkxHfQKjqZBFpIyKjgSYx2z926CsmAzNVdYqtYE4Gfh17gF2S70HgJCAfmCci0+y5Pe54ERkIXAQMwvKOvS8i/VS1AngLeABYGUeeF1X1RoeuzZCGtGraiDu+P4gLR3Xnd28uYfJri3hh3gbyd+1jpOmqlJaEQsJFo7OZMLgz9727gic/W8tbX2+m/WGN6diiSdyYX6dJpnxTdPW+MEWyGDxMh8Myad2sEfe/v5JwSPjJ8X34yfF9HWkzZkgd/Tq14PWvNvJp3g6O7d+BKecMbZCYIAPYVsGbgSxgITAWmIPVvc4JJgLH2u+fAmZRRREFRgN5qrralukFe9zSGsZPBF5Q1f3AGhHJs88zR1Xn2udx6BIMXuTwLi158cdjeWPhRu767zL27C83FtE0p3Wzxtx11hAuGpXNb15fxNf5hYzIbt0g351M+aZUr94NHkZEePjSkXyychsTBndmaFZrt0UyJMDPT+pH97bN6N2hOd8f1tUoEA3LzVgtkueq6nEiMgC408Hzd1LVzQCqullE4oVSdQM2xHzOB8bUMr4bMLfKmG4JyHOuiBwDfAv8TFU31DbA4F1EhLOHZ3Fc/44898V6zh6eyH8Rg9sM7taK164fx6tf5pPVpvryTk6SjGs+Zat3EWkLvAjkAGuBC1R1V5zjJgB/B8LA46o6pbbxInIrcA1QAdykqjOqnHMa0EtVB9f3OoLOkb3bcWTvdm6LYUiC7m2b8fOT+rktRlApVdVSEUFEMlV1uYj0T+YEdsJovHIGv0n0FHG21dbhoC5j3gKeV9X9IjIJy8Ia97dDRK4FrgXIzs6u5bSGdKd1s8Zcf2wft8UwJEE4JFyQ273Bvi8Zv2l09b5OVY8DhgPbHJIjGovUFyuDdHLVA2JimU4FBgIX27FK1Y6vEss0AXjIPk/0nOcA3wmqNxgMhgYiX0RaA28A74nIm8CmZE6gqieq6uA4rzeBLSLSBcD+uzWeDEDsL05WjAzVja9pTHVy7rBd+QD/BEbWcOxjqpqrqrkdOnSo6bQGg8EHJKOIlqpqKVC5egeSWr3XwESsFTL237PiHFMZy6SqB7A6kUysZXxlLJOqrgGisUyIyGHAz4G7HLoGg8FgSBhVPVtVd6vqHcDtwL+IP/fVlWnAFfb7K4A34xwzD+grIj1FpDHWwn1aLeOnAReJSKaI9AT6Al/UJEhUobX5PmC68hkMBiA5RbTeq/ca+E4sEvHLQsWLZYoGnVQ3vqYxfwD+ApQ4cQEGg8FQD1ao6jR7ke0UU4CTRGQlVlZ8NJSpq4hMB1DVcuBGYAaWcviSqi6paby9/yWshKZ3gBvsjHlE5F4RyQeaiUi+iNxhn+smEVkiIl8DNwFXOnidBoPBwySTrHS2/fYOEfkQaIU1CSVEOsUyicgRQB9V/ZmI5NT6xSZmyWAwpJbpwAgnT6iqO4AT4mzfBJwW83m6/f0Jjbf33Q3cHWf7LcAtcbbfCtyahPgGgyEgJFO+KZYVqlqQzICa+ieLyBYR6WJnZtY5linO+OrGHAmMFJG1WP8GHUVklqoeW43sjwGPAeTm5tam/BoMBkOymHIFBoMhkNS1yOMhq+d60qCxTKr6sKp2VdUcYDzwbXVKqMFgMDiJiMRLR/2nve/oBhbHYDAYXKWuiqjTq/cGj2UyGAwGl/hIRG4RkViP1Ksi8h/gr24JZTAYDG4gqjV7mkWke9XCwyJyvao+JCJHq+onKZUwzRCRbcC6BA9vD2xPoTgNgbmG9MBcg/P0UNUGrw9k92yfAhyFVRZvCFYFj3uBh1U10tAypStmvvUk5hrSg3S7hmrn20QU0dXAI8BfbaskItIJK+O8v6qOclhY3yAi81U112056oO5hvTAXIP/EJGbgb9hxa2PVdV8l0XyNH74/2WuIT0w19CwJOKaHwn0Br4SkePtyfMLrK5KY2ocaTAYDIbvICKtReRR4CqsRhuvAG+LiFM95g0Gg8Ez1Jo1b7fK/LGtgL6PWb0bDAZDffgSeAgrZr0ceNcuKfeQiKxT1Ytdlc5gMBgakFotomb1Xi8ec1sABzDXkB6Ya/APx6jqfdFQJwBVXaiqRwEfuCiX1/HD/y9zDemBuYYGJNEY0YeA+2NiRI+wt5nVu8FgMBgMBoOhTiSiiGZV54YXkR+p6j9TIpnBYDAYDAaDwdfU6pqvKRbUKKHxEZEJIrJCRPJEZLLb8tQFEXlCRLaKyGK3ZakLItJdRD4UkWV2j+ub3ZYpWUSkiYh8ISJf29dwp9sy1RURCYvIVyLyX7dlMfgPr8+5Xp9vwcy56YTX5tu6FrQ3VIOIhIEHgVOBgcDFIjLQXanqxJNYMcFepRz4haoeDowFbvDgfdgPHK+qw4AjgAkiMtZdkerMzViNKAwGR/HJnPsk3p5vwcy56YSn5lujiDrPaCBPVVer6gHgBWCiyzIljap+DOx0W466oqqbVfVL+30x1kPZzV2pkkMt9tgfG9mvmmNp0hARyQJOBx53WxaDL/H8nOv1+RbMnJsueHG+NYqo83QDYjtR5eOxh9FviEgOMBz43GVRksZ2sSwEtgLvqarnrgG4H7gFMB2DDKnAzLlphplzXeV+PDbfGkXUeSTONk+tqPyEiBwGvAr8VFWL3JYnWVS1QlWPALKA0SIy2GWRkkJEzgC2quoCt2Ux+BYz56YRZs51D6/Ot0YRdZ58oHvM5yysJgCGBkZEGmFNiM+q6mtuy1MfVHU3MAvvxZGNA74vImuxXKbHi8h/3BXJ4DPMnJsmmDnXdTw53xpF1HnmAX1FpKeINAYuAqa5LFPgEBEB/gUsU9W/ui1PXRCRDiLS2n7fFDgRWO6qUEmiqreqapaq5mA9Cx+o6g9cFsvgL8ycmwaYOdd9vDrfGkXUYeyi/zcCM7CCtV9S1SXuSpU8IvI8MAfoLyL5InKN2zIlyTjgMqwV4UL7dZrbQiVJF+BDEfkG68f2PVX1RDkOg6Gh8MOc64P5Fsyca6gjtRa0NxgMBoPBYDAYUoGxiBoMBoPBYDAYXMEoogaDwWAwGAwGVzCKqMFgMBgMBoPBFYwiajAYDAaDwWBwBaOIGgwGg8FgMBhcwSiiBoPBYDAYDAZXMIqowdOISLuYmnUFIrLRfr9HRB5Kwfc9KSJrRGRSzOfz4hzXOyqH0zIYDAaDW5g51+A0GW4LYDDUB1XdARwBICJ3AHtU9b4Uf+2vVPWVWuRaBRxhJkWDweAnzJxrcBpjETX4EhE5VkT+a7+/Q0SeEpF3RWStiJwjIveKyCIRecfuj4yIjBSRj0RkgYjMEJEuCX7dMSLymYisjrdSNxgMBr9j5lxDXTGKqCEo9AZOByYC/wE+VNUhwD7gdHti/AdwnqqOBJ4A7k7w3F2A8cAZwBSnBTcYDAYPYuZcQ0IY17whKLytqmUisggIA+/Y2xcBOUB/YDDwnohgH7M5wXO/oaoRYKmIdHJUaoPBYPAmZs41JIRRRA1BYT+AqkZEpExV1d4ewXoOBFiiqkfW9dw2Uj8xDQaDwReYOdeQEMY1bzBYrAA6iMiRACLSSEQGuSyTwWAw+BUz5xoAo4gaDACo6gHgPOAeEfkaWAgc5apQBoPB4FPMnGuIIget5QaDoTZE5Engv7WVEok5fo+qHpZaqQwGg8GfmDnX/xiLqMGQHIXAH6LFlasjWlwZ2NIgUhkMBoM/MXOuzzEWUYPBYDAYDAaDKxiLqMFgMBgMBoPBFYwiajAYDAaDwWBwBaOIGgwGg8FgMBhcwSiiBoPBYDAYDAZXMIqowWAwGAwGg8EV/h9m/699qo12KAAAAABJRU5ErkJggg==\n", + "image/png": 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\n", 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\n", 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\n", 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" ] @@ -264,7 +263,7 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": 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KWiP4/3FfXPviy97fv/yxPAkHUsbmTtv/ryS5cjb+Obmvk3/+7HJpT/iAkOuhYd/fQVZ4PPd+9nk/7t67f97sv5+9wd+LP4AUzmmHNSm+iqikikDHcHdROIq+sKYBHSS1AVYTdHo/P885E4DrJI0leEOwJSwM1xeQdwIwHLg7/Bwfk/6cpHuBpgQd6D8zs72Stkk6AvgUuBh4qAh+3z4ntT6Jez+/l/8s+E9ORbRiVajbNtjyYwY7t4UV1TW5Kq1s/Qa2roZFb8H2PN3H0jKgZrOwYtoSarWIqbC2gFrNIb1CvrdV9lNdmX2Oc67kMrO3Unj5MlGmDj10KP9e8G9eWvIyV3e/OijbOp2Rc8K2b2HtbFgzK9xmwvxXc47XaAqNukCDQ6BhJ2hwKNTvCJVr7jslu9UgvRAP9a70sTwPC7kfHoI0izmW9+EiKyvv+WW3YlutUtG8y0x4FUn9CfonrSBocmkhaXjYKf6gmdkeSdcBbwPpwFNmNk/S1eHxR4E3CVZ2WgL8AFxaUN7w0ncDz0u6HPgaGBzmmSfpeWA+QYP4iJg3DtcQjDatQjBN1cTC/La8KqRVYFCHQfxz1j9Zu30tjas1Ti6jFBSMlWsGBWZ+dv8IW1bB5q9g80rY/DVsCT+XTg4qr7HPm0oLKqr12kHddlCvfc73Oq0KrKQ650ouSWMIpn6qL2kV8DugApStMrVVzVYc2eRIXvzyRa447Aoy0vL8U1ajEdQ4CTqclJP24yZYOwfWhBXUdQtg+VTYG7Nadc1mQVnb4NDwsxPU7wBVC//Wx5UO/iKm+CWz1vznBM1Ei8L9jsAYM+tVDPGVWAe6LvLKbSs59eVTGdlzJFccdkUKI4tjzy7YuiqomGZXVDetgA1LYONS2LEl51ylB5XReu2hXofgrUGjLkHBXCHZGWScK90U4Vrz5dWBlqmTvprEjVNu5IHjH+CElicc3E2z9gZl4fpFsH5hzPYl7Pkx57zKtWMe3LM/2wafVWof3L2dK0cKKlOTea9aIbsSCmBmX0ryV2YHqEWNFvRs2JPxS8ZzedfLi3ewR0bF/LsBmMEPG3MqpRuW5nxf/kFOYaz0oHKa3deqal1yD6tUzue+tBj79vMej3d+onMOdv9gr58nLaNK8MalWsPgz9a5IibpTKBfuPu+mb0WZTwl0XEtjqNh1YY8v+j5g6+IpqUHFct67eDQU3PSs7Jgy9ewbmHusvHrj2HOC+RqYapaL3cFtU4rqN0q6C5QvRGkJbVujHPlVjIV0emSngT+Fe5fQLC6kjtAZ7Y7kzs/vpO5383lsAaHRR1OQIJq9YKtZZ7Zs7L2wsbl8O3cYFs7B1Z8CHOejybWkqhqPajeOBg8VqNx8A9PjcbBgLHaLYJBZFXr7l8xdy4fkv5MMK/nf8KkGyQdZWa/jjCsEicjLYNzO5zLI7MeYeXWlbSo2SJxpmSlpUGd1sGW1+4dsGl5UDHNrqBuXAbL3odZY3Kfm14pp39+duW0dsvgurVbQrUGXja4ci+ZpvlKwAjgGILXQlOBh8NJj8utA21GgmBi++OfP56z25/N7UfcnqLIisH274JBVABY7DDMnLSD2S+Ka+w3HL6w18s1FjT42DfjwbcxMx+she+/DbasPOs9VKgWVkpb5MxssG+mgxbBm1V/a1KiRNk0L2k20CN7yqZwtaIvzKxbFPEUl4MpU9f9sI4BLw5g6KFDuaXPLSmK7ADs/jHs/vRVuH0Nm8LPzV/BDxtyn59RJXxz2hAq1Qj672fL1dJEzPd4LVHJHqeQ+Qs6XohrVmsAjQ8LuoFVqlHQn7ArpQrbNH+1md0L3BtzwZHAA0UUX7lRo2INjmt+HG+veJtf9fkVFdJKaQ+HavWDze0vKwt+3BjMaLB5ZThoLPyHactKWD09GDQRK71SMJNBdiV131RcLaFum+Atq781KW9qk7NCUq0I4yjRGlZtyEmtT+LVJa9y3eHXUa1CtWgDqlAFGnQMtnh2fh+UA7GV081fwfYNQTmxb7rY7Af82Adiy/2gnPA4B5EnyWsedP44x/Oq0xoadYXG3aBx1+B77ZZeBpZhyVREh7N/pfOSOGkuCae3PZ3/fvVfPv7mY/o175c4gytd0tJyKupNusc/Z+e2mErq1znblpXxp+PKqJLTTFi3Tfg9+7MVZFRK7W9yxe3PwBeSJhO8SuoH3BZtSCXXhZ0uZOLyiby65FUu6HRB1OEUrFL1YLqohiV/YYViYxY8uK+dC9/OCT7XzoGFb7CvolqpVvC2tPFhOZXThp2Cir8r9fKtiEoaRjCPXBtJE2IO1QA2xM/lEjmm2THUqlSL15e97hXR8qpSDWjUOdji2de893XQF23TiqCv7qYVsPz9PIscKFjYILtiWrd18L1eu2BexIoRvyFyB8zMxkiaAvQmqIjeYmZro42q5OrWoBvd6ndjzMIxDDt0GGnybi6lihS0CNVqDoecnJO+azt8Oz+ncvrtXPji37B7e5gvLZjZZV/l9LBgqq1aLbyrUylT0BvR/wFrgPrA32PStwGzUxlUWVYhvQIDWg3gtWWv8cPuH6haoWrUIbmSpqDmPTPYvj6nYhpbUV3ybtBndR8FTVrZcyJmv1Go39Hnii3BJE0ysxMJJozPm+biuKDTBdzywS18uPpDf8AvKypWgxa9gy1bVlZQ5n07N6dyuvIzmPtizjkZlcPpB9sHFdP6HXO+e//TEinfiqiZfQV8BRxZfOGUD6e1PY3nv3yeSV9P4ox2ZyTO4Fw2KRjYUL3h/rMcQDCQatMK2LA4mBtx3YLgc9lk2Bs7vlAFDCwoo+q2gxGfRB1FviRVBqoSTEZfh5wJx2oSrFzk8nFS65P4+/S/M3r+aK+IlmVpaTnTbXUemJP+42ZYNx+++xK+WxxMubV2NiyYENPvlmA2k+xK6b5WpPDTK6mRiXKt+XKrR8MeNK3WlDeWveEVUVe0KlaN3+y/d09YOM8JPm1vcgMHypKq9aKOIJGfATcSVDo/J6ciuhV4OKKYSoUKaRW4oPMF3Pf5fcz9bi5d63eNOiRXnKrUhlZHBVusPTuD1qINi4MK6neLg+9zX4Ydm3OfW7X+/n3ws/erN/bm/hTyimgE0pTGaW1P48m5T/Ldj99Rv4qPQHcplp4BDQ8NNlcimdkDwAOSrjezIl2bvTw4r+N5PDHnCZ6Y8wT3H39/1OG4kiCjUv7l3o+b9+/etGk5rPwU5r6U+01qesWgL37N5lCrWbAUbK1mufer1CnbLUop5BXRiJzW9jQen/M4by1/iws7Xxh1OM65EsIroQenesXqnH/o+Tw2+zGWbl5Ku9rtog7JlWRVakOVHtC0x/7H9uwKp9laHlRQt6yELauD0f1ffQzbvtl/vujyqMvZMPiZQl8mYUVUUgeC6UQ6A/sWGzezOOtFumS1q92OTnU78cayN7wi6pxzReCCThcwev5onpzzJH869k9Rh+NKq4yKOX1R48naC9+vgy2rYOuqoJK6b5GXcqSIWtiSeSP6NPA74D7geOBSYlbtdgfvtLancc/0e1ixZQWta7WOOhznnCvV6lSuw7kdz+W5Bc9xTY9raFGjCJf9dC5bWjrUbBJs9E54uitYMr1vq5jZJILlQL8yszuBE1IbVvlwSptTEOKN5W9EHYpzrgSRVEdSH0n9sreoYyothnceTrrSeWLOE1GH4pxLQjIV0R2S0oDFkq6TdDbQMMVxlQsNqzakT5M+vLHsDczK+Ihl51xSJF0BTAXeBn4fft4ZZUylSaNqjTi347lMWDKBldtWRh2Ocy6BZCqiNxLMbXcD0Au4kGDZT1cETm97Oiu3rWT2d75GgHMOgJEE7X1fmdnxwOHA+mhDKl0uP+xy0pTG47MfjzoU51wCCSuiZjbNzL4HNpnZpWY2yMwKNSu0pLqS3pG0OPysk895J0taJGmJpFuTyS/p1+H5iyQNiEnvJWlOeOxBKZhnQdLNkuZLmi1pkqRWhfltB+onLX9ClYwqjF04tjhv65wruXaY2Q4ASZXMbCFwSMQxlSoNqzZk8CGDmbDU34o6V9IlrIhKOlLSfGBBuN9d0iOFvO+twCQz6wBMCvfz3jedYBLnUwhG7A+T1Lmg/OHxoUAX4GTgkfA6AP8ErgI6hFv2orZfAJlm1g14EfhrIX/bAalesTqDOw5m4vKJXmA65wBWSaoNvAq8I2k88E2kEZVCl3W9jIy0DEbNHhV1KM65AiTTNH8/MADYAGBms4DCdpwfCDwbfn8WOCvOOX2AJWa2zMx2AWPDfAXlHwiMNbOdZrYcWAL0kdQEqGlmH1vQGXN0dh4zm2xmP4T5PwGaF/K3HbDhXYaTpjSemftMcd/aOVfCmNnZZrY5HBj6G+BJ4peRrgANqzZkcMfBvLb0NVZu9Yd850qqpNasMrO8/xfvLeR9G5nZmvDaa4g/+KkZEHvfVWFaQfnzy9Ms/B7vWrEuBybmF7SkqyRNlzR9/fqi67LVsGpDzmp/Fq8seYU1368psus650onScdIutTM3gc+Jn555RLIfiv62OzHog7FOZePZCqiKyUdBZikipJ+QdhMXxBJ70qaG2cbmChv9iXipCUaWp5fnoTXknQhkAn8Lb+Lm9koM8s0s8wGDRokCOXAXHnYlQjx0Be+qIpz5Zmk3wG3AL8OkyoA/44uotKrQdUGDO44mNeXvc7XW7+OOhznXBzJVESvBkaQ81axR7hfIDP7iZl1jbONB74Nm8sJP9fFucQqIHY24ubk9JPKL39+eVaRu8k99lpI+glwO3Cmme1M9NtSoUn1JlzU+SJeW/Ya8zbMiyIE51zJcDZwJrAdwMy+AWpEGlEp5m9FnSvZCqyIhgN97jezC8yskZk1NLMLzWxDIe87gZwpoIYD4+OcMw3oIKmNpIoEg5AmJMg/ARgqqZKkNgSDkj4Lm++3SToiHC1/cXYeSYcDjxFUQuNViIvNFYddQd3Kdbln2j0+r6hz5deusC+7AUiqFnE8pVqDqg0475DzeGPZG/5W1LkSqMCKqJntBRqEFcGidDdwkqTFwEnhPpKaSnozvPce4DqCyZwXAM+b2byC8ofHnwfmA28BI8LfAHAN8ATBAKal5PQF/RtQHXhB0kxJ2ZXdYle9YnWu7X4t07+dzuSVk6MKwzkXreclPQbUlnQl8C6Q1ISY+U15F3O8jqRXwunqPpPUNebYyLD71DxJN8akd5f0cTj93WuSaobpFSU9HabPktQ/Js+UMI6Z4RbpIiiXdb2MCmkV/K2ocyWQEr15CwvEngRvG7dnp5vZvakNrWTLzMy06dOnF/l192Tt4ZwJ52BmvDzwZSqkVSjyezjnCibpczPLjOC+Iug6dCjwU4L+7W+b2TtJ5E0HviR4OF9F0Ko0zMzmx5zzN+B7M/u9pEOBh83sxLBCOpZgtpJdBA/y15jZYknTgF+Y2fuSLgPamNlvJI0gmPru0rCiORHobWZZkqaEeZIuJFNVpmb727S/8e8F/+aVga/QtlbblN3HObe/gsrUZPqIfgO8Hp5bI2ZzKZCRlsHPe/2cFVtX8Pyi56MOxzlXjMIm+VfN7B0z+6WZ/SKZSmiooCnvsnUmmHuZcKL81pIaAZ2AT8zsh7A16n2CvqoQTKY/Nfz+DjAozrXWAZsJBnyWSJd1vYzK6ZV5aIYPCHWuJElmZaXfx9uKI7jyql/zfvRt3JdHZz3K1l1bow7HOVe8PpHU+yDyFTTlXbZZwDkAkvoArQjewM4F+kmqJ6kqcCo5Az/nEgyeAhgckz4LGCgpI+yT34vcg0WfDpvlf5O9kl1eqZoSL556VepxSZdLePfrd5m93pdUdq6kSGZlpQaS/ibpTUnvZW/FEVx5JYlf9P4FW3Zu4YnZT0QdjnOueB0PfCxpadiXc46kZGpOyUx5dzdQR9JM4HqCleX2mNkC4C8EbzzfIqhk7gnzXAaMkPQ5QWvYrjD9KYLK7nSChU/+F5PnAjM7DDg23C6KF3Aqp8SL5+IuF1O3cl3un3G/Dwh1roRIpmn+P8BCoA3we2AFQd8jl0KH1j2UM9udyb8X/JtV21YlzuCcKytOAdoBJwBnAKeHn4kUNOUdAGa21cwuNbMeBLOHNACWh8eeNLOeZtYP2AgsDtMXmtlPzawXMIZgsCdmtsfMbjKzHmY2EKgdk2d1+LkNeI6g20DkqlWoxs+6/Yxpa6fx0TcfRR2Oc47kKqL1zOxJYLeZvW9mlwFHpDguB1x/+PVkpGXwwIwHog7FOVdMzOwrM/sK+JHgjea+qZwSKGjKOwAk1Y6ZBeUKYKqZbQ2PNQw/WxI034/Jk54G3AE8Gu5XzZ5aStJJBG9W54dN9fXD9AoEFem5B/WHkQKDOw6mefXm3P/5/WRZVtThOFfuJVMR3R1+rpF0WjjvZrGvx14eNarWiAs7XchbK95i2ZZlUYfjnCsGks4Mp6ZbTjBoaAUFLD2cLb8p7yRdLenq8LROwDxJCwnevI6MucRLkuYDrxFMfbcpTB8m6UuClrFvgKfD9IbADEkLCFaCym5+rwS8HXYnmAmsJsnpp4pDhfQKXHf4dSzatIg3l78ZdTjOlXvJTN90OvABQZPPQ0BN4PdmFtl8myVBqqcaybbhxw0MeGkAZ7Q7g98d+buU3885F930TeG9ZxE0y79rZodLOp5gGqarooinuBRXmQqQZVkMeX0I23Zt47WzXqNCuk+T51wqFWr6JjN73cy2mNlcMzvezHqV90pocapXpR5ntDuD15a+xsYdG6MOxzmXervD1evSJKWZ2WSCpZVdEUlTGiN7jmT196t5/kufJs+5KCXTNO8idlHni9i5dyfjFo6LOhTnXOptllSdYO7O/0h6gJzR6K6IHN30aHo37s2o2aPYvnt74gzOuZTwimgp0LZWW45udjQvLn6RPVn+75FzZdxA4AfgJoKplJaS3Kh5dwAkcVPPm9i4YyOj542OOhznyi2viJYSgzsOZt0P6/hg1QdRh+KcSyEz225mWeH0SM+a2YNhU70rYoc1OIyTWp3E0/Oe5rsfv4s6HOfKpWQmtG8k6UlJE8P9zpIuT31oLtZxzY+jQZUGvPDlC1GH4pxzZcYNh9/Arr27eHTWo1GH4ly5lMwb0WcIpgNpGu5/CdyYonhcPjLSMji7w9l8uPpD1ny/JupwnHOuTGhdqzXndjyXF798kRVbVkQdjnPlTjIV0fpm9jyQBfvmqtub0qhcXIM6DALgpcUvRRyJcy6VJFWRdEjUcZQXV3e/mkrplXjwiwejDsW5cieZiuh2SfUIV/aQdASwJaVRubiaVm/K0c2O5pXFr/igJefKKElnEEwE/1a430OST5mXQvWr1OeSrpfwzlfvMHPdzKjDca5cSaYiejPBMnHtJH0EjAauL8xNJdWV9I6kxeFnnXzOO1nSIklLJN2aTH5Jvw7PXyRpQEx6L0lzwmMPSlKee50rySRFMol1sgZ3HMy6H9cxddXUqENxzqXGnQRrs28GMLOZQOvIoiknhnceTv0q9bn383tJtNCLc67oJDOh/QzgOOAo4GdAFzObXcj73gpMMrMOwKRwPxdJ6cDDBMvQdSZYZq5zQfnD40OBLsDJwCPhdQD+CVwFdAi3k2PuVQO4Afi0kL8r5fo170fDqg190JJzZdceM/NWp2JWtUJVru1xLV+s+4L3Vr4XdTjOlRvJjJofAVQ3s3lmNheoLunaQt53IPBs+P1Z4Kw45/QBlpjZMjPbBYwN8xWUfyAw1sx2mtlyYAnQR1IToKaZfWzBo+7oPPf8P+CvwI5C/q6Uy0jL4JwO5/DR6o9Y/f3qqMNxzhW9uZLOB9IldZD0EPC/qIMqD85ufzZtarXh/s/v9+5PzhWTZJrmrzSzzdk7ZrYJuLKQ921kZmvC660BGsY5pxmwMmZ/VZhWUP788jQLv+93LUmHAy3M7PXC/KDiNKjDICTx0pc+aMm5Muh6gladncBzBH3yb4wyoPIiIy2DG3veyIqtK3h58ctRh+NcuZBMRTQttj9l2NRdMVEmSe9KmhtnG5gob/Yl4qQl6riTX5646ZLSgPuAnycVkHSVpOmSpq9fvz6ZLCnRuFpjjm12LK8seYXdWbsji8M5V/TM7Aczu93MeofbHWZW4ltryorjWxxPz4Y9eWTmI/yw+4eow3GuzEumIvo28LykEyWdAIwhHM1ZEDP7iZl1jbONB74Nm8sJP9fFucQqoEXMfnPgm/B7fvnzy7Mq/J43vQbQFZgiaQVwBDAhvwFLZjbKzDLNLLNBgwaJ/ghSanDHwXz343dMWTkl0jicc0UrHIBZO2a/jqS3IwypXJHEzZk3s2HHBp6d92ziDM65QkmmInoL8B5wDTCCYHDQrwp53wnA8PD7cGB8nHOmAR0ktZFUkWAQ0oQE+ScAQyVVktSGYFDSZ2Hz/TZJR4Rvdy8GxpvZFjOrb2atzaw18AlwpplNL+TvS7ljmh1Dk2pN+Nf8f/kIT+fKlvpxukPF677kUqR7g+6+9KdzxSSZUfNZZvZPMzvXzAaZ2WNmVtgJ7e8GTpK0GDgp3EdSU0lvhvfdA1xH8EZ2AfC8mc0rKH94/HlgPsFb2xExsV4DPEEwgGkpMLGQvyFS6WnpXNLlEr5Y9wXT1k6LOhznXNHJktQye0dSKxJ3S3JF7IbDb2D33t2+9KdzKaZEb9MkdQD+TDCFUuXsdDNrm9rQSrbMzEybPj3aF6c79+7klJdOoXWt1jw14KlIY3GuLJH0uZlFMqewpJOBUcD7YVI/4CozK9PN8yWhTM3rrk/u4oUvX+CVga/QplabqMNxrtQqqExNpmn+aYI5OPcAxxNMffSvogvPHaxK6ZW4rOtlTFs7jY+/+TjqcJxzRcDM3gJ6AuMIWnh6lfVKaEmVvfTnAzMeiDoU58qsZCqiVcxsEsHb06/M7E7ghNSG5ZJ1bsdzaVGjBX/69E/s3Lsz6nCcc0VjL8EgzC1AZ0n9Io6nXKpXpR6Xdr2USV9P8qU/nUuRZCqiO8JpjhZLuk7S2XjH+RKjckZl7jjiDlZsXcGTc56MOhznXCFJugKYStA//vfh551RxlSeXdz5YupXqc/fp//dB4Y6lwLJVERvBKoSLIHZC7iQnBHrrgQ4qulRnNb2NB6f/Tgzvp0RdTjOucIZCfQGvjKz44HDgegmLi7nqlaoyogeI5i5fibvfe1LfzpX1PKtiErK7gd6lJl9b2arzOzScOT8J8UUn0vSbX1vo1mNZtw85Wa+3f5t1OE45w7ejuwJ7CVVMrOFwCERx1SundX+rGDpzxn3+yIizhWxgt6I9gqnDbksnFC5buxWXAG65NSsWJMHjn+AH/f8yLWTrmXLzi1Rh+ScOzirwgntXwXekTSenMU8CiTpZEmLJC2RdGuc43UkvSJptqTPJHWNOTYyXP1unqQbY9K7S/pY0hxJr0mqGaZXlPR0mD5LUv+YPL3C9CWSHoxdna80ykjL4KaeN7Fi6wpeWfxK1OE4V6YUVBF9lGAuzkOBz/NsJWuODQdAu9rtuK//fSzfspyr37marbu2Rh2Scy5J4SIcmNnZZrY5HBj6G+BJ4Kwk8qcDDwOnEEy3N0xS5zyn3QbMNLNuBAt7PBDm7QpcCfQBugOnh1P3QTD/8q1mdhjwCvDLMP3KMN7DCOZz/ns4ngCCmVauIlhUpANwctJ/ECVU/xb96dmwJw/PfJjtu7dHHY5zZUa+FVEze9DMOgFPmVlbM2sTs5XrOURLsqOaHcW9/e9l4aaFXPjmhazcujLqkJxzyXkRQNKk7AQze9/MJpjZriTy9wGWmNmy8PyxwMA853QmWB2PsMm/taRGQCfgk3Cd+z0Ec5ieHeY5hGDwFMA7wKA411oHbAYyw2WXa5rZxxaM7hlNEhXpkk4SP8/8ORt3bPSlP50rQgUOVgqfbo8tplhcEenfoj+jThrFxh0bGfLGEF5b+pqP9nSu5EuT9Dugo6Sb825J5G8GxD55rgrTYs0CzgGQ1AdoBTQH5gL9JNWTVBU4FWgR5pkLnBl+HxyTPgsYKCkjfJvbKzzWLLx3QXGUSt0adOOkVifxzLxnfOlP54pIgRVRM8sCZsUuN+dKh96NezPm1DG0q9WO2z68jSvfuZJ5G+Ylzuici8pQYAeQAdSIsyUSrx9m3ifQu4E6kmYC1wNfAHvMbAHwF4I3nm8RVDL3hHkuA0ZI+jyMI/vt7FMElczpwP3A/8I8ycQRBCxdJWm6pOnr15eOiQFG9hzJ7r27+efMf0YdinNlQkYS5zQB5kn6DNjXMcbMzsw/iysJWtRswTMnP8PYRWN5dNajDH19KD9t9VOGdxnOYfUPo5SPH3CuTDGzRZL+BnxtZmMO4hKryHlbCcGbzlyDnMxsK3ApQDiAaHm4YWZPEvRHRdKfwutlN+H/NEzvCJwWpu8Bbsq+tqT/AYuBTeG9840jJp5RBMuZkpmZWSqabVrVbMXgQwbz/KLnuaDzBbSt5T3VnCuMZOYR/T1wOvAH4O8xmysF0tPSuaDTBbx5zptc1e0qPlz9IRe8eQFDXh/Cy4tf5sc9P0YdonMuFLZCXXOQ2acBHSS1kVSR4A3rhNgTJNUOjwFcAUwNK6dIahh+tiRovh+TJz0NuINgICuSqkqqFn4/ieDN6nwzWwNsk3REWNm9GBh/kL+pRPpZt59ROaMyD3zuS386V1gJK6JhZ/n9tuIIzhWdGhVrcP3h1/Peee9xR9872J21m9/973ec+MKJPD77cX7Y/UPUITrnAu9I+oWkFgcyZV74hvI6gpWYFgDPm9k8SVdLujo8rRNBC9dCgtH1I2Mu8ZKk+cBrwAgz2xSmD5P0JbCQ4M3m02F6Q2CGpAXALcBFMde6hmC0/RJgKTDxQP8QSrJ6VepxaZdLeW/le770p3OFpESDWCRtI6d/T0WgArDdzGqmOLYSLTMz06ZPL72zWJkZM9bN4Jl5zzBl5RQaVm3Ib4/4Lce1OC7q0JyLnKTPzSwzonsvj5NsZX22ktJWpv6w+wdOefkU2tduz5MDfHll5wpSUJmazBvRGmZWM9wqE0zd8Y+iDtIVL0n0atSLh054iNGnjKZWpVpc99513DL1Fh8N6lyE8kyV51PmlVBVK1TlysOu5LO1n/HJGl9s0LmDlfCNaNxM0idmdkQK4ik1StvTeyK79+7m8TmP8/jsx5FE78a9yWyUSYsaLWhWvRlNqjehbuW6pCmZbsXOlW4RvxG9OF66mY0u7liKU2ksU3fu3cnpr5xOgyoN+M+p//EBoM7lo6AyNeGoeUnnxOymAZnkMxXHAQRUFxgHtAZWAOfF9EeKPe9kgpU/0oEnzOzuRPkl/Rq4HNgL3GBmb4fpvYBngCrAm8DIcLJlJJ0H3Bn+rllmdn5hfl9pVCG9Atf2uJbT257O2EVj+Wj1Rzz4xYO5zslIy6B1zdac3f5sjml2DOlp6aQrvdwUvpXSK1G/Sv2ow3BlX++Y75WBE4EZBBPDuxKkUnolrul+Db/73++YvHIyJ7Q8IeqQnCt1kukj+nTM7h6Cit/j4UoaB3dT6a/ARjO7O1wPuY6Z3ZLnnHTgS4Kl41YRjAgdZmbz88sfLmc3hmCFkabAu0BHM9sbTj81EviEoCL6oJlNDJexex44wcw2SWqYzG8rjU/vB+r7Xd/zzfZvWL1tNWt/WMva7WuZuW4mM9bNiDq0yBzT7Bj+dMyfqFO5TtShuBSK8o1oXpJqAf8q61PmldYydU/WHs4afxYV0irw0pkveauRc3EU6o2omV1a9CExEOgffn8WmEIw6jLWvuXqACRlL1c3v4D8A4GxZrYTWC5pCdBH0grCJefCa2UvOTeRYL3kh7PfqBamgl3WVK9YnY4VO9KxTsdc6V+s+4Jvt3/L7qzd7LW9EUVX/NZuX8sTc57gsrcv49+n/ptqFapFHZIrH34gWK/dlUAZaRmM6DGCX039FW8se4Mz2p0RdUjOlSrJNM3/Ffgj8CPBihvdgRvN7N+FuG+jcK45zGxN9jx1ecRbrq5vgvzNCN54xuZpBuwm/yXnOgJI+oigC8CdZvZWvKAlXQVcBdCyZfldbOrwhodHHUJkujXoxrXvXsvtH97Ovf3v9bcfrshJeo2c7k9pBGu6Px9dRC6RAa0H8My8Z7j/8/s5seWJVK1QNeqQnCs1kvlX9KfhhMenE1TgOgK/TJRJ0ruS5sbZBiYZW9LLxCWRp6BrZRC8begPDAOekFQ73sXNbJSZZZpZZoMGDRKE4sqio5oexc29bmbS15P41/x/RR2OK5vuIWfhkD8D/czs1mhDcgVJUxq39b2NdT+u47HZj0UdjnOlSjIV0Qrh56nAGDPbmMyFzewnZtY1zjYe+FZSE4DwM15zeEHL1eWXP788q8h/yblVwHgz221my4FFeDOYK8BFnS+if4v+PDzzYdZuXxt1OK7smQ58EC4csh7oKalCgjwuYt0bdGdgu4GMnj+aLzd9GXU4zpUayVREXwtX4cgEJklqAOwo5H0nAMPD78OJv/xbQcvV5Zd/AjBUUiVJbQgqlJ8lWHLuVeB4AEn1Cd74Livk73NlmCRu7XMrWZbF36b9LepwXNkzFagsqRkwiWBt+Gcijcgl5ebMm6lZsSa3f3g7u/fujjoc50qFZCa0vxU4Esg0s90EHeeTbV7Pz93ASZIWE4yKz56WqamkN8P7xl2urqD84fHnCQY0vUWwTF32aJr8lpx7G9gQLm03GfilmW0o5O9zZVyz6s244rAr+O9X/2XGt+V3FgGXEjKzHwjWe3/IzM4m6CfqSri6levyuyN/x8KNC/nnrH9GHY5zpcJBTWjvSu9UI67o/LjnRwa8OICu9bvyyE8eiTocV4QintD+C+Ba4D7g8nC9+DlmdlgU8RSXslSm/vaj3/LKkld44PgHfG5R5yjkEp/OufiqZFThgk4X8MHqD1i0cVHU4biyYyTwa+CVsBLalqC1xpUSt/W9ja71uvLrD37tZYNzCXhF1LlCGHroUKpmVOXJOU9GHYorI8xsqpmdaWZ/CfeXmdkNUcflklc5ozL3H38/1StW58r/XumDl5wrQMKKqAIXSvptuN9SUp/Uh+ZcyVerUi3O7Xgu73z1Dt/9+F3U4TjnSohG1Rrx1ICnqJBegcvfvpzpa8tGtwPniloyb0QfIRisNCzc3wY8nLKInCtlBnUYxB7bw+tLX486FOdcCdKqZiueHvA0tSvV5sr/Xsmz855lb1b5WY3OuWQkUxHta2YjCKdsCpfCrJjSqJwrRdrWbkv3Bt15ecnL+OA/51ysljVb8txpz3Fs82O5Z/o9XDzxYuZ+NzfqsJwrMZKpiO6WlE64ElE4j2hWSqNyrpQ5p8M5LN+ynFnrZ0UdiivlJHWUNEnS3HC/m6Q7oo7LHbwaFWvwwPEP8Odj/8zKbSsZ9sYwrpt0HfM2zEuc2bkyLuFa88CDwCtAQ0l3AecCXig6F2NA6wHc/dndTFg6gR4Ne0QdjivdHidYRvkxADObLek54I+RRuUKRRKntz2d/s3789zC53h23rMMfX0o/Zr34/Kul9OyZkvSlU6a0gjWXSn7qqRXoUK6LxpW3iWsiJrZfyR9DpxIsGb7WWa2IOWROVeKVKtQjWObHct7X7/H7X1vJz0tPeqQXOlV1cw+y1MZ2RNVMK5oVa9Ynau6XcWwQ4cxZuEY/jX/Xwx/a3jijGVQnUp1GPXTURxa99CoQ3ERyrciKqluzO46YEzssWTXnHeuvDip1Un896v/MnP9THo16hV1OK70+k5SO3K6Q50LrIk2JFfUalSswVXdruLCThcy6etJbN+9nSzLIsuyMMp+X3MzY/T80dw85WZeP/t10uSzSZZXBb0R/ZygIBTQEtgUfq8NfA20SXVwzpUmxzY/loppFXn3q3e9IuoKYwQwCjhU0mpgOXBhtCG5VKlaoSpntDsj6jAi0bBqQ3459Zd88s0nHNXsqKjDcRHJ9xHEzNqYWVuCtdjPMLP6ZlYPOB14ubgCdK60qFahGkc1PYpJX0/y0fPuoIUT2P8EaAAcambHmNmKiMNyrsid0PIEaleqzYuLX4w6FBehZAYr9Tazq7N3zGyipP9LYUzOlVontjqRKaumMH/jfLrU6xJ1OK4UkXRzPukAmNm9xRqQcylWMb0iZ7Q7gzELx7Dhxw3Uq1Iv6pBcBJLplPGdpDsktZbUStLtwIZUB+ZcaXRss2MB+Gj1RxFH4kqhGuGWCVwDNAu3q4HOyVxA0smSFklaIunWOMfrSHpF0mxJn0nqGnNspKS5kuZJujEmvbukjyXNkfSapJphegVJz4bpCyT9OibPlDCOmeHW8OD+SFxZd26Hc9mTtYcJSydEHYqLSDIV0WEETUSvAK8CDclZZck5F6NelXp0qtuJ/33zv6hDcaWMmf3ezH4P1Ad6mtnPzeznQC+geaL84XzPDwOnEFRch0nKW4G9DZhpZt2Ai4EHwrxdgSuBPkB34HRJHcI8TwC3mtlhBP8O/DJMHwxUCtN7AT+T1DrmXheYWY9wW3cgfxau/Ghbuy2HNzyclxf7giDlVcKKqJltNLORwHHAsWY20kfMO5e/o5oexax1s/h+1/dRh+JKp5bArpj9XUDrJPL1AZaEfUx3AWOBgXnO6QxMAjCzhUBrSY2ATsAnZvaDme0B3gfODvMcAkwNv78DDAq/G1BNUgZQJYxza7I/0rls53Y8lxVbVzD92+lRh+IikLAiKukwSV8Ac4B5kj6Pbc45GJLqSnpH0uLws04+58VtZioov6Rfh+cvkjQgJr1X2IS0RNKDCjteSWopabKkL8LmqlML89ucO6rpUeyxPXy29rOoQ3Gl07+AzyTdKelO4FPg2STyNQNWxuyvCtNizQLOAZDUB2hF8LZ1LtBPUj1JVYFTgRZhnrnAmeH3wTHpLwLbCaaW+hq4J89LiqfDZvnfZJe3zsVzUquTqFGhBi9+6YOWyqNkmuYfA242s1Zm1gr4OcHUIoVxKzDJzDoQPJ3H68tUUDNT3Pzh8aFAF+Bk4JHwOgD/BK4COoTbyWH6HcDzZnZ4mPeRQv42V871aNiDKhlVvHneHRQzuwu4lGDKvI3ApWb25ySyxqvs5W3rvBuoI2kmcD3wBbAnXKTkLwRvPN8iqLBmT6J/GTAiXNikBjlva/sAe4GmBNP5/VxS2/DYBWGT/bHhdlHcgKWrJE2XNH39+vVJ/ERXFlXJqMLp7U7nna/eYdOOTVGH44pZMhXRamY2OXvHzKYA1Qp534HkPOE/C5wV55yCmpnyyz8QGGtmO81sObAE6COpCVDTzD62oBPK6Jg8BtQMv9cCvinkb3PlXMX0ivRu3Nsroq4w9gJZMVsyVpHzthKCN525yjMz22pml5pZD4I+og0I5inFzJ40s55m1o+gArw4TF9oZj81s14EC5ssDS93PvCWme0O+4B+RDDQCjNbHX5uA54jKM/3Y2ajzCzTzDIbNGiQ5M90ZdHgjoPZnbXb34qWQ8lURJeFTSutw+0OwoKrEBqZ2RqA8DPeiMqCmpnyy59fnmbh93jXuhO4UNIq4E2CtwTOFUrfxn1ZuW0la7evjToUV8pIGgn8h2DQUkPg35KSKZemAR0ktZFUkaCFJ9dQZEm1w2MAVwBTzWxreKxh+NmSoPl+TJ70NIIWpEfD/F8DJyhQDTgCWCgpQ1L9ME8Fgrmn5x74n4QrTzrU6cBRTY/iuYXPsWvvrsQZXJmRTEX0MoKn5pfDrT5Bs1GBJL0bTgWSd8vbeT7fS8RJSzSkLr88BV1rGPCMmTUn6Bf1r7DA3f/i3ozkktSnSfACyPuJuoNwOdDXzH5nZr8lqOBdmShTOMjoOoJFSBYQdDmaJ+lqSdlzQXci6Ou/kKDb08iYS7wkaT7wGjDCzLLbSIdJ+hJYSPCG9ekw/WGgOkElcxrwtJnNBioBb0uaDcwEVgOPH8Sfgytnhnceznc/fscby96IOhRXjAqc0D7sX/lCuMrHASkoj6RvJTUxszVhs3m8qT0KambKL39+eVaRe/qT2GtdTthf1Mw+llSZoLK9X0xmNoqwf2xmZqbPM+Hy1bFOR2pVqsW0tdM4s92ZiTM4l0METfPZ9hL/YXo/ZvYmQctObNqjMd8/JugjHy/vsfmkP0A4zVOe9O8JBi/lTd9OMJ2TcwfkyKZH0qFOB0bPH81Z7c/at5iDK9sKfCNqZnuBHyTVKuL7TgCGh9+HA+PjnFNQM1N++ScAQyVVktSGoMD9LGy+3ybpiHD05sUxeb4GTgSQ1AmoDPjrTlcoaUojs1Em09ZOizoUV/o8BXwaM2r+E+DJaENyLvUkMbzzcJZsXuJ97MuRZJrmdwBzJD0ZTnv0oKQHC3nfu4GTJC0GTgr3kdRU0puQfzNTQfnD488D8wlGfo4IK9MQrFTyBMEApqXAxDD958CVkmYR9Im6xHxWXVcEejfuzervV7P6+9VRh+JKibBb0KcE3Z82Eoycv9TM7o8yLueKy6ltTqVBlQY8PffpxCe7MiGZtebfCLdYhaqomdkGwreQedK/Ieinmb2/XzNTQfnDY3cBd8VJnw7sN/+pmc0Hjj6A8J1LSu/GvQGYtnYazdrnnc7Ruf2ZWZakv5vZkcCMqONxrrhVSK/A8C7DuWf6PcxcN5MeDXtEHZJLsWTeiNY2s2djNyDuBPTOuRzta7enTqU63jzvDtR/JQ3ySeBdeTW442DqVKrDY7MfizoUVwySqYgOj5N2SRHH4VyZk6Y0Mhtn8tnaz3wNZXcgbgZeAHZK2ippmyRfOtOVG1UrVOXiLhfz4eoPmfudz/xV1uVbEZU0TNJrQBtJE2K2ycCG4gvRudKrT+M+rN2+llXbViU+2TnAzGqYWZqZVTSzmuF+zcQ5nSs7hh4ylJoVa/pb0XKgoD6i/yNYQ7g+8PeY9G3A7FQG5VxZsa+f6LfTaFGzRYKznQNJk8zsxERpzpVl1StW58JOF/LIrEdYtHERh9Q9JOqQXIrk+0bUzL4Kl/O8APjUzN43s/cJRrA3zy+fcy5H21ptqVe5nk9s7xKSVFlSXaC+pDqS6oZba4L13J0rV87vdD7VKlTzt6JlXDJ9RJ8n91rHewn6LznnEpBE78a9mbZmmvcTdYn8DPgcODT8zN7GE6xi5Fy5UqtSLc4/9Hze/epdlm5eGnU4LkWSqYhmmNm+hV/D7xULON85F6N3496s+3EdX239KupQXAlmZg+YWRvgF2bW1szahFt3M/tH1PE5F4WLOl9E5YzKjJo9KupQXIokUxFdL2nfGoXhWvHfpS4k58qWI5seCcAHqz+IOBJXSmRJqp29EzbTXxthPM5Fpk7lOgw9dCgTl09k8abFUYfjUiCZiujVwG2SVkr6GriFoAnJOZeEFjVa0L52e6asnBJ1KK50uNLMNmfvmNkm4MrownEuWpd1uYxqFarx0BcPRR2KS4GEFVEzW2pmRwCdgC5mdpSZLUl9aM6VHce3OJ7Pv/2cLTu3RB2KK/nSYiezl5SOd4dy5VjtyrUZ3mU4k1dOZtb6WVGH44pYwoqopEaSngReMLNtkjpLurwYYnOuzOjfoj97bS8frv4w6lBcyfc28LykEyWdAIwB3oo4JucidVHni6hbuS4PznjQB36WMck0zT9DUDBmTx/yJXBjiuJxrkzqWr8r9SrXY/LKyVGH4kq+W4D3gGuAEcAk4FeRRuRcxKpVqMZV3a7is7Wf8fGaj6MOxxWhZCqi9c1s3xROZraHYAon51yS0pRG/xb9+XD1h+zeuzvqcFwJZmZZBC8AbjezQWb2mJl5mevKvcEdB9O0WlN/K1rGJFMR3S6pHmAAko4AvKObcweof4v+bN+9nWnfTos6FFeChbOUzCRsjpfUQ9KESINyrgSomF6Ra3pcw7wN83j363ejDscVkWQqojcDE4B2kj4CRgPXpzQq58qgvk36Ujm9so+ed4n8DugDbAYws5lA6+jCca7kOKPtGbSt1ZaHvniIPVl7og7HFYFkRs3PAI4DjiKYtqmLmfla884doCoZVTii6RFMWTnFm5VcQfaYmbc6ORdHelo61x9+Pcu3LOe1pa9FHY4rAvlWRCWdk70BZwKHAB2BM8K0gxaun/yOpMXhZ518zjtZ0iJJSyTdmkx+Sb8Oz18kaUBM+l3hXKjf57lHJUnjwjyfhus6O5cSx7c4njXb1/Dlpi+jDsWVXHMlnQ+kS+og6SHgf1EH5VxJcWLLE+laryuPzHqEHXt2RB2OK6SC3oieUcB2eiHveyswycw6EIwIvTXvCeHceQ8DpwCdgWGSOheUPzw+FOgCnAw8El4H4DWC5q68Lgc2mVl74D7gL4X8bc7lq1/zfgjx3sr3og7FlVzXE5RhOwmmbtqKz1Ti3D6SuKnXTazdvpb/LPhP1OG4QsrI74CZXZrC+w4E+offnwWmEExZEqsPsMTMlgFIGhvmm19A/oHAWDPbCSyXtCS8zsdm9kl4nXix3Bl+fxH4hySZt526FKhfpT6H1T+MqSunck33a6IOx5VAZvYDcHu4Oefi6NOkD/2b9+eJOU9wdoezqVu5btQhuYOUb0U0m6RGwJ+ApmZ2SvjW8Ugze7IQ921kZmsAzGyNpIZxzmkGrIzZXwX0TZC/GfBJnjzNEsSy7z5mtkfSFqAe8F3eEyVdBVwF0LJly/0utHv3blatWsWOHd5UUFZUrlyZ5s2bU6FChSK75nEtjuOhLx7iux+/o36V+kV2XVe6SXqNcHaSeMzszGIMp0TwMrXsKcoy9aZeN3HOhHN4bNZj/Lrvr4sgOheFhBVRgvnsnibn6fxLYBxQYEVU0rtA4ziHkn3K3+/VJQUU0sWRx8xGAaMAMjMz9ztn1apV1KhRg9atW8d78+pKGTNjw4YNrFq1ijZt2hTZdY9rHlREp66ayjkdCtXd2pUt9xT2ApJOBh4A0oEnzOzuPMfrAE8B7YAdwGVmNjc8NpJgTXsBj5vZ/WF6d+BRoDqwArjAzLZKqgA8AfQk+LdktJn9OczTi+DfjirAm8DIg2ll8jK1bCnqMrVt7bYM6jCI5xc9z7BDh9G6VuvCB+mKXcomtDezn5hZ1zjbeOBbSU0Aws91cS6xCmgRs98c+Cb8nl/+gvLkZ18eSRlALWBjot8Xz44dO6hXr54XmGWEJOrVq1fkb2M61ulI42qNeX/l+0V6XVe6mdn72RvwGbA2T1qBEvSrz3YbMNPMugEXE1RakdSVoBLaB+gOnC6pQ5jnCeBWMzsMeAX4ZZg+GKgUpvcCfhYz2POfBK1HHcLt5AP70wh4mVq2pKJMvabHNVRMr8j9M+4vsmu64hXVhPYTgOHh9+HA+DjnTAM6SGojqSLBIKQJCfJPAIaGI+HbEBSAnx1ALOcC7xWmf6gXmGVLKv4+JXFc8+P4eM3H7Ny7s8iv70o3SWdwcBPa7+tXb2a7gOx+9bE6EwzwxMwWAq3D7ledgE/M7IfwZcP7wNlhnkOAqeH3d4BB4XcDqoUP8FWAXcDW8OVATTP7OCxLRwNnHcAfQS5eppYtRf33Wb9KfS7rehmTvp7EjG9nFOm1XfGIakL7u4GTJC0GTgr3kdRU0puw783rdQTr3C8AnjezeQXlD48/TzCg6S1gRPbSeJL+KmkVUFXSKkl3htd6EqgXDmy6mTgj+J0rasc1P44f9/zIZ2sSPSe5cuhODm5C+3j96vP2kZ8FnAMgqQ/QiqDlaC7QT1I9SVWBU8lpXZpLMIUfBG9Bs9NfBLYDa4CvgXvMbGN4z1UJ4iCM4SpJ0yVNX79+fRI/0bn9XdzlYhpWacg90+/xOZpLoUgmtDezDWZ2opl1CD83hunfmNmpMee9aWYdzaydmd2VKH947K7w/EPMbGJM+q/MrLmZpYWfd4bpO8xssJm1N7M+2aP0S6MVK1bQtWvXpM6dMmUKp5+e/yxc3bt3Z9iwYbnSLrnkEqpWrcq2bdv2pY0cORJJfPfdfmO7DoiZccMNN9C+fXu6devGjBnxn2yXL19O37596dChA0OGDGHXrl0J87/11lsccsghtG/fnrvvzuky98ILL9ClSxfS0tKYPn16oeI/UH2a9KFKRhXeX+XN824/BzuhfTL93e8G6kiaSfBC4YvwfgsIpq57h+AhfhaQvWzNZcAISZ8DNQjefEJQWd4LNAXaAD+X1DbJOIJEs1FmlmlmmQ0aNEjqRxYnL1NLR5laJaMK1/e8njnfzeHtFW8X231d0UjmjShmtsfM5pnZXDPbneqgXLQWLFhAVlYWU6dOZfv27bmOtW/fnvHjg54QWVlZTJ48mWbNEk1MkNjEiRNZvHgxixcvZtSoUVxzTfypjW655RZuuukmFi9eTJ06dXjyyScLzL93715GjBjBxIkTmT9/PmPGjGH+/PkAdO3alZdffpl+/foVOv4DVSm9Ekc0OYL3V73vT/Aur4Od0D5hH3kz22pml5pZD4I+og2A5eGxJ82sp5n1I+gnvzhMX2hmPzWzXgTzmi4NL3c+8JaZ7TazdcBHQGYYR/OC4ihvvExNvTPankHHOh25f8b97Nq7K3EGV2IkM2reHYTfvzaP+d9sLdJrdm5ak9+d0SWpc5ctW8agQYMYNWoUvXv3PqD7PPfcc1x00UUsWLCACRMm5HqKHzZsGOPGjePCCy9kypQpHH300UycOLGAqyVn/PjxXHzxxUjiiCOOYPPmzaxZs4YmTZrsO8fMeO+993juuecAGD58OHfeeSfXXHNNvvlXrFhB+/btadu2LQBDhw5l/PjxdO7cmU6dOhU67sLo36I/k1dO5stNX3JI3UMijcWVKNcTzC6yE3iOoHvSH5PIt69fPbCaoF/9+bEnSKoN/BD2Ib0CmGpmW8NjDc1snaSWBM33R+ZJTwPuIBhBD0Fz/AmS/g1UBY4A7g+n1NsWjif4lKDC+9DB/VHk8DL1wJS3MjU9LZ2fZ/6cn73zM8YsHMPwLsMTZ3IlQlJvRF3psmjRIgYNGsTTTz99wAUmwLhx4xgyZAjDhg1jzJgxuY516NCB9evXs2nTJsaMGcPQoUPzvc6QIUPo0aPHftvo0aP3O3f16tW0aJHzMqd58+asXr061zkbNmygdu3aZGRk7HdOfvmTuW5Ujm12LIA3z7tcwgFDt5tZ73C7w8wSDjPOr1+9pKslXR2e1gmYJ2khwej6kTGXeEnSfIJV6EaY2aYwfZikL4GFBG82nw7THyaY0mkuQSX46ZhuW9cQjLZfQvAGtfA1qwh5mVo6ytSjmh7F0c2O5rHZj7FlZ2HHVLviksyE9gIuANqa2R/Cp+XGZuajLAqQ7FN2UVu/fj0DBw7kpZdeokuXA49h2rRpNGjQgFatWtG8eXMuu+wyNm3aRJ06dfadc8455zB27Fg+/fRTHnvssXyvNW7cuKTvG695Ou/oyoLOye9YMteNSoOqDeharyvvr3qfq7pdFXU4rgwwszcJ5u2MTXs05vvHBLOJxMt7bD7pDxBO85Qn/XuCwUvx8kwHkutcmSQvU71MTcbNvW5m8GuDeWz2Y/yq96+iDsclIZk3oo8QNNFktyVsI3gSdiVQrVq1aNGiBR999NFB5R8zZgwLFy6kdevWtGvXjq1bt/LSSy/lOmfo0KH85je/4aSTTiItLf//hA7k6b158+asXJkz4HfVqlU0bdo01zn169dn8+bN7NmzZ79z8sufzHWj1K9FP+asn8OGHzdEHYpzLg4vU3PnL+llasc6HTmr/VmMWTiGldtWJs7gIpdMRbSvmY0gWIWDsLmmYkqjcgetYsWKvPrqq4wePXpfv59kZWVl8cILLzB79mxWrFjBihUrGD9+/H5NSS1btuSuu+7i2muvLfB648aNY+bMmfttF1988X7nnnnmmYwePRoz45NPPqFWrVq5+jJB8NR9/PHH8+KLLwLw7LPPMnDgwALz9+7dm8WLF7N8+XJ27drF2LFjOfPMkrNSYv/m/TGMD1Z/EHUozrk4vEwtXWUqwIgeI6iQVoEHZzwYdSguGWZW4EbQ2TwdmBHuNwC+SJSvrG+9evWyvObPn79fWnFavny5denSxczMNm3aZJmZmfbqq6/GPXfy5MlWuXJla9as2b7tT3/6k/Xt2zfXeXv27LHGjRvbN998Y8OHD7cXXnhhv2u1atXK1q9fX6jYs7Ky7Nprr7W2bdta165dbdq0afuOnXLKKbZ69WozM1u6dKn17t3b2rVrZ+eee67t2LEjYf433njDOnToYG3btrU//vGP+9Jffvlla9asmVWsWNEaNmxoP/3pT+PGlsq/16ysLDvh+RPsxvduTNk93IEDpltEZQvQkWDS+bnhfjfgjqjiKa7Ny9QcXqYW3kMzHrKuz3S12etmp/xeLrGCylQFx/Mn6QJgCMF6ws8SrD50h5m9UPTV4tIjMzPT8s6TtmDBgshHYruil+q/1z98/AfeWPYGHwz9gIrp3thQEkj63MwyI7r3+wTLaD5mZoeHaXPNrEj7XJY0XqaWH8Xx97p993ZOfflUWtdszTMnP1Oi+rGWRwWVqclMaP8f4FfAnwlW0DirvFdCnStK/Vv054c9PzB9bfFOqu9KrKq2/2DQPXHPdM7FVa1CNUb0GMGMdTOYvHJy1OG4AiSsiEp6AKhrZg+b2T8sWIHDlRJvv/32fh3bzz777MQZXbHp07gPldMr+zROLtt3ktoRrkYk6VyClwCuBPAytfQ4p8M5tKnVhvs+v4/dWb4WT0mVzIT2M4A7JHUEXgHGWTA1hysFBgwYwIABA6IOwxWgckblfass3drnVm9CciOAUcChklYTrHx0QbQhuWxeppYeGWkZ3NTzJm6YfAMvf/kyQw4dEnVILo5kmuaftWD99z7Al8BfJC1OeWTOlSP9WvRj9ferWbp5aeKTXVn3lZn9hGBg6KFmdoyZfRV1UM6VRv1b9KdXo148MusRtu/enjiDK3YHsrJSe+BQoDXBChvOuSLSr1mwNvOUVVOiDcSVBMsljSJYMvP7qINxrjSTxC8yf8HGHRt5au5TUYfj4kimj2j2G9A/APOAXmZ2Rsojc64caVStEZ3qdmLqqqlRh+KidwjwLkET/XJJ/5B0TMQxOVdqda3flVNan8LoeaP5dvu3UYfj8kjmjehy4EgzO9nMnjKzzSmOyblyqX+L/sxaP4tNOzYlPtmVWWb2o5k9b2bnAIcDNQEfyeZcIdzQ8wb22l4enukLQ5Y0+VZEJR0afv0MaCmpZ+xWmJtKqivpHUmLw886+Zx3sqRFkpZIujWZ/JJ+HZ6/SNKAmPS7JK2U9H2ee9wsab6k2ZImSWpVmN8WpRUrVtC1a3JTDU6ZMoXTTz893+Pdu3dn2LBhudIuueQSqlatyrZt2/aljRw5Ekl89913Bxd0yMy44YYbaN++Pd26dWPGjBlxz1u+fDl9+/alQ4cODBkyhF27diXMf9lll9GwYcOk/2yicmLLE8myLN5a8VbUobiISTpO0iMEg0UrA+dFHFK55GVq6S5TYzWv0ZzzDz2fV5e8yuJNPsylJCnojejN4eff42z3FPK+twKTzKwDwQoit+Y9QVI6wZr2pwCdgWGSOheUPzw+FOgCnAw8El4H4DWCAVd5fQFkmlk34EXgr4X8baXeggULyMrKYurUqWzfnrtzd/v27Rk/fjwQLF83efJkmjVrVuh7Tpw4kcWLF7N48WJGjRrFNddcE/e8W265hZtuuonFixdTp04dnnzyyYT5L7nkEt56q+RX7g6pewid6nbilcWvRB2Ki5Ck5cCNwAdAVzM7z8xeKjiXK8m8TC0Zrux2JdUqVOMfX/wj6lBcjHynbzKzq8Kvp5jZjthjkioX8r4Dgf7h92eBKcAtec7pAywxs2XhPceG+eYXkH8gMNbMdhL0rVoSXudjM/skvE6um5hZ7Ey3nwAXFvK3BSbeCmvnFMml9ml8GJxyd1KnLlu2jEGDBjFq1Ch69+59QLd57rnnuOiii1iwYAETJkzI9RQ/bNgwxo0bx4UXXsiUKVM4+uijmThx4gFdP57x48dz8cUXI4kjjjiCzZs3s2bNmlxrI5sZ77333r71nocPH86dd97JNddcU2D+fv36sWLFikLHWBzO6XAOd316F/M3zKdzvc6JM7iyqLuZbY06iBLHy9QD4mXq/mpVqsUlXS7hHzP/wZz1cziswWFRh+RIro/o/5JMOxCNzGwNQPjZMM45zYCVMfurwrSC8heUJxmXA4UvASK2aNEiBg0axNNPP33ABSbAuHHjGDJkCMOGDWPMmDG5jnXo0IH169ezadMmxowZw9ChQ/O9zpAhQ/ab+LlHjx6MHj16v3NXr15NixYt9u03b96c1atX5zpnw4YN1K5dm4yMjP3OSSZ/aXBq21OplF6Jlxe/HHUorphJ+lX49S5JD+bdIg2unPMytfSWqXld2PlC6lauy4Nf+P9SJUW+b0QlNSaoxFWRdDiQ/SqxJlA10YUlvQs0jnPo9iRjizert6UgT5BRuhDIBI4r4JyrgKsAWrZsWfAFk3zKLmrr169n4MCBvPTSS3Tp0uWA80+bNo0GDRrQqlUrmjdvzmWXXcamTZuoUyenG+8555zD2LFj+fTTT3nsscfyvda4ceOSvq/Z/n9Ncd5e53tOMvlLg5oVa/LTVj/l9WWvc/3h11OrUq2oQ3LFJ3vVOl8wJB4vU71MLQLVKlTjisOu4K/T/sqnaz6lb5O+UYdU7hW0stIA4BKgOXBvTPo24LZEFw4nZI5L0reSmpjZGklNgHVxTlsFtIjZbw58E37PL39BefIl6ScEFeTjwmb9/H7TKIIVT8jMzEyqglvcatWqRYsWLfjoo48OqtAcM2YMCxcupHXr1gBs3bqVl156iSuuuGLfOUOHDqVnz54MHz6ctLT8X6oPGTKERYsW7Zd+8803c/HFF+dKa968OStX5rzMXrVqFU2bNs11Tv369dm8eTN79uwhIyMj1znJ5C8tLul6Ca8te41/zf8X1x1+XdThuGJiZq+FX38wsxdij0kaHEFIDi9TC8pfWp13yHk8O+9ZHvziQf7d+N9looJdmuX7X3y4otLxwCVmdnzMdqaZFbbdcAIwPPw+HBgf55xpQAdJbSRVJBiENCFB/gnAUEmVJLUBOhCM+s9X+Lb3MeBMM4tXIS5VKlasyKuvvsro0aP39ftJVlZWFi+88AKzZ89mxYoVrFixgvHjx+/XlNSyZUvuuusurr322gKvN27cOGbOnLnflrfABDjzzDMZPXo0ZsYnn3xCrVq1cvVlguBp/Pjjj+fFF18E4Nlnn2XgwIFJ5y8tOtbpyEmtTuI/C/7Dlp1bog7HFb9fJ5nmioGXqaW/TM2rUnolru5+NbPXz+b9VT4zWuTMLOEGnAb8Cvht9pZMvgKuV49gtPvi8LNumN4UeDPmvFMJlhVdCtyeKH947Pbw/EUEA62y0/9K8MY0K/y8M0x/F/gWmBluE5L5Db169bK85s+fv19acVq+fLl16dLFzMw2bdpkmZmZ9uqrr8Y9d/LkyVa5cmVr1qzZvu1Pf/qT9e3bN9d5e/bsscaNG9s333xjw4cPtxdeeGG/a7Vq1crWr19fqNizsrLs2muvtbZt21rXrl1t2rRp+46dcsoptnr1ajMzW7p0qfXu3dvatWtn5557ru3YsSNh/qFDh1rjxo0tIyPDmjVrZk888cQBxRbF3+uijYus6zNd7b7p9xX7vZ0ZMN0KUcYdzEYwQ8hDYXn0YMz2DPBZccdT3JuXqTm8TE29XXt32akvnWrnjD/H9mbtjTqcMq+gMlXB8fxJepSgT+jxwBPAuWGheHnStd0yKDMz06ZPz92Va8GCBXTq1CmiiFyqRPX3evuHt/Pm8jd58YwXaVe7XbHfvzyT9LmZZRbzPbsDPQhWsfttzKFtwGQzK9MrHXiZWn6UlL/XN5e9yS0f3MJf+/2VU9qcEnU4ZVpBZWoyo+aPMrOLgU1m9nvgSHL3w3TOpcDPM39OtQrV+MPHfyDLsqIOx6WYmc0ys2eBdhZ0jcreXi7rlVDnonBym5PpUKcD//jiH+zO2h11OOVWMhXRH8PPHyQ1BXYDbVIXkitKb7/99n5TfZx99tlRh+WSULdyXX7e6+fMWDeD/yz4T9ThuBST9Hz49YtwpbfsbY6k2ZEG5/bxMrXsSFMaNxx+A19v+5oJSyYkzuBSoqBR89lel1Qb+BvBcnNG0ETvSoEBAwYwYMCAxCe6Eums9mfx3tfvcd/n95HZKJNO9aJvznIpMzL8zH+dyAQknQw8AKQDT5jZ3XmO1wGeAtoBO4DLzGxueGwkcCXBNHiPm9n9YXp34FGgOrACuMDMtkq6APhlzOW7AT3NbKakKUATcl5k/NTKwGBQ8DK1rDmu+XF0q9+Nf876J6e3O51K6ZWiDqncSfhG1Mz+z8w2W7DEXCvgUDP7TepDc85J4g9H/4E6lerwy6m/9FH0ZZiFi3QA3wErzewroBLQneSmoStoWeRstwEzLVjS+GKCSiuSuhJUQvuE9ztdUocwzxPArWZ2GPAKYeXTzP5jZj3MrAdwEbDCzGbG3OuC7ONlpRLqyh5J3NDzBr794VueX/R84gyuyCWsiEo6J3sjGD1/oqQTJcVbDck5V8TqVK7D3477G6u/X83NU25m917vy1TGTQUqS2pGMCvIpQQj5xPZtyyyme0CspdFjtU5vCZmthBoLakR0An4xMx+MLM9wPtAdnvzIWFMAO8Ag+LcexgwJk66cyVe3yZ96dukL6Nmj2LTDu+OXdyS6SN6OcET8QXh9jhwM/CRpItSGJtzLtSzUU/+cNQf+GztZ9z24W3esb5sk5n9AJwDPGRmZxNUIBNJZonjWeF1kdSHoJWrOTAX6CepnqSqBFPnZQ9KnQucGX4fTPzBqkPYvyL6tKSZkn4jnzHclXC39L6F73d9zz3T74k6lHInmYpoFtDJzAaZ2SCCAnEn0Be4JZXBOedynNHuDG7udTNvrXiLX77/S3bt3RV1SC41JOlIggf/N8K0ZPrzJ7PE8d1AHUkzgeuBL4A9ZrYA+AvBG8+3CCqse8I8lwEjJH0O1ABy/YcnqS/BalBzY5IvCJvyjw23uC8tJF0labqk6evXr0/iJzqXGh3qdODSrpcyYekE/vfN/6IOp1xJpiLa2sy+jdlfB3Q0s40EI+hdCbFixQq6du2a1LlTpkzh9NPzHxPRvXt3hg0blivtkksuoWrVqmzbtm1f2siRI5HEd999d3BBh8yMG264gfbt29OtWzdmzJgR97zly5fTt29fOnTowJAhQ9i1K/g3ceHChRx55JFUqlSJe+4pu0+0l3a9lFv73Mqkrydxw+Qb2L57e9QhuaJ3I8FKSq+Y2TxJbYHJSeRLuMSxmW01s0vDfp0XAw2A5eGxJ82sp5n1AzYSLBiCmS00s5+aWS+Ct55L89x3KHnehprZ6vBzG/AcQbeB/ZjZKDPLNLPMBg0aJPETi5eXqWW/TI31s+4/o3XN1tzx4R1s3LEx6nDKjWQqoh9Iel3ScEnDCZbRnCqpGrA5pdG5SCxYsICsrCymTp3K9u25Kzrt27dn/PhgRdWsrCwmT55Ms2Z5W/8O3MSJE1m8eDGLFy9m1KhRXHPNNXHPu+WWW7jppptYvHgxderU4cknnwSgbt26PPjgg/ziF78odCwl3QWdLuDOI+/kk28+4cI3L2TltpWJM7lSw8zeN7MzgUckVQ/7fN6QRNaClkUGQFLt8BjAFcBUM9saHmsYfrYkaL4fkyc9DbiDYAQ9MWmDCfqjZqdlSKoffq9AMAtA7NvScsfL1NKhUnol/nbc39iycwu3fXibz99cTJJp7hlBUCgdQ9D08yzwUrhk0/EpjK1U+8tnf2HhxoVFes1D6x7KLX2S6w2xbNkyBg0axKhRo+jdu/cB3ee5557joosuYsGCBUyYMCHXU/ywYcMYN24cF154IVOmTOHoo49m4sSJB3T9eMaPH8/FF1+MJI444gg2b97MmjVrcq1tbGa89957+9Z7Hj58OHfeeSfXXHMNDRs2pGHDhrzxxhv53aJMGdRxEE2rN+UX7/+Coa8P5a/9/srRzY6OOixXBCQdBowG6ga7Wg9cbGbzCspnZnskXQe8TTB901PhG9Wrw+OPEgxKGi1pLzCfYAxAtpck1SNo6RoRM4n+MEkjwu8vA0/H5OkHrDKzZTFplYC3w0poOsEyyo8f2J/C/rxMPTBeph6cQ+seyq96/4o/fvpH7p1+L7/oXX4q4lFJZvomA6YDb5jZjcCbBPPJuRJq0aJFDBo0iKeffvqAC0yAcePGMWTIEIYNG8aYMbnHH3To0IH169ezadMmxowZw9ChQ/O9zpAhQ/ab+LlHjx6MHj16v3NXr15NixY5rYrNmzdn9erVuc7ZsGEDtWvXJiMjI99zypMjmx7J2NPG0rhaY6559xqfeqTseAy42cxamVlL4OckWZEzszfNrKOZtTOzu8K0R8NKKGb2sZl1MLNDzeyc2BWbzOxYM+tsZt3NbFJM+gPhNTua2a0Wsy60mU0xsyPyxLDdzHqZWTcz62JmI81sb6H+RCLmZWr5ct4h5zHs0GE8O/9Znpr7VNThlHkJ34hKuhK4iuDpvB3BKMxHgRNTG1rpluxTdlFbv349AwcO5KWXXqJLly4HnH/atGk0aNCAVq1a0bx5cy677DI2bdpEnTp19p1zzjnnMHbsWD799FMee+yxfK81bty4pO8b82/bPnkH2iZzTnnTomYL/n3qv/nl+7/k/z75PyQxuOPgqMNyhVPNzPb1CTWzKWFXqHLNy1QvU4uLJG7pfQubdmzivs/v4/td33P94df7n02KJNs03wf4FMDMFvscoiVXrVq1aNGiBR999NFBFZpjxoxh4cKFtG7dGoCtW7fy0ksvccUVV+w7Z+jQofTs2ZPhw4eTlpb/S/UhQ4awaNGi/dJvvvlmLr744lxpzZs3Z+XKnL6Oq1atomnTprnOqV+/Pps3b2bPnj1kZGTEPac8qpJRhXv738uNk2/kDx//gSoZVTi97UEvzuOit0zSb4B/hfsXEg4ocsXPy9TyKT0tnT8f+2eqV6zO43MeZ8XWFfzuyN9Rq1KtqEMrc5KpiO40s13ZTwKSMth/ShBXQlSsWJFXX32VAQMGUL16dc4///yk82ZlZfHCCy8we/bsfZ3lJ0+ezB//+MdchWbLli256667+MlPflLg9Q7k6f3MM8/kH//4B0OHDuXTTz+lVq1aufoyQfCUevzxx/Piiy8ydOhQnn32WQYOzDtfd/lUMb0i9x1/H9e+ey13fHgHldMr85NWBf/9uBLrMuD3BP0xRTCZ/KWRRlSOeZlafmWkZfDbI35L65qtuX/G/cxaP4tbet/CSa1O8rejRcnMCtyAvxIsC7cQOIlgibe7EuUr61uvXr0sr/nz5++XVpyWL19uXbp0MTOzTZs2WWZmpr366qtxz508ebJVrlzZmjVrtm/705/+ZH379s113p49e6xx48b2zTff2PDhw+2FF17Y71qtWrWy9evXFyr2rKwsu/baa61t27bWtWtXmzZt2r5jp5xyiq1evdrMzJYuXWq9e/e2du3a2bnnnms7duwwM7M1a9ZYs2bNrEaNGlarVi1r1qyZbdmypVAxZYv67/VAfL/rexv2+jDr+kxX+/mUn9uby960Nd+vsaysrKhDK1WA6RZxGQPUAmpEHUdxbV6m5vAyteSZ+91cO2f8Odb1ma520ZsX2UerP/Jy9QAUVKYqOJ6/cHqOy4GfEjydvw08YYkylnGZmZk2ffr0XGkLFiygU6dOEUXkUqW0/b3u2LODUbNHMXbRWLbtCuYnrF6hOm1rteWYZsdwfqfzvXkpAUmfm1lmRPfuDTxFMHk8wBbgMjP7PIp4iouXqeVHaf173Zu1l5cWv8Rjsx9j3Q/r6Fa/G1d1u4p+zfv5G9IECipTEzbNm1kWwYjNQk+/ERNQXWAc0BpYAZxnMaM3Y847GXiAYAqQJ8zs7kT5Jf2aoOK8F7jBzN4O0+8imMC5jpntN+pf0rnAC0BvM5ue97hzpUXljMrc0PMGru1xLYs2LWLO+jks3byULzd9ySOzHuGZec9Qu1JtMtIySFMyUwmXDS1rtuThEx+OOoxkPAlca2YfAEg6hmDKpG6RRuVcOZeels55h5zHWe3P4tUlr/LU3Ke47r3rqF+lPpXTK5OmtHJVph7X/Lgimd4qmVHzRwN3EqxJnEHwVtTMrG0h7nsrMMnM7pZ0a7ifa0ikpHTgYYLuAKuAaZImmNn8/PJL6kwwiXMXoCnwrqSOFkwd8hrwD8LVQvLcqwZwA+GArLLk7bff5pZbco82bdOmDa+88kpEEbnikpGWQZd6XehSL2eAxfwN83nxyxfZuXcnu7N2U54aNhpVbRR1CMnall0JBTCzDyVtKyiDKz5eprqK6RU575DzOLvD2by57E0+W/sZWZa1bysvmlRvkvikJCQzWOlJ4Cbgc4K3jEVhINA//P4sMIX9163vAyyxcKJkSWPDfPMLyD8QGGtmO4HlkpaE1/nYzD4JrxMvnv8j6Atb6Kq9mZWoV/QDBgxgwIABUYdRapW1ilrnep357ZG/jToMV7DPJD1GsLKRAUOAKZJ6AphZ/LUayygvU8uWslSmVkirwMD2AxnY3gd4FUYyFdEtZlb4ZR5ya2RmawDMbE0+00E1A2LXLlwF9E2QvxnwSZ48Ba6VJulwoIWZvS6pwIqopKsI5lSlZcuW+x2vXLkyGzZsoF69eiWq4HQHx8zYsGEDlStXjjoUV770CD9/lyf9KIKK6QnFGk2EvEwtW7xMdfEkUxGdLOlvBFOJ7MxOTPRULuldoHGcQ7cnGVu8UifRo9QB5QkHYt0HXJJMQGY2ChgFQcf6vMebN2/OqlWrWL9+fTKXc6VA5cqVad68edRhuHLEzHzp5JCXqWWPl6kur2QqotlvIWNHOyV8KjezfCdEk/StpCbh28wmwLo4p60CWsTsNwe+Cb/nl7+gPPHUALoSNHtBUHGeIOnMgxmwVKFCBdq0aXOg2ZxzzsXhZapzZV8ya80fH2crbNPQBGB4+H04MD7OOdOADpLaSKpIMAhpQoL8E4ChkipJagN0AD7LLwgz22Jm9c2stZm1JmjWP6hKqHPOOeecOzBRzTNwN3CSpMUEo+Kzp2VqKulNADPbA1xHMG/pAuB5M5tXUP7w+PMEA5reAkaEI+aR9FdJq4CqklZJurNYfqlzzjnnnIsr4YT2Lr54ky8758qGKCa0l3ROQcfN7OXiiiUKXqY6V3YVVKZ6RfQgSVoPfJXk6fWB71IYTnHx31Gy+O9InVZm1qA4byjp6fBrQ4IR8u+F+8cDU8yswIpqaedlaqnmv6NkKYm/I98yNd+KaHl/Oi9KkqZHtVxgUfLfUbL47yibJL0OXJk9RV04IPPhsl4RPRBl5b8Z/x0li/+OaBQ0av6M8DPu0znBdE7OOeeKVuvsSmjoW6BjVME451wq5VsRNbNLYd/Teee8T+fFE55zzpU7UyS9Tc7KSkOBydGG5JxzqZHMPKL+dF54o6IOoIj47yhZ/HeUQWZ2naSzgX5h0igz84XMcysr/8347yhZ/HdEIOFgJUn/IJiPM/bpfImZXZ/68JxzrvyR1AroYGbvSqoKpJvZtqjjcs65opbUqPk8T+dT/encOedSQ9KVwFVAXTNrJ6kD8KiZnRhxaM45V+SSaZoHmAFsy346l1TDn86dcy4lRgB9gE8BzGyxpIbRhuScc6mRcGWl8On8ReCxMKkZ8GoKYypTJJ0saZGkJZJujTqegyHpKUnrJM2NOpbCkNRC0mRJCyTNkzQy6pgOhqTKkj6TNCv8Hb+POqbCkJQu6YtwYKSDnWa2K3tHUgZBtyiHl6kliZepJVNpK1OTWeJzBHA0sBWCp3OCKZ1cApLSCWYYOAXoDAyT1DnaqA7KM8DJUQdRBPYAPzezTsARwIhS+vexEzjBzLoDPYCTJR0RbUiFMpJgGV8XeF/SbUAVSScBLwCvRRxTieBlaonjZWrJVKrK1GQqov50fvD6EAzsWhb+GY4FBkYc0wEzs6nAxqjjKCwzW2NmM8Lv2wj+R20WbVQHzgLfh7sVwq1U/j8pqTlwGvBE1LGUILcC64E5wM+AN4E7Io2o5PAytQTxMrXkKY1lajIVUX86P3jNgJUx+6sohf+TlkWSWgOHE/bDK23CppeZwDrgHTMrlb8DuB/4FZAVcRwlhpllmdnjZjbYzM4Nv5fKfxRTwMvUEsrL1BLjfkpZmZpMRdSfzg+e4qT5PygRk1QdeAm40cy2Rh3PwTCzvWbWA2gO9JHUNeKQDpik04F1ZvZ51LGUJJLmSJqdZ/tA0n2S6kUdX8S8TC2BvEwtGUprmZpw1LyZZQGPh5s7MKuAFjH7zYFvIorFAZIqEBSY/zGzUr9MrZltljSFoL9ZaRv4cDRwpqRTgcpATUn/NrMLI44rahOBvcBz4f7Q8HMrQd/CM+LkKS+8TC1hvEwtUUplmZrMhPZz2P+JcwswHfijmW1IUWylXtif9kvgRGA1MA0438zmRRrYQQibXV43s1L3lJhNkoBngY1mdmPE4Rw0SQ2A3WGBWQX4L/AXMysVIyTjkdQf+IWZnR5xKJGT9JGZHR0vTdIcMzssqtii5mVqyeJlaslVmsrUZJrmJwJvABeE22vAVGAtwdO5y4eZ7QGuA94m6MT9fCktMMcAHwOHSFol6fKoYzpIRwMXASdImhlup0Yd1EFoAkyWNJvgH+J3SnOB6fZTXVLf7B1JfYDq4e6eaEIqGbxMLXG8THWFlswbUX86d865YiKpN/AUQeVTBE3yVwDzgNPM7PkIw3POuSKVzMpK1SX1zR5B5k/nzjmXOmY2DThMUi2ClwWbYw57JdQ5V6YkUxG9AngqHBW37+lcUjXgz6kMzjnnyiNJpwFdgMpBNzwwsz9EGpRzzqVAwqb5fSfGfzp3zjlXhCQ9ClQFjieYlPpc4DMzK639CJ1zLl9JVURjn86z0/zp3Dnnip6k2WbWLeazOvCymf006ticc66oJRw1Hz6dDwGuJ2iaHwy0SnFczjlXXu0IP3+Q1BTYDbSJMB7nnEuZZKZvOsrMLgY2mdnvgSPJPaGwc865ovOapNrA34AZwApgTJQBOedcqiRTEfWnc1eqSKoXM6fdWkmrw+/fS3okBfd7RtJySVfH7J8b57x22XEUdQyubJCUBkwys81m9hJB69OhZvbbiENz5ZiXqS6Vkhk1n/fp3PDlPl0JFq721QNA0p3A92Z2T4pv+0szezFBXEuBHl5ouvyYWZakvxO0PGFmO4Gd0UblyjsvU10qFfhG1J/OXVkiqb+k18Pvd0p6VtJ/Ja2QdI6kv0qaI+mtcP1kJPWS9L6kzyW9LalJkrfrJ+l/kpbFe5J3rgD/lTRI2fM2OVdCeZnqikKBFVEzywL+HrO/08y2pDwq54pHO+A0YCDwb2ByuFLYj8BpYcH5EHCumfUiWO3mriSv3QQ4BjgduLuoA3dl2s3AC8AuSVslbZO0NeqgnEuCl6nugCXTNP9fSYMIpg9JbtJR50qHiWa2W9IcIB14K0yfA7QGDgG6Au+EL6fSgTVJXvvV8EFuvqRGRRq1K9PMrEbUMTh3kLxMdQcsmYrozUA1YK+kHwmmcDIzq5nSyJxLvZ2wr1/e7pgHrSyC/zcEzDOzIw/22iFvYnVJC5vkLwDamNn/SWoBNDGzzyIOzblEvEx1ByzhqHkzq2FmaWZWwcxqhvteCXXlwSKggaQjASRVkNQl4phc2fcIwWCl88P974GHowvHuSLjZarbTzIT2kvShZJ+E+63kNQn9aE5Fy0z20WwvOJfJM0CZgJHRRqUKw/6mtkIwqnzzGwTUDHakJwrPC9TXTwJl/iU9E+C1+onmFknSXWA/5pZ7+II0LmSTtIzwOuJphqJOf97M6ue2qhcaSXpU4J/nKeZWU9JDQjK3MMjDs25YuFlavmSzIT2/nTuXMG2AP+XPflyfrInXwa+LZaoXGn1IPAK0FDSXcCHwJ+iDcm5YuVlajmSzBtRfzp3zrliJOlQ4ESCQRmTzGxBxCE551xKJDNqPu/T+bnAHSmNyjnnyilJDwDjzMwHKDnnyryEb0TBn86dc664SBoODAE6ErwEGGdm06ONyjnnUiOZpvnsp/P/FU9IzjnnJNUFBgFDgZZm1iHikJxzrsglM1hpBnCHpCWS/iYpM9VBOeecoz1wKMGKNAujDcU551IjqaZ58Kdz55wrDpL+ApwDLAWeJ1heeXOkQTnnXIokM1gpW+zT+fyUROOcc245cKSZfRd1IM45l2rJ9BH1p3PnnCtG4cIhHYDK2WlmNjW6iJxzLjWSeSPqT+fOOVdMJF0BjASaEyyBeATwMXBChGE551xKJDt9kz+dO+dcMZA0B+gNfGJmPcLp835vZkMiDs0554pcwjei/nTunHPFaoeZ7ZCEpEpmtlDSIVEH5ZxzqZDM9E0jCZ7OvzKz44HDgfUpjco558qvVZJqA68C70gaD3wTaUTOOZciyfQR9adz55wrJmZ2dvj1TkmTgVrAWxGG5JxzKZNMRTTv0/km/OncOeeKwyFmNirqIJxzLlWSntAeQNJxhE/nZrYrZVE555xD0gwz6xl1HM45lyrJ9BGNdYiZTfBKqHPOFQtFHYBzzqXSgVZEr05JFM45V85JahEn+Yzw2LHFHI5zzhWLA62I+tO5c86lxvuSfiUptu/+bkn/Bu6NKijnnEulfCui/nTunHPFqhfQDvhC0gmSRgKfEczb3DfSyJxzLkXyHawkaRnwKHCvme0J0xoBfyfoK9q72KJ0zrlyIqyA3kcwO8kRZrYq4pCccy5lCmqa96dz55wrJpJqS3oMuBQ4GXgRmCjJV7FzzpVZCadv8qdz55xLvbAV6hHg/phWqB5h2ldmNizC8JxzLiUK6iPqT+fOOVd8+pnZPdmVUAAzm2lmRwHvRRiXc86lTKI+ov507pxzzjnnUqKgimjz/JrhJV1pZo+nNDLnnHPOOVemHdASn84555xzzhWVA53Q3jnnnHPOuSLhFVHnnHPOORcJr4g655xzzrlIeEXUOeecc85FwiuizjnnnHMuEv8PILnIiLFlyAw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" ] @@ -309,7 +308,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] diff --git a/examples/notebooks/models/thermal-models.ipynb b/examples/notebooks/models/thermal-models.ipynb index d9ffb759bb..46f2ac85a9 100644 --- a/examples/notebooks/models/thermal-models.ipynb +++ b/examples/notebooks/models/thermal-models.ipynb @@ -138,15 +138,7 @@ "cell_type": "code", "execution_count": 4, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The history saving thread hit an unexpected error (OperationalError('disk I/O error')).History will not be written to the database.\n" - ] - } - ], + "outputs": [], "source": [ "# lumped with pouch cell geometry (equivalent to choosing \"x-lumped\" thermal option)\n", "options = {\"cell geometry\": \"pouch\", \"thermal\": \"lumped\"}\n", @@ -260,7 +252,7 @@ "metadata": {}, "outputs": [], "source": [ - "parameter_values = pybamm.ParameterValues("Marquis2019")" + "parameter_values = pybamm.ParameterValues(\"Marquis2019\")" ] }, { @@ -391,7 +383,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6216fb2037704e90ac40a13eef79a112", + "model_id": "ee873b57af934694abc47b15f91f7d87", "version_major": 2, "version_minor": 0 }, @@ -405,7 +397,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 11, @@ -472,8 +464,8 @@ "[2] Marc Doyle, Thomas F. Fuller, and John Newman. Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell. Journal of the Electrochemical society, 140(6):1526–1533, 1993. doi:10.1149/1.2221597.\n", "[3] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n", "[4] Scott G. Marquis, Valentin Sulzer, Robert Timms, Colin P. Please, and S. Jon Chapman. An asymptotic derivation of a single particle model with electrolyte. Journal of The Electrochemical Society, 166(15):A3693–A3706, 2019. doi:10.1149/2.0341915jes.\n", - "[5] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n", - "[6] Robert Timms, Scott G. Marquis, Valentin Sulzer, Colin P. Please, and S. Jon Chapman. Asymptotic Reduction of a Lithium-ion Pouch Cell Model. Submitted for publication, 2020. arXiv:2005.05127.\n", + "[5] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n", + "[6] Robert Timms, Scott G Marquis, Valentin Sulzer, Colin P. Please, and S Jonathan Chapman. Asymptotic Reduction of a Lithium-ion Pouch Cell Model. SIAM Journal on Applied Mathematics, 81(3):765–788, 2021. doi:10.1137/20M1336898.\n", "\n" ] } @@ -485,9 +477,9 @@ ], "metadata": { "kernelspec": { - "display_name": "PyBaMM development (env)", + "display_name": "Python 3 (ipykernel)", "language": "python", - "name": "pybamm-dev" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -499,9 +491,22 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/examples/notebooks/models/using-model-options_thermal-example.ipynb b/examples/notebooks/models/using-model-options_thermal-example.ipynb index c7488a93ac..8db67a8054 100644 --- a/examples/notebooks/models/using-model-options_thermal-example.ipynb +++ b/examples/notebooks/models/using-model-options_thermal-example.ipynb @@ -83,7 +83,7 @@ "metadata": {}, "outputs": [], "source": [ - "param = pybamm.ParameterValues("Marquis2019")\n", + "param = pybamm.ParameterValues(\"Marquis2019\")\n", "param.update(\n", " {\n", " \"Total heat transfer coefficient [W.m-2.K-1]\": 1.0,\n", @@ -196,7 +196,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -210,7 +210,20 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.12" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true } }, "nbformat": 4, diff --git a/examples/notebooks/parameterization/parameter-values.ipynb b/examples/notebooks/parameterization/parameter-values.ipynb index 992e981d70..7a029638ba 100644 --- a/examples/notebooks/parameterization/parameter-values.ipynb +++ b/examples/notebooks/parameterization/parameter-values.ipynb @@ -129,7 +129,7 @@ ], "source": [ "print(\"Marquis2019 chemistry set is {}\".format(pybamm.parameter_sets.Marquis2019))\n", - "chem_parameter_values = pybamm.ParameterValues("Marquis2019")\n", + "chem_parameter_values = pybamm.ParameterValues(\"Marquis2019\")\n", "print(\"Negative current collector thickness is {} m\".format(\n", " chem_parameter_values[\"Negative current collector thickness [m]\"])\n", ")" @@ -512,7 +512,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -526,7 +526,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.8" + "version": "3.8.12" }, "toc": { "base_numbering": 1, diff --git a/examples/notebooks/parameterization/parameterization.ipynb b/examples/notebooks/parameterization/parameterization.ipynb index 8fb6ca343c..6632b24ea6 100644 --- a/examples/notebooks/parameterization/parameterization.ipynb +++ b/examples/notebooks/parameterization/parameterization.ipynb @@ -2185,8 +2185,7 @@ } ], "source": [ - "chemistry = pybamm.parameter_sets.Chen2020\n", - "param_same = pybamm.ParameterValues(chemistry)\n", + "param_same = pybamm.ParameterValues(\"Chen2020\")\n", "{k: v for k,v in param_same.items() if k in spm._parameter_info}" ] }, @@ -2459,7 +2458,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -2473,7 +2472,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.8.12" }, "toc": { "base_numbering": 1, diff --git a/examples/notebooks/simulating-long-experiments.ipynb b/examples/notebooks/simulating-long-experiments.ipynb index d8b18d5741..de16fdccae 100644 --- a/examples/notebooks/simulating-long-experiments.ipynb +++ b/examples/notebooks/simulating-long-experiments.ipynb @@ -21,7 +21,15 @@ "execution_count": 1, "id": "novel-spectacular", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], "source": [ "%pip install pybamm -q\n", "import pybamm\n", @@ -52,7 +60,7 @@ "metadata": {}, "outputs": [], "source": [ - "parameter_values = pybamm.ParameterValues("Mohtat2020")\n", + "parameter_values = pybamm.ParameterValues(\"Mohtat2020\")\n", "parameter_values.update({\"SEI kinetic rate constant [m.s-1]\": 1e-14})\n", "spm = pybamm.lithium_ion.SPM({\"SEI\": \"ec reaction limited\"})" ] @@ -128,12 +136,12 @@ "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:21,963 - [NOTICE] simulation.solve(809): Cycle 1/1 (32.063 ms elapsed) --------------------\n", - "2021-09-17 01:13:21,964 - [NOTICE] simulation.solve(843): Cycle 1/1, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:22,041 - [NOTICE] simulation.solve(843): Cycle 1/1, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:22,087 - [NOTICE] simulation.solve(843): Cycle 1/1, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:22,141 - [NOTICE] simulation.solve(843): Cycle 1/1, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:22,383 - [NOTICE] simulation.solve(938): Finish experiment simulation, took 456.533 ms\n" + "2021-11-19 15:28:37,539 - [NOTICE] simulation.solve(850): Cycle 1/1 (24.919 ms elapsed) --------------------\n", + "2021-11-19 15:28:37,539 - [NOTICE] simulation.solve(884): Cycle 1/1, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:37,582 - [NOTICE] simulation.solve(884): Cycle 1/1, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:37,614 - [NOTICE] simulation.solve(884): Cycle 1/1, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:37,654 - [NOTICE] simulation.solve(884): Cycle 1/1, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:37,836 - [NOTICE] simulation.solve(990): Finish experiment simulation, took 322.213 ms\n" ] } ], @@ -173,361 +181,325 @@ "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:24,591 - [NOTICE] simulation.solve(809): Cycle 1/500 (171.398 ms elapsed) --------------------\n", - "2021-09-17 01:13:24,593 - [NOTICE] simulation.solve(843): Cycle 1/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:24,635 - [NOTICE] simulation.solve(843): Cycle 1/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:24,684 - [NOTICE] simulation.solve(843): Cycle 1/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:24,731 - [NOTICE] simulation.solve(843): Cycle 1/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:24,952 - [NOTICE] simulation.solve(921): Capacity is now 4.943 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:24,952 - [NOTICE] simulation.solve(809): Cycle 2/500 (544.763 ms elapsed) --------------------\n", - "2021-09-17 01:13:24,952 - [NOTICE] simulation.solve(843): Cycle 2/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:24,999 - [NOTICE] simulation.solve(843): Cycle 2/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:25,025 - [NOTICE] simulation.solve(843): Cycle 2/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:25,054 - [NOTICE] simulation.solve(843): Cycle 2/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:25,083 - [NOTICE] simulation.solve(921): Capacity is now 4.917 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:25,083 - [NOTICE] simulation.solve(809): Cycle 3/500 (667.741 ms elapsed) --------------------\n", - "2021-09-17 01:13:25,083 - [NOTICE] simulation.solve(843): Cycle 3/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:25,117 - [NOTICE] simulation.solve(843): Cycle 3/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:25,144 - [NOTICE] simulation.solve(843): Cycle 3/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:25,174 - [NOTICE] simulation.solve(843): Cycle 3/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:25,209 - [NOTICE] simulation.solve(921): Capacity is now 4.891 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:25,209 - [NOTICE] simulation.solve(809): Cycle 4/500 (790.023 ms elapsed) --------------------\n", - "2021-09-17 01:13:25,209 - [NOTICE] simulation.solve(843): Cycle 4/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:25,242 - [NOTICE] simulation.solve(843): Cycle 4/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:25,267 - [NOTICE] simulation.solve(843): Cycle 4/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:25,297 - [NOTICE] simulation.solve(843): Cycle 4/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:25,325 - [NOTICE] simulation.solve(921): Capacity is now 4.867 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:25,333 - [NOTICE] simulation.solve(809): Cycle 5/500 (913.531 ms elapsed) --------------------\n", - "2021-09-17 01:13:25,333 - [NOTICE] simulation.solve(843): Cycle 5/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:25,367 - [NOTICE] simulation.solve(843): Cycle 5/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:25,391 - [NOTICE] simulation.solve(843): Cycle 5/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:25,422 - [NOTICE] simulation.solve(843): Cycle 5/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:25,450 - [NOTICE] simulation.solve(921): Capacity is now 4.842 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:25,450 - [NOTICE] simulation.solve(809): Cycle 6/500 (1.037 s elapsed) --------------------\n", - "2021-09-17 01:13:25,450 - [NOTICE] simulation.solve(843): Cycle 6/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:25,490 - [NOTICE] simulation.solve(843): Cycle 6/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:25,513 - [NOTICE] simulation.solve(843): Cycle 6/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:25,540 - [NOTICE] simulation.solve(843): Cycle 6/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:25,574 - [NOTICE] simulation.solve(921): Capacity is now 4.818 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:25,575 - [NOTICE] simulation.solve(809): Cycle 7/500 (1.156 s elapsed) --------------------\n", - "2021-09-17 01:13:25,575 - [NOTICE] simulation.solve(843): Cycle 7/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:25,603 - [NOTICE] simulation.solve(843): Cycle 7/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:25,631 - [NOTICE] simulation.solve(843): Cycle 7/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:25,650 - [NOTICE] simulation.solve(843): Cycle 7/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:25,693 - [NOTICE] simulation.solve(921): Capacity is now 4.794 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:25,694 - [NOTICE] simulation.solve(809): Cycle 8/500 (1.274 s elapsed) --------------------\n", - "2021-09-17 01:13:25,694 - [NOTICE] simulation.solve(843): Cycle 8/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:25,722 - [NOTICE] simulation.solve(843): Cycle 8/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:25,747 - [NOTICE] simulation.solve(843): Cycle 8/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:25,772 - [NOTICE] simulation.solve(843): Cycle 8/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:25,806 - [NOTICE] simulation.solve(921): Capacity is now 4.771 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:25,807 - [NOTICE] simulation.solve(809): Cycle 9/500 (1.388 s elapsed) --------------------\n", - "2021-09-17 01:13:25,808 - [NOTICE] simulation.solve(843): Cycle 9/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:25,838 - [NOTICE] simulation.solve(843): Cycle 9/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:25,850 - [NOTICE] simulation.solve(843): Cycle 9/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:25,887 - [NOTICE] simulation.solve(843): Cycle 9/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:25,922 - [NOTICE] simulation.solve(921): Capacity is now 4.748 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:25,923 - [NOTICE] simulation.solve(809): Cycle 10/500 (1.503 s elapsed) --------------------\n", - "2021-09-17 01:13:25,923 - [NOTICE] simulation.solve(843): Cycle 10/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:25,955 - [NOTICE] simulation.solve(843): Cycle 10/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:25,979 - [NOTICE] simulation.solve(843): Cycle 10/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:26,008 - [NOTICE] simulation.solve(843): Cycle 10/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:26,042 - [NOTICE] simulation.solve(921): Capacity is now 4.725 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:26,042 - [NOTICE] simulation.solve(809): Cycle 11/500 (1.626 s elapsed) --------------------\n", - "2021-09-17 01:13:26,042 - [NOTICE] simulation.solve(843): Cycle 11/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:26,075 - [NOTICE] simulation.solve(843): Cycle 11/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:26,091 - [NOTICE] simulation.solve(843): Cycle 11/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:26,130 - [NOTICE] simulation.solve(843): Cycle 11/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:26,151 - [NOTICE] simulation.solve(921): Capacity is now 4.703 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:26,151 - [NOTICE] simulation.solve(809): Cycle 12/500 (1.746 s elapsed) --------------------\n", - "2021-09-17 01:13:26,151 - [NOTICE] simulation.solve(843): Cycle 12/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:26,199 - [NOTICE] simulation.solve(843): Cycle 12/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:26,223 - [NOTICE] simulation.solve(843): Cycle 12/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:26,250 - [NOTICE] simulation.solve(843): Cycle 12/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:26,288 - [NOTICE] simulation.solve(921): Capacity is now 4.681 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:26,290 - [NOTICE] simulation.solve(809): Cycle 13/500 (1.870 s elapsed) --------------------\n", - "2021-09-17 01:13:26,290 - [NOTICE] simulation.solve(843): Cycle 13/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:26,320 - [NOTICE] simulation.solve(843): Cycle 13/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:26,336 - [NOTICE] simulation.solve(843): Cycle 13/500, step 3/4: Charge at 1C until 4.2V\n" + "2021-11-19 15:28:39,407 - [NOTICE] simulation.solve(850): Cycle 1/500 (30.887 ms elapsed) --------------------\n", + "2021-11-19 15:28:39,408 - [NOTICE] simulation.solve(884): Cycle 1/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:39,484 - [NOTICE] simulation.solve(884): Cycle 1/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:39,587 - [NOTICE] simulation.solve(884): Cycle 1/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:39,832 - [NOTICE] simulation.solve(884): Cycle 1/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:40,361 - [NOTICE] simulation.solve(972): Capacity is now 4.940 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:40,361 - [NOTICE] simulation.solve(850): Cycle 2/500 (984.937 ms elapsed) --------------------\n", + "2021-11-19 15:28:40,361 - [NOTICE] simulation.solve(884): Cycle 2/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:40,390 - [NOTICE] simulation.solve(884): Cycle 2/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:40,412 - [NOTICE] simulation.solve(884): Cycle 2/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:40,442 - [NOTICE] simulation.solve(884): Cycle 2/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:40,475 - [NOTICE] simulation.solve(972): Capacity is now 4.913 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:40,475 - [NOTICE] simulation.solve(850): Cycle 3/500 (1.099 s elapsed) --------------------\n", + "2021-11-19 15:28:40,476 - [NOTICE] simulation.solve(884): Cycle 3/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:40,501 - [NOTICE] simulation.solve(884): Cycle 3/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:40,520 - [NOTICE] simulation.solve(884): Cycle 3/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:40,545 - [NOTICE] simulation.solve(884): Cycle 3/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:40,578 - [NOTICE] simulation.solve(972): Capacity is now 4.885 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:40,578 - [NOTICE] simulation.solve(850): Cycle 4/500 (1.202 s elapsed) --------------------\n", + "2021-11-19 15:28:40,578 - [NOTICE] simulation.solve(884): Cycle 4/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:40,604 - [NOTICE] simulation.solve(884): Cycle 4/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:40,625 - [NOTICE] simulation.solve(884): Cycle 4/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:40,651 - [NOTICE] simulation.solve(884): Cycle 4/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:40,687 - [NOTICE] simulation.solve(972): Capacity is now 4.858 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:40,688 - [NOTICE] simulation.solve(850): Cycle 5/500 (1.311 s elapsed) --------------------\n", + "2021-11-19 15:28:40,688 - [NOTICE] simulation.solve(884): Cycle 5/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:40,715 - [NOTICE] simulation.solve(884): Cycle 5/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:40,735 - [NOTICE] simulation.solve(884): Cycle 5/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:40,759 - [NOTICE] simulation.solve(884): Cycle 5/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:40,794 - [NOTICE] simulation.solve(972): Capacity is now 4.832 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:40,794 - [NOTICE] simulation.solve(850): Cycle 6/500 (1.418 s elapsed) --------------------\n", + "2021-11-19 15:28:40,795 - [NOTICE] simulation.solve(884): Cycle 6/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:40,817 - [NOTICE] simulation.solve(884): Cycle 6/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:40,837 - [NOTICE] simulation.solve(884): Cycle 6/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:40,858 - [NOTICE] simulation.solve(884): Cycle 6/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:40,894 - [NOTICE] simulation.solve(972): Capacity is now 4.806 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:40,895 - [NOTICE] simulation.solve(850): Cycle 7/500 (1.518 s elapsed) --------------------\n", + "2021-11-19 15:28:40,895 - [NOTICE] simulation.solve(884): Cycle 7/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:40,919 - [NOTICE] simulation.solve(884): Cycle 7/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:40,938 - [NOTICE] simulation.solve(884): Cycle 7/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:40,958 - [NOTICE] simulation.solve(884): Cycle 7/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:40,991 - [NOTICE] simulation.solve(972): Capacity is now 4.780 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:40,992 - [NOTICE] simulation.solve(850): Cycle 8/500 (1.616 s elapsed) --------------------\n", + "2021-11-19 15:28:40,992 - [NOTICE] simulation.solve(884): Cycle 8/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:41,015 - [NOTICE] simulation.solve(884): Cycle 8/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:41,033 - [NOTICE] simulation.solve(884): Cycle 8/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:41,055 - [NOTICE] simulation.solve(884): Cycle 8/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:41,088 - [NOTICE] simulation.solve(972): Capacity is now 4.755 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:41,089 - [NOTICE] simulation.solve(850): Cycle 9/500 (1.713 s elapsed) --------------------\n", + "2021-11-19 15:28:41,089 - [NOTICE] simulation.solve(884): Cycle 9/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:41,113 - [NOTICE] simulation.solve(884): Cycle 9/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:41,131 - [NOTICE] simulation.solve(884): Cycle 9/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:41,154 - [NOTICE] simulation.solve(884): Cycle 9/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:41,188 - [NOTICE] simulation.solve(972): Capacity is now 4.731 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:41,188 - [NOTICE] simulation.solve(850): Cycle 10/500 (1.812 s elapsed) --------------------\n", + "2021-11-19 15:28:41,189 - [NOTICE] simulation.solve(884): Cycle 10/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:41,213 - [NOTICE] simulation.solve(884): Cycle 10/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:41,232 - [NOTICE] simulation.solve(884): Cycle 10/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:41,254 - [NOTICE] simulation.solve(884): Cycle 10/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:41,289 - [NOTICE] simulation.solve(972): Capacity is now 4.706 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:41,289 - [NOTICE] simulation.solve(850): Cycle 11/500 (1.913 s elapsed) --------------------\n", + "2021-11-19 15:28:41,290 - [NOTICE] simulation.solve(884): Cycle 11/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:41,314 - [NOTICE] simulation.solve(884): Cycle 11/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:41,334 - [NOTICE] simulation.solve(884): Cycle 11/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:41,358 - [NOTICE] simulation.solve(884): Cycle 11/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:41,394 - [NOTICE] simulation.solve(972): Capacity is now 4.682 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:41,395 - [NOTICE] simulation.solve(850): Cycle 12/500 (2.018 s elapsed) --------------------\n", + "2021-11-19 15:28:41,395 - [NOTICE] simulation.solve(884): Cycle 12/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:41,420 - [NOTICE] simulation.solve(884): Cycle 12/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:41,439 - [NOTICE] simulation.solve(884): Cycle 12/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:41,459 - [NOTICE] simulation.solve(884): Cycle 12/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:41,496 - [NOTICE] simulation.solve(972): Capacity is now 4.659 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:41,497 - [NOTICE] simulation.solve(850): Cycle 13/500 (2.121 s elapsed) --------------------\n", + "2021-11-19 15:28:41,498 - [NOTICE] simulation.solve(884): Cycle 13/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:41,519 - [NOTICE] simulation.solve(884): Cycle 13/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:41,538 - [NOTICE] simulation.solve(884): Cycle 13/500, step 3/4: Charge at 1C until 4.2V\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:26,368 - [NOTICE] simulation.solve(843): Cycle 13/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:26,404 - [NOTICE] simulation.solve(921): Capacity is now 4.660 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:26,404 - [NOTICE] simulation.solve(809): Cycle 14/500 (1.984 s elapsed) --------------------\n", - "2021-09-17 01:13:26,405 - [NOTICE] simulation.solve(843): Cycle 14/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:26,434 - [NOTICE] simulation.solve(843): Cycle 14/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:26,457 - [NOTICE] simulation.solve(843): Cycle 14/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:26,473 - [NOTICE] simulation.solve(843): Cycle 14/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:26,523 - [NOTICE] simulation.solve(921): Capacity is now 4.638 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:26,525 - [NOTICE] simulation.solve(809): Cycle 15/500 (2.106 s elapsed) --------------------\n", - "2021-09-17 01:13:26,525 - [NOTICE] simulation.solve(843): Cycle 15/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:26,556 - [NOTICE] simulation.solve(843): Cycle 15/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:26,580 - [NOTICE] simulation.solve(843): Cycle 15/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:26,609 - [NOTICE] simulation.solve(843): Cycle 15/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:26,644 - [NOTICE] simulation.solve(921): Capacity is now 4.617 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:26,644 - [NOTICE] simulation.solve(809): Cycle 16/500 (2.231 s elapsed) --------------------\n", - "2021-09-17 01:13:26,644 - [NOTICE] simulation.solve(843): Cycle 16/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:26,679 - [NOTICE] simulation.solve(843): Cycle 16/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:26,705 - [NOTICE] simulation.solve(843): Cycle 16/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:26,730 - [NOTICE] simulation.solve(843): Cycle 16/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:26,759 - [NOTICE] simulation.solve(921): Capacity is now 4.597 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:26,759 - [NOTICE] simulation.solve(809): Cycle 17/500 (2.345 s elapsed) --------------------\n", - "2021-09-17 01:13:26,759 - [NOTICE] simulation.solve(843): Cycle 17/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:26,795 - [NOTICE] simulation.solve(843): Cycle 17/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:26,818 - [NOTICE] simulation.solve(843): Cycle 17/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:26,847 - [NOTICE] simulation.solve(843): Cycle 17/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:26,875 - [NOTICE] simulation.solve(921): Capacity is now 4.576 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:26,875 - [NOTICE] simulation.solve(809): Cycle 18/500 (2.464 s elapsed) --------------------\n", - "2021-09-17 01:13:26,875 - [NOTICE] simulation.solve(843): Cycle 18/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:26,915 - [NOTICE] simulation.solve(843): Cycle 18/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:26,938 - [NOTICE] simulation.solve(843): Cycle 18/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:26,965 - [NOTICE] simulation.solve(843): Cycle 18/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:27,002 - [NOTICE] simulation.solve(921): Capacity is now 4.556 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:27,003 - [NOTICE] simulation.solve(809): Cycle 19/500 (2.583 s elapsed) --------------------\n", - "2021-09-17 01:13:27,003 - [NOTICE] simulation.solve(843): Cycle 19/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:27,032 - [NOTICE] simulation.solve(843): Cycle 19/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:27,058 - [NOTICE] simulation.solve(843): Cycle 19/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:27,084 - [NOTICE] simulation.solve(843): Cycle 19/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:27,118 - [NOTICE] simulation.solve(921): Capacity is now 4.536 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:27,118 - [NOTICE] simulation.solve(809): Cycle 20/500 (2.702 s elapsed) --------------------\n", - "2021-09-17 01:13:27,118 - [NOTICE] simulation.solve(843): Cycle 20/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:27,152 - [NOTICE] simulation.solve(843): Cycle 20/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:27,175 - [NOTICE] simulation.solve(843): Cycle 20/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:27,203 - [NOTICE] simulation.solve(843): Cycle 20/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:27,238 - [NOTICE] simulation.solve(921): Capacity is now 4.516 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:27,239 - [NOTICE] simulation.solve(809): Cycle 21/500 (2.819 s elapsed) --------------------\n", - "2021-09-17 01:13:27,240 - [NOTICE] simulation.solve(843): Cycle 21/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:27,268 - [NOTICE] simulation.solve(843): Cycle 21/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:27,293 - [NOTICE] simulation.solve(843): Cycle 21/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:27,318 - [NOTICE] simulation.solve(843): Cycle 21/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:27,351 - [NOTICE] simulation.solve(921): Capacity is now 4.497 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:27,351 - [NOTICE] simulation.solve(809): Cycle 22/500 (2.935 s elapsed) --------------------\n", - "2021-09-17 01:13:27,351 - [NOTICE] simulation.solve(843): Cycle 22/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:27,382 - [NOTICE] simulation.solve(843): Cycle 22/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:27,406 - [NOTICE] simulation.solve(843): Cycle 22/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:27,430 - [NOTICE] simulation.solve(843): Cycle 22/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:27,466 - [NOTICE] simulation.solve(921): Capacity is now 4.478 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:27,467 - [NOTICE] simulation.solve(809): Cycle 23/500 (3.047 s elapsed) --------------------\n", - "2021-09-17 01:13:27,468 - [NOTICE] simulation.solve(843): Cycle 23/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:27,495 - [NOTICE] simulation.solve(843): Cycle 23/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:27,517 - [NOTICE] simulation.solve(843): Cycle 23/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:27,543 - [NOTICE] simulation.solve(843): Cycle 23/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:27,576 - [NOTICE] simulation.solve(921): Capacity is now 4.459 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:27,576 - [NOTICE] simulation.solve(809): Cycle 24/500 (3.161 s elapsed) --------------------\n", - "2021-09-17 01:13:27,576 - [NOTICE] simulation.solve(843): Cycle 24/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:27,608 - [NOTICE] simulation.solve(843): Cycle 24/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:27,632 - [NOTICE] simulation.solve(843): Cycle 24/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:27,642 - [NOTICE] simulation.solve(843): Cycle 24/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:27,691 - [NOTICE] simulation.solve(921): Capacity is now 4.440 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:27,692 - [NOTICE] simulation.solve(809): Cycle 25/500 (3.272 s elapsed) --------------------\n", - "2021-09-17 01:13:27,692 - [NOTICE] simulation.solve(843): Cycle 25/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:27,720 - [NOTICE] simulation.solve(843): Cycle 25/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:27,742 - [NOTICE] simulation.solve(843): Cycle 25/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:27,768 - [NOTICE] simulation.solve(843): Cycle 25/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:27,801 - [NOTICE] simulation.solve(921): Capacity is now 4.421 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:27,801 - [NOTICE] simulation.solve(809): Cycle 26/500 (3.384 s elapsed) --------------------\n" + "2021-11-19 15:28:41,558 - [NOTICE] simulation.solve(884): Cycle 13/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:41,594 - [NOTICE] simulation.solve(972): Capacity is now 4.636 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:41,594 - [NOTICE] simulation.solve(850): Cycle 14/500 (2.218 s elapsed) --------------------\n", + "2021-11-19 15:28:41,594 - [NOTICE] simulation.solve(884): Cycle 14/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:41,616 - [NOTICE] simulation.solve(884): Cycle 14/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:41,635 - [NOTICE] simulation.solve(884): Cycle 14/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:41,655 - [NOTICE] simulation.solve(884): Cycle 14/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:41,688 - [NOTICE] simulation.solve(972): Capacity is now 4.613 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:41,689 - [NOTICE] simulation.solve(850): Cycle 15/500 (2.312 s elapsed) --------------------\n", + "2021-11-19 15:28:41,689 - [NOTICE] simulation.solve(884): Cycle 15/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:41,710 - [NOTICE] simulation.solve(884): Cycle 15/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:41,728 - [NOTICE] simulation.solve(884): Cycle 15/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:41,749 - [NOTICE] simulation.solve(884): Cycle 15/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:41,783 - [NOTICE] simulation.solve(972): Capacity is now 4.590 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:41,783 - [NOTICE] simulation.solve(850): Cycle 16/500 (2.407 s elapsed) --------------------\n", + "2021-11-19 15:28:41,783 - [NOTICE] simulation.solve(884): Cycle 16/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:41,806 - [NOTICE] simulation.solve(884): Cycle 16/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:41,824 - [NOTICE] simulation.solve(884): Cycle 16/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:41,845 - [NOTICE] simulation.solve(884): Cycle 16/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:41,879 - [NOTICE] simulation.solve(972): Capacity is now 4.568 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:41,879 - [NOTICE] simulation.solve(850): Cycle 17/500 (2.503 s elapsed) --------------------\n", + "2021-11-19 15:28:41,880 - [NOTICE] simulation.solve(884): Cycle 17/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:41,903 - [NOTICE] simulation.solve(884): Cycle 17/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:41,922 - [NOTICE] simulation.solve(884): Cycle 17/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:41,943 - [NOTICE] simulation.solve(884): Cycle 17/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:41,976 - [NOTICE] simulation.solve(972): Capacity is now 4.546 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:41,977 - [NOTICE] simulation.solve(850): Cycle 18/500 (2.600 s elapsed) --------------------\n", + "2021-11-19 15:28:41,977 - [NOTICE] simulation.solve(884): Cycle 18/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:42,000 - [NOTICE] simulation.solve(884): Cycle 18/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:42,019 - [NOTICE] simulation.solve(884): Cycle 18/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:42,042 - [NOTICE] simulation.solve(884): Cycle 18/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:42,075 - [NOTICE] simulation.solve(972): Capacity is now 4.524 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:42,076 - [NOTICE] simulation.solve(850): Cycle 19/500 (2.699 s elapsed) --------------------\n", + "2021-11-19 15:28:42,076 - [NOTICE] simulation.solve(884): Cycle 19/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:42,099 - [NOTICE] simulation.solve(884): Cycle 19/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:42,118 - [NOTICE] simulation.solve(884): Cycle 19/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:42,137 - [NOTICE] simulation.solve(884): Cycle 19/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:42,170 - [NOTICE] simulation.solve(972): Capacity is now 4.503 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:42,171 - [NOTICE] simulation.solve(850): Cycle 20/500 (2.795 s elapsed) --------------------\n", + "2021-11-19 15:28:42,171 - [NOTICE] simulation.solve(884): Cycle 20/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:42,191 - [NOTICE] simulation.solve(884): Cycle 20/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:42,210 - [NOTICE] simulation.solve(884): Cycle 20/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:42,232 - [NOTICE] simulation.solve(884): Cycle 20/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:42,295 - [NOTICE] simulation.solve(972): Capacity is now 4.482 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:42,296 - [NOTICE] simulation.solve(850): Cycle 21/500 (2.920 s elapsed) --------------------\n", + "2021-11-19 15:28:42,296 - [NOTICE] simulation.solve(884): Cycle 21/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:42,332 - [NOTICE] simulation.solve(884): Cycle 21/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:42,370 - [NOTICE] simulation.solve(884): Cycle 21/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:42,403 - [NOTICE] simulation.solve(884): Cycle 21/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:42,597 - [NOTICE] simulation.solve(972): Capacity is now 4.461 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:42,598 - [NOTICE] simulation.solve(850): Cycle 22/500 (3.221 s elapsed) --------------------\n", + "2021-11-19 15:28:42,598 - [NOTICE] simulation.solve(884): Cycle 22/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:42,622 - [NOTICE] simulation.solve(884): Cycle 22/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:42,645 - [NOTICE] simulation.solve(884): Cycle 22/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:42,671 - [NOTICE] simulation.solve(884): Cycle 22/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:42,716 - [NOTICE] simulation.solve(972): Capacity is now 4.440 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:42,717 - [NOTICE] simulation.solve(850): Cycle 23/500 (3.341 s elapsed) --------------------\n", + "2021-11-19 15:28:42,717 - [NOTICE] simulation.solve(884): Cycle 23/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:42,751 - [NOTICE] simulation.solve(884): Cycle 23/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:42,779 - [NOTICE] simulation.solve(884): Cycle 23/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:42,806 - [NOTICE] simulation.solve(884): Cycle 23/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:42,854 - [NOTICE] simulation.solve(972): Capacity is now 4.420 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:42,855 - [NOTICE] simulation.solve(850): Cycle 24/500 (3.478 s elapsed) --------------------\n", + "2021-11-19 15:28:42,856 - [NOTICE] simulation.solve(884): Cycle 24/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:42,885 - [NOTICE] simulation.solve(884): Cycle 24/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:42,916 - [NOTICE] simulation.solve(884): Cycle 24/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:42,970 - [NOTICE] simulation.solve(884): Cycle 24/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:43,032 - [NOTICE] simulation.solve(972): Capacity is now 4.400 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:43,032 - [NOTICE] simulation.solve(850): Cycle 25/500 (3.656 s elapsed) --------------------\n", + "2021-11-19 15:28:43,033 - [NOTICE] simulation.solve(884): Cycle 25/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:43,085 - [NOTICE] simulation.solve(884): Cycle 25/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:43,118 - [NOTICE] simulation.solve(884): Cycle 25/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:43,153 - [NOTICE] simulation.solve(884): Cycle 25/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:43,213 - [NOTICE] simulation.solve(972): Capacity is now 4.380 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:43,214 - [NOTICE] simulation.solve(850): Cycle 26/500 (3.837 s elapsed) --------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:27,801 - [NOTICE] simulation.solve(843): Cycle 26/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:27,834 - [NOTICE] simulation.solve(843): Cycle 26/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:27,859 - [NOTICE] simulation.solve(843): Cycle 26/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:27,885 - [NOTICE] simulation.solve(843): Cycle 26/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:27,918 - [NOTICE] simulation.solve(921): Capacity is now 4.403 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:27,918 - [NOTICE] simulation.solve(809): Cycle 27/500 (3.501 s elapsed) --------------------\n", - "2021-09-17 01:13:27,918 - [NOTICE] simulation.solve(843): Cycle 27/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:27,949 - [NOTICE] simulation.solve(843): Cycle 27/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:27,972 - [NOTICE] simulation.solve(843): Cycle 27/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:28,001 - [NOTICE] simulation.solve(843): Cycle 27/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:28,033 - [NOTICE] simulation.solve(921): Capacity is now 4.385 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:28,035 - [NOTICE] simulation.solve(809): Cycle 28/500 (3.615 s elapsed) --------------------\n", - "2021-09-17 01:13:28,035 - [NOTICE] simulation.solve(843): Cycle 28/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:28,064 - [NOTICE] simulation.solve(843): Cycle 28/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:28,090 - [NOTICE] simulation.solve(843): Cycle 28/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:28,108 - [NOTICE] simulation.solve(843): Cycle 28/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:28,149 - [NOTICE] simulation.solve(921): Capacity is now 4.367 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:28,150 - [NOTICE] simulation.solve(809): Cycle 29/500 (3.731 s elapsed) --------------------\n", - "2021-09-17 01:13:28,150 - [NOTICE] simulation.solve(843): Cycle 29/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:28,180 - [NOTICE] simulation.solve(843): Cycle 29/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:28,203 - [NOTICE] simulation.solve(843): Cycle 29/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:28,227 - [NOTICE] simulation.solve(843): Cycle 29/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:28,259 - [NOTICE] simulation.solve(921): Capacity is now 4.349 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:28,259 - [NOTICE] simulation.solve(809): Cycle 30/500 (3.843 s elapsed) --------------------\n", - "2021-09-17 01:13:28,259 - [NOTICE] simulation.solve(843): Cycle 30/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:28,292 - [NOTICE] simulation.solve(843): Cycle 30/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:28,317 - [NOTICE] simulation.solve(843): Cycle 30/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:28,340 - [NOTICE] simulation.solve(843): Cycle 30/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:28,375 - [NOTICE] simulation.solve(921): Capacity is now 4.331 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:28,376 - [NOTICE] simulation.solve(809): Cycle 31/500 (3.957 s elapsed) --------------------\n", - "2021-09-17 01:13:28,376 - [NOTICE] simulation.solve(843): Cycle 31/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:28,401 - [NOTICE] simulation.solve(843): Cycle 31/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:28,424 - [NOTICE] simulation.solve(843): Cycle 31/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:28,447 - [NOTICE] simulation.solve(843): Cycle 31/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:28,482 - [NOTICE] simulation.solve(921): Capacity is now 4.314 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:28,483 - [NOTICE] simulation.solve(809): Cycle 32/500 (4.063 s elapsed) --------------------\n", - "2021-09-17 01:13:28,484 - [NOTICE] simulation.solve(843): Cycle 32/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:28,509 - [NOTICE] simulation.solve(843): Cycle 32/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:28,517 - [NOTICE] simulation.solve(843): Cycle 32/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:28,554 - [NOTICE] simulation.solve(843): Cycle 32/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:28,590 - [NOTICE] simulation.solve(921): Capacity is now 4.297 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:28,592 - [NOTICE] simulation.solve(809): Cycle 33/500 (4.172 s elapsed) --------------------\n", - "2021-09-17 01:13:28,593 - [NOTICE] simulation.solve(843): Cycle 33/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:28,622 - [NOTICE] simulation.solve(843): Cycle 33/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:28,642 - [NOTICE] simulation.solve(843): Cycle 33/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:28,671 - [NOTICE] simulation.solve(843): Cycle 33/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:28,707 - [NOTICE] simulation.solve(921): Capacity is now 4.280 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:28,708 - [NOTICE] simulation.solve(809): Cycle 34/500 (4.288 s elapsed) --------------------\n", - "2021-09-17 01:13:28,708 - [NOTICE] simulation.solve(843): Cycle 34/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:28,734 - [NOTICE] simulation.solve(843): Cycle 34/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:28,757 - [NOTICE] simulation.solve(843): Cycle 34/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:28,768 - [NOTICE] simulation.solve(843): Cycle 34/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:28,816 - [NOTICE] simulation.solve(921): Capacity is now 4.263 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:28,817 - [NOTICE] simulation.solve(809): Cycle 35/500 (4.397 s elapsed) --------------------\n", - "2021-09-17 01:13:28,818 - [NOTICE] simulation.solve(843): Cycle 35/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:28,845 - [NOTICE] simulation.solve(843): Cycle 35/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:28,870 - [NOTICE] simulation.solve(843): Cycle 35/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:28,896 - [NOTICE] simulation.solve(843): Cycle 35/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:28,927 - [NOTICE] simulation.solve(921): Capacity is now 4.246 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:28,927 - [NOTICE] simulation.solve(809): Cycle 36/500 (4.511 s elapsed) --------------------\n", - "2021-09-17 01:13:28,927 - [NOTICE] simulation.solve(843): Cycle 36/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:28,959 - [NOTICE] simulation.solve(843): Cycle 36/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:28,983 - [NOTICE] simulation.solve(843): Cycle 36/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:29,008 - [NOTICE] simulation.solve(843): Cycle 36/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:29,042 - [NOTICE] simulation.solve(921): Capacity is now 4.230 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:29,043 - [NOTICE] simulation.solve(809): Cycle 37/500 (4.623 s elapsed) --------------------\n", - "2021-09-17 01:13:29,044 - [NOTICE] simulation.solve(843): Cycle 37/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:29,072 - [NOTICE] simulation.solve(843): Cycle 37/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:29,098 - [NOTICE] simulation.solve(843): Cycle 37/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:29,123 - [NOTICE] simulation.solve(843): Cycle 37/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:29,151 - [NOTICE] simulation.solve(921): Capacity is now 4.213 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:29,151 - [NOTICE] simulation.solve(809): Cycle 38/500 (4.737 s elapsed) --------------------\n", - "2021-09-17 01:13:29,151 - [NOTICE] simulation.solve(843): Cycle 38/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:29,187 - [NOTICE] simulation.solve(843): Cycle 38/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:29,211 - [NOTICE] simulation.solve(843): Cycle 38/500, step 3/4: Charge at 1C until 4.2V\n" + "2021-11-19 15:28:43,214 - [NOTICE] simulation.solve(884): Cycle 26/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:43,261 - [NOTICE] simulation.solve(884): Cycle 26/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:43,293 - [NOTICE] simulation.solve(884): Cycle 26/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:43,342 - [NOTICE] simulation.solve(884): Cycle 26/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:43,412 - [NOTICE] simulation.solve(972): Capacity is now 4.360 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:43,413 - [NOTICE] simulation.solve(850): Cycle 27/500 (4.036 s elapsed) --------------------\n", + "2021-11-19 15:28:43,413 - [NOTICE] simulation.solve(884): Cycle 27/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:43,456 - [NOTICE] simulation.solve(884): Cycle 27/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:43,482 - [NOTICE] simulation.solve(884): Cycle 27/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:43,508 - [NOTICE] simulation.solve(884): Cycle 27/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:43,550 - [NOTICE] simulation.solve(972): Capacity is now 4.341 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:43,551 - [NOTICE] simulation.solve(850): Cycle 28/500 (4.175 s elapsed) --------------------\n", + "2021-11-19 15:28:43,551 - [NOTICE] simulation.solve(884): Cycle 28/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:43,577 - [NOTICE] simulation.solve(884): Cycle 28/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:43,598 - [NOTICE] simulation.solve(884): Cycle 28/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:43,621 - [NOTICE] simulation.solve(884): Cycle 28/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:43,668 - [NOTICE] simulation.solve(972): Capacity is now 4.321 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:43,669 - [NOTICE] simulation.solve(850): Cycle 29/500 (4.293 s elapsed) --------------------\n", + "2021-11-19 15:28:43,669 - [NOTICE] simulation.solve(884): Cycle 29/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:43,698 - [NOTICE] simulation.solve(884): Cycle 29/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:43,739 - [NOTICE] simulation.solve(884): Cycle 29/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:43,769 - [NOTICE] simulation.solve(884): Cycle 29/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:43,837 - [NOTICE] simulation.solve(972): Capacity is now 4.302 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:43,838 - [NOTICE] simulation.solve(850): Cycle 30/500 (4.462 s elapsed) --------------------\n", + "2021-11-19 15:28:43,839 - [NOTICE] simulation.solve(884): Cycle 30/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:43,895 - [NOTICE] simulation.solve(884): Cycle 30/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:43,926 - [NOTICE] simulation.solve(884): Cycle 30/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:43,963 - [NOTICE] simulation.solve(884): Cycle 30/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:44,032 - [NOTICE] simulation.solve(972): Capacity is now 4.284 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:44,036 - [NOTICE] simulation.solve(850): Cycle 31/500 (4.660 s elapsed) --------------------\n", + "2021-11-19 15:28:44,038 - [NOTICE] simulation.solve(884): Cycle 31/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:44,080 - [NOTICE] simulation.solve(884): Cycle 31/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:44,118 - [NOTICE] simulation.solve(884): Cycle 31/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:44,158 - [NOTICE] simulation.solve(884): Cycle 31/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:44,206 - [NOTICE] simulation.solve(972): Capacity is now 4.265 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:44,206 - [NOTICE] simulation.solve(850): Cycle 32/500 (4.830 s elapsed) --------------------\n", + "2021-11-19 15:28:44,207 - [NOTICE] simulation.solve(884): Cycle 32/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:44,240 - [NOTICE] simulation.solve(884): Cycle 32/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:44,279 - [NOTICE] simulation.solve(884): Cycle 32/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:44,306 - [NOTICE] simulation.solve(884): Cycle 32/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:44,349 - [NOTICE] simulation.solve(972): Capacity is now 4.247 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:44,350 - [NOTICE] simulation.solve(850): Cycle 33/500 (4.974 s elapsed) --------------------\n", + "2021-11-19 15:28:44,350 - [NOTICE] simulation.solve(884): Cycle 33/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:44,374 - [NOTICE] simulation.solve(884): Cycle 33/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:44,396 - [NOTICE] simulation.solve(884): Cycle 33/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:44,418 - [NOTICE] simulation.solve(884): Cycle 33/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:44,454 - [NOTICE] simulation.solve(972): Capacity is now 4.228 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:44,455 - [NOTICE] simulation.solve(850): Cycle 34/500 (5.079 s elapsed) --------------------\n", + "2021-11-19 15:28:44,455 - [NOTICE] simulation.solve(884): Cycle 34/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:44,480 - [NOTICE] simulation.solve(884): Cycle 34/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:44,500 - [NOTICE] simulation.solve(884): Cycle 34/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:44,522 - [NOTICE] simulation.solve(884): Cycle 34/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:44,556 - [NOTICE] simulation.solve(972): Capacity is now 4.210 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:44,557 - [NOTICE] simulation.solve(850): Cycle 35/500 (5.181 s elapsed) --------------------\n", + "2021-11-19 15:28:44,557 - [NOTICE] simulation.solve(884): Cycle 35/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:44,579 - [NOTICE] simulation.solve(884): Cycle 35/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:44,599 - [NOTICE] simulation.solve(884): Cycle 35/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:44,620 - [NOTICE] simulation.solve(884): Cycle 35/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:44,654 - [NOTICE] simulation.solve(972): Capacity is now 4.192 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:44,654 - [NOTICE] simulation.solve(850): Cycle 36/500 (5.278 s elapsed) --------------------\n", + "2021-11-19 15:28:44,655 - [NOTICE] simulation.solve(884): Cycle 36/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:44,677 - [NOTICE] simulation.solve(884): Cycle 36/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:44,696 - [NOTICE] simulation.solve(884): Cycle 36/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:44,714 - [NOTICE] simulation.solve(884): Cycle 36/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:44,747 - [NOTICE] simulation.solve(972): Capacity is now 4.175 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:44,748 - [NOTICE] simulation.solve(850): Cycle 37/500 (5.371 s elapsed) --------------------\n", + "2021-11-19 15:28:44,748 - [NOTICE] simulation.solve(884): Cycle 37/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:44,772 - [NOTICE] simulation.solve(884): Cycle 37/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:44,790 - [NOTICE] simulation.solve(884): Cycle 37/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:44,809 - [NOTICE] simulation.solve(884): Cycle 37/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:44,841 - [NOTICE] simulation.solve(972): Capacity is now 4.157 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:44,841 - [NOTICE] simulation.solve(850): Cycle 38/500 (5.465 s elapsed) --------------------\n", + "2021-11-19 15:28:44,842 - [NOTICE] simulation.solve(884): Cycle 38/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:44,862 - [NOTICE] simulation.solve(884): Cycle 38/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:44,880 - [NOTICE] simulation.solve(884): Cycle 38/500, step 3/4: Charge at 1C until 4.2V\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:29,218 - [NOTICE] simulation.solve(843): Cycle 38/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:29,269 - [NOTICE] simulation.solve(921): Capacity is now 4.197 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:29,270 - [NOTICE] simulation.solve(809): Cycle 39/500 (4.850 s elapsed) --------------------\n", - "2021-09-17 01:13:29,270 - [NOTICE] simulation.solve(843): Cycle 39/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:29,300 - [NOTICE] simulation.solve(843): Cycle 39/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:29,325 - [NOTICE] simulation.solve(843): Cycle 39/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:29,350 - [NOTICE] simulation.solve(843): Cycle 39/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:29,383 - [NOTICE] simulation.solve(921): Capacity is now 4.181 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:29,384 - [NOTICE] simulation.solve(809): Cycle 40/500 (4.965 s elapsed) --------------------\n", - "2021-09-17 01:13:29,385 - [NOTICE] simulation.solve(843): Cycle 40/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:29,413 - [NOTICE] simulation.solve(843): Cycle 40/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:29,437 - [NOTICE] simulation.solve(843): Cycle 40/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:29,459 - [NOTICE] simulation.solve(843): Cycle 40/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:29,492 - [NOTICE] simulation.solve(921): Capacity is now 4.165 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:29,492 - [NOTICE] simulation.solve(809): Cycle 41/500 (5.075 s elapsed) --------------------\n", - "2021-09-17 01:13:29,492 - [NOTICE] simulation.solve(843): Cycle 41/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:29,520 - [NOTICE] simulation.solve(843): Cycle 41/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:29,544 - [NOTICE] simulation.solve(843): Cycle 41/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:29,566 - [NOTICE] simulation.solve(843): Cycle 41/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:29,601 - [NOTICE] simulation.solve(921): Capacity is now 4.149 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:29,601 - [NOTICE] simulation.solve(809): Cycle 42/500 (5.183 s elapsed) --------------------\n", - "2021-09-17 01:13:29,601 - [NOTICE] simulation.solve(843): Cycle 42/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:29,629 - [NOTICE] simulation.solve(843): Cycle 42/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:29,652 - [NOTICE] simulation.solve(843): Cycle 42/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:29,674 - [NOTICE] simulation.solve(843): Cycle 42/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:29,709 - [NOTICE] simulation.solve(921): Capacity is now 4.134 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:29,709 - [NOTICE] simulation.solve(809): Cycle 43/500 (5.290 s elapsed) --------------------\n", - "2021-09-17 01:13:29,709 - [NOTICE] simulation.solve(843): Cycle 43/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:29,736 - [NOTICE] simulation.solve(843): Cycle 43/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:29,760 - [NOTICE] simulation.solve(843): Cycle 43/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:29,785 - [NOTICE] simulation.solve(843): Cycle 43/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:29,820 - [NOTICE] simulation.solve(921): Capacity is now 4.118 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:29,820 - [NOTICE] simulation.solve(809): Cycle 44/500 (5.401 s elapsed) --------------------\n", - "2021-09-17 01:13:29,821 - [NOTICE] simulation.solve(843): Cycle 44/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:29,849 - [NOTICE] simulation.solve(843): Cycle 44/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:29,859 - [NOTICE] simulation.solve(843): Cycle 44/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:29,896 - [NOTICE] simulation.solve(843): Cycle 44/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:29,931 - [NOTICE] simulation.solve(921): Capacity is now 4.103 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:29,931 - [NOTICE] simulation.solve(809): Cycle 45/500 (5.512 s elapsed) --------------------\n", - "2021-09-17 01:13:29,932 - [NOTICE] simulation.solve(843): Cycle 45/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:29,957 - [NOTICE] simulation.solve(843): Cycle 45/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:29,967 - [NOTICE] simulation.solve(843): Cycle 45/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:30,006 - [NOTICE] simulation.solve(843): Cycle 45/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:30,033 - [NOTICE] simulation.solve(921): Capacity is now 4.088 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:30,033 - [NOTICE] simulation.solve(809): Cycle 46/500 (5.625 s elapsed) --------------------\n", - "2021-09-17 01:13:30,033 - [NOTICE] simulation.solve(843): Cycle 46/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:30,072 - [NOTICE] simulation.solve(843): Cycle 46/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:30,097 - [NOTICE] simulation.solve(843): Cycle 46/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:30,122 - [NOTICE] simulation.solve(843): Cycle 46/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:30,152 - [NOTICE] simulation.solve(921): Capacity is now 4.072 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:30,152 - [NOTICE] simulation.solve(809): Cycle 47/500 (5.740 s elapsed) --------------------\n", - "2021-09-17 01:13:30,152 - [NOTICE] simulation.solve(843): Cycle 47/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:30,187 - [NOTICE] simulation.solve(843): Cycle 47/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:30,212 - [NOTICE] simulation.solve(843): Cycle 47/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:30,237 - [NOTICE] simulation.solve(843): Cycle 47/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:30,267 - [NOTICE] simulation.solve(921): Capacity is now 4.058 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:30,267 - [NOTICE] simulation.solve(809): Cycle 48/500 (5.853 s elapsed) --------------------\n", - "2021-09-17 01:13:30,267 - [NOTICE] simulation.solve(843): Cycle 48/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:30,300 - [NOTICE] simulation.solve(843): Cycle 48/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:30,326 - [NOTICE] simulation.solve(843): Cycle 48/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:30,351 - [NOTICE] simulation.solve(843): Cycle 48/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:30,383 - [NOTICE] simulation.solve(921): Capacity is now 4.043 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:30,383 - [NOTICE] simulation.solve(809): Cycle 49/500 (5.967 s elapsed) --------------------\n", - "2021-09-17 01:13:30,383 - [NOTICE] simulation.solve(843): Cycle 49/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:30,417 - [NOTICE] simulation.solve(843): Cycle 49/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:30,440 - [NOTICE] simulation.solve(843): Cycle 49/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:30,462 - [NOTICE] simulation.solve(843): Cycle 49/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:30,493 - [NOTICE] simulation.solve(921): Capacity is now 4.028 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:30,493 - [NOTICE] simulation.solve(809): Cycle 50/500 (6.080 s elapsed) --------------------\n", - "2021-09-17 01:13:30,493 - [NOTICE] simulation.solve(843): Cycle 50/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:30,532 - [NOTICE] simulation.solve(843): Cycle 50/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:30,547 - [NOTICE] simulation.solve(843): Cycle 50/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:30,582 - [NOTICE] simulation.solve(843): Cycle 50/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:30,624 - [NOTICE] simulation.solve(921): Capacity is now 4.013 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:30,625 - [NOTICE] simulation.solve(809): Cycle 51/500 (6.205 s elapsed) --------------------\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2021-09-17 01:13:30,626 - [NOTICE] simulation.solve(843): Cycle 51/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:30,809 - [NOTICE] simulation.solve(843): Cycle 51/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:30,835 - [NOTICE] simulation.solve(843): Cycle 51/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:30,857 - [NOTICE] simulation.solve(843): Cycle 51/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:30,892 - [NOTICE] simulation.solve(921): Capacity is now 3.999 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:30,892 - [NOTICE] simulation.solve(809): Cycle 52/500 (6.479 s elapsed) --------------------\n", - "2021-09-17 01:13:30,892 - [NOTICE] simulation.solve(843): Cycle 52/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:30,925 - [NOTICE] simulation.solve(843): Cycle 52/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:30,948 - [NOTICE] simulation.solve(843): Cycle 52/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:30,970 - [NOTICE] simulation.solve(843): Cycle 52/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:31,000 - [NOTICE] simulation.solve(921): Capacity is now 3.985 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:31,000 - [NOTICE] simulation.solve(809): Cycle 53/500 (6.588 s elapsed) --------------------\n", - "2021-09-17 01:13:31,000 - [NOTICE] simulation.solve(843): Cycle 53/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:31,033 - [NOTICE] simulation.solve(843): Cycle 53/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:31,053 - [NOTICE] simulation.solve(843): Cycle 53/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:31,080 - [NOTICE] simulation.solve(843): Cycle 53/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:31,109 - [NOTICE] simulation.solve(921): Capacity is now 3.970 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:31,109 - [NOTICE] simulation.solve(809): Cycle 54/500 (6.698 s elapsed) --------------------\n", - "2021-09-17 01:13:31,109 - [NOTICE] simulation.solve(843): Cycle 54/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:31,142 - [NOTICE] simulation.solve(843): Cycle 54/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:31,165 - [NOTICE] simulation.solve(843): Cycle 54/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:31,190 - [NOTICE] simulation.solve(843): Cycle 54/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:31,226 - [NOTICE] simulation.solve(921): Capacity is now 3.956 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:31,226 - [NOTICE] simulation.solve(809): Cycle 55/500 (6.809 s elapsed) --------------------\n", - "2021-09-17 01:13:31,226 - [NOTICE] simulation.solve(843): Cycle 55/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:31,256 - [NOTICE] simulation.solve(843): Cycle 55/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:31,280 - [NOTICE] simulation.solve(843): Cycle 55/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:31,306 - [NOTICE] simulation.solve(843): Cycle 55/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:31,333 - [NOTICE] simulation.solve(927): Stopping experiment since capacity (3.942 Ah) is below stopping capacity (3.954 Ah).\n", - "2021-09-17 01:13:31,345 - [NOTICE] simulation.solve(938): Finish experiment simulation, took 6.925 s\n" + "2021-11-19 15:28:44,898 - [NOTICE] simulation.solve(884): Cycle 38/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:44,930 - [NOTICE] simulation.solve(972): Capacity is now 4.140 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:44,931 - [NOTICE] simulation.solve(850): Cycle 39/500 (5.555 s elapsed) --------------------\n", + "2021-11-19 15:28:44,931 - [NOTICE] simulation.solve(884): Cycle 39/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:44,951 - [NOTICE] simulation.solve(884): Cycle 39/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:44,970 - [NOTICE] simulation.solve(884): Cycle 39/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:44,988 - [NOTICE] simulation.solve(884): Cycle 39/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:45,021 - [NOTICE] simulation.solve(972): Capacity is now 4.123 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:45,021 - [NOTICE] simulation.solve(850): Cycle 40/500 (5.645 s elapsed) --------------------\n", + "2021-11-19 15:28:45,021 - [NOTICE] simulation.solve(884): Cycle 40/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:45,041 - [NOTICE] simulation.solve(884): Cycle 40/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:45,060 - [NOTICE] simulation.solve(884): Cycle 40/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:45,080 - [NOTICE] simulation.solve(884): Cycle 40/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:45,111 - [NOTICE] simulation.solve(972): Capacity is now 4.106 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:45,112 - [NOTICE] simulation.solve(850): Cycle 41/500 (5.736 s elapsed) --------------------\n", + "2021-11-19 15:28:45,112 - [NOTICE] simulation.solve(884): Cycle 41/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:45,132 - [NOTICE] simulation.solve(884): Cycle 41/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:45,150 - [NOTICE] simulation.solve(884): Cycle 41/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:45,171 - [NOTICE] simulation.solve(884): Cycle 41/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:45,204 - [NOTICE] simulation.solve(972): Capacity is now 4.089 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:45,204 - [NOTICE] simulation.solve(850): Cycle 42/500 (5.828 s elapsed) --------------------\n", + "2021-11-19 15:28:45,204 - [NOTICE] simulation.solve(884): Cycle 42/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:45,226 - [NOTICE] simulation.solve(884): Cycle 42/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:45,246 - [NOTICE] simulation.solve(884): Cycle 42/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:45,267 - [NOTICE] simulation.solve(884): Cycle 42/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:45,300 - [NOTICE] simulation.solve(972): Capacity is now 4.072 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:45,301 - [NOTICE] simulation.solve(850): Cycle 43/500 (5.925 s elapsed) --------------------\n", + "2021-11-19 15:28:45,301 - [NOTICE] simulation.solve(884): Cycle 43/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:45,322 - [NOTICE] simulation.solve(884): Cycle 43/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:45,342 - [NOTICE] simulation.solve(884): Cycle 43/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:45,364 - [NOTICE] simulation.solve(884): Cycle 43/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:45,401 - [NOTICE] simulation.solve(972): Capacity is now 4.056 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:45,401 - [NOTICE] simulation.solve(850): Cycle 44/500 (6.025 s elapsed) --------------------\n", + "2021-11-19 15:28:45,402 - [NOTICE] simulation.solve(884): Cycle 44/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:45,429 - [NOTICE] simulation.solve(884): Cycle 44/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:45,451 - [NOTICE] simulation.solve(884): Cycle 44/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:45,472 - [NOTICE] simulation.solve(884): Cycle 44/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:45,506 - [NOTICE] simulation.solve(972): Capacity is now 4.039 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:45,507 - [NOTICE] simulation.solve(850): Cycle 45/500 (6.130 s elapsed) --------------------\n", + "2021-11-19 15:28:45,507 - [NOTICE] simulation.solve(884): Cycle 45/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:45,528 - [NOTICE] simulation.solve(884): Cycle 45/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:45,547 - [NOTICE] simulation.solve(884): Cycle 45/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:45,565 - [NOTICE] simulation.solve(884): Cycle 45/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:45,603 - [NOTICE] simulation.solve(972): Capacity is now 4.023 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:45,604 - [NOTICE] simulation.solve(850): Cycle 46/500 (6.228 s elapsed) --------------------\n", + "2021-11-19 15:28:45,605 - [NOTICE] simulation.solve(884): Cycle 46/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:45,628 - [NOTICE] simulation.solve(884): Cycle 46/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:45,647 - [NOTICE] simulation.solve(884): Cycle 46/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:45,666 - [NOTICE] simulation.solve(884): Cycle 46/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:45,703 - [NOTICE] simulation.solve(972): Capacity is now 4.007 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:45,703 - [NOTICE] simulation.solve(850): Cycle 47/500 (6.327 s elapsed) --------------------\n", + "2021-11-19 15:28:45,704 - [NOTICE] simulation.solve(884): Cycle 47/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:45,735 - [NOTICE] simulation.solve(884): Cycle 47/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:45,754 - [NOTICE] simulation.solve(884): Cycle 47/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:45,773 - [NOTICE] simulation.solve(884): Cycle 47/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:45,809 - [NOTICE] simulation.solve(972): Capacity is now 3.991 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:45,809 - [NOTICE] simulation.solve(850): Cycle 48/500 (6.433 s elapsed) --------------------\n", + "2021-11-19 15:28:45,810 - [NOTICE] simulation.solve(884): Cycle 48/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:45,829 - [NOTICE] simulation.solve(884): Cycle 48/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:45,848 - [NOTICE] simulation.solve(884): Cycle 48/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:45,866 - [NOTICE] simulation.solve(884): Cycle 48/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:45,901 - [NOTICE] simulation.solve(972): Capacity is now 3.975 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:45,902 - [NOTICE] simulation.solve(850): Cycle 49/500 (6.526 s elapsed) --------------------\n", + "2021-11-19 15:28:45,902 - [NOTICE] simulation.solve(884): Cycle 49/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:45,924 - [NOTICE] simulation.solve(884): Cycle 49/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:45,944 - [NOTICE] simulation.solve(884): Cycle 49/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:45,964 - [NOTICE] simulation.solve(884): Cycle 49/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:45,999 - [NOTICE] simulation.solve(972): Capacity is now 3.960 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:28:45,999 - [NOTICE] simulation.solve(850): Cycle 50/500 (6.623 s elapsed) --------------------\n", + "2021-11-19 15:28:46,000 - [NOTICE] simulation.solve(884): Cycle 50/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:46,020 - [NOTICE] simulation.solve(884): Cycle 50/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:46,039 - [NOTICE] simulation.solve(884): Cycle 50/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:46,058 - [NOTICE] simulation.solve(884): Cycle 50/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:46,094 - [NOTICE] simulation.solve(978): Stopping experiment since capacity (3.944 Ah) is below stopping capacity (3.952 Ah).\n", + "2021-11-19 15:28:46,095 - [NOTICE] simulation.solve(990): Finish experiment simulation, took 6.719 s\n" ] } ], @@ -569,12 +541,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b150d7c09a7d42f7b1e35209c35da4ac", + "model_id": "4bfc75010f7d4501bcb209e354073268", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "interactive(children=(FloatSlider(value=0.0, description='t', max=154.4852454053064, step=1.544852454053064), …" + "interactive(children=(FloatSlider(value=0.0, description='t', max=147.01922550864583, step=1.4701922550864583)…" ] }, "metadata": {}, @@ -583,7 +555,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 6, @@ -704,7 +676,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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9XT0qlouFR8YS514z23SY7UaoBpwSGCIxZvWWXbw9LYt3M7JYu3U3NSuW5ZqejbigSwOaJFUKOrxAlfi/Ru5+H3AfQLgHxp15khcAq4B+wHgzqwO0AJYXY5hHpUXdyowc0p1P5qzloX8v5Nxnv+ecjsncM6AldaokBh2eiJQiZhYHjHL3h/Lb7u7nFHNIIhJBG7bt5t3poS7JqzbvpFqFBC7vnsaFXRrQou6hRuZKMRkLnHGEfb4qjkBEpOjtO5DDNws3MHLaKsYu3gjAic2SeGBQa/q1qkPZMnEBRxgdSnwC41DMbCiAuz8HPAi8bGZzCWWr73H3w2W0A2dmnNm+Pv1a1uaZMUsZPi6TL+av45Z+zbj6hDTKlSl93YVEpPi5e46Z9QfyTWCISMlzsEvyW1NW8c2iDRzIcbo3rsFvTm2u6U+jiLtfHXQMIlL0Vv24k5HTVvHu9Gw2bt9D3SqJ3NK3KeenN9DMTvmIqQSGu48BxoS/P5dr/Rrg1GCiKpyK5cpw12mhKVYf/HQhj3y2iLenZfG7Qa04qWWdoMMTkdLhq3DRuLeBHQdXqninSMmybutu3snI4u1pWazesotalcpy7YmNuKhLKo1qVQw6PBGRUmPv/hy+Xriet6auYvySTcQZnNSyNhd1SaVPiyTKxKu3xaHEVAIjljWsWZERV6Yz5ocN/OnTBfzq5Qx6N0/id4Na0bS2uniKSJH6VfjnTbnWOdA4gFhE5CgcyHHGLd7Im1NX8W24t0XPprW4f2ArTmmtLskiIsVp5Y87GBmubbHp573Ur5rIHac054L0BtStqlIBBaEERgnTp0VtejSpxavfr+DJb5bQ/4nxXHF8Grf1a0bVCglBhyciMcjdGwUdg4gcnQ3bdvP2tCxG5uptcd2Jjbm4awMa1lRvCxGR4rLvQA5fL1jPm//T26IOl3ZLpVfzJM04eZSUwCiBypaJ49oTG3N2x2Qe+2oxL03K5IOZ2fzm1BZc1KWBuhyJSESZWQJwA9ArvGoM8Ly77wssKBH5hZwcZ8LSTbw5ZRVfLVzPgRznhKY11duihDKzOw633d0fL8A5+gNPAvHACHd/JM/2qsDrQCqhfxf83d1fOuagReQ/sn/aycipWbydkcXG7XuoVzWRX5/cnAu7qLdFYSiBUYLVrFSOh85uy6XdUvnTJwv47YfzeH3ySn57emt6NqsVdHgiEjueBRKAZ8LLl4fXXRtYRCLyHz/+vId3p2fz5pRVrNq8kxrh6fYu7qraFiVcocYIm1k88DRwCpANTDOzj919Qa7dbgIWuPsZZpYE/GBmb7j73sJcW6S0OpDjfLdoA29MWcmY8EwifVvU5tJuqfRpUVu9LSJACYwYcFz9qowc0p3P563joc8WctkLU+jXsjb3n96q1M8TLCIR0cXd2+da/tbMZgcWjYjg7kzN3MwbU1bx+bx17D2QQ9dGoZlE+repq9nKYoC7/7GQp+gKLHX35QBmNhIYDOROYDhQ2cwMqARsBvYX8roipc7BYXtvTV3Fmq27qV25HDf3bcpFXVNJrlY+6PBiihIYMcLMGNC2Hn1b1ublSSt46tulnPaPcVx+fENu69eMahXKBh2iiJRcB8ysibsvAzCzxsCBgGMSKZW27d7H+9OzeWPKKpZs+JnKiWW4pFsql3ZLpVkdFfWOJWb2jrtfEP7+qLvfk2vbl+5+pBn2koGsXMvZQLc8+zwFfAysIdTj40J3z8knliHAEIDU1NSjvRWRmOTuTFr2I69PXslXC9azP1wk+YEzWtOvVR0SNKy/SCiBEWMSE+IZ2rsJ53ZK4fGvFvPKpBV8MHM1t57UjMu6N9T4VxE5FncB35nZcsCAhvx3ZpJDMrMXgUHABndvE173B+A6YGN4t/vdfXRRBC0SS+at3sobU1by4cw17Np3gHYpVfnrue0Y1L4eFcrqcS5GNcv1/RTgnlzLSQU4Pr++6p5n+TRgFnAS0ITQtNnj3X3b/xzkPgwYBpCenp73HCKlytad+3hvRjZvTFnJ8o07qFYhgatPSOOSbg01bK8Y6C9ejEqqXI6Hz2nLFcc35C//XsifPl3Aq9+v4L6BrTi1dR1CPQVFRApkAqEH6RaEHogXFfC4lwm93Xs1z/p/uPvfIxadSIzave8Ao+eu5bXJK5m5aguJCXGc2b4+l3VvSLuUakGHJ0XvcImCgiQRsoEGuZZTCPW0yO1q4BF3d2CpmWUCLYGpRxOoSGkwN3srr01ewcez17B7Xw4dU6vx+AXtGdi2HokJGrZXXKIigWFmNQqwW467bynqWGJNq3pVeO2aroz5YSN/Gb2Q61+bTtdGNfjt6a308CMiBfW9u3cC5hxcYWYzgE6HO8jdx5lZWhHHJhJzsjbv5PUpK3lnWhY/7dxH46SKPDCoNed2StGU6aVLBTPrCMQB5cPfLfwpyKD6aUAzM2sErAYuAi7Js88qoB8w3szqEEpUL49Q/CIl3u59B/h0TiiRPDtrC+UT4jm7YzKXdmtIm+SqQYdXKkVFAoNQNngN+Xd1Oyie0BRPcpTMjL4ta3Nis1qMnJbFP75azJlPTeSsDvW587QWpFSvEHSIIhKFzKwuoTHUuR+cAaoAhWk4bjazK4AM4Dfu/lPhIhUp+Q7kOOMWb+TV71cwZvFG4sw4pVUdLj++IT2a1FTPydJpHfB4Pt8PLh+Wu+83s5uBLwg9R7/o7vPNbGh4+3PAg8DLZjaXUBt/j7tviuA9iJRIq37cyRtTVvJ2RhZbdu6jSVJF/nBGa87pnEKVRCWSgxQtCYyF7t7xcDuY2cziCiZWlYmP47LuDRncoT7PjFnGixMyGT1vHVf3SOPGvk2pWl7/MYrI/zgNuIpQt+PcD87bgfuP8ZzPEnpg9vDPxzhEPQ0VjZPSYMvOvbyTkcVrk1eStXkXtSqV45a+Tbm4Wyr1qqpyfWnm7n0icI7RwOg8657L9X0NcKRioCKlQk6OM3bJRl6d9N9E8qmt63B594Ycr0Ry1IiWBMbxEdpHCqByYgL39G/J5d0b8vcvf2DY+OW8nZHFLSc143IV+hSRMHd/BXjFzM5191EROuf6g9/NbDjw6WH2VdE4iVnzVm/l1e9X8NGsNezZn0PXtBrcfVpLTjuurv4OCwBm1gXIcvd14eUrgHOBlcAf3H1zkPGJxIqtO/fx7vRQInnljzuVSI5yUZHAcPfdB7+bWTxQh1yxufuq3PtIZNSvVp7HL+jANT0b8fDoRTz46QJembSCu05rwaB29ZRlFJGDPjWzS4A0/rdt/tPRnsjM6rn72vDi2cC8iEQoUgLs3Z/DZ/PW8sqkFcxYFRpLfU6nFK44viGt6lUJOjyJPs8DJwOYWS/gEeAWoAOh5O55gUUmEgMWrt3Gq9+HZmzcvS+H9IbV+c2pLeivRHJUi4oExkFmdgvwe2A9cHAOagfaBRZUKXBc/aq8dk1Xxi3ZxMOjF3LLWzMZPn459w5oSY8mtYIOT0SC9xGwFZgO7CnoQWb2FtAHqGVm2YTa9z5m1oFQ274CuD7CsYpEnfXbdvPGlFW8OWUVm37eQ1rNCvxuUGvO65yi4ZtyOPG5ellcCAwL94YbZWazggtLpOTadyCHL+ev55VJK5i6YjOJCXGc1SGZy49vyHH1VZSzJIiqBAZwG9DC3X8MOpDSxszo3TyJnk1r8cHM1Tz+5Q9cMnwKfVokce+AlrSsqzdDIqVYirv3P9qD3P3ifFa/EIF4RKKeuzNj1U+8PGkln81dywF3+jRP4soeafRqlkRcnHo5yhHFm1kZd99PaKaQIbm2RdszvEhU2/TzHt6asoo3pqxi3bbdNKhRnv8b2Irz01OoVqFs0OHJUYi2xi+L0Fs+CUh8nHFe5xQGtavHK5NW8PR3Sxnw5HjO6ZjCr09pphlLREqnSWbW1t3nBh2ISLQ7OOXey5Mymbd6G5UTy3BljzQu796QtFoVgw5PSpa3gLFmtgnYBYwHMLOm6HlZpEDmZm/lpUmZfDp7LXsP5HBis1r8+aw29G1Zm3glkkukqEhgmNkd4a/LgTFm9m9ydVN298fzPVCKTGJCPNf3bsKFXRrwzJhlvDxpBZ/MXsPlxzfkpr5NqVFRmUqRUqQncJWZZRJqmw1wd9fwPpGwdVt38/rklbw1dRU/7thLs9qV+PNZbTinUzIVykbF45aUMO7+FzP7BqgHfOnuB4sZxxGqhSEi+dh3IIfP5q3j5YmZzFi1hYpl47m4awMuPz6NprUrBR2eFFK0/EWtHP65KvwpG/5IwKpVKMv9A1txVY80nvh6MS9NzOSdaVkM6dWYa05spIcykdJhQNABiESj0DCRLbw0MZPP563jgDsnt6rDVT3S6KEp9yQC3H1yPusWBxGLSLT78ec9vDllFa9PWcn6baF6Qw8Mas156SlUSVS9oVgRFf/6dPc/FvYc4dlLMoDV7j4on+19gCeABGCTu/cu7DVLk/rVyvPX89pz3YmN+dsXP/DYV4t55fuV3NqvKRd1SVWlXpEY5u4rzawn0MzdXzKzJECvMKTU2rs/h3/PXcNLE1cwJ3srlRPLcFWPNK44Po3UmhpqKSJSnBas2cZLEzP5aPYa9u4PDRN55Jx29G6uekOxKCoSGIdjZkPcfVgBdr0NWAj8otqkmVUDngH6u/sqM6sd2ShLj2Z1KjPsinSmr/yJRz9fxAMfzWf4+OX8+uTmDO6QrLFkIjHIzH4PpAMtgJcIJYJfB04IMi6R4rbp5z28MTn0dm/j9j00TqrIg4OP45xOKVQsF/WPVCIiMeNAjvPVgvW8NDGTKZmbKZ8QzwXpKVzVI42mtSsf+QRSYpWEv7ZH/BexmaUApwN/Ae7IZ5dLgPfdfRWAu2+IaISlUOeG1Xl7SHfGLt7I3774gTvemc3zY5fzm1Obc0rrOuo2KxJbzgY6AjMA3H2NmenpQEqNhWu38eKE/77d6908iavP02wiUnzMrA7QJbw4Vc+yUlpt372PdzKyeXlSJlmbd5FcrTz3D2zJhempVK2gYSKlQUlIYMwowD5PAHfz31oaeTUHEsxsTHifJ9391fx2NLMhhKepSk1NPdpYSxUzo0+L2vRqlsToeWt5/MvFDHltOh1Tq3HXqS3o0bRW0CGKSGTsdXc3MwcwM02lIDEvJ8f5dtEGXpyYyaRlP+Z6u9dIReCkWJnZBcDfgDGEXuz9y8zucvf3Ag1MpBit/HEHL09awbsZ2fy8Zz9d0qpz/4BWnNK6DmXiNZS9NInKBIaZtQYuAi4mNE1U+mH2HQRscPfp4ToX+SkDdCY0h3Z54Hszm5xfEaTwcJVhAOnp6Z53u/xSXJwxqF19+h9Xl/emZ/PkN0u4ZMQUejSpyZ2ntaBTavWgQxSRwnnHzJ4HqpnZdcCvgOEBxyRSJHbs2c+oGdm8OCGTFT/upF7VRO4d0JKLujSgWgXVF5dA/B/Q5WCvi3Adoq8BJTAkprk7UzM3M2JCJl8vXE+8GWe0r8/VJ6TRLqVa0OFJQKImgWFmDQklLC4G9gMNgXR3X3GEQ08AzjSzgUAiUMXMXnf3y3Ltk02ocOcOYIeZjQPaA6riHEFl4uO4qGsqZ3VM5o0pq3jmu6Wc88wk+rWszW9ObUHr+r8oTyIiJYC7/93MTgG2EaqD8YC7fxVwWCIRtXbrLl6ZtJI3p6xk2+79tG9QjX+d2oL+beqSoLd7Eqy4PENGfiQ0lapITNq7P4fRc9cyYsJy5q3eRrUKCdzYpwlXHJ9GnSqJQYcnAYuKBIaZTQKqAiOB89x9iZllFiB5gbvfB9wXPk8f4M48yQuAj4CnzKwMoelZuwH/iNgNyP9ITIjnmp6NuKhLA16etILnxy5j4D/Hc3q7evz65GYqrCNSwpjZr4F3lbSQWDQnewsvTMjk33PWkuNO/zZ1uaZnYzo3VO9BiRqfm9kXwFvh5QuBzwKMR6RIbNm5lzenruKVSStYv20PTZIq8pez23BOxxTKl40POjyJElGRwAA2AilAHSAJWAIUaviGmQ0FcPfn3H2hmX0OzAFygBHuPq9wIcuRVCxXhpv6NuWy7g0ZPm45L07M5LO5azmrQzK3ndyMhjU1jF6khKgCfGFmmwklmt9z9/UBxyRyzHJynK8XrmfEhEymZm6mUrkyXNkjjat6pNGghqZBleji7neZ2TlAT0I1MIa5+wcBhyUSMSs27eDFiZm8m5HNrn0H6NlU06DKoZl7dJR5MLOqwLmEhpA0BaoBp7n71KBiSk9P94yMjKAuH3N+/HkPz49bziuTVrA/xzm/cwo3n9SUlOp6WJTYZmbT3f2QtXxKCjNrR+jN37lAtrufXFzXVnsskbBr7wHeC9e3yNy0g+Rq5bn6hDQu7NKAyomqXl9alLQ22cwedfd7jrSuuKg9lkhwdzJW/sSI8cv5csF6ysQZgzskc03PRrSqp2HnpcWxtMfR0gMDd98KvAi8aGa1CT0kP2FmDdy9QbDRSSTUrFSO+we24tqejXhmzDLenLKKUTOyuahLKjf2bUK9quWDDlFEDm8DsI7Q+OvaAcciUmAbt+/h1e9X8NrklWzZuY/2KVX518UdGdCmrqrXS0lwCpA3WTEgn3UiUe9AjvPF/HUMG7ecWVlbqFo+VN/iyuPTqK36FlIAUZPAyC1cqOhfhKaJahh0PBJZtask8oczj2NIr8b869ulvDV1FW9nZHFJ11Ru7NNEjZdIlDGzGwgllZMIVb2/zt0XBBuVyJEt3bCdEeMzeX/mavYdyOHkVnUY0qsx6Q2rY6ZuyRLdwm3vjUBjM5uTa1NlYGIBz9EfeBKIJzSE+pF89ukDPAEkECp637tQgYvkY+fe/bybkc2ICcvJ2ryLtJoVeHDwcZzbOYUKZaPyn6QSpaLit8XM/uDuf8hvm7uvPNI+UjLVr1aeh89py419mvDUt0t5bfJK3pq6isu6N2Ro7yYkVS4XdIgiEtIQuN3dZwUdiMiRHJx2b9i45XyzaAPlysRxfucUrunZiMZJlYIOT+RovEmoWOfDwL251m93981HOtjM4oGnCfXgyAammdnHuRPQZlYNeAbo7+6rwr2gRSJm4/Y9vDIp1ANu6659dG5Ynf8b2JpTWtchXvUt5BhERQIDuNbMth1muwEXAX8onnCkODWoUYFHz2vHjX2b8K9vl/LSxEzemLKSy7s3ZEgvJTJEgubu95pZvJnVJ9ffDXdfFWBYIv/jYLfk58ctZ3bWFmpULMvtJzfj8u4NqVlJf0ek5AkPr95KqD7csegKLHX35QBmNhIYDOTuQXcJ8P7B9jzPdK0ix2zZxp8ZMX45o2aEesCd1rou1/VqROeGNYIOTUq4aElgDCfUHe5I+0gMa1izIn8/v/1/emS8MCGT1yYrkSESNDO7mVACeT2hmZwgNFNUu6BiEjlo974DvDs9mxHjl7Pyx500rFmBB89qw3mdNO2elHrJQFau5WygW559mgMJZjaG0LP4k+7+at4TmdkQYAhAampqkQQrsWH6ys08P3Y5Xy1cT0J8qAfctSc2plEtzT4okREVCQx3/2PQMUj0aJxUiccv7MDNJzVVIkMkOtwOtHD3H4MOROSgn3bs5dXvV/LK9yvYvGMv7RtU497+LTn1uLrqliwSkt9/CHmnHywDdAb6AeWB781ssrsv/p+D3IcBwyA0C0kRxColWE6O882iDTw/dhkZK3+iWoUEbunblCt6pFFLPeAkwqIigSGSn0MlMi7t1pDrezVWsU+R4pNFqBuzSOCyf9rJiPGZvD0ti137DnBSy9pc36sxXRvVUGFOiUnhXnBvuPtPR3loNpB7Jr8UYE0++2xy9x3ADjMbB7QHFiNyBHv35/DhrNUMG7ecpRt+Jrlaef5wRmsu6NJAhTmlyOg3S6Je7kTG098t4+VJK3h98kou7prK0N5NqFtViQyRIrYcGGNm/wb2HFzp7o8HF5KUNovWbeP5scv5ePYaDDizQ32u79WEFnWPNAJVpMSrS6gA5wzgReALdy9IL4hpQDMzawSsJlRP7pI8+3wEPGVmZYCyhIaY/CNikUtM+nnPft6asooXJmSybttuWtWrwpMXdeD0tvU0NbUUuahKYJhZjYJUVZbSqXFSJR67oD23nNSUZ8aEZi15c8oqLuzSgBv6NKF+tfJBhygSq1aFP2XDH5FiM23FZp4ds4xvF22gQtl4rjw+jWtObESy2nwpJdz9t2b2O+BU4GpCCYd3gBfcfdlhjtsf7r3xBaFpVF909/lmNjS8/Tl3X2hmnwNzCNU4GuHu84r6nqRk2vTzHl6euIJXv1/Btt37Ob5xTR49rx29mtVSDzgpNlGVwACmmNks4CXgswJml6WUSatVkb+e155bTmrGM2OW8tbUVYyctopzO6VwY5+mpNasEHSIIjFFdYqkuLk73/2wgWe+C42nrlGxLHec0pwrjm9ItQrKoUnp4+5uZuuAdcB+oDrwnpl95e53H+a40cDoPOuey7P8N+BvkY9aYkXW5p0MH7+ct6dlsfdADv2Pq8v1vZvQoUG1oEOTUijaEhjNgZOBXwH/MrO3gZfzFhISgdD0qw+f046bT2rGc2OW8fa0LN6dns3gDvW5qW9TmiRVCjpEkRLNzJ5w99vN7BN+WfgNdz8zgLAkhu0/kMOnc9by3NhlLFq3/T/jqS/skqoZRaTUMrNbgSuBTcAI4C5332dmccAS4JAJDJHC+GHddp4bu4yPZ68hzuDsjslc37uJnrElUFGVwAj3uPgK+MrM+gKvAzea2WzgXnf/PtAAJSolVyvPg2e14eaTmvL82OW8OXUlH8xczaB29bmpbxNa1q0SdIgiJdVr4Z9/DzQKiXm79x3gvenZPD9uGVmbd9GsdiUev6A9Z7SvT4LGU4vUAs5x95W5V7p7jpkNCigmiWEzVv3EM98t4+uF66lQNp6re4SG7tWrqqF7EryoSmCYWU3gMuByYD1wC/Ax0AF4F2gUWHAS9epUSeSBM1pzY98mjBifyWvfr+CT2Ws4uVUdbj6pqbq5iRwld58e/jk26FgkNv28Zz9vTF7JiAmZbNy+h/YNqvHAoOPo17I2cZoKVeSgRnmTF2b2mrtf7u4LgwpKYou7M3Hpjzz93VK+X/4j1SokcPvJzbiqR5qG7klUiaoEBvA9oTd+Z7l7dq71GWb23CGOEfkftSqV494BLRnauzEvT1rBSxNXcNbTEzmxWS1u6tuUbppqT6RYmNmLwCBgg7u3Ca+rAbwNpAErgAuOYWpAKeF+2rGXlyat4JVJK9i6ax8nNK3Jkxd24PgmNdU+i/zScbkXzCwe6BxQLBJjcnKcrxau55nvljI7eyu1K5fjt6e34uKuqVQsF23/VBSJvgTGb939ndwrzOx8d3/X3R8NKigpmapVKMvtJzfn2hMb8/rklYwYv5yLhk0mvWF1burblD4tkvSgLFK0XgaeAl7Nte5e4Bt3f8TM7g0v3xNAbBKADdt3M2J8Jq9PXsnOvQc4pXUdbuqrHnIi+TGz+4D7gfJmtu3gamAvMCywwCQmHMhxPp2zhme+W8YP67fToEZ5Hjq7Led2TqZcGdUckugVbQmMe4F38qy7j9DwEZFjUqlcGYb2bsJVPdJ4e1oWz49dxtUvT6NVvSrc1LcJA9rUI15dlUUizt3HmVlantWDgT7h768AY1ACI+at3rKL58cuY+S0LPYfyGFQu/rcqBpFIofl7g8DD5vZw+5+X9DxSGzYuz+HD2Zm8+yYZaz4cSdNa1fiHxe254x29SmjmkNSAkRFAsPMBgADgWQz+2euTVUITRUlUmiJCfFc2SONi7um8tGs1Tw7dhk3vzmTRrUWM7R3Y87umELZMmq4RfIys3Tg/4CGhP5uGKG6y+2O4XR13H0toROsNbPah7nuEGAIQGpq6jFcSoK2YtMOnh2zjFEzsjGDczqmMLRPExrVqhh0aCJRz8xauvsi4F0z65R3u7vPCCAsKaF27zvAuxlZPDd2Oau37KJNchWeu6wTp7auq5pDUqJERQIDWANkAGcC03Ot3w78uiAnCI8HzABWu3u+FZnNrAswGbjQ3d8rVMRSYpUtE8f56Q04p1MKX85fx9NjlnLPqLn846slXHtiI435E/mlN4C7gLlATnFd1N2HEe4mnZ6e/otpXCV6Ld3wM09/t5SPZq2mTHwcl3RL5freTUiupgr2IkfhDkJJ3Mfy2ebAScUbjpREu/Ye4I0pKxk2bjkbtu+hc8Pq/PnsNvRprqHUUjJFxb/S3H02MNvM3nD3Y+1xcRuwkFCvjV8IJzgeBb44xvNLjImPMwa0rUf/NnUZt2QTz45Zyp//vZB/fbuUK3ukcVWPNGpUVNVlEWCju38coXOtN7N64d4X9YANETqvRIFF67bxr2+XMnruWhLLxHNNz0Zcd2JjaldJDDo0kRLH3YeEf/YNOhYpeX7es5/Xvg/VgPtxx16Ob1yTJ1QsWWJAVCQwzOwdd78AmGlmv3jLdqRuymaWApwO/IVQtjo/twCjgC6FDFdijJnRu3kSvZsnMWPVTzw7Zhn//GYJw8ct58IuDbj2xEakVK8QdJgiQfq9mY0AvgH2HFzp7u8fw7k+Bq4EHgn//CgiEUqg5q/Zyj+/WcIX89dTqVwZbuzThF+d0IialcoFHZpIiWdmNwFvuPuW8HJ14GJ3fybQwCQqbdu9j1cnrWDEhEy27NxH7+ZJ3HJSU9LTagQdmkhEREUCg1DvCQhNt3csngDuBirnt9HMkoGzCXW1O2wCQ2OuS7dOqdUZfkU6S9Zv59mxy3h98kpem7ySM9vX5/rejVVwTkqrq4GWQAL/HULiwGETGGb2FqGCnbXMLBv4PaHExTtmdg2wCji/iGKWYjAnewv//GYpXy9cT+XEMtzWrxm/OqERVSskBB2aSCy5zt2fPrjg7j+Z2XWAEhjyH1t37eOliZm8OCGTbbv3069lbW7t14z2muVJYkxUJDAOFnQD4oC17r4bwMzKA3UOd6yZDQI2uPt0M+tziN2eAO5x9wNH6jKlMdcC0KxOZR6/oAO/ObUFL4zPZOS0VXwwczV9WyQxtHcTujaqoe53Upq0d/e2R3uQu198iE39ChmPBGxW1hae/Hox3/2wkarlE/jNKc258oQ0qiQqcSFSBOLMzNzd4T/DojXGVQDYunMfL0xYzksTV7B9z35ObV2HW/s1o01y1aBDEykSUZHAyOVdoEeu5QPhdYfrNXECcKaZDQQSgSpm9rq7X5Zrn3RgZPgfnLWAgWa2390/jGTwEnuSq5XngTNac2u/prz2/UpenrSCC4dNpkODagzt3ZhTWtfVFKxSGkw2s9buviDoQCRYuRMX1SskcNdpLbji+IZUVuJCpCh9Qajn2nOEer8NBT4PNiQJWt7ERf/j6nJLv6YcV1+JC4lt0ZbAKOPuew8uuPteMztshjk8L/Z9AOEeGHfmSV7g7o0Ofjezl4FPlbyQo1GtQllu6deM63o15t2MLIaPz2To6zNoVKsi157YiHM7pZCYEB90mCJFpSdwpZllEqqBUZhpVKUEypu4uLt/C644Po1KmrFJpDjcA1wP3ECo/f0SGBFoRBKYvImLAW3qcmu/ZrSqp2HOUjpE25PHRjM782C1ezMbDGw6lhOZ2VAAd38ugvFJKZeYEM/lx6dxSbeGfD5vHc+PW8b/fTCPx79czFU90rise0Oqa+YSiT39gw5AgjE7awtPKHEhEih3zwGeDX+klFLiQiQk2p5AhgJvmNlThDLMWcAVBT3Y3ccAY8Lf801cuPtVhQ1SJD7OOL1dPQa2rcvk5Zt5ftwyHvtqMc+MWcYF6Slc07MxqTU1c4nEDNUDKmXmrd7KE18v5uuFG6gWHipyZQ8lLkSCYGbNgIeB1oSGSwPg7o0DC0qKzbbd+3hpwgpGTFjO9t1KXIhE1ZOIuy8DuptZJcDcfXvQMYkcjplxfJOaHN+kJj+s287w8ct5c+oqXpu8kv5t6nLdiY3pmFo96DBFCuvfhJIYRujhuRHwA3BckEFJ5C1cu40nvl7MF/PXUyWxDHee2pwre6SpxoVIsF4iNIvTP4C+hGaGUgGuGPfznv28PDGT4eMz2bprH6e2rsPtJzendX0lLqR0i6oEBoCZnU7ooTjx4CwP7v6nQIMSKYAWdSvz9/Pbc9dpLXh50gpen7yS0XPX0SWtOtee2JiTW9VRwU8pkfLOQGJmnQiNx5YYsWT9dv7x9WJGz11H5cQy/Prk5lzdU7OKiESJ8u7+TXgmkpXAH8xsPKGkxmGZWX/gSSAeGOHujxxivy7AZOBCd38vgrHLUdq5dz+vfr+S58cu46ed+zi5VW1uP7m5ZhURCYuqBEa4unIFQtnlEcB5wNRAgxI5SnWqJHJP/5bc1Lcpb0/L4sUJmVz/2nTSalbgmp6NOK9zA8qXVcFPKbncfUb4YVdKuMxNO3jy68V8NHsNFcuW4ZaTmnJtz8ZUraDEhUgU2W1mccASM7sZWA3UPtJB4elWnwZOAbKBaWb2cd4ZpcL7PUpothMJyO59B3hjyiqeHbOUTT/vpXfzJO44pTntG1QLOjSRqBJVCQygh7u3M7M57v5HM3sMeD/ooESORaVyZbimZyOuPL4hn89fx/Dxmfzuo/k89tViLuvWkCt6NKR25cQjn0gkYGZ2R67FOKATsDGgcCQCsjbv5F/fLmHUjNUkxBvX92rC9b0aqwixSHS6ndALvluBB4GTgCsLcFxXYKm7Lwcws5HAYCDvlNi3AKMAJaYDsHd/Dm9nZPH0t0tZt203PZrU5PnLm9O5YY2gQxOJStGWwNgV/rnTzOoDPxIaay1SYpWJj2NQu/qc3rYeGSt/Yvi45Tw9ZinDxi3njPb1uaZnI41nlGhXOdf3/YRqYowKKBYphPXbdvPUt0sZOW0VZsaVx6dxQ58mJFUuF3RoInII7j4NINwL49ajqBGXTKgg/kHZQLfcO5hZMnA2oaTIIRMYZjYEGAKQmppa4Njl0PYfyOGDmat58pslZP+0i/SG1Xn8wvb0aFIr6NBEolq0JTA+NbNqwN+AGYSKxg0PNCKRCDEzuqTVoEtaDVZs2sFLEzN5JyObUTOyOaFpTa7t2ZjezZOIU50MiTLu/segY5DC2bxjL8+NXcYrk1ZwIMe5sEsDbj6pKfWqlg86NBE5AjNLJ1TIs3J4eSvwK3effqRD81mXd1apJ4B73P3Awdpz+XH3YcAwgPT0dM1MVQg5Oc7oeWt5/KvFLN+4g7bJVfnzWW3o3TyJw/1/ICIhUZXAcPcHw19HmdmnQKK7bw0yJpGikFarIn8c3IY7TmnBm1NX8cqkFVz98jQaJ1XkVyc04pxOyVQoG1X/eUopZGZPuPvtZvYJ+Uyl6u5nBhCWHIXtu/cxYnwmL0zIZOfe/ZzVMZnb+zXXNM8iJcuLwI3uPh7AzHoSSmi0O8Jx2UCDXMspwJo8+6QDI8P/cK4FDDSz/e7+YQTillzcne9+2MDfv1jMgrXbaF6nEs9d1pnTjqujxIXIUYiqfyGZWSJwI9CT0MPyBDN71t13BxuZSNGoWiGBG/o04doTGzF67lpemJDJbz+cx9+++IGLu6ZyZY+GekMqQXot/PPvgUYhR233vgO89v1Knh6zlC079zGgTV3uOKU5zepUPvLBIhJtth9MXgC4+wQzK8gwkmlAMzNrRKjw50XAJbl3cPf/DNU2s5eBT5W8iLwpy3/kb1/8QMbKn0itUYF/XNieM9sna3Y6kWMQVQkM4FVgO/Cv8PLFhB6gzw8sIpFikBAfx+AOyZzZvj7TV/7EixMzGTZuGcPHL2dg23r86oQ0OqZWDzpMKWUOdk9297FBxyIFs/9ADu9Oz+bJr5ewbttuejVP4q5TW9A2RdPviZRgU83seeAtQi/4LgTGhKe0xt1n5HeQu+8Pz1ryBaFpVF909/lmNjS8/bliib4Um7d6K3/74gfGLt5InSrl+MvZbbggvQEJ8XFBhyZSYkVbAqOFu7fPtfydmc0OLBqRYmZmpKfVID2tBlmbd/Lq9ysYOTWLT2avoUODalx9QhoD29bTHz4pVmZ2AvAHoCGhvxsGuLs3DjIu+a+DY6of+3IxmZt20Cm1Gk9c1IHujWsGHZqIFF6H8M/f51nfg1BC46RDHejuo4HRedblm7hw96uOOUL5H5mbdvDYlz/w6Zy1VC2fwH0DWnJljzQSE+KDDk2kxIu2BMZMM+vu7pMBzKwbMDHgmEQC0aBGBf7v9NbcdnJzRk3P5qWJmdw2chYPj17E5cc35OKuqdTQlIdSPF4Afg1MBw4EHIvkMX7JRh79fBHzVm+jRZ3KDL8inZNb1daYapEY4e59g45BCmbDtt088c0S3p6WRdn4OG7u25TrejWmavmEoEMTiRnRlsDoBlxhZqvCy6nAQjObS+ht35GKFYnEnErlynBljzQu796QMYs38NLEFfztix/45zdLGNyhPlf10DSsUuS2uvtnQQch/2tO9hYe/XwRE5f+SHK18jx+QXsGd9CYapFYZGanA8cBiQfXufufgotIctu2ex/Pj13GCxMyOZDjXNYtlZtPaqYpqkWKQLQlMPoHHYBItIqLM05qWYeTWtZh8frtvDRxBR/MzOadjGy6NarB1SekcXKrOpTR8BKJkIPjqwkN5/sb8D6w5+D2Q427lqKVuWkHf//iB/49dy01KpblgUGtubR7KuXKqGuySCwys+eACkBfYARwHjA10KAE+GXB5DPb1+c3pzanYc2KQYcmErOiKoHh7isBzKw2/5thXnXIg0RKoeZ1KvPwOW25p38L3p6Wxavfr2To6zNIrlaey49vyEVdGlCtgoaXSKE9lmc5Pdf3w467lsjbuH0PT36zmJFTsyhbJo5bTwp1Ta6cqK7JIjGuh7u3M7M57v5HM3uMUEJZAnIgx/lw5moe/2oxq7fsolfzJO4+rQVtklUwWaSoRVUCw8zOJPTAXB/YQKhg3EJCXeZEJI9qFcpyfe8mXNOzEV8v3MBLEzN55LNF/OOrxZzVIZkre6RpeIkcs4Pjrs2ssbsvz73NzFTAs5js2LOfYeOWM3z8cvbuz+Hirqnc2k9dk0VKkV3hnzvNrD7wI9DoMPtLEXF3xi7eyCOfLWLRuu20S6nK385rR4+mtYIOTaTUiKoEBvAg0B342t07mllfQlOpishhlImPo3+buvRvU5dF67bxyqSVfDAzm7czsuiaVoMre6Rx6nF1NHuJHKv3gE551r0LdA4gllJj34EcRk5dxZPfLGHTz3sZ2LYud53Wkka11DVZpJT51MyqAX8DZhDqATci0IhKobnZW3n4s4VMWvYjqTUq8K+LO3J623rEqe6QSLGKtgTGPnf/0czizCzO3b8zs0eDDkqkJGlZtwoPn9OWe/u35J2MLF6dvIKb3pxB3SqJXNotlYu6purNrRSImbUk1AOuqpmdk2tTFXIN85PIcne+mL+ev36+iOWbdtC1UQ2GX9GSjqnVgw5NRALg7g+Gv44ys0+BRHffGmRMpUnW5p38/csf+GjWGmpULMvvz2jNpd0aUraMXgqJBCHaEhhbzKwSMA54w8w2APsLcqCZxQMZwGp3H5Rn26XAPeHFn4Eb3H125MIWiT5VKyRwXa/G/KpnI75btIFXJ6/ksa8W889vl3B623pcfnwanVKraapFOZwWwCCgGnBGrvXbgeuCCCjWzVz1Ew+NXsi0FT/RJKkiI65Ip5+mRBUp1czsJuANd9/i7nvMrIKZ3ejuzwQdWyzbunMfT49ZyssTV2AGN/VtwtDeTVR3SCRg0ZbAGExonN+vgUuBqkBBp4i6jVC9jPwG/GcCvd39JzMbAAwjNGWrSMyLjzNObl2Hk1vXYfnGn3lt8krey8jmw1lraJNchSu6p3FG+/qUL6sZDOR/uftHwEdmdry7fx90PLFs1Y87efSLRfx7zlpqVSrHX85uw4XpDTSrkIgAXOfuTx9cCD/PXgcogVEE9u7P4bXJK/nXt0vYumsf53ZK4TenNqde1fJBhyYiREkCw8yaAnXcfWJ4VQ7wipn1IvTm78cjHJ8CnA78Bbgj73Z3n5RrcTKQEoGwRUqcxkmV+P0Zx3HnqS34YOZqXv1+BXePmsNfRi/kgvQULu3WkDSNr5cwM7vb3f8KXGJmv6hH5O63BhBWTNm6cx//+nYJr3y/gjJxoZlFhvRuQqVyUfHnWUSiQ5yZmbs7/KfXsaYaizB357N563jks0Ws2ryTE5vV4r4BrVQMXSTKRMsT0hPA/fms3xnedkY+2/IefzdQuQDXugb47FAbzWwIMAQgNTW1AKcTKXkqlivDZd0bcmm3VKZkbua1ySt5aeIKho/PpHfzJK44viF9WtQmXoWpSruF4Z8ZgUYRg/YdyOH1ySt58pvQG77zO6fwm1NbUKeKSouIyC98AbxjZs8RKuA5FPg82JBiy6ysLfz50wVkrPyJFnUq8/LVXejTonbQYYlIPqIlgZHm7nPyrnT3DDNLO9yBZjYI2ODu082szxH27UsogdHzUPu4+zBCQ0xIT0/3I0YuUoKZGd0b16R745qs37abt6au4q2pq7jmlQySq5Xnkm6pXNilAbUqqehnaeTun4R/vhLpc5vZCkK1NA4A+909PdLXiEbuzlcL1vPIZ6ECnSc0rcn/DWytN3wicjj3EHq5dgNgwJdoFpKIWL1lF3/9fBEfzVpDrUplefictpzfOUXD90SiWLQkMA73yulIA85OAM40s4Hh81Qxs9fd/bLcO5lZO0KN/QB3P+yQFJHSqE6VRG4/uTk39W3K1wvW89rklfztix944uvFDGhTj8u6N6RLWnUVEyxFzOwTQm/78uXuZxbyEn3dfVMhz1FizF+zlQc/XcDk5ZtpklSRF69Kp28LFegUkcNz9xzgufBHIuDnPft5dsxSRozPBODmvk0Z2kfD90RKgmj5r3SamV3n7sNzrzSza4DphzvQ3e8D7gvv3we4M5/kRSrwPnC5uy+OYNwiMSchPo4BbesxoG09lm7YzuuTVzFqRjYfz15DizqVubR7Kmd3TFYV7tLh70EHEAs2bN/NY18s5p3pWVQrn8CfBh/HxV1TSdAbPhGRYpWT47w3I5u/ffEDG7fv4awO9bmrf0uSq6lAp0hJES0JjNuBD8LTnR5MWKQTKlB09rGc0MyGArj7c8ADQE3gmfCbrlLTXVmkMJrWrswfzjyOu/u34ONZa3h9ykoe+Gg+j3y2iMEdkrm0WyptkqsGHaYUEXcfW5SnB740MweeDw/f+x8lvSbR7n0HeGFCJs98t5S9B3K4tmcjbj6pGVXLK/knIlLcJi//kQc/XcD8NdvomFqNYZd3pmNq9aDDEpGjZOGCxlEhXKOiTXhxvrt/G2Q86enpnpGh2nUiB7k7c7K38vrklXw8ew179ufQoUE1Lu2WyqB2mor1UMxsupKm/8vM6rv7GjOrDXwF3OLu4w61f0lqjw9Wsn9o9EKyf9rFKa3rcP/AVjTSDD8iUaGktMlm9pq7X25mt7n7k0HHc1BJao8hNE31w58t5LN566hfNZF7B7bijHb1NHxPJAocS3scLT0wAHD374Dvgo5DRPJnZrRvUI32Darx29Nb896MbN6cspK73pvDg58u4NzOKVzaLZWmtQsyIZCUZu6+Jvxzg5l9AHQFDpnAKCkWrNnGHz+Zz5TMzbSsW5k3r+1Gj6a1gg5LREqmzmbWEPiVmb1KqIDnf7j75mDCKhl27NnPM2OWMnx8JvFm/OaU5lx7YmO9bBEp4aIqgSEiJUfVCglc07MRvzohjSmZm3ljyipeD0/H2rVRDS7tlkr/NnUpV0YPCiVVUb39M7OKQJy7bw9/PxX4U6TOH4Qff97DY18tZuTUVVQtn8Bfzm7DRV1SNRWxiBTGc4SmS21MaIh17gbFw+sPy8z6A08C8cAId38kz/ZLCc1yAvAzcIO7zy586MHJyXE+nLWaRz5bxIbtezi7YzL39G9J3aqaplokFiiBISKFknsq1k0/t+a96dm8OWUVt42cRfUKCZzXOYWLuqbSJKlS0KHK0Suqt391CNU9gtDfoTfd/fNCRRqQfQdyeO37lTzx9WJ27D3AlT3SuL1fc6pWUJ0LESkcd/8n8E8ze9bdbzja480sHngaOAXIJlQ0/2N3X5Brt0ygt7v/ZGYDgGFAtwiEH4hZWVv44yfzmblqC+1TqvLsZZ3p3FB1LkRiiRIYIhIxtSqVY2jvJgw5sTETl23iramreGniCoaPz6R74xpc3FW9MkqYQr/9y4+7LwfaFzq6gE1cuok/fDyfJRt+5sRmtXhgUGua1dHwKRGJLHe/wczaAyeGV41z9zkFOLQrsDTc5mJmI4HBwH8SGO4+Kdf+k4GUyERdvDZu38NfP1/Eu9OzqVWpHH87rx3ndkohTr3gRGKOEhgiEnFxccaJzZI4sVkSG7bv5t2MbEZO+2+vjHM7hXplNK2tXhnRrLBv/2JV1uad/OXfC/l8/jpSa1Rg+BXpnNyqtgrCiUiRMLNbCc3I9H541RtmNszd/3WEQ5OBrFzL2Ry+d8U1wGeHiCEqZ4XadyCHVyat4Mmvl7B7/wGu79WYm09qqqneRWKYEhgiUqRqV07kpr5NuaF3EyYs3cTIaat4edIKRkzIpGujGlwS7pWRmKBeGdGqEG//YsrufQd4buwynh2zjDgz7jw1VBBOv7siUsSuBbq5+w4AM3sU+B44UgIjv6xqvtMPhmcCvAbomd/28FTXwyA0C0nBwi5auXvB9WqexO/PaK3hqiKlgBIYIlIs4uKMXs2T6NU8iY3b9/De9FCvjNvfnkXVjxM4u2MyF3dNpUVddcGPNoV4+xcT3J2vFqznT58uIPunXQxqV4/7B7aifrXyQYcmIqWDAQdyLR8g/+REXtlAg1zLKcCaX5zcrB0wAhjg7j8WIs5isWbLLv787wWMnqtecCKlkRIYIlLskiqX44Y+Tbi+V2O+X/4jI6dl8eaUUM+MDg2qcXHXBgxqV5+K5dRERYljfftX4q3YtIM/fDKfMT9spHmdSrx1XXeOb1Iz6LBEpHR5CZgSnnIa4CzghQIcNw1oZmaNgNXARcAluXcws1RCyenL3X1xxCIuAnv2H2DE+Eye+nYpjvObU5pzXS/1ghMpbfSvAxEJTFyccULTWpzQtBabd+zl/RnZjJyWxT2j5vKnTxZwZof6XNgllfYpVfVmJVjH+vavxNq19wDPjFnK82OXU7ZMHL89vRVX9kgjIT4u6NBEpJRx98fNbAyh4R0GXO3uMwtw3H4zuxn4gtA0qi+6+3wzGxre/hzwAFATeCb8d3a/u6cXzZ0cu3GLN/KHj+ezfNMOTjuuDr8b1JqU6hWCDktEAqAEhohEhRoVy3LtiY25pmcjZqz6ibemZvHhzDW8NTWLlnUrc0F6A87umEz1imWDDrU0Ota3fyWOu/PlgvX86ZMFrN6yi7M7JnPfgJbUrpIYdGgiUoq5+wxgxjEcNxoYnWfdc7m+X0uol11UWrNlFw9+uoDP5q0jrWYFXr66C31a1A46LBEJkBIYIhJVzIzODWvQuWENfn9Gaz6ZvZa3p63iT58u4JHPFnFam7pcmN6AHk1qanq0YnKsb/9KmlU/7uQPn8zn20UbaFGnMm8P6U63xhouIiJS3PYdyOHFCZk8+c0Scty567QWXHtiI03DLiJKYIhI9KqcmMAl3VK5pFsqC9Zs452MLD6YuZpPZq8hpXp5zu/cgPPSU0hWMcUid6xv/0qCPfsPMGzscp76bill4kzDRUREAjRl+Y/89sN5LNnwM6e0rsMDg1rToIaGi4hIiBIYIlIitK5fhT+ceRz3DmjJlwvW8860LP7x9WKe+GYxJzZL4sL0BpzcurbezshRmbBkEw98NI/lm3Zwett6/HZQK+pVVUJMRKKHmVUEdrl7jpk1B1oCn7n7voBDi6iN2/fw8GcLeX/GalKql2fEFemc3LpO0GGJSJRRAkNESpTEhHjObF+fM9vXJ2vzTt6dns17GVnc9OYMqlVI4KwOyVyQ3oDW9asEHapEsQ3bd/PnTxfy8ew1pNWswCu/6krv5klBhyUikp9xwIlmVh34BsgALgQuDTSqCMnJcd6atopHP1vErn0HuLlvU27q25TyZfVCQkR+SQkMESmxGtSowB2nNOe2fs2YuHQT72T8dzrWNslVuCC9AWe2r0+1Cir8WRix9PYvJ8d5c+oqHv18EXv25XBbv2bc0KeJpuETkWhm7r7TzK4B/uXufzWzmKhDtHDtNv7vg7nMWLWF7o1r8Oez2tK0dqWgwxKRKKYEhoiUePFxRq/mSfRqnsSWnXv5aNYa3snI4oGP5vPnTxdyynF1OL9zCic2SyJehT+PRUy8/VuwZhv3fzCXWVlb6NGkJn8+qw2Nk/SgLCJRz8zseEJt7jXhdSX6GX7n3v08+fUSRkzIpGr5BB47vz3ndErWlOkickQluvETEcmrWoWyXNkjjSt7pDFv9Vbem57Nh7NW8+85a6lbJZFzOiVzfnoDGtWqGHSoJUmJfvu3c+9+nvh6CS9MyKRa+QQev6A9Z3fUg7KIlBi3A/cBH7j7fDNrDHwXbEjH7ttF6/ndh/NZvWUXF6Y34N4BLTVFuogUWMwkMMwsntBbwdXuPijPNgOeBAYCO4GrwhX1RSSGtUmuSpvkqtw3sCXfLNzAuxlZPDd2Gc+MWUZ6w+qcn57CwLb1qJyYEHSo0a7Evv377ocN/PaDeazesouLuoQelDWkSERKEncfC4wFMLM4YJO73xpsVEdvw/bd/PGTBfx7zlqa1a7EO9cfT9dGNYIOS0RKmBLxAFpAtwELgfwq9w0AmoU/3YBnwz9FpBQoVyaegW3rMbBtPdZv2837M1bz3vQs7hk1l99/PJ8BbepxfucUujeuSZyGmOTndkrY27+N2/fw4KcL+Hj2GpokVdSDsoiUWGb2JjAUOABMB6qa2ePu/rdgIyuYnBzn7YwsHh69kN37cvjNKc25vncTypbRVNUicvRiIoFhZinA6cBfgDvy2WUw8Kq7OzDZzKqZWT13X1uccYpI8OpUSeSGPk0Y2rsxs7K28N70bD6evYYPZq4muVp5zumUzLmdUkjTEJP/KElv/9yddzKyeGj0InbtPcDtJ4eKdGp6XREpwVq7+zYzuxQYDdxDKJER9QmMpRu2c//785i6YjPdGtXgoXPa0kS1h0SkEGIigQE8AdwNVD7E9mQgK9dydnidEhgipZSZ0TG1Oh1Tq/O7Qa35Yv46Rs1YzdPfLeVf3y4lvWF1zu2cwunt6lGllA8xKSlv/1Zs2sG9789h8vLNdE2rwUPntKFp7UP9WRARKTESzCwBOAt4yt33mZkHHNNh7d2fw3Njl/HUt0spXzaev57bjvPTU1R7SEQKrcQnMMxsELDB3aebWZ9D7ZbPunwbfjMbAgwBSE1NjUSIIhLlEhPiGdwhmcEdklm3dTcfzFzNqBnZ3Pf+XP7w8XxOPa4u53ZKLs2zmET127/9B3IYMSGTf3y1mLLxcTx0dlsu6tJAw4FEJFY8D6wAZgPjzKwhsC3QiA5j5qqfuHfUXH5Yv50z2tfngUGtSapcLuiwRCRGlPgEBnACcKaZDQQSgSpm9rq7X5Zrn2ygQa7lFGBNfidz92HAMID09PSozm6LSOTVrfrfISazs7cyKjzE5JPZa6hduRxndQwNMWlRt1S92Y/at3/z12zlnlFzmLd6G6e2rsODZ7WhTpXEoMMSEYkYd/8n8M9cq1aaWd+g4jmUnXv38/cvFvPSpEzqVE7khSvT6deqTtBhiUiMKfEJDHe/j1BxOcI9MO7Mk7wA+Bi42cxGEireuVX1L0TkcMyMDg2q0aFBNX47qBXfLdrAe9NX8+KETIaNW85x9atwTqcUzmxfvzS8WYq6t3+79x3gn98s4flxy6leIYFnLu3EgDZ11T1ZRGKOmVUFfg/0Cq8aC/wJ2BpYUHlMWLKJe9+fQ/ZPu7iseyr39G+pGb5EpEiU+ATGoZjZUAB3f45Ql+eBwFJC06heHWBoIlLClCsTT/829ejfph6bft7Dx7NCRT8f/HQBD41eSO/mSZzTKZmTW9UhMSH2ikVG29u/6St/4u73ZrNs4w7O65zCb09vpalRRSSWvQjMAy4IL18OvAScE1hEYdt27+Ohfy9k5LQsGteqyNtDutOtcc2gwxKRGBZTCQx3HwOMCX9/Ltd6B24KJioRiSW1KpXjVz0b8auejVi8fjvvz1jNhzNX8+2iDVQuV4bT29Xj7I7JdEmrETM1GKLl7d+uvQf4+5c/8OLETOpXLc+rv+pKr+ZJxRmCiEgQmrj7ubmW/2hms4IK5qBvF63n/vfnsWH7bob2bsLtJzeLySS+iESXmEpgiIgUp+Z1KnPvgJbcdVoLJi//kVEzQvUyRk7LIrlaec7umMzZnZKDDjMSAn/7t2PPfvo/OY6VP+7k8u4NuWdASyqV058wESkVdplZT3efAGBmJwC7ggrmQI7z67dn8cHM1bSoU5nnL+9M+wbVggpHREoZPf2JiBRSfJxxQtNanNC0Fn8+az9fzF/H+zNW88yYpTz13dKgw4uEwN/+Ld+0gySHt67rzvFN1D1ZREqVocCr4d5wAD8BVxbkQDPrDzwJxAMj3P2RPNstvH0goWHWV7n7jMOdc/H67WyfvYZb+zXjpr5NKFdGvS5EpPgogSEiEkEVypbh7I4pnN0xhQ3bdvPRrDUMeTToqAot8Ld/tSqV4/PbT6RCWf3ZEpHSxd1nA+3NrEp4eZuZ3Q7MOdxxZhYPPA2cQmhGvmlm9rG7L8i12wCgWfjTDXg2/POQEuLj+PjmnrSuX+UY70hE5NjFBR2AiEisql0lket6NQ46jEgYCjxtZivMbAXwFHB9YU5oZv3N7AczW2pm9x5p/3pVE5W8EJFSzd23ufvBGaDuKMAhXYGl7r7c3fcCI4HBefYZDLzqIZOBamZW73AnbVq7kpIXIhIYJTBEROSw3H22u7cH2gHt3L0jcNKxni/XW8EBQGvgYjNrHZFgRURKh4JUiU4GsnItZ4fXHe0+mNkQM8sws4yNGzcebawiIhGjBIaIiBTIMbz9O5SCvBUUEZFD8wLsk1+SI+9xBdkHdx/m7ununp6UpNmfRCQ46o8rIiLHojBzxOb3xu8XY67NbAgwBCA1NbUQlxMRKXnMbDv5JyoMKF+AU2QDDXItpwBrjmEfEZGoEbEEhpkdtpBQ2EZ37xepa4qISGAK8vbvUAr8xg8YBpCenl6Y64mIlDjuXrmQp5gGNDOzRsBq4CLgkjz7fAzcbGYjCSWSt7r72kJeV0SkyESyB0Y8oSmYDsUINZIiIlICRODt36HojZ+ISBFz9/1mdjPwBaHn9Bfdfb6ZDQ1vfw4YTej5fSmhaVSvDipeEZGCMPfIvNTKPcVeYfaJJma2EVgZdBwRUAvYFHQQRSzW71H3V7K1iMCbtAIzs04F2G2fu88t8mDyYWZlgMVAP0JvBacBl7j7/MMcEyvtMcT+77vur+SL9Xss1jY51qg9LlFi/f4g9u8x1u/vqNvjiPXAyC8xYWZNgAoHH5JLUvICwN1jokqRmWW4e3rQcRSlWL9H3V/JZmYZxXzJsYSSAoerU9EISCuWaPI41FvBIxwTE+0xlI7fd91fyRbr9xhAmxxT1B6XHLF+fxD791ga7u9ojymyIp5mdj/QFsgxsxx3v7yoriUiIv9jmrsfdppTM/u2uILJj7uPJtR1WURERESkQCI2jaqZ3WJm8blWtXf3i939UqB9pK4jIiKHd6TkRUH3ERERERGJJhFLYAA/AZ+b2Rnh5S/NbKyZjSfUTViCMyzoAIpBrN+j7q9kC/T+zCzJzP5sZo+ZWdMgYxFAv+8lXazfH8T+Pcb6/UnBxfrvQqzfH8T+Per+8ohYEU8AM0sE7gLSgQeAJUCCu2+N2EVEROSomNmrwOuEZhR5yN27BBySiIiIiMhRi2QPDIAmwNvA9cDNwBMUbqo9ERE5Smb2uZmdmGtVWWBF+FMuiJhERERERAorkjUwXgbuAx4G7nD364BngeFm9rtIXUcOz8xeNLMNZjYv17oaZvaVmS0J/6weZIyFYWYNzOw7M1toZvPN7Lbw+pi4RzNLNLOpZjY7fH9/DK+Pifs7yMzizWymmX0aXo61+1thZnPNbNbB6srFfI8XAoPN7M3wbFC/I9Qr7hHgxiK8ruSi9jgm7lFtcgm/vyhojyVKqE0u2feo9jhm7q/QbXIke2B0dPfL3P1c4BQAd5/p7mcAcyJ4HTm8l4H+edbdC3zj7s2Ab8LLJdV+4Dfu3groDtxkZq2JnXvcA5zk7u2BDkB/M+tO7NzfQbcBC3Mtx9r9AfR19w65pr4qtnt0963ufifwW+DPhHrF3eTu55a06axLuJdRe1zS71FtcmzcX2DtsUSVl1GbXJLvUe1xbNwfFLZNdveIfIBHgbHA98BdkTqvPsf0/0UaMC/X8g9AvfD3esAPQccYwXv9iFDCLObuEagAzAC6xdL9ASnhxukk4NPwupi5v/A9rABq5VlXbPcINAb+BjwE1AdOJFRM+RYgPuj/fUrTR+1x7Nyj2uTgYz3G+wu0PdYnuj5qk2PjHtUeBx9rIe6x0G1yxHpguPs9wBnAKe7+t0idVyKijruvBQj/rB1wPBFhZmlAR2AKMXSP4a5js4ANwFfuHlP3R6g2zt1ATq51sXR/ECqW+aWZTTezIeF1xXmPbwGfA5OB19x9vLufBmwDvizC68qRxdrvOhC77TGoTY6B+wu6PZboFpO/C7HaJqs9LvH3BxFok8tEKhIzG+TunxZ2H5GCMLNKwCjgdnffZmZBhxQx7n4A6GBm1YAPzKxNwCFFjJkNAja4+3Qz6xNwOEXpBHdfY2a1ga/MbFExXz8RyAQqEnpLAYC7v2Jm7xRzLBLjYrk9BrXJMSDo9likWMVym6z2OCYUuk2OWAID+JuZrQYO91/JQ4ASGMVvvZnVc/e1ZlaPUNayxDKzBEIN8xvu/n54dUzdI4C7bzGzMYTGa8bK/Z0AnGlmAwn9I7uKmb1O7NwfAO6+Jvxzg5l9AHSleO/xBkJDSPYCQ/PEtqsIrytHFlO/66WlPQa1yYFGWQhR0B5LdIup34XS0iarPS65ItEmR7KI53rgceCxw3yWRPB6UnAfA1eGv19JaExciWShNPILwEJ3fzzXppi4RzNLCmeVMbPywMnAImLk/tz9PndPcfc04CLgW3e/jBi5PwAzq2hmlQ9+B04F5lGM9+jukzxUsPNid59dVNeRYxJLv+sx3R6D2uTwbiX2/qKhPZaoFzO/C7HeJqs9Bkrw/UHk2mQLF8uQGGFmbwF9gFqEkkq/Bz4E3gFSgVXA+e6+OaAQC8XMegLjgbn8d3zY/YTG+JX4ezSzdsArQDyhBOM77v4nM6tJDNxfbuHucXe6+6BYuj8zawx8EF4sA7zp7n8pzns0s2HuPqSw+0jhqD2OiXtUm1yC7y8a2mOJHmqTS/Y9qj0u+fcXqTZZCQwRkRhjZhuAkYfbBejvoemqRERERERKhEjWwBARkehwVwH2GV/kUYiIiIiIRJB6YIiIiIiIiIhI1ItkEU8AzKyCmf3OzIaHl5uFp4URERERERERETkmEU9gAC8Be4Djw8vZwJ+L4DoiIiIiIiIiUkoURQKjibv/FdgH4O67CBWMExGRAISnqhIRERERKdGKIoGxNzw3rwOYWRNCPTJEIsrM6prZSDNbZmYLzGy0mTU/hvOMMbP0oojxKOO4ysyeCjoOiR1m1sPMFgALw8vtzeyZgMOSGKT2WEQkeqhNllhWFAmM3wOfAw3M7A3gG+DuIriOlGJmZoTmER7j7k3cvTWhua7rBBtZcMwsPugYJOr8AzgN+BHA3WcDvQKNSGKO2uNfUnssIkFRm/xLapNjS8QTGO7+FXAOcBXwFpDu7mMifR0p9foC+9z9uYMr3H2Wu483s9fMbPDB9Wb2hpmdaWbxZvZ3M5trZnPM7Ja8JzWzU83sezObYWbvmlmlfPYZY2aPmtlUM1tsZieG1/9PdtjMPjWzPuHvP4ePmW5mX5tZ1/B5lpvZmblO38DMPjezH8zs97nOdVn4erPM7PmDDXH4vH8ysyn8t+6MyH+4e1aeVQcCCURimdpj1B6LSNRQm4za5FgWsQSGmXU6+AEaAmuBNUBqeJ1IJLUBph9i2wjgagAzqwr0AEYDQ4BGQEd3bwe8kfsgM6sF/BY42d07ARnAHYe4Rhl37wrcTqjX0ZFUJJQJ7wxsJ1TY9hTgbOBPufbrClwKdADON7N0M2sFXAic4O4dCP0D9NJc553n7t3cfUIB4pDSJcvMegBuZmXN7E7Cw0lEIkjt8X/Pq/ZYRIKmNvm/51WbHIPKRPBcj4V/JgLpwGxCxTvbAVOAnhG8lsghuftYM3vazGoT6g00yt33m9nJwHPuvj+83+Y8h3YHWgMTzQygLPD9IS7zfvjndCCtAGHtJTS0CmAusMfd95nZ3DzHf+XuPwKY2fuE/rvZD3QGpoXjKg9sCO9/ABhVgOtL6TQUeBJIJjQj1JfATYFGJKWK2mMRkeihNlliQcQSGO7eF8DMRgJD3H1ueLkNcGekriMSNh847zDbXyOUgb0I+FV4nREuLnsIRqhxvLgA1z9YmPYA//3vaD//26spMdf3fe5+8No5B4939xwzy/3fYd74PBzXK+5+Xz5x7HZ3DQmQfLn7Jv77JkKkqKg9DlF7LCLRQG1yiNrkGFUURTxbHkxeALj7PEJdfUQi6VugnJldd3CFmXUxs97hxZcJdV3D3eeH130JDD3YGJpZjTznnAycYGZNw9sr2NFVbF4BdDCzODNrQKir29E6xcxqWGgmn7OAiYQK4Z4XzpYT3t7wGM4tpYSZ/cvM/nmoT9DxScxReywiEj3UJktMK4oExkIzG2Fmfcyst5kNR2OuJcLCmdqzCTVmy8xsPvAHQnVXcPf1hH7vXsp12AhgFTDHzGYDl+Q550bCxWfNbA6hxrrlUYQ1Ecgk1P3t78CMo74xmEAoMz6LULe+DHdfQGjc4ZfhuL4C6h3DuaX0yCDUdTMR6AQsCX86oCKeEmFqj9Uei0j0UJusNjnW2X977ETohGaJwA38d6q+ccCz7r47ohcSOQwzq0Cokezk7luDjkckCGb2HXCqu+8LLycAXx4c8idSHNQei4hED7XJUtJFsognAO6+28yeBr4mNDbph4MPzyLFIVyI6EXgcTXMUsrVByoDB4txVQqvEykWao9FRKKH2mSJBUXRA6MP8AqhsU4GNACudPdxEb2QiIgclpldTajb6HfhVb2BP7j7K4EFJSIiIiJyjIoigTEduMTdfwgvNwfeCs/tKyIixcjM6gLdCPWIm+ru6wIOSURERETkmER8CAmQcDB5AeDui8PjrkVEpPh1BU4Mf3fgkwBjERERERE5ZkXRA+MlQnP4vhZedSlQxt2vjuiFRETksMzsEaAL8EZ41cVAxiHmSxcRERERiWpFkcAoB9wE9CRUA2Mc8Iy774nohURE5LDCU4p1cPec8HI8MNPd2wUbmYiIiIjI0YvoEBIziwOmu3sb4PFInltERI5JNf47C0nVAOMQERERESmUiCYw3D3HzGabWaq7r4rkuUVE5Kg9BMw0s+8I9YjrBWj4iIiIiIiUSEVRxLMeMN/MpgI7Dq509zOL4FoiIpKPcI+4HKA7oToYBtyjWUhEREREpKQqihoYvfNb7+5jI3ohERE5LDMb5+69go5DRERERCQSiqIHxkB3vyf3CjN7FFACQ0SkeH1lZncCb/O/PeI2H/oQEREREZHoVBQ9MGa4e6c86+ao6r2ISPEys8x8Vru7Ny72YERERERECiliPTDM7AbgRqBJeOq+gyoDkyJ1HRERKbBW7r479wozSwwqGBERERGRwohYDwwzqwpUBx4G7s21abu6K4uIFL9D9Ij7xToRERERkZIgYj0w3H0rsNXMngQ2u/t2ADOrbGbd3H1KpK4lIiKHZmZ1gWSgvJl1JDQDCUAVoEJggYmIiIiIFEJR1MCYCXTy8InDU/lllMQ3frVq1fK0tLSgwxCREm769Omb3D2puK5nZlcCVwHpwDT+m8DYBrzi7u8XVyyRovZYRCKluNvkWKP2WEQi5Vja46KYhcQ8V1bE3XPMrCiuU+TS0tLIyMgIOgwRKeHMbGVxXs/dXwFeMbNz3X1UcV67qKg9FpFIKe42OdaoPRaRSDmW9jiuCOJYbma3mllC+HMbsLwIriMiIofX2cyqHVwws+pm9ucA4xEREREROWZFkcAYCvQAVgPZQDdgSBFcR0REDm+Au285uODuPwEDgwtHREREROTYRXxoh7tvAC6K9HlFROSoxZtZOXffA2Bm5YFyAcckIiIiInJMIt4Dw8yam9k3ZjYvvNzOzH4b6euIiMgRvQ58Y2bXmNmvgK+AVwKOSURESrCdew8EHYKIlGJFMYRkOHAfsA/A3eegHhkiIsXO3f8K/BloBRwHPBheJyIickyWbfyZ+96fy7bd+4IORURKoaKYHaSCu081s9zr9hfBdURE5MgWAvvd/Wszq2Bmld19e9BBiYhIyVSrUjnenraKMT9s4KGz29K3Ze2gQxKRUqQoemBsMrMmgAOY2XnA2iK4joiIHIaZXQe8BzwfXpUMfBhYQCIiUuLVq5rIqBt6UKlcGa5+eRp3vDOLLTv3Bh2WiJQSRZHAuInQw3JLM1sN3A7cUATXERGRw7sJOAHYBuDuSwC9KhMRkULpmFqdT2/tyS0nNeWjWWs4+fFxfD5P7ytFpOhFPIHh7svd/WQgCWjp7j3dfUWkryMiIke0x93/81rMzMoQ7h0nIiJSGOXKxPObU1vw0U0nULtyOYa+PoOhr01nw7bdQYcmIjEsYjUwzOyOQ6wHwN0fj9S1RESkQMaa2f1AeTM7BbgR+CTgmEREJIa0Sa7KRzefwPDxy3ni6yVMenwT/3d6Ky5Ib0CemngiIoUWyR4YlY/wERGR4nUvsBGYC1wPjAY0rbWIiERUQnwcN/Zpyue3nUjLelW4Z9RcLh0xhZU/7gg6NBGJMRHrgeHuf4zUuUREpPDcPYfQ1NbDg45FRERiX+OkSoy8rjsjp2Xx8OiFnPbEOG4/uTnX9GxEQnxRlN4TkdIm4i2JmTU3s2/MbF54uZ2Z6Y2fiEgxMbO5ZjbnUJ+g4xMRkdgVF2dc0i2Vr+7oTa9mSTzy2SLOfGois7O2BB2aiMSAiPXAyGU4cBfhafvcfY6ZvQn8uQiuJSIivzQo6ABERKR0q1s1kWFXpPP5vHX8/uN5nP3MRK44Po07T2tBpXJF8U8QESkNiqIvVwV3n5pn3f5InNjM+pvZD2a21MzuzWe7mdk/w9vnmFmnPNvjzWymmX0aiXhERKKRu688+Amvahb+vgHYHIlrqD0WEZGC6N+mLl/f0ZvLujfkle9XcMrjY/lqwfqgwxKREqooEhibzKwJ4an6zOw8oNATQ5tZPPA0MABoDVxsZq3z7DYAaBb+DAGezbP9NmBhYWMRESkJzOw64D3CPeKAFODDCJxX7bGIiBRY5cQE/jS4DaNu6EGVxASuezWD61/LYO3WXUGHJiIlTFEkMG4i9LDc0sxWA7cDQyNw3q7AUndf7u57gZHA4Dz7DAZe9ZDJQDUzqwdgZinA6cCICMQiIlIS3AScAGwDcPclQO0InFftsYiIHLVOqdX59Nae3NO/JWMXb+Tkx8bywoRM9h/ICTo0ESkhIp7ACD/QngwkAS3dvWeubsyFkQxk5VrODq8r6D5PAHcDaiFFpLTYE04wAGBmZQj3jisktcciInJMEuLjuKFPE776dW+6NqrBg58uYPDTE5mlIp8iUgBFNp+Ru+9w9+0RPKXld5mC7GNmg4AN7j79iBcxG2JmGWaWsXHjxmOJU0QkWow1s/uB8mZ2CvAu8EkEzqv2WERECqVBjQq8eFUXnrm0E5t+3sPZz0zkdx/OY+uufUGHJiJRrCRNyJwNNMi1nAKsKeA+JwBnmtkKQl2dTzKz1/O7iLsPc/d0d09PSkqKVOwiIkG4F9gIzAWuB0YDkZjWWu2xiIgUmpkxsG09vr6jN1cen8YbU1bS77ExvD8jG/dIdBgUkVhTkhIY04BmZtbIzMoCFwEf59nnY+CKcPX77sBWd1/r7ve5e4q7p4WP+9bdLyvW6EVEipm757j7cHc/393PC3+PxBOh2mMREYmYyokJ/OHM4/j45p6kVK/AHe/M5sJhk1m8PpKduUUkFkQ8gWFmFczsd2Y2PLzcLNxluFDcfT9wM/AFocr177j7fDMbamYHi4SOBpYDS4HhwI2Fva6IiPwvtcciIlIU2iRX5f0bevDwOW35Yd12Bj45nodHL2THnv1BhyYiUcIi3T3LzN4GpgNXuHsbMysPfO/uHSJ6oWKQnp7uGRkZQYchIiWcmU139/Sg4yjJ1B6LSKSoTS6c4mqPf/x5D49+voh3MrKpWyWR3w5qxelt62GWX4klESmJjqU9LoohJE3c/a/APgB330X+xdxERKQYmFnFoGMQERE5GjUrleOv57Vn1A09qFmpLDe/OZPLXpjC0g0aViJSmhVFAmNvuNeFA5hZE2BPEVxHREQOw8x6mNkCQsM8MLP2ZvZMwGGJiEiEmVl/M/vBzJaa2b35bK9qZp+Y2Wwzm29mVxf02KB1blidj2/uyYODj2Nu9lb6PzGeh0Yv5GcNKxEplYoigfEH4HOggZm9AXwD3F0E1xERkcP7B3Aa8COAu88GegUakYiIRJSZxQNPAwOA1sDFZtY6z243AQvcvT3QB3jMzMoW8NjAxccZlx+fxnd39uGcTskMG7ecfo+N4aNZqzVbiUgpE/EEhrt/CZwDXAW8BaS7+5hIX0dERI7M3bPyrDoQSCAiIlJUugJL3X25u+8lNEX14Dz7OFDZQgUkKgGbgf0FPDZqHBxW8v6NPahTJZHbRs7igue/Z/6arUGHJiLFpChmIfkYOBUY4+6fuvumSF9DREQKJMvMegAeftN2J+HhJCIiEjOSgdzJ6uzwutyeAloBa4C5wG3unlPAYzGzIWaWYWYZGzdujGTsx6RTanU+vPEEHjmnLcs27uCMf03gtx/O5acde4MOTUSKWFEMIXkMOBFYYGbvmtl5ZpZYBNcREZHDG0qo23AyoYfSDuFlERGJHfkVy887ruI0YBZQn9DfgqfMrEoBj8Xdh7l7urunJyUlFS7aCImLMy7qmsp3v+nDFcen8dbULPr8fQyvfb+C/Qdygg5PRIpIUQwhGevuNwKNgWHABcCGSF9HRESOyNz9Unev4+613f0yd/8x6KBERCSisoEGuZZTCPW0yO1q4H0PWQpkAi0LeGxUq1ohgT+ceRz/vrUnretV4Xcfzef0f05g0lJ1AheJRUXRA4PwLCTnEnr71wV4pSiuIyIihzXJzL40s2vMrFrQwYiISJGYBjQzs0ZmVha4CPg4zz6rgH4AZlYHaAEsL+CxJULLulV487puPHdZJ3bs3c8lI6Yw9LXpZG3eGXRoIhJBZSJ9QjN7G+hGaCaSpwnVwlA/LhGRYubuzcysK6EH0v8LT6k60t1fDzg0ERGJEHffb2Y3A18A8cCL7j7fzIaGtz8HPAi8bGZzCQ0buedgnbr8jg3iPiLBzOjfph59WtRmxPjlPP3dMr79YQPXndiIG/s0pWK5iP/TR0SKmUV66iEz6w985e4lvtJ9enq6Z2RkBB2GiJRwZjbd3dMDjqEW8DhwqbvHBxnLsVB7LCKREg1tcklWktrjdVt38+jni/hg5mqSKpfj7tNacG6nFOLi8iv9ISLF7Vja44gNITGzk8JfKwCDzeyc3J9IXUdERArGzKqY2ZVm9hkwCVhLaMo8ERGRmFe3aiL/uLADo27oQXK18tz13hzOfHoCU5arHJRISRXJflS9gW+BM/LZ5sD7EbyWiIgc2WzgQ+BP7v59wLGIiIgEonPD6rx/Qw8+mbOGRz5bxIXDJjOwbV3uG9CKBjUqBB2eiByFiCUw3P334a9/cvfM3NvMrFGkriMiIgXW2CM9TlBERKQEioszBndI5tTWdRk+fjnPjlnG1ws2cPUJadzYtylVyycEHaKIFEBRzEIyKp917xXBdUREJB9m9kT468dm9otPkLGJiIgEqXzZeG7t14zv7uzDmR3qM2z8cvr+fQyvfr+CfQc074BItItYDwwzawkcB1TNU/OiCpAYqeuIiMgRvRb++fdAoxAREYlSdasm8vfz23NVjzT+8u+FPPDRfF6ZtIL7B7bipJa1MVOhT5FoFMkeGC2AQUA1QnUwDn46AddF8DoiInIY7j49/LWDu4/N/QE6BBiaiIhIVGmTXJU3r+vGiCvScYdrXsng0hFTmLd6a9ChiUg+IlkD4yPgIzM7XsXiRESiwpXAk3nWXZXPOhERkVLLzDi5dR16t0jizSmrePKbJQz61wTO7pjMnae1ILla+aBDFJGwSM5CctBMM7uJ0HCS/wwdcfdfFcG1REQkDzO7GLgEaJSn5kVlQHPHiYiI5CMhPo4re6Rxdqdknh2zjBcnZPLvuWv51QmNuLFvE6okqtCnSNCKoojna0Bd4DRgLJACbI/Eic2sv5n9YGZLzezefLabmf0zvH2OmXUKr29gZt+Z2UIzm29mt0UiHhGRKDUJeAxYFP558PMboH8kLqD2WEREYlWVxATu6d+Sb+/sw6C29Xhu7DJ6//U7XpyQyd79KvQpEqSiSGA0dfffATvc/RXgdKBtYU9qZvHA08AAoDVwsZm1zrPbAKBZ+DMEeDa8fj/wG3dvBXQHbsrnWBGRmODuK919jLsfn6cGxgx331/Y86s9FhGR0iC5Wnkev7ADn97Sk9b1q/CnTxfQ7/ExfDx7DTk5mqVcJAhFkcDYF/65xczaAFWBtAictyuw1N2Xu/teYCQwOM8+g4FXPWQyUM3M6rn7WnefAeDu24GFQHIEYhIRiTpmNiH8c7uZbcv12W5m2yJwCbXHIiJSarRJrsrr13TjlV91pVK5BG59ayaDn57IpKWbgg5NpNQpigTGMDOrDvwO+BhYAPw1AudNBrJyLWfzy4feI+5jZmlAR2BKfhcxsyFmlmFmGRs3bixszCIixc7de4Z/Vnb3Krk+ld29SgQuofZYRERKFTOjd/Mk/n1LTx6/oD2bd+zlkhFTuPLFqcxfoxlLRIpLxBMY7j7C3X8Kd1du7O613f25CJw6v8mY8/bdOuw+ZlYJGAXc7u75voV092Hunu7u6UlJScccrIhI0MysiZmVC3/vY2a3mlm1SJw6n3Vqj0VEJObFxRnndErhm9/05v6BLZmVtYXT/zmB20bOZNWPO4MOTyTmRXwWEjO7I5/VW4Hp7j6rEKfOBhrkWk4B1hR0HzNLIPSw/Ia7v1+IOERESopRQLqZNQVeINQr7k1gYCHPq/ZYRERKtcSEeIb0asKFXVJ5fuwyXpyYyei5a7m0W0NuPqkptSqVCzpEkZhUFENI0oGhhLoKJxMq3tYHGG5mdxfivNOAZmbWyMzKAhcRehjP7WPginD1++7AVndfa2ZG6OF9obs/XogYRERKkpxw0c6zgSfc/ddAvQicV+2xiIgIULV8Anf3b8nYu/pyXucGvDZ5Jb3/+h2Pf7WY7bv3HfkEInJUiiKBURPo5O6/cfffEEpoJAG9gKuO9aThh/CbgS8IFX17x93nm9lQMxsa3m00sBxYCgwHbgyvPwG4HDjJzGaFP4V9AykiEu32mdnFwJXAp+F1hZ7EXu2xiIjI/6pTJZGHz2nLl7/uRe8WSfzzmyX0+ut3DB+3nN37DgQdnkjMiPgQEiAV2JtreR/Q0N13mdmewpzY3UcTeijOve65XN8duCmf4yaQ/3hsEZFYdjWhHnF/cfdMM2sEvB6JE6s9FhER+aUmSZV45tLOzM3eyl+/WMRfRi/khQmZ3HZyM87vnEKZ+KJ4fyxSehTFf0FvApPN7Pdm9ntgIvCWmVUkNCOJiIgUA3dfANwJzA1Pa53t7o8EHJaIiEjMa5tSldeu6cZb13WnXrVE7nt/Lqf8Yxwfz15DTk7eutciUlBFMQvJg8B1wBZCxTuHuvuf3H2Hu18a6euJiEj+zKwPsAR4GngGWGxmvYKMSUREpDQ5vklN3r+hB8OvSKdsfBy3vjWTgf8cz9cL1hPqrCgiR6MohpAAlAe2uftLZpZkZo3cPbOIriUiIvl7DDjV3X8AMLPmwFtA50CjEhERKUXMjFNa16Ffy9p8MmcN//hqMde+mkGHBtW467QWnNC0VtAhipQYEe+BER42cg9wX3hVAhEacy0iIkcl4WDyAsDdFxOBIp4iIiJy9OLijMEdkvnqjt48ck5bNmzbzaUjpnDxsMlkrNgcdHgiJUJR1MA4GzgT2AHg7muAykVwHRERObwMM3vBzPqEP8OB6UEHJSIiUpolxMdxUddUvr2zDw8Mas2SDT9z3nPfc+WLU5mTvSXo8ESiWlEkMPaGq887QLh4p4iIFL8bgPnArcBthAopDz3sESIiIlIsEhPi+VXPRoy7uw/3DWjJnOwtnPnURK57NYOFa7cFHZ5IVCqKGhjvmNnzQDUzuw74FTC8CK4jIiKH4e57zOwp4BsgB/jB3fce4TAREREpRhXKluH63k24pFsqL01cwfDxyxnw5HhOb1uP205uRvM66swuclDEExju/nczOwXYBrQAHnD3ryJ9HREROTwzOx14DlgGGNDIzK5398+CjUxERETyqpyYwK39mnHl8WkMH7+clyZmMnreWs5oV59b+zWjae1KQYcoErgimYUknLBQ0kJEJFiPAX3dfSmAmTUB/g0ogSEiEmXMrA6QTGgY9hp3Xx9wSBKQqhUSuPO0FlzTsxHDxy/n5Ukr+HTOGgZ3SObWfs1oVEsj9KX0ingCw8zOAR4FahN642eAu3uVSF9LREQOa8PB5EXYcmBDUMGIiMgvmVkHQr3lqgKrw6tTzGwLcKO7zwgoNAlY9Yplubt/S67p2Yhh45bzyvcr+GjWas7qmMwtJymRIaVTUfTA+CtwhrsvLIJzi4hIwc03s9HAO4Te6J0PTAsnmnH394MMTkREAHgZuN7dp+ReaWbdgZeA9kEEJdGjZqVy3DewFdee2Jhh45bx2uSVfDhTiQwpnYoigbFeyQsRkaiQCKwHeoeXNwI1gDMIJTSUwBARCV7FvMkLAHefrNn8JLekyuX4v9NbM6RXk18kMm7u25TGSaqRIbGvKBIYGWb2NvAhsOfgSr3pExEpXu5+ddAxiIjIEX1mZv8GXgWywusaAFcAnwcWlUStQyUyzmxfn5tPUrFPiW1FkcCoAuwETs21Tm/6RERERETycPdbzWwAMJhQEU8DsoGn3X10Qc5hZv2BJ4F4YIS7P5Jn+13ApeHFMkArIMndN5vZCmA7cADY7+7phb8rKQ65ExnDxy/nte9X8tHsNQxqV59bTmqq6VclJhXFNKp64yciIiIiUkDh6a2PaYYoM4sHngZOIZT4mGZmH7v7glzn/xvwt/D+ZwC/dvfNuU7T1903HWv8EqykyuW4f2Arru/VmOHjM3n1+9CsJQPb1OPmk5rSqp7mUpDYUSTTqIqIiIiIyJGZWRngGuAsck2jCnwEvODu+45wiq7AUndfHj7fSEK9ORYcYv+LgbcKH7lEm5qVynHvgJYM6dWYFydk8vKkFfx77lpOaV2HW05qSruUakGHKFJoSmCIiMQoMysHnAukkau9d/c/BRWTiIj8wmvAFuCPhHpQAKQAVwKvAxce4fhk/ls7g/A5uuW3o5lVAPoDN+da7cCXZubA8+4+LJ/jhgBDAFJTU48QjgStRsWy3HlaC647sTEvTcrkxQmZfLVgPb2bJ3Frv6Z0blgj6BBFjllc0AEcDTPrb2Y/mNlSM7s3n+1mZv8Mb59jZp0KeqyISAz6iNBbuP3AjlyfQlN7LCISMZ3c/QZ3n+zu2eHPZHe/AehYgOMtn3V+iH3PACbmGT5ygrt3AgYAN5lZr1+czH2Yu6e7e3pSUlIBQpJoULVCAref3JyJ957E3f1bMHf1Vs599nsuHjaZSUs34X6oXxOR6BXxHhhF9cavIOP7CDW8zcKfbsCzQLcCHisiEmtS3L1/pE+q9lhEJKJ+MrPzgVHungNgZnHA+cBPBTg+m9CsJQelEBqCkp+LyDN8xN3XhH9uMLMPCA1JGXdUdyBRrXJiAjf2acpVPdJ4c8oqho1bziUjptAxtRo3923KSS1rY5ZfHkwk+hTFEJKPgK3AdHJNoxoBBRnfNxh41UPpxMlmVs3M6hFKphzN2EAAlm/cwYXPfx/BWxARKVaTzKytu8+N8HnVHouIRM5FwKPAM/b/7N13fJXl+cfxz5VFIEBYAUIg7CGyhLCR5QKr4qx7VUtt1draoXbZ+utwdWirtWrd4l64RWUoygh77xX2kD2TXL8/zhONaYBAzsk5Ofm+X6/zOufZ123j5dPruZ/7NisqWNQBxgbbjmYq0NbMWgJrg2MuK7mTmaUDg4Ariq1LAxLcfVfw+3RArxnGqRopSVx/ciuu6NOcV6fl8cj4ZVz3dC4nZNbmxiGtGd4pk8QEFTIktkWigBGRJ36U7f2+0vbJKuOxwLff8auZ2bp8EYuIRNcA4BozW0GooGyAu3uXcp5X+VhEJEzcfSXBOBdmVh+wY5kRxN3zzewm4ENC06g+4e7zzOyGYPsjwa7nAR+5e/FXCRsBbwRP35OAUe7+QTmbJDEuNTmRK/o05+KezXhr5joeHreUm0bNoFWDxdwwuDXndssiJalSjTQgVUgkChiReuJXlvf7DrdPmd8NDAYuehQgJyfHX/pB32OJUUTkf7x8Q9QuPTxC51U+FpFKK4o5+ajcfWvxZTM7zd3HlOG494D3Sqx7pMTyU8BTJdYtB7oeZ7hSySUnJnBhj6acd1IWH8zdwMPjlvLLV2fzjzGL+f7AVlzSM5vqKYnRDlPkWyJRwIjUE7+yvN93uH1SynCsiEhcMLPa7r4T2BWhSygfi4hUjP8CmvZDIioxwfhOl0zO7NyY8Ys38/DYZfzh7fn869OlXNu/BVf2bUF69eRohykCRKaAEaknfmV5v280cFPwTnVvYIe7rzezzWU4VkQkXowCziI0FlHJXg8OtCrn+ZWPRUTCxMxGH24TUL8iY5GqzcwY3L4hg9s3ZOrKbTw0din3f7SYR8Yv5/Le2Vw3oCUNa6dGO0yp4sJWwIj0E78yvt/3HnAmsBTYC1x7pGMjEaeISLS5+1nBd8sInV/5WEQkfE4mNLDm7hLrjdCgySIVrmeLejx1bS/mrdvBf8Yv57HPlvPkxJVc0KMpPxjYihYN0qIdolRRFq75f83sHXc/K3h15H+e+Ll7eZ/4VbicnBzPzc2NdhgiUsmZ2TR3z4l2HJWZ8rGIhEus5WQzex+4193HlrJtgrsPjEJYh6V8XDWt2rqHRycs55VpeeQXFDK8UyY3DGpN56bp0Q5NKrHjycdh64ER6Sd+IiIiIiLxxt0P+/p1rBUvpOpqXj+NP53XmVtObcsTn6/k+UmreHfOevq3qc8Ng1ozoE0DgtlsRCJK8+OIiIiIiMQ4M/sy2jGINKyVyu3DO/DFHUO5Y3gHlmzczZX/ncJZ//yc0bPWkV9QGO0QJc5FYhBPERGJIjOrd6Tt7r6tomIREZGw0eiJEjNqpSbzg0GtuaZ/C96csZb/TFjOj1+YwX31qnP9gFZclNOUGin6v5oSfvqrEhGJP6XNPlIkHLOQiIhIxQvPwHUiYVQtKZGLe2ZzUY9mjFmwkf+MX8ado+fx948Xc1Wf5lzVrwUNalaLdpgSR8I5C4me+ImIxACNRSQiIiIVKSHBOOPExpxxYmNyV27jPxOW8+CnS/nPhOVc2KMp15/cipaauUTCIJw9MPTET0QkxphZXaAtxboeu/uE6EUkIiKlMbOO7j6/xLrB7j6uaLHioxI5djkt6pHToh5LN+3msQnLeSU3j1FTVnN6x0aMHNiKHs2P+Nxb5IjCOQuJnviJiMQQM7seuAVoCswE+gBfAkOjGJaIiJTuZTN7FriXUNH5XiAH6BtsvzJagYkcjzYNa3LPhV342RnteOaLVTw7aRUfzttI9+w6jBzYitM6NiYxQXU5OTYRmYXEzOqaWS8zG1j0icR1RETkiG4BegKr3H0IcBKwObohiYjIYfQGmgFfAFOBdUD/oo3uPjdKcYmUS8Naqfz8jPZ8ecdQ/nDOiWzefYAbnpvO0L+O4+kvVrL3YH60Q5RKJOwFjOCJ3wTgQ+APwffvw30dERE5qv3uvh/AzKq5+0KgfZRjEhGR0h0C9gHVCfXAWOHumpNS4kaNlCSu7teCcT8fwsOXd6deWgp3jp5H3798yr0fLGTjzv3RDlEqgUj0wNATPxGR2JBnZnWAN4ExZvYWoSd6IiISe6YSKmD0BAYAl5rZq9ENSST8EhOMMztn8saP+vPaD/vSr3V9Hhm/jAH3fMqtL89k3rod0Q5RYlgkplHd7+77zezrJ35mpid+IiIVzN3PC37+3szGAunAB1EMSUREDu86d88Nfm8ARpiZxr2QuNajeT16NK/Hqq17eHLiSl7OXcPr09fSr3V9rhvQkiHtG5KgcTKkmEgUMEo+8fsKPfETEakwZlbb3XeWmN56TvBdE9C01iIiMaZY8aL4umejEYtIRWteP43fn3MiPz21HS9MXc3TX6zkuqdzadUgjWsHtOTC7k2pnpIY7TAlBoS9gKEnfiIiUTcKOItvT29d/FvTWouIiEjMSa+RzA2DWnPdgJa8N2c9//18Bb99cy73f7iIy3pnc1Xf5mSmV492mBJFYStg6ImfiEhscPezzMyAQe6+OtrxiIiIiByL5MQERnTL4pyuTchd9RVPfL6C/4xfxqMTlnNm50y+178FJ2XXjXaYEgXh7IGhJ34iIjHC3d3M3gB6RDsWERERkeNhZvRsUY+eLeqxZttenvlyJS9OWcPbs9bRPbsO1/ZvybBOjUlOjMTcFBKLwlbA0BM/EZGYM8nMerr71GgHIiIiIlIezerV4Nff6cgtp7bj1dw1PPnFSm5+YQaZ6alc0ac5l/XKpm5aSrTDlAgLa6nK3R14I5znFBGR4zaEUBFjmZnNNrM5ZjY72kGJiIiIHK+a1ZK4pn9Lxv5sMP+9OofWGTW578NF9PnLJ9z+2mwWbdgV7RAlgiIxC0nYn/gF42q8BLQAVgLfdfevStlvGPAAkAg87u53B+vvA84GDgLLgGvdfXu44hMRiVHDw31C5WMRERGJBQkJxiknNOKUExqxeOMunpy4kjdm5PHi1DX0a12fq/u14NQTGpGoaVjjSiReForEE7/bgU/cvS3wSbD8LWaWCDxE6Ia9I3CpmXUMNo8BOrl7F2AxcEc54xERiXnuvgpoBgwNfu+l/Hlf+VhERERiSrtGtfjL+Z358vZTuH14B1Zt3csPnp3GoPvG8uiEZezYeyjaIUqYRKKAMZzQgJ1DCT1lOyv4Lo8RwNPB76eBc0vZpxew1N2Xu/tB4MXgONz9I3fPD/abBDQtZzwiIjHPzO4EbuObIkEy8Fw5T6t8LCIiIjGpbloKNwxqzfhfDOaRK7qTVac6f35vIX3+8gl3vD6HhRt2RjtEKaewv0Li7qvMbADQ1t2fNLMMQtOolkcjd18fnH+9mTUsZZ8sYE2x5Tygdyn7fY9Q9+dSmdlIYCRAdnb2cQcsIhIDzgNOAqYDuPs6M6tVznMqH4uIiEhMS0pMYFinTIZ1ymT+up08/cVKXp+exwtTVtO7ZT2u6deC0zo2Ikmzl1Q6YS9gBE/8coD2wJN888Sv/1GO+xhoXMqmX5f10qWs8xLX+DWQDzx/uJO4+6PAowA5OTl+uP1ERCqBg8F0qg5gZmllOUj5WEREROJFxya1uefCLtw+vAMv567hmS9X8cPnp389e8nFPZvRoGa1aIcpZRSJQTyP64mfu596uG1mttHMMoOnfZnAplJ2yyP0rneRpsC6Yue4mtDrLKcEs6WIiMS7l83sP0AdM/s+oR4Pjx/tIOVjERERiTd101L4waDWXH9yKz5ZsJFnvlzFfR8u4oGPl3BWl0yu6teCbs3qRDtMOYpIFDCO64nfUYwGrgbuDr7fKmWfqUBbM2sJrAUuAS4LYhhG6D3wQe6+NwzxiIjEPHe/38xOA3YS6hX3O3cfU87TKh+LiIhIpZWYYJx+YmNOP7ExSzft4tkvV/HqtDxen7GWrk3TuapvC77TJZPU5MRohyqliMRLPyWf+H1MGZ74HcXdwGlmtgQ4LVjGzJqY2XsAwaBwNwEfAguAl919XnD8v4BawBgzm2lmj5QzHhGRmGdm97j7GHf/hbv/3N3HmNk95Tyt8rGIiIjEhTYNa/GHEZ2Y9KtTuGvEiew5WMDPXplF3798wl/eX8CabXrWEmssEr13gyd+pxN6D/rDMDzxi4qcnBzPzc2NdhgiUsmZ2TR3z4nCdae7e/cS62YHU5hWKsrHIhIu0crJ8UL5WOKZu/Plsq088+UqxizYSKE7Q9o35Mq+zRnUNoOEhNKG+ZLjdTz5OBKDeN7j7rcBY0pZJyIiEWZmPwR+BLQys9nFNtUCJkYnKhERiZTg9bwHgETgcXe/u8T2XwCXB4tJwAlAhrtvO9qxIlWJmdGvTQP6tWnA+h37eGHyakZNWcO1T04lu14NLu+dzUU5zaiXlhLtUKusSLxCclop64ZH4DoiIlK6UcDZhMarOLvYp4e7XxHNwEREJLzMLBF4iND9dkfgUjPrWHwfd7/P3bu5ezfgDmB8ULw46rEiVVVmenVuPb09X9w+lH9eehKNa6fyl/cX0ucvn3DrSzOZtuorNBZ5xQtbDww98RMRiQ3uvgPYAVwKYGYNgVSgppnVdPfV0YxPRETCqhew1N2XA5jZi8AIYP5h9r8UeOE4jxWpclKSEji7axPO7tqERRt28fzkVbw+fS2vz1jLCZm1ubJPc0Z0a0JatUjMjyElhbMHhp74iYjEEDM7OxhscwUwHlgJvB/VoEREJNyygDXFlvOCdf/DzGoAw4DXjuVYMxtpZrlmlrt58+awBC1SGbVvXIu7RnRi8q9O4U/ndQLgV2/MofefP+G3b85l4YadUY4w/oWtTKQnfiIiMeePQB/gY3c/ycyGEORoERGJG6WNKni4fu1nAxPdfduxHOvujwKPQmgQz+MJUiSepFVL4vLezbmsVzbTV2/n+cmreCl3Dc9OWkVO87pc3ieb4Z00FWskhH0MDD3xExGJGYfcfSuQYGYJ7j4W6BblmEREJLzygGbFlpsC6w6z7yV88/rIsR4rIiWYGT2a1+Vv3+3G5DtO4TffOYGtew7y05dm0ecvn/DHd+azfPPuaIcZVyLxoo6e+ImIxIbtZlYTmAA8b2abgPwoxyQiIuE1FWhrZi2BtYSKFJeV3MnM0oFBwBXHeqyIHF3dtBSuP7kV3+vfki+WbWXUlFU89cVKHv98BX1b1efyPtmc3rExKUmRmEej6ohEAeOQu281s6+f+JnZPRG4joiIHNkIYD/wU0LT56UDd0U1IhERCSt3zzezm4APCU2F+oS7zzOzG4LtjwS7ngd85O57jnZsxbZAJL4kJBgD2jZgQNsGbNq1n1dy83hhympuGjWDBjVTuLBHMy7p2YwWDdKiHWqlFIkChp74iYjEgKKbVDOrDbwd5XBERCRC3P094L0S6x4psfwU8FRZjhWR8GhYK5Ubh7Thh4NaM2HJZkZNXs1jny3nkfHL6N+mPpf1as5pHRupV8YxiEQBQ0/8RERigJn9gFD+3QcUEhqszYFW0YxLREREpCpJSDAGt2/I4PYN2bBjP6/kruHFqWu4cdR06qelcGFOUy7pmU1L9co4qrAXMPTET0QkZvwcONHdt0Q7EBERERGBxump3HxKW340pA2fBb0yHv9sBf8Zv5y+repzSa9mDOvUmGpJmsGkNGEvYOiJn4hIzFgG7I12ECIiIiLybYnFemVs3LmfV6eFxsq45cWZ1K2RzPndm3Jpr2a0aVgr2qHGlEi8QqInfiIiseEO4AszmwwcKFrp7j+OXkgiIiIiUlyj2t+MlTFx2RZenLKGZ75cyX8/X0FO87pc3LMZ3+mSSY2USPzf98olEv8E9MRPRCQ2/Af4FJhDqEeciIiIiMSohATj5LYZnNw2gy27D/D69DxenLqGX7w6m7vens853ZpwSc9sOmXVxsyiHW5URKKAoSd+IiKxId/db412ECIiIiJybBrUrMbIga35/smtmLryK16cuprXpufx/OTVdMyszcU9m3FutyzSayRHO9QKFYkChp74iYjEhrFmNpLQgMrFC8rboheSiIiIiJSVmdGrZT16tazHnWefyOiZa3kpdw13jp7Hn95bwPBOjbk4pxl9WtUnISH+e2VEooChJ34iIrHhsuD7jmLrNKiyiIiISCWUXj2ZK/u24Mq+LZi7dgcv567hjRlreWvmOrLr1eCiHk25MKcpmenVox1qxCRE4JxjzWykmWWaWb2iT3lOGJxjjJktCb7rHma/YWa2yMyWmtntpWz/uZm5mTUoTzwiIpWBu7cs5VOu4oXysYiIiEj0dcpK564RnZj661P5x8XdyKpTnb+OWUz/uz/l6iem8N6c9RzIL4h2mGEXiQLGZQTjYADTgk9uOc95O/CJu7cFPgmWv8XMEoGHgOFAR+BSM+tYbHsz4DRgdTljERGpypSPRURERGJEanIi556UxQsj+zDhF0O4cUgbFm/cxY+en06fP3/CH96ex4L1O6MdZtiEvYARiSd+wAjg6eD308C5pezTC1jq7svd/SDwYnBckb8DvyTUfVpERI6P8rGIiIhIDMquX4Ofnd6ez28bylPX9qRv6/o8N2kVwx/4jLP++RnPfLmS7XsPRjvMcqksE8k2cvf1AO6+3swalrJPFrCm2HIe0BvAzM4B1rr7rKo63YyISJgoH4uIiIjEsMQEY3D7hgxu35Btew7y1sy1vJybx+/emscf31nA6Sc24qKcZgxo04DESjbwZ8wUMMzsY6BxKZt+XdZTlLLOzaxGcI7TyxjHSGAkQHZ2dhkvLSISeyxUIbgcaOXud5lZNtDY3acc5TjlYxEREZE4UC8thWv7t+Ta/i2Zu3YHr07L482Za3ln9noy01M5v3sWF/ZoRssGadEOtUxipoDh7qcebpuZbTSzzOBpXyawqZTd8oBmxZabAuuA1kBLoOhpX1Ngupn1cvcNpcTxKPAoQE5Ojro3i0hl9jCh6ayHAncBu4DXgJ5HOkj5WERERCT+dMpKp1NWOnec2YFPFmzildw1/HvcMh4au4yc5nW5KKcpZ3bOpFZqcrRDPaywj4FhIVeY2e+C5Wwz61XO044Grg5+Xw28Vco+U4G2ZtbSzFKAS4DR7j7H3Ru6ewt3b0Hoxrp7aTfLIiJxpre73wjsB3D3r4CUcp5T+VhERESkEquWlMiZnTN58tpefHnHKdw2rAPb9h7kttfm0PNPH/PTl2YycekWCgtj7/lRJHpgHNcTv6O4G3jZzK4jNGr9RQBm1gR43N3PdPd8M7sJ+BBIBJ5w93nluKaISGV3KJgRxAHMLINQfi4P5WMRERGRONGodio/HNyaGwa1Yuaa7bw6LY/Rs9bxxoy1NElP5fzuTbmgR9OYecXE3MNbVTGz6e7e3cxmuPtJwbpZ7t41rBeqADk5OZ6bW94ZYEWkqjOzae6eE4XrXg5cDHQnNGPIhcBv3P2Vio6lvJSPRSRcopWT44XysUj823+ogDHzN/LqtDw+W7KZQocezetyQfemfKdLJunVw/OKyfHk40j0wIjEEz8RETlG7v68mU0DTiE0sOa57r4gymGJiIiISAxLTU7k7K5NOLtrEzbs2M+bM9fy2rQ8fvXGHH7/9jxO79iIC3o05eQ2DUhKDPuoFEcUiQLGg8AbQEMz+xPBE78IXEdERI7AzB4AXnL3h6Idi4iIiIhUPo3TU7lhUGt+MLAVc9bu4LVpebw1ax3vzF5PRq1qnNutCed3b8oJmbUrJJ6wFzD0xE9EJGZMB35jZu0IFZZfcnf1+xURERGRY2JmdGlahy5N6/Dr73Tk04WbeH16Hk99sZLHPlvBCZm1uaB7Fud0a0LDWqkRiyPsBQw98RMRiQ3u/jTwtJnVAy4A7jGzbHdvG+XQRERERKSSSklKYFinxgzr1Jhtew7yzux1vDYtjz++u4A/v7eAk9tmcH73LE7v2JjqKYlhvXYkXiHREz8RkdjSBugAtADmRzcUEREREYkX9dJSuKpvC67q24Klm3bx+vS1vDljLbe8OJOa1ZIY1qkx55+URZ9W9UlIsHJfLxKvkOiJn4hIDDCze4DzgWXAy8D/ufv2qAYlIiIiInGpTcNa/HJYB35+ensmr9jG69PzeH/uBl6dlkdmeiojumVxfvcs2jWqddzXiEQPjCJ64iciEl0rgL7uviXagYiIiIhI1ZCQYPRtXZ++retz14hOjFmwkTdnrOWxz5bzyPhldMyszfnds47r3JEYA0NP/EREosjMOrj7QmAKkG1m2cW3u/v06EQmIiIiIlVJ9ZREzunahHO6NmHL7gO8PWsdb85Yyx/fPb55PiLRA0NP/EREoutWYCTw11K2OTC0YsMRERERkaquQc1qXNu/Jdf2b8nSTbtpe8+xnyNsBQw98RMRiQ3uPjL4Odzd9xffZmaRm9dKRERERKQM2jSseVzHhbMHhp74iYjEli+A7mVYJyIiIiIS88JWwNATPxGR2GBmjYEsoLqZnQQUzVlVG6gRtcBERERERMohEmNg6ImfiEh0nQFcAzQl1CuuqICxE/hVlGISERERESmXcI6BoSd+IiIxwN2fBp42swvc/bVoxyMiIiIiEg7m7uE5kdnVhJ745QBT+fYTv6fd/fWwXKgCmdlmYFW04wiDBkC8zwoT721U+yq39u5eq6IvamZ/Bu4tmsrazOoCP3P331R0LOUVR/kY4v/vXe2r/OK9jVHJyfFC+bhSiff2Qfy3Md7bd8z5OGwFjK9PqCd+McfMct09J9pxRFK8t1Htq9yi1T4zm+HuJ5VYN93d9UpfFOnvvXKL9/ZB/Lcx3tsnZRfvfwvx3j6I/zaqff8rIQJx9DCzOkULZlbXzP4YgeuIiMiRJZpZtaIFM6sOVDvC/iIiIiIiMSsSBYzhRd2VAdz9K+DMCFxHRESO7DngEzO7zsy+B4wBno5yTCIiIiIixyUSs5Akmlk1dz8AeuIXIx6NdgAVIN7bqPZVblFpn7vfa2ZzgFMIjUv0f+7+YTRikW/R33vlFu/tg/hvY7y3T8ou3v8W4r19EP9tVPtKiMQYGL8EzgGeBBz4HjDa3e8N64VEREREREREpMoIewEDwMyG880Tv4/0xE9EpOKZWR/gn8AJQAqQCOxx99pRDUxERERE5DhEpIAhIiLRZ2a5wCXAK4SmuL4KaOPuv45qYCIiIiIixyHsg3iaWR8zm2pmu83soJkVmNnOcF9HSmdmT5jZJjObW2xdPTMbY2ZLgu+60YyxPMysmZmNNbMFZjbPzG4J1sdFG80s1cymmNmsoH1/CNbHRfuKmFmimc0ws3eC5Xhr30ozm2NmM4MiQtTa6O5LgUR3L3D3J4EhFXFdUT6OkzYqJ1fy9sVSPpboUk6u3G1UPo6b9pU7J0diFpJ/AZcCS4DqwPWEujBLxXgKGFZi3e3AJ+7eFvgkWK6s8oGfufsJQB/gRjPrSPy08QAw1N27At2AYRZ6DSBe2lfkFmBBseV4ax/AEHfvVmxu62i0ca+ZpQAzzexeM/spkFYB15WQp1A+ruxtVE6Oj/bFQj6W6HsK5eTK3Ebl4/hoH5Q3J7t7WD9AbvA9u9i6L8J9HX2O+L9BC2BuseVFQGbwOxNYFO0Yw9jWt4DT4rGNQA1gOtA7ntoHNA2S01DgnWBd3LQvaMNKoEGJdRXeRqA5kArUBu4E/kboFZKo/zOqKh/l4/hpo3Jy9GM9zvbFRD7WJzY+ysnx0Ubl4+jHWo42ljsnR6IHhp74xZ5G7r4eIPhuGOV4wsLMWgAnAZOJozYGXcdmApuAMe4eV+0D/gH8Eigsti6e2gehGZg+MrNpZjYyWFfhbXT3Ve6+3913uvsf3P1WD71SItETb3/rQPzmY1BOjoP2xUQ+lpgVl38L8ZqTlY8rffsgDDk5KQJBXUno1ZSbgJ8CzYALInAdqcLMrCbwGvATd99pZtEOKWzcvQDoZmZ1gDfMrFOUQwobMzsL2OTu08xscJTDiaT+7r7OzBoCY8xsYbQDEomUeM7HoJwcB5SPpUqJ55ysfBwXyp2Tw17AcPdVwc/9wB/CfX45LhvNLNPd15tZJqGqZaVlZsmEEvPz7v56sDqu2gjg7tvNbByh9zXjpX39gXPM7EyCVxvM7Dnip30AuPu64HuTmb0B9CLO2ijHLa7+DqpKPgbl5KhGWQ7Kx3IUcfW3UFVysvJx5RWOnByJV0gk9owGrg5+X03onbhKyUJl5P8CC9z9b8U2xUUbzSwjqCpjZtWBU4GFxEn73P0Od2/q7i0ITe/5qbtfQZy0D8DM0sysVtFv4HRgLhXYRjN7Nvi+JVLXkOMWT3/rcZ2PQTk52K3Sti8W8rHEvLj5W4j3nKx8DFTi9kH4crIFg2VInDCzF4DBQANgI6GB+94EXgaygdXARe6+LUohlouZDQA+A+bwzfthvyL0jl+lb6OZdQGeBhIJFRhfdve7zKw+cdC+4oLucT9397PiqX1m1gp4I1hMAka5+58qso1mNh8YTug/CIOBb/Ufraz/bCsb5eO4aKNyciVuXyzkY4kdysmVu43Kx5W/feHKyWErYJjZs+5+pZnd4u4PhOWkIiJyzMzsx8APgVbAWr5dwHB3bxWVwEREREREyiGcBQw98RMRiSFm9m93/2G04xARERERCYdwFjD0xE9EJMaYWVfg5GBxgrvPjmY8IiIiIiLHK+xjYOiJn4hIbAgKyyOBopHIzwMedfd/Ri8qEREREZHjE5FBPPXET0Qk+sxsNtDX3fcEy2nAl+7eJbqRiYiIiIgcu7BPoxo88XseaBh8njezm8N9HREROSoDCootF1BifCIRERERkcoi7AUM4Hqgt7v/zt1/B/QBvh+B60gVZ2aNzexFM1tmZvPN7D0za3cc5xlnZjmRiPEY47jGzP4V7TgkrjwJTDaz35vZ74FJhOaIFwkr5WMRkdihnCzxLCkC59QTP4k4MzNC8wg/7e6XBOu6AY2AxVEMLWrMLNHdC46+p1QV7v43MxsHDCCUh6919xnRjUrijfLx/1I+FpFoUU7+X8rJ8SUSPTD0xE8qwhDgkLs/UrTC3We6+2dm9qyZjShab2bPm9k5ZpZoZveb2Rwzm13aq01mdrqZfWlm083sFTOrWco+48zsHjObYmaLzezkYP23qsNm9o6ZDQ5+7w6OmWZmH5tZr+A8y83snGKnb2ZmH5jZIjO7s9i5rgiuN9PM/mNmicXOe5eZTQb6luOfp8Qpd5/u7g+6+wMqXkiEKB+jfCwiMUM5GeXkeBb2Aoa7/w24FtgGfEXoid8/wn0dqfI6AdMOs+1xQn+DmFk60A94j9BsDC2Bk4JBDJ8vfpCZNQB+A5zq7t2BXODWw1wjyd17AT8B7jzMPsWlAePcvQewC/gjcBqhWSHuKrZfL+ByoBtwkZnlmNkJwMVAf3fvRqhX0+XFzjvX3Xu7++dliENEJNyUj785r/KxiESbcvI351VOjkOReIUEd58OTI/EuUWOxt3Hm9lDZtYQOB94zd3zzexU4BF3zw/221bi0D5AR2CimQGkAF8e5jJF01JOA1qUIayDwAfB7znAAXc/ZGZzShw/xt23ApjZ64S6/ucDPYCpQVzVgU3B/gXAa2W4vohIhVM+FhGJHcrJEg8iUsAQqQDzgAuPsP1ZQhXYS4DvBesMONK8wUYoOV5ahusfCL4L+Obfo3y+3asptdjvQ/7NnMWFRce7e6GZFf/3sGR8HsT1tLvfUUoc+/VOnxyOhaZN3Rf8nbUDOgDvu/uhKIcm8UX5OET5WERigXJyiHJynIrEGBgiFeFToJqZfT3DjZn1NLNBweJThLqu4e7zgnUfATcUJUMzq1finJOA/mbWJthew45txOaVQDczSzCzZoS6uh2r08ysnplVB84FJgKfABcG1XKC7c2P49xS9UwAUs0si9Df0bWE/t0QCSflYxGR2KGcLHEt7AUMM0szs4TgdzsLDQyTHO7rSNUWVGrPI5TMlpnZPOD3wLpg+0ZgAaFBZYs8DqwGZpvZLOCyEufcDFwDvGBmswkl6w7HENZEYAWh7m/3c3yvUX1OqDI+k1C3vlx3n0/ovcOPgrjGAJnHcW6peszd9xLqJvpPdz+PUBdQkbBRPlY+FpHYoZysnBzv7JseO2E6odk04GSgLqE/7lxgr7tffsQDRcLIzGoQSpLd3X1HtOMRiQYzmwH8CPg7cJ27zzOzOe7eOcqhSRWifCwiEjuUk6Wyi8QrJHriJ1EVDES0kNDfnxKzVGU/Ae4A3giKF62AsdENSaoS5WMRkdihnCzxIBI9MPTET0QkxgSv9tV0953RjkVERERE5HhEogfGT9ATPxGRqDOzUWZWO5iNZD6wyMx+Ee24RERERESOR9h7YHzr5HriJyISNWY20927mdnlhOZJvw2Y5u5dohyaiIiIiMgxi8QsJHriJyISG5KDWaDOBd5y90MceZ53EREREZGYFYlXSDoGPS7OBd4DsoErI3AdERE5sv8Qmns9DZgQzI2uHnEiIiIiUilFYhDPeUA3YBTwL3cfb2az3L1rWC8kIiLHzMyS3D0/2nGIiIiIiByrSPTA0BM/EZEYYGbpZvY3M8sNPn8llJtFRERERCqdiA7i+fVF9MRPRKTCmdlrwFzg6WDVlUBXdz8/elGJiIiIiByfSLxCkg7cCQwMVo0H7nL3HWG9kIiIHFHRLCRHWyciIiIiUhlE4hWSJ4BdwHeDz07gyQhcR0REjmyfmQ0oWjCz/sC+KMYjIiIiInLcItEDQ0/8RERigJl1BZ4B0oNVXwFXu/vs6EUlIiIiInJ8ItEDo+QTv1uB9ma21MxuL7mzhTwYbJ9tZt2LbRtmZotKHmtmF5nZPDMrNLOcYutbmNk+M5sZfB4ptq2Hmc0JzvWgmVkE2i4iEjPcvWgGqC5AF3c/CRga5bBERERERI5LJAoYNwAPmdlKM1sJ/AU4H+gIXGpmHUvsPxxoG3xGAv8GMLNE4KFge8lj5wbnnFDK9Ze5e7fgc0Ox9f8Ozl90rWHlbaiISGXg7jvdvWg2qFujGoyIiIiIyHEKewGjxBO/64BxQHt3Pwi8CIwoccgI4BkPmQTUMbNMoBew1N2XlzzW3Re4+6KyxhScr7a7f+mhd2aeAc4tTztFRCop9T4TERERkUopKVIndvedZlYXWEPoid8/gDygd4lds4J9iuQF60pbX/LY0rQ0sxmEBg/9jbt/Fpwrr5Rr/A8zG0mopwZpaWk9OnToUIZLiogc3rRp07a4e0a04whEfu7sCGjQoIG3aNEi2mGISByIsZxc6Sgfi0i4HE8+jlgBI2AlvuF/b55LexroR1h/JOuBbHffamY9gDfN7MRjOZe7Pwo8CpCTk+O5ublHuaSIyJGZ2aoKvt4uSs9xBlSvyFjCpUWLFigfi0g4VHROjjfKxyISLseTjyNdwMgDmvHNjXRTYN1h9qHEPimHWX9Y7n4AOBD8nmZmy4B2wTWaHsu5REQqK3evFe0YRERERETCLWwFjCM88asJFJpZCnAJcFmJ7aOBm8zsRUKviOxw9/Vmthloa2YtgbWHObZkDBnANncvMLNWhAbrXO7u28xsl5n1ASYDVwH/PO7GioiIiIiIiEiFClsB43BP/MzsTELjXywAnnD3eWZ2Q3DMI8B7wJnAUmAvcG2wLd/MbgI+BBKLjg3OeR6hAkQG8K6ZzXT3M4CBwF1mlg8UADe4+7YglB8CTxHqPv1+8BERERERERGRSiDSr5Dg7u8RKlIUX/dIsd8O3FjWY4P1bwBvlLL+NeC1w5wrF+h0LLEfKqiUY92JiMSdbXsORjsEEREB1m3fx469h0ivkRztUESkCgr7NKrxZPW2PRzIL4h2GCIiVd7mXQeiHYKIiABb9xzk1L+P54O5G6IdiohUQSpgHMHegwX85o25hDqJiIhItBwsKGTllj3RDkNEpMpr07AmGTWrccNz07hx1HS27FaBWUQqjgoYR9CwVjVemZbH01+sjHYoIiJV3oQlm6MdgohIlVc9OZG3burPL85oz5h5Gzntb+N5c8ZaPfATkQqhAsYRNKqdyqknNOL/3l3AF8u2RDscEZEqKyUxgQmLlYdFRGJBcmICNw5pw3u3DKBlgzR+8tJMrns6l7Xb90U7NBGJcypgHMXfL+5KywZp3Pj8dNZs2xvtcEREqqSaqUl8uWwLB/MLox2KiIgE2jSsxSs39OO3Z3Xky2VbOf1v43n6i5UUFKo3hohEhgoYR1ErNZnHrsqhoND5/jO57D2YH+2QRESqnFrVkthzsIDpq7+KdigiIlJMYoJx3YCWfPTTgfRoUY87R8/joke+YPHGXdEOTUTikAoYZdCyQRr/vKw7izfu4uevzKJQVWURkQqVlppEYoIxYbHGwRARiUXN6tXg6Wt78veLu7Jiyx6+8+Bn/H3MYs3oJyJhpQJGGQ1ql8Edw0/gvTkbuP+jRdEOR0SkSkk0o3t2HT5bonEwRERilZlx3klN+fjWQXyncyYPfLKEMx/4jMnLt0Y7NBGJEypgHIPrT27Jpb2yeXjcMl6csjra4YiIVCkD22Ywd90OtmrKPhGRmFa/ZjX+cclJPHVtTw7kF3Lxo5O47dXZbN97MNqhiUglpwLGMTAz7hpxIie3bcCv35zLZ5rST0SkwpzcLgN3+HypemGIiFQGg9s35KOfDuQHg1rx6vQ8Tv3beN6aqSlXReT4qYBxjJITE3j48u60bViTHz03nUUbNECRiEhF6JyVTp0ayZpOVUSkEqmRksQdw0/g7ZsGkFW3Bre8OJOrnpjCyi17oh2aiFRCKmAch1qpyTxxTU+qpyTyvaemsmnn/miHJCIS9xITjAFtGvDZks16eiciUsl0bFKb13/Yjz+ccyIzVm/n9H9M4J+fLNEgnyJyTFTAOE5N6lTniWt6sm3PQa57WtOriohUhIHtMti06wAL1ftNRKTSSUwwru7Xgk9+NojTOjbir2MWM/yBz/himXrWiUjZqIBRDp2y0vnnpScxb90Obho1g0MFhdEOSUQkrg1smwGg6VRFRCqxRrVTeeiy7jx1bU/yC5zLHpvMrS/NZIsGaRaRo1ABo5xO7diIu0Z04tOFm7jttdkUFqpbs4hIpDROT6Vdo5qaTlVEJA4UDfJ589A2vD17HUPvH8ezk1ZRoPtpETkMFTDC4Io+zfnpqe14ffpa7v5gYbTDERGJawPbZjBl5Tb2HdR70yIilV1qciI/O709798ykM5N0/ntm3M57+GJzFqzPdqhiUgMingBw8yGmdkiM1tqZreXst3M7MFg+2wz6360Y83sIjObZ2aFZpZTbP1pZjbNzOYE30OLbRsXnGtm8GkYznb++JQ2XN23OY9OWM4j45eF89QiIlLMwHYZHMwvZNKKrdEORUREwqRNw5o8d11vHrz0JDbs2M+5D0/kV2/MYfveg9EOTURiSEQLGGaWCDwEDAc6ApeaWccSuw0H2gafkcC/y3DsXOB8YEKJc20Bznb3zsDVwLMltl/u7t2Cz6YwNPFrZsadZ5/I2V2bcPf7C3l56ppwnl5ERAK9WtajWlICn2k6VRGRuGJmnNO1CZ/8bBDf69+Sl6auYehfx/PS1NV6TVtEgMj3wOgFLHX35e5+EHgRGFFinxHAMx4yCahjZplHOtbdF7j7opIXc/cZ7r4uWJwHpJpZtcg07X8lJBh/vagrJ7dtwO2vz2bM/I0VdWkRkSojNTmRXi3rMWGJBvIUEYlHtVKT+e1ZHXnn5gG0apDGba/N4fx/f8HsvO3RDk1EoizSBYwsoHhXhLxgXVn2KcuxR3IBMMPdiw9n/GTw+shvzcxKO8jMRppZrpnlbt587DfHKUkJPHJFDzo3rcONo6ZrWigRkQgY1C6DpZt2s277vmiHIiIiEXJCZm1euaEvf/tuV/K+2seIh0KvlXy1R6+ViFRVkS5glFYkKNn/63D7lOXY0i9qdiJwD/CDYqsvD14tOTn4XFnase7+qLvnuHtORkZGWS73P9KqJfHkNT1pUb8G1z2Vy9SV247rPCIi4XS8YxKZWaqZTTGzWcH4Q38odsz/BfvONLOPzKxJsL6Fme0rNu7QI8H6Gmb2rpktDM519/G0ZWC7UH4euyisbwOKiEiMMTPO796UT38+iGv7hV4rGfLXcTw/WbOViFRFkS5g5AHNii03BdaVcZ+yHPs/zKwp8AZwlbt/PZqmu68NvncBowi9ohIx9dJSeO763mSmp3Ltk1OZsfqrSF5OROSIyjMmEXAAGOruXYFuwDAz6xNsu8/du7h7N+Ad4HfFzres2LhDNxRbf7+7dwBOAvqb2fBjbU/bhjVp2SCN9+dsONZDRUSkEqqdmszvzu7Iez8+mfaNavHrN+Zyzr8+J1cPCkWqlEgXMKYCbc2spZmlAJcAo0vsMxq4Knjy1wfY4e7ry3jst5hZHeBd4A53n1hsfZKZNQh+JwNnERoINKIa1kpl1Pf7UC8thauemMLctTsifUkRkcM57jGJguXdwT7JwccB3H1nsePTOEpPOXff6+5jg98HgemECtTHxMw4s3Njvly+la27Dxz9ABERiQvtG9fixZF9+NdlJ7Ftz0EufORLbnlxBht27I92aCJSASJawHD3fOAm4ENgAfCyu88zsxvMrOhp3HvAcmAp8BjwoyMdC2Bm55lZHtAXeNfMPgzOdRPQBvhtielSqwEfmtlsYCawNrhWxDVOT2XU93tTOzWZK/47mYUbdh79IBGR8CvPmESYWaKZzQQ2AWPcfXLRTmb2JzNbA1zOt3tgtDSzGWY23sxOLhlQUHQ+G/iktICPNibRdzo3oaDQ+XCeBkwWEalKzIyzuoRmK7l5aBven7uBoX8dx0Njl3IgvyDa4YlIBEW6Bwbu/p67t3P31u7+p2DdI+7+SPDb3f3GYHtnd8890rHB+jfcvam7V3P3Ru5+RrD+j+6eVqzLcjd33+Tue9y9R9DN+UR3v8XdKyy7Na1bg1Hf701qUiKXPzaZpZt2VdSlRUSKlGdMIty9IHhNpCnQy8w6fb2D+6/dvRnwPKFCMsB6INvdTwJuBUaZWe2vL2SWBLwAPOjuy0sL+GhjEp2QWYuWDdJ4b876UhssIlJVlGGMo3Qze7vYWEbXFtu20szmBA/+ckseG8tqpCTxs9Pb8/FPBzGgTQPu+3ARp/99Ah/N24C7xscQiUcRL2BISPP6aTz//d6YGZc+NpklG1XEEJEKVZ4xib7m7tuBccCwUq4xitAMULj7AXffGvyeBiwD2hXb91Fgibv/49ia8Q0z4zudM/li2Ra9RiIiVVYZxzi6EZgfjGU0GPhr8Ip2kSHBg7+ciog53LLr1+DRq3J49rpepCQmMPLZaVzx38ks2qD7bZF4owJGBWqdUZMXvt8bd7jk0UksWK/XSUSkwhz3mERmlhG87oGZVQdOBRYGy22LHX9OsfUZwU01ZtaK0MCgy4PlPwLpwE/K26gzO2dS6Og1EhGpysoyxpEDtczMgJrANiC/YsOMvJPbZvD+LSfzh3NOZO7anQx/YAK/e2uupl0ViSMqYFSwto1q8fIP+pCcmMClj03SwJ4iUiHKMyYRkAmMDcYRmkpoDIx3gm13m9ncYNvpwC3B+oHAbDObBbwK3ODu24KZon5N6Cnh9KDL8vXH264TMmvRqkEa78456iRVIiLxqixjHP0LOIFQr7o5wC3uXhhsc+AjM5tmZiMjHWykJSUmcHW/Foz7+WCu7NOc5yevZvD943hy4goOFRQe/QQiEtOSoh1AVdQqoyYv/aAPlz02mcsem8Qz1/WmW7M60Q5LROKcu79HqEhRfN0jxX47oW7GJY+bTWjK09LOecFh1r8GvFbK+jxKH2vjuIRmI8nk4XFL2br7APVrVgvXqUVEKouyjHF0BqGB7IcCrYExZvZZMJNUf3dfFwx8P8bMFrr7hG9dIFTYGAmQnZ0d7vgjom5aCn8Y0YnLejfn/96Zzx/ens+zk1bxm++cwJD2DQl1RhGRykY9MKKkef00XvpBH+rUSOGKxydrDmsRkeNU9BrJB/M2RDsUEZFoKMsYR9cCrweD5y8FVgAdANx9XfC9CXiD0Csp33K0QZVjWfvGtXj2ul48cU0OOHzvqVyuemKKxscQqaRUwIiipnVr8NIP+tCwVjWuemIKXyzbEu2QREQqnaLXSDQbiYhUUWUZ42g1cAqAmTUC2gPLzSzNzGoF69MIvQo4t8IiryBmxtAOjfjwpwP53VkdmZ23g+EPTODXb8xhiwaBFqlUVMCIssz06rw4sg9ZdapzzZNT+VBPEEVEjknRayRfLtuqG1ERqXLKOMbR/wH9zGwO8Alwm7tvARoBnwfjFU0B3nX3Dyq+FRUjOTGB7w1oyfhfDOaqvi14aeoaBt83jofGLmX/oYJohyciZaACRgxoWDuVl3/Ql46Ztfnhc9N4OXfN0Q8SEZGvfadL0WwkKgKLSNXj7u+5ezt3b+3ufwrWPVI0zpG7r3P30929s7t3cvfngvXL3b1r8Dmx6Nh4V6dGCr8/50Q++ulA+rauz30fLuKUv47nzRlrKSwsOXyIiMQSFTBiRN20FJ6/vjf92zTgl6/O5j/jl0U7JBGRSqND42A2ktl6jURERMqmVUZNHrsqhxe+34e6acn85KWZnPfwRCYv3xrt0ETkMFTAiCFp1ZL479U9OatLJn95fyF/eX8BoUkBRETkSMyM73TJZNJyvUYiIiLHpm/r+oy+cQB/vagrG3ce4OJHJ3H907ks3bQ72qGJSAkqYMSYlKQEHrjkJK7s05z/jF/Oba/NJl9zVouIHNXXs5HM1WskIiJybBISjAt6NGXszwfzizPaM2n5Vs74R2igz827VBgXiRUqYMSgxATjrhEn8uNT2vJybh7XP5PL7gP50Q5LRCSmFb1GotlIRETkeFVPSeTGIW0Y94vBXN47OxjocywPfrKEvQd1Py4SbSpgxCgz49bT2vHn8zrz2ZItXPyfL9m4c3+0wxIRiVlmxlnBayTrd+yLdjgiIlKJNahZjbtGdOKjnw5kQNsG/G3MYgbfN45Rk1erd7RIFKmAEeMu653N41fnsHLLHs57aCKLNuyKdkgiIjHrwh7NKHR4aapmcxIRkfJrlVGT/1yZw6s39KVZvRr86o05nPGPCXw4b4PGqhOJAhUwKoEh7Rvy0g/6kl/oXPjvL5i4dEu0QxIRiUnZ9WtwctsGvDR1jZ6QiYhI2OS0qMerN/TlP1f2AOAHz07jwke+JHfltihHJlK1qIBRSXTKSueNG/uTWSeVq5+Ywiu5erooIlKay3tns37HfsYv3hztUEREJI6YGWec2JgPfzKQv5zfmTXb9nLhI19y/dO5LN6oXtIiFSHiBQwzG2Zmi8xsqZndXsp2M7MHg+2zzaz70Y41s4vMbJ6ZFZpZTonz3RHsv8jMzii2voeZzQm2PWhmFqk2R0pWneq8+sN+9G5Vj1+8Ops/v7eAgkJ1XRMRKe6UExqRUasaoyavjnYoIiISh5ISE7i0VzbjfhGasWRyMGPJz1+ZxdrtGoNJJJIiWsAws0TgIWA40BG41Mw6lthtONA2+IwE/l2GY+cC5wMTSlyvI3AJcCIwDHg4OA/BeUcWu9awsDW0AtVOTeapa3txVd/mPDphOdc/PZVd+w9FOywRkZiRnJjAd3OaMnbRJtbpRlJERCKkRkoSNw5pw4RfDuH6AS0ZPWsdQ+4fxx/fmc+2PQejHZ5IXIp0D4xewFJ3X+7uB4EXgREl9hkBPOMhk4A6ZpZ5pGPdfYG7LyrleiOAF939gLuvAJYCvYLz1Xb3Lz002s4zwLnhb27FSE5M4K4Rnfi/czsxYckWznv4C1Zt3RPtsEREYsYlPbNx4EUN5ikiIhFWNy2FX3+nI2N/PpgRXZvwxMQVDLx3LA98vITdBzT1qkg4RbqAkQUUv3vMC9aVZZ+yHFvW62UFv496LjMbaWa5Zpa7eXNsvz99ZZ/mPHtdL7bsPsCIhybyxTIN7ikiAtCsXg0Gts3gpama7k5ERCpGVp3q3HdRVz78yUD6t6nP3z9ezMB7x/L4Z8vZf6gg2uGJxIVIFzBKG2ei5KANh9unLMeW9XplPpe7P+ruOe6ek5GRcZTLRV+/1g1468b+NKhZjav+O4WnJq7QlE4iIoSmod648wBjF8V2MVpEROJL20a1+M+VObx5Y386Ztbmj+8uYOj941RUFwmDSBcw8oBmxZabAuvKuE9Zji3r9fKC38dyrkqjef003vhRPwa3z+D3b8/npy/NZN9BVXlFpGo7pUNDGtWuxqjJq6IdioiIVEHdmtXhuet7M+r63mTUTuW21+Zw2t8nMHrWOgo1EL/IcYl0AWMq0NbMWppZCqEBNkeX2Gc0cFUwG0kfYIe7ry/jsSWNBi4xs2pm1pLQYJ1TgvPtMrM+wewjVwFvha2VMaBWajKPXpnDz05rx1uz1nHewxM1LoaIVGlJiQlcnNOMcYs3k/fV3miHIyIiVVS/Ng1480f9ePTKHqQkJvDjF2Zw5oOfMWb+RvWcFjlGES1guHs+cBPwIbAAeNnd55nZDWZ2Q7Dbe8ByQgNuPgb86EjHApjZeWaWB/QF3jWzD4Nj5gEvA/OBD4Ab3b2oK8IPgceD6ywD3o9k26MhIcG4+ZS2PHlNT9bv2M/Z//ycTxdujHZYIiJRc3GvbABe0mCeIiISRWbG6Sc25v1bTuaBS7qx/1AB338ml/Me/oLPl2xRIUOkjEz/shxeTk6O5+bmRjuM47Jm215ueG4a89bt5MentOWWU9qSmFDaUCAiEmlmNs3dc6IdR2VWnnx87ZNTmLduJxNvH0pyYqQ7HopIrFNOLp/KfH8cSw4VFPLatDwe/GQJ63bsp1fLevzstHb0blU/2qGJVJjjyce6k4tTzerV4LUf9uPCHk158JMlXPnfyWzatT/aYYmIVLjLejdn064DfLpwU7RDERERASA5MYFLemXz6c8H8/uzO7Jiyx4ufnQSV/53MjNWfxXt8ERilgoYcSw1OZH7LuzCvRd0Yfrqrzjzgc+ZuFRTrYpI1TKkfQaZ6ak8OXFFtEMRERH5ltTkRK7p35IJvxjCr87swLx1Oznv4S+47qmpzF27I9rhicQcFTDinJnx3Z7NGH3TAOrUSOaK/07mbx8tokAjH4tIFZGUmMB1A1oyafk2pq3aFu1wRERE/kf1lERGDmzNhF8O4RdntGfqym2c9c/PGflMLvPX7Yx2eCIxQwWMKqJdo1qMvqk/F3RvyoOfLuWyxyaxcadeKRGRquGy3tnUS0vhX58ujXYoIiIih1WzWhI3DmnD57cP5SentuXL5Vs588HP+OFz01i0YVe0wxOJOhUwqpAaKUncf1FX/npRV2bn7WDYPybwwdwN0Q5LRI6RmTUys+5mdpKZNYp2PJVBjZQkrhvQkrGLNqtLroiIxLzaqcn85NR2fP7Lofx4aBs+W7KFYQ9M4MZR01m8UYUMqbpUwKiCLujRlLdvHkBW3erc8Nw0bn9tNnsO5Ec7LBE5CjPrZmaTgHHAvcB9wHgzm2Rm3aMaXCVwZd/m1EpN4uFx6oUhIiKVQ3qNZG49vT2f3zaEHw1uzbiFmzjjHxO4SYUMqaJUwKii2jSsyes/7M8Ng1rzUu4azvrn58xasz3aYYnIkT0F3OLuJ7j7qcGnA/AT4MmoRlYJ1E5N5uq+LXh/7gaWbtJNn4iIVB51aqTwizM68PltQ/nR4NaMVSFDqigVMKqwlKQEbh/egVHX92H/oQIu+PcXPDR2qQb4FIldae4+ueRKd58EpEUhnkrnewNakpqUyMNjl0U7FBERkWNWN630QsaNo6azcIMG+5T4pwKG0Ld1fT64ZSBndGrMfR8u4qJHvmD55t3RDktE/tf7ZvaumV1sZv2Cz8Vm9i7wwdEONrNhZrbIzJaa2e2lbDczezDYPrvotRQzSzWzKWY2y8zmmdkfih3zf8G+M83sIzNrEqxvYWb7gvUzzeyRYsf0MLM5wXUeNDMLyz+dMqiXlsJlvbN5a9Y6Vm/dW1GXFRERCauShYzxizYz7B+fccOz05i3TmM9SfxSAUOA0Pt1/7r0JP5xcTeWbtrNmQ9+xhOfr6BQvTFEYoa7/xj4FzAEuAP4VfD7IXe/6UjHmlki8BAwHOgIXGpmHUvsNhxoG3xGAv8O1h8Ahrp7V6AbMMzM+gTb7nP3Lu7eDXgH+F2x8y1z927B54Zi6/8dnL/oWsPK9k8gPEYObEWiGY9MUC8MERGp3L4pZAzhx6e0ZeKyLXznwc/5/jO5zMlTIUPiT9LRdjCzdEI3l1mAA+uAD919e2RDk4pmZpx7UhZ9W9fn9tdmc9c78/lw3gbuu7Ar2fVrRDs8EQHc/X3g/eM4tBew1N2XA5jZi8AIYH6xfUYAz7i7A5PMrI6ZZbr7eqCoW1Zy8PEgnuL9VdOK1h+OmWUCtd39y2D5GeDc42zTcWlUO5WLcprySm4ePx7alsbpqRV1aRGRUul+W8qrTo0Ubj2tHdcNaMlTE1fy38+Xc/b8jQxpn8FNQ9vSo3ndaIcoEhZH7IFhZlcB04HBQA1CN6dDgGnBNolDjWqn8sQ1Pbn3gi7MW7eTYQ9M4NlJq9QbQyTKzCzJzH5gZu8Hr23MCn7fYGbJRzk8C1hTbDkvWFemfcws0cxmApuAMcXH4jCzP5nZGuByvt0Do6WZzTCz8WZ2crFr5B0ljqLzjjSzXDPL3bx581Gad2xuGNSaAncenbA8rOcVETlWut+WcEqvnswtp7Zl4u1D+cUZ7Zm5ZjsX/PsLLn98EpOWb412eCLldrQeGL8GepSs/ppZXWAy8EyE4pIoMzO+27MZ/ds24LZXZ/PbN+fy9qx13H1+Z1pl1Ix2eCJV1bPAduAPfFMEaApcDTwHXHyEY0sbZ6JkVfKw+7h7AdDNzOoAb5hZJ3efG2z7NfBrM7sDuAm4E1gPZLv7VjPrAbxpZieWMQ6C8z4KPAqQk5MT1gpqs3o1GNGtCaOmrOJHQ1rToGa1cJ5eRORY6H5bwq5WajI3DmnDNf1a8PzkVTw6YQWXPDqJXi3qcfMpbRjQpgEVOASVSNgcbQwMo/Qby0JKvwmVOJNVpzrPXteLey/owsL1Oxn2wGc8NHYphwoKox2aSFXU3d1/6O6T3D0v+Exy9x8CJx3l2DygWbHlpoS6KB/TPsEN9jhKH7diFHBBsN8Bd98a/J4GLAPaBddoepQ4KsSNQ9pwqMD5x8eLo3F5EZEi5b7fLsMgzelm9naxwZivLeuxUrmlVUti5MDWfH7bEH5/dkdWb9vLlf+dwrkPTeSjeRvUw1oqnaMVMP4ETDezf5vZr4LPI4S6uf0p8uFJLCjqjfHxrYM4pUND7vtwESP+NVEDA4lUvK/M7CIz+zp3m1mCmV0MfHWUY6cCbc2spZmlAJcAo0vsMxq4KpiNpA+ww93Xm1lG0PMCM6sOnAosDJbbFjv+nGLrM4KBQzGzVoQG61wejKexy8z6BLOPXAW8dez/KMqvdUZNruzTnFGTV2vqORGJpnLdb5dxkOYbgfnBYMyDgb+aWUoZj5U4kJqcyDX9WzL+l4P583md2bb3ICOfncaZD37G6FnrKFAhQyqJIxYw3P1pIAcYT2gU+oOEnrzluPtTkQ5OYkvD2qn8+4oePHJFD7bsPsCIhz7nj+/MZ8+B/GiHJlJVXAJcCGw0s8VmthjYAJwfbDssd88n9HrHh8AC4GV3nxeMn1E0Q8h7wHJgKfAY8KNgfSYw1sxmEyqEjHH3d4Jtd5vZ3GDb6cAtwfqBwGwzmwW8Ctzg7tuCbT8EHg+us4wKHMCzpJ+c2pba1ZO56+35hMYuFRGpWGG43/56kGZ3PwgUDdL8rcsAtYLCcU1gG5BfxmMljlRLSuSy3tmM/dlg/n5xV/ILnR+/MINT/zael6eu4WC+ellLbLNw3LCZ2Zfu3vcw24YBDwCJwOPufneJ7RZsPxPYC1zj7tOPdKyZ1QNeAloAK4HvuvtXZnY58Itip+9CqMv1TDMbR+gmfF+w7XR333SkduXk5Hhubm6Z/hlUNTv2HeLu9xfywpTVZKancufZHTnjxMZ6l06kFGY2zd1zwnzO+oRy+JZwnjdWRTIfP/3FSu4cPY//XNmDM05sHJFriEjsiEROrgiHu982swuBYe5+fbB8JdC7+PTaZlaLUC+7DkAt4GJ3f7csxwbrRxKa/prs7Oweq1atikgbpeIVFjofztvAv8YuZd66nWSmpzJyYCsu6ZlN9ZTEaIcnce548vHRXiEpq1LnoCtjt7ThhLoWtyWUGP9dhmNvBz5x97bAJ8Ey7v68u3dz927AlcBKd59Z7FqXF20/WvFCjiy9ejJ/Ob8zr/2wH+nVk7nhuelc93Qua7btjXZoIlWCu28tXrwws9OiGU9ldnnvbNo2rMmf31vAgfyCaIcjInI4h5vzuSyDI58BzASaAN2Af5lZ7TIei7s/6u457p6TkZFR5oAl9iUkGMM7Z/LOzQN4+nu9aFavBn94ez797/mUf326hB37DkU7RJFvCVcB43DdOMrSLW0E8IyHTALqmFnmUY4dATwd/H4aOLeUa18KvHC8DZKy6dG8Lu/cPIDffOcEJi/fyml/H89DY5fq/wSIVLz/RjuAyiopMYHfntWRVVv38uTEldEOR0TkcA53v12WQZqvBV4P7reXAisI9cYoy7FSBZgZg9pl8PIP+vLKDX3p2jSd+z9aTP+7P+Uv7y9g08790Q5RBAhfAeNwsoA1xZbzgnVl2edIxzYKBoIj+G5YyrUv5n8LGE+a2Uwz+60d5l0HMxtpZrlmlrt58+bDt0y+lpSYwPUnt+Ljnw1iSPvQIJ9n/H0Cny7cGO3QROKKmY0+zOdtoH6046vMBrbL4JQODfnXp0vZvOtAtMMRETkWZRmkeTVwCoCZNQLaExrzqCzHShXTs0U9nry2F+/+eABDOjTksQnLGXDvWH71xhxWbtkT7fCkiitTAaO00YjNbHDxxcMdWsq6ktXjw+1Tpi5tpV7UrDew193nFlt9ubt3Bk4OPleWdqy6yB2/zPTq/PuKHjz9vV4kJBjfeyqX7z01lRVKdCLhcjLwH+CvpXx2RzGuuPDr75zAgfwC7v9wUbRDEZEqyMxuMrO6R9qltJVlHKT5/4B+ZjaH0OvXt7n7lsMdG6YmSSV3YpN0/nnpSXz6s8Fc2KMpr+bmMfSv47hp1HTmrtVshBIdSWXc72Uzexa4l9D7d/cSGi25aCChUosBlK1b2uH2STnCsRvNLDOY3i8TKDmexSWU6H3h7muD711mNorQKyrPHCZuKYdB7TL44JaBPP3FSh74ZAmn/3081w1oxc1D25BWrax/ciJSikmEirPjS24wM/2/7nJqlVGTa/q14PHPV3Bl3+Z0ykqPdkgiUrU0Bqaa2XTgCeBD//Zo+4e738bd3yM0k1TxdY8U+72O0ExRZTpWpLgWDdL483md+ckpbXli4kqem7SKd2av5+S2DbhhUGv6ta6vgfylwpT1FZLehIoJXxDqarYO6F+0sURPh+LK0i1tNHCVhfQBdgSvhRzp2NHA1cHvq4G3ik5mZgnARYTGzChal2RmDYLfycBZwOFiljBISUrg+wNb8enPBzGiWxaPjF/G4PvH8dLU1ZpnWuQ4uftwdx97mG0DKzqeeHTzKW2pVyOF34+eR6FylYhUIHf/DaFB7f8LXAMsMbM/m1nrYLvuXSWqGtZO5fbhHZh4+1B+Oaw9C9bv4vLHJ3POvyby7uz1useXClHWAsYhQtOPVifUA2OFux91kuAydml7j9A7eEuBx4AfHenY4Ji7gdPMbAlwWrBcZCCQ5+7Li62rBnxoZrMJjcC8NriWRFjDWqncf1FX3vhRP5rVrc5tr83hOw9+xudLqsTMjyJRYWZfRjuGyqp2ajK3D+9A7qqvePKLldEOR0SqmKDHxYbgkw/UBV41s3ujGphIMenVk/nR4DZ8ftsQ/nxeZ3btP8SNo6Yz9K/jeG7SKvYf0mD+Ejn27Z5ph9nJbBahXg7/R2iguP8Ah9z9wsiGF105OTmem5sb7TDihrvz7pz13P3+QvK+2sfQDg351ZkdaNOwVrRDE4mo45njupzXm+HuJ1XU9SpCReZjd+f7z+Ty2ZItvPvjk2nTsGaFXFdEKkZF5+SyMrMfE+pZvAV4HHjT3Q8FvYuXuHvrqAYY0P2xlFRQ6Hw0bwOPjF/GrLwd1E9L4ep+LbiyT3PqpqVEOzyJYceTj8vaA+M6d/+dux9y9w3uPoJir22IlIWZcVaXJnx86yDuGN6BqSu2ccY/PuNXb8zR1Ewi4aU+nOVgZvz5/M7USEnkZy/PJL/gqB0ORUTCoQFwvruf4e6vuPshgKDX81nRDU3k8BITjOGdM3nzxv68OLIPXZqm87cxi+l396f8fvQ81mzbG+0QJY6UqYDh7v9TZnX3Z8MfjlQFqcmJ/GBQa8b9YjBX9M7m5alrGHjfWO77cCE79x+KdngiIjSslcqfzuvMrLwdPDxuWbTDEZEqIHhYuOow2xZUdDwix8rM6NOqPk9e24sPfzKQMztn8vzkVQy+fxw3vzCD2Xnbox2ixIGy9sAQCbv6NavxhxGd+ORngzi9Y2MeGruMgfeO5bEJy/XunMgRHO9Ue3JszuycyYhuTXjwkyXMydN0cSIiImXVvnEt/vrdrkz45RCuH9CScQs3cc6/JnLJo1/y6cKNGihbjpsKGBJ1zeun8eClJ/HOzQPonJXOn95bwND7x/HClNUcUtdtkdIUTbX3spkNs/+du+ywU+3JsbnrnE7Ur5nCrS/PVGFVRETkGGWmV+eOM0/gizuG8pvvnMDqrXv53lO5nP6PCbw4ZbX+2yrHTAUMiRmdstJ59rrePH99bxrWTuWO1+dwyl/H89q0PE3LJFKMptqrOOk1krn3wq4s2bSbv41ZHO1wREREKqVaqclcf3Irxv9yCA9c0o2UxARuf30OA+75lAc+XsLW3QeiHaJUEipgSMzp36YBb/yoH/+9Ooea1ZL42SuzOP3v43l71jp1NxMJaKq9ijOoXQaX987msc+WM3n51miHIyIiUmklJyYwolsW7/54AKOu703nrHT+/nFowM9fvTGHZZt3RztEiXEqYEhMMjNOOaER79w8gH9f3p0EM25+YQbDHpjA27PWqUeGVGlm9mMzmwbcC0wEOrv7D4EewAVRDS5O/erME2hRP40bR81g/Y590Q5HRESkUjMz+rVpwJPX9mLMTwdy3klZvDotj1P+Op7rnprKF8u2EHpWI/JtKmBITEsIpmX64CcDeeCSbhQUOje/MIPT/z6eN2es1fSGUlVpqr0KllYtiUev7MG+g/n84NlpemdXREQkTNo2qsXdF3Rh4m1D+fEpbZm5ZjuXPTaZMx/8nNem5XEwX/f78g0VMKRSSEwwRnTL4qOfDuJfl51EUkICP3lpJqf9fQKvTsvTYJ9SpWiqveho26gW/7jkJGbn7eCO1+foyZCIiEgYZdSqxq2ntWPi7UO5+/zO5BcU8rNXZtH/nk/55ydL2LbnYLRDlBigAoZUKokJxlldmvD+LSfzyBXdSU1O5OevzGLwfeN45suVeioqIhF1WsdG3HpaO96YsZb/fr4i2uGIiIjEndTkRC7plc1HPx3I09/rRYfGtfjrmMX0/csn3PH6bBZv3BXtECWKkqIdgMjxSEgwhnXK5IwTG/PJgk08PG4pv3trHg9+soRr+7fkyr7NqZ2aHO0wRSQO3TSkDQvW7+TP7y2gfeNanNw2I9ohiYiIxB0zY1C7DAa1y2Dxxl08OXElr0/P44Upazi5bQO+N6Alg9pmkJBQcjZ5iWemLrCHl5OT47m5udEOQ8rA3ZmyYhsPj1vG+MWbqVUticv7NOfa/i1oVDs12uFJFWdm09w9J9pxVGaxlo/3HMjngn9/wfod+3nrxv60aJAW7ZBEpIyUk8sn1vKxVC3b9hzkhSmrefqLlWzadYBWGWlc268F53dvSlo1PZuvbI4nH+sVEokLZkbvVvV5+nu9ePfHAxjUPoNHJyxjwD2f8rOXZ7Fww85ohygicSStWhKPXZWDGXz/mVx27DsU7ZBERETiXr20FG4c0obPbxvKPy7uRs1qSfz2rXn0/csn/Pm9BeR9tTfaIUqEqQfGEajCXLmt3rqXJyau4KWpa9h3qICB7TIYeXIr+repj5m6mknF0dO+8ovVfPzFsi1c/cQUOmWl8+x1vamppz8iMU85uXxiNR9L1eTuTF/9FU9MXMkHczfg7pzesTHX9G9B75b1dM8f444nH6uAcQRK0PFh+96DPD95NU99sZLNuw7QoXEtru3fghHdskhNTox2eFIF6Ga5/GI5H38wdwM3jppOzxZ1efKaXlRPUV4RiWXKyeUTy/lYqrZ12/fx7KRVvDBlNdv3HuKEzNpc268F53Rronv+GKUCRpgpQceXA/kFvDVzHU98voKFG3ZRt0Yyl/XO5so+LWicrnEyJHJ0s1x+sZ6P35q5lp+8NJOT22bw2FU9qJakGyWRWKWcXD6xno9F9h8q4K2Za3ly4sqv7/kv7ZXNFX2a06RO9WiHJ8XE5BgYZjbMzBaZ2VIzu72U7WZmDwbbZ5tZ96Mda2b1zGyMmS0JvusG61uY2T4zmxl8Hil2TA8zmxOc60FTf6Iqp1pSIt/Nacb7t5zMC9/vQ88W9Xh4XGicjB+/MIPcldtQQU9EjseIblncc34XJizezM2jZnCooDDaIYmIiFRJqcmJXNwz++t7/l4t6/HI+GWcfO9YfvjcNCYt36p7/kosoi/rmlki8BBwGpAHTDWz0e4+v9huw4G2wac38G+g91GOvR34xN3vDgobtwO3Bedb5u7dSgnn38BIYBLwHjAMeD+c7ZXKwczo27o+fVvXZ/XWvTz95UpenrqG0bPW0TGzNlf2bc6Ibk2okaJ32UWk7L7bsxn7DhVw5+h53PryLP5xcTcSNbWbiIhIVBS/51+zbS/PTV7FS1PX8P7cDXRoXIur+7Xg3G5ZevWzkol0D4xewFJ3X+7uB4EXgREl9hkBPOMhk4A6ZpZ5lGNHAE8Hv58Gzj1SEMH5arv7lx4qtz1ztGOkasiuX4PfntWRSb86hT+f15lCd+54fQ69//wJd709n+Wbd0c7RBGpRK7u14Lbh3fg7Vnr+MWrs9QTQ0REJAY0q1eDO4afwKQ7TuGeCzpjZtzx+hz6/OUT/vTufFZt3RPtEKWMIv2IOQtYU2w5j1Avi6Ptk3WUYxu5+3oAd19vZg2L7dfSzGYAO4HfuPtnwbnySrmGCBCaEvGy3tlc2qsZuau+4pkvV/HspJU8MXEFfVvV59Le2ZxxYiO91y4iR3XDoNYcyi/kr2MWs3X3QR6+vLvmphcREYkBRa+XfDcndM//1BcreXLiSh7/fAVD2jfkyr7NGdQ2gwT1oIxZkb6jKu1/+ZIvHB1un7IcW9J6INvdt5pZD+BNMzvxWM5lZiMJvWpCdnb2US4n8cbM6NmiHj1b1GPTrhN4JTePF6eu5scvzKBeWgoX9WjKJb2yadkgLdqhihwzMxsGPAAkAo+7+90ltluw/UxgL3CNu083s1RgAlCN0H83XnX3O4Nj/o9Qr7hCYFNwzLpi58wG5gO/d/f7g3WXAr8ilIfXAVe4+5aINTwKbj6lLRm1qvHrN+dy8aNf8sQ1PWlYS4MFi4iIxILi9/wbduxn1JTVjJq8mmufnEqL+jW4ok9zLurRjPQaydEOVUqI9CskeUCzYstNCd2slmWfIx27MXgtpOj1kE0A7n7A3bcGv6cBy4B2wbmaHiUOguMedfccd8/JyMgoYzMlHjWslcqNQ9ow/udDeOZ7vejVol6oOnv/OC559Eten57HvoMF0Q5TpEyKjSs0HOgIXGpmHUvsVnxMopGExg4COAAMdfeuQDdgmJn1Cbbd5+5dgrGH3gF+V+Kcf6fYeENmlkSoSDLE3bsAs4GbwtHGWHNJr2wevyqHZZv2cP7DX7BMr6SJiIjEnMbpqdx6Wju+uH0oD1zSjfo1q/HHdxfQ+y8fc9urs5m7dke0Q5RiIl3AmAq0NbOWZpYCXAKMLrHPaOCqYDaSPsCO4PWQIx07Grg6+H018BaAmWUEN+mYWStCN+HLg/PtMrM+wRPGq4qOETmahARjYLsMHrmyB1/ePpRfnNGe9Tv2c+vLs+j1p4/59RtzmLVmu0Yzllh33GMSBctF/+87Ofg4gLvvLHZ8GsV6t5nZucByYF6xfSz4pAX5uDaHKSjHgyEdGvLSD/qw/1ABF/z7C3JXbot2SCIiIlKKlKQERnTL4rUf9uOdmwdwbrcs3pq1lrP++TnnPzyRN2bkcSBfDy+jLaIFDHfPJ/Rk7UNgAfCyu88zsxvM7IZgt/cI3eAuBR4DfnSkY4Nj7gZOM7MlhGYpKeoGPRCYbWazgFeBG9y96G7xh8DjwXWWoRlI5Dg0rB3qlTH2Z4N5cWQfTuvYiNem5zHioYkMf+AzHpuwnE279kc7TJHSHG68oTLtY2aJZjaTUI+3Me4+uWgnM/uTma0BLifogWFmaYRmh/pD8Qu4+yFC+XgOocJFR+C/5WxbTOvStA6v/7A/dWukcPnjk3lzxtpohyQiIiJH0Ckrnbsv6MLkO07lt2d15Ku9h/jpS7Po95dPueeDhazZtjfaIVZZpqfGh5eTk+O5ubnRDkNi3M79h3h71jpeyc1j5prtJCYYA9s24IIeTTn1hEakJmvgz6rOzKa5e06UY7gIOMPdrw+WrwR6ufvNxfZ5F/iLu38eLH8C/DJ4Ja9onzrAG8DN7j63xDXuAFLd/U4zux+Y4u4vm9nvgd3ufr+ZJQMfEHpFZTnwT2CDu/+xlJiLj0nUY9WqVWH6pxEd2/Yc5IbnpjFlxTYu7dWMO88+UflBJApiISdXZro/lqqosND5fOkWnpu0io8XbMSBoe0bckWf5gxsl6Fp04/T8eRjDYsuUk61U5O5vHdzLu/dnKWbdvP69DzemLGWm0bNoFZqEmd1yWREtyx6tainEY0lmsozJtHX3H27mY0DhgHfKmAAo4B3gTsJzRp1oZndC9QBCs1sPzA5OM8yADN7Gbi9tIDd/VHgUQjdMJehjTGtXloKo67vzd8/XsxDY5cxY/V2Hrq8O60zakY7NBERETmColfKB7bLYN32fbwwZTUvTFnDJ09NpVm96lzWqzkX5TSlQc1q0Q417qkHxhGowizHq6DQ+XLZVl6bnseH8zaw92ABTdJTOadbFuee1IQOjWtHO0SpQLHwtC8YPHMxcAqwltA4Q5cVezUPM/sOoVf3ziRUgHjQ3XuZWQZwKCheVAc+Au5x93fMrK27LwmOvxkY5O4Xlrj27/mmB0YTYBrQxd03B7OY1HD3nx0p/njLx+MWbeKnL83kYH4hfz6/MyO6aWZvkYoSCzk53Mowy9QvCL3mB6EHmCcAGe6+zcxWAruAAiD/aP9s4i0fixyvg/mFfDR/A89+uYrJK7aRnGgM65TJFb2z6dWyHqGhvuRI1ANDJEYkJhgD2jZgQNsG7D2Yz5j5G3lzxloe+2w5j4xfRofGtTinWxPO7tKEZvVqRDtcqQLcPd/MisYVSgSeKBqTKNj+CKExic4kNFbQXuDa4PBM4OlgkOQEQmMSvRNsu9vM2hOaRnUVUDS+0eHiWGdmfwAmmNmh4JhrwtfSymFw+4a8d8vJ3DxqBre8OJNJy7fx6++cQM1q+s+yiBybYrNMnUaoJ91UMxvt7vOL9nH3+4D7gv3PBn5abJw4CM0MFVfTWYtEWkpSAmd1acJZXZqwdNMunpu0mtem5/H2rHW0bViTy3tnc173pqRX11Ss4aQeGEegCrOE29bdB3h3znrenLGW6au3A9C1WR3O7pLJWV2a0Dg9NboBSkTE49O+ihav+fhQQSF//Wgx/5mwjCbp1fnjeZ0Y0r5htMMSiWvxlpPNrC/we3c/I1i+A8Dd/3KY/UcBY939sWB5JZBT1gJGvOZjkXDYd7CAt2et47nJq5idt4PU5ATO7tKEy/s0p2vTdPXKKOF48rEKGEegBC2RtGbbXt6ds553Zq9j7tqdmEHP5vUY3rkxwztlqpgRR+LtZjka4j0fT1u1jdtem8PSTbs5t1sTfntWR+rrPVqRiIi3nGxmFwLDSgzS3Nvdbypl3xqEemm0KeqBYWYrgK8ITYP9n2D8oZLHxdWgyiIVYU7eDkZNWcVbM9ex92ABHTNrc3mfbEZ0y1KPy4AKGGEW7zfMEjuWb97N27PW896c9SzauAuAnOZ1Gd45k+GdGtOkTvUoRyjlEW83y9FQFfLxgfwCHh67jIfHLaVmtSR+d3ZHzu2Wpac1ImEWbzm5LLNMFdv3YuAKdz+72Lomwet9DYExhGaZmnC461WFfCwSTrv2H+LNmet4ftIqFm7YRVpKIud0y+KyXtl0bpoe7fCiSgWMMFOClmhYumk3789Zz7tz1rNwQ6iY0bVZHYad2JgzTmxEK81YUOnE281yNFSlfLx44y5ue202M1Zvp1/r+vzqzBPolFW1b3BEwinecvKxvEJiZm8Ar7j7qMOc6/cEgy4f7npVKR+LhJO7M2PNdkZNXs07s9ex/1AhnbPSuax3Nud0bUJaFeyVoQJGmClBS7Qt37yb9+du4MN5G5idtwOAtg1rcsaJjTnjxMZ0yqqtp7OVQLzdLEdDVcvHBYXO85NX8bcxi9mx7xDndcviZ2e0J0u9sUTKLd5ycllmmQr2SwdWAM3cfU+wLg1IcPddwe8xwF3u/sHhrlfV8rFIJOzYd4g3pucxaspqFm/cXWV7ZaiAEWZK0BJL1m3fx0fzNvDBvA1MWbGNQofM9FROOaEhp57QiL6t61MtKTHaYUop4u1mORqqaj7ese8QD49bypMTVwLwvf4t+dGQ1tRO1YjmIscrHnOymZ0J/INvZpn6U4lZpjCzawiNlXFJseNaAW8Ei0nAKHf/05GuVVXzsUgkuDvTV3/FqMlreHdOqFdGp6zaXNor1CujVpz/914FjDBTgpZYtW3PQT5ZsJGPF2xkwuIt7DtUQFpKIoPaZ3BKh0YMbp+hAQBjSDzeLFe0qp6P127fx18/XMTrM9ZSt0Yy1w1oyZV9W2hqNpHjoJxcPlU9H4tEyo59h3hr5lpGTV7Nwg27qJ6cyNldM7mkVzYnNasTl72uVcAIMyVoqQz2Hyrgy2VbGbNgIx/P38imXQcwg65N6zC0Q0OGdmjIiU30qkk06Wa5/JSPQ+au3cH9Hy1i3KLN1KyWxOV9srluQEsa1tKsRSJlpZxcPsrHIpHl7szK28ELk1fz9uzQDCbtG9Xikl7NOO+kLOrUSIl2iGGjAkaYKUFLZVNY6Mxbt5NPF27i00WbmLVmOwANa1VjcPsMBrVryIA2DUivoae2FUk3y+WnfPxt89bt4N/jlvHenPUkJSZwUY+m/GBga7Lr14h2aCIxTzm5fJSPRSrO7gP5vD1rHS9OWc2svB2kJCUwvFNjLumZTZ9W9Sr9A0oVMMJMCVoqu827DjBu0SbGLtrEZ0u2sGt/PgkGJ2XXZXC7DAa1z6BTk3QSEip38ot1ulkuP+Xj0q3csof/TFjGa9PWcqiwkEHtMri8d3OGtM8gKTEh2uGJxCTl5PJRPhaJjvnrdvLS1NW8PmMtu/bn07x+Db6b04wLezSlUe3K2RNTBYwwU4KWeJJfUMjMNdsZt2gz4xdvZs7a0KwmdWsk069NAwa2bcCAthma5SACdLNcfsrHR7Zx536en7yaF6esZtOuA2Smp3JJz2wu7tmMxumV86ZGJFKUk8tH+VgkuvYfKuD9uet5aeoaJi3fRmKCMaR9Bhf3zK50DzBUwAgzJWiJZ1t2H+CzJZv5bMkWPl+yhU27DgDQKiONAW0a0K91A/q2qq/XTcJAN8vlp3xcNocKCvlkwSaen7yKz5ZsITHBGNQugxHdmnDqCY2q5BzzIiUpJ5eP8rFI7FixZQ8v567h1Wl5bN51gIxa1bige1O+m9OUVhk1ox3eUamAEWZK0FJVuDuLN+7+uqAxZcU29h0qwAw6NUmnX+v69GvTgJzmdfV/gI6DbpbLT/n42K3auocXpqxh9My1rNuxn+rJiZzWsREjujXh5LYZpCRVnic0IuGknFw+yscisedQQSHjFm3mpalrGLtoEwWFTs8WdfluTjO+0yWTGimxef+uAkaYKUFLVXUwv5BZeduZuHQLXyzbyozVX3GowElKMLo0TadPq/r0aVWfHipolIlulstP+fj4FRY6uau+4q2Za3l3znq27z1EevVkhnZoyKknNGJguwZxP8+8SHHKyeWjfCwS2zbt3M9r09fySu4alm/ZQ1pKImd3bcJFOc3onh1b07HGZAHDzIYBDwCJwOPufneJ7RZsPxPYC1zj7tOPdKyZ1QNeAloAK4HvuvtXZnYacDeQAhwEfuHunwbHjAMygX3BpU93901Hil0JWiRk78F8cld+xaTlW5m0fCuz83aQX/hNQaNny3r0alGPnOb19MpJKXSzXH7Kx+FxML+Qz5du5p1Z6/l00Sa27z1EcqLRp1V9Tj2hEUM7NKRZPc1kIvFNObl8lI9FKgd3Z+rKr3gldw3vzlnP3oMFtM5I47s5zTive1ZMTMEecwUMM0sEFgOnAXnAVOBSd59fbJ8zgZsJFTB6Aw+4e+8jHWtm9wLb3P1uM7sdqOvut5nZScBGd19nZp2AD909K7jOOODn7l7mjKsELVK6PQfymbYqVNCYvGIbs/O2c6jAMYP2jWrRq2U9clrUo0fzuhoUFN0sh4PycfjlFxQyffV2Pl6wkY/nb2T5lj0AZNerQf829ekfjIVTLy1+5psXAeXk8lI+Fql8dh/I573Z63k5dw25q776euDPC3s0Y2iHhlF7rfR48nGk+373Apa6+3IAM3sRGAHML7bPCOAZD1VSJplZHTPLJNS74nDHjgAGB8c/DYwDbnP3GcXOOw9INbNq7n4gMs0TqZrSqiUxsF0GA9tlAKHRkGes3s7UlduYunIbr07L45kvVwGQmZ5Kj+Z16dG8LjnN69EhsxbJlWh0ZJF4lZSYQK+W9ejVsh6/OvMElm3ezYTFm5m4dCvvzFrPC1PWANAxs3ZQlAz9e5yZrqKkiIhIZVKzWhLf7dmM7/ZsxrLNu3klN4/Xp+fx8YJN1EtL4dxuWVyU05QTMmtHO9SjinQBIwtYU2w5j1Avi6Ptk3WUYxu5+3oAd19vZg1LufYFwIwSxYsnzawAeA34o5fS/cTMRgIjAbKzs4/cOhEBIDU5kb6t69O3dX0g9GR34YZd5K7cRu6qr5i26ivemb0+2DeBLll1OCm7Didl16V7dh0aVtK5q0XiSeuMmrTOqMm1/VuSX1DI7LU7+GLpFiYu3cqLU1fz1BcrAciqU/3romTnpul0zKxNanJidIMXERGRMmmdUZPbh3fg56e347MlW3hl2hqenbSSJyauoFNWbS7q0Yxzujahboz2wIx0AaO0EUJKFg0Ot09Zji39omYnAvcApxdbfbm7rzWzWoQKGFcCz/zPBdwfBR6FUBe5slxPRL4tKTGBTlnpdMpK55r+LQFYt30fuau+Yubq7Uxf/RVPTFzBoQnLAWiSnkrXZnXo0rQOXZul0zkrXYMKikRRUmIC3bPr0j27LjcNbcuhgkIWrN9J7spQQXLyiq2MnrUOgMQEo23DmnTOSv+6oNGucS1q699hERGRmJWUmMCQDg0Z0qEhX+05yFsz1/LKtDzuHD2PP747n1NPaMRFOU0Z2DaDpBjqPR3pAkYe0KzYclNgXRn3STnCsRvNLDPofZEJfD0Yp5k1Bd4ArnL3ZUXr3X1t8L3LzEYRer3lfwoYIhIZTepU55w61TmnaxMg9NrJ/PU7mb7qK2bl7WB23nben7sBALNQdbhLUAQp+j9FmvFEJDqSExPo0jRUZPzegJa4O+t37GfO2h3MXbuD2Xk7+HThJl6Zlvf1MVl1qtO+cS3aN65Fh8a1aJ1Rk5YN0vTvsYiISIypm5bCNf1bck3/lsxft5PXpufx5oy1vD93Axm1qnHeSVlc0L0p7RvXinaoES9gTAXamllLYC1wCXBZiX1GAzcFY1z0BnYEhYnNRzh2NHA1oRlHrgbeAjCzOsC7wB3uPrHoAmaWBNRx9y1mlgycBXwcgfaKSBmlJid+/YS3yFd7DjJ77Q5mrdnOrDXb+XzpFl6fsRb4pqjROSudE5vUpmOT2pyYma5ZT0SiwMxoUqc6TepU54wTGwOh0c7X7djPgnU7WbRxF4s2hD4TFm8mv/CbDo2Z6am0ykijVYNQQaN5/Ro0r1+DpnVr6FUUERGRKOvYpDYdm3Tk9uEdGBs8nHji8xU8OmE5nbPSuaB7Fud0y4raIN8VMY3qmcA/CE2F+oS7/8nMbgBw90eCaVT/BQwjNI3qtUUzhZR2bLC+PvAykA2sBi5y921m9hvgDmBJsRBOB/YAE4Dk4FwfA7e6e8GRYtcoyyLRt3Hnfubk7fj6Se/cdTvYuPOboW2y6lT/uqDRoXFtOmbWpmnd6iQkVO45ruXblI8rr4P5hazYsoflm3ezbPNulm/ew7Jgedf+/G/t27h2Ktn1atC0bnWy6oYKJFl1vvmunqICh5SfcnL5KB+LVD1bdx9g9Kx1vDotj3nrdpKcaAzt0JALujdlcPvjn8Uk5qZRreyUoEVi05bdB5i/bifz1u1k/vqdzFu3gxVb9lCUztJSEkPd1jNr06FxLdo1qkX7RrWiNhiRbpbLT/k4/rg7W/ccZPW2vazZtpdVW0Of1dv2sParfWzYuZ/CErco6dWTaVS7Go1qp9K4diqN01NpWDuVjJrVyKhVjYa1qtGgZjUVOuSIlJPLR/lYpGpbsH4nr03L482Za9my+yD10lI4p2sTzu+eReesdEL9E8pGBYwwU4IWqTz2HSxg8cZdLFi/k4UbQt8L1u9kZ7EnvBm1qtG+US3aNqpJ24a1aNOwJm0b1ox4YUM3y+WnfFz15BcUsmHnftZt38/a7XtZt30/G3bsZ+PO0GfDzv1s3nXgf4ocEJourn7NFOqlpVA/LfiuWY36aSmkV0+mbo0U6qYlU6dGCnVrhNYlxlCvLYks5eTyUT4WEQj9d/qzJVt4dXoeY+Zv5GB+IW0b1uT87k0596QmZZp2/XjysUbSEpG4UD0lka7N6tC1WZ2v17k7G3ceYPHGXSwO3slfvHEXL05Zw75D37xBVj8thdYNa9KmYU1aNUj7ejrJrLrV9X9qRKIkKTGBpnVDY2NAvVL3yS8oZOueg2zedYAtuw+wedcBNgffW3cfZNueg6zdvp/ZeTvYtufgt8biKKlWtSRqV0+mdvVk0qsnUTs19LtWahK1UpOpnZr09e+a1ZJIqxZaTquWFFpOSYypUdpFREQiqfgsJjv2HeLd2et5bXoe93ywkHs/XEj/1g04v3sWZ5zYOKwDeKuAISJxy8xonB7qZj6wXcbX6wsLnXU79rF0026WbtrNko27WbJpF+/OXs+OfYe+3i8lKYEW9WvQskEaLRqk0bJ+8N0gjYa1qh1TFzkRCb+kxAQa1U6lUe3Uo+7r7uzcn8+OvYf4au9Bvtp7kO3B7x37Dn392bkvn537DrFq61527T/Erv357DqQf9TzA1RLSiCtWhI1UhJJS0miRrVEaqQkUj05tK5GSiLVg+/UpNDv1OREqieHvlOTE6ienEi14HdqsL5aUgLVkkLLSQmm3CMiIjElvXoyl/XO5rLe2azcsoc3Zqzl9Rl53PryLGqkzGXYiY05r3sW/Vo3KPfDQRUwRKTKSUiwr5/sDm7f8Ov17s62PQdZ/vWAg6HvpZt2M3bhZg4WFH69b42URLLr1SC7XmgGhex6Nciun0Z2vRpk1al+3IMZiUhkmBnp1ZNJr55Mdv0ax3RsYaGz+2B+qJix/xB7DoR+7zlQwO4DoSLH3oMF7DmYz94DBew5kB/6fbCAvQcL2LZnH/uC5X2HCth3sOCIvUGOJMGgWlIi1ZITSElM+OY7KZGUpITQJ/Hb38lfL9vXv4u+kxJC65KTEkgOficlGimJCSQV/51gJCUmkJxoJCWEvhOL7Z+YYCQnJJCYGHwnGEkJFlMDKouISOS1aJDGT09rx09Obcu0VV/x2vS1vDN7Ha/PWEuj2tUY0S2L807K4oTM2sd1fhUwREQCZhZ6T75mNXq2+HaX9YJCZ932fazYsoeVW/ewcktosMEVW/YwfvFmDuQXFjtPaDaFZnVr0LTe0d//E5HYlpBgoVdKUpOB8Pw7faigkP2HQgWN/QcL2Xson/2HQutCn0IO5Id+H8gv5ECwfCC/8Ot1B4PPga8/BRzML2TPwXy27/tm+8H8Qg4Veui7oOhTMWOgmfGtgkZiYvCdECqEJAa/v95e/GMlloN1CaVsSzAjMYFiv7/5/tZ29V4REakQZkZOi3rktKjHnWd35NOFm3h9+tqvp2Tt0LjWcZ1XBQwRkTJITDCa1atBs3o1GEjGt7YVFjqbdh1g1dY9rPlqH2u27WXNV3vJ27aPL5dtjVLEIhLLkhNDvSBqpSZH5fqFhU5+oXOooJD8AudgwbeLG/mFhRzKdw4VhrYXbcsv2hZ85xc4BYXOoUKnoKAwOKdT6KFjCoLrFATXKiy2nF/o5BcUUuBF8Xx7/6LPwfxCCvzb6wqLL7tTWEix3/71/oXFtwfrRESkYqUmJ3Jm50zO7JzJ1t0HeGf2el6fsfa4zqUChohIOSUkfDPWRu9SttuvKjwkEZEjSkgwUhKsSr7uZvdEOwIRkaqrfs1qXN2vBVf3a4HddOzHV73/aomIVFFmNszMFpnZUjO7vZTtZmYPBttnm1n3YH2qmU0xs1lmNs/M/lDsmP8L9p1pZh+ZWZMS58w2s91m9vNi61LM7FEzW2xmC83sgki2W0RERETigwoYIiJVgJklAg8Bw4GOwKVm1rHEbsOBtsFnJPDvYP0BYKi7dwW6AcPMrE+w7T537+Lu3YB3gN+VOOffgfdLrPs1sMnd2wWxjC9f60RERESkKtArJCIiVUMvYKm7LwcwsxeBEcD8YvuMAJ5xdwcmmVkdM8t09/XA7mCf5ODjAO6+s9jxaUXrg2ucCywH9pSI5XtAh+D4QmBLOBooIiIiIvFNPTBERKqGLGBNseW8YF2Z9jGzRDObCWwCxrj75KKdzOxPZrYGuJygB4aZpQG3AX8odj7MrE7w8//MbLqZvWJmjUoL2MxGmlmumeVu3rz5WNoqIiIiInFIBQwRkaqhtLkDSw7Hf9h93L0geE2kKdDLzDp9vYP7r929GfA8UDQc0x+Av7v77hLnSwrOMdHduwNfAveXFrC7P+ruOe6ek5GRUdouIiIiIlKF6BWSI5g2bdoWM1sV7TjCoAHx30U73tuo9lVu7aMdAKHeFM2KLTcF1h3rPu6+3czGAcOAuSWOHwW8C9wJ9AYuNLN7gTpAoZntJzQOx17gjeCYV4DrjhZ8HOVjiP+/d7Wv8ov3NsZCTq60lI8rlXhvH8R/G+O9fcecj1XAOAJ3j4tHfmaW6+450Y4jkuK9jWpf5WZmudGOAZgKtDWzlsBa4BLgshL7jAZuCsbH6A3scPf1ZpYBHAqKF9WBU4F7AMysrbsvCY4/B1gI4O4nF53UzH4P7Hb3fwXLbwODgU+BU/j2OBylipd8DFXj713tq9zivY0xkpMrLeXjyiPe2wfx38aq0L5jPUYFDBGRKsDd883sJuBDIBF4wt3nmdkNwfZHgPeAM4GlhHpJXBscngk8HcxkkgC87O7vBNvuNrP2QCGwCrihDOHcBjxrZv8ANhe7joiIiIjIYamAISJSRbj7e4SKFMXXPVLstwM3lnLcbOCkw5zzgjJc9/clllcBA8sUtIiIiIhIQIN4Vg2PRjuAChDvbVT7Krd4b58cm3j/e1D7Kr94b2O8t0/KLt7/FuK9fRD/bVT7SrDQAzcRERERERERkdilHhgiIiIiIiIiEvNUwBARERERERGRmKcCRpwxsyfMbJOZzS22rp6ZjTGzJcF33WjGWB5m1szMxprZAjObZ2a3BOvjoo1mlmpmU8xsVtC+PwTr46J9Rcws0cxmmNk7wXK8tW+lmc0xs5lF00PFWxvl6JSP46KNysmVvH3Kx1JEOblyt1H5OG7aV+6crAJG/HkKGFZi3e3AJ+7eFvgkWK6s8oGfufsJQB/gRjPrSPy08QAw1N27At2AYWbWh/hpX5FbgAXFluOtfQBD3L1bsbm747GNcmRPoXxc2duonBwf7VM+FlBOruxtVD6Oj/ZBOXOyChhxxt0nANtKrB4BPB38fho4tyJjCid3X+/u04Pfuwj9C55FnLTRQ3YHi8nBx4mT9gGYWVPgO8DjxVbHTfuOoCq0UYpRPgYqfxuVkyt5+w4j3tsnpVBOBipxG5WPgUreviM4pjaqgFE1NHL39RBKbkDDKMcTFmbWAjgJmEwctTHoOjYT2ASMcfe4ah/wD+CXQGGxdfHUPgj9B/UjM5tmZiODdfHWRjk+cfl3EK/5GJST46B9ysdyJHH5txCvOVn5uNK3D8KQk5MiHKBIRJhZTeA14CfuvtPMoh1S2Lh7AdDNzOoAb5hZpyiHFDZmdhawyd2nmdngKIcTSf3dfZ2ZNQTGmNnCaAckEinxnI9BOTkOKB9LlRLPOVn5OC6UOyerB0bVsNHMMgGC701RjqdczCyZUGJ+3t1fD1bHVRsB3H07MI7Q+5rx0r7+wDlmthJ4ERhqZs8RP+0DwN3XBd+bgDeAXsRZG+W4xdXfQVXJx6CcHL0Qy0f5WI4irv4WqkpOVj6uvMKRk1XAqBpGA1cHv68G3opiLOVioTLyf4EF7v63Ypvioo1mlhFUlTGz6sCpwELipH3ufoe7N3X3FsAlwKfufgVx0j4AM0szs1pFv4HTgbnEURulXOLm7yDe8zEoJwe7Vdr2KR9LGcTN30K852TlY6AStw/Cl5PN3SMZp1QwM3sBGAw0ADYCdwJvAi8D2cBq4CJ3LzmIUaVgZgOAz4A5fPN+2K8IveNX6dtoZl0IDV6TSKjA+LK732Vm9YmD9hUXdI/7ubufFU/tM7NWhCrKEHpNb5S7/yme2ihlo3wcF21UTq7E7VM+luKUkyt3G5WPK3/7wpWTVcAQERERERERkZinV0hEREREREREJOapgCEiIiIiIiIiMU8FDBERERERERGJeSpgiIiIiIiIiEjMUwFDRERERERERGKeChhSaZlZYzN70cyWmdl8M3vPzNodx3nGmVlOJGI8xjiuMbN/RTsOEZFjpXwsIhI7lJMlnqmAIZWSmRmheYTHuXtrd+9IaK7rRtGNLHrMLDHaMYhI1aN8/L+Uj0UkWpST/5dycnxRAUMqqyHAIXd/pGiFu89098/M7FkzG1G03syeN7NzzCzRzO43szlmNtvMbi55UjM73cy+NLPpZvaKmdUsZZ9xZnaPmU0xs8VmdnKw/lvVYTN7x8wGB793B8dMM7OPzaxXcJ7lZnZOsdM3M7MPzGyRmd1Z7FxXBNebaWb/KUrEwXnvMrPJQN9y/PMUETleyscoH4tIzFBORjk5nqmAIZVVJ2DaYbY9DlwLYGbpQD/gPWAk0BI4yd27AM8XP8jMGgC/AU519+5ALnDrYa6R5O69gJ8Adx5mn+LSCFXCewC7gD8CpwHnAXcV268XcDnQDbjIzHLM7ATgYqC/u3cDCoJ9is471917u/vnZYhDRCTclI+/Oa/ysYhEm3LyN+dVTo5DSdEOQCTc3H28mT1kZg2B84HX3D3fzE4FHnH3/GC/bSUO7QN0BCaaGUAK8OVhLvN68D0NaFGGsA4CHwS/5wAH3P2Qmc0pcfwYd98KYGavAwOAfKAHMDWIqzqwKdi/AHitDNcXEalwysciIrFDOVnigQoYUlnNAy48wvZnCVVgLwG+F6wzwI9wjBFKjpeW4foHgu8Cvvn3KJ9v92pKLfb7kLsXXbuw6Hh3LzSz4v8elozPg7iedvc7Soljv7sXlCFeEZFIUT4OUT4WkVignByinByn9AqJVFafAtXM7PtFK8ysp5kNChafItR1DXefF6z7CLihKBmaWb0S55wE9DezNsH2GnZsIzavBLqZWYKZNSPU1e1YnWZm9cysOnAuMBH4BLgwqJYTbG9+HOcWEYkE5WMRkdihnCxxTQUMqZSCSu15hJLZMjObB/weWBds3wgsAJ4sdtjjwGpgtpnNAi4rcc7NwDXAC2Y2m1Cy7nAMYU0EVhDq/nY/MP2YGwafE6qMzyTUrS/X3ecTeu/woyCuMUDmcZxbRCTslI+Vj0UkdignKyfHO/umx45I/DCzGoSSZHd33xHteEREqirlYxGR2KGcLJWdemBI3AkGIloI/FOJWUQkepSPRURih3KyxAP1wBARERERERGRmKceGCLy/+3YsQAAAADAIH/raewojAAAAPYEBgAAALAnMAAAAIA9gQEAAADsCQwAAABgL9b4fdlFzlcNAAAAAElFTkSuQmCC\n", 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" ] @@ -776,1172 +748,1064 @@ "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:32,933 - [NOTICE] simulation.solve(809): Cycle 1/500 (36.016 ms elapsed) --------------------\n", - "2021-09-17 01:13:32,933 - [NOTICE] simulation.solve(843): Cycle 1/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:32,975 - [NOTICE] simulation.solve(843): Cycle 1/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:33,012 - [NOTICE] simulation.solve(843): Cycle 1/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:33,036 - [NOTICE] simulation.solve(843): Cycle 1/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:33,186 - [NOTICE] simulation.solve(921): Capacity is now 3.944 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:33,186 - [NOTICE] simulation.solve(809): Cycle 2/500 (281.840 ms elapsed) --------------------\n", - "2021-09-17 01:13:33,186 - [NOTICE] simulation.solve(843): Cycle 2/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:33,218 - [NOTICE] simulation.solve(843): Cycle 2/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:33,244 - [NOTICE] simulation.solve(843): Cycle 2/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:33,268 - [NOTICE] simulation.solve(843): Cycle 2/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:33,292 - [NOTICE] simulation.solve(921): Capacity is now 3.930 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:33,292 - [NOTICE] simulation.solve(809): Cycle 3/500 (398.978 ms elapsed) --------------------\n", - "2021-09-17 01:13:33,292 - [NOTICE] simulation.solve(843): Cycle 3/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:33,333 - [NOTICE] simulation.solve(843): Cycle 3/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:33,356 - [NOTICE] simulation.solve(843): Cycle 3/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:33,381 - [NOTICE] simulation.solve(843): Cycle 3/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:33,417 - [NOTICE] simulation.solve(921): Capacity is now 3.916 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:33,417 - [NOTICE] simulation.solve(809): Cycle 4/500 (513.367 ms elapsed) --------------------\n", - "2021-09-17 01:13:33,417 - [NOTICE] simulation.solve(843): Cycle 4/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:33,443 - [NOTICE] simulation.solve(843): Cycle 4/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:33,455 - [NOTICE] simulation.solve(843): Cycle 4/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:33,491 - [NOTICE] simulation.solve(843): Cycle 4/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:33,525 - [NOTICE] simulation.solve(921): Capacity is now 3.903 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:33,525 - [NOTICE] simulation.solve(809): Cycle 5/500 (622.454 ms elapsed) --------------------\n", - "2021-09-17 01:13:33,525 - [NOTICE] simulation.solve(843): Cycle 5/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:33,554 - [NOTICE] simulation.solve(843): Cycle 5/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:33,575 - [NOTICE] simulation.solve(843): Cycle 5/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:33,600 - [NOTICE] simulation.solve(843): Cycle 5/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:33,625 - [NOTICE] simulation.solve(921): Capacity is now 3.889 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:33,625 - [NOTICE] simulation.solve(809): Cycle 6/500 (734.356 ms elapsed) --------------------\n", - "2021-09-17 01:13:33,625 - [NOTICE] simulation.solve(843): Cycle 6/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:33,667 - [NOTICE] simulation.solve(843): Cycle 6/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:33,691 - [NOTICE] simulation.solve(843): Cycle 6/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:33,712 - [NOTICE] simulation.solve(843): Cycle 6/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:33,742 - [NOTICE] simulation.solve(921): Capacity is now 3.876 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:33,742 - [NOTICE] simulation.solve(809): Cycle 7/500 (844.195 ms elapsed) --------------------\n", - "2021-09-17 01:13:33,742 - [NOTICE] simulation.solve(843): Cycle 7/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:33,777 - [NOTICE] simulation.solve(843): Cycle 7/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:33,792 - [NOTICE] simulation.solve(843): Cycle 7/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:33,818 - [NOTICE] simulation.solve(843): Cycle 7/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:33,859 - [NOTICE] simulation.solve(921): Capacity is now 3.862 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:33,859 - [NOTICE] simulation.solve(809): Cycle 8/500 (955.172 ms elapsed) --------------------\n", - "2021-09-17 01:13:33,859 - [NOTICE] simulation.solve(843): Cycle 8/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:33,887 - [NOTICE] simulation.solve(843): Cycle 8/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:33,913 - [NOTICE] simulation.solve(843): Cycle 8/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:33,933 - [NOTICE] simulation.solve(843): Cycle 8/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:33,967 - [NOTICE] simulation.solve(921): Capacity is now 3.849 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:33,967 - [NOTICE] simulation.solve(809): Cycle 9/500 (1.069 s elapsed) --------------------\n", - "2021-09-17 01:13:33,967 - [NOTICE] simulation.solve(843): Cycle 9/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:34,001 - [NOTICE] simulation.solve(843): Cycle 9/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:34,025 - [NOTICE] simulation.solve(843): Cycle 9/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:34,047 - [NOTICE] simulation.solve(843): Cycle 9/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:34,075 - [NOTICE] simulation.solve(921): Capacity is now 3.836 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:34,075 - [NOTICE] simulation.solve(809): Cycle 10/500 (1.178 s elapsed) --------------------\n", - "2021-09-17 01:13:34,075 - [NOTICE] simulation.solve(843): Cycle 10/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:34,107 - [NOTICE] simulation.solve(843): Cycle 10/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:34,131 - [NOTICE] simulation.solve(843): Cycle 10/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:34,152 - [NOTICE] simulation.solve(843): Cycle 10/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:34,183 - [NOTICE] simulation.solve(921): Capacity is now 3.823 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:34,183 - [NOTICE] simulation.solve(809): Cycle 11/500 (1.284 s elapsed) --------------------\n", - "2021-09-17 01:13:34,183 - [NOTICE] simulation.solve(843): Cycle 11/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:34,213 - [NOTICE] simulation.solve(843): Cycle 11/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:34,233 - [NOTICE] simulation.solve(843): Cycle 11/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:34,260 - [NOTICE] simulation.solve(843): Cycle 11/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:34,293 - [NOTICE] simulation.solve(921): Capacity is now 3.810 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:34,293 - [NOTICE] simulation.solve(809): Cycle 12/500 (1.393 s elapsed) --------------------\n", - "2021-09-17 01:13:34,293 - [NOTICE] simulation.solve(843): Cycle 12/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:34,322 - [NOTICE] simulation.solve(843): Cycle 12/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:34,343 - [NOTICE] simulation.solve(843): Cycle 12/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:34,370 - [NOTICE] simulation.solve(843): Cycle 12/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:34,406 - [NOTICE] simulation.solve(921): Capacity is now 3.797 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:34,407 - [NOTICE] simulation.solve(809): Cycle 13/500 (1.502 s elapsed) --------------------\n", - "2021-09-17 01:13:34,407 - [NOTICE] simulation.solve(843): Cycle 13/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:34,433 - [NOTICE] simulation.solve(843): Cycle 13/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:34,458 - [NOTICE] simulation.solve(843): Cycle 13/500, step 3/4: Charge at 1C until 4.2V\n" + "2021-11-19 15:28:47,257 - [NOTICE] simulation.solve(850): Cycle 1/500 (26.952 ms elapsed) --------------------\n", + "2021-11-19 15:28:47,258 - [NOTICE] simulation.solve(884): Cycle 1/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:47,294 - [NOTICE] simulation.solve(884): Cycle 1/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:47,314 - [NOTICE] simulation.solve(884): Cycle 1/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:47,335 - [NOTICE] simulation.solve(884): Cycle 1/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:47,466 - [NOTICE] simulation.solve(972): Capacity is now 3.946 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:47,466 - [NOTICE] simulation.solve(850): Cycle 2/500 (236.473 ms elapsed) --------------------\n", + "2021-11-19 15:28:47,467 - [NOTICE] simulation.solve(884): Cycle 2/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:47,486 - [NOTICE] simulation.solve(884): Cycle 2/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:47,504 - [NOTICE] simulation.solve(884): Cycle 2/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:47,522 - [NOTICE] simulation.solve(884): Cycle 2/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:47,555 - [NOTICE] simulation.solve(972): Capacity is now 3.930 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:47,555 - [NOTICE] simulation.solve(850): Cycle 3/500 (325.191 ms elapsed) --------------------\n", + "2021-11-19 15:28:47,555 - [NOTICE] simulation.solve(884): Cycle 3/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:47,574 - [NOTICE] simulation.solve(884): Cycle 3/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:47,592 - [NOTICE] simulation.solve(884): Cycle 3/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:47,612 - [NOTICE] simulation.solve(884): Cycle 3/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:47,647 - [NOTICE] simulation.solve(972): Capacity is now 3.915 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:47,647 - [NOTICE] simulation.solve(850): Cycle 4/500 (417.476 ms elapsed) --------------------\n", + "2021-11-19 15:28:47,648 - [NOTICE] simulation.solve(884): Cycle 4/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:47,669 - [NOTICE] simulation.solve(884): Cycle 4/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:47,687 - [NOTICE] simulation.solve(884): Cycle 4/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:47,708 - [NOTICE] simulation.solve(884): Cycle 4/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:47,744 - [NOTICE] simulation.solve(972): Capacity is now 3.900 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:47,744 - [NOTICE] simulation.solve(850): Cycle 5/500 (514.553 ms elapsed) --------------------\n", + "2021-11-19 15:28:47,745 - [NOTICE] simulation.solve(884): Cycle 5/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:47,765 - [NOTICE] simulation.solve(884): Cycle 5/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:47,785 - [NOTICE] simulation.solve(884): Cycle 5/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:47,803 - [NOTICE] simulation.solve(884): Cycle 5/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:47,839 - [NOTICE] simulation.solve(972): Capacity is now 3.885 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:47,840 - [NOTICE] simulation.solve(850): Cycle 6/500 (610.046 ms elapsed) --------------------\n", + "2021-11-19 15:28:47,840 - [NOTICE] simulation.solve(884): Cycle 6/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:47,861 - [NOTICE] simulation.solve(884): Cycle 6/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:47,880 - [NOTICE] simulation.solve(884): Cycle 6/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:47,898 - [NOTICE] simulation.solve(884): Cycle 6/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:47,934 - [NOTICE] simulation.solve(972): Capacity is now 3.870 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:47,934 - [NOTICE] simulation.solve(850): Cycle 7/500 (704.328 ms elapsed) --------------------\n", + "2021-11-19 15:28:47,935 - [NOTICE] simulation.solve(884): Cycle 7/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:47,955 - [NOTICE] simulation.solve(884): Cycle 7/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:47,976 - [NOTICE] simulation.solve(884): Cycle 7/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:47,992 - [NOTICE] simulation.solve(884): Cycle 7/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:48,025 - [NOTICE] simulation.solve(972): Capacity is now 3.855 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:48,026 - [NOTICE] simulation.solve(850): Cycle 8/500 (795.894 ms elapsed) --------------------\n", + "2021-11-19 15:28:48,026 - [NOTICE] simulation.solve(884): Cycle 8/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:48,046 - [NOTICE] simulation.solve(884): Cycle 8/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:48,064 - [NOTICE] simulation.solve(884): Cycle 8/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:48,080 - [NOTICE] simulation.solve(884): Cycle 8/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:48,112 - [NOTICE] simulation.solve(972): Capacity is now 3.840 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:48,113 - [NOTICE] simulation.solve(850): Cycle 9/500 (882.787 ms elapsed) --------------------\n", + "2021-11-19 15:28:48,113 - [NOTICE] simulation.solve(884): Cycle 9/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:48,130 - [NOTICE] simulation.solve(884): Cycle 9/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:48,148 - [NOTICE] simulation.solve(884): Cycle 9/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:48,166 - [NOTICE] simulation.solve(884): Cycle 9/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:48,326 - [NOTICE] simulation.solve(972): Capacity is now 3.826 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:48,326 - [NOTICE] simulation.solve(850): Cycle 10/500 (1.097 s elapsed) --------------------\n", + "2021-11-19 15:28:48,327 - [NOTICE] simulation.solve(884): Cycle 10/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:48,343 - [NOTICE] simulation.solve(884): Cycle 10/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:48,361 - [NOTICE] simulation.solve(884): Cycle 10/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:48,377 - [NOTICE] simulation.solve(884): Cycle 10/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:48,410 - [NOTICE] simulation.solve(972): Capacity is now 3.811 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:48,410 - [NOTICE] simulation.solve(850): Cycle 11/500 (1.180 s elapsed) --------------------\n", + "2021-11-19 15:28:48,410 - [NOTICE] simulation.solve(884): Cycle 11/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:48,428 - [NOTICE] simulation.solve(884): Cycle 11/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:48,447 - [NOTICE] simulation.solve(884): Cycle 11/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:48,467 - [NOTICE] simulation.solve(884): Cycle 11/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:48,503 - [NOTICE] simulation.solve(972): Capacity is now 3.797 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:48,504 - [NOTICE] simulation.solve(850): Cycle 12/500 (1.274 s elapsed) --------------------\n", + "2021-11-19 15:28:48,504 - [NOTICE] simulation.solve(884): Cycle 12/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:48,523 - [NOTICE] simulation.solve(884): Cycle 12/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:48,543 - [NOTICE] simulation.solve(884): Cycle 12/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:48,562 - [NOTICE] simulation.solve(884): Cycle 12/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:48,599 - [NOTICE] simulation.solve(972): Capacity is now 3.783 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:48,599 - [NOTICE] simulation.solve(850): Cycle 13/500 (1.369 s elapsed) --------------------\n", + "2021-11-19 15:28:48,600 - [NOTICE] simulation.solve(884): Cycle 13/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:48,619 - [NOTICE] simulation.solve(884): Cycle 13/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:48,639 - [NOTICE] simulation.solve(884): Cycle 13/500, step 3/4: Charge at 1C until 4.2V\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:34,481 - [NOTICE] simulation.solve(843): Cycle 13/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:34,516 - [NOTICE] simulation.solve(921): Capacity is now 3.784 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:34,517 - [NOTICE] simulation.solve(809): Cycle 14/500 (1.613 s elapsed) --------------------\n", - "2021-09-17 01:13:34,517 - [NOTICE] simulation.solve(843): Cycle 14/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:34,542 - [NOTICE] simulation.solve(843): Cycle 14/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:34,566 - [NOTICE] simulation.solve(843): Cycle 14/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:34,589 - [NOTICE] simulation.solve(843): Cycle 14/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:34,625 - [NOTICE] simulation.solve(921): Capacity is now 3.772 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:34,625 - [NOTICE] simulation.solve(809): Cycle 15/500 (1.722 s elapsed) --------------------\n", - "2021-09-17 01:13:34,625 - [NOTICE] simulation.solve(843): Cycle 15/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:34,650 - [NOTICE] simulation.solve(843): Cycle 15/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:34,678 - [NOTICE] simulation.solve(843): Cycle 15/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:34,704 - [NOTICE] simulation.solve(843): Cycle 15/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:34,733 - [NOTICE] simulation.solve(921): Capacity is now 3.759 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:34,733 - [NOTICE] simulation.solve(809): Cycle 16/500 (1.836 s elapsed) --------------------\n", - "2021-09-17 01:13:34,733 - [NOTICE] simulation.solve(843): Cycle 16/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:34,769 - [NOTICE] simulation.solve(843): Cycle 16/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:34,794 - [NOTICE] simulation.solve(843): Cycle 16/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:34,819 - [NOTICE] simulation.solve(843): Cycle 16/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:34,850 - [NOTICE] simulation.solve(921): Capacity is now 3.747 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:34,850 - [NOTICE] simulation.solve(809): Cycle 17/500 (1.949 s elapsed) --------------------\n", - "2021-09-17 01:13:34,850 - [NOTICE] simulation.solve(843): Cycle 17/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:34,880 - [NOTICE] simulation.solve(843): Cycle 17/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:34,909 - [NOTICE] simulation.solve(843): Cycle 17/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:34,930 - [NOTICE] simulation.solve(843): Cycle 17/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:34,965 - [NOTICE] simulation.solve(921): Capacity is now 3.734 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:34,966 - [NOTICE] simulation.solve(809): Cycle 18/500 (2.061 s elapsed) --------------------\n", - "2021-09-17 01:13:34,966 - [NOTICE] simulation.solve(843): Cycle 18/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:34,993 - [NOTICE] simulation.solve(843): Cycle 18/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:35,017 - [NOTICE] simulation.solve(843): Cycle 18/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:35,038 - [NOTICE] simulation.solve(843): Cycle 18/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:35,067 - [NOTICE] simulation.solve(921): Capacity is now 3.722 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:35,067 - [NOTICE] simulation.solve(809): Cycle 19/500 (2.168 s elapsed) --------------------\n", - "2021-09-17 01:13:35,067 - [NOTICE] simulation.solve(843): Cycle 19/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:35,095 - [NOTICE] simulation.solve(843): Cycle 19/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:35,122 - [NOTICE] simulation.solve(843): Cycle 19/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:35,134 - [NOTICE] simulation.solve(843): Cycle 19/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:35,175 - [NOTICE] simulation.solve(921): Capacity is now 3.710 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:35,175 - [NOTICE] simulation.solve(809): Cycle 20/500 (2.274 s elapsed) --------------------\n", - "2021-09-17 01:13:35,180 - [NOTICE] simulation.solve(843): Cycle 20/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:35,208 - [NOTICE] simulation.solve(843): Cycle 20/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:35,233 - [NOTICE] simulation.solve(843): Cycle 20/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:35,253 - [NOTICE] simulation.solve(843): Cycle 20/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:35,284 - [NOTICE] simulation.solve(921): Capacity is now 3.697 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:35,284 - [NOTICE] simulation.solve(809): Cycle 21/500 (2.383 s elapsed) --------------------\n", - "2021-09-17 01:13:35,284 - [NOTICE] simulation.solve(843): Cycle 21/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:35,313 - [NOTICE] simulation.solve(843): Cycle 21/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:35,338 - [NOTICE] simulation.solve(843): Cycle 21/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:35,359 - [NOTICE] simulation.solve(843): Cycle 21/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:35,393 - [NOTICE] simulation.solve(921): Capacity is now 3.685 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:35,394 - [NOTICE] simulation.solve(809): Cycle 22/500 (2.490 s elapsed) --------------------\n", - "2021-09-17 01:13:35,395 - [NOTICE] simulation.solve(843): Cycle 22/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:35,421 - [NOTICE] simulation.solve(843): Cycle 22/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:35,444 - [NOTICE] simulation.solve(843): Cycle 22/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:35,461 - [NOTICE] simulation.solve(843): Cycle 22/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:35,499 - [NOTICE] simulation.solve(921): Capacity is now 3.673 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:35,500 - [NOTICE] simulation.solve(809): Cycle 23/500 (2.596 s elapsed) --------------------\n", - "2021-09-17 01:13:35,500 - [NOTICE] simulation.solve(843): Cycle 23/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:35,528 - [NOTICE] simulation.solve(843): Cycle 23/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:35,551 - [NOTICE] simulation.solve(843): Cycle 23/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:35,572 - [NOTICE] simulation.solve(843): Cycle 23/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:35,600 - [NOTICE] simulation.solve(921): Capacity is now 3.662 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:35,600 - [NOTICE] simulation.solve(809): Cycle 24/500 (2.706 s elapsed) --------------------\n", - "2021-09-17 01:13:35,600 - [NOTICE] simulation.solve(843): Cycle 24/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:35,635 - [NOTICE] simulation.solve(843): Cycle 24/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:35,659 - [NOTICE] simulation.solve(843): Cycle 24/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:35,681 - [NOTICE] simulation.solve(843): Cycle 24/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:35,708 - [NOTICE] simulation.solve(921): Capacity is now 3.650 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:35,708 - [NOTICE] simulation.solve(809): Cycle 25/500 (2.810 s elapsed) --------------------\n", - "2021-09-17 01:13:35,708 - [NOTICE] simulation.solve(843): Cycle 25/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:35,738 - [NOTICE] simulation.solve(843): Cycle 25/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:35,761 - [NOTICE] simulation.solve(843): Cycle 25/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:35,785 - [NOTICE] simulation.solve(843): Cycle 25/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:35,808 - [NOTICE] simulation.solve(921): Capacity is now 3.638 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:35,808 - [NOTICE] simulation.solve(809): Cycle 26/500 (2.915 s elapsed) --------------------\n" + "2021-11-19 15:28:48,661 - [NOTICE] simulation.solve(884): Cycle 13/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:48,695 - [NOTICE] simulation.solve(972): Capacity is now 3.769 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:48,696 - [NOTICE] simulation.solve(850): Cycle 14/500 (1.466 s elapsed) --------------------\n", + "2021-11-19 15:28:48,696 - [NOTICE] simulation.solve(884): Cycle 14/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:48,714 - [NOTICE] simulation.solve(884): Cycle 14/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:48,733 - [NOTICE] simulation.solve(884): Cycle 14/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:48,751 - [NOTICE] simulation.solve(884): Cycle 14/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:48,785 - [NOTICE] simulation.solve(972): Capacity is now 3.755 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:48,785 - [NOTICE] simulation.solve(850): Cycle 15/500 (1.555 s elapsed) --------------------\n", + "2021-11-19 15:28:48,785 - [NOTICE] simulation.solve(884): Cycle 15/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:48,805 - [NOTICE] simulation.solve(884): Cycle 15/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:48,823 - [NOTICE] simulation.solve(884): Cycle 15/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:48,841 - [NOTICE] simulation.solve(884): Cycle 15/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:48,874 - [NOTICE] simulation.solve(972): Capacity is now 3.741 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:48,875 - [NOTICE] simulation.solve(850): Cycle 16/500 (1.645 s elapsed) --------------------\n", + "2021-11-19 15:28:48,875 - [NOTICE] simulation.solve(884): Cycle 16/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:48,894 - [NOTICE] simulation.solve(884): Cycle 16/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:48,912 - [NOTICE] simulation.solve(884): Cycle 16/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:48,928 - [NOTICE] simulation.solve(884): Cycle 16/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:48,961 - [NOTICE] simulation.solve(972): Capacity is now 3.727 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:48,962 - [NOTICE] simulation.solve(850): Cycle 17/500 (1.732 s elapsed) --------------------\n", + "2021-11-19 15:28:48,962 - [NOTICE] simulation.solve(884): Cycle 17/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:48,982 - [NOTICE] simulation.solve(884): Cycle 17/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:49,002 - [NOTICE] simulation.solve(884): Cycle 17/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:49,019 - [NOTICE] simulation.solve(884): Cycle 17/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:49,052 - [NOTICE] simulation.solve(972): Capacity is now 3.713 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:49,053 - [NOTICE] simulation.solve(850): Cycle 18/500 (1.823 s elapsed) --------------------\n", + "2021-11-19 15:28:49,053 - [NOTICE] simulation.solve(884): Cycle 18/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:49,073 - [NOTICE] simulation.solve(884): Cycle 18/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:49,091 - [NOTICE] simulation.solve(884): Cycle 18/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:49,107 - [NOTICE] simulation.solve(884): Cycle 18/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:49,139 - [NOTICE] simulation.solve(972): Capacity is now 3.700 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:49,139 - [NOTICE] simulation.solve(850): Cycle 19/500 (1.910 s elapsed) --------------------\n", + "2021-11-19 15:28:49,140 - [NOTICE] simulation.solve(884): Cycle 19/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:49,160 - [NOTICE] simulation.solve(884): Cycle 19/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:49,178 - [NOTICE] simulation.solve(884): Cycle 19/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:49,194 - [NOTICE] simulation.solve(884): Cycle 19/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:49,226 - [NOTICE] simulation.solve(972): Capacity is now 3.686 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:49,226 - [NOTICE] simulation.solve(850): Cycle 20/500 (1.996 s elapsed) --------------------\n", + "2021-11-19 15:28:49,226 - [NOTICE] simulation.solve(884): Cycle 20/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:49,246 - [NOTICE] simulation.solve(884): Cycle 20/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:49,264 - [NOTICE] simulation.solve(884): Cycle 20/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:49,279 - [NOTICE] simulation.solve(884): Cycle 20/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:49,310 - [NOTICE] simulation.solve(972): Capacity is now 3.673 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:49,310 - [NOTICE] simulation.solve(850): Cycle 21/500 (2.080 s elapsed) --------------------\n", + "2021-11-19 15:28:49,310 - [NOTICE] simulation.solve(884): Cycle 21/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:49,329 - [NOTICE] simulation.solve(884): Cycle 21/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:49,346 - [NOTICE] simulation.solve(884): Cycle 21/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:49,362 - [NOTICE] simulation.solve(884): Cycle 21/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:49,392 - [NOTICE] simulation.solve(972): Capacity is now 3.660 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:49,393 - [NOTICE] simulation.solve(850): Cycle 22/500 (2.163 s elapsed) --------------------\n", + "2021-11-19 15:28:49,393 - [NOTICE] simulation.solve(884): Cycle 22/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:49,410 - [NOTICE] simulation.solve(884): Cycle 22/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:49,428 - [NOTICE] simulation.solve(884): Cycle 22/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:49,445 - [NOTICE] simulation.solve(884): Cycle 22/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:49,477 - [NOTICE] simulation.solve(972): Capacity is now 3.646 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:49,477 - [NOTICE] simulation.solve(850): Cycle 23/500 (2.247 s elapsed) --------------------\n", + "2021-11-19 15:28:49,477 - [NOTICE] simulation.solve(884): Cycle 23/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:49,494 - [NOTICE] simulation.solve(884): Cycle 23/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:49,512 - [NOTICE] simulation.solve(884): Cycle 23/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:49,529 - [NOTICE] simulation.solve(884): Cycle 23/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:49,560 - [NOTICE] simulation.solve(972): Capacity is now 3.633 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:49,560 - [NOTICE] simulation.solve(850): Cycle 24/500 (2.330 s elapsed) --------------------\n", + "2021-11-19 15:28:49,561 - [NOTICE] simulation.solve(884): Cycle 24/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:49,578 - [NOTICE] simulation.solve(884): Cycle 24/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:49,595 - [NOTICE] simulation.solve(884): Cycle 24/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:49,613 - [NOTICE] simulation.solve(884): Cycle 24/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:49,646 - [NOTICE] simulation.solve(972): Capacity is now 3.620 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:49,646 - [NOTICE] simulation.solve(850): Cycle 25/500 (2.416 s elapsed) --------------------\n", + "2021-11-19 15:28:49,646 - [NOTICE] simulation.solve(884): Cycle 25/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:49,664 - [NOTICE] simulation.solve(884): Cycle 25/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:49,682 - [NOTICE] simulation.solve(884): Cycle 25/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:49,699 - [NOTICE] simulation.solve(884): Cycle 25/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:49,732 - [NOTICE] simulation.solve(972): Capacity is now 3.607 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:49,733 - [NOTICE] simulation.solve(850): Cycle 26/500 (2.503 s elapsed) --------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:35,808 - [NOTICE] simulation.solve(843): Cycle 26/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:35,844 - [NOTICE] simulation.solve(843): Cycle 26/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:35,868 - [NOTICE] simulation.solve(843): Cycle 26/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:35,891 - [NOTICE] simulation.solve(843): Cycle 26/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:35,924 - [NOTICE] simulation.solve(921): Capacity is now 3.626 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:35,925 - [NOTICE] simulation.solve(809): Cycle 27/500 (3.020 s elapsed) --------------------\n", - "2021-09-17 01:13:35,925 - [NOTICE] simulation.solve(843): Cycle 27/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:35,949 - [NOTICE] simulation.solve(843): Cycle 27/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:35,962 - [NOTICE] simulation.solve(843): Cycle 27/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:35,995 - [NOTICE] simulation.solve(843): Cycle 27/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:36,026 - [NOTICE] simulation.solve(921): Capacity is now 3.615 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:36,026 - [NOTICE] simulation.solve(809): Cycle 28/500 (3.124 s elapsed) --------------------\n", - "2021-09-17 01:13:36,031 - [NOTICE] simulation.solve(843): Cycle 28/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:36,054 - [NOTICE] simulation.solve(843): Cycle 28/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:36,068 - [NOTICE] simulation.solve(843): Cycle 28/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:36,100 - [NOTICE] simulation.solve(843): Cycle 28/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:36,134 - [NOTICE] simulation.solve(921): Capacity is now 3.603 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:36,135 - [NOTICE] simulation.solve(809): Cycle 29/500 (3.230 s elapsed) --------------------\n", - "2021-09-17 01:13:36,136 - [NOTICE] simulation.solve(843): Cycle 29/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:36,158 - [NOTICE] simulation.solve(843): Cycle 29/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:36,182 - [NOTICE] simulation.solve(843): Cycle 29/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:36,205 - [NOTICE] simulation.solve(843): Cycle 29/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:36,234 - [NOTICE] simulation.solve(921): Capacity is now 3.592 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:36,234 - [NOTICE] simulation.solve(809): Cycle 30/500 (3.335 s elapsed) --------------------\n", - "2021-09-17 01:13:36,234 - [NOTICE] simulation.solve(843): Cycle 30/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:36,263 - [NOTICE] simulation.solve(843): Cycle 30/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:36,288 - [NOTICE] simulation.solve(843): Cycle 30/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:36,307 - [NOTICE] simulation.solve(843): Cycle 30/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:36,344 - [NOTICE] simulation.solve(921): Capacity is now 3.581 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:36,345 - [NOTICE] simulation.solve(809): Cycle 31/500 (3.440 s elapsed) --------------------\n", - "2021-09-17 01:13:36,346 - [NOTICE] simulation.solve(843): Cycle 31/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:36,371 - [NOTICE] simulation.solve(843): Cycle 31/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:36,396 - [NOTICE] simulation.solve(843): Cycle 31/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:36,418 - [NOTICE] simulation.solve(843): Cycle 31/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:36,450 - [NOTICE] simulation.solve(921): Capacity is now 3.569 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:36,450 - [NOTICE] simulation.solve(809): Cycle 32/500 (3.550 s elapsed) --------------------\n", - "2021-09-17 01:13:36,450 - [NOTICE] simulation.solve(843): Cycle 32/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:36,482 - [NOTICE] simulation.solve(843): Cycle 32/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:36,506 - [NOTICE] simulation.solve(843): Cycle 32/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:36,526 - [NOTICE] simulation.solve(843): Cycle 32/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:36,561 - [NOTICE] simulation.solve(921): Capacity is now 3.558 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:36,561 - [NOTICE] simulation.solve(809): Cycle 33/500 (3.657 s elapsed) --------------------\n", - "2021-09-17 01:13:36,562 - [NOTICE] simulation.solve(843): Cycle 33/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:36,587 - [NOTICE] simulation.solve(843): Cycle 33/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:36,611 - [NOTICE] simulation.solve(843): Cycle 33/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:36,631 - [NOTICE] simulation.solve(843): Cycle 33/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:36,664 - [NOTICE] simulation.solve(921): Capacity is now 3.547 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:36,666 - [NOTICE] simulation.solve(809): Cycle 34/500 (3.761 s elapsed) --------------------\n", - "2021-09-17 01:13:36,666 - [NOTICE] simulation.solve(843): Cycle 34/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:36,692 - [NOTICE] simulation.solve(843): Cycle 34/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:36,716 - [NOTICE] simulation.solve(843): Cycle 34/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:36,736 - [NOTICE] simulation.solve(843): Cycle 34/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:36,764 - [NOTICE] simulation.solve(921): Capacity is now 3.536 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:36,764 - [NOTICE] simulation.solve(809): Cycle 35/500 (3.866 s elapsed) --------------------\n", - "2021-09-17 01:13:36,764 - [NOTICE] simulation.solve(843): Cycle 35/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:36,798 - [NOTICE] simulation.solve(843): Cycle 35/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:36,823 - [NOTICE] simulation.solve(843): Cycle 35/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:36,843 - [NOTICE] simulation.solve(843): Cycle 35/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:36,867 - [NOTICE] simulation.solve(921): Capacity is now 3.525 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:36,867 - [NOTICE] simulation.solve(809): Cycle 36/500 (3.973 s elapsed) --------------------\n", - "2021-09-17 01:13:36,867 - [NOTICE] simulation.solve(843): Cycle 36/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:36,906 - [NOTICE] simulation.solve(843): Cycle 36/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:36,924 - [NOTICE] simulation.solve(843): Cycle 36/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:36,951 - [NOTICE] simulation.solve(843): Cycle 36/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:36,975 - [NOTICE] simulation.solve(921): Capacity is now 3.514 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:36,975 - [NOTICE] simulation.solve(809): Cycle 37/500 (4.080 s elapsed) --------------------\n", - "2021-09-17 01:13:36,975 - [NOTICE] simulation.solve(843): Cycle 37/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:37,006 - [NOTICE] simulation.solve(843): Cycle 37/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:37,022 - [NOTICE] simulation.solve(843): Cycle 37/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:37,037 - [NOTICE] simulation.solve(843): Cycle 37/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:37,081 - [NOTICE] simulation.solve(921): Capacity is now 3.503 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:37,081 - [NOTICE] simulation.solve(809): Cycle 38/500 (4.180 s elapsed) --------------------\n", - "2021-09-17 01:13:37,081 - [NOTICE] simulation.solve(843): Cycle 38/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:37,096 - [NOTICE] simulation.solve(843): Cycle 38/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:37,127 - [NOTICE] simulation.solve(843): Cycle 38/500, step 3/4: Charge at 1C until 4.2V\n" + "2021-11-19 15:28:49,733 - [NOTICE] simulation.solve(884): Cycle 26/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:49,751 - [NOTICE] simulation.solve(884): Cycle 26/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:49,771 - [NOTICE] simulation.solve(884): Cycle 26/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:49,790 - [NOTICE] simulation.solve(884): Cycle 26/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:49,821 - [NOTICE] simulation.solve(972): Capacity is now 3.595 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:49,822 - [NOTICE] simulation.solve(850): Cycle 27/500 (2.592 s elapsed) --------------------\n", + "2021-11-19 15:28:49,822 - [NOTICE] simulation.solve(884): Cycle 27/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:49,839 - [NOTICE] simulation.solve(884): Cycle 27/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:49,857 - [NOTICE] simulation.solve(884): Cycle 27/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:49,874 - [NOTICE] simulation.solve(884): Cycle 27/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:49,905 - [NOTICE] simulation.solve(972): Capacity is now 3.582 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:49,905 - [NOTICE] simulation.solve(850): Cycle 28/500 (2.676 s elapsed) --------------------\n", + "2021-11-19 15:28:49,906 - [NOTICE] simulation.solve(884): Cycle 28/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:49,924 - [NOTICE] simulation.solve(884): Cycle 28/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:49,942 - [NOTICE] simulation.solve(884): Cycle 28/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:49,959 - [NOTICE] simulation.solve(884): Cycle 28/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:49,990 - [NOTICE] simulation.solve(972): Capacity is now 3.569 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:49,991 - [NOTICE] simulation.solve(850): Cycle 29/500 (2.761 s elapsed) --------------------\n", + "2021-11-19 15:28:49,991 - [NOTICE] simulation.solve(884): Cycle 29/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:50,010 - [NOTICE] simulation.solve(884): Cycle 29/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:50,028 - [NOTICE] simulation.solve(884): Cycle 29/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:50,043 - [NOTICE] simulation.solve(884): Cycle 29/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:50,074 - [NOTICE] simulation.solve(972): Capacity is now 3.557 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:50,075 - [NOTICE] simulation.solve(850): Cycle 30/500 (2.845 s elapsed) --------------------\n", + "2021-11-19 15:28:50,075 - [NOTICE] simulation.solve(884): Cycle 30/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:50,094 - [NOTICE] simulation.solve(884): Cycle 30/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:50,112 - [NOTICE] simulation.solve(884): Cycle 30/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:50,127 - [NOTICE] simulation.solve(884): Cycle 30/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:50,158 - [NOTICE] simulation.solve(972): Capacity is now 3.544 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:50,158 - [NOTICE] simulation.solve(850): Cycle 31/500 (2.929 s elapsed) --------------------\n", + "2021-11-19 15:28:50,159 - [NOTICE] simulation.solve(884): Cycle 31/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:50,178 - [NOTICE] simulation.solve(884): Cycle 31/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:50,195 - [NOTICE] simulation.solve(884): Cycle 31/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:50,210 - [NOTICE] simulation.solve(884): Cycle 31/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:50,241 - [NOTICE] simulation.solve(972): Capacity is now 3.532 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:50,242 - [NOTICE] simulation.solve(850): Cycle 32/500 (3.012 s elapsed) --------------------\n", + "2021-11-19 15:28:50,242 - [NOTICE] simulation.solve(884): Cycle 32/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:50,262 - [NOTICE] simulation.solve(884): Cycle 32/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:50,281 - [NOTICE] simulation.solve(884): Cycle 32/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:50,296 - [NOTICE] simulation.solve(884): Cycle 32/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:50,328 - [NOTICE] simulation.solve(972): Capacity is now 3.519 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:50,328 - [NOTICE] simulation.solve(850): Cycle 33/500 (3.099 s elapsed) --------------------\n", + "2021-11-19 15:28:50,329 - [NOTICE] simulation.solve(884): Cycle 33/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:50,348 - [NOTICE] simulation.solve(884): Cycle 33/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:50,366 - [NOTICE] simulation.solve(884): Cycle 33/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:50,382 - [NOTICE] simulation.solve(884): Cycle 33/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:50,413 - [NOTICE] simulation.solve(972): Capacity is now 3.507 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:50,414 - [NOTICE] simulation.solve(850): Cycle 34/500 (3.184 s elapsed) --------------------\n", + "2021-11-19 15:28:50,415 - [NOTICE] simulation.solve(884): Cycle 34/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:50,432 - [NOTICE] simulation.solve(884): Cycle 34/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:50,450 - [NOTICE] simulation.solve(884): Cycle 34/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:50,468 - [NOTICE] simulation.solve(884): Cycle 34/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:50,498 - [NOTICE] simulation.solve(972): Capacity is now 3.495 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:50,499 - [NOTICE] simulation.solve(850): Cycle 35/500 (3.269 s elapsed) --------------------\n", + "2021-11-19 15:28:50,499 - [NOTICE] simulation.solve(884): Cycle 35/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:50,515 - [NOTICE] simulation.solve(884): Cycle 35/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:50,533 - [NOTICE] simulation.solve(884): Cycle 35/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:50,549 - [NOTICE] simulation.solve(884): Cycle 35/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:50,580 - [NOTICE] simulation.solve(972): Capacity is now 3.483 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:50,581 - [NOTICE] simulation.solve(850): Cycle 36/500 (3.351 s elapsed) --------------------\n", + "2021-11-19 15:28:50,581 - [NOTICE] simulation.solve(884): Cycle 36/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:50,599 - [NOTICE] simulation.solve(884): Cycle 36/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:50,617 - [NOTICE] simulation.solve(884): Cycle 36/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:50,635 - [NOTICE] simulation.solve(884): Cycle 36/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:50,669 - [NOTICE] simulation.solve(972): Capacity is now 3.471 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:50,670 - [NOTICE] simulation.solve(850): Cycle 37/500 (3.440 s elapsed) --------------------\n", + "2021-11-19 15:28:50,670 - [NOTICE] simulation.solve(884): Cycle 37/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:50,687 - [NOTICE] simulation.solve(884): Cycle 37/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:50,706 - [NOTICE] simulation.solve(884): Cycle 37/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:50,725 - [NOTICE] simulation.solve(884): Cycle 37/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:50,759 - [NOTICE] simulation.solve(972): Capacity is now 3.459 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:50,760 - [NOTICE] simulation.solve(850): Cycle 38/500 (3.530 s elapsed) --------------------\n", + "2021-11-19 15:28:50,760 - [NOTICE] simulation.solve(884): Cycle 38/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:50,778 - [NOTICE] simulation.solve(884): Cycle 38/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:50,796 - [NOTICE] simulation.solve(884): Cycle 38/500, step 3/4: Charge at 1C until 4.2V\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:37,143 - [NOTICE] simulation.solve(843): Cycle 38/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:37,181 - [NOTICE] simulation.solve(921): Capacity is now 3.492 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:37,181 - [NOTICE] simulation.solve(809): Cycle 39/500 (4.279 s elapsed) --------------------\n", - "2021-09-17 01:13:37,181 - [NOTICE] simulation.solve(843): Cycle 39/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:37,196 - [NOTICE] simulation.solve(843): Cycle 39/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:37,228 - [NOTICE] simulation.solve(843): Cycle 39/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:37,243 - [NOTICE] simulation.solve(843): Cycle 39/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:37,283 - [NOTICE] simulation.solve(921): Capacity is now 3.482 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:37,283 - [NOTICE] simulation.solve(809): Cycle 40/500 (4.381 s elapsed) --------------------\n", - "2021-09-17 01:13:37,283 - [NOTICE] simulation.solve(843): Cycle 40/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:37,295 - [NOTICE] simulation.solve(843): Cycle 40/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:37,329 - [NOTICE] simulation.solve(843): Cycle 40/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:37,352 - [NOTICE] simulation.solve(843): Cycle 40/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:37,390 - [NOTICE] simulation.solve(921): Capacity is now 3.471 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:37,390 - [NOTICE] simulation.solve(809): Cycle 41/500 (4.490 s elapsed) --------------------\n", - "2021-09-17 01:13:37,390 - [NOTICE] simulation.solve(843): Cycle 41/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:37,415 - [NOTICE] simulation.solve(843): Cycle 41/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:37,442 - [NOTICE] simulation.solve(843): Cycle 41/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:37,466 - [NOTICE] simulation.solve(843): Cycle 41/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:37,492 - [NOTICE] simulation.solve(921): Capacity is now 3.460 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:37,492 - [NOTICE] simulation.solve(809): Cycle 42/500 (4.598 s elapsed) --------------------\n", - "2021-09-17 01:13:37,492 - [NOTICE] simulation.solve(843): Cycle 42/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:37,523 - [NOTICE] simulation.solve(843): Cycle 42/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:37,544 - [NOTICE] simulation.solve(843): Cycle 42/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:37,566 - [NOTICE] simulation.solve(843): Cycle 42/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:37,604 - [NOTICE] simulation.solve(921): Capacity is now 3.450 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:37,605 - [NOTICE] simulation.solve(809): Cycle 43/500 (4.699 s elapsed) --------------------\n", - "2021-09-17 01:13:37,605 - [NOTICE] simulation.solve(843): Cycle 43/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:37,616 - [NOTICE] simulation.solve(843): Cycle 43/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:37,647 - [NOTICE] simulation.solve(843): Cycle 43/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:37,666 - [NOTICE] simulation.solve(843): Cycle 43/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:37,693 - [NOTICE] simulation.solve(921): Capacity is now 3.439 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:37,693 - [NOTICE] simulation.solve(809): Cycle 44/500 (4.803 s elapsed) --------------------\n", - "2021-09-17 01:13:37,693 - [NOTICE] simulation.solve(843): Cycle 44/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:37,728 - [NOTICE] simulation.solve(843): Cycle 44/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:37,750 - [NOTICE] simulation.solve(843): Cycle 44/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:37,766 - [NOTICE] simulation.solve(843): Cycle 44/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:37,803 - [NOTICE] simulation.solve(921): Capacity is now 3.429 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:37,803 - [NOTICE] simulation.solve(809): Cycle 45/500 (4.908 s elapsed) --------------------\n", - "2021-09-17 01:13:37,803 - [NOTICE] simulation.solve(843): Cycle 45/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:37,832 - [NOTICE] simulation.solve(843): Cycle 45/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:37,855 - [NOTICE] simulation.solve(843): Cycle 45/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:37,867 - [NOTICE] simulation.solve(843): Cycle 45/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:37,905 - [NOTICE] simulation.solve(921): Capacity is now 3.419 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:37,905 - [NOTICE] simulation.solve(809): Cycle 46/500 (5.011 s elapsed) --------------------\n", - "2021-09-17 01:13:37,905 - [NOTICE] simulation.solve(843): Cycle 46/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:37,936 - [NOTICE] simulation.solve(843): Cycle 46/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:37,961 - [NOTICE] simulation.solve(843): Cycle 46/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:37,967 - [NOTICE] simulation.solve(843): Cycle 46/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:38,001 - [NOTICE] simulation.solve(921): Capacity is now 3.408 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:38,001 - [NOTICE] simulation.solve(809): Cycle 47/500 (5.111 s elapsed) --------------------\n", - "2021-09-17 01:13:38,017 - [NOTICE] simulation.solve(843): Cycle 47/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:38,037 - [NOTICE] simulation.solve(843): Cycle 47/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:38,056 - [NOTICE] simulation.solve(843): Cycle 47/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:38,068 - [NOTICE] simulation.solve(843): Cycle 47/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:38,116 - [NOTICE] simulation.solve(921): Capacity is now 3.398 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:38,116 - [NOTICE] simulation.solve(809): Cycle 48/500 (5.214 s elapsed) --------------------\n", - "2021-09-17 01:13:38,116 - [NOTICE] simulation.solve(843): Cycle 48/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:38,133 - [NOTICE] simulation.solve(843): Cycle 48/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:38,164 - [NOTICE] simulation.solve(843): Cycle 48/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:38,171 - [NOTICE] simulation.solve(843): Cycle 48/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:38,224 - [NOTICE] simulation.solve(921): Capacity is now 3.388 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:38,225 - [NOTICE] simulation.solve(809): Cycle 49/500 (5.320 s elapsed) --------------------\n", - "2021-09-17 01:13:38,226 - [NOTICE] simulation.solve(843): Cycle 49/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:38,250 - [NOTICE] simulation.solve(843): Cycle 49/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:38,273 - [NOTICE] simulation.solve(843): Cycle 49/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:38,292 - [NOTICE] simulation.solve(843): Cycle 49/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:38,332 - [NOTICE] simulation.solve(921): Capacity is now 3.378 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:38,333 - [NOTICE] simulation.solve(809): Cycle 50/500 (5.429 s elapsed) --------------------\n", - "2021-09-17 01:13:38,334 - [NOTICE] simulation.solve(843): Cycle 50/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:38,358 - [NOTICE] simulation.solve(843): Cycle 50/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:38,367 - [NOTICE] simulation.solve(843): Cycle 50/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:38,401 - [NOTICE] simulation.solve(843): Cycle 50/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:38,437 - [NOTICE] simulation.solve(921): Capacity is now 3.368 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:38,438 - [NOTICE] simulation.solve(809): Cycle 51/500 (5.534 s elapsed) --------------------\n" + "2021-11-19 15:28:50,814 - [NOTICE] simulation.solve(884): Cycle 38/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:50,848 - [NOTICE] simulation.solve(972): Capacity is now 3.447 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:50,848 - [NOTICE] simulation.solve(850): Cycle 39/500 (3.619 s elapsed) --------------------\n", + "2021-11-19 15:28:50,849 - [NOTICE] simulation.solve(884): Cycle 39/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:50,867 - [NOTICE] simulation.solve(884): Cycle 39/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:50,886 - [NOTICE] simulation.solve(884): Cycle 39/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:50,905 - [NOTICE] simulation.solve(884): Cycle 39/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:50,940 - [NOTICE] simulation.solve(972): Capacity is now 3.436 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:50,941 - [NOTICE] simulation.solve(850): Cycle 40/500 (3.711 s elapsed) --------------------\n", + "2021-11-19 15:28:50,941 - [NOTICE] simulation.solve(884): Cycle 40/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:50,959 - [NOTICE] simulation.solve(884): Cycle 40/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:50,977 - [NOTICE] simulation.solve(884): Cycle 40/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:50,995 - [NOTICE] simulation.solve(884): Cycle 40/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:51,027 - [NOTICE] simulation.solve(972): Capacity is now 3.424 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:51,027 - [NOTICE] simulation.solve(850): Cycle 41/500 (3.797 s elapsed) --------------------\n", + "2021-11-19 15:28:51,027 - [NOTICE] simulation.solve(884): Cycle 41/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:51,046 - [NOTICE] simulation.solve(884): Cycle 41/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:51,064 - [NOTICE] simulation.solve(884): Cycle 41/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:51,079 - [NOTICE] simulation.solve(884): Cycle 41/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:51,110 - [NOTICE] simulation.solve(972): Capacity is now 3.412 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:51,110 - [NOTICE] simulation.solve(850): Cycle 42/500 (3.880 s elapsed) --------------------\n", + "2021-11-19 15:28:51,110 - [NOTICE] simulation.solve(884): Cycle 42/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:51,129 - [NOTICE] simulation.solve(884): Cycle 42/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:51,147 - [NOTICE] simulation.solve(884): Cycle 42/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:51,161 - [NOTICE] simulation.solve(884): Cycle 42/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:51,192 - [NOTICE] simulation.solve(972): Capacity is now 3.401 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:51,193 - [NOTICE] simulation.solve(850): Cycle 43/500 (3.963 s elapsed) --------------------\n", + "2021-11-19 15:28:51,193 - [NOTICE] simulation.solve(884): Cycle 43/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:51,211 - [NOTICE] simulation.solve(884): Cycle 43/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:51,229 - [NOTICE] simulation.solve(884): Cycle 43/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:51,245 - [NOTICE] simulation.solve(884): Cycle 43/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:51,276 - [NOTICE] simulation.solve(972): Capacity is now 3.389 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:51,277 - [NOTICE] simulation.solve(850): Cycle 44/500 (4.047 s elapsed) --------------------\n", + "2021-11-19 15:28:51,277 - [NOTICE] simulation.solve(884): Cycle 44/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:51,295 - [NOTICE] simulation.solve(884): Cycle 44/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:51,313 - [NOTICE] simulation.solve(884): Cycle 44/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:51,327 - [NOTICE] simulation.solve(884): Cycle 44/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:51,358 - [NOTICE] simulation.solve(972): Capacity is now 3.378 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:51,358 - [NOTICE] simulation.solve(850): Cycle 45/500 (4.129 s elapsed) --------------------\n", + "2021-11-19 15:28:51,359 - [NOTICE] simulation.solve(884): Cycle 45/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:51,377 - [NOTICE] simulation.solve(884): Cycle 45/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:51,394 - [NOTICE] simulation.solve(884): Cycle 45/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:51,409 - [NOTICE] simulation.solve(884): Cycle 45/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:51,440 - [NOTICE] simulation.solve(972): Capacity is now 3.367 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:51,440 - [NOTICE] simulation.solve(850): Cycle 46/500 (4.211 s elapsed) --------------------\n", + "2021-11-19 15:28:51,441 - [NOTICE] simulation.solve(884): Cycle 46/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:51,459 - [NOTICE] simulation.solve(884): Cycle 46/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:51,477 - [NOTICE] simulation.solve(884): Cycle 46/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:51,491 - [NOTICE] simulation.solve(884): Cycle 46/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:51,522 - [NOTICE] simulation.solve(972): Capacity is now 3.355 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:51,522 - [NOTICE] simulation.solve(850): Cycle 47/500 (4.292 s elapsed) --------------------\n", + "2021-11-19 15:28:51,522 - [NOTICE] simulation.solve(884): Cycle 47/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:51,540 - [NOTICE] simulation.solve(884): Cycle 47/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:51,559 - [NOTICE] simulation.solve(884): Cycle 47/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:51,574 - [NOTICE] simulation.solve(884): Cycle 47/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:51,604 - [NOTICE] simulation.solve(972): Capacity is now 3.344 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:51,605 - [NOTICE] simulation.solve(850): Cycle 48/500 (4.375 s elapsed) --------------------\n", + "2021-11-19 15:28:51,605 - [NOTICE] simulation.solve(884): Cycle 48/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:51,623 - [NOTICE] simulation.solve(884): Cycle 48/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:51,641 - [NOTICE] simulation.solve(884): Cycle 48/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:51,655 - [NOTICE] simulation.solve(884): Cycle 48/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:51,686 - [NOTICE] simulation.solve(972): Capacity is now 3.333 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:51,686 - [NOTICE] simulation.solve(850): Cycle 49/500 (4.457 s elapsed) --------------------\n", + "2021-11-19 15:28:51,687 - [NOTICE] simulation.solve(884): Cycle 49/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:51,702 - [NOTICE] simulation.solve(884): Cycle 49/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:51,720 - [NOTICE] simulation.solve(884): Cycle 49/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:51,736 - [NOTICE] simulation.solve(884): Cycle 49/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:51,767 - [NOTICE] simulation.solve(972): Capacity is now 3.322 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:51,767 - [NOTICE] simulation.solve(850): Cycle 50/500 (4.538 s elapsed) --------------------\n", + "2021-11-19 15:28:51,768 - [NOTICE] simulation.solve(884): Cycle 50/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:51,783 - [NOTICE] simulation.solve(884): Cycle 50/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:51,800 - [NOTICE] simulation.solve(884): Cycle 50/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:51,816 - [NOTICE] simulation.solve(884): Cycle 50/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:51,847 - [NOTICE] simulation.solve(972): Capacity is now 3.311 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:51,847 - [NOTICE] simulation.solve(850): Cycle 51/500 (4.617 s elapsed) --------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:38,439 - [NOTICE] simulation.solve(843): Cycle 51/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:38,465 - [NOTICE] simulation.solve(843): Cycle 51/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:38,489 - [NOTICE] simulation.solve(843): Cycle 51/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:38,508 - [NOTICE] simulation.solve(843): Cycle 51/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:38,545 - [NOTICE] simulation.solve(921): Capacity is now 3.358 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:38,546 - [NOTICE] simulation.solve(809): Cycle 52/500 (5.641 s elapsed) --------------------\n", - "2021-09-17 01:13:38,547 - [NOTICE] simulation.solve(843): Cycle 52/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:38,571 - [NOTICE] simulation.solve(843): Cycle 52/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:38,590 - [NOTICE] simulation.solve(843): Cycle 52/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:38,615 - [NOTICE] simulation.solve(843): Cycle 52/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:38,650 - [NOTICE] simulation.solve(921): Capacity is now 3.348 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:38,650 - [NOTICE] simulation.solve(809): Cycle 53/500 (5.749 s elapsed) --------------------\n", - "2021-09-17 01:13:38,650 - [NOTICE] simulation.solve(843): Cycle 53/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:38,679 - [NOTICE] simulation.solve(843): Cycle 53/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:38,703 - [NOTICE] simulation.solve(843): Cycle 53/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:38,723 - [NOTICE] simulation.solve(843): Cycle 53/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:38,760 - [NOTICE] simulation.solve(921): Capacity is now 3.338 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:38,761 - [NOTICE] simulation.solve(809): Cycle 54/500 (5.856 s elapsed) --------------------\n", - "2021-09-17 01:13:38,762 - [NOTICE] simulation.solve(843): Cycle 54/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:38,787 - [NOTICE] simulation.solve(843): Cycle 54/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:38,810 - [NOTICE] simulation.solve(843): Cycle 54/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:38,831 - [NOTICE] simulation.solve(843): Cycle 54/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:38,868 - [NOTICE] simulation.solve(921): Capacity is now 3.328 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:38,869 - [NOTICE] simulation.solve(809): Cycle 55/500 (5.965 s elapsed) --------------------\n", - "2021-09-17 01:13:38,870 - [NOTICE] simulation.solve(843): Cycle 55/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:38,892 - [NOTICE] simulation.solve(843): Cycle 55/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:38,916 - [NOTICE] simulation.solve(843): Cycle 55/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:38,932 - [NOTICE] simulation.solve(843): Cycle 55/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:38,975 - [NOTICE] simulation.solve(921): Capacity is now 3.319 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:38,976 - [NOTICE] simulation.solve(809): Cycle 56/500 (6.072 s elapsed) --------------------\n", - "2021-09-17 01:13:38,977 - [NOTICE] simulation.solve(843): Cycle 56/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:38,997 - [NOTICE] simulation.solve(843): Cycle 56/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:39,021 - [NOTICE] simulation.solve(843): Cycle 56/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:39,042 - [NOTICE] simulation.solve(843): Cycle 56/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:39,075 - [NOTICE] simulation.solve(921): Capacity is now 3.309 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:39,075 - [NOTICE] simulation.solve(809): Cycle 57/500 (6.175 s elapsed) --------------------\n", - "2021-09-17 01:13:39,075 - [NOTICE] simulation.solve(843): Cycle 57/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:39,106 - [NOTICE] simulation.solve(843): Cycle 57/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:39,131 - [NOTICE] simulation.solve(843): Cycle 57/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:39,151 - [NOTICE] simulation.solve(843): Cycle 57/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:39,190 - [NOTICE] simulation.solve(921): Capacity is now 3.299 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:39,191 - [NOTICE] simulation.solve(809): Cycle 58/500 (6.286 s elapsed) --------------------\n", - "2021-09-17 01:13:39,192 - [NOTICE] simulation.solve(843): Cycle 58/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:39,213 - [NOTICE] simulation.solve(843): Cycle 58/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:39,238 - [NOTICE] simulation.solve(843): Cycle 58/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:39,260 - [NOTICE] simulation.solve(843): Cycle 58/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:39,291 - [NOTICE] simulation.solve(921): Capacity is now 3.290 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:39,291 - [NOTICE] simulation.solve(809): Cycle 59/500 (6.392 s elapsed) --------------------\n", - "2021-09-17 01:13:39,291 - [NOTICE] simulation.solve(843): Cycle 59/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:39,321 - [NOTICE] simulation.solve(843): Cycle 59/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:39,343 - [NOTICE] simulation.solve(843): Cycle 59/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:39,367 - [NOTICE] simulation.solve(843): Cycle 59/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:39,396 - [NOTICE] simulation.solve(921): Capacity is now 3.280 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:39,396 - [NOTICE] simulation.solve(809): Cycle 60/500 (6.500 s elapsed) --------------------\n", - "2021-09-17 01:13:39,396 - [NOTICE] simulation.solve(843): Cycle 60/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:39,426 - [NOTICE] simulation.solve(843): Cycle 60/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:39,450 - [NOTICE] simulation.solve(843): Cycle 60/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:39,474 - [NOTICE] simulation.solve(843): Cycle 60/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:39,508 - [NOTICE] simulation.solve(921): Capacity is now 3.271 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:39,508 - [NOTICE] simulation.solve(809): Cycle 61/500 (6.609 s elapsed) --------------------\n", - "2021-09-17 01:13:39,508 - [NOTICE] simulation.solve(843): Cycle 61/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:39,525 - [NOTICE] simulation.solve(843): Cycle 61/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:39,555 - [NOTICE] simulation.solve(843): Cycle 61/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:39,570 - [NOTICE] simulation.solve(843): Cycle 61/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:39,616 - [NOTICE] simulation.solve(921): Capacity is now 3.261 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:39,616 - [NOTICE] simulation.solve(809): Cycle 62/500 (6.713 s elapsed) --------------------\n", - "2021-09-17 01:13:39,616 - [NOTICE] simulation.solve(843): Cycle 62/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:39,639 - [NOTICE] simulation.solve(843): Cycle 62/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:39,659 - [NOTICE] simulation.solve(843): Cycle 62/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:39,670 - [NOTICE] simulation.solve(843): Cycle 62/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:39,715 - [NOTICE] simulation.solve(921): Capacity is now 3.252 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:39,715 - [NOTICE] simulation.solve(809): Cycle 63/500 (6.817 s elapsed) --------------------\n", - "2021-09-17 01:13:39,715 - [NOTICE] simulation.solve(843): Cycle 63/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:39,731 - [NOTICE] simulation.solve(843): Cycle 63/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:39,770 - [NOTICE] simulation.solve(843): Cycle 63/500, step 3/4: Charge at 1C until 4.2V\n" + "2021-11-19 15:28:51,847 - [NOTICE] simulation.solve(884): Cycle 51/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:51,865 - [NOTICE] simulation.solve(884): Cycle 51/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:51,883 - [NOTICE] simulation.solve(884): Cycle 51/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:51,899 - [NOTICE] simulation.solve(884): Cycle 51/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:51,936 - [NOTICE] simulation.solve(972): Capacity is now 3.301 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:51,936 - [NOTICE] simulation.solve(850): Cycle 52/500 (4.706 s elapsed) --------------------\n", + "2021-11-19 15:28:51,936 - [NOTICE] simulation.solve(884): Cycle 52/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:51,952 - [NOTICE] simulation.solve(884): Cycle 52/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:51,970 - [NOTICE] simulation.solve(884): Cycle 52/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:51,986 - [NOTICE] simulation.solve(884): Cycle 52/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:52,017 - [NOTICE] simulation.solve(972): Capacity is now 3.290 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:52,018 - [NOTICE] simulation.solve(850): Cycle 53/500 (4.788 s elapsed) --------------------\n", + "2021-11-19 15:28:52,018 - [NOTICE] simulation.solve(884): Cycle 53/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:52,034 - [NOTICE] simulation.solve(884): Cycle 53/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:52,051 - [NOTICE] simulation.solve(884): Cycle 53/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:52,067 - [NOTICE] simulation.solve(884): Cycle 53/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:52,098 - [NOTICE] simulation.solve(972): Capacity is now 3.279 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:52,098 - [NOTICE] simulation.solve(850): Cycle 54/500 (4.868 s elapsed) --------------------\n", + "2021-11-19 15:28:52,099 - [NOTICE] simulation.solve(884): Cycle 54/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:52,114 - [NOTICE] simulation.solve(884): Cycle 54/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:52,132 - [NOTICE] simulation.solve(884): Cycle 54/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:52,148 - [NOTICE] simulation.solve(884): Cycle 54/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:52,179 - [NOTICE] simulation.solve(972): Capacity is now 3.268 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:52,179 - [NOTICE] simulation.solve(850): Cycle 55/500 (4.949 s elapsed) --------------------\n", + "2021-11-19 15:28:52,179 - [NOTICE] simulation.solve(884): Cycle 55/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:52,195 - [NOTICE] simulation.solve(884): Cycle 55/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:52,214 - [NOTICE] simulation.solve(884): Cycle 55/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:52,231 - [NOTICE] simulation.solve(884): Cycle 55/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:52,262 - [NOTICE] simulation.solve(972): Capacity is now 3.258 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:52,263 - [NOTICE] simulation.solve(850): Cycle 56/500 (5.033 s elapsed) --------------------\n", + "2021-11-19 15:28:52,263 - [NOTICE] simulation.solve(884): Cycle 56/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:52,279 - [NOTICE] simulation.solve(884): Cycle 56/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:52,297 - [NOTICE] simulation.solve(884): Cycle 56/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:52,312 - [NOTICE] simulation.solve(884): Cycle 56/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:52,343 - [NOTICE] simulation.solve(972): Capacity is now 3.247 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:52,344 - [NOTICE] simulation.solve(850): Cycle 57/500 (5.114 s elapsed) --------------------\n", + "2021-11-19 15:28:52,344 - [NOTICE] simulation.solve(884): Cycle 57/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:52,361 - [NOTICE] simulation.solve(884): Cycle 57/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:52,379 - [NOTICE] simulation.solve(884): Cycle 57/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:52,395 - [NOTICE] simulation.solve(884): Cycle 57/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:52,426 - [NOTICE] simulation.solve(972): Capacity is now 3.237 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:52,426 - [NOTICE] simulation.solve(850): Cycle 58/500 (5.197 s elapsed) --------------------\n", + "2021-11-19 15:28:52,427 - [NOTICE] simulation.solve(884): Cycle 58/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:52,444 - [NOTICE] simulation.solve(884): Cycle 58/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:52,462 - [NOTICE] simulation.solve(884): Cycle 58/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:52,478 - [NOTICE] simulation.solve(884): Cycle 58/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:52,511 - [NOTICE] simulation.solve(972): Capacity is now 3.227 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:52,511 - [NOTICE] simulation.solve(850): Cycle 59/500 (5.281 s elapsed) --------------------\n", + "2021-11-19 15:28:52,512 - [NOTICE] simulation.solve(884): Cycle 59/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:52,529 - [NOTICE] simulation.solve(884): Cycle 59/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:52,547 - [NOTICE] simulation.solve(884): Cycle 59/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:52,561 - [NOTICE] simulation.solve(884): Cycle 59/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:52,591 - [NOTICE] simulation.solve(972): Capacity is now 3.217 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:52,592 - [NOTICE] simulation.solve(850): Cycle 60/500 (5.362 s elapsed) --------------------\n", + "2021-11-19 15:28:52,592 - [NOTICE] simulation.solve(884): Cycle 60/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:52,610 - [NOTICE] simulation.solve(884): Cycle 60/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:52,627 - [NOTICE] simulation.solve(884): Cycle 60/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:52,641 - [NOTICE] simulation.solve(884): Cycle 60/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:52,672 - [NOTICE] simulation.solve(972): Capacity is now 3.207 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:52,673 - [NOTICE] simulation.solve(850): Cycle 61/500 (5.443 s elapsed) --------------------\n", + "2021-11-19 15:28:52,673 - [NOTICE] simulation.solve(884): Cycle 61/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:52,690 - [NOTICE] simulation.solve(884): Cycle 61/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:52,708 - [NOTICE] simulation.solve(884): Cycle 61/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:52,721 - [NOTICE] simulation.solve(884): Cycle 61/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:52,752 - [NOTICE] simulation.solve(972): Capacity is now 3.197 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:52,752 - [NOTICE] simulation.solve(850): Cycle 62/500 (5.522 s elapsed) --------------------\n", + "2021-11-19 15:28:52,752 - [NOTICE] simulation.solve(884): Cycle 62/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:52,770 - [NOTICE] simulation.solve(884): Cycle 62/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:52,787 - [NOTICE] simulation.solve(884): Cycle 62/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:52,803 - [NOTICE] simulation.solve(884): Cycle 62/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:52,833 - [NOTICE] simulation.solve(972): Capacity is now 3.187 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:52,834 - [NOTICE] simulation.solve(850): Cycle 63/500 (5.604 s elapsed) --------------------\n", + "2021-11-19 15:28:52,834 - [NOTICE] simulation.solve(884): Cycle 63/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:52,851 - [NOTICE] simulation.solve(884): Cycle 63/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:52,869 - [NOTICE] simulation.solve(884): Cycle 63/500, step 3/4: Charge at 1C until 4.2V\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:39,791 - [NOTICE] simulation.solve(843): Cycle 63/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:39,828 - [NOTICE] simulation.solve(921): Capacity is now 3.243 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:39,828 - [NOTICE] simulation.solve(809): Cycle 64/500 (6.924 s elapsed) --------------------\n", - "2021-09-17 01:13:39,828 - [NOTICE] simulation.solve(843): Cycle 64/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:39,849 - [NOTICE] simulation.solve(843): Cycle 64/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:39,870 - [NOTICE] simulation.solve(843): Cycle 64/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:39,897 - [NOTICE] simulation.solve(843): Cycle 64/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:39,932 - [NOTICE] simulation.solve(921): Capacity is now 3.234 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:39,932 - [NOTICE] simulation.solve(809): Cycle 65/500 (7.030 s elapsed) --------------------\n", - "2021-09-17 01:13:39,932 - [NOTICE] simulation.solve(843): Cycle 65/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:39,958 - [NOTICE] simulation.solve(843): Cycle 65/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:39,970 - [NOTICE] simulation.solve(843): Cycle 65/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:39,986 - [NOTICE] simulation.solve(843): Cycle 65/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:40,033 - [NOTICE] simulation.solve(921): Capacity is now 3.224 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:40,033 - [NOTICE] simulation.solve(809): Cycle 66/500 (7.133 s elapsed) --------------------\n", - "2021-09-17 01:13:40,033 - [NOTICE] simulation.solve(843): Cycle 66/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:40,050 - [NOTICE] simulation.solve(843): Cycle 66/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:40,086 - [NOTICE] simulation.solve(843): Cycle 66/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:40,092 - [NOTICE] simulation.solve(843): Cycle 66/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:40,126 - [NOTICE] simulation.solve(921): Capacity is now 3.215 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:40,126 - [NOTICE] simulation.solve(809): Cycle 67/500 (7.236 s elapsed) --------------------\n", - "2021-09-17 01:13:40,126 - [NOTICE] simulation.solve(843): Cycle 67/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:40,162 - [NOTICE] simulation.solve(843): Cycle 67/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:40,187 - [NOTICE] simulation.solve(843): Cycle 67/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:40,206 - [NOTICE] simulation.solve(843): Cycle 67/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:40,231 - [NOTICE] simulation.solve(921): Capacity is now 3.206 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:40,231 - [NOTICE] simulation.solve(809): Cycle 68/500 (7.337 s elapsed) --------------------\n", - "2021-09-17 01:13:40,231 - [NOTICE] simulation.solve(843): Cycle 68/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:40,263 - [NOTICE] simulation.solve(843): Cycle 68/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:40,289 - [NOTICE] simulation.solve(843): Cycle 68/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:40,308 - [NOTICE] simulation.solve(843): Cycle 68/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:40,332 - [NOTICE] simulation.solve(921): Capacity is now 3.198 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:40,332 - [NOTICE] simulation.solve(809): Cycle 69/500 (7.439 s elapsed) --------------------\n", - "2021-09-17 01:13:40,332 - [NOTICE] simulation.solve(843): Cycle 69/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:40,363 - [NOTICE] simulation.solve(843): Cycle 69/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:40,391 - [NOTICE] simulation.solve(843): Cycle 69/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:40,409 - [NOTICE] simulation.solve(843): Cycle 69/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:40,432 - [NOTICE] simulation.solve(921): Capacity is now 3.189 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:40,432 - [NOTICE] simulation.solve(809): Cycle 70/500 (7.540 s elapsed) --------------------\n", - "2021-09-17 01:13:40,432 - [NOTICE] simulation.solve(843): Cycle 70/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:40,464 - [NOTICE] simulation.solve(843): Cycle 70/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:40,492 - [NOTICE] simulation.solve(843): Cycle 70/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:40,510 - [NOTICE] simulation.solve(843): Cycle 70/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:40,543 - [NOTICE] simulation.solve(921): Capacity is now 3.180 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:40,543 - [NOTICE] simulation.solve(809): Cycle 71/500 (7.641 s elapsed) --------------------\n", - "2021-09-17 01:13:40,543 - [NOTICE] simulation.solve(843): Cycle 71/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:40,568 - [NOTICE] simulation.solve(843): Cycle 71/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:40,586 - [NOTICE] simulation.solve(843): Cycle 71/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:40,597 - [NOTICE] simulation.solve(843): Cycle 71/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:40,647 - [NOTICE] simulation.solve(921): Capacity is now 3.171 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:40,648 - [NOTICE] simulation.solve(809): Cycle 72/500 (7.743 s elapsed) --------------------\n", - "2021-09-17 01:13:40,648 - [NOTICE] simulation.solve(843): Cycle 72/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:40,671 - [NOTICE] simulation.solve(843): Cycle 72/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:40,686 - [NOTICE] simulation.solve(843): Cycle 72/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:40,715 - [NOTICE] simulation.solve(843): Cycle 72/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:40,746 - [NOTICE] simulation.solve(921): Capacity is now 3.163 Ah (originally 3.944 Ah, will stop at 3.155 Ah)\n", - "2021-09-17 01:13:40,746 - [NOTICE] simulation.solve(809): Cycle 73/500 (7.850 s elapsed) --------------------\n", - "2021-09-17 01:13:40,746 - [NOTICE] simulation.solve(843): Cycle 73/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:40,771 - [NOTICE] simulation.solve(843): Cycle 73/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:40,798 - [NOTICE] simulation.solve(843): Cycle 73/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:40,809 - [NOTICE] simulation.solve(843): Cycle 73/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:40,838 - [NOTICE] simulation.solve(927): Stopping experiment since capacity (3.154 Ah) is below stopping capacity (3.155 Ah).\n", - "2021-09-17 01:13:40,853 - [NOTICE] simulation.solve(938): Finish experiment simulation, took 7.950 s\n", - "2021-09-17 01:13:40,889 - [NOTICE] simulation.solve(809): Cycle 1/500 (33.021 ms elapsed) --------------------\n", - "2021-09-17 01:13:40,890 - [NOTICE] simulation.solve(843): Cycle 1/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:40,930 - [NOTICE] simulation.solve(843): Cycle 1/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:40,951 - [NOTICE] simulation.solve(843): Cycle 1/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:40,971 - [NOTICE] simulation.solve(843): Cycle 1/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:41,116 - [NOTICE] simulation.solve(921): Capacity is now 3.154 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:41,116 - [NOTICE] simulation.solve(809): Cycle 2/500 (264.522 ms elapsed) --------------------\n", - "2021-09-17 01:13:41,116 - [NOTICE] simulation.solve(843): Cycle 2/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:41,126 - [NOTICE] simulation.solve(843): Cycle 2/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:41,160 - [NOTICE] simulation.solve(843): Cycle 2/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:41,172 - [NOTICE] simulation.solve(843): Cycle 2/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:41,448 - [NOTICE] simulation.solve(921): Capacity is now 3.146 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n" + "2021-11-19 15:28:52,884 - [NOTICE] simulation.solve(884): Cycle 63/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:52,915 - [NOTICE] simulation.solve(972): Capacity is now 3.177 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:52,916 - [NOTICE] simulation.solve(850): Cycle 64/500 (5.686 s elapsed) --------------------\n", + "2021-11-19 15:28:52,916 - [NOTICE] simulation.solve(884): Cycle 64/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:52,935 - [NOTICE] simulation.solve(884): Cycle 64/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:52,953 - [NOTICE] simulation.solve(884): Cycle 64/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:52,968 - [NOTICE] simulation.solve(884): Cycle 64/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:53,004 - [NOTICE] simulation.solve(972): Capacity is now 3.167 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:53,004 - [NOTICE] simulation.solve(850): Cycle 65/500 (5.775 s elapsed) --------------------\n", + "2021-11-19 15:28:53,005 - [NOTICE] simulation.solve(884): Cycle 65/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:53,020 - [NOTICE] simulation.solve(884): Cycle 65/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:53,039 - [NOTICE] simulation.solve(884): Cycle 65/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:53,053 - [NOTICE] simulation.solve(884): Cycle 65/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:53,085 - [NOTICE] simulation.solve(972): Capacity is now 3.158 Ah (originally 3.946 Ah, will stop at 3.156 Ah)\n", + "2021-11-19 15:28:53,086 - [NOTICE] simulation.solve(850): Cycle 66/500 (5.856 s elapsed) --------------------\n", + "2021-11-19 15:28:53,086 - [NOTICE] simulation.solve(884): Cycle 66/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:53,101 - [NOTICE] simulation.solve(884): Cycle 66/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:53,121 - [NOTICE] simulation.solve(884): Cycle 66/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:53,134 - [NOTICE] simulation.solve(884): Cycle 66/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:53,167 - [NOTICE] simulation.solve(978): Stopping experiment since capacity (3.149 Ah) is below stopping capacity (3.156 Ah).\n", + "2021-11-19 15:28:53,168 - [NOTICE] simulation.solve(990): Finish experiment simulation, took 5.938 s\n", + "2021-11-19 15:28:53,194 - [NOTICE] simulation.solve(850): Cycle 1/500 (25.617 ms elapsed) --------------------\n", + "2021-11-19 15:28:53,194 - [NOTICE] simulation.solve(884): Cycle 1/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:53,224 - [NOTICE] simulation.solve(884): Cycle 1/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:53,242 - [NOTICE] simulation.solve(884): Cycle 1/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:53,256 - [NOTICE] simulation.solve(884): Cycle 1/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:53,379 - [NOTICE] simulation.solve(972): Capacity is now 3.149 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:53,380 - [NOTICE] simulation.solve(850): Cycle 2/500 (211.736 ms elapsed) --------------------\n", + "2021-11-19 15:28:53,380 - [NOTICE] simulation.solve(884): Cycle 2/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:53,396 - [NOTICE] simulation.solve(884): Cycle 2/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:53,413 - [NOTICE] simulation.solve(884): Cycle 2/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:53,427 - [NOTICE] simulation.solve(884): Cycle 2/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:53,463 - [NOTICE] simulation.solve(972): Capacity is now 3.139 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:53,464 - [NOTICE] simulation.solve(850): Cycle 3/500 (295.808 ms elapsed) --------------------\n", + "2021-11-19 15:28:53,464 - [NOTICE] simulation.solve(884): Cycle 3/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:53,481 - [NOTICE] simulation.solve(884): Cycle 3/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:53,499 - [NOTICE] simulation.solve(884): Cycle 3/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:53,513 - [NOTICE] simulation.solve(884): Cycle 3/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:53,546 - [NOTICE] simulation.solve(972): Capacity is now 3.130 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:53,547 - [NOTICE] simulation.solve(850): Cycle 4/500 (378.413 ms elapsed) --------------------\n", + "2021-11-19 15:28:53,547 - [NOTICE] simulation.solve(884): Cycle 4/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:53,563 - [NOTICE] simulation.solve(884): Cycle 4/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:53,580 - [NOTICE] simulation.solve(884): Cycle 4/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:53,595 - [NOTICE] simulation.solve(884): Cycle 4/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:53,626 - [NOTICE] simulation.solve(972): Capacity is now 3.121 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:53,627 - [NOTICE] simulation.solve(850): Cycle 5/500 (458.620 ms elapsed) --------------------\n", + "2021-11-19 15:28:53,627 - [NOTICE] simulation.solve(884): Cycle 5/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:53,643 - [NOTICE] simulation.solve(884): Cycle 5/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:53,660 - [NOTICE] simulation.solve(884): Cycle 5/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:53,678 - [NOTICE] simulation.solve(884): Cycle 5/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:53,710 - [NOTICE] simulation.solve(972): Capacity is now 3.112 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:53,711 - [NOTICE] simulation.solve(850): Cycle 6/500 (542.688 ms elapsed) --------------------\n", + "2021-11-19 15:28:53,711 - [NOTICE] simulation.solve(884): Cycle 6/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:53,727 - [NOTICE] simulation.solve(884): Cycle 6/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:53,745 - [NOTICE] simulation.solve(884): Cycle 6/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:53,761 - [NOTICE] simulation.solve(884): Cycle 6/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:53,792 - [NOTICE] simulation.solve(972): Capacity is now 3.104 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:53,793 - [NOTICE] simulation.solve(850): Cycle 7/500 (624.667 ms elapsed) --------------------\n", + "2021-11-19 15:28:53,793 - [NOTICE] simulation.solve(884): Cycle 7/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:53,809 - [NOTICE] simulation.solve(884): Cycle 7/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:53,827 - [NOTICE] simulation.solve(884): Cycle 7/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:53,843 - [NOTICE] simulation.solve(884): Cycle 7/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:53,875 - [NOTICE] simulation.solve(972): Capacity is now 3.095 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:53,876 - [NOTICE] simulation.solve(850): Cycle 8/500 (707.375 ms elapsed) --------------------\n", + "2021-11-19 15:28:53,876 - [NOTICE] simulation.solve(884): Cycle 8/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:53,892 - [NOTICE] simulation.solve(884): Cycle 8/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:53,910 - [NOTICE] simulation.solve(884): Cycle 8/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:53,927 - [NOTICE] simulation.solve(884): Cycle 8/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:53,961 - [NOTICE] simulation.solve(972): Capacity is now 3.087 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:53,962 - [NOTICE] simulation.solve(850): Cycle 9/500 (793.389 ms elapsed) --------------------\n", + "2021-11-19 15:28:53,962 - [NOTICE] simulation.solve(884): Cycle 9/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:53,982 - [NOTICE] simulation.solve(884): Cycle 9/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:54,001 - [NOTICE] simulation.solve(884): Cycle 9/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:54,020 - [NOTICE] simulation.solve(884): Cycle 9/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:54,053 - [NOTICE] simulation.solve(972): Capacity is now 3.079 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:41,448 - [NOTICE] simulation.solve(809): Cycle 3/500 (598.112 ms elapsed) --------------------\n", - "2021-09-17 01:13:41,448 - [NOTICE] simulation.solve(843): Cycle 3/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:41,472 - [NOTICE] simulation.solve(843): Cycle 3/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:41,494 - [NOTICE] simulation.solve(843): Cycle 3/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:41,502 - [NOTICE] simulation.solve(843): Cycle 3/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:41,551 - [NOTICE] simulation.solve(921): Capacity is now 3.137 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:41,551 - [NOTICE] simulation.solve(809): Cycle 4/500 (698.211 ms elapsed) --------------------\n", - "2021-09-17 01:13:41,551 - [NOTICE] simulation.solve(843): Cycle 4/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:41,572 - [NOTICE] simulation.solve(843): Cycle 4/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:41,594 - [NOTICE] simulation.solve(843): Cycle 4/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:41,603 - [NOTICE] simulation.solve(843): Cycle 4/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:41,637 - [NOTICE] simulation.solve(921): Capacity is now 3.129 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:41,637 - [NOTICE] simulation.solve(809): Cycle 5/500 (796.450 ms elapsed) --------------------\n", - "2021-09-17 01:13:41,653 - [NOTICE] simulation.solve(843): Cycle 5/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:41,673 - [NOTICE] simulation.solve(843): Cycle 5/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:41,693 - [NOTICE] simulation.solve(843): Cycle 5/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:41,701 - [NOTICE] simulation.solve(843): Cycle 5/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:41,738 - [NOTICE] simulation.solve(921): Capacity is now 3.121 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:41,738 - [NOTICE] simulation.solve(809): Cycle 6/500 (897.322 ms elapsed) --------------------\n", - "2021-09-17 01:13:41,754 - [NOTICE] simulation.solve(843): Cycle 6/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:41,773 - [NOTICE] simulation.solve(843): Cycle 6/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:41,795 - [NOTICE] simulation.solve(843): Cycle 6/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:41,805 - [NOTICE] simulation.solve(843): Cycle 6/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:41,856 - [NOTICE] simulation.solve(921): Capacity is now 3.113 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:41,856 - [NOTICE] simulation.solve(809): Cycle 7/500 (1.001 s elapsed) --------------------\n", - "2021-09-17 01:13:41,856 - [NOTICE] simulation.solve(843): Cycle 7/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:41,878 - [NOTICE] simulation.solve(843): Cycle 7/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:41,901 - [NOTICE] simulation.solve(843): Cycle 7/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:41,922 - [NOTICE] simulation.solve(843): Cycle 7/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:41,959 - [NOTICE] simulation.solve(921): Capacity is now 3.105 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:41,962 - [NOTICE] simulation.solve(809): Cycle 8/500 (1.106 s elapsed) --------------------\n", - "2021-09-17 01:13:41,963 - [NOTICE] simulation.solve(843): Cycle 8/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:41,987 - [NOTICE] simulation.solve(843): Cycle 8/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:42,013 - [NOTICE] simulation.solve(843): Cycle 8/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:42,036 - [NOTICE] simulation.solve(843): Cycle 8/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:42,072 - [NOTICE] simulation.solve(921): Capacity is now 3.098 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:42,073 - [NOTICE] simulation.solve(809): Cycle 9/500 (1.217 s elapsed) --------------------\n", - "2021-09-17 01:13:42,074 - [NOTICE] simulation.solve(843): Cycle 9/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:42,095 - [NOTICE] simulation.solve(843): Cycle 9/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:42,119 - [NOTICE] simulation.solve(843): Cycle 9/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:42,139 - [NOTICE] simulation.solve(843): Cycle 9/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:42,173 - [NOTICE] simulation.solve(921): Capacity is now 3.090 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:42,174 - [NOTICE] simulation.solve(809): Cycle 10/500 (1.318 s elapsed) --------------------\n", - "2021-09-17 01:13:42,175 - [NOTICE] simulation.solve(843): Cycle 10/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:42,197 - [NOTICE] simulation.solve(843): Cycle 10/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:42,222 - [NOTICE] simulation.solve(843): Cycle 10/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:42,244 - [NOTICE] simulation.solve(843): Cycle 10/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:42,275 - [NOTICE] simulation.solve(921): Capacity is now 3.083 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:42,275 - [NOTICE] simulation.solve(809): Cycle 11/500 (1.426 s elapsed) --------------------\n", - "2021-09-17 01:13:42,275 - [NOTICE] simulation.solve(843): Cycle 11/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:42,311 - [NOTICE] simulation.solve(843): Cycle 11/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:42,332 - [NOTICE] simulation.solve(843): Cycle 11/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:42,356 - [NOTICE] simulation.solve(843): Cycle 11/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:42,390 - [NOTICE] simulation.solve(921): Capacity is now 3.075 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:42,391 - [NOTICE] simulation.solve(809): Cycle 12/500 (1.535 s elapsed) --------------------\n", - "2021-09-17 01:13:42,391 - [NOTICE] simulation.solve(843): Cycle 12/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:42,414 - [NOTICE] simulation.solve(843): Cycle 12/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:42,439 - [NOTICE] simulation.solve(843): Cycle 12/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:42,458 - [NOTICE] simulation.solve(843): Cycle 12/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:42,491 - [NOTICE] simulation.solve(921): Capacity is now 3.068 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:42,492 - [NOTICE] simulation.solve(809): Cycle 13/500 (1.636 s elapsed) --------------------\n", - "2021-09-17 01:13:42,492 - [NOTICE] simulation.solve(843): Cycle 13/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:42,515 - [NOTICE] simulation.solve(843): Cycle 13/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:42,540 - [NOTICE] simulation.solve(843): Cycle 13/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:42,562 - [NOTICE] simulation.solve(843): Cycle 13/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:42,593 - [NOTICE] simulation.solve(921): Capacity is now 3.061 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:42,593 - [NOTICE] simulation.solve(809): Cycle 14/500 (1.739 s elapsed) --------------------\n", - "2021-09-17 01:13:42,593 - [NOTICE] simulation.solve(843): Cycle 14/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:42,617 - [NOTICE] simulation.solve(843): Cycle 14/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:42,642 - [NOTICE] simulation.solve(843): Cycle 14/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:42,664 - [NOTICE] simulation.solve(843): Cycle 14/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:42,696 - [NOTICE] simulation.solve(921): Capacity is now 3.054 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:42,697 - [NOTICE] simulation.solve(809): Cycle 15/500 (1.842 s elapsed) --------------------\n", - "2021-09-17 01:13:42,698 - [NOTICE] simulation.solve(843): Cycle 15/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:42,722 - [NOTICE] simulation.solve(843): Cycle 15/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:42,750 - [NOTICE] simulation.solve(843): Cycle 15/500, step 3/4: Charge at 1C until 4.2V\n" + "2021-11-19 15:28:54,054 - [NOTICE] simulation.solve(850): Cycle 10/500 (885.735 ms elapsed) --------------------\n", + "2021-11-19 15:28:54,054 - [NOTICE] simulation.solve(884): Cycle 10/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:54,074 - [NOTICE] simulation.solve(884): Cycle 10/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:54,094 - [NOTICE] simulation.solve(884): Cycle 10/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:54,115 - [NOTICE] simulation.solve(884): Cycle 10/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:54,150 - [NOTICE] simulation.solve(972): Capacity is now 3.071 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:54,151 - [NOTICE] simulation.solve(850): Cycle 11/500 (982.614 ms elapsed) --------------------\n", + "2021-11-19 15:28:54,152 - [NOTICE] simulation.solve(884): Cycle 11/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:54,172 - [NOTICE] simulation.solve(884): Cycle 11/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:54,192 - [NOTICE] simulation.solve(884): Cycle 11/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:54,211 - [NOTICE] simulation.solve(884): Cycle 11/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:54,248 - [NOTICE] simulation.solve(972): Capacity is now 3.063 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:54,248 - [NOTICE] simulation.solve(850): Cycle 12/500 (1.080 s elapsed) --------------------\n", + "2021-11-19 15:28:54,249 - [NOTICE] simulation.solve(884): Cycle 12/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:54,271 - [NOTICE] simulation.solve(884): Cycle 12/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:54,290 - [NOTICE] simulation.solve(884): Cycle 12/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:54,307 - [NOTICE] simulation.solve(884): Cycle 12/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:54,339 - [NOTICE] simulation.solve(972): Capacity is now 3.055 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:54,339 - [NOTICE] simulation.solve(850): Cycle 13/500 (1.171 s elapsed) --------------------\n", + "2021-11-19 15:28:54,339 - [NOTICE] simulation.solve(884): Cycle 13/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:54,357 - [NOTICE] simulation.solve(884): Cycle 13/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:54,375 - [NOTICE] simulation.solve(884): Cycle 13/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:54,394 - [NOTICE] simulation.solve(884): Cycle 13/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:54,425 - [NOTICE] simulation.solve(972): Capacity is now 3.048 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:54,425 - [NOTICE] simulation.solve(850): Cycle 14/500 (1.257 s elapsed) --------------------\n", + "2021-11-19 15:28:54,426 - [NOTICE] simulation.solve(884): Cycle 14/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:54,444 - [NOTICE] simulation.solve(884): Cycle 14/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:54,462 - [NOTICE] simulation.solve(884): Cycle 14/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:54,479 - [NOTICE] simulation.solve(884): Cycle 14/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:54,510 - [NOTICE] simulation.solve(972): Capacity is now 3.041 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:54,510 - [NOTICE] simulation.solve(850): Cycle 15/500 (1.342 s elapsed) --------------------\n", + "2021-11-19 15:28:54,511 - [NOTICE] simulation.solve(884): Cycle 15/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:54,528 - [NOTICE] simulation.solve(884): Cycle 15/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:54,547 - [NOTICE] simulation.solve(884): Cycle 15/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:54,560 - [NOTICE] simulation.solve(884): Cycle 15/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:54,591 - [NOTICE] simulation.solve(972): Capacity is now 3.034 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:54,592 - [NOTICE] simulation.solve(850): Cycle 16/500 (1.423 s elapsed) --------------------\n", + "2021-11-19 15:28:54,592 - [NOTICE] simulation.solve(884): Cycle 16/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:54,609 - [NOTICE] simulation.solve(884): Cycle 16/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:54,628 - [NOTICE] simulation.solve(884): Cycle 16/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:54,641 - [NOTICE] simulation.solve(884): Cycle 16/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:54,672 - [NOTICE] simulation.solve(972): Capacity is now 3.027 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:54,672 - [NOTICE] simulation.solve(850): Cycle 17/500 (1.504 s elapsed) --------------------\n", + "2021-11-19 15:28:54,673 - [NOTICE] simulation.solve(884): Cycle 17/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:54,691 - [NOTICE] simulation.solve(884): Cycle 17/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:54,709 - [NOTICE] simulation.solve(884): Cycle 17/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:54,724 - [NOTICE] simulation.solve(884): Cycle 17/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:54,755 - [NOTICE] simulation.solve(972): Capacity is now 3.020 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:54,756 - [NOTICE] simulation.solve(850): Cycle 18/500 (1.588 s elapsed) --------------------\n", + "2021-11-19 15:28:54,756 - [NOTICE] simulation.solve(884): Cycle 18/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:54,774 - [NOTICE] simulation.solve(884): Cycle 18/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:54,792 - [NOTICE] simulation.solve(884): Cycle 18/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:54,806 - [NOTICE] simulation.solve(884): Cycle 18/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:54,837 - [NOTICE] simulation.solve(972): Capacity is now 3.013 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:54,837 - [NOTICE] simulation.solve(850): Cycle 19/500 (1.669 s elapsed) --------------------\n", + "2021-11-19 15:28:54,838 - [NOTICE] simulation.solve(884): Cycle 19/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:54,856 - [NOTICE] simulation.solve(884): Cycle 19/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:54,874 - [NOTICE] simulation.solve(884): Cycle 19/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:54,888 - [NOTICE] simulation.solve(884): Cycle 19/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:54,920 - [NOTICE] simulation.solve(972): Capacity is now 3.007 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:54,920 - [NOTICE] simulation.solve(850): Cycle 20/500 (1.752 s elapsed) --------------------\n", + "2021-11-19 15:28:54,921 - [NOTICE] simulation.solve(884): Cycle 20/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:54,940 - [NOTICE] simulation.solve(884): Cycle 20/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:54,958 - [NOTICE] simulation.solve(884): Cycle 20/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:54,972 - [NOTICE] simulation.solve(884): Cycle 20/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,004 - [NOTICE] simulation.solve(972): Capacity is now 3.000 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,004 - [NOTICE] simulation.solve(850): Cycle 21/500 (1.836 s elapsed) --------------------\n", + "2021-11-19 15:28:55,005 - [NOTICE] simulation.solve(884): Cycle 21/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,020 - [NOTICE] simulation.solve(884): Cycle 21/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:55,038 - [NOTICE] simulation.solve(884): Cycle 21/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:55,053 - [NOTICE] simulation.solve(884): Cycle 21/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,084 - [NOTICE] simulation.solve(972): Capacity is now 2.994 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,085 - [NOTICE] simulation.solve(850): Cycle 22/500 (1.917 s elapsed) --------------------\n", + "2021-11-19 15:28:55,086 - [NOTICE] simulation.solve(884): Cycle 22/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,101 - [NOTICE] simulation.solve(884): Cycle 22/500, step 2/4: Rest for 1 hour\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:42,772 - [NOTICE] simulation.solve(843): Cycle 15/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:42,805 - [NOTICE] simulation.solve(921): Capacity is now 3.047 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:42,806 - [NOTICE] simulation.solve(809): Cycle 16/500 (1.951 s elapsed) --------------------\n", - "2021-09-17 01:13:42,807 - [NOTICE] simulation.solve(843): Cycle 16/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:42,831 - [NOTICE] simulation.solve(843): Cycle 16/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:42,864 - [NOTICE] simulation.solve(843): Cycle 16/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:42,875 - [NOTICE] simulation.solve(843): Cycle 16/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:42,916 - [NOTICE] simulation.solve(921): Capacity is now 3.041 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:42,916 - [NOTICE] simulation.solve(809): Cycle 17/500 (2.066 s elapsed) --------------------\n", - "2021-09-17 01:13:42,916 - [NOTICE] simulation.solve(843): Cycle 17/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:42,950 - [NOTICE] simulation.solve(843): Cycle 17/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:42,975 - [NOTICE] simulation.solve(843): Cycle 17/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:42,996 - [NOTICE] simulation.solve(843): Cycle 17/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:43,030 - [NOTICE] simulation.solve(921): Capacity is now 3.034 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:43,031 - [NOTICE] simulation.solve(809): Cycle 18/500 (2.175 s elapsed) --------------------\n", - "2021-09-17 01:13:43,031 - [NOTICE] simulation.solve(843): Cycle 18/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:43,055 - [NOTICE] simulation.solve(843): Cycle 18/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:43,079 - [NOTICE] simulation.solve(843): Cycle 18/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:43,092 - [NOTICE] simulation.solve(843): Cycle 18/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:43,125 - [NOTICE] simulation.solve(921): Capacity is now 3.028 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:43,125 - [NOTICE] simulation.solve(809): Cycle 19/500 (2.275 s elapsed) --------------------\n", - "2021-09-17 01:13:43,125 - [NOTICE] simulation.solve(843): Cycle 19/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:43,152 - [NOTICE] simulation.solve(843): Cycle 19/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:43,178 - [NOTICE] simulation.solve(843): Cycle 19/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:43,195 - [NOTICE] simulation.solve(843): Cycle 19/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:43,226 - [NOTICE] simulation.solve(921): Capacity is now 3.022 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:43,226 - [NOTICE] simulation.solve(809): Cycle 20/500 (2.374 s elapsed) --------------------\n", - "2021-09-17 01:13:43,226 - [NOTICE] simulation.solve(843): Cycle 20/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:43,255 - [NOTICE] simulation.solve(843): Cycle 20/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:43,280 - [NOTICE] simulation.solve(843): Cycle 20/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:43,298 - [NOTICE] simulation.solve(843): Cycle 20/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:43,332 - [NOTICE] simulation.solve(921): Capacity is now 3.015 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:43,333 - [NOTICE] simulation.solve(809): Cycle 21/500 (2.478 s elapsed) --------------------\n", - "2021-09-17 01:13:43,333 - [NOTICE] simulation.solve(843): Cycle 21/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:43,358 - [NOTICE] simulation.solve(843): Cycle 21/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:43,380 - [NOTICE] simulation.solve(843): Cycle 21/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:43,399 - [NOTICE] simulation.solve(843): Cycle 21/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:43,433 - [NOTICE] simulation.solve(921): Capacity is now 3.009 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:43,434 - [NOTICE] simulation.solve(809): Cycle 22/500 (2.578 s elapsed) --------------------\n", - "2021-09-17 01:13:43,435 - [NOTICE] simulation.solve(843): Cycle 22/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:43,459 - [NOTICE] simulation.solve(843): Cycle 22/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:43,484 - [NOTICE] simulation.solve(843): Cycle 22/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:43,503 - [NOTICE] simulation.solve(843): Cycle 22/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:43,538 - [NOTICE] simulation.solve(921): Capacity is now 3.003 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:43,539 - [NOTICE] simulation.solve(809): Cycle 23/500 (2.684 s elapsed) --------------------\n", - "2021-09-17 01:13:43,540 - [NOTICE] simulation.solve(843): Cycle 23/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:43,565 - [NOTICE] simulation.solve(843): Cycle 23/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:43,591 - [NOTICE] simulation.solve(843): Cycle 23/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:43,610 - [NOTICE] simulation.solve(843): Cycle 23/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:43,642 - [NOTICE] simulation.solve(921): Capacity is now 2.998 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:43,642 - [NOTICE] simulation.solve(809): Cycle 24/500 (2.793 s elapsed) --------------------\n", - "2021-09-17 01:13:43,642 - [NOTICE] simulation.solve(843): Cycle 24/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:43,670 - [NOTICE] simulation.solve(843): Cycle 24/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:43,693 - [NOTICE] simulation.solve(843): Cycle 24/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:43,711 - [NOTICE] simulation.solve(843): Cycle 24/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:43,745 - [NOTICE] simulation.solve(921): Capacity is now 2.992 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:43,746 - [NOTICE] simulation.solve(809): Cycle 25/500 (2.890 s elapsed) --------------------\n", - "2021-09-17 01:13:43,747 - [NOTICE] simulation.solve(843): Cycle 25/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:43,770 - [NOTICE] simulation.solve(843): Cycle 25/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:43,796 - [NOTICE] simulation.solve(843): Cycle 25/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:43,814 - [NOTICE] simulation.solve(843): Cycle 25/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:43,848 - [NOTICE] simulation.solve(921): Capacity is now 2.986 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:43,849 - [NOTICE] simulation.solve(809): Cycle 26/500 (2.993 s elapsed) --------------------\n", - "2021-09-17 01:13:43,850 - [NOTICE] simulation.solve(843): Cycle 26/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:43,869 - [NOTICE] simulation.solve(843): Cycle 26/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:43,893 - [NOTICE] simulation.solve(843): Cycle 26/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:43,912 - [NOTICE] simulation.solve(843): Cycle 26/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:43,945 - [NOTICE] simulation.solve(921): Capacity is now 2.981 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:43,947 - [NOTICE] simulation.solve(809): Cycle 27/500 (3.091 s elapsed) --------------------\n", - "2021-09-17 01:13:43,947 - [NOTICE] simulation.solve(843): Cycle 27/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:43,970 - [NOTICE] simulation.solve(843): Cycle 27/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:43,994 - [NOTICE] simulation.solve(843): Cycle 27/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:44,010 - [NOTICE] simulation.solve(843): Cycle 27/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:44,046 - [NOTICE] simulation.solve(921): Capacity is now 2.976 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:44,047 - [NOTICE] simulation.solve(809): Cycle 28/500 (3.192 s elapsed) --------------------\n" + "2021-11-19 15:28:55,120 - [NOTICE] simulation.solve(884): Cycle 22/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:55,133 - [NOTICE] simulation.solve(884): Cycle 22/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,164 - [NOTICE] simulation.solve(972): Capacity is now 2.988 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,165 - [NOTICE] simulation.solve(850): Cycle 23/500 (1.997 s elapsed) --------------------\n", + "2021-11-19 15:28:55,165 - [NOTICE] simulation.solve(884): Cycle 23/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,180 - [NOTICE] simulation.solve(884): Cycle 23/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:55,199 - [NOTICE] simulation.solve(884): Cycle 23/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:55,213 - [NOTICE] simulation.solve(884): Cycle 23/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,244 - [NOTICE] simulation.solve(972): Capacity is now 2.982 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,245 - [NOTICE] simulation.solve(850): Cycle 24/500 (2.077 s elapsed) --------------------\n", + "2021-11-19 15:28:55,245 - [NOTICE] simulation.solve(884): Cycle 24/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,260 - [NOTICE] simulation.solve(884): Cycle 24/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:55,278 - [NOTICE] simulation.solve(884): Cycle 24/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:55,292 - [NOTICE] simulation.solve(884): Cycle 24/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,323 - [NOTICE] simulation.solve(972): Capacity is now 2.976 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,323 - [NOTICE] simulation.solve(850): Cycle 25/500 (2.155 s elapsed) --------------------\n", + "2021-11-19 15:28:55,323 - [NOTICE] simulation.solve(884): Cycle 25/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,339 - [NOTICE] simulation.solve(884): Cycle 25/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:55,357 - [NOTICE] simulation.solve(884): Cycle 25/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:55,374 - [NOTICE] simulation.solve(884): Cycle 25/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,404 - [NOTICE] simulation.solve(972): Capacity is now 2.970 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,405 - [NOTICE] simulation.solve(850): Cycle 26/500 (2.237 s elapsed) --------------------\n", + "2021-11-19 15:28:55,405 - [NOTICE] simulation.solve(884): Cycle 26/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,421 - [NOTICE] simulation.solve(884): Cycle 26/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:55,440 - [NOTICE] simulation.solve(884): Cycle 26/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:55,455 - [NOTICE] simulation.solve(884): Cycle 26/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,487 - [NOTICE] simulation.solve(972): Capacity is now 2.965 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,487 - [NOTICE] simulation.solve(850): Cycle 27/500 (2.319 s elapsed) --------------------\n", + "2021-11-19 15:28:55,487 - [NOTICE] simulation.solve(884): Cycle 27/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,503 - [NOTICE] simulation.solve(884): Cycle 27/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:55,521 - [NOTICE] simulation.solve(884): Cycle 27/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:55,536 - [NOTICE] simulation.solve(884): Cycle 27/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,567 - [NOTICE] simulation.solve(972): Capacity is now 2.959 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,568 - [NOTICE] simulation.solve(850): Cycle 28/500 (2.400 s elapsed) --------------------\n", + "2021-11-19 15:28:55,568 - [NOTICE] simulation.solve(884): Cycle 28/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,583 - [NOTICE] simulation.solve(884): Cycle 28/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:55,602 - [NOTICE] simulation.solve(884): Cycle 28/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:55,617 - [NOTICE] simulation.solve(884): Cycle 28/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,648 - [NOTICE] simulation.solve(972): Capacity is now 2.953 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,649 - [NOTICE] simulation.solve(850): Cycle 29/500 (2.481 s elapsed) --------------------\n", + "2021-11-19 15:28:55,649 - [NOTICE] simulation.solve(884): Cycle 29/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,664 - [NOTICE] simulation.solve(884): Cycle 29/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:55,683 - [NOTICE] simulation.solve(884): Cycle 29/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:55,701 - [NOTICE] simulation.solve(884): Cycle 29/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,732 - [NOTICE] simulation.solve(972): Capacity is now 2.948 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,732 - [NOTICE] simulation.solve(850): Cycle 30/500 (2.564 s elapsed) --------------------\n", + "2021-11-19 15:28:55,733 - [NOTICE] simulation.solve(884): Cycle 30/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,748 - [NOTICE] simulation.solve(884): Cycle 30/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:55,767 - [NOTICE] simulation.solve(884): Cycle 30/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:55,782 - [NOTICE] simulation.solve(884): Cycle 30/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,814 - [NOTICE] simulation.solve(972): Capacity is now 2.942 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,814 - [NOTICE] simulation.solve(850): Cycle 31/500 (2.646 s elapsed) --------------------\n", + "2021-11-19 15:28:55,814 - [NOTICE] simulation.solve(884): Cycle 31/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,830 - [NOTICE] simulation.solve(884): Cycle 31/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:55,848 - [NOTICE] simulation.solve(884): Cycle 31/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:55,864 - [NOTICE] simulation.solve(884): Cycle 31/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,896 - [NOTICE] simulation.solve(972): Capacity is now 2.937 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,896 - [NOTICE] simulation.solve(850): Cycle 32/500 (2.728 s elapsed) --------------------\n", + "2021-11-19 15:28:55,896 - [NOTICE] simulation.solve(884): Cycle 32/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,912 - [NOTICE] simulation.solve(884): Cycle 32/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:55,931 - [NOTICE] simulation.solve(884): Cycle 32/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:55,947 - [NOTICE] simulation.solve(884): Cycle 32/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:55,980 - [NOTICE] simulation.solve(972): Capacity is now 2.931 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:55,981 - [NOTICE] simulation.solve(850): Cycle 33/500 (2.812 s elapsed) --------------------\n", + "2021-11-19 15:28:55,981 - [NOTICE] simulation.solve(884): Cycle 33/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:55,996 - [NOTICE] simulation.solve(884): Cycle 33/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:56,015 - [NOTICE] simulation.solve(884): Cycle 33/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:56,032 - [NOTICE] simulation.solve(884): Cycle 33/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:56,063 - [NOTICE] simulation.solve(972): Capacity is now 2.926 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:56,064 - [NOTICE] simulation.solve(850): Cycle 34/500 (2.895 s elapsed) --------------------\n", + "2021-11-19 15:28:56,064 - [NOTICE] simulation.solve(884): Cycle 34/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:56,080 - [NOTICE] simulation.solve(884): Cycle 34/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:56,100 - [NOTICE] simulation.solve(884): Cycle 34/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:56,114 - [NOTICE] simulation.solve(884): Cycle 34/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:56,149 - [NOTICE] simulation.solve(972): Capacity is now 2.920 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:44,048 - [NOTICE] simulation.solve(843): Cycle 28/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:44,069 - [NOTICE] simulation.solve(843): Cycle 28/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:44,085 - [NOTICE] simulation.solve(843): Cycle 28/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:44,113 - [NOTICE] simulation.solve(843): Cycle 28/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:44,141 - [NOTICE] simulation.solve(921): Capacity is now 2.970 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:44,141 - [NOTICE] simulation.solve(809): Cycle 29/500 (3.291 s elapsed) --------------------\n", - "2021-09-17 01:13:44,141 - [NOTICE] simulation.solve(843): Cycle 29/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:44,168 - [NOTICE] simulation.solve(843): Cycle 29/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:44,192 - [NOTICE] simulation.solve(843): Cycle 29/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:44,211 - [NOTICE] simulation.solve(843): Cycle 29/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:44,248 - [NOTICE] simulation.solve(921): Capacity is now 2.965 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:44,249 - [NOTICE] simulation.solve(809): Cycle 30/500 (3.393 s elapsed) --------------------\n", - "2021-09-17 01:13:44,250 - [NOTICE] simulation.solve(843): Cycle 30/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:44,271 - [NOTICE] simulation.solve(843): Cycle 30/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:44,298 - [NOTICE] simulation.solve(843): Cycle 30/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:44,321 - [NOTICE] simulation.solve(843): Cycle 30/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:44,356 - [NOTICE] simulation.solve(921): Capacity is now 2.960 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:44,358 - [NOTICE] simulation.solve(809): Cycle 31/500 (3.503 s elapsed) --------------------\n", - "2021-09-17 01:13:44,359 - [NOTICE] simulation.solve(843): Cycle 31/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:44,381 - [NOTICE] simulation.solve(843): Cycle 31/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:44,406 - [NOTICE] simulation.solve(843): Cycle 31/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:44,430 - [NOTICE] simulation.solve(843): Cycle 31/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:44,469 - [NOTICE] simulation.solve(921): Capacity is now 2.955 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:44,470 - [NOTICE] simulation.solve(809): Cycle 32/500 (3.615 s elapsed) --------------------\n", - "2021-09-17 01:13:44,471 - [NOTICE] simulation.solve(843): Cycle 32/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:44,495 - [NOTICE] simulation.solve(843): Cycle 32/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:44,521 - [NOTICE] simulation.solve(843): Cycle 32/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:44,544 - [NOTICE] simulation.solve(843): Cycle 32/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:44,577 - [NOTICE] simulation.solve(921): Capacity is now 2.949 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:44,578 - [NOTICE] simulation.solve(809): Cycle 33/500 (3.722 s elapsed) --------------------\n", - "2021-09-17 01:13:44,579 - [NOTICE] simulation.solve(843): Cycle 33/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:44,600 - [NOTICE] simulation.solve(843): Cycle 33/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:44,624 - [NOTICE] simulation.solve(843): Cycle 33/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:44,645 - [NOTICE] simulation.solve(843): Cycle 33/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:44,676 - [NOTICE] simulation.solve(921): Capacity is now 2.944 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:44,679 - [NOTICE] simulation.solve(809): Cycle 34/500 (3.823 s elapsed) --------------------\n", - "2021-09-17 01:13:44,679 - [NOTICE] simulation.solve(843): Cycle 34/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:44,701 - [NOTICE] simulation.solve(843): Cycle 34/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:44,716 - [NOTICE] simulation.solve(843): Cycle 34/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:44,746 - [NOTICE] simulation.solve(843): Cycle 34/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:44,779 - [NOTICE] simulation.solve(921): Capacity is now 2.939 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:44,779 - [NOTICE] simulation.solve(809): Cycle 35/500 (3.924 s elapsed) --------------------\n", - "2021-09-17 01:13:44,779 - [NOTICE] simulation.solve(843): Cycle 35/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:44,789 - [NOTICE] simulation.solve(843): Cycle 35/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:44,830 - [NOTICE] simulation.solve(843): Cycle 35/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:44,851 - [NOTICE] simulation.solve(843): Cycle 35/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:44,891 - [NOTICE] simulation.solve(921): Capacity is now 2.934 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:44,893 - [NOTICE] simulation.solve(809): Cycle 36/500 (4.037 s elapsed) --------------------\n", - "2021-09-17 01:13:44,893 - [NOTICE] simulation.solve(843): Cycle 36/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:44,914 - [NOTICE] simulation.solve(843): Cycle 36/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:44,941 - [NOTICE] simulation.solve(843): Cycle 36/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:44,963 - [NOTICE] simulation.solve(843): Cycle 36/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:44,998 - [NOTICE] simulation.solve(921): Capacity is now 2.929 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:44,998 - [NOTICE] simulation.solve(809): Cycle 37/500 (4.147 s elapsed) --------------------\n", - "2021-09-17 01:13:44,998 - [NOTICE] simulation.solve(843): Cycle 37/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:45,022 - [NOTICE] simulation.solve(843): Cycle 37/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:45,033 - [NOTICE] simulation.solve(843): Cycle 37/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:45,052 - [NOTICE] simulation.solve(843): Cycle 37/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:45,101 - [NOTICE] simulation.solve(921): Capacity is now 2.924 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:45,103 - [NOTICE] simulation.solve(809): Cycle 38/500 (4.247 s elapsed) --------------------\n", - "2021-09-17 01:13:45,103 - [NOTICE] simulation.solve(843): Cycle 38/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:45,123 - [NOTICE] simulation.solve(843): Cycle 38/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:45,149 - [NOTICE] simulation.solve(843): Cycle 38/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:45,159 - [NOTICE] simulation.solve(843): Cycle 38/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:45,196 - [NOTICE] simulation.solve(921): Capacity is now 2.919 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:45,196 - [NOTICE] simulation.solve(809): Cycle 39/500 (4.348 s elapsed) --------------------\n", - "2021-09-17 01:13:45,196 - [NOTICE] simulation.solve(843): Cycle 39/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:45,224 - [NOTICE] simulation.solve(843): Cycle 39/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:45,240 - [NOTICE] simulation.solve(843): Cycle 39/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:45,251 - [NOTICE] simulation.solve(843): Cycle 39/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:45,291 - [NOTICE] simulation.solve(921): Capacity is now 2.914 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:45,291 - [NOTICE] simulation.solve(809): Cycle 40/500 (4.444 s elapsed) --------------------\n", - "2021-09-17 01:13:45,291 - [NOTICE] simulation.solve(843): Cycle 40/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:45,313 - [NOTICE] simulation.solve(843): Cycle 40/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:45,342 - [NOTICE] simulation.solve(843): Cycle 40/500, step 3/4: Charge at 1C until 4.2V\n" + "2021-11-19 15:28:56,150 - [NOTICE] simulation.solve(850): Cycle 35/500 (2.982 s elapsed) --------------------\n", + "2021-11-19 15:28:56,150 - [NOTICE] simulation.solve(884): Cycle 35/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:56,168 - [NOTICE] simulation.solve(884): Cycle 35/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:56,188 - [NOTICE] simulation.solve(884): Cycle 35/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:56,207 - [NOTICE] simulation.solve(884): Cycle 35/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:56,247 - [NOTICE] simulation.solve(972): Capacity is now 2.915 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:56,247 - [NOTICE] simulation.solve(850): Cycle 36/500 (3.079 s elapsed) --------------------\n", + "2021-11-19 15:28:56,247 - [NOTICE] simulation.solve(884): Cycle 36/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:56,265 - [NOTICE] simulation.solve(884): Cycle 36/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:56,284 - [NOTICE] simulation.solve(884): Cycle 36/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:56,298 - [NOTICE] simulation.solve(884): Cycle 36/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:56,332 - [NOTICE] simulation.solve(972): Capacity is now 2.910 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:56,332 - [NOTICE] simulation.solve(850): Cycle 37/500 (3.164 s elapsed) --------------------\n", + "2021-11-19 15:28:56,333 - [NOTICE] simulation.solve(884): Cycle 37/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:56,350 - [NOTICE] simulation.solve(884): Cycle 37/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:56,369 - [NOTICE] simulation.solve(884): Cycle 37/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:56,385 - [NOTICE] simulation.solve(884): Cycle 37/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:56,418 - [NOTICE] simulation.solve(972): Capacity is now 2.904 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:56,419 - [NOTICE] simulation.solve(850): Cycle 38/500 (3.250 s elapsed) --------------------\n", + "2021-11-19 15:28:56,419 - [NOTICE] simulation.solve(884): Cycle 38/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:56,437 - [NOTICE] simulation.solve(884): Cycle 38/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:56,456 - [NOTICE] simulation.solve(884): Cycle 38/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:56,470 - [NOTICE] simulation.solve(884): Cycle 38/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:56,504 - [NOTICE] simulation.solve(972): Capacity is now 2.899 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:56,504 - [NOTICE] simulation.solve(850): Cycle 39/500 (3.336 s elapsed) --------------------\n", + "2021-11-19 15:28:56,504 - [NOTICE] simulation.solve(884): Cycle 39/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:56,521 - [NOTICE] simulation.solve(884): Cycle 39/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:56,540 - [NOTICE] simulation.solve(884): Cycle 39/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:56,553 - [NOTICE] simulation.solve(884): Cycle 39/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:56,588 - [NOTICE] simulation.solve(972): Capacity is now 2.893 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:56,588 - [NOTICE] simulation.solve(850): Cycle 40/500 (3.420 s elapsed) --------------------\n", + "2021-11-19 15:28:56,588 - [NOTICE] simulation.solve(884): Cycle 40/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:56,606 - [NOTICE] simulation.solve(884): Cycle 40/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:56,624 - [NOTICE] simulation.solve(884): Cycle 40/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:56,638 - [NOTICE] simulation.solve(884): Cycle 40/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:56,670 - [NOTICE] simulation.solve(972): Capacity is now 2.888 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:56,671 - [NOTICE] simulation.solve(850): Cycle 41/500 (3.503 s elapsed) --------------------\n", + "2021-11-19 15:28:56,671 - [NOTICE] simulation.solve(884): Cycle 41/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:56,688 - [NOTICE] simulation.solve(884): Cycle 41/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:56,707 - [NOTICE] simulation.solve(884): Cycle 41/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:56,722 - [NOTICE] simulation.solve(884): Cycle 41/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:56,754 - [NOTICE] simulation.solve(972): Capacity is now 2.882 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:56,755 - [NOTICE] simulation.solve(850): Cycle 42/500 (3.587 s elapsed) --------------------\n", + "2021-11-19 15:28:56,755 - [NOTICE] simulation.solve(884): Cycle 42/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:56,772 - [NOTICE] simulation.solve(884): Cycle 42/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:56,791 - [NOTICE] simulation.solve(884): Cycle 42/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:56,805 - [NOTICE] simulation.solve(884): Cycle 42/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:56,838 - [NOTICE] simulation.solve(972): Capacity is now 2.876 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:56,839 - [NOTICE] simulation.solve(850): Cycle 43/500 (3.670 s elapsed) --------------------\n", + "2021-11-19 15:28:56,839 - [NOTICE] simulation.solve(884): Cycle 43/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:56,856 - [NOTICE] simulation.solve(884): Cycle 43/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:56,875 - [NOTICE] simulation.solve(884): Cycle 43/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:56,890 - [NOTICE] simulation.solve(884): Cycle 43/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:56,923 - [NOTICE] simulation.solve(972): Capacity is now 2.871 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:56,924 - [NOTICE] simulation.solve(850): Cycle 44/500 (3.756 s elapsed) --------------------\n", + "2021-11-19 15:28:56,925 - [NOTICE] simulation.solve(884): Cycle 44/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:56,942 - [NOTICE] simulation.solve(884): Cycle 44/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:56,961 - [NOTICE] simulation.solve(884): Cycle 44/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:56,977 - [NOTICE] simulation.solve(884): Cycle 44/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:57,011 - [NOTICE] simulation.solve(972): Capacity is now 2.865 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:57,012 - [NOTICE] simulation.solve(850): Cycle 45/500 (3.844 s elapsed) --------------------\n", + "2021-11-19 15:28:57,012 - [NOTICE] simulation.solve(884): Cycle 45/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:57,030 - [NOTICE] simulation.solve(884): Cycle 45/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:57,049 - [NOTICE] simulation.solve(884): Cycle 45/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:57,067 - [NOTICE] simulation.solve(884): Cycle 45/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:57,100 - [NOTICE] simulation.solve(972): Capacity is now 2.859 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:57,101 - [NOTICE] simulation.solve(850): Cycle 46/500 (3.933 s elapsed) --------------------\n", + "2021-11-19 15:28:57,101 - [NOTICE] simulation.solve(884): Cycle 46/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:57,119 - [NOTICE] simulation.solve(884): Cycle 46/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:57,137 - [NOTICE] simulation.solve(884): Cycle 46/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:57,152 - [NOTICE] simulation.solve(884): Cycle 46/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:57,187 - [NOTICE] simulation.solve(972): Capacity is now 2.853 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:57,188 - [NOTICE] simulation.solve(850): Cycle 47/500 (4.019 s elapsed) --------------------\n", + "2021-11-19 15:28:57,188 - [NOTICE] simulation.solve(884): Cycle 47/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:57,206 - [NOTICE] simulation.solve(884): Cycle 47/500, step 2/4: Rest for 1 hour\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:45,351 - [NOTICE] simulation.solve(843): Cycle 40/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:45,404 - [NOTICE] simulation.solve(921): Capacity is now 2.909 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:45,404 - [NOTICE] simulation.solve(809): Cycle 41/500 (4.549 s elapsed) --------------------\n", - "2021-09-17 01:13:45,405 - [NOTICE] simulation.solve(843): Cycle 41/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:45,430 - [NOTICE] simulation.solve(843): Cycle 41/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:45,458 - [NOTICE] simulation.solve(843): Cycle 41/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:45,476 - [NOTICE] simulation.solve(843): Cycle 41/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:45,516 - [NOTICE] simulation.solve(921): Capacity is now 2.904 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:45,517 - [NOTICE] simulation.solve(809): Cycle 42/500 (4.662 s elapsed) --------------------\n", - "2021-09-17 01:13:45,518 - [NOTICE] simulation.solve(843): Cycle 42/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:45,541 - [NOTICE] simulation.solve(843): Cycle 42/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:45,567 - [NOTICE] simulation.solve(843): Cycle 42/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:45,581 - [NOTICE] simulation.solve(843): Cycle 42/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:45,622 - [NOTICE] simulation.solve(921): Capacity is now 2.899 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:45,622 - [NOTICE] simulation.solve(809): Cycle 43/500 (4.767 s elapsed) --------------------\n", - "2021-09-17 01:13:45,623 - [NOTICE] simulation.solve(843): Cycle 43/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:45,645 - [NOTICE] simulation.solve(843): Cycle 43/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:45,669 - [NOTICE] simulation.solve(843): Cycle 43/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:45,686 - [NOTICE] simulation.solve(843): Cycle 43/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:45,717 - [NOTICE] simulation.solve(921): Capacity is now 2.894 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:45,723 - [NOTICE] simulation.solve(809): Cycle 44/500 (4.868 s elapsed) --------------------\n", - "2021-09-17 01:13:45,724 - [NOTICE] simulation.solve(843): Cycle 44/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:45,747 - [NOTICE] simulation.solve(843): Cycle 44/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:45,772 - [NOTICE] simulation.solve(843): Cycle 44/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:45,791 - [NOTICE] simulation.solve(843): Cycle 44/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:45,825 - [NOTICE] simulation.solve(921): Capacity is now 2.889 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:45,825 - [NOTICE] simulation.solve(809): Cycle 45/500 (4.976 s elapsed) --------------------\n", - "2021-09-17 01:13:45,825 - [NOTICE] simulation.solve(843): Cycle 45/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:45,856 - [NOTICE] simulation.solve(843): Cycle 45/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:45,880 - [NOTICE] simulation.solve(843): Cycle 45/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:45,896 - [NOTICE] simulation.solve(843): Cycle 45/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:45,933 - [NOTICE] simulation.solve(921): Capacity is now 2.884 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:45,933 - [NOTICE] simulation.solve(809): Cycle 46/500 (5.078 s elapsed) --------------------\n", - "2021-09-17 01:13:45,934 - [NOTICE] simulation.solve(843): Cycle 46/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:45,957 - [NOTICE] simulation.solve(843): Cycle 46/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:45,981 - [NOTICE] simulation.solve(843): Cycle 46/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:45,998 - [NOTICE] simulation.solve(843): Cycle 46/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:46,035 - [NOTICE] simulation.solve(921): Capacity is now 2.879 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:46,036 - [NOTICE] simulation.solve(809): Cycle 47/500 (5.181 s elapsed) --------------------\n", - "2021-09-17 01:13:46,037 - [NOTICE] simulation.solve(843): Cycle 47/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:46,062 - [NOTICE] simulation.solve(843): Cycle 47/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:46,089 - [NOTICE] simulation.solve(843): Cycle 47/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:46,107 - [NOTICE] simulation.solve(843): Cycle 47/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:46,146 - [NOTICE] simulation.solve(921): Capacity is now 2.874 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:46,147 - [NOTICE] simulation.solve(809): Cycle 48/500 (5.291 s elapsed) --------------------\n", - "2021-09-17 01:13:46,148 - [NOTICE] simulation.solve(843): Cycle 48/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:46,170 - [NOTICE] simulation.solve(843): Cycle 48/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:46,195 - [NOTICE] simulation.solve(843): Cycle 48/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:46,213 - [NOTICE] simulation.solve(843): Cycle 48/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:46,250 - [NOTICE] simulation.solve(921): Capacity is now 2.869 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:46,250 - [NOTICE] simulation.solve(809): Cycle 49/500 (5.398 s elapsed) --------------------\n", - "2021-09-17 01:13:46,250 - [NOTICE] simulation.solve(843): Cycle 49/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:46,280 - [NOTICE] simulation.solve(843): Cycle 49/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:46,306 - [NOTICE] simulation.solve(843): Cycle 49/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:46,329 - [NOTICE] simulation.solve(843): Cycle 49/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:46,369 - [NOTICE] simulation.solve(921): Capacity is now 2.864 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:46,369 - [NOTICE] simulation.solve(809): Cycle 50/500 (5.514 s elapsed) --------------------\n", - "2021-09-17 01:13:46,370 - [NOTICE] simulation.solve(843): Cycle 50/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:46,395 - [NOTICE] simulation.solve(843): Cycle 50/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:46,422 - [NOTICE] simulation.solve(843): Cycle 50/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:46,442 - [NOTICE] simulation.solve(843): Cycle 50/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:46,467 - [NOTICE] simulation.solve(921): Capacity is now 2.858 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:46,467 - [NOTICE] simulation.solve(809): Cycle 51/500 (5.622 s elapsed) --------------------\n", - "2021-09-17 01:13:46,467 - [NOTICE] simulation.solve(843): Cycle 51/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:46,502 - [NOTICE] simulation.solve(843): Cycle 51/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:46,526 - [NOTICE] simulation.solve(843): Cycle 51/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:46,534 - [NOTICE] simulation.solve(843): Cycle 51/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:46,580 - [NOTICE] simulation.solve(921): Capacity is now 2.853 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:46,581 - [NOTICE] simulation.solve(809): Cycle 52/500 (5.725 s elapsed) --------------------\n", - "2021-09-17 01:13:46,582 - [NOTICE] simulation.solve(843): Cycle 52/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:46,604 - [NOTICE] simulation.solve(843): Cycle 52/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:46,617 - [NOTICE] simulation.solve(843): Cycle 52/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:46,647 - [NOTICE] simulation.solve(843): Cycle 52/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:46,684 - [NOTICE] simulation.solve(921): Capacity is now 2.848 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:46,685 - [NOTICE] simulation.solve(809): Cycle 53/500 (5.829 s elapsed) --------------------\n" + "2021-11-19 15:28:57,225 - [NOTICE] simulation.solve(884): Cycle 47/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:57,241 - [NOTICE] simulation.solve(884): Cycle 47/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:57,276 - [NOTICE] simulation.solve(972): Capacity is now 2.847 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:57,277 - [NOTICE] simulation.solve(850): Cycle 48/500 (4.109 s elapsed) --------------------\n", + "2021-11-19 15:28:57,278 - [NOTICE] simulation.solve(884): Cycle 48/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:57,295 - [NOTICE] simulation.solve(884): Cycle 48/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:57,315 - [NOTICE] simulation.solve(884): Cycle 48/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:57,331 - [NOTICE] simulation.solve(884): Cycle 48/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:57,365 - [NOTICE] simulation.solve(972): Capacity is now 2.841 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:57,366 - [NOTICE] simulation.solve(850): Cycle 49/500 (4.198 s elapsed) --------------------\n", + "2021-11-19 15:28:57,366 - [NOTICE] simulation.solve(884): Cycle 49/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:57,384 - [NOTICE] simulation.solve(884): Cycle 49/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:57,403 - [NOTICE] simulation.solve(884): Cycle 49/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:57,422 - [NOTICE] simulation.solve(884): Cycle 49/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:57,457 - [NOTICE] simulation.solve(972): Capacity is now 2.835 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:57,458 - [NOTICE] simulation.solve(850): Cycle 50/500 (4.290 s elapsed) --------------------\n", + "2021-11-19 15:28:57,458 - [NOTICE] simulation.solve(884): Cycle 50/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:57,481 - [NOTICE] simulation.solve(884): Cycle 50/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:57,502 - [NOTICE] simulation.solve(884): Cycle 50/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:57,518 - [NOTICE] simulation.solve(884): Cycle 50/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:57,553 - [NOTICE] simulation.solve(972): Capacity is now 2.829 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:57,553 - [NOTICE] simulation.solve(850): Cycle 51/500 (4.385 s elapsed) --------------------\n", + "2021-11-19 15:28:57,553 - [NOTICE] simulation.solve(884): Cycle 51/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:57,568 - [NOTICE] simulation.solve(884): Cycle 51/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:57,586 - [NOTICE] simulation.solve(884): Cycle 51/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:57,601 - [NOTICE] simulation.solve(884): Cycle 51/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:57,636 - [NOTICE] simulation.solve(972): Capacity is now 2.823 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:57,636 - [NOTICE] simulation.solve(850): Cycle 52/500 (4.468 s elapsed) --------------------\n", + "2021-11-19 15:28:57,636 - [NOTICE] simulation.solve(884): Cycle 52/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:57,651 - [NOTICE] simulation.solve(884): Cycle 52/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:57,669 - [NOTICE] simulation.solve(884): Cycle 52/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:57,684 - [NOTICE] simulation.solve(884): Cycle 52/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:57,718 - [NOTICE] simulation.solve(972): Capacity is now 2.817 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:57,719 - [NOTICE] simulation.solve(850): Cycle 53/500 (4.550 s elapsed) --------------------\n", + "2021-11-19 15:28:57,719 - [NOTICE] simulation.solve(884): Cycle 53/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:57,733 - [NOTICE] simulation.solve(884): Cycle 53/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:57,752 - [NOTICE] simulation.solve(884): Cycle 53/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:57,769 - [NOTICE] simulation.solve(884): Cycle 53/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:57,803 - [NOTICE] simulation.solve(972): Capacity is now 2.811 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:57,803 - [NOTICE] simulation.solve(850): Cycle 54/500 (4.635 s elapsed) --------------------\n", + "2021-11-19 15:28:57,804 - [NOTICE] simulation.solve(884): Cycle 54/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:57,819 - [NOTICE] simulation.solve(884): Cycle 54/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:57,837 - [NOTICE] simulation.solve(884): Cycle 54/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:57,853 - [NOTICE] simulation.solve(884): Cycle 54/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:57,887 - [NOTICE] simulation.solve(972): Capacity is now 2.804 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:57,888 - [NOTICE] simulation.solve(850): Cycle 55/500 (4.720 s elapsed) --------------------\n", + "2021-11-19 15:28:57,888 - [NOTICE] simulation.solve(884): Cycle 55/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:57,903 - [NOTICE] simulation.solve(884): Cycle 55/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:57,922 - [NOTICE] simulation.solve(884): Cycle 55/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:57,936 - [NOTICE] simulation.solve(884): Cycle 55/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:57,971 - [NOTICE] simulation.solve(972): Capacity is now 2.798 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:57,972 - [NOTICE] simulation.solve(850): Cycle 56/500 (4.803 s elapsed) --------------------\n", + "2021-11-19 15:28:57,972 - [NOTICE] simulation.solve(884): Cycle 56/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:57,990 - [NOTICE] simulation.solve(884): Cycle 56/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:58,009 - [NOTICE] simulation.solve(884): Cycle 56/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:58,021 - [NOTICE] simulation.solve(884): Cycle 56/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:58,057 - [NOTICE] simulation.solve(972): Capacity is now 2.791 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:58,057 - [NOTICE] simulation.solve(850): Cycle 57/500 (4.889 s elapsed) --------------------\n", + "2021-11-19 15:28:58,058 - [NOTICE] simulation.solve(884): Cycle 57/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:58,074 - [NOTICE] simulation.solve(884): Cycle 57/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:58,093 - [NOTICE] simulation.solve(884): Cycle 57/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:58,108 - [NOTICE] simulation.solve(884): Cycle 57/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:58,141 - [NOTICE] simulation.solve(972): Capacity is now 2.785 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:58,142 - [NOTICE] simulation.solve(850): Cycle 58/500 (4.973 s elapsed) --------------------\n", + "2021-11-19 15:28:58,142 - [NOTICE] simulation.solve(884): Cycle 58/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:58,157 - [NOTICE] simulation.solve(884): Cycle 58/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:58,176 - [NOTICE] simulation.solve(884): Cycle 58/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:58,189 - [NOTICE] simulation.solve(884): Cycle 58/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:58,222 - [NOTICE] simulation.solve(972): Capacity is now 2.778 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:58,223 - [NOTICE] simulation.solve(850): Cycle 59/500 (5.055 s elapsed) --------------------\n", + "2021-11-19 15:28:58,223 - [NOTICE] simulation.solve(884): Cycle 59/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:58,239 - [NOTICE] simulation.solve(884): Cycle 59/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:58,258 - [NOTICE] simulation.solve(884): Cycle 59/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:58,271 - [NOTICE] simulation.solve(884): Cycle 59/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:58,306 - [NOTICE] simulation.solve(972): Capacity is now 2.771 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:46,685 - [NOTICE] simulation.solve(843): Cycle 53/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:46,708 - [NOTICE] simulation.solve(843): Cycle 53/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:46,735 - [NOTICE] simulation.solve(843): Cycle 53/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:46,754 - [NOTICE] simulation.solve(843): Cycle 53/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:46,791 - [NOTICE] simulation.solve(921): Capacity is now 2.842 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:46,792 - [NOTICE] simulation.solve(809): Cycle 54/500 (5.937 s elapsed) --------------------\n", - "2021-09-17 01:13:46,793 - [NOTICE] simulation.solve(843): Cycle 54/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:46,816 - [NOTICE] simulation.solve(843): Cycle 54/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:46,845 - [NOTICE] simulation.solve(843): Cycle 54/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:46,865 - [NOTICE] simulation.solve(843): Cycle 54/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:46,902 - [NOTICE] simulation.solve(921): Capacity is now 2.837 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:46,903 - [NOTICE] simulation.solve(809): Cycle 55/500 (6.048 s elapsed) --------------------\n", - "2021-09-17 01:13:46,904 - [NOTICE] simulation.solve(843): Cycle 55/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:46,926 - [NOTICE] simulation.solve(843): Cycle 55/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:46,951 - [NOTICE] simulation.solve(843): Cycle 55/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:46,971 - [NOTICE] simulation.solve(843): Cycle 55/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:47,008 - [NOTICE] simulation.solve(921): Capacity is now 2.831 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:47,009 - [NOTICE] simulation.solve(809): Cycle 56/500 (6.153 s elapsed) --------------------\n", - "2021-09-17 01:13:47,009 - [NOTICE] simulation.solve(843): Cycle 56/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:47,031 - [NOTICE] simulation.solve(843): Cycle 56/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:47,042 - [NOTICE] simulation.solve(843): Cycle 56/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:47,059 - [NOTICE] simulation.solve(843): Cycle 56/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:47,111 - [NOTICE] simulation.solve(921): Capacity is now 2.826 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:47,111 - [NOTICE] simulation.solve(809): Cycle 57/500 (6.256 s elapsed) --------------------\n", - "2021-09-17 01:13:47,112 - [NOTICE] simulation.solve(843): Cycle 57/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:47,131 - [NOTICE] simulation.solve(843): Cycle 57/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:47,143 - [NOTICE] simulation.solve(843): Cycle 57/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:47,175 - [NOTICE] simulation.solve(843): Cycle 57/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:47,201 - [NOTICE] simulation.solve(921): Capacity is now 2.820 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:47,201 - [NOTICE] simulation.solve(809): Cycle 58/500 (6.359 s elapsed) --------------------\n", - "2021-09-17 01:13:47,201 - [NOTICE] simulation.solve(843): Cycle 58/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:47,236 - [NOTICE] simulation.solve(843): Cycle 58/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:47,261 - [NOTICE] simulation.solve(843): Cycle 58/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:47,280 - [NOTICE] simulation.solve(843): Cycle 58/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:47,309 - [NOTICE] simulation.solve(921): Capacity is now 2.814 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:47,309 - [NOTICE] simulation.solve(809): Cycle 59/500 (6.465 s elapsed) --------------------\n", - "2021-09-17 01:13:47,309 - [NOTICE] simulation.solve(843): Cycle 59/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:47,341 - [NOTICE] simulation.solve(843): Cycle 59/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:47,365 - [NOTICE] simulation.solve(843): Cycle 59/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:47,387 - [NOTICE] simulation.solve(843): Cycle 59/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:47,425 - [NOTICE] simulation.solve(921): Capacity is now 2.809 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:47,426 - [NOTICE] simulation.solve(809): Cycle 60/500 (6.569 s elapsed) --------------------\n", - "2021-09-17 01:13:47,426 - [NOTICE] simulation.solve(843): Cycle 60/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:47,446 - [NOTICE] simulation.solve(843): Cycle 60/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:47,471 - [NOTICE] simulation.solve(843): Cycle 60/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:47,488 - [NOTICE] simulation.solve(843): Cycle 60/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:47,518 - [NOTICE] simulation.solve(921): Capacity is now 2.803 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:47,518 - [NOTICE] simulation.solve(809): Cycle 61/500 (6.672 s elapsed) --------------------\n", - "2021-09-17 01:13:47,518 - [NOTICE] simulation.solve(843): Cycle 61/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:47,549 - [NOTICE] simulation.solve(843): Cycle 61/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:47,574 - [NOTICE] simulation.solve(843): Cycle 61/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:47,590 - [NOTICE] simulation.solve(843): Cycle 61/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:47,618 - [NOTICE] simulation.solve(921): Capacity is now 2.797 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:47,618 - [NOTICE] simulation.solve(809): Cycle 62/500 (6.776 s elapsed) --------------------\n", - "2021-09-17 01:13:47,633 - [NOTICE] simulation.solve(843): Cycle 62/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:47,653 - [NOTICE] simulation.solve(843): Cycle 62/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:47,678 - [NOTICE] simulation.solve(843): Cycle 62/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:47,695 - [NOTICE] simulation.solve(843): Cycle 62/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:47,725 - [NOTICE] simulation.solve(921): Capacity is now 2.791 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:47,725 - [NOTICE] simulation.solve(809): Cycle 63/500 (6.878 s elapsed) --------------------\n", - "2021-09-17 01:13:47,725 - [NOTICE] simulation.solve(843): Cycle 63/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:47,754 - [NOTICE] simulation.solve(843): Cycle 63/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:47,778 - [NOTICE] simulation.solve(843): Cycle 63/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:47,795 - [NOTICE] simulation.solve(843): Cycle 63/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:47,835 - [NOTICE] simulation.solve(921): Capacity is now 2.785 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:47,836 - [NOTICE] simulation.solve(809): Cycle 64/500 (6.980 s elapsed) --------------------\n", - "2021-09-17 01:13:47,837 - [NOTICE] simulation.solve(843): Cycle 64/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:47,860 - [NOTICE] simulation.solve(843): Cycle 64/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:47,889 - [NOTICE] simulation.solve(843): Cycle 64/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:47,906 - [NOTICE] simulation.solve(843): Cycle 64/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:47,950 - [NOTICE] simulation.solve(921): Capacity is now 2.779 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:47,951 - [NOTICE] simulation.solve(809): Cycle 65/500 (7.095 s elapsed) --------------------\n", - "2021-09-17 01:13:47,952 - [NOTICE] simulation.solve(843): Cycle 65/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:47,972 - [NOTICE] simulation.solve(843): Cycle 65/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:47,999 - [NOTICE] simulation.solve(843): Cycle 65/500, step 3/4: Charge at 1C until 4.2V\n" + "2021-11-19 15:28:58,306 - [NOTICE] simulation.solve(850): Cycle 60/500 (5.138 s elapsed) --------------------\n", + "2021-11-19 15:28:58,307 - [NOTICE] simulation.solve(884): Cycle 60/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:58,322 - [NOTICE] simulation.solve(884): Cycle 60/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:58,342 - [NOTICE] simulation.solve(884): Cycle 60/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:58,355 - [NOTICE] simulation.solve(884): Cycle 60/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:58,394 - [NOTICE] simulation.solve(972): Capacity is now 2.765 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:58,395 - [NOTICE] simulation.solve(850): Cycle 61/500 (5.226 s elapsed) --------------------\n", + "2021-11-19 15:28:58,395 - [NOTICE] simulation.solve(884): Cycle 61/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:58,411 - [NOTICE] simulation.solve(884): Cycle 61/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:58,430 - [NOTICE] simulation.solve(884): Cycle 61/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:58,444 - [NOTICE] simulation.solve(884): Cycle 61/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:58,481 - [NOTICE] simulation.solve(972): Capacity is now 2.758 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:58,482 - [NOTICE] simulation.solve(850): Cycle 62/500 (5.314 s elapsed) --------------------\n", + "2021-11-19 15:28:58,483 - [NOTICE] simulation.solve(884): Cycle 62/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:58,498 - [NOTICE] simulation.solve(884): Cycle 62/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:58,516 - [NOTICE] simulation.solve(884): Cycle 62/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:58,529 - [NOTICE] simulation.solve(884): Cycle 62/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:58,567 - [NOTICE] simulation.solve(972): Capacity is now 2.751 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:58,567 - [NOTICE] simulation.solve(850): Cycle 63/500 (5.399 s elapsed) --------------------\n", + "2021-11-19 15:28:58,568 - [NOTICE] simulation.solve(884): Cycle 63/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:58,584 - [NOTICE] simulation.solve(884): Cycle 63/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:58,604 - [NOTICE] simulation.solve(884): Cycle 63/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:58,617 - [NOTICE] simulation.solve(884): Cycle 63/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:58,655 - [NOTICE] simulation.solve(972): Capacity is now 2.744 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:58,656 - [NOTICE] simulation.solve(850): Cycle 64/500 (5.488 s elapsed) --------------------\n", + "2021-11-19 15:28:58,656 - [NOTICE] simulation.solve(884): Cycle 64/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:58,673 - [NOTICE] simulation.solve(884): Cycle 64/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:58,692 - [NOTICE] simulation.solve(884): Cycle 64/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:58,706 - [NOTICE] simulation.solve(884): Cycle 64/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:58,743 - [NOTICE] simulation.solve(972): Capacity is now 2.737 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:58,743 - [NOTICE] simulation.solve(850): Cycle 65/500 (5.575 s elapsed) --------------------\n", + "2021-11-19 15:28:58,744 - [NOTICE] simulation.solve(884): Cycle 65/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:58,760 - [NOTICE] simulation.solve(884): Cycle 65/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:58,778 - [NOTICE] simulation.solve(884): Cycle 65/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:58,793 - [NOTICE] simulation.solve(884): Cycle 65/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:58,831 - [NOTICE] simulation.solve(972): Capacity is now 2.731 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:58,831 - [NOTICE] simulation.solve(850): Cycle 66/500 (5.663 s elapsed) --------------------\n", + "2021-11-19 15:28:58,831 - [NOTICE] simulation.solve(884): Cycle 66/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:58,848 - [NOTICE] simulation.solve(884): Cycle 66/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:58,866 - [NOTICE] simulation.solve(884): Cycle 66/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:58,881 - [NOTICE] simulation.solve(884): Cycle 66/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:58,917 - [NOTICE] simulation.solve(972): Capacity is now 2.724 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:58,917 - [NOTICE] simulation.solve(850): Cycle 67/500 (5.749 s elapsed) --------------------\n", + "2021-11-19 15:28:58,918 - [NOTICE] simulation.solve(884): Cycle 67/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:58,934 - [NOTICE] simulation.solve(884): Cycle 67/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:58,953 - [NOTICE] simulation.solve(884): Cycle 67/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:58,969 - [NOTICE] simulation.solve(884): Cycle 67/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:59,006 - [NOTICE] simulation.solve(972): Capacity is now 2.717 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:59,006 - [NOTICE] simulation.solve(850): Cycle 68/500 (5.838 s elapsed) --------------------\n", + "2021-11-19 15:28:59,006 - [NOTICE] simulation.solve(884): Cycle 68/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:59,028 - [NOTICE] simulation.solve(884): Cycle 68/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:59,057 - [NOTICE] simulation.solve(884): Cycle 68/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:59,074 - [NOTICE] simulation.solve(884): Cycle 68/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:59,114 - [NOTICE] simulation.solve(972): Capacity is now 2.710 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:59,115 - [NOTICE] simulation.solve(850): Cycle 69/500 (5.946 s elapsed) --------------------\n", + "2021-11-19 15:28:59,115 - [NOTICE] simulation.solve(884): Cycle 69/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:59,133 - [NOTICE] simulation.solve(884): Cycle 69/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:59,153 - [NOTICE] simulation.solve(884): Cycle 69/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:59,171 - [NOTICE] simulation.solve(884): Cycle 69/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:59,214 - [NOTICE] simulation.solve(972): Capacity is now 2.703 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:59,215 - [NOTICE] simulation.solve(850): Cycle 70/500 (6.047 s elapsed) --------------------\n", + "2021-11-19 15:28:59,216 - [NOTICE] simulation.solve(884): Cycle 70/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:59,234 - [NOTICE] simulation.solve(884): Cycle 70/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:59,254 - [NOTICE] simulation.solve(884): Cycle 70/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:59,270 - [NOTICE] simulation.solve(884): Cycle 70/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:59,312 - [NOTICE] simulation.solve(972): Capacity is now 2.696 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:59,313 - [NOTICE] simulation.solve(850): Cycle 71/500 (6.144 s elapsed) --------------------\n", + "2021-11-19 15:28:59,313 - [NOTICE] simulation.solve(884): Cycle 71/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:59,333 - [NOTICE] simulation.solve(884): Cycle 71/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:59,356 - [NOTICE] simulation.solve(884): Cycle 71/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:59,375 - [NOTICE] simulation.solve(884): Cycle 71/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:59,418 - [NOTICE] simulation.solve(972): Capacity is now 2.689 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:59,419 - [NOTICE] simulation.solve(850): Cycle 72/500 (6.251 s elapsed) --------------------\n", + "2021-11-19 15:28:59,419 - [NOTICE] simulation.solve(884): Cycle 72/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:59,439 - [NOTICE] simulation.solve(884): Cycle 72/500, step 2/4: Rest for 1 hour\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:48,015 - [NOTICE] simulation.solve(843): Cycle 65/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:48,054 - [NOTICE] simulation.solve(921): Capacity is now 2.773 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:48,055 - [NOTICE] simulation.solve(809): Cycle 66/500 (7.199 s elapsed) --------------------\n", - "2021-09-17 01:13:48,055 - [NOTICE] simulation.solve(843): Cycle 66/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:48,066 - [NOTICE] simulation.solve(843): Cycle 66/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:48,086 - [NOTICE] simulation.solve(843): Cycle 66/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:48,103 - [NOTICE] simulation.solve(843): Cycle 66/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:48,161 - [NOTICE] simulation.solve(921): Capacity is now 2.767 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:48,163 - [NOTICE] simulation.solve(809): Cycle 67/500 (7.307 s elapsed) --------------------\n", - "2021-09-17 01:13:48,163 - [NOTICE] simulation.solve(843): Cycle 67/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:48,186 - [NOTICE] simulation.solve(843): Cycle 67/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:48,213 - [NOTICE] simulation.solve(843): Cycle 67/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:48,233 - [NOTICE] simulation.solve(843): Cycle 67/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:48,260 - [NOTICE] simulation.solve(921): Capacity is now 2.761 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:48,260 - [NOTICE] simulation.solve(809): Cycle 68/500 (7.417 s elapsed) --------------------\n", - "2021-09-17 01:13:48,260 - [NOTICE] simulation.solve(843): Cycle 68/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:48,295 - [NOTICE] simulation.solve(843): Cycle 68/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:48,319 - [NOTICE] simulation.solve(843): Cycle 68/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:48,325 - [NOTICE] simulation.solve(843): Cycle 68/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:48,375 - [NOTICE] simulation.solve(921): Capacity is now 2.755 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:48,376 - [NOTICE] simulation.solve(809): Cycle 69/500 (7.520 s elapsed) --------------------\n", - "2021-09-17 01:13:48,377 - [NOTICE] simulation.solve(843): Cycle 69/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:48,397 - [NOTICE] simulation.solve(843): Cycle 69/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:48,422 - [NOTICE] simulation.solve(843): Cycle 69/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:48,439 - [NOTICE] simulation.solve(843): Cycle 69/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:48,478 - [NOTICE] simulation.solve(921): Capacity is now 2.749 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:48,479 - [NOTICE] simulation.solve(809): Cycle 70/500 (7.623 s elapsed) --------------------\n", - "2021-09-17 01:13:48,480 - [NOTICE] simulation.solve(843): Cycle 70/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:48,501 - [NOTICE] simulation.solve(843): Cycle 70/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:48,527 - [NOTICE] simulation.solve(843): Cycle 70/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:48,545 - [NOTICE] simulation.solve(843): Cycle 70/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:48,568 - [NOTICE] simulation.solve(921): Capacity is now 2.743 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:48,584 - [NOTICE] simulation.solve(809): Cycle 71/500 (7.728 s elapsed) --------------------\n", - "2021-09-17 01:13:48,584 - [NOTICE] simulation.solve(843): Cycle 71/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:48,604 - [NOTICE] simulation.solve(843): Cycle 71/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:48,623 - [NOTICE] simulation.solve(843): Cycle 71/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:48,633 - [NOTICE] simulation.solve(843): Cycle 71/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:48,671 - [NOTICE] simulation.solve(921): Capacity is now 2.737 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:48,671 - [NOTICE] simulation.solve(809): Cycle 72/500 (7.826 s elapsed) --------------------\n", - "2021-09-17 01:13:48,671 - [NOTICE] simulation.solve(843): Cycle 72/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:48,705 - [NOTICE] simulation.solve(843): Cycle 72/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:48,733 - [NOTICE] simulation.solve(843): Cycle 72/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:48,742 - [NOTICE] simulation.solve(843): Cycle 72/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:48,789 - [NOTICE] simulation.solve(921): Capacity is now 2.731 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:48,790 - [NOTICE] simulation.solve(809): Cycle 73/500 (7.934 s elapsed) --------------------\n", - "2021-09-17 01:13:48,791 - [NOTICE] simulation.solve(843): Cycle 73/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:48,814 - [NOTICE] simulation.solve(843): Cycle 73/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:48,838 - [NOTICE] simulation.solve(843): Cycle 73/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:48,851 - [NOTICE] simulation.solve(843): Cycle 73/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:48,891 - [NOTICE] simulation.solve(921): Capacity is now 2.725 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:48,891 - [NOTICE] simulation.solve(809): Cycle 74/500 (8.041 s elapsed) --------------------\n", - "2021-09-17 01:13:48,891 - [NOTICE] simulation.solve(843): Cycle 74/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:48,919 - [NOTICE] simulation.solve(843): Cycle 74/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:48,943 - [NOTICE] simulation.solve(843): Cycle 74/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:48,961 - [NOTICE] simulation.solve(843): Cycle 74/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:48,991 - [NOTICE] simulation.solve(921): Capacity is now 2.718 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:48,991 - [NOTICE] simulation.solve(809): Cycle 75/500 (8.144 s elapsed) --------------------\n", - "2021-09-17 01:13:48,991 - [NOTICE] simulation.solve(843): Cycle 75/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:49,024 - [NOTICE] simulation.solve(843): Cycle 75/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:49,048 - [NOTICE] simulation.solve(843): Cycle 75/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:49,059 - [NOTICE] simulation.solve(843): Cycle 75/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:49,100 - [NOTICE] simulation.solve(921): Capacity is now 2.712 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:49,100 - [NOTICE] simulation.solve(809): Cycle 76/500 (8.250 s elapsed) --------------------\n", - "2021-09-17 01:13:49,100 - [NOTICE] simulation.solve(843): Cycle 76/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:49,128 - [NOTICE] simulation.solve(843): Cycle 76/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:49,143 - [NOTICE] simulation.solve(843): Cycle 76/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:49,171 - [NOTICE] simulation.solve(843): Cycle 76/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:49,200 - [NOTICE] simulation.solve(921): Capacity is now 2.706 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:49,200 - [NOTICE] simulation.solve(809): Cycle 77/500 (8.354 s elapsed) --------------------\n", - "2021-09-17 01:13:49,200 - [NOTICE] simulation.solve(843): Cycle 77/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:49,234 - [NOTICE] simulation.solve(843): Cycle 77/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:49,258 - [NOTICE] simulation.solve(843): Cycle 77/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:49,277 - [NOTICE] simulation.solve(843): Cycle 77/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:49,308 - [NOTICE] simulation.solve(921): Capacity is now 2.700 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:49,308 - [NOTICE] simulation.solve(809): Cycle 78/500 (8.459 s elapsed) --------------------\n" + "2021-11-19 15:28:59,463 - [NOTICE] simulation.solve(884): Cycle 72/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:59,481 - [NOTICE] simulation.solve(884): Cycle 72/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:59,523 - [NOTICE] simulation.solve(972): Capacity is now 2.682 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:59,524 - [NOTICE] simulation.solve(850): Cycle 73/500 (6.356 s elapsed) --------------------\n", + "2021-11-19 15:28:59,524 - [NOTICE] simulation.solve(884): Cycle 73/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:59,543 - [NOTICE] simulation.solve(884): Cycle 73/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:59,563 - [NOTICE] simulation.solve(884): Cycle 73/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:59,581 - [NOTICE] simulation.solve(884): Cycle 73/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:59,620 - [NOTICE] simulation.solve(972): Capacity is now 2.675 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:59,621 - [NOTICE] simulation.solve(850): Cycle 74/500 (6.453 s elapsed) --------------------\n", + "2021-11-19 15:28:59,621 - [NOTICE] simulation.solve(884): Cycle 74/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:59,641 - [NOTICE] simulation.solve(884): Cycle 74/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:59,661 - [NOTICE] simulation.solve(884): Cycle 74/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:59,678 - [NOTICE] simulation.solve(884): Cycle 74/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:59,719 - [NOTICE] simulation.solve(972): Capacity is now 2.669 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:59,719 - [NOTICE] simulation.solve(850): Cycle 75/500 (6.551 s elapsed) --------------------\n", + "2021-11-19 15:28:59,720 - [NOTICE] simulation.solve(884): Cycle 75/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:59,735 - [NOTICE] simulation.solve(884): Cycle 75/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:59,755 - [NOTICE] simulation.solve(884): Cycle 75/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:59,773 - [NOTICE] simulation.solve(884): Cycle 75/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:59,813 - [NOTICE] simulation.solve(972): Capacity is now 2.662 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:59,813 - [NOTICE] simulation.solve(850): Cycle 76/500 (6.645 s elapsed) --------------------\n", + "2021-11-19 15:28:59,814 - [NOTICE] simulation.solve(884): Cycle 76/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:59,839 - [NOTICE] simulation.solve(884): Cycle 76/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:59,861 - [NOTICE] simulation.solve(884): Cycle 76/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:59,874 - [NOTICE] simulation.solve(884): Cycle 76/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:28:59,913 - [NOTICE] simulation.solve(972): Capacity is now 2.655 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:28:59,913 - [NOTICE] simulation.solve(850): Cycle 77/500 (6.745 s elapsed) --------------------\n", + "2021-11-19 15:28:59,914 - [NOTICE] simulation.solve(884): Cycle 77/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:28:59,929 - [NOTICE] simulation.solve(884): Cycle 77/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:28:59,949 - [NOTICE] simulation.solve(884): Cycle 77/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:28:59,962 - [NOTICE] simulation.solve(884): Cycle 77/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:00,002 - [NOTICE] simulation.solve(972): Capacity is now 2.648 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:00,003 - [NOTICE] simulation.solve(850): Cycle 78/500 (6.835 s elapsed) --------------------\n", + "2021-11-19 15:29:00,003 - [NOTICE] simulation.solve(884): Cycle 78/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:00,018 - [NOTICE] simulation.solve(884): Cycle 78/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:00,038 - [NOTICE] simulation.solve(884): Cycle 78/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:00,052 - [NOTICE] simulation.solve(884): Cycle 78/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:00,090 - [NOTICE] simulation.solve(972): Capacity is now 2.641 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:00,091 - [NOTICE] simulation.solve(850): Cycle 79/500 (6.922 s elapsed) --------------------\n", + "2021-11-19 15:29:00,091 - [NOTICE] simulation.solve(884): Cycle 79/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:00,105 - [NOTICE] simulation.solve(884): Cycle 79/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:00,124 - [NOTICE] simulation.solve(884): Cycle 79/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:00,136 - [NOTICE] simulation.solve(884): Cycle 79/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:00,172 - [NOTICE] simulation.solve(972): Capacity is now 2.634 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:00,172 - [NOTICE] simulation.solve(850): Cycle 80/500 (7.004 s elapsed) --------------------\n", + "2021-11-19 15:29:00,173 - [NOTICE] simulation.solve(884): Cycle 80/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:00,188 - [NOTICE] simulation.solve(884): Cycle 80/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:00,207 - [NOTICE] simulation.solve(884): Cycle 80/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:00,221 - [NOTICE] simulation.solve(884): Cycle 80/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:00,263 - [NOTICE] simulation.solve(972): Capacity is now 2.627 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:00,264 - [NOTICE] simulation.solve(850): Cycle 81/500 (7.096 s elapsed) --------------------\n", + "2021-11-19 15:29:00,265 - [NOTICE] simulation.solve(884): Cycle 81/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:00,285 - [NOTICE] simulation.solve(884): Cycle 81/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:00,306 - [NOTICE] simulation.solve(884): Cycle 81/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:00,320 - [NOTICE] simulation.solve(884): Cycle 81/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:00,364 - [NOTICE] simulation.solve(972): Capacity is now 2.620 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:00,364 - [NOTICE] simulation.solve(850): Cycle 82/500 (7.196 s elapsed) --------------------\n", + "2021-11-19 15:29:00,365 - [NOTICE] simulation.solve(884): Cycle 82/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:00,380 - [NOTICE] simulation.solve(884): Cycle 82/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:00,401 - [NOTICE] simulation.solve(884): Cycle 82/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:00,415 - [NOTICE] simulation.solve(884): Cycle 82/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:00,462 - [NOTICE] simulation.solve(972): Capacity is now 2.614 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:00,463 - [NOTICE] simulation.solve(850): Cycle 83/500 (7.294 s elapsed) --------------------\n", + "2021-11-19 15:29:00,463 - [NOTICE] simulation.solve(884): Cycle 83/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:00,480 - [NOTICE] simulation.solve(884): Cycle 83/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:00,501 - [NOTICE] simulation.solve(884): Cycle 83/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:00,513 - [NOTICE] simulation.solve(884): Cycle 83/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:00,550 - [NOTICE] simulation.solve(972): Capacity is now 2.607 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:00,551 - [NOTICE] simulation.solve(850): Cycle 84/500 (7.383 s elapsed) --------------------\n", + "2021-11-19 15:29:00,551 - [NOTICE] simulation.solve(884): Cycle 84/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:00,567 - [NOTICE] simulation.solve(884): Cycle 84/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:00,587 - [NOTICE] simulation.solve(884): Cycle 84/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:00,599 - [NOTICE] simulation.solve(884): Cycle 84/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:00,636 - [NOTICE] simulation.solve(972): Capacity is now 2.600 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:49,308 - [NOTICE] simulation.solve(843): Cycle 78/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:49,338 - [NOTICE] simulation.solve(843): Cycle 78/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:49,363 - [NOTICE] simulation.solve(843): Cycle 78/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:49,381 - [NOTICE] simulation.solve(843): Cycle 78/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:49,416 - [NOTICE] simulation.solve(921): Capacity is now 2.694 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:49,416 - [NOTICE] simulation.solve(809): Cycle 79/500 (8.563 s elapsed) --------------------\n", - "2021-09-17 01:13:49,416 - [NOTICE] simulation.solve(843): Cycle 79/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:49,441 - [NOTICE] simulation.solve(843): Cycle 79/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:49,465 - [NOTICE] simulation.solve(843): Cycle 79/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:49,484 - [NOTICE] simulation.solve(843): Cycle 79/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:49,516 - [NOTICE] simulation.solve(921): Capacity is now 2.688 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:49,516 - [NOTICE] simulation.solve(809): Cycle 80/500 (8.668 s elapsed) --------------------\n", - "2021-09-17 01:13:49,516 - [NOTICE] simulation.solve(843): Cycle 80/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:49,546 - [NOTICE] simulation.solve(843): Cycle 80/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:49,571 - [NOTICE] simulation.solve(843): Cycle 80/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:49,589 - [NOTICE] simulation.solve(843): Cycle 80/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:49,628 - [NOTICE] simulation.solve(921): Capacity is now 2.681 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:49,628 - [NOTICE] simulation.solve(809): Cycle 81/500 (8.773 s elapsed) --------------------\n", - "2021-09-17 01:13:49,629 - [NOTICE] simulation.solve(843): Cycle 81/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:49,653 - [NOTICE] simulation.solve(843): Cycle 81/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:49,676 - [NOTICE] simulation.solve(843): Cycle 81/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:49,695 - [NOTICE] simulation.solve(843): Cycle 81/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:49,734 - [NOTICE] simulation.solve(921): Capacity is now 2.675 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:49,735 - [NOTICE] simulation.solve(809): Cycle 82/500 (8.879 s elapsed) --------------------\n", - "2021-09-17 01:13:49,735 - [NOTICE] simulation.solve(843): Cycle 82/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:49,758 - [NOTICE] simulation.solve(843): Cycle 82/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:49,781 - [NOTICE] simulation.solve(843): Cycle 82/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:49,799 - [NOTICE] simulation.solve(843): Cycle 82/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:49,825 - [NOTICE] simulation.solve(921): Capacity is now 2.669 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:49,825 - [NOTICE] simulation.solve(809): Cycle 83/500 (8.983 s elapsed) --------------------\n", - "2021-09-17 01:13:49,825 - [NOTICE] simulation.solve(843): Cycle 83/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:49,846 - [NOTICE] simulation.solve(843): Cycle 83/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:49,882 - [NOTICE] simulation.solve(843): Cycle 83/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:49,901 - [NOTICE] simulation.solve(843): Cycle 83/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:49,934 - [NOTICE] simulation.solve(921): Capacity is now 2.663 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:49,934 - [NOTICE] simulation.solve(809): Cycle 84/500 (9.086 s elapsed) --------------------\n", - "2021-09-17 01:13:49,934 - [NOTICE] simulation.solve(843): Cycle 84/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:49,962 - [NOTICE] simulation.solve(843): Cycle 84/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:49,986 - [NOTICE] simulation.solve(843): Cycle 84/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:50,002 - [NOTICE] simulation.solve(843): Cycle 84/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:50,033 - [NOTICE] simulation.solve(921): Capacity is now 2.657 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:50,033 - [NOTICE] simulation.solve(809): Cycle 85/500 (9.185 s elapsed) --------------------\n", - "2021-09-17 01:13:50,033 - [NOTICE] simulation.solve(843): Cycle 85/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:50,061 - [NOTICE] simulation.solve(843): Cycle 85/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:50,085 - [NOTICE] simulation.solve(843): Cycle 85/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:50,102 - [NOTICE] simulation.solve(843): Cycle 85/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:50,125 - [NOTICE] simulation.solve(921): Capacity is now 2.651 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:50,140 - [NOTICE] simulation.solve(809): Cycle 86/500 (9.285 s elapsed) --------------------\n", - "2021-09-17 01:13:50,140 - [NOTICE] simulation.solve(843): Cycle 86/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:50,161 - [NOTICE] simulation.solve(843): Cycle 86/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:50,185 - [NOTICE] simulation.solve(843): Cycle 86/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:50,201 - [NOTICE] simulation.solve(843): Cycle 86/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:50,233 - [NOTICE] simulation.solve(921): Capacity is now 2.644 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:50,233 - [NOTICE] simulation.solve(809): Cycle 87/500 (9.383 s elapsed) --------------------\n", - "2021-09-17 01:13:50,233 - [NOTICE] simulation.solve(843): Cycle 87/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:50,257 - [NOTICE] simulation.solve(843): Cycle 87/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:50,285 - [NOTICE] simulation.solve(843): Cycle 87/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:50,300 - [NOTICE] simulation.solve(843): Cycle 87/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:50,325 - [NOTICE] simulation.solve(921): Capacity is now 2.638 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:50,325 - [NOTICE] simulation.solve(809): Cycle 88/500 (9.482 s elapsed) --------------------\n", - "2021-09-17 01:13:50,325 - [NOTICE] simulation.solve(843): Cycle 88/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:50,357 - [NOTICE] simulation.solve(843): Cycle 88/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:50,382 - [NOTICE] simulation.solve(843): Cycle 88/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:50,397 - [NOTICE] simulation.solve(843): Cycle 88/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:50,426 - [NOTICE] simulation.solve(921): Capacity is now 2.632 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:50,426 - [NOTICE] simulation.solve(809): Cycle 89/500 (9.581 s elapsed) --------------------\n", - "2021-09-17 01:13:50,426 - [NOTICE] simulation.solve(843): Cycle 89/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:50,458 - [NOTICE] simulation.solve(843): Cycle 89/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:50,475 - [NOTICE] simulation.solve(843): Cycle 89/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:50,499 - [NOTICE] simulation.solve(843): Cycle 89/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:50,535 - [NOTICE] simulation.solve(921): Capacity is now 2.626 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:50,535 - [NOTICE] simulation.solve(809): Cycle 90/500 (9.680 s elapsed) --------------------\n", - "2021-09-17 01:13:50,535 - [NOTICE] simulation.solve(843): Cycle 90/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:50,557 - [NOTICE] simulation.solve(843): Cycle 90/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:50,581 - [NOTICE] simulation.solve(843): Cycle 90/500, step 3/4: Charge at 1C until 4.2V\n" + "2021-11-19 15:29:00,637 - [NOTICE] simulation.solve(850): Cycle 85/500 (7.468 s elapsed) --------------------\n", + "2021-11-19 15:29:00,637 - [NOTICE] simulation.solve(884): Cycle 85/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:00,652 - [NOTICE] simulation.solve(884): Cycle 85/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:00,672 - [NOTICE] simulation.solve(884): Cycle 85/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:00,684 - [NOTICE] simulation.solve(884): Cycle 85/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:00,723 - [NOTICE] simulation.solve(972): Capacity is now 2.593 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:00,724 - [NOTICE] simulation.solve(850): Cycle 86/500 (7.555 s elapsed) --------------------\n", + "2021-11-19 15:29:00,724 - [NOTICE] simulation.solve(884): Cycle 86/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:00,738 - [NOTICE] simulation.solve(884): Cycle 86/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:00,757 - [NOTICE] simulation.solve(884): Cycle 86/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:00,770 - [NOTICE] simulation.solve(884): Cycle 86/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:00,808 - [NOTICE] simulation.solve(972): Capacity is now 2.587 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:00,809 - [NOTICE] simulation.solve(850): Cycle 87/500 (7.641 s elapsed) --------------------\n", + "2021-11-19 15:29:00,809 - [NOTICE] simulation.solve(884): Cycle 87/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:00,825 - [NOTICE] simulation.solve(884): Cycle 87/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:00,845 - [NOTICE] simulation.solve(884): Cycle 87/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:00,860 - [NOTICE] simulation.solve(884): Cycle 87/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:00,897 - [NOTICE] simulation.solve(972): Capacity is now 2.580 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:00,897 - [NOTICE] simulation.solve(850): Cycle 88/500 (7.729 s elapsed) --------------------\n", + "2021-11-19 15:29:00,897 - [NOTICE] simulation.solve(884): Cycle 88/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:00,914 - [NOTICE] simulation.solve(884): Cycle 88/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:00,934 - [NOTICE] simulation.solve(884): Cycle 88/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:00,948 - [NOTICE] simulation.solve(884): Cycle 88/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:00,985 - [NOTICE] simulation.solve(972): Capacity is now 2.573 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:00,986 - [NOTICE] simulation.solve(850): Cycle 89/500 (7.818 s elapsed) --------------------\n", + "2021-11-19 15:29:00,986 - [NOTICE] simulation.solve(884): Cycle 89/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:01,002 - [NOTICE] simulation.solve(884): Cycle 89/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:01,022 - [NOTICE] simulation.solve(884): Cycle 89/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:01,036 - [NOTICE] simulation.solve(884): Cycle 89/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:01,075 - [NOTICE] simulation.solve(972): Capacity is now 2.566 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:01,076 - [NOTICE] simulation.solve(850): Cycle 90/500 (7.907 s elapsed) --------------------\n", + "2021-11-19 15:29:01,076 - [NOTICE] simulation.solve(884): Cycle 90/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:01,092 - [NOTICE] simulation.solve(884): Cycle 90/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:01,111 - [NOTICE] simulation.solve(884): Cycle 90/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:01,126 - [NOTICE] simulation.solve(884): Cycle 90/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:01,163 - [NOTICE] simulation.solve(972): Capacity is now 2.560 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:01,163 - [NOTICE] simulation.solve(850): Cycle 91/500 (7.995 s elapsed) --------------------\n", + "2021-11-19 15:29:01,164 - [NOTICE] simulation.solve(884): Cycle 91/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:01,180 - [NOTICE] simulation.solve(884): Cycle 91/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:01,200 - [NOTICE] simulation.solve(884): Cycle 91/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:01,214 - [NOTICE] simulation.solve(884): Cycle 91/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:01,252 - [NOTICE] simulation.solve(972): Capacity is now 2.553 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:01,253 - [NOTICE] simulation.solve(850): Cycle 92/500 (8.084 s elapsed) --------------------\n", + "2021-11-19 15:29:01,253 - [NOTICE] simulation.solve(884): Cycle 92/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:01,270 - [NOTICE] simulation.solve(884): Cycle 92/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:01,289 - [NOTICE] simulation.solve(884): Cycle 92/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:01,303 - [NOTICE] simulation.solve(884): Cycle 92/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:01,341 - [NOTICE] simulation.solve(972): Capacity is now 2.547 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:01,341 - [NOTICE] simulation.solve(850): Cycle 93/500 (8.173 s elapsed) --------------------\n", + "2021-11-19 15:29:01,341 - [NOTICE] simulation.solve(884): Cycle 93/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:01,358 - [NOTICE] simulation.solve(884): Cycle 93/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:01,377 - [NOTICE] simulation.solve(884): Cycle 93/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:01,394 - [NOTICE] simulation.solve(884): Cycle 93/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:01,437 - [NOTICE] simulation.solve(972): Capacity is now 2.540 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:01,438 - [NOTICE] simulation.solve(850): Cycle 94/500 (8.270 s elapsed) --------------------\n", + "2021-11-19 15:29:01,438 - [NOTICE] simulation.solve(884): Cycle 94/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:01,455 - [NOTICE] simulation.solve(884): Cycle 94/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:01,476 - [NOTICE] simulation.solve(884): Cycle 94/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:01,492 - [NOTICE] simulation.solve(884): Cycle 94/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:01,531 - [NOTICE] simulation.solve(972): Capacity is now 2.533 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:01,531 - [NOTICE] simulation.solve(850): Cycle 95/500 (8.363 s elapsed) --------------------\n", + "2021-11-19 15:29:01,532 - [NOTICE] simulation.solve(884): Cycle 95/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:01,549 - [NOTICE] simulation.solve(884): Cycle 95/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:01,568 - [NOTICE] simulation.solve(884): Cycle 95/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:01,582 - [NOTICE] simulation.solve(884): Cycle 95/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:01,628 - [NOTICE] simulation.solve(972): Capacity is now 2.527 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:01,629 - [NOTICE] simulation.solve(850): Cycle 96/500 (8.461 s elapsed) --------------------\n", + "2021-11-19 15:29:01,630 - [NOTICE] simulation.solve(884): Cycle 96/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:01,649 - [NOTICE] simulation.solve(884): Cycle 96/500, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:01,671 - [NOTICE] simulation.solve(884): Cycle 96/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:01,686 - [NOTICE] simulation.solve(884): Cycle 96/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:01,724 - [NOTICE] simulation.solve(972): Capacity is now 2.520 Ah (originally 3.149 Ah, will stop at 2.519 Ah)\n", + "2021-11-19 15:29:01,725 - [NOTICE] simulation.solve(850): Cycle 97/500 (8.557 s elapsed) --------------------\n", + "2021-11-19 15:29:01,725 - [NOTICE] simulation.solve(884): Cycle 97/500, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:01,742 - [NOTICE] simulation.solve(884): Cycle 97/500, step 2/4: Rest for 1 hour\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:50,597 - [NOTICE] simulation.solve(843): Cycle 90/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:50,626 - [NOTICE] simulation.solve(921): Capacity is now 2.620 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:50,626 - [NOTICE] simulation.solve(809): Cycle 91/500 (9.779 s elapsed) --------------------\n", - "2021-09-17 01:13:50,626 - [NOTICE] simulation.solve(843): Cycle 91/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:50,656 - [NOTICE] simulation.solve(843): Cycle 91/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:50,682 - [NOTICE] simulation.solve(843): Cycle 91/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:50,698 - [NOTICE] simulation.solve(843): Cycle 91/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:50,726 - [NOTICE] simulation.solve(921): Capacity is now 2.614 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:50,726 - [NOTICE] simulation.solve(809): Cycle 92/500 (9.882 s elapsed) --------------------\n", - "2021-09-17 01:13:50,726 - [NOTICE] simulation.solve(843): Cycle 92/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:50,758 - [NOTICE] simulation.solve(843): Cycle 92/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:50,783 - [NOTICE] simulation.solve(843): Cycle 92/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:50,799 - [NOTICE] simulation.solve(843): Cycle 92/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:50,838 - [NOTICE] simulation.solve(921): Capacity is now 2.608 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:50,839 - [NOTICE] simulation.solve(809): Cycle 93/500 (9.983 s elapsed) --------------------\n", - "2021-09-17 01:13:50,839 - [NOTICE] simulation.solve(843): Cycle 93/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:50,859 - [NOTICE] simulation.solve(843): Cycle 93/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:50,885 - [NOTICE] simulation.solve(843): Cycle 93/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:50,900 - [NOTICE] simulation.solve(843): Cycle 93/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:50,941 - [NOTICE] simulation.solve(921): Capacity is now 2.602 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:50,941 - [NOTICE] simulation.solve(809): Cycle 94/500 (10.089 s elapsed) --------------------\n", - "2021-09-17 01:13:50,941 - [NOTICE] simulation.solve(843): Cycle 94/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:50,967 - [NOTICE] simulation.solve(843): Cycle 94/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:50,991 - [NOTICE] simulation.solve(843): Cycle 94/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:51,009 - [NOTICE] simulation.solve(843): Cycle 94/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:51,049 - [NOTICE] simulation.solve(921): Capacity is now 2.596 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:51,049 - [NOTICE] simulation.solve(809): Cycle 95/500 (10.202 s elapsed) --------------------\n", - "2021-09-17 01:13:51,049 - [NOTICE] simulation.solve(843): Cycle 95/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:51,082 - [NOTICE] simulation.solve(843): Cycle 95/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:51,108 - [NOTICE] simulation.solve(843): Cycle 95/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:51,117 - [NOTICE] simulation.solve(843): Cycle 95/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:51,169 - [NOTICE] simulation.solve(921): Capacity is now 2.590 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:51,170 - [NOTICE] simulation.solve(809): Cycle 96/500 (10.315 s elapsed) --------------------\n", - "2021-09-17 01:13:51,171 - [NOTICE] simulation.solve(843): Cycle 96/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:51,190 - [NOTICE] simulation.solve(843): Cycle 96/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:51,201 - [NOTICE] simulation.solve(843): Cycle 96/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:51,232 - [NOTICE] simulation.solve(843): Cycle 96/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:51,273 - [NOTICE] simulation.solve(921): Capacity is now 2.584 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:51,274 - [NOTICE] simulation.solve(809): Cycle 97/500 (10.418 s elapsed) --------------------\n", - "2021-09-17 01:13:51,275 - [NOTICE] simulation.solve(843): Cycle 97/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:51,296 - [NOTICE] simulation.solve(843): Cycle 97/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:51,320 - [NOTICE] simulation.solve(843): Cycle 97/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:51,338 - [NOTICE] simulation.solve(843): Cycle 97/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:51,375 - [NOTICE] simulation.solve(921): Capacity is now 2.578 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:51,375 - [NOTICE] simulation.solve(809): Cycle 98/500 (10.524 s elapsed) --------------------\n", - "2021-09-17 01:13:51,375 - [NOTICE] simulation.solve(843): Cycle 98/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:51,395 - [NOTICE] simulation.solve(843): Cycle 98/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:51,424 - [NOTICE] simulation.solve(843): Cycle 98/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:51,442 - [NOTICE] simulation.solve(843): Cycle 98/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:51,475 - [NOTICE] simulation.solve(921): Capacity is now 2.572 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:51,475 - [NOTICE] simulation.solve(809): Cycle 99/500 (10.627 s elapsed) --------------------\n", - "2021-09-17 01:13:51,475 - [NOTICE] simulation.solve(843): Cycle 99/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:51,504 - [NOTICE] simulation.solve(843): Cycle 99/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:51,528 - [NOTICE] simulation.solve(843): Cycle 99/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:51,546 - [NOTICE] simulation.solve(843): Cycle 99/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:51,575 - [NOTICE] simulation.solve(921): Capacity is now 2.566 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:51,575 - [NOTICE] simulation.solve(809): Cycle 100/500 (10.731 s elapsed) --------------------\n", - "2021-09-17 01:13:51,575 - [NOTICE] simulation.solve(843): Cycle 100/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:51,609 - [NOTICE] simulation.solve(843): Cycle 100/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:51,632 - [NOTICE] simulation.solve(843): Cycle 100/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:51,649 - [NOTICE] simulation.solve(843): Cycle 100/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:51,690 - [NOTICE] simulation.solve(921): Capacity is now 2.560 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:51,690 - [NOTICE] simulation.solve(809): Cycle 101/500 (10.837 s elapsed) --------------------\n", - "2021-09-17 01:13:51,690 - [NOTICE] simulation.solve(843): Cycle 101/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:51,714 - [NOTICE] simulation.solve(843): Cycle 101/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:51,739 - [NOTICE] simulation.solve(843): Cycle 101/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:51,757 - [NOTICE] simulation.solve(843): Cycle 101/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:51,783 - [NOTICE] simulation.solve(921): Capacity is now 2.554 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:51,797 - [NOTICE] simulation.solve(809): Cycle 102/500 (10.941 s elapsed) --------------------\n", - "2021-09-17 01:13:51,797 - [NOTICE] simulation.solve(843): Cycle 102/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:51,805 - [NOTICE] simulation.solve(843): Cycle 102/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:51,845 - [NOTICE] simulation.solve(843): Cycle 102/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:51,858 - [NOTICE] simulation.solve(843): Cycle 102/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:51,897 - [NOTICE] simulation.solve(921): Capacity is now 2.548 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:51,897 - [NOTICE] simulation.solve(809): Cycle 103/500 (11.047 s elapsed) --------------------\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2021-09-17 01:13:51,897 - [NOTICE] simulation.solve(843): Cycle 103/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:51,927 - [NOTICE] simulation.solve(843): Cycle 103/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:51,950 - [NOTICE] simulation.solve(843): Cycle 103/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:51,970 - [NOTICE] simulation.solve(843): Cycle 103/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:52,001 - [NOTICE] simulation.solve(921): Capacity is now 2.542 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:52,001 - [NOTICE] simulation.solve(809): Cycle 104/500 (11.157 s elapsed) --------------------\n", - "2021-09-17 01:13:52,001 - [NOTICE] simulation.solve(843): Cycle 104/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:52,034 - [NOTICE] simulation.solve(843): Cycle 104/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:52,058 - [NOTICE] simulation.solve(843): Cycle 104/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:52,076 - [NOTICE] simulation.solve(843): Cycle 104/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:52,108 - [NOTICE] simulation.solve(921): Capacity is now 2.536 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:52,108 - [NOTICE] simulation.solve(809): Cycle 105/500 (11.261 s elapsed) --------------------\n", - "2021-09-17 01:13:52,108 - [NOTICE] simulation.solve(843): Cycle 105/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:52,138 - [NOTICE] simulation.solve(843): Cycle 105/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:52,163 - [NOTICE] simulation.solve(843): Cycle 105/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:52,181 - [NOTICE] simulation.solve(843): Cycle 105/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:52,208 - [NOTICE] simulation.solve(921): Capacity is now 2.531 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:52,208 - [NOTICE] simulation.solve(809): Cycle 106/500 (11.366 s elapsed) --------------------\n", - "2021-09-17 01:13:52,208 - [NOTICE] simulation.solve(843): Cycle 106/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:52,229 - [NOTICE] simulation.solve(843): Cycle 106/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:52,269 - [NOTICE] simulation.solve(843): Cycle 106/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:52,287 - [NOTICE] simulation.solve(843): Cycle 106/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:52,317 - [NOTICE] simulation.solve(921): Capacity is now 2.525 Ah (originally 3.154 Ah, will stop at 2.523 Ah)\n", - "2021-09-17 01:13:52,317 - [NOTICE] simulation.solve(809): Cycle 107/500 (11.473 s elapsed) --------------------\n", - "2021-09-17 01:13:52,317 - [NOTICE] simulation.solve(843): Cycle 107/500, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:52,350 - [NOTICE] simulation.solve(843): Cycle 107/500, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:52,375 - [NOTICE] simulation.solve(843): Cycle 107/500, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:52,392 - [NOTICE] simulation.solve(843): Cycle 107/500, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:52,432 - [NOTICE] simulation.solve(927): Stopping experiment since capacity (2.519 Ah) is below stopping capacity (2.523 Ah).\n", - "2021-09-17 01:13:52,432 - [NOTICE] simulation.solve(938): Finish experiment simulation, took 11.578 s\n" + "2021-11-19 15:29:01,760 - [NOTICE] simulation.solve(884): Cycle 97/500, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:01,774 - [NOTICE] simulation.solve(884): Cycle 97/500, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:01,939 - [NOTICE] simulation.solve(978): Stopping experiment since capacity (2.514 Ah) is below stopping capacity (2.519 Ah).\n", + "2021-11-19 15:29:01,941 - [NOTICE] simulation.solve(990): Finish experiment simulation, took 8.773 s\n" ] } ], @@ -1961,78 +1825,71 @@ { "data": { "text/plain": [ - "[,\n", - " None,\n", - " None,\n", - " None,\n", - " ,\n", + "[,\n", " None,\n", " None,\n", " None,\n", + " ,\n", " None,\n", - " ,\n", " None,\n", " None,\n", " None,\n", + " ,\n", " None,\n", - " ,\n", " None,\n", " None,\n", " None,\n", + " ,\n", " None,\n", - " ,\n", " None,\n", " None,\n", " None,\n", + " ,\n", " None,\n", - " ,\n", " None,\n", " None,\n", " None,\n", + " ,\n", " None,\n", - " ,\n", " None,\n", " None,\n", " None,\n", + " ,\n", 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None,\n", - " ,\n", " None,\n", " None,\n", " None,\n", @@ -2108,8 +1954,8 @@ " None,\n", " None,\n", " None,\n", - " ,\n", " None,\n", + " ,\n", " None,\n", " None,\n", " None,\n", @@ -2119,6 +1965,7 @@ " None,\n", " None,\n", " None,\n", + " ,\n", " None,\n", " None,\n", " None,\n", @@ -2189,12 +2036,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "99a387ca564e44efb13f4c7c78971dcc", + "model_id": "91b862c0b90e4115b09d45327198c651", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "interactive(children=(FloatSlider(value=100.84278906802614, description='t', max=103.08965241980624, min=100.8…" + "interactive(children=(FloatSlider(value=104.91777482952412, description='t', max=107.27032274825723, min=104.9…" ] }, "metadata": {}, @@ -2203,7 +2050,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 12, @@ -2223,7 +2070,7 @@ "outputs": [ { "data": { - "image/png": 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JBVLnmNAYy0iNLu2J0aU9Ie2gaiyQ0mIZKdCQWJYKpBTlTEgpX5JSXhf7/OtSysdjn6+UUmZJKatiH9e/+SspijKqsaYHgEDNWtpKk9GFzuzWAxxwzwLgoNtiaSKEw41Y1myi0ShFnhywJD2OdqLhENnlC+lrH6FsXhqDz79A4qqVPNP8Al6Hl0v1JOirpznnauq7R7hubk48p/uGVCB1jo0u7TksMBE4Ykt75mggBSAlUkqk0NEsMITAgYmhAilFURTlPNG4vwefX8fTcZhdOWFm+PJIsEzWjpRTmO6jV4NZ2gEAWppTcblcZHa40QIuDhzYEFvWS0NoguzgIazhYXxXX8Uz9c9wecHlJNQ+BZqDB4fn4tAEV886/5b1QAVS55ymCSTaCRmpsWJzYWExGixJwF7aszNSlspIKYqiKOcFy7RoOtBLlqcPATyT3koVHqTQeagjh8xsuz6qOPgsfv9MamvbqSgrJ3poAPe0ZA5v30L5IntZL39aMpEXnkRPSWFXkUV/uJ9rS9bA/keRJct5aP8Il1Wkn5VWBe8EFUidY6MZKT22ZKdjL+NZaCDkaPgEWGNLe+ZosbmqkVIURVHOAx31g4RHDJJbdiBLC2jzRZk/0EMwbSYdYSeRZBfZLh3v0FpczvkMDw9TGshHRiz63F1EQ0GyyubT3xmkdE4Kg2tfIvHqq/hb/dMkuZO4RPih9xgNOVfR3Bfkurm58Z7yG1KB1DkmNAFCIMYFSPauPQ2BRCIRQgDyeI2UILZrTwVSiqIoSvwd3d2F0MC/42maZ2UCUN1aw2HvXPtxr2RBQhCkSXd3GpqmkTMQQHh0DhzeiCcxwHB/OpomyBrYjwwGcV+1grWNa7mq6Cqc+x4BzckDg/Nw6RqrZmXFc7pvSgVS55gW+4lrlob1uqW9WCCFxlggNX5pT2WkFEVRlDiTUnJkRydZGeAI9vNK3hAzEotIjwR5JVxGXqqXTg1manUI4eDgQYuiwiI4OIi7MpnDOzZTvugie1lvRgrhF57CkZHBpowBgkaQNcXXwJ6HkBWr+EvNCMunZRDwOOM97TekAqlzTGgCAE3qmIADMxZI6QghsZBoCJD20p4+VmxuYZgqkFIURVHiq6dlmL72EbJDdQiPm6cCR+0ddsADHflkZ/sBKAmtIyFhJh0dfZSmF2ANGwx4+4gEg2SVzmegK0TprCSG1r1M4jXX8GTD02QlZDF/eBCG2qjLvpa2gdB5u1tvlAqkzrHjgZSGKUQsIyVPzEiJWEaK8e0PVEZKURRFib/DOzpBQNKWRxmeP42QbnFpbzuh1OkcC/kxU1xkOHWSRl7CssoByBpJBF1wqGkLHn8ig30ZaLogo2c3MhJBW3kZ65vXs7pkNdqeh8Ad4Pfd0/E6dVbOOH+X9UAFUuecFgukBOM7m8eKzUdrpBCABaMNOVE1UoqiKMr54fD2DrIydfTWo+yc7SXR6Wduww4OBS4C4JhXMD8hBNKgpzsdj8eD/6jEXZZE3c7NlFQv5MiOLgpmphJ67kkcuTm8lNSCIQ3W5K+Amscxpl/PY3u7uWZ2Nj73eX2anQqkzjW7kDyWkYKxzuaj7Q8kHM9IjRWbC9XZXFEURYm7rqYhelqGyYnUIVwuHkg/wiWJJTgsg6fDc8lJ9tCmS2ZqhxFC5+hRjcKcAqzeMKHkMKGhQdIL5zLUE6Z0up/h9RsIrF7Nk8eeoiSphOkddRAZYmvSKgZCBjfPz4v3lN+SCqTOsdGlPTFuaU8wbmlPjGakjgdSptBUHylFmWQs0+THP7qVP9zz7/EeiqKcNQe3tKFpguQtfyG6aDYtspdVYRPpTuQPzVkUFdi1UmWRV0hImEF39zB57nQAGrr3ozschIaz0RyCtPYdYBhEr1jMtvZtrClZg9jzIATyuKshh6yAm0vK0uM53VOiAqlzbHTXnkDDEprd2dw6vmvPitVIyVixuWZJDE1Tnc0VZZIxLYvsPXNhvRHvoSjKWSEtycEt7eTla2jNR9k+y4NH93BZ/S66My9hICIg00OyQyN5+EUsswKArGAALdFJ7d5XKJg1l/r9Q+RPSyX8/JM4iwp53n0EgDXZF0Pd84xMv5m1B7u5sToPPZZ8OJ+pQOocO56REseLzQETPdaQ83iNlMTetWcJXWWkFGWSEcAL8wfZVh2J91AU5axoPtTHcF+Y7N5dCK+XP2bUsSx1NgmDrbyiL8bl0Djoliz0RRAyQk+PXR+V2ARanoe+tlayyuYy0BmkqMzD8KbNY8t6c9LnUHhsE0iTZ/TlGJbk5ur8eE/5lKhA6hwbC6Qse2nvpA05Y4XnjNVIaTiEVDVSijKJCE3j0lf8zNoyQjAUivdwFOVtO7i5Dadbx7/uz4Qvm0+r1cNVYRN0N7/pnMmcomRaTJNFjkMn1EfJYYN+0QWAadrBUXrHTrAsBi6dS01PDWtK1sDu+yFrDncf8jI7L8C07MQ4zvbUqUDqHBu/a+94Z3Ps7lFjS3ujNVKxs/Y0ewnQtOI7dkVRTp2u64S8pehmKdvXPxXv4SjK22JETA5v76AwM4IY6OXlOQK/08/yw5sZKrycfd2SQI7dP2pm+Dm83ul0d4+Q784A7PooX3IK7cc0skoCGC8/g6u4mKe1fWhC4+pAJTRvo7P0BnY39XPTJMlGwVkMpIQQuhBihxDiibP1mlPR+KU9a6yP1PjO5ic5a09oOITqI6Uok41mdSG1TA69sjneQ1GUt+XYnm4iIZPMxlfRMzO517OTq9Pm4Rlq4yXnMjQBLSk6c/0u9KFXkdY0ALKG/ehJbupqt5BbOZvOhiEKK/0Mb3kN/8qVPHnsKRZnLybj0POA4IHwReia4Pp55+/ZehOdzYzUF4Gas/h6U5IY/YlLDUuIWGdzOa79gUQTAqRECj0WSAkcQnU2V5TJxnL0EXFl0iLC8R6KorwtBza3kZDowPPKw3Qum8GIFeL64WGk08fPm8tZUJzK7kiEiz2dSGnS1Z2P1+vF3wRkOxjp7yMhpQyAtIFDYBh0LCyhcbBxbFlPlizn3n0RlldmkJHoju+ET8NZCaSEEPnAtcBvzsbrTWVabNveCcXmcmKxeSwjRawhp9BVRkpRJiE9ycLS3VjRvngPRVHO2HB/mPq93RQl9iJMg8fK+ynw51Ndu5a+kjXUdJvkFCchgSpzHU5nGofrTAqy8pFBk146ADCMHFweHceWZ3FkZfFcwlEcmoMVejL0HuNQ9hpa+0OTonfUeGcrI/Uj4CuAquJ5C2Jc+wO7RkoeX9ojViM1vo+UFWvIiVSdzRVlkimaUwlAwoD63VUmrwOb2pCWJGPfE2jTynlK7OVd/lJEZJC/alfg0ARHkzTKE1yk9D+Cz3cR/f0DFHmzATjWsYekzCw6GwS55UkEN27Af8UVPNf4PEtylpBU8wQ4vNzTM4dEj+O8PxJmorcdSAkhrgM6pJTb3uK6TwkhtgohtnZ2dr7dt520RjubIwWWGO1sfvKz9phQI6V27SnK5DJv+XIAEoY9DA2PxHk0inL6pJTUbGglK9eFY9erHLzIzhZd33YYmVLMTw5lsLQyg63BEKsDQ5jmAIMDJQDkDyejp7o5cmAr2eWzGOgKkeUfRo6M0DevmKahJlbmXw57H8aoXM2jNQNcOycHj1OP44xP39nISC0FrhdCHAP+DKwQQtw78SIp5Z1SyoVSyoUZGRln4W0np9Fde0h7157d2Tx21t74zuZjDTmPZ6RUHylFmVzSirIQloEzksLzj9wR7+EoymlrPdxPX/sI+aEahNPJHwrqWZg2h7yjGzmcez1dw1HSS+1lvSXGc+i6j7o6N3l5eTgawliZGuHhYTyJdnCV3LEPNI11GV1oQmOF5YZgD68lrmAkYnLz/MmzW2/U2w6kpJT/IqXMl1IWA+8HXpRS3v62RzZFje3aExoWEueEYvOxzuav27WnOpsrymSj6RoOoxvNSqfrtSPxHo6inLaa9S043RqJa/9A9LKF1JhNXI8PgDv7LyIj0c1Wl0l1ogdn74MkJ19BU1MHZemFyJBJN60AhEPZJARc6DtewjNnNs/3bKQ6s5rUQ8+DO8CdzcUUpHpZWJQSz+meEdVH6hwbzUhJNKQU4w4t1mMNOTleIxXrbG5qAofqbK4ok5KgB6llcqwwUf0OK5NKJGRQt62DoswIWm8nL1Xr+Jw+rq7bRKTwUv5yRHDp7EwOBMO8y9+BYQwSHJkDQEE4DeHUONyyndS8AtqPGuSVJxLavRttURUHeg9wac7FUPs3gqVX8dLhAW6qzj++ajOJnNVASkr5kpTyurP5mlPNaLG5FBqWBIeQE/pIHe9sLoXAITUsNHTV2VxRJiVfMoQ9GZihI2ze/Gy8h6Mop6xuawdGxCLr0LPo+Xn83rOda9Pnk9DXwKu+qzEtyUi2F6+mUR3+Cy5XOvv2WWRmZuI7YuIqDdBQs5vMkpkEB6Nk6N1gmhwqTwDgYssFwV42uJYiJdxQNXl6R42nMlLn2OjSHkKAPPGImLH2B8KumkJo6LE2CTqW2rWnKJNQafUsLN1FZtsA+x98JN7DUZRTtu/VFpLTnbg2/Y2G5RWErAjv6e1BugN8v3Ea1YXJPB8Ocl26h2DP0yQlXU1TUwuziqdjDUQY8g9iRMJ4A3ZzzqSm7QiPh3VJrSS5k5jeuBNcfn7TWsr07ETKMvzxnfAZUoHUOTYaSEmhIS3GLe2Nz0iNNuTUcGB3QNdVHylFmZTKls4FILE/lYHUDLW8p0wKnQ2DdBwboFgcQ2gavy9uZFbKNGYcfIHO0pvZ32VQUpnKsGmx0vEaUhp0dc4AoCySCRrUtW3HneBjZCCdpAwv8rWXSFi4kA2dr7Ekewn64RcJFVzGxoZhrpubE+cZnzkVSJ1jYzVSwt7e6TjhiJjjxeajR8ToUmAIu0ZKdTZXlMkntSgZYUVxhQo5lOpk48Zn4j0kRXlLe9c14XBpJL/8e8yLqthh1fNuRwaYEX4XuYIEl06tX6M8wU16910kJS1i9+52SopL0PYP465I4eCuDRRXLaS5bpC8Yi+RusOEqivpCHZwcaAc+hvY5qwGYM0cFUgpp2gsI4XAskYDKYkZa8h5Qo0Uml0jFVvaUxkpRZl8dF0jwdGLphXiHDlCzf0PxXtIivKmwkGDg6+1U5wdQWtv4uXFXrwOL2vqNmLkL+E3B9xcPjub7cEgNyUNEgrV43BcQV9fH3PypmENRAhlhQkNDpCcPRsjbJItmwDYU2z/N/DiEbuv2oM95UzPTqR0ki7rgQqkzjlt3NIeEvTXFZtzQmdzfVy/KVUjpSiTU2ZBgCF/ITkdB3AkZBA1zHgPSVHe0IFNbRgRi+zaJ9HzcrnHt5M1adX4eo7yStL1hA0LvdCPQ8CiyEM4HEnU1iSQkJBAfmciwuOgtn4DTreHkaFs3AkOEg+uR09J4UXXEQoTC8lr3IqVXMTfmj0sr5zcvSVVIHWOjR1aLDSwsIvNATn+rL2xpT2BLo/XSKmVPUWZnIrml2E6PCT1uNld5uP5p/8Q7yEpyklJKdn7cjPpWU5cW57h2JXTCVph3tvXjfSm8t/HKqkuTObZaJDVaV6M7r+SmrqGAweOUDV7HpH9fXhmp1C7+WUqliylYf8gRbNSGXn1ZbwXX8RrHVu5OGcJHH2ZlrSLiZqwTAVSyukYPSJGCg2JHUhpow05sTuba7Fi89Fde5awr1NFqooyOWXPsY/VcA0V0WHoNP/t1TiPSFFOrrWuj97WYQpD+xAuF78uPExV6ixmHlxLc/FNHOyOUj49jX7D5FrXDqSM0N01Aykl0/V8MCy6vK1EgkEyS5cQHjbI8w9g9vTQtbicoBHkImcqRIZ41ZqDx6mxsHjyNeEcTwVS59j4XXvEdu2JcUt7J3Y21+1icwQ6JoalzoRWlMkoJduHJiP4IiWkDR4iISGHkVA43sNSlNfZ81IzLq9O0gv3ELx8AbVmM7dqyWAZ3Dm0nJQEJ9sSJDN8HjK67yQQqGb79nZKS0px7QniKgqwe/vzJGVm0d2aiMvrIOngOoTbzcaiEJrQWNzXAULjjx3FXFSahtsxuc7Wm0gFUufYCZ3NLYkjdtaeObH9QaxGyjG6tIeFiqMUZXLSNEFacoSQr4LMkf20Twvy5EM/ifewFOUEgz0hDu/opDRtADHUz+PzoqR50lhV8yLh4iv542Eny+Zmsz8Y5pak7liR+VUMDAwwN386RlcQprlp2LuLGZeu5OiObioWZjLy/DP4LruUtV0bmZs+l8DRVwlnzWdPt2BZxeRe1gMVSJ1zxzNSAiT2ocVy9NBia1yNlETqjnHF5qqzuaKcCSGELoTYIYR44iSPuYUQ9wsh6oQQm4UQxe/UOApnZjPsy8HfE+U1Xyb9aw+9U2+lKGdk77pmkJLMLX9Cm17BXxy7uCV5Fs6hdp7wXo8lJQM5XhJ1jerg73G5Mti/z43P5yO3OQEtwcG+Yy+j6Q68yVUYUYuStEGM9nYil86ntqeWlbmXQPN2DvgXApO/PgpUIHXOjT8iBmnXPp24tBfbtSct0PQTaqTUrj1FOSNfBGre4LGPA71SynLgh8D/vFODKLq4DABHfwWhficJgQKONTW+U2+nKKclGjHZ92ozBfkCx8EdbF+egy50bmnYh5Vazn8dyOGyaRm8EBzh3ekORnqeJzXlRg4dOsr82VVEanvxVKWx9+XnqbxoKYe3D5Ga68PxymOIhAReLrWXsq+yvIDkqeBM8pK9lGX44jvxs0AFUufY2IGMQgNLosV27Vkn9JGKLe1pOrolMLEzV6qPlKKcHiFEPnAt8Js3uOQG4Hexzx8CrhSjO0LOsszSFDQZxR+qIH/wANHSDp7/wzffibdSlNN2cHMb4WGD/KPPoWek84uM3azIqCazeQc7c95L94hBekUyESlZKZ9GCCcNDSVomsYMKx8saJZHiARHKJx7OR31g8xcks7gU08RWH0Nz3SsY076HHKObUR6kvlTUwbLKtN5h37dzikVSJ1j4nV9pMxYRko/XiM12v5A09Ek9ll70lSdzRXl9P0I+ArwRhWGeUAjgJTSAPqBtHdiILpDI9k7hHRWkGbsYV+2B73WrTLNStxJKdm9tom0TCfuVx+hcdVs+swhPjgURLoS+c+meVRmJ/KcDHN5SgKOrt+RlnYVO3YcZvbMWbCzH3dlCttffYKM4lJaD3txeXRye3cgR0aIrF7Gvu59rMy/HA48SXf+KvrCksumQH0UqEDqnBtfbK5bABZCSizhON5HKtbZHE23i81RGSlFOV1CiOuADinltrPwWp8SQmwVQmzt7Ow849cpnpXFsD+f5A6DfVYhif5iXnn5r293eIrytjQd6KWnZZji4B40t5tfFh9mbuoMqmqeo7X0Zna0m8ybk0ln1OQ93v2Y5hBDg4uIRCLMS6nEGowSLozS1XCMmZddzeHtnUy/OIehh+7HVV7Go5796ELnWi0A4QFeclyKJmBpWXq8p35WqEDqHBufkdIsQNo1UjKWkbLbHwhOyEihaqQU5QwsBa4XQhwD/gysEELcO+GaZqAAQAjhAJKA7okvJKW8U0q5UEq5MCPjzP+KrrxmDgDe7nmEe7zIrDAHHr3njF9PUc6Gnc814vU7SHzutwytWMAB2cqHSQLL4GdDV5Lqc7HVZzEtwU1O909JTJzL1q3dFBQU4N8bxZGZwI7dz+D2+Yga5VimpDyzn9DevSTddiuPHn6My/IvI+vQi0hPMnc05nNRaRpJCc54T/2sUIHUOTZ+154mATFaI6WfUCMlYFyxeeyIGJWRUpRTJqX8FyllvpSyGHg/8KKU8vYJlz0OfDj2+Xti17xjv2ip+QHcVg8ecy7lfXvoyW7G3VlIZ0/fO/WWivKmupqGaNjXTbm/FS00zB/nDpDny2HFvmcYLlvDnw47uGxuNjXBCLcldxEKHcPpWENvbx/zi2cTbR1Gn+vn0JYNzL78Kmo3dFI4Kw3zsfvQAgF2LUimO9TNLSXvgton6Su8ikPdYa6bmxvvqZ81KpA6x8bq6oRmB1JY487as5ACe2lPSKTQ0SwwkWiYqrO5opwFQohvCSGuj315F5AmhKgD/gH453f4vcnOlwwlTmNa724Op7nx+fN4/pH/fSffVlHe0I7n6nG4NNJe+DXWkiqe12q53VeKI9TPH7TrcWoabdku0pwO5gz+Eo8nn127dAKBALmNCWg+B/saX0FogpS8ixkZiDBrrpfBZ58l5b23cN+xh8n2ZbO0pwUigzzpuBJdE1wzOzveUz9rVCB1jo3WSFlCQ7Mkx2ukdIRmL+1pItZTShs9tBg0aWGoQEpRzoiU8iUp5XWxz78upXw89nlISnmLlLJcSrlYSnnknR7LvDULkZqOryufA0YRus/FwOZa3sFEmKKc1EB3kEOvdVCWMYjW2cyTS90kOv3cVLueaN4SfliTxJVzs1k3EuTWtCjBgc0EAjdx7FgDi+csIHqgD/f8dHa/9AzTLr6Mg1uGScr0krD5MRCC7tWL2dK2hdum34a+7XfIjOnccTSTS8rSSPW54j39s0YFUueY0EdTUnZGSgg7IyXR0QRju/aEkKA5xmqkVEZKUaaG/PnFOI0eHOElJLSPYGT0ofcXsnP3266JV5TTsuuFRgSQtf4etNnTude9nfekzsXX38DfEm8hYlqYxX7cmmBZ5D4cjgA1NWm43W7KBzNAExwd2UM0FKRw7ko66geZtyyb/oceInHVKv7Q8zReh5d3J1ZCy3aOFr2Xht4gN1blxXvqZ5UKpM4xbdyhxboFMra0Z+JAaNiHFmujBxjb14zu2lM1Uooy+QlNkJU7xIh/OrOad9CZ2YwnIZPXnvh2vIemXEBCQ1H2v9pCUU4Ux7H9rLsiHYfm5EP1dgPOb9QWsGx6Jk8FR7glw0W0+1FSU2+iZv8RFsybj7G9F++8dLa9+BiFs+dybI/Am+gku20T1sAA3HItTx19ipsrbiaw/Q/g9PHznoUkJzi5dm5OvKd/VqlA6hybuGtPxs7ak6Nn7QnQhA7Cbn+gSbCEvbRnqrP2FGVKuPgDK0FoZLXnUpOchj/BhfNAiP7hYLyHplwgdr/UhBGxyN15P1pJEb9KfI2bMxeT3rqHDVm30hcy8VUkYSG5Vj6OEDr19WVomsYsqwBMi87EVoZ6uqm8aDX1e7uZszyX/t/fg2fOHP7i2YspTT6QvxL2PMjI7Ft5rHaYWxbk43FO7kOKJ1KBVBwIcXzXnkQipYw15IQTztrT7GDLlCBUHylFmTIyp+XjCR9FcBE93V6kz41zcCYvP/u7t36yorxN4aDB7hcbKcgD974NbFtZgETw0eZDyEAu/3Z4NguKU3jaCPGuNC903kNG+rvYueMoc2fNga39eGamsfmFh0jLL6SzKQWHS6PYOEC0oYHEj32IBw4+yJWFV1Kw9zGQFvdp78KwJLctKYr39M86FUjFgR1I6cfbH8R27WmxXXua0BFYY9eYSDRpYqiUlKJMGfnTNcKebKr2H2Q4o42RhFSO7bgn3sNSLgB71jYRHjEoqn0ELTuLn2bsZE3mQnIbXmNHwUeoHzDJnZHGiGlxk/4slmXQ0bkAwzCY5y1Hhgz6M/voaqxn7qobOfRaJzOW5jL4u9/gKinhuaIBBiIDfKj83bDtHozpN/CzHRFWzcyiJH3yn603kQqk4sDeuRdb2pPjd+2BFauRstsfxDJSAjRpomrNFWXquOxTtyCsCGndZRzIHibBo0Ez1Bw8FO+hKVNYJGSw84UG8vM0XNueZ9+aaQzLMB9vb0L6MvnKkXnMygvwnAizMtWLu/NO0tNXs2XzUWZMn45r+zDusiQ2rXuQpMwshgcKkUBloJ1wTQ3JH/sId++/h3kZ86hq2A7hAf6W+B76RqJ8ZnlZvKf/jlCBVBzYReXCDqSERI47aw8kQujYR8Ro6BIsaR9urDqbK8rUkZDiJ0EexHAtpK8rgs/rJLVrBhvW/SzeQ1OmsL3rmgkPGxTVPoyencUPs3exMmM+pUc3sKfoQ9T1mkybl0WfaXGLcz2mOUJP92LC4TCL0mdhDUYYKYrQdvgQVVffyP5X26hYlEn4T7/BkZXFy7MErcOtfGrWxxCbf4VVdCn/uzuBRcUpLChKiff03xEqkIoDIYSdbZKxXXuWjDXkjBWWx9ofyFjWygQEEkua8R66oihn0bzVMzCcPmbsD2JmhJGOfHrb1zIcNuI9NGUKioZNdjzXQF6OwL3tOfaumUa/HOGzPT1IbypfPbaAGTkBnhIhliV7Se76KampK9m8uYlplZV4twVx5vvZvOEv+FNSCYcqMaIWs4tDjGzZQspHPsxdB37H9NTpXNbTCgPNbMq+jea+4JTNRoEKpOLCzkiNBkkCXZrjOpuPLzbXEbEaKQAsFUgpylQy78aVOKI9eIML2Z4TZMTvxWqPsG7jpngPTZmCdq9tJDQUpfDAo2jZWXwveztXZy6iom4d+4tup6ZHUjEvg17D4nbvZgxjgIH+pYRCIRanz8bsDROdrtFYs4d5V9/AvlfaqFiQifHnX6MnJbFtSSr1A/V8ctbHEK/8HzJ7Dt+qzacyy88V0zLjPf13jAqk4kDTjmekRlsbWKPtD7AzUjBaI2V3OwdUIKUoU4ymCZLTmhjxz8B7tIEUj4NARzHt29TuPeXsCg1H2fFsA/m5Au/2Z9m9uoIRIny2owWZkMZXGi+mMjuR5/QIy5O9JHX8kNSUK9i0qZWK8nISdoRw5vvZtOkhvIkBLDmTaNhkdlmEoXXrSPnoR7iz7veUJJWwcnAAeg6zp/zT1LYP8ellZWOnekxFKpCKA6EJe9lufNfy2NLe8YyUNRZsjWakNCzV3VxRpphVn3sfwjLJaSkglB8kfbiSkLGR9oFQvIemTCE7nmsgPGJQvPdPaDnZ/F/2DtZkLKD06AZ2FX+cfd2SafMy6TUsPuB5FcMYYHDwCoLBIIsz5sSyUVC/ZwfVq29i3yudlFVnYPz5DvSkJPZdXsTB3oN8YtbH0F75PjJzJv9eU0RBqpfrq6bOAcUnowKpOBCagFjXclMIdGmNFZvL0bP2kPbBxhZj/aN01d1cUaac1OIc3NEaTMdF7EjsYcCXTlc4yEtbd8d7aMoUMdwfZvcLjRTnGbh2v8LW6ysICYPPNh9FJubw/w4vsHfq6RGuSPEQ6PgxaWlXs2FDIxXl5fh3hHHm+1n/6v34klNAn0skaDC7PMLwupdJ+dhH+fmh31KQWMDqUAS6DrK3/NPsah7kC1dU4NSndqgxtWd3ntLE8V17FiDGaqTszuZi7HMNYckTMlJq556iTD2zVhViOP2U1YzgSnFgtibSsfPJeA9LmSK2PnkMy5QUbPgNWkUp/5e6hRszFlLYtJ31eR/naL9J6bxM+kyLW50vYpojdHddTCgU4qLMeZh9YULlJk01e6lefTN7XmqjtDoD6/470JOT2XlZDrU9tXx27mdwvvwDZMZ0/q22lMLUBG6aP7XO1TsZFUjFgdDEuGab44vN7XooTWhIaY3btWcHTw4VSCnKlLT4fdfjjHTiHVlEw6whitorcIysU8t7ytvW3xlk/ystlGYO4Ty6h6evScehO/lc/X6s5GL+4eBsFpWm8oQMc12ah8TOn5OWtoZNmxqYNWMm3tdGcBUlsv7VP+NPSycSmY4RNplXGWH45VdI+ehH+NnBuyhNKmVNMAydNewt+xS7Wwb5uxXlUz4bBSqQigs7kIplpARolomFGFvaE8I+fU8KDSHl2HKeWtpTlKlJ0zUC6c0EfeVYTU14KMZy1fNyTWu8h6ZMclueOIKmC3LW/gJZPYvf+LbxobT5ZLbt45msT9AxYpE0M5WotHi/9jBSGrS2LMQwDBb7Z9p9o8rCtB6qpfrqd7PvlXYql2QTvfsn6KmpbLk0nSP9R/jc3E+jr/1vZOZM/u1gGUVpCdxcPfWzUaACqbjQdO3EYvMTdu0db3+AECfs2lPF5ooyda35fx9GWAa5LUUMT/PT1+nk6O5X4j0sZRLrbh7i4JZ2ypM6cLYf4w+XQ6onlY/WrCOaXc0/1ZRz2fQMnjKCvD/Dgei4m4z097B1az1Vc+bheG0A9/QU1j37e5KyshkaKEFaktlZXXbfqM98il8c+C3TUqaxqrsNeg6zvfzv2N0yzBdWVOC4ALJRoAKpuJhYbK5JCxMNwfEaKRhd2pMnFpurQEpRpqRAThpuq4aoawl1yS0kNU/D2/wCUXXGpnKGNj9+BJdbI+uZnxC6rJonPAf4nK8c30Arv/Z+gogpMSoDeDSNayN34HD4OHRoGkII5lOGDJt0prbR1VjP/DXv58DGTmZdmsvIr36AMz+fl+Y7aRhs4PNzPon28v8i8xfx5d25VGT6uXGK79QbTwVScTC+j5Td/sDOSCGsCUt7IlZsbt9INaGW9hRlKlt0czWGM4GSAxaprrl43TvYVt8b72Epk1BnwyBHd3VR7jyGPtLHTxf3UOzP5+bdT9Ffsobv1aZw9fw81oZDfCQ9hNX7JMnJt7F79xGWzF+M2N6PZ146rzz5e3LKp9Fen4nmEFToBwkfOEDgC5/h5/vupDqzmsuba2GwlRdyP8uRrhG+cs30CyYbBSqQigsxGkhZYCHQMTEtjhebj8tICQtMaQdSDkyVkVKUKWzO6stwRtpxRi+hZp7BwGCIzXsPxntYyiS05YmjuDwa6c/9gu6VVbzmauZLVgCHZfC1ofeQkuBif7aTXLeT5YP/g9udy9bXAvj9fmb35gCCo3IfQ709zLr8vRzZ0UX1lfkM3/Fj3DNn8GBBK92hbv5pzqcR63+IWbqCf92RxMKiFFbOmLpdzE/mbQdSQogCIcRaIcR+IcQ+IcQXz8bApjKhj2akJKawl+wsGVvaG62RkuMzUmppT1EuBEIIssqGCPqKSD3aiK/xYkZqn4n3sJRJpqN+gGO7uyjT6nCYIf5vVj3VyZWs2PcMR0s/wF8bPVy6OJf9kQhfSG0gOrwTt+t9NDa2sXzeJZh7+vAsSWfTM/dTtvAiDm7V8CW7KWp/hWhzM67PfYzf1fyeq4uvZu6+JyHYx4PJH6NjMMw/r54eW1W5cJyNjJQB/KOUciZwEfB5IcTMs/C6U5amaeMyUrGlPSmOL+0RW9rD7iMFo9dJLFUuoShT2jVf/CC6MUJSzzyGZxTjC6+ltT8Y72Epk8hrTxzF7dHIeP5XtKycTZ27j3/oGwBvCp9rvJKKLD/PeU2WBNyUdnydQGABr74aITs7m4L9bvQkF9sbn8OIRCiYdS0d9YMsvjKTvjt+jm/5Mn6d8BpRK8oXS26CzXcQmn0r397mYtXMLBYWp8Z7+ufc2w6kpJStUsrtsc8HgRrgwtjzeIbGDi2Wsc7mWJjy+Fl7diBl2SFVLHIyUe0PFOVC4PZ78LpqCfmq6Y804Gp18Oq++ngPS5kkOuoHOLanmzJ5AIcw+P6MIyxLmUnV0S28kvdxavs0Cqsz6TctPul+EtPsZ3DgOvr7B7i8aDFG6wjWfA971j1N1dXvYs/LI2QWJZK09h6scJiRz7yPR+se5dbpt1Kw4Regu/iB+V5CUZOvXjMt3tOPi7NaIyWEKAaqgc1n83WnGk0ToI0224wt7QFg10iJsUOLxfGMlFBLe4pyoVj1+RuRCAqOZOHwLaF91yPxHpIySWx7qh63RyP9xTupXzmdJvcwX2hpwEgq5gsHq7h4WjpPE+b9GQJvxy9JS3sP69fXM2fmbAJbI7iKElm79h58Kak4Ey5muC/Mwvk6A488QuoHb+e/235HwBXg00lzoPYJ2ud9nl/vHOFDFxdTnpkY7+nHxVkLpIQQfuAvwJeklAMnefxTQoitQoitnZ2dZ+ttJ6Xxnc1HAyRpaohxS3tSWkh5fGnPHCtKV4GUokx1ubPK8URrMJ2XcCB7APPos4QNM97DUs5z/Z1BjuzqpMg8iNMh+d60Oq5Onsn0tv08FPgwI6bGQFkiAV3n2uD3cLnS2LWzCIfDwRIxDWskSmd2B+1HD7Hgug+w56UOKpdkIe75PnpqKltXl7C9Yztfqv57kl74DjKpgP/XcAmpCS6+uLIi3tOPm7MSSAkhnNhB1B+llA+f7Bop5Z1SyoVSyoUZGRln420nLW3crj07QLIwx+qiYjVS8sSM1NjSngqkFOWCUH39dPv8vf0GKf3zeXlXXbyHpJzndq9tRAjIeOUeDl1RRpcnyucaaginzeTf6ipYOjebbWaEz6a1wuBG3K4PcORIK5dXL4VtfXgWpfPS3+4hb8Ysmg6m43TrzPYcIrhjB4EvfJbv1/6SOelzuKm3G9r3sLXy/7GhYYQvXz2NJK8z3tOPm7Oxa08AdwE1UsofvP0hTX0nZKQYLTYHIaxYZdRo+4PxS3sidp0KpBTlQlB9w0pc4Wac0aXsn6lz4LnvxXtIynksGjap2dBKgbcLtzHAT8oP867ANEq76/mV83Y8Lif7spxMT3Ayt+trJCbOZ926EHm5uRTtS0BPdrOt+RkiI8OULbyFloP9LFqZzeCPvou3uprflzTRHezm32Z/Gu3Fb2OUXMHf7ypidl6AWxYWxHv6cXU2MlJLgQ8CK4QQO2Mfa87C605Z4zubG+OKzUczUgiBlPLkxeYqI6UoFwQhBHmzLUIJeeQcaMJ3ELoG1SHGyskd29NFNGSSvvVBWpeU0u4z+MSRnQxmLeaHx4pYWJVNozT5hPclLLOPrs5VjIwEuSJrEVZnkPBc2Pvq88xffTN7Xg6RWZRI+kt3YY6MEPzHj3DfgT/x7sp3M2vL3WBG+JXvs7QOhPnm9bPRtQur3cFEZ2PX3qtSSiGlnCulrIp9PHk2BjdVCXF8154F6MICaReaH29/YCEljPY7sIR9ndq1pygXjlWfvw3dGCKpfyHNs7J56m+/jveQlPNU3dYOvC6TpPZ9/HZmByv8JRQPtPPd8HvISPSwKVlwWZJObvePSQpcz5YtLSycMx/Pa8O4Z6Xw7N9+SWpeAZFINaGhKItnhRh4/HFSPv5R/qP1NyS7k/lSUhXse4S2qs/zg20Gt19UyIKilHhPPe5UZ/M4OKFGSoCOiZAgBVhSImSs2Hzc0p4xWkulMlKKcsFwepwEUhsY9s/F0XqQ4Rc3q7P3lNeJBA3q93aTNXKQSG4qu9KG+EjLEfrS5/PHtnzK52UwgORW6/foWgI7duTj9/up6shFODT2jmxksLuLOSs/zMHXuph/ZS7Rn30bV1ERf7vMS01PDf+28B9Jeu7ryNRyPnX4MtL9br5yzfR4T/28oAKpOBC6QGqjGSk7QCL2+QnF5qOBlJSq/YGiXKCu+8fbEdIkq20WweJSnl37RLyHpJxnjuzqxDQs0vY8yWuz3ZR7M6nqbuAX0XeRneRhfYLkxpQwSQMP43TdTFNTH8vLFyOPjSCr3Wx/8THmXnkte14ySMvzU7j3QaINDcivfpZf7P81q4pWserAy9B7jCeKvsrutiDfumEWAc+FW2A+ngqk4sCuzz+xs7m9tGdXScHxjBSAGH+4sQqkFOWCEshKJkGvIZhwEX2RehoeuheplviVcfa/2oLfYxDoP8JDxe1cOxIhGCjh1+0VZM1IRdMF1wa/j8dTyIb1LvJz88jd7cBZ6OfZtXcQyMjCkksIDUW5eG6I/j/9keQPf4hvhf+Cx+HhX3OugC130jf343x5ayIrZ2Rx9azseE/7vKECqTgYW9qTjJ21B3ZQZckJNVJwQuZK1UgpyoVn1eeuRQqdwiPZkDWNjVs3xXtIynmip2WY1rp+8jo3M1ycSUua4Jrm/TytLSfZ52FbItwQ6MIb3M7w8GqGhkJc6p+LDJocc9fQ29rCnCs/SN32XqqvyCLy/a/hKi/jb6uS2dGxg3+u/iLpT/0rMrWUTzWvwePU+c5Nsy+48/TejAqk4mD0iBh9XB8pe2lPiy3tMbZrD7CvU0t7inJahBAeIcQWIcSu2IHq3zzJNYWxQ9d3CCF2n687jvPmVOA1aoi6LuNoQjs771WtEBTbvlea0TTI2P04L1QJqjyZ5BsmP+6oIrssGaELrhj+AQkJc9m0Mci8ytn490TQZ/vZ8ML9TF96Bfs36KTn+8ld/xuMvj6G/+WT/Gz/HawuXs11B1+FvkYeyP9XtjSH+c6Nc8gKeOI97fOKCqTiQJwsIyUlUoCUll11Li2ktAOp4407VWdzRTkNYWCFlHIeUAVcI4S4aMI1XwMekFJWA+8HfnFuh3jqLv3gYkxHAhU1HjzeWew9WBvvISlxZkRNDmxuI1dvxekw+EtpFzf099ORNJdjVia1SRrXJPaSGKmlrXUBDoeT6u58NJ+T9Qf/gsvjRXNfSnjEYElJJ8NPP0XSZz7JV9t+RVZCFl9LrkZs/x0dcz7Jv271cVN1HtfOzYn3tM87KpCKA00TdttNa2KxuRbrcT56REzseqnO2lOU0yVtQ7EvnbGPib9AEgjEPk8CWs7R8E5b5eVLcEfqkOJy9mT08tKv/yXeQ1Li7NjubsIjBhm7HuXA4iycvgTWtNbxF2MpeRk+ggk6i4N/wOudxa5dURYUzcHRHGWoJEh97U5mXXELR3YMU7U0jfCPv4W3qoqfz2qmZbiF71b9PYEnv4KZM58PHLmKrEQ337h+VrynfF5SgVQcjDbk1MYVkY8GUnZoxQnF5qOHG6vO5opyeoQQuhBiJ9ABPCelnHig+jeA24UQTcCTwBfO7QhPz4J3lRN1JzN9b5hEYzb7Dx+M95CUODqwqRWvyyS5Yx+/L2vlBpGM2+HjZ90L0fISyHdZFEdepr1tNm63h2kNqeg5Xp5f+2uyy6fRUJtNcqaX7LW/QEajHPi7a3i8/m98evbHqX7xe0jgP9z/xJHeKD98X9UFfQzMm1GBVByIWEZKl2Is02Tv2tNAjC7t2QGTRJxYbK5ayCjKKZNSmlLKKiAfWCyEmD3hkluBe6SU+cAa4A9CiNfdF8+XQ9erbrwCV6QJh3UFuwv7eOHOf47bWJT4GhmIUL+vh5z+3YwUpVOXaXJL/W62JF1N1OGjLkXnCudenLqPPXs0qvNm4ui3OKbVEBoeIqvsega7wyws7ib0yjrcn/8Y32j4FVUZVXyqvRladvDCtG9wby185eppLClNi/eUz1sqkIoDTYgTi83FaEZKx5J2pCRH/xXieLG56myuKGdEStkHrAWumfDQx4EHYtdsBDxA+kmef14cui6EYMayVELebCr39pEUnsneQwfiNh4lfg691o60JBl7nuDF2ZJqTxal4SDfbr+E0tJkcOksGPkdljkfy3JQ0pCEludl08a/ULFkBQe3Wkybn4K449t4qqv4dt42JJLv5l2FY/OvaJ/xYT6zNYerZmbxqWWl8Z7ueU0FUnEgtNFMkxgrNhexpT0hJEiQ1mggpceWAEczUiolpSinQgiRIYRIjn3uBVYBEyu0G4ArY9fMwA6k4pdyOgWXfHANzmgnzuhKdpUMs/Y3/xrvISlxULuplRT3MAnhDh4v6+XG3i5ak+ezL5rDsSwXl/qGyLCOUVeXQVFmPr4hncOhnQhNIxyuwu11ULrvT1gjI2z/6EVs6djKV2Z9krynvkY0ax7vrltNXoqX790yT7U6eAsqkIoDTRdINPTRs/bGLe0JMZpxknYLhBOOklFLe4pyGnKAtUKI3cBr2DVSTwghviWEuD52zT8CnxRC7AL+BHxEnufdLjVdo2KhTjChgPJ9XSSFZ7Kndl+8h6WcQ93NQ3Q1DpF1bB0tc7KJJLq5uqOee0KXUZjjpy9BZ6XxZ1yuUlpavFRauQi/g63b/krpghW0H7WYUxEl/MxfcX7idv6n848szV3KTTseRloGXxVfpDMIv/zAAlUXdQpUIBUHQhyvkTIRJxSbC2FhcTyYYqxGSnU2V5TTIaXcLaWsjh2oPltK+a3Y978upXw89vl+KeVSKeW82IHrz8Z31Kdm2SdvwhnpxBVaybaKEK/e8bV4D0k5h2o3tSEEpB9ZxyMVfazUk/A4fPy+bx7hvATK3CZloafo6qrG4/aS15xAv78HS5oM9FYQSPOQ8sj3cZWV8u2yPTiEg2+4SxDHXuWFoi/x8DEP/3nDbGbmBt56MIoKpOJBjG9/cEJncw3E6CEx9g6+sYyU6myuKEqM7tApqzIJJRRQubsdD7PYuHVDvIelnAOWaXFwcxtZWhu6x2JDcZgbW+rY4rsCXD7qk3Su1l/B6Uhl9y43czMqcUid7XXPklU2m/4OJ9OTWzHqj3LwA5ewtXsnX5l2O9nr/o++gpV8et9MbqjK5b2LCuI91UlDBVJxYLc/sGukjLE+UhITLXZssYytScuxxp2qj5SiKONd/rn34Yx04AleybbyEDvu/m91Bt8FoKm2l5GBCBn7nmR3dRJZ3iQWDvXzw+7F5BQn4XZqVA3fTSi4GE1zUdmSipWj0d55GLd/Li6Pjv+xn+Fesojvas8wP6OaG7b8EcudyAe7PkBOkpf/vHHi5lblzahAKg602E9ds0bbH5jjlvYkFhLtdRkpVGdzRVHG6A6dikUaoYQCZu5sx5cwn+fWPh7vYSnvsNpNbbgcFmntu7i/tJMbQiYD/jK2REupT3dwRUILPkbYvTuJ6VlleEZ0avs24w0k09WcSXF2GLraeGV5Gr3hPv7ZU4xo38vvUr7Ivj43P35/FQGPqos6HSqQigOhxRpt2iHUCZ3NhYhlpBCxY2NGj5IR6EgVSCmKMmbZJ99tZ6VCK9mW38eRP9+NoXakTFmRoMGRnZ3kDNUQzAtwJFtyfctB/iKvIDvdx7DfwSWhe9H1KoaHXUzrzURkONmz/0VyKpdjmRpZNU+h5+XxS9d61hSsYMamu+jMuZxvHi7jCysqWFCUGu9pTjoqkIqDsUBKalhitNhcnhhICQ2Qdm7KGldsrlL3iqLE6A6dmZf6CPoKmLm7C2fGPB5+5I54D0t5hxza2o4ZtUjf9yTPz7ZY4s4g1xT8onsB5Pso9RiUGps5dqyQ7NRMUnvdHI3sw+Xx0tNeQm6hB+fmp2m6cgbDZpDb+geQZoTPd7+Xyiw/f7eiPN5TnJRUIBUHWiyQElJMyEjpwLiMFFasloqx61RGSlGU8S758LU4o524IlezJ62T3qdeZmAkFO9hKe+Afa+0kOQKkjhcz98qBrmhs5mawFIG9BSOpThYKdbjdGRy7KiPmVohIkFn6+4nyJ1+KaEhjZKe9Qi3m98WHWNGSiVz9j/F3rTVbBlI5j9vmI1TVyHBmVA/tTgYbW6mSc0OkMSJ7Q8kHM9IxTqgW0KozuaKoryOpmvMuSKFoC+fmXsHMMoqeeDur8Z7WMpZ1lE/QGfDIDlHn6dpXjZGkoeVvR38vP9icosCuNwa84N3MzhYhdvlpaDZT29iN6Y0GOyvJCPXg+up3xG6bhm7jGO8z5mNiI7wnc6lrJqZpY6AeRtUIBUHYiwjpcVqnyzEuKU9S8gT2x9IMIRdUWWaKpBSFOVES25bhTPajsNYzWFnC/qWMMea2+I9LOUs2rO2CV2XZB55iT9N62GNTAB3Bk+HZtGS4WKZt5VEguzdm8yM1FKc6LxW81dyyucx3OemZGQ7mqbxm9mdZHozuO7gq3SmVLMpmM/HlpbEe3qTmgqk4kDTY4EUGpbQTl5sLsS4zuYSU9NVHylFUU5K0wTzV+cTTMhhxr4w7Qsz+eudn4n3sJSzpOVQH7Wb2igM7sNI97C92OB9jTU87VhBclICg0kOlobuRRPzCAXdVHSkEs206OlvQTiq8CU58T11F+GrLmFdZC8fS1uAu/cYd0auZnp2IheVqgLzt0MFUnEwemzRaEZKe11DzuM1UhI7IyWFpjqbK4ryhhbcfCkuow1NrqZr+BhJTdPZ8Jpq0jnZRUIGL/6hBn+CReGmu3hqoUa1O52KqMH/di3FVeCn0G1QYW7i8OF8CtJySRrxUNOxgaTMXLpbUyjztiDCIf44d4AMbzrv2f8Cg8nT+E33bD66tFidpfc2qUAqDsS4YnNrXENOa3xDTuwaKcbO2tNwCKkyUoqinJTQBEuuLyfkzaKyRqfmIg/bf/9NwlEj3kNTzpAZtXj6zr0MdAaZtuu3BMsz+PPsfm5rb6ImcCldejpH051cqW3AoWfR1BRgejQXknRqjqwnkLUEh0sn5aW7YEk1T7GHDyTPwd19mB9F30NBqp+b5+fHe5qTngqk4mD8rj1DiBN27Y025Dze2VzYxeaahkMdWqwoypuY865FeMw2dK7C6thPChdz/33fi/ewlDNgWZLn7t5P4/4eZvc9T1LXfv5zRS9Lfflc1dfJ93uXk1ucjNujsyT4W/r75uDz+sjvSKSFIzg9XnpaCyjJCqG3NfLCRV68Di/vObSZgUAld3XP5EsrK9ROvbNA/QTjYHyxuSVErLO5HLdrL9bZXFpIoY8VmzuEhWmpSEpRlJMTQrDoxpmEvFmUHtB4db5O6MVdNLR2xntoymmQUvLynw5weHsH00c2kLH3CX59Wyo9mS6+eWg7h9JX8mJkOvVZTlZ6jxEQYfbtS2GmvwTdobNl71/JLF2MaTrI3vUXtJIi7krYxs3pC0nqrOVO4zpK0/3cUJUX76lOCSqQioPRjBRSxAKpicXmnOSsPQ2nUBkpRVHe3Oxr5uKS/XiNlaQ3vIa7YAaP3vFJdQ7fJHJ0Vxf7XmmhLLKH3G1/5p73p7E+b4ifdQ+R7Ezm/S3vo6I8lVCik2Ujv8I0FxKNeilrS2EoeYiwMczw4DSyc3Rce15lzxUFWELygdbDhBOy+VVPFZ9eXoquqdqos0EFUnEwlpFCHC82lxOLzWPtDxBjNVK6UJ3NFUV5c5quMf+qEgYDpRQcNnm+1EXgcCVPv/RkvIemnAIzarH+L3UEXCEKNt7Jfe9J56WiIX7VM8ScoUE+Hf0n9MRUaoo8XOnrIl8eYt/ebCozSvBH3ew4+jSZJbMIDfkpaH8VLSmJn2Xv5cqM+RQc28SDjneRFvBxY7XKRp0tKpCKAxH7qQupxYrN5fGMFLEaKSZmpNRZe4qinJq575qDLoP4Q6uY0fQK4Sonhx/4Kd0Dw/EemvIW9q9vYaAzSOmOuzm4KJNnKob4Zdcgc0aCfMD4GtvNYqJVqWQnaNw6/FV0fT59fX5m9mRhpEtauuoQjnn4kxz4195Hy8pZdMshPtQ/iOkK8N2OJXxsaQluhx7vqU4ZKpCKg7GtplJgitHO5hIzVmw+/qy9E3ftqT5SiqK8NadLZ9aSVHpT55J6bJhn0jJINi/lz7/+XLyHpryFntZhnERIHjrED5Z08vkRizmhKLeE/o1DWjHRxRmE/Dpf5P8IOFy8tmUmBWm5pA0lsK/zVQIZufR1ZlEiDiN0jTvKGpiXMp2qAy/wvG8NwhPgtiWF8Z7mlKICqTgYq5FCYGIXm4vxR8SIWEZKxjqbW2AKYe/aU53NFUU5BQvfuwAhoyT1r6C6+SU6Fvbh3OZm7YZ18R6a8ibMqIVuRjhQqJOeksJtLYf5p8gnafaU0LcgFU+i4Jt8gwJjF3WHrsQyE7hsoBKZrFF7bAP+jItxex2kvngXw8uq2Ke38WHDjRQ6X2+7jNsvKiLR44z3NKcUFUjFgRjf2RxwYAFyrEbKimWk5LgjYiyVkVIU5TR4/S4KCgUDyfNJ6DrIWk8x/uwCdj/4dXoGg/EenvIGjKiFZkXpF0Gu6GqmNnEZT4Tm0jEridwki69Fv0AO7dTW3EBzs5uVCfNJCDnZ2vsM3kAyPa15lAa60Ae6+XPVMPm+XFbsf55tSavo1dP46NLieE9xylGBVBxosaU9iYYlJxxaTGzX3miNVKyzuanZu/tUZ3NFUU7VnHdVYTh9ZB2bS1XTa7RXNxHoWMYff/N5tYvvPGVETDQrQtgBHjPKr7vnkDEtBT3g4O9DXyRdT2DzpisYHAhwfcLFZLV6qPcd4Ej9DjJKrkd3OMl86U6MxXN5xn2ID7ry0I0g/965gnfPzycz0RPvKU45KpCKg9Ficxn7xCHk68/ai3U2l0LgkBoWGrrqbK4oymkonJWOS4/iEgvJNDbypFiAv9CDvmOYx59Tu/jOR2bUQjMjRBzglpIwLuoDOh90PE6GFuaVl+fjd+VxQ3AB6YMJ1Hp2sGnHw5RUX0dHQzozs7pxdDTw8MWQ6k7h5tqXqEteSq2Zy6eWlcZ7elOSCqTiYLT9AUIgreNHxMjx7Q+EfdYeQkOXdpsEHUvt2lMU5ZRpukZFdTrd6XMYbvYx+9gRmmcfxa/NpO6lf6eutTveQ1QmMGKBVNQBHikJ4QJdMCv8V44euQSvK52r22eQ4PHwYud97D20lqJ576blSDklxRrpf/4G5iXzeShhPx/xV+AZ6eYbvatZPTubknRfvKc3JalAKg5GAykpdKQFjtjSnjn+iBg0u9u50HDGAim7s7kKpBRFOXUzrqzA0pwUtlczS3uRZ/wLCRT4STl4GX+999OEDTPeQ1TGMaIWmnE8IxWSLtAELiI0NCSzzJiJK8HFI7t/RFAGSS34MO0NRUwvCFL8wJdxlBXz1RWtZHozeG/tOo4lL+HVcCl/d0VFvKc2ZalAKg60sUDK/vGf2NncOklGSlMZKUVRzkhmcSI+VwTpXkSH6KStIYuWsp34U7OwDvRy70P3xnuIyjhGxEQzwkQcIpaRciJ1gVNG0YST7H4/m7qewJmYgKXfghFJYYmxlrx7v4ycWcx/vNugWxvh51YavqFO/r33Wq6Zlc3M3EC8pzZlqUAqDsYyUggsGdu1N3rWHhNqpLCX9kaPklGdzRVFOR1CCKYtyqQvuYJoQzarO9ZyIDsTV0YySUPL6Kz9LptqjsV7mEqMGTHRrSgRZywjhQuhgRNwCB1Lt6hv3YMncC0ul5eFW7+Lf9sT7PrwEm5dWUuXN8ovtHym1z7LvYFPsj5SzhdXqmzUO+msBFJCiGuEEAeEEHVCiH8+G685lZ2QkbJAf12xOSd0NndIu9+UpjJSiqKcgRlXTwehUd6+kFLfBtb1XUpf/hbSEjXydlWx5bHP0B+MxnuYCmBETTQrai/tWXYg5dItkE6cmo4lTHSnh+GBNOa2PYZrsIMffTaH/8rdzvvTq3n02BGqD67lT4kf4WsdV/D9W+YxI0dlo95JbzuQEkLowM+B1cBM4FYhxMy3+7pT2eiuPYSGlLGlPSactSdiZ+0JgTaakRIWqh+noiinKzkzgVR/GCNhEb3hHrzNYQZzBklKKWHIN5fetgbuv++X8R6mAhgRayyQ8sRqpJy6iZROdHtdAk13IoQkYdtTPHdrORs9zfzMXca/bn2Mbr2QNeH/4r8G1vD9W+Zx8/z8eE9pynOchddYDNRJKY8ACCH+DNwA7D8Lrz0ljR4RE3H6Se1LZCDooKqnBk9dmKFeJ3WyhkggTIQG6srduJwzkEdhc8iiNPQw9/zouTjP4PwlNBPTr5PgCGA4k0l1WvgtDYfw4XDpaF4Hbp8bh9+JIymZZFcy0p9JRqLn+NE9ijIFzbi8lPVPuHEcKeGmoqfY7ptDYmIjic4+sg9cQlvuT3lux2pWVatloHgyDTuQijrALS0iuhuPZiKlw17aw0TTneiaRAD3BvbxxUAVy3b+ld97P8jXO6/hvQsL+MM100n3u+M9nQvC2Qik8oDGcV83AUvOwutOWQ6XfVjkgWm3sbgJ9gGr+4DW6QBEYtd5AVMHb8j+CAEZwHDnOR/ypKGZEQoO/Ssb39NLYutVfGX2R/ha5rcZem061/Wu4sWG3yH872PJa9/jW+/v50taF6/130Dmmn/mo0tL4j18RXnHVC4rYf1fG8nvW8TwjEe4q+NWLsq6h4KOyziUmkbPoY3Uh/6Froo/qv8Ax4mUEiMq0c3Y0p6EqO7BTRTL0nGgY2IiNKfdyBkIO2Hp/qfZ6F/FN7qv4a4PL+LKGVlxnsmF5WwEUqdECPEp4FMAhYUX9oGJgXQPV3+0krYNm2nvOUp4uI+RqIEhTaS0kJYE5Oj/KacsH0uvJhDy0eoYokL0IEImfSIZj3uEiGbh1l2EiGA4A6QM9dGW5iFX66GpPxTvwZ91o52rhRBIKRFSgqbZ3fGF3WFfSjn2+Ni1loXQNKQlEdrxry1poQkNLGvsdY6fG6mc7xICLnKzoTu8kIb+R5hHDd2zXRQeS8LoO8aCw7PZOWMzd//lCb784XfHe7gXJMuwfw/HaqSkRURzkUgEy3Kgo2FKYyyQkpqGqYHHktzXM40vrZymgqg4OBuBVDNQMO7r/Nj3TiClvBO4E2DhwoUXdHwghKB8ST7lS9Ta9dl0cEsbz/12Pw7hQGqOWO3ZxN2QAqQEIdAkSIcbpyanVBG/GbXY8VwD9duaqNr7M7auyufFrCZ+0VjPven/wFPDhXTOTuLvAzvI7nuQhob3kuxMZm5DJsHpBi89czfzrv47Dr02zOW5Bxh5/mnWf+Uqnm5+nt9mrULfciffzfkhnWEnP3xfVbynq5yG6Sun8eIfD5F7pJSc2U/yBDeRlbSf/A4PnRlLaW3aw2WDP2DD4eVcUpYe7+FecAzDzjJpVoSIEzScCIeGi8jxjJSMIoQDBwaW2wHCwiMlQdzMUi0O4uJs7Np7DagQQpQIIVzA+4HHz8LrKsppGesYL7WxdhGvO3pnrIg/dhi0puFg6hwG3XKojz99cxObHz+CuXMLHUcP8eyRp0hq2EJjVztP7zzK+qERWgfbONr8AI1NPdQd2ktkayfBjj7W3/cHhnojvPpgLVb9YVp/8FNqwvX8ZNP3CPQ1MvK3v6emR/LopgMEPI4pFYBeCErmZyOwyBquIuSu41h9IUZeLZlJ0+hJMFmxO5WGpCaeePRP6iy+ODAidnNUzTKIOAS6dCF0gZMIpqnjsDQMywDhRJMmlssJgEdaBHHhderxHP4F621npKSUhhDi74BnAB34rZRy39semaKcptFicYHAEqCNBVL68d2Q49pKaBZjuyGnwmHQtZtaWfuHWjzRfubt+R07Sg5x/8d0/qG/i4NtV/Bu9220LMhiVfom3mvdy7F9c2gfXs71gzMwHYM8duhnJGRUoxlLmDaynZxt9/H8TQX8pqyBr3pKua12HQ943sPXh27mhx+Yz5o5OfGe8psSQniAlwE39r3uISnlf5zkuvcC38BeSd8lpbztXI7zXPL4nOTmu+gOVtHT8ghrAi9RU1FMum8Yf1cLTn0RuwZ7+Xjkj7xQ815WzlTLROeSGbUzUnpsaU+YzlhX8zCmqaNLDcOKIHCgSwMzVm/rtSRB6cbjUoFUPJyVPlJSyiellJVSyjIp5XfOxmsqyukaq9eJ9d3S37DRqYXEzkiZYmocBl23rYMX7qkhJdTE/M3f4d7LDrJ9lYvfdrbwx4HP8OOUT9OyOJ+PZTzKx7iPmq2X4jMvYk3vPKKJQzx38B7SK1YTMZayQNtB7tZ72fzpi/l1eQPfzruKD9Su45mMj/LP/Tfzq9sXnfdBVEwYWCGlnAdUAdcIIS4af4EQogL4F2CplHIW8KVzPchzrWJ5GSFvBmX1BSxxreX5vivpyt5IYUIOTZkVLNorGQjU88Cz61RW6hwzIrGlvdhZexYupCZwyjCmETvlwooicaBbUQyXjobACYRURipuVGdzZcoY7c8lRg95FhZi3NE7lhhd2rMzUrqFfYbhJG902n50gOfv3k+q3svsjf/LHe8yGJybxK8aDvNN8+/ZkrSctjlJfMj/Eiutx9m1axkJrlKWt1Ug8py8sOtuyhavoa+zjPnTwgReuIehj17PDwIbuL34Oq7f9Ac6s5fx2cYr+fsVFVwxPTPeUz4l0jYU+9IZ+5j4P/QngZ9LKXtjz+k4h0OMi9KqDECSGq6i1d2Jt2WY3gILMyWDsGhmTnM5j3gSmdf1V7Yc7Yn3cC8o5liNVBThEIRxIXWBiyCGqeGwBFEzDDjQrAiGS8OjORFAEDcJKiMVFyqQUqaM0RopITUsMfEMw3Ed46U1trRnCm1SHwZtRi1e+N1+PE6TmS//Ny9dmULNTC8/PFrLU77384xcTMfsJFYkD7Eq9HMGB25goD/ASmMeHr+X5/bdTXpBCZ1NM8gu9pNy3zfxzK/mG8U7KE8u50ttjUjdxWcGP05ZZoAvrCiP95RPixBCF0LsBDqA56SUmydcUglUCiHWCyE2CSGuOeeDPMe8iS6yc5x0p1XR1pbAdd3r2OmdQ32glnyXRkv2ZfiOOlnoeZUHXzsa7+FeUEZrpHQrinDagZSlgVMGMQyBbmoYRhgpdTtr5dTwCDt4CkqVkYoXFUgpU8b4o3ded4bhWLG5vcg3umvPGjsMOs6DP0Pbn62nt22EygP3YRQk8uv5PfxL3zBeXwn/1LWGnDlpOP0O3jvyDbyeeWzf7mRx0Tx8nYK2tGYG+jrInXEz0ZCk2r0HOdDPgY9cRsNwE39ffD3umr+yv+gDbOt28k9XVeLQJ9ctQ0ppSimrsHcTLxZCzJ5wiQOoAC4HbgV+LYRInvg6QohPCSG2CiG2dnZO/kZuFZcVM+LLoexYLrPdm9jStQBn7h6ykmfQ4RdcuSeD5wISc99j6uiYc8iIjstI6YKgdGEJgVMGMQ272DxihJGWA80ME3UKPMIudQ6iaqTiZXLdFRXlTYhxgZS0sBvWyQlH7zBuaU+KWI3U5DwMemQgwran6ylI7CPl6EZ+eMUIi3x5rOo4xn+Ebyc7PcDeFJ3b/QdJNBs5duxiEhMDzGzJwFngZ+OWBymdv4RjezTK5qVi3P8bfJcv56dDTzAjdQaX17yA9CTxb23LmJ0X4OpZ2fGe8hmTUvYBa4GJGacm4HEpZVRKeRQ4iB1YTXz+nVLKhVLKhRkZGe/4eN9ppdV2EXnGyDxaPZ2kt3TRme2n3RsihTYsz+Uc7vHxXvFXHtvRFOfRXjjGB1K6A4LSiakx1v5ARyNq2hkpPRom4hB4YjUNqkYqflQgpUwZY4EUAomwD4OGsWJzK5aRGi0212NnGE7WGqndaxsxDYv8TXfRs6SCXZkj/ENLPd2Zl/BwfyWps1JJdulcNvQDEhMv5dDBYaqLZiP6DDoD7YSGh0jKuoRIyKSMA5h9fbS+eykNgw18vPJ9iINP013xXnZ2wq2LCyfdETpCiIzR7JIQwgusAmonXPYodjYKIUQ69lLfkXM2yDjxp7jJyNDoSaumuT2Ba3vXsZnFdKTuoCChgJb0XK7a7OBgUheb1z2JMVlTtpPM6NIeRHExGkgJnIQxLR0HdrG5ZeloRoiwEzxoSASm5sI5yTLGU4X6qStThhb7/2YpdKQFTkywJBY6QlhIe68eSDsj5ZDa2O6+yRZIRYIGe9c1U5AaxNt5hN/P7WeBv4iZfa381ria7CQP2zwWNwS6EUYHHR2zcTgclLenoKd62LLtUXIqptN6JIHcimQc6x7DPW0af/UeINGZyBX9PWBFedhYikvXuG5ObrynfCZygLVCiN3Y/e6ek1I+IYT4lhDi+tg1zwDdQoj92BmrL0spu+M03nOq4tJihvz5lB7NZI57I9s7q3BnHsEbyMeIHiB7eA7PRQOsGXmYx3a2xHu4F4TRYnOpmXikxbDlBF3EMlKOWENOA2npaJEQYafEgyCqefA6z9lBJcoEKpBSpgwRi6SkECA5MSN1Qh8pKxZI2bv7JmOx+YHNbYRHDHJ3PUB4Rgkb0rq5vX+ISKCIX7WUUTQtFQvBpaF7SEioYNfOILMrZ6I1hqHSRW9rE8VVl9LXPkJppYfgjh0kXLOKFxpeYEXhClz7HkGmVXDnQT8rpmeSlOCM95RPm5Ryt5SyWko5V0o5W0r5rdj3vy6lfDz2uZRS/oOUcqaUco6U8s/xHfW5U7bAXt7LHppHs7eLzJZ2mjNTqXd2kOWC5pyFzK4BK1DDIy+8MiV6rZ3vRtsfWJqBS0pGLBfoAjcRrNE+UtJuyCkiI4QcEi+CiFD1UfGkAillyhhtf4DQkPLEXXsIiQUntD9wSA1LaGiTsLP5oa3tJKdo+Oq28MqiBLI8aVzesINXk96FruscTnWwLMlJwvCrOBzLiEYNyj32kUQNA7UgBKYsQQhIb90KQG1VGkPRIdZkLYH69TQVXEfXcIQbqiZlNkp5C4F0L2mpgr7Uaho7Eriufx0brUvoydhJgW8a3Qmw9GAqD/kTWTnwMK/WdcV7yFPeaENOUzdwWyYhnEhtYkbKPiJGC48Q1C08EiKaR9VHxZEKpJQpY/yuPTsjdZJde7HO5ggNjVi/KSZXZ/PBnhCtdf3kyXpwOrk/4wir3Dk4gF/3zGN2YTJN0uQSl13q09KSgcfjIa3FiTM7gZpd68ifPovGfUFyK5KJvvAknpkzec7cQ5I7icVDAwCsYyFCwCXl6sy1qap8aREDgWIq69KY49nI7s6ZeLIakf5UtOhhhvwLsVodXOx5lYc37I/3cKc8I2rXSBmagcc0CWFnpJyEx4rNTWkADrRoiJBu4ZYWYdwqkIojFUgpU8ZoMbTE3rXnGN9Higln7SFwSBHrNzW5OpvXbbN7RqZsf5zg/Er6XVFW9LQRTpvJxm4fyXmJAMwMP0FCQhm1NT2Ul5Rh1g8hC110NzWQP3MhvW0jlMwMENy9G/8VV7CtfRuLshbhaNgAnmT+1p7CrNwASd7Jt6ynnJryRfZOzKyRxbS4u8lvaaI+LZujrmby3Ik0Z89l+R7JM4lOfHWP0zEQivOIpzZ7154kqhu4LcMOpGIZKdPScUgd04qCcKJbEUZ0E68lCQmXWtqLIxVIKVPG69ofYHc2N0eLzYUc15BTR7cEBgIdc1LVSNVt6yA9w4GrYT9bZ7pIcSUxv3EnexOXAtAY0Jjnd6EPrMXlWkwwGKQ0IQ8kdFr2Vna3vxKA9GgzSElodinNQ80syFoAx9ZjFlzMtsYBLipJi9s8lXdecmYCuXkO2rMupbklkesHXmKjeQmDmTvJ809nWHQwva2UZ10BbtLW8uA21QrhnWRGLDRpEnFIPFISlqOdzSNYpsPetScNe2nPjDDsiOKxTIK48TrVf87jRf3klSnjhKU97KU9u+3BaI3U+CNiRjNS9lEykyWQCg1H6awfIFM2g65zf/phLvcVokuLBwbnUpGdyF4zyqUJXUhp0t9XjBCC3GAyWoKDhua9+FNS6et04PE5cRzcDg4He7LsTMMCfyH0HqUxaT4Rw+KiUhVITXVzr51G2JPC9Po55Ps3sr+tkoSsVoZ9blxWPe0Zi6mslYR8zWzavH5SLYNPNkbUQpcGEV3ituQJGSl7aU+3i81jZ+0NawYeyySkuprHlQqklClDjLU/EDAuIzWxRkqe0JBzcrU/aDnUh5SQ1LANWVlMh2OES4IhpC+Lv7SmUVwQAGCO3IWmeWhq0snKyoKmIK7CAC2HasidNpO2w/3klCcR3L4Nz8yZbO3fi9/pp7K3FYD1xnSEgEUlqfGcrnIOlMzLwOuMormv5MhwmNmNNdQlF3LMc5RCbw7tGcVcsc/JI4mJXDr0DOsPq6Lzd4oRNdGkQchh4ZFyrEbKRThWbK5hyijEMlIjuonHNBiRLrxqaS9uVCClTBmjS3sIu1fUCYEUo2ft2TVSaA40KbAAjcnT2bz5YC+6U8Oz60XaK+xs0fz2OnrTqjEsMFNcuDVBZnAdiYlzaGpqJT87F6NjBJmhM9DZQUZRJf0dQbKKfIR27yZhwQK2tW+jOrMavWEjuAM835PBtKxEVR91AdB0jUU3VNKfVEbRvsW83/ozzw6uxMjZQWZiJZFoHYHwTGpDXq5yref+zVO+X2ncGBEL3YoSckjcUhKSzpPUSBkI7BqpiBO8ZpQR6cKjMlJxowIpZco4vrSnn1AjZTfktDNSmrB37UlNRx+3a8+YJBmp5gN9ZKYLRDjIzjyDfF8OmT311DhnAtDiEczxewgN7cXpnEYkEiHbY++667PsM+KcsTYIaXQho1HkvBkc6T9CdWY1tO+FnHnUto8wPTsxPpNUzrlZK4oJeINEAzfROtJO4OgwA7kaLd4wiXTQkr2IpXtMNvoMjJpn6BoKx3vIU5JpWGhWlIgDO5DChdRjR8SY43btCcfYdR4jyrDlVEt7caQCKWXKGH9EzFhGiuNLe9boWXvSQuo6DgtMmDTtD4JDEbqbh0iTbSAEzyY1MN9j77p6OVhCcVoCNdEIczzDSBllZNh+LCPsBw2aOmtwuN2MDAXQHRq+dvu0lJZCHwDTUqZBRw3h1Gm09oeYlh2Iz0SVc07TBFd8YhFhTyqFB9dw08hveCJ6Nc1pr1Hoq6Ar0c1lB1N5LDGJd2treXRHc7yHPCUZEQvNjNgBknx9jdT4pT3djBB2CtxGhCFL1UjFkwqklCnjhGLzCTVSY4cWxzJSaHpsaU9MmoacbYf7AQg0bkeUFdMk+qiKmkjdzePt6RTnJBK2JJXCXnppb/eRkJCAt03izPHTeuQA2WUV9LYGSc31YRypQ09Opk6zM1XlegJEhmh1lwCojNQFJn9WJkUFJv3pqwg2SUr2NTNU3oOWkoMerWMg8WKczYI87z6e37wTOQl+ZyYbM2qOBVJuaY2rkYqAdCHEaJGCA82K2GftGWEGTaeqkYojFUgpU8b49geaBMZ27R0/a8+ukZJIzRErNgdNmkyGM1k7G4dAgHvXOnoqMwGY391COHMurcMST5oHgKLIJryeQpqaBigoKCDaNoIzz093UyPpBcX0tI6QmusjfKgOd3k5df2HSXAkkDNgB1S1VgEAlSqQuuAs/+ylICCv6yYutX7Pn7vfzaGCtZT5c2nImcF1rzn4q9/Lot6/saOxL97DnXKMqIVmhIk6wC0hJF1ITeCQFg7hwBIWQnMghIZu2kt7XjNKUNVIxZUKpJQpY/wRMZoFQtoNOaXQxxWb24t9aBq6BRaTZ2mvq3GQpFQnYqifo1ngc/ooad1Lk28WAEOJDnLcTjwj2/AnzqK7u5uMlHRk0MBKlESCIyRl5jHcFyY1J4FwXR3uygrq+uooTylHdNYA8NpIJokeB7lJnnhOV4mDxFQvcy5OpyetGnNvHh869gAv55cykO1Et/aRFlzEnqEANzjXcs+rh+M93CnHiIxmpARuyyKME6GDE3BoOlJINN3eAKJZUSJOewkwqDqbx5UKpJQpY6yzeSyQksIOpMxxxeZjfaRiu/YM7F17hnX+p6S6GodI9tpFvnuThyn35aGZEQ5QhEMTtDgl0xNcBEONCHKRUpKq21mlYcteFnS4MwAIeKJYQ0O4ysup662jIrkCOmogkM+eTpiWlTj281QuLAvfMxdds0iJrkaTr9Fdm8HRWdspS5/FwcJZXL3BxxPJBsa+v9LYMxLv4U4pdiB1PEAK4cKtS5BOHELHEiaa7kQTEoEkPK6WSi3txY8KpJQpY6xGCntpT8RqpCS63ZAz1tlcCPusPV2CJUbbH8R58G8hNBxlsCdEINoFQrDF20q5wy4G3xHMpjjdx5FQhBJXEJCEw3ZrhGTLLiTvGbb7Q0mZDIBvpA2AcEEmveFeypLLoKMGmTmD2rYBtax3AfP4ncxdnkdH5gL0g3l8OHQ393ETh4teo9AbQvPcQH19Ih/3/JF71qnz984mM2KesGsvjAunbiClfWCxhR1IOTT7D7+wEzyWJChVRiqeVCClTBlCH81ICbtGCtNeyBM62riMlBASqevoo32k5Pl/REx30xAA/q46tII8OmQ/FSaAYH1fGnlpCYQsSUGscHxw0A6gEoedCI9OZ8cxvIEkhvt0HC4NZ6u9LNNoJ6goD5RA1wFGkisZCBlMy1KB1IVs9qpSAIp7qqn1tpJT08axSghm+4j4B1m1dyn36YL07T9kR0NvnEc7dRhRu4/U6K69iHDh1kwsy4EudExMhOa0D2QHog7wSkkQVSMVTyqQUqYM7YSlPQnCAilP6CN1/IgYHS3W/kCbBJ3Nu2KBlPvINkLFWQBUDPcjU4o50GPgT3IDkGMdRQidri6dlJQUZGcEZ2YC3c2NpOUX0NM6REq2j0jdIfS0NA7Jdvu1NC+YETrdhQAUpibEYZbK+SKQ5iUjx0V3ejX6IQ+fiD7Ew4M3MFT6ApXps6nLLWPZ2mLCya/yhz/ew2AoGu8hTwkT+0hFdDduouO6mhsI4UTHxHI5QQjcozVSamkvbhzxHoCinC3Hj4ixl/YkEkYbcmpgIdGEBsKwG3JKJk1n887GQRICTrRjB+hYcikA5T1NDCWVY7WCSHQCYTKie9G8hXR29pKRkYFxeATPjFS6tzYw/ZLlNB0aJn9GKuGn7B17jYON+Jw+0oKDADRj7wbMT/HGa6rKeaLikkI2tEaYXp+Go2I/7oYRDs7LxzjWQGHfCF2Z18PWO7ii6id8695pfOWayxjoDBIeMYiGTYyIyRv+Wp3Jr9tJSvbeqozvlOr8Tva6E7858ctTedkzeG8jKtGsSGzXnh1IJRG1e0hJHVNGEcJhB1JuBxDFE2uToJb24kcFUsqUMb79gT5WbD4uIyVAEzpg2Tv7JHaxuTz/O5v3tAyTHJAgJUfSTdI8aaTW7+FQynIAhjwamTjQgjUkeMvo7u6mrLgMaziKlQjh4WGSsvI4sDVCSnYC0aZmElesoGWohRxfDqK/EYAj0VRgmDwVSF3wyuZnsOEvdfitap5wt3JF22u8Er2UivwHyRn+AA0tG5jWeSXP9w4xrX6IB7a+Fu8hTwneYDcRBzilhqm77HP2TLsUwbCioDnRpIHpsgMpr6qRijsVSClTxvG/AGO79uRoRkpDEyAFCC1WI6XpaOZoRso8r9sfSCnp7wxSnGYv7+3y91LuywVrB3UyD01Am1NS6XQT7DuG37cU0zRJdSYCJkHNfp7HlwGESAw4MLu7cebl0jK0n1x/LvQ3gtA4MBIg1RclwaVuDRe6QJqXQACG/MUMdrm5XN/OQ21rSMjt4OiRboo9fo4UzqW0LwX34BHKmp9GmM10+QYIug0iWoSI00K+YWLmdH7nBEKe+PWbv6R4w6vEhGtO+m6SE9JOJ321CcM/2TXidVOc+J4Tc18WBzKDHM7T8HY4wBE7Z88cPWcvCujoMorh0tEQOIEgLrwuVakTL+puqUwpmnZ8aU9gju3aE5q0e7AIewffaK8pE2kXm5/RWsO5ERqOEgkaeMPd4HCwXW/kRr0KgB2hbApTE6gLRbjJpyOlQTSaDnSQjB/oZygaKwbWAkAIrzXIEODMzaVluIWqzCpobYDEHBoGDLWsp4xJL0mltT2PWfWSnGm16D1BdhZVkZ20n6rBSyGUTGr3XoqO3MFPrgdHlsmVwSHyoiZRy4e0nEjLgYnjTX/Dzvi37/WRyls/JdZTbvRdj389+viJYxInXD3hGnHi18ed+Bwx4REx7tUmvg/Af3ZavBBZjOEWOAljmBq61IhaEcCJbkUxXBoezYkAgrhVsXkcqUBKmVKEOL5rzxKxjJQYXdqza6TE6KHF1vH2B+dzsXl/RxAAT38Tek4Ww1Y7BYYJwKb+VPLTEqg1LfJ1u84pGAwAHSRGXRhA33AHAKZh7+Rzj3QzBBgZKQz2DtoZqb6NkFRAU686rFg5Lr0wiSM705l5yEnjXIOF/TVslJfwwZRHaGvyIqTBtAN387UPCm7R+7ioJZn/Mj7PVv88BpMTkG4ddAG6QNcMNPnm/dpOtXPZW/62niQN9lbPkePf/RRuB/INwyebOEkUNfE93uptrGQ3BeY6jKiGbgkMM4KUOpoVJurU8Aj7P+EhqWqk4kkFUsqUIjRxvCGntJBCji3tGTBu156GJgWmlAh5fnc27++0Ayl322Gi2WlAO/nhINKfRV2fxeWF9o69TGG3PhgacuFwOHAOC6xEJwPdnSQkJTMyYKI5BI7eFgC6ku2lAHtprwFZcBHNR4NcOT3z3E9SOS+l5fpBCDKHstmuDXCRsZcfhT9BUmon3VGd5L46dpUYVHrCXNrl4T2Rr9FZVURFTgcfMO+iMNqGNiAhomNZOpblQL7xWt9ZJU4lGnrdUOSbP/y657/Je4xlq97gGjHh35ONYcD+aGorZ0bURSQ6ANKBZkaIOjW8wg6eVEPO+FKBlDKl2Bkpu9gcYZ8BM9bZPJaRAss+NsaS9tLeed7ZvL9jBCHAUb+fgUtnAJA33IuZWMBIl4nL5wSipJpNaJqL/n6LpKQkrP4IjmQPg92dBDIyGewJkZjiwWhtAV2nLdYlPdebBf3NjEzLJWxY5Keo1geKLTXXzmKOJOTRFmlkldaG7DMZTkjDslxkdO/h0WqLd4WG+Gn0Y3RX5lCReoyvGt/h8P7F9PVdTXkomxTpQ0ZDGGYYTBMpzQkLahOdXv3UGz5LTIxTJCf7zuuf9sYhlIQJ2/ZOlps6C+8xTiGCBMtk/0Athl6EZoSIOMEd26ocxI3HoQKpeFGBlDKl2N3N7RopE4Gw7FBptI+U3f5Awujy3+gt6y2WHOKpryOIP9kF/b10p9q/srl9rQylzgXA8uhAlGTjCKY7l/7+QZKSkjA7wjhzfAwc6iCjqITB7hCJaR6iLS04s7JoDtrdzXOlBtKk22H3p1I1UsqoQIYXXYdhXw4jw4J8rQ2tL0L34Hy8QGr3PnaXCL7TFeKr1lyMXD+fdvyUw/sX4h1cwMqR2ezqfpGtoUOYFCP0DDTc6JaJZkk0y7TPxDxbXhebnFjxdPLw7I1aHZyswmn8a5z88YlOO9f9upr28d+YToKVRWL9k7TmBvHgwUJHczjHTnZQzj0VSClTyvilPUuAQ1pYaAhNYgkQowcYjzXkjBWcWkacR/7G+juDJPrscTYn2a0PEvr30pZ5FQAht0ayqaNFGnB6cunr66OyshLjYAjPjFQGuzopXbCYrr0hCmelEd3agjM3l9bhVlyai9TgAAAt0m5zrlofKKM0TZCS6WaoM5fUASCzB60/ghEpxx3ppDtpgALN5JhRTtjlIdXRSkakiwOdV/Gh8Ay2dT9NOz0Iz+2UDuwl59ATdKX1cSA9SJ9PEHFAxAGmDuKs93J7i115b3blWzz+VjXub/n6b3M8R2bBtgrBvL4+wsKNV+2yjSv101emFDFu156Jfd6eRazAfDQjNVojZUnG/haWFlLK8/Kg3v7OEYrSQwAc9g2T580AK0oLduDT74R8p4tQqJmUlMsYHh4m4E0EQ2J6LIxohMTUDEb6IySm2hkp36JFdg8pfw7aQDMAR81UIEResgqklOPSC5M5Up9HRr+kNS9IQu8w0kzEP3iI7SVRVoSGeMa6jOHCJFawjt6eHFIsP8IB9YP7cAU+QVn/NgoPP8J/3GJiFvi4ra2VVWGT3mgWvWYaUem2P9BPulB2pibWJ524ICdPUr90Yr7p9c0KTuNxMfH95Qkrgiffvff6CO2NdhHO7QOnFHzfKiUnU/3OxpMKpJQpRRPi+K49hN0BGFcswBrtNSXHBVv2TUmPHVysn2dxVGg4SnjYwJvUB0CNu4dpznwAjplpJLh02i2TQq+TyGAHAjsYCjgSgChhRgBweJIBg8RkJ0Z7B47cXFqHN5Pry4U+uxlnXSiZRE8XiR7nOZ+ncv5KyfUTcQVI73LR6HRQaLVjWGUIy2TELaiIRHjEmouRlcAibSvtPaVUWlk0Bo/gSylG6D4Kd9/P997vwFWUwp0Hd/KUXMnf67ex+qJZLCxOISfJi9ep43FpODXtlDqHn6qJia7XhU4TLnj94xOf/+YveLrPP93xTXzOYuCf/O7XXaOcOyqQUqYUe2nPXrYzBAjLsovNsWJn7emMz0iZ8nggZVgWunZ+FWwOdMVaHwy2oKelUW+0c6UoAeDA/2/v3YNkzc/6vs/z+71v37tn5pwze9FqV0KAFCStJMQiJIyxUJBLZRGpKlbKJCYRCbEKkhBSdkwlkChcKlXGJLgSExdWgQp8i3EUcBTZwhZBNqmKJViEriBAtxXSavecM3Pm0tPX9/09+eP3e7t7Zmf33M/0vPt8qk7tXPrM+XVvz9vffp7v830mF3hos82XpnO+LSUWzIsNYEJXW8Cco2IfAOcHwC4dGTMqy5ghNXySNz78Rth9EtoXeGokbPftgmwcp9WLwnp7PODTbo8XydNo+VJEA6WLLyL79Gh0A18f/pjHrz3Ki8N9/P7uByhbL+YF4UnCZoePvWjEP3rij/g38mf4n7Mf5Fd/8A286GL3bO+cYdwBLArVqBXOC5qSzQOC1xWzeTW1JwEVl4b6opByBNZxcG94LU7W5ZefgIceoNSSFxbxoJ8a9nlgs8VhGbjPxQyp6SRO3PWKKIgORlcBCGV8wWpNdgFwD9zP7mSX7c42DC9D7z6uDKdcsne2xgla3SikNkZdrnnPI/I0ElgIKa9KoUKXCeVhCx+a9ILj8vjLlOWL2fyT3+ZPXrHBdmPAKyYj/u74TfzY97zcRJRRG0xIGbVCnCwm8koBryVlElKB6IESqmRzXbT2MsKiOrVOVEIqe+oLTLYHADw0OYLe/XxxP9BPFaRt2QHg6KgFQHuSIU3P/t5lGu02k1GstDXG8XajjSaKcrF1EY6uQHebq8Mp2yakjBNUQqo5bbHrGrxYnsaXKX9NwAOleDwBSk9bmwznX2Xse/hsiwtf+xgffGiHN2qbUbbFp9zLeOPLts/2ThnGHeS2hJSI/KyIfFZEPikivy4im3foXIZxSyym9jTu0RMtCQiIJnNnZTZPPipdVqTWMd38aG+K84L72hMcbKTog6NdysHD7I/nNDvxRe6Cfg0QDg48/X4f3ZvhN5sc7lylf3Gb8eGcVjdHr8WK1H43mlAuti8uKlJXD6dc7DXO5H4a60slpMqsS5jmvEiexqkiWsbWniolHkdAVXAqzLXEuR5dNyTzc37v4Rnf9fQX+W1ey+tess3AfHhGjbjditSHgFeq6quAPwb+29s/kmHcOqvxByWCr+IPUmtPxMXEc1wK5IxtMs96ppsP9yZ0+jnMplzrx1/X+/ee5Kj9gniDTqw0bRVfotHYZn//KGZIHc7wG01G+3t0NzcZH8xoDxoUO1fBe3YbM4BUkbpK0bnEwaSw1p7xDCqP1Dzr4g/hRe4ybrW1B5TicFqi6vAqFAQ8IMWE0VaHIne87mCHXxu9mje//P4zvT+Gcae5LSGlqv9SVasAno8AL7z9IxnGreOSkPIhtvZiRWolkJNl/IGsms0lUKyhkDram9JNQeNXuyWbzU0ah0+xl8XWyLzhaTmhPXuCVutBDg8P6ff7hMM5vpcz2t+js7HF6GBGZ5BT7uzgL2yxM4uLjC9mXZgdMsovAtRKSIlIS0R+R0Q+ISKfEZGffI7b/kURURF57F6e8TzQ7MZK6Dzv0tkvuSB7OAWngZA8UrG1F3/XvAqlhjhBGwLqhIZ4GsAf6cP82W+0tp5RL+6kR+o/AT54B3+eYdw0zrsol1JrzxEoVRY5UlKtiEGOVaQcYdHmWyeG16a0szkAX2vP2G5dgGLCrtsCYJTDdiNnXlyl0bjE0dER3W6XcjjD9Rsc7e/RGWwwOpzR6Tcoru6QXbzETvJKXSzj/T9IP+9SvVp7U+BNqvpq4DXAW0Tk9SdvJCJ94EeAj97b450PvHc0Wp553uXiIUz9HKcsW3tEj5SjiAt140fxLUsoCV7wKc+gUE+vacPiRr24rpASkd8UkU+f8uftK7f5ceJO2H/4HD/nXSLyuIg8fuXKlTtzesM4QTSbp9aeCBmBoNEjVZnNWTGbV+Ipo1w7j5SqcnRtSitlQf1pa8h2HnMOLusmAIcOthsZs9lV8vwi4/GYbqsDpUJLmE/GdDY2GR9Wrb0dsgsX2Jns0PRNutMhALuyAcClGsUfaGSYPs3Tn9P+J/808DPA5F6d7bzR6ubMGz06U2XX+eSRqqb24j5LT2ztZeoo0SieQklwgk8vNQWezFaZGDXjukJKVb9bVV95yp//C0BEvh/4HuAv62nJYcuf8x5VfUxVH9vettKucXeIHinBqa5UpBwiIZnNBVQXFamQ4vHW0Ww+HRUU80BzFle4fDHbY9vHBOOvlQP6rYydULKdZ8xmu0Cc6uv4OLlXSPRBtXobzCclnUGD8upV/KWL7E52udC6gBzFNzVPhyjQLnXrI6QARMSLyMeBy8CHVPWjJ77/WuBhVf1nZ3G+80KrlzNv9mnN4JqPDXKpWnsoQTwutfYcjqDHK1J5Wq5b4vDrlnprGLfJ7U7tvQX4UeBtqjq6M0cyjFvHVYGcaUWMTxWpRWuP4609iC1Av4atvaO9GH3QHO/gt7Z4er7LdsrQfWI2YLvf5PKs4GJWAoEQegB0JIqhqcYCi89jXk+7nypSqbUXjeaXAfhakYRUv1atPVS1VNXXEP2brxORV1bfk9jn/Tngr13v5zzfK+pVRSoKKY8gi9aeBEGcw1OgeLyuLGYqiyS2onia48mdpe4Y9eJ2n9E/D/SBD4nIx0XkF+7AmQzjlhEnqKvM5oJPHimkSjYXYh3KLYRUJbjWzWxeZUg19p9Cti9SaMF2OuMXJ122e0125wVbPgqmsoiu9JZGMTQpjwAQn8I484BOp2SXLrIz2UnRB1EUfGXWo9PwdGq6/FRV94APA29Z+XIfeCXwr0TkS8DrgfefZjh/vlfUm92cIuvSmsOuc0lIxdYeeBAWrb1YkQogDgkFpVt6pEo83lp7Rs24raumqn7DnTqIYdwJVlfElLDItjlWkdKYI7UQUiIp2Xy9hFRVkcqu/inFxehh2p7PwDd5YpjzkgdzArAlUTBNpymMs4zj6qPpfvpJbeAazfKIKeAvXmRnvMPLL74c9q5Ac4OnR/Wa2AMQkW1grqp7ItIG3kz0QgGgqvvApZXb/yvgv1bVx+/1WdedVi9n7jv0Z3DNZQshFYRqiWWc2ktCKg5zOwjHK1LmkTLqiNVYjVrhHKhLU3siZJSEsGI2Jy0tRpC0Eyawnsnmw2uT+E7/6SeYbEZv1PZsDL37uTKc0Wmn1R1ED9VkGitRrXmsEAzHMeIglFFg5fO4RsZfvMDuZHfZ2uvFVPOaTewBPAh8WEQ+Cfwu0SP1ARH5KRF52xmf7VzR6uYUrkl3nnHNx/ffi9Yegoik1l4M5AwaG+YuFBRu6ZFScTgTUkbNqGcd33jesjq1t/Q+AdXSYgT0uEeqlPU0mw/3prR7OXr1MsPNVwBw32iP0LuPw6cLGu0MmDPQmFY+OsrI8xw/BtfNGR3s0+x2mY7i/cqP4u0m/RallsvWXvc+ru7PeORi50zu591CVT8JfPMpX3/3s9z+jXf7TOeVKt28FXpcczO2WAZyqnrUgZNYkcqpQm89Xkvm6KIihbNEc6N+WEXKqBWrK2IqgbQayLlakWJhNpeUbH62Zz/J+GBGpxNbkbu9+EJ0abjLpBU9OtKMqeaDcBnnGgyHBb1ej3J4MoxzHkXXXsyO2k+7Yp9ZkapXa8+4c7R68T13rj32pKpIBYKT2NpzkjxSEheDJyHltGQuigcCHm9Gc6OG2LPaqBUiqx4piaPZAZSwaO2pJt9UUk4FVbL5eimp0eGcVl4CcKVKNR8+zVFKIQ+N+OvbK5+kkV/i6GhEt9slDGe4XiOuh9nYTKnmMYwTYLcVlxFcaF2A4WVCZ5vd0ayOrT3jDlFVpCR02E9Vpaq1Bw5dmM0FOVaRKpijZAhBPJlFHxg1xISUUSucX6lIAU5CqkHFgMvTWnuhMpuvmUdqfDij4VKqeWvCpdZFGF9jz18AYJYLbSf4+VM0GpcYDofHKlJH+3vLMM5+TrFzFb+5yU4RTegXGxsw2WPavIAqbHZMSBmnUwkptM2+i8+TxdSepqk9iW9QvHhUNb2hKZg7yBBKMaO5UU9MSBm1QmTFI5XiD0jG8yiTlvN7nMiRKterIMV4OKcRYrTBV7ND7mvEyb0dNgEYZRLXw8yPr4cJh1VF6hqdjQ3Gh7EiVe7s4C9d5NokmtC3JLYGxz5mSG20zb9inE4lpIK0mWt82agCOauKlEvxB4s3K5pae6TWnlhrz6gn9qw2aoVzHKtIZZSQUs4DYaUiBaKKqFKmtsQ6mc3n05JiWtIs44aTP/UHXEqJ5U+FTUTgwOliPUyWX2A0GtFtddB5gLZjenREJ7X22v0G5bU9ss0t9mexIjUoYttwKDHI04SU8Wy0evG5Mc+7uHkU4FVrL+BQEbwkj1Q1tSceF0oK0cUamdxae0YNMSFl1IqF2TxASGZzNBrKq9Ze5ZEC0nSfrF2y+fgwrnfJpwe4TocrYY8t4gvYk8WAC50GV4qSS3nGfL6Lk00AOlkUW2UWfVDt/gbTUUGrl1Pu7+M2NziYHtDLe2SzGIdwQBRSmx0TUsbp5I343Ct9g+Z8WZFCookclzxSSEw0V4U0tVcsFhtnFsZp1BITUkatqIRUfAe80tpjkR6VjLBJSCkUsn7J5uNh9EZloz3chS3GxZjNJPS+PO2w3W9yZVZwKStRLRfrYdo+Tt7N0569vBG/3urklAcH+I0NDmYHDBoDGO8BsKdxjM8qUsazIU5woqhktGZVRSqAi/vzlhWp2NrTlM62qEgRK1LmkTLqiAkpo1bEsL9YkSoXFSklIKnilJYWJ81U5U05dK2SzRcVqcMr6Eb0MG2V8XxPTNpsdRtpPUxMPy9D2qdHElLJWyWpQtXqZpT7+/hBrEgNmgNIgZ27wYSUcX2cF4LLaM2qilSJOihOTO05hKBxr0Bs/ymZxspV5u0lx6gf9qw2akWsSElMNodFRUrTjj1RnlGRqipX6+SRqoSU33uaYiMKna1iBlmbp8eOXjtHgYFEIVXMo4BqaMz4mRZjAERSqnkOOpngNzbYn+2zkSb2AK6WMTXdhJTxXHhPFFLF8dZeiUcXOVKrFSl3rCJV2NSeUVNMSBm1QpygVUUKIVu09tIi1cVEUbx95aXylGu1ImZ8GFt7fudJZv0ohrbmU+hcYG80p5XCOHtpz958HkVQs0iTePNoUl8IKY2Cy28MVipSewBcmbdpZI5W7u/BPTPOKz5zBJevVKSikCqSkHLHKlKapmdTRQq1hcVGbTEhZdSKGLQseF0xm6MEHEhIHqnollJYTPf5NVtaPD6ckeUOdp5mnCamNqdHaOcCe6MZjSSk+hoN49NprEQ1kpCazKKQChozfxplrFAd80hN9iDvsjuBTatGGdchCqlsxWxegpPkkWJRkXKxUQ4IEkrmbjm1Z609o47Ys9qoFVVFyqtQrJjNy2R3JbX2gMV0XymSks3XSUjN41qO+ZxhN4qjC+NDyuYWQcGnKaoOMcpgMvFkWYafgrQ8k6NDnM8okjE4S8LKDTbYn+4vPVLtTfbHc2vrGdfF544g2bGpPT2lIiUaBzoEj4SQPFJKibPWnlFLTEgZtUJ89Ej5Kv5Aoi+qqkjBUkiBW3ip1i3ZfDyc0WrFF539juLE0R/tMm1sAiBJSHXDNUQyxmOl3W4TxgWukzMZDmn1eszGMQbBT2Llquy1mIXZcmqvvWVCyrghfMOjLlu0j0UD4qBQDyn8NlakhEAAkZh+LpCpUmDxB0Y9MSFl1AonySOlsmjZxam9tLhYgUVFSlZ28q2b2XxOK4/n3G3FPXtufI1RtgmA5vEFqROukmUbjMeTKKRGc1w7Y3I0pNXtMTkqyJsehgcAHCVxttFMZvOWVaSMGyNrZM9s7YlSkFbELHbtpUDOxdRewKMUOAvkNGqJCSmjVogTIHmkkJRsnipSLIVS3AXmFpWr9RNSM5ppz97V1oyt5iaM9xi6AQDzzCFAs7xKnm8yHo9XKlIZk+EhrV6f6WhOs5MRDmILcNiOL2SxIrXS2rMwTuM6+NwTfINGuWztiWMhpNzCI7Wc2hMNlF7xGgWXrYgx6og9q41aIY6YrqyykiPFsiKVQjkhHFsls07J5qrK+HBOQ6NB/Ol8zGbeB5R9iUJqlgmbmacsrpHnG0shNSpiRSq19iZHBc1uTDVHhIM8irON5kZs7VlFyrhBfCaErEFjxSMlUgmpqrVXJZuvVqQUHwKFBXIaNcWElFErVlfEHG/teUSUkJZYHBNS6UVgXczm80lJWQQaRYw2eDI/Yivt2dtL61zGXtnKM+bzffJstSJVtfYOaXV7TEdzWp2Mcv8ANxhwUETTeTW1F1qbDKeFCSnjuvjMEXy+qEihJV5grtkzKlLRI5UqUslsXqiZzY16YkLKqBUuXai9CkHk9IqUCLHNtxRcbo3iD6r1MPnkAGm1uKz7bKXVLzuhhxMYCmzmnmK+t2zttVJFamE27zMdLStSfjDgYBa9UgPfgvmISRZT001IGdfD5w71DfIUyKkS8KrMFxWppUdqtSIVXMBpqkiZR8qoISakjFohrlpG7FcqUsupvbgkJvqlqopUWDOz+XSU9uyN9/BbW+xP99lMC4svF1022jl7ZclWljEv9nG+T1EUtBrNqA+bjtl4RKvXZ3KUKlIH+zHVfBq9Uhvpvo5crHCZkDKuR5UjVWWVqQQyhVJ9ypEKJzxSaWrPgw+BuZpHyqgn9qw2akVVkYq1qJRsngI54+U9xIqUhkVMQrlINj/bs1dMj2JkgTvcRbY2KLVkS+P9enLeYavT4Nq8ZDMTyvII0tLhVqpaBV/Gz3s9pkcFzU6qSKUwTieObhFX0By6WJHaNLO5cR185lCXkZfxuRgb5nEaDyd4ikWOVNCA4HCVR0pDnNqz1p5RQ0xIGbUitu14DrM5yWyuCy9VtZNvXVp7k1SR8oc7lIO0Z6+M4ujJaYfNTs7evGAjCaagcVdeU6IYmpMWHjc7lEWg2c0I+wf4jUEM42wMcJPY4jvAKlLGjeGzGMiZlakiRUhBm6dM7emqRypWpAq1FTFGPTEhZdQKSc9op8dbe2Uym+sxs7lfms3XKNl8epSE1MEV5t244mWrmIFv8tTYsdFpcFgG+i7uzwtp6XCTJKTSXj2XdQBoJY+UO7keBtjTeBsTUsb18Jkj4MnLyiNVpqDNKkcqLHOkWJ3aAx9K5urMI2XUEhNSRq1wvmrtCaVISjZXFAeiqCgiySOF4BSKZEpfl/iDSWrt+WuXmaSW2+ZsEhcWjws6rVgRGMgEgHkRW3pNjfv2ZiHGJrg06ddoZ5QHB/jBRlxYXGVIAbtlFFIDE1LGdfC5o8QthFSQkJYRuxWz+UpFKuVIBQeZBua2tNioKSakjFpRtfZQRxA5ZjYXVnKkFtvpIYhfK7P5ZDQnazh0/xrjThJN0yPoXOTaaEarGQVTjxiPMJ9FEdQs49cn8xEAIklI+QLKcuGRWmRIAbshCamWCSnjufFZ3BogxOeZSiBfqUhVu/YcjoAuWnuFhyyEWJEys7lRQ+xZbdSKxdSexnfP2QmPVEjxB1rlSAUliFsrITUdFTTbHkJg1Iq/ooPxAaF9gdGsjCtfgC4xE2qahFQjeVfGaUFx0Gb6eqxc+Y3BsrU3jR6pnXmbhne0cn+P7p1xXvF5erlIXrw4tRdWKlJxau8Z8QcCXishZRUpo36YkDJqxWJqT9PS4mO79sKKR2ol/kCi4FqX1t70aE6zGe/HsB0raP3xHrM8ppr7tLC4pzHKYDrxOOfwE5DcMRnFBcUhxBe8rIgVKtfvM5wN6TV6MD2ErM3BXOk2TUQZ18dnlTcqTYey4pFyqxUpIVCyiD9wkIWSmXq8eaSMGmJCyqgVldlc1FOkSlM0my+n9pysJJsHKJxbK7P55GhOI4tn2W8Geo0ebrLPxMeoAm3EO9nRXUQ847HSbrfRcblINW+0O8wn8WdkRfRM+X6f4XxIL09CqtnnaFrSa2VncC+N80YlpIKLAxALj5T6GCVyzCMVA28XZnMNzIMjt9aeUUPsWW3UimWO1DOTzTm2ay8a0BcVKdG1iT+YjgoaWYw22GsUacpun3ESUiG9q2+HHbJsg/F4slhYLO2M2WhEs9tlNk55VJPU6uu0mZZTunl3IaQOJwW9pvmjjOtTCamyyitzMZCzwCWPVICUI6UEpIo/8EKuJQXOzOZGLTEhZdQKWbT2hDIllq8Gch43m0uKP3Bksj4eqcnRnAYxAmG3MWOQ96GYMEwp5EXmEKBZ7JBlAyaTCa1WC50UuFbGdHREs9NlNkl+qnE0pU+T32rR2mv2GU7n9Ky1Z9wAlUeq9FVFqsRT5UjFilQIadde5ZEKJaVAHkrmtrTYqCkmpIxaUQmpamovozzFbL5s7fkAwTlyAuW6eKRGBblGg/jVfMIgizlRQ2I458zDIPOE8oB8RUiFaYlreaajEY12h9m4oNHOCMNYkRol39Vqa284Leg1rbVnXJ9nVqQUv1KR8pTJgVitiDkef1CqJ/P2kmPUD3tWG7Wiij+Irb3VZHP/zNbeIv4gBnKuQ2uvmJWU80BWRCF1xY8YpBeu/SSkJi4KqaI4JMv6TKdTms0mYVIgi4pUh9mkoNHylIeVkIr3bymkBskjZa094/r4LP5ula4BWkaBxDLZvPJILab2pFoRAxnEpcVWkTJqiAkpo1a4RUVKKKrW3smpvVWzuRJN6aJrYTavwjjz+RBptdjVIYM0bn4tRCE1drCReebF4SmtPc9sPIqtvdWKVJZxJHF1TLfRjfEHC4+UVaSM67NakZLFDj1SjpQcn9pbCeQsPYvpPvNIGXXEhJRRK6RKNk+tvZhsvgzkDMIy/oCqIrU+8QfTtGcvmxzEAM3pAQOJHqbdsk2vmXEYAoPMU6aK1GQySRWpMnmkRjQ7HabjkmY7IwwP8b0ew3n0Si0rUr1ae6REpCUivyMinxCRz4jIT55ym78qIn8gIp8Ukf9HRF50Fmc9DyyFVCMFbUrySC1be1QVqZMrYogtwNziD4waYkLKqBVVsLlobO15Ti4trszmy4pU3LWna2E2n6Q9e9l4Hxn0mYUZA4136krRZtDK2C/KVJE6wPkeZVnSajShVKSVMRsd0eh0mU8K8lZGORziej2G89ji62YdmB4S8h6Teajz1N4UeJOqvhp4DfAWEXn9idv8PvCYqr4KeB/wN+/tEc8Pldk8+GasNImmqT2/Esgpi7GORUVKwKflxt7iD4waYs9qo1ZUrT0VR9Do4Vi29pKQknShT1N70ZQeKMMZH55oNAfww120H1t5gyTwrsybDNo5B0VJ3wshjEHTGhiXxFAOZVHQbHeYjmNCehge4fp9jqqKlGtAmDPL4hRgXXOkNDJMn+bpj564zYdVdZQ+/Qjwwnt4xHPF8YpUSemJFSl16CKQ06VU8+hXlIWXyjxSRn0xIWXUClkRUhogk/KUHKllsrkPQikOL+VatPaqipQ7uErZi9N6gxAzpZ6atRi0kpBy8WtB420qIVVIFGLHPFKHh/hud1mRCvGFbuzinr1+jT1SIuJF5OPAZeBDqvrR57j5DwAfvCcHO4cshJRr4lQphOSRyhbxBwQh/hrF2y527SWPVGatPaOG3BEhJSJ/TURURC7diZ9nGLfKMSGl4EUXU3sigYCuJJt7MhXKVJFaB7P5NJnN/f4V5t04rTco5pB32Z3AoJ1xWAZ6LgouDbEi1UyG9DLlT+WtNsUs0GhnlEeptTcb4sXTLqLpfJKEVLfGQkpVS1V9DbHS9DoReeVptxOR7wMeA372Wb7/LhF5XEQev3Llyl077zrj8zS1lypSIXmkloGcJYTomloVUiF5pEoL5DRqym0LKRF5GPjzwJdv/ziGcXssWns4VCUtLV4N5GQRyKkIGdGU7lmPZPPJaB7F4LUrTLtRHA1mU2htcDCe00qipytTAMoyhiM2NH690CiSXJZafq2McDhctPa6eRdJS42PiNWsurb2VlHVPeDDwFtOfk9Evhv4ceBtqjp9lr//HlV9TFUf297evqtnXVcWu/Zcttyhp6zEHwQEt5jYQwOCLjxShXoy80gZNeROPKv/FvCjnPAeGMZZsKxICSh4iW2sZ5jNq0DOKgF9TZLNp6Poa2I8ZtyJ03SD+QjamxxM5jTTwuKuxJypoohiK9f49VmIOsC5WM2q4g9cr3t8zx4wJFak6hp/ICLbIrKZPm4DbwY+e+I23wz8XaKIunzPD3mOqIQUsDSRLypSgtOAw8WJPYkTe8BCcFlrz6grtyWkROTtwFdV9RN36DyGcVtUS4upWnun7dqTFY+UCiEtN16HZPPZuKDRjHfiqBVfdAbTI7S1wXBakFdCiriIeJ6EVDNEMTQvo8ASXwkpTxgOY/zBbJgypKKQOkz+qn59K1IPAh8WkU8Cv0v0SH1ARH5KRN6WbvOzQA/4P0Tk4yLy/rM67LpTTe0BCxO5X6lISSWkVjKkgJgjhZrZ3Kgt172CishvAg+c8q0fB36M2Na7LiLyLuBdAI888shNHNEwbpzVqT0UMgnHpvbCSrI54shC9EjFPWFnL6Smo4JGGsAbtuJ5+uMDiv5DqELWiC9mHWJ7bjaLv8J56SmBybwaQIstv9wrs/kc14utvV7eg9TaO9AWMKutR0pVPwl88ylff/fKx999Tw91jnlGRcotBVKsSMXfrVA10CshtRBc5pEy6sl1r6DPdqERkUeBrwM+kdZyvBD4mIi8TlWfOuXnvAd4D8Bjjz129q9YRi2pVsSoOEIgeaTiu+bF0uKVZPMMt2xRrIGQmo0Lch9fgA6agV7ew08OmGx9EwCSqgIdPQBgOo2fZ3MBgeksCSmNFams8kyl1t5WayummgN7RQs4qG1rz7izuJW2XCWkKoEUC74anYgr62GAxSqZORm57dozasgtP6tV9VOqep+qvlhVXwx8BXjtaSLKMO4V1cVecRCiQFokm0tAZSWQk+SRqnbtrUFrbzouyF2c3NvL5wwaA5jsMfYx80mTkGrrASDMpkKz2YRpQBqe6ThmRYUQy1pZGVuAPpnN+3l/0drbLaPYMiFl3Agigk8h+IvWHtFErlVFSoWgZVxdrIFA9CtmVpEyaoy9PTBqxWpFCqLZPC6sqDxSrHikBKdCSDv51sFsPhsX5CnCYDeb0m/0YHrA2PcBCGlxbDPskmU9JpMZrVaLMClwrYzZ+Ii81WY+jVWtavlxlWy+8Ei5jIO5p9Ow/WfGjeMWK5hWp/ZcjD54Rqp5FFtQmdLNI2XUkzsmpFJl6uqd+nmGcStUZnMVSRWplV17K1N7mszmVY6UWxMhNR0XZGny7mo+YZDFybqhxIpUkUWHV6u8RuaP79mTlo979tptZpOUR5Vafa7bW3qkpofQ6DGclbX1Rxl3hyxf5kMtd+h5vARU3bK1lypSRapgeYVSPZm19owaYs9qo1ZU8QeIA1U85fGlxYtk8wAuwwcIxIWrZ93aC2WgmJbkafLuqhsx8DEP6oC4LmbuhH7mKMsDsnzAdDql1WqhVUVqNKLR6TIblzgvyDgay7XbYlyM6eapItUccDgpap1qbtx5lhWpamov7tBzUqIqMUdqEX8QFhWp6JGyipRRT0xIGbViObXn0WMVKb+oSDmJU3vqPB6XpvbOPtl8No7mXD8fIe0218pDBi5O3+1rrExNPPS9pygOFxWpVqtFmJa4lmc6HtHsdJhN0nqYoyikpq1YGlhUpJp9htPieRHGadw5/KkVKYcTfWZFKpSUSTeZR8qoMyakjFqxCORM6eU+fnSitRdTl9VnaeqI+D76jIXUdFy144b4fp+D2QEDiULnWuggAiNRNrIkpPLBSmuvQFoZ09HRcs9eyxMOo5AaRV95qkgdQLPP0bSg2zAhZdw4VQRCFchZ7dCrKlJV3bfySJUnPFK5BXIaNcSElFErjuVIBXCy9EhR5UilihQuLi1emM3PuLU3S0IqGx8ggz6TcsJA4/3ZKTv0mxkHZWCQeYrigMz3j7f22hnTRWvveEXqKI/3rddYVqQOJ1aRMm6OpZAqCU6WO/SkRNXFHCldtvbK5JGqks29rYgxaog9q41asbq02ClEmaSLpcUxKjBN7bkMp0IpJLP5mR6d6ShO67nxAdqLrbxBEneX5y02OjkHRclGnipS2XGzuWt5ZqOj1Noraab1MNJoMJKYJ3WytWceKeNm8HlURsscqaoiFRYVqUBAUiBnVZFyYFN7Rm0xIWXUitUVMS7Ed85o9EwtAjlTsw/nyCqzuZ59snnlkcqG1wjdaDIfJHV3edZi0MrZL0oGySMl0kVVaTWaUGpq7Y1odroxj6qVUaaFxcN5rEytCqkj80gZN0nWOC6kMtI0XjW1p6tTeyUhtf+EWLmyXXtGHTEhZdSK1RwpF0BlJdn85K69VJEqiBWpIpxtSWo6jhUpOdhh3okm80E5B5dxZeoZtGJFqu8DEFDirryGSztlcqGYTWm028wnxaIi5XpdhmktTJUjpakiZfEHxs2wNJsvp/YKHJ5qam/VI7WsWgEUZGY2N2qJCSmjVqwmmy9aewqKjx6plGwuouA8XiGk1t5Zx0hVFSl3cJVZJ4qjwXwKrU0OJiX9dsZhEei5KLg0xKpVMwmp4OLfrypSjZanHB7iu71lRcq1YD6iyHvMS7VUc+OmOGY2T1N7JR7HMkdq6ZEq08LiSKGOzDxSRg2xZ7VRK5YeKcEpKCE28sTHEe1UkRJR1LmUbF55pM54aq/ySO1dZdyOLZTBbAKtDfbHczrNDAV6Em9Xhli1akgUUgXRrN5od5iNy2g2Hx7h0noYgF6qDkx9zKXqW2vPuAlOCqlsUZEqVipSVbL58YpUibfWnlFLTEgZtcIda+0pSADVYzlSyxUxHlfFH+jZC6nZuCRvxvydcSvej/50CO1NDiZzGsmf0pUY2FmmXXmNEMXQXGMietZoo0GjkDo8XKyHEYR2GcXWxEUzu1WkjJvh+NRetbTYp9ZeVZGKgSKuikhIf9cCOY26YkLKqBXLFTGxtQfRIxXwxEQExUnau+f8ItncrUGy+XQ8p9GMd2DYjGcZTIeE1iajWUmjmYQUce1LMY8vUQ2NXy/Sahnnk8BKHinfW66HkVmsTI2Sv8o8UsbN8MxAzji15wknPFISBz3keEXKPFJGHTEhZdSK1fgDvzCbr1SkBJx4SGssvBLN5roeyeaN5Bs/aAbaWZt8vM88jwuLq9HzThJSs0pIpYrUNK2WEVcJKU95dBQrUrPhMkMKOCJWpCz+wLgZTgZy+pQP5RYVKYeqLjxSTlc8Ujhy80gZNcSe1UatEBFidy9N7akuVsQ4AQScqzxSsbUXzeZnH38wHc/Jszg5uJ8XDBoDmOwxzQYAuFQNaOsBAPNZVF15CuuZzqPAEokm9EarmtqLrb3Fnj1gmCpSFn9g3Awnd+1laAzkpDyRIxU9Ui4cr0g5q0gZNcSElFE7RJ7Z2lMc4tLUnsQJvpg1JZSq8R32mSeblzTS5N21fJaE1D5jHytSmqoBnSSkplPBOYebAQLTWRRSqklgSQFlie9HIRUzpOLfPdQotswjZdwMlRBahG2qg7SqWNUhx3KkopDK0q/VHH9WxzaMu4oJKaN2RCGVpvZSjlSQqrUXPVJCVZHSRfzBWZvNp6M5GXEibyebMMi7EApGEifsQhZfxFphD+eaTCYlzWYTpgFpemaTUfpJcZovCzHN3PV6HM2OFhlSAHtlqkiZkDJuAvGnCSmOVaR0Jf4AYtUqqKD2cmPUFHtmG7VDnCwDOTWgKAGHE+KKmMXUXrxNqeDWINl8Oi7Ik2H8SjZm4KPYOZQeAPMkpJrhGlm23LMXJgUuLSzO8gbzqJ/IQvRMue5qRSoKqf0QfVTW2jNuhmVFKrb2SLsgK48UQEjjGxXRR2UvNUZ9sWe3UTuq1p4PxPiDsJJsnipSEGL8QYASPfNk82tPHTEbl2TJMH5Fhgx8rCztazSGzz30vEPLfbJscMqevRGNTmex/Ngnz5TrL6f2KiF1rWjgBNq5tVuMG0cWQkrTHr34/Kmm9oAYyEls+cXvKQUm2I36Ys9uo3Y4Jzx9/+v41qdeym89rfwoT8Hn4BrfB8BngSYvZQfY6f8V3vYv4ReBv85VfvGdf+9Mzjxr3ofonPG/+SVmDbg2usynL0cf0y9/5SrwAv7kyQ/i/av4/Gc/Sd8pu3/4VUbzQ748+STe9fjDpz6DFkP+6O/8L3DfW/mpX/8+/grw2V//YQ5fA3/88d/n1/Y3+Hd8h4NpTDWvVuoYxs1SrlSk/EpFqloRo0lIZVaRMmqOCSmjdrzmzY/wxd/4CMOjQ7Scc8Ye8huiffQl7rv8QV7y1T2e2oSpg9eUXwHgSrEJoswbGd1yiGYTJrMOwQkdaZM5z7Q8oBSFrI9qG19MuDjOgJLPbPSZuENeHp5EZp5DaTOcFuaPMm6L2NqLFSmXPFLAwiNVESf7rPJp1Be7khq147G3voTH3vqSsz7GLfBuvvKR3+K/+/CPAPDScgeAMBsguWfe2OaCFDTLEmluMvclL7zvBbQv9yn9Pu2ZZzreYPPl38HwC0e88+G/zCHvZf4db4Wv/WNelM14pFtwOGpzNC3MH2XcFqUTtKjM5uGER2pZ6ayypgyjrli91TDWiBe+/k284HVvBGAQ4tTTV/dyykw4YINWOCDL5kxnjikFjcKTSYPJ9BANU0KZM5MWWTGBL8WK1hfmXwOgNz5gw03YL1tWkTJumzLltQGLXXsQK1KCW2ipKv3cMOqKCSnDWDP+0r/1lwC4v4xCaj+0IXN8pdykFa7h/ITxWJhrQTYVMs0YjQ8oiwkiDQ5HDl+MmX7h8wD88TQKqu58zFa5w0FocvlgauthjNsiONBQmc1PTO3J0myeKZT2UmPUGHt2G8aa8R0PfQfv+7af5rHJlCEdAg7NHSWOju4jUjA6isavfBr3m03mR8xGByBNDvYKsnLC7IkvM2s4vnj0ZQB6qmyOn2BIhy/uHNG31p5xG8SpvfgS4hZTe7oI5KzIVCnUKlJGfTEhZRhryMu+4S8gvrlINadKNScuHS6KGI3Q0CiG5mGaTL4NQoBMZzCfU7Ry5iGGfHZDwIc5Q9rMimCtPeO2KF1cvQSnT+1VeMwjZdQbE1KGsY5kDXjw1cybmwBIHtskCyFVxjUwq0IKQCQGbebp9qHbWvzIfsrJOtQq1Ty/m/fAqDnBsZjGW53aC6sVKQGPmJAyao0JKcNYV77n5/jEq/57AHqtKHq6xJDNsqpIcVxIOR+FVKOVfrW7ncWP66bk9sXC4qa9uBm3TumW+VCrU3uKLuMPFDIR80gZtcae3YaxrjzwKBvf8AYAttpJSMkYgKI4vSLV7HbTf6PQ8v3+4sf1siigJhLFlcUfGLdD+awVqRKQZSAnzhYWG7XGhJRhrDHfeH+f3AsPbMYW3UYe/xtC/G9DohiSJLQ6g7iXr9mPoinvD+L3Edq9++PHrfg1a+0Zt0M4VpGKHimlij9YCicvzgI5jVpjQsow1pjtfpPf/Kt/jm//pvsA2GrEalK7fSH+txc/bw6icOpsxApUczNWplqDLQC6eRfXfwEAWTsJKatIGbfBakXq2K49NC68BPNIGc8LTEgZxprzootdHh10yEV4qBUFUqdzCYD2RhJSW1FA9S5EkdS6ECtT7c14u27ehf4D8bbdzXjbmnukRKQlIr8jIp8Qkc+IyE+ecpumiPyqiHxORD4qIi8+g6OeS0oHhVbxBytTe5XZPGmpTLzFHxi1xoSUYZwD3nxxwMe+/eW8sP8g3vfo9y+SZRmNzQ4IdC5sAtBPQqq9HStRzcEm/bxPL+9Bau21+hvA86K1NwXepKqvBl4DvEVEXn/iNj8AXFPVbwD+FvAz9/aI55cgUKRhB7+6a28RfyDJbO7MbG7UGqvtG8Y5QETYbuRceOQHuP/+7+Hznx+SZQ3yXofZV1ts3P8Azns2798CrtJ+4AJzwPX6bHe26TV60H8QgG7/AqC1z5FSVQWG6dM8/Tm5wvrtwE+kj98H/LyISPq7xnNQnuKRghR/kKb2hOiRstaeUWfqfSU1jJrhfYdO5+t49FF49NFH0SLQ+/YXsKXfxEMvezn3veRBxoeBB177EP4/+Pfp/bnv5M8fjsgkg81HobXJ/Q+/hIb/IvcNmmd9d+46IuKB3wO+AfjfVPWjJ27yEPCnAKpaiMg+cBG4euLnvAt4F8Ajjzxyt4+9tjzwktQ6Hn+JeQaXdRPZbrElB8xmbR4MW3whHCFZlwvXPsInXtlnu9nhad3k6y51z/j0hnF3kLN44/XYY4/p448/fs//XcMwQFXZPZpxsXdvhZSI/J6qPnZP/9Hlv70J/Drww6r66ZWvfxp4i6p+JX3+eeDbVPXqqT8Iu36N9sYQhtBQCm0xyVv05ZBy3qQtTablCJE22XzIqOPoKExLT9bs0MqtMmWcT57r+mUVKcN4niEi91xEnTWquiciHwbeAnx65VtfBR4GviIiGbAB7JzBEc8Nnc02pFBXgFijugjpKdVhI33nwuKj2rvxjOc15gA0DKOWiMh2qkQhIm3gzcBnT9zs/cA708fvAH7L/FGGYdwMVpEyDKOuPAj8SvJJOeCfqOoHROSngMdV9f3ALwF/X0Q+B+wC33t2xzUM4zxy20JKRH4Y+M+BEvhnqvqjt30qwzCM20RVPwl88ylff/fKxxPg37uX5zIMo17clpASke8ijg+/WlWnInLfnTmWYRiGYRjG+nO7HqkfAv6Gqk4BVPXy7R/JMAzDMAzjfHC7QuqlwJ9NqxX+tYh86504lGEYhmEYxnnguq09EflN4IFTvvXj6e9fAF4PfCvwT0TkJadNvVignWEYhmEYdeO6QkpVv/vZviciPwT8WhJOvyMiAbgEXDnl57wHeA/EQLtbPrFhGIZhGMaacLutvX8KfBeAiLwUaHBitYJhGIZhGEZdud34g/cC701rFmbAOy3MzjAMwzCM5wtnsmtPRK4AT9zgzS9xvqpcdt67x3k6K9h5T/IiVd2+iz//nnCT1y84X8+D83RWsPPeTc7TWeEMr19nIqRuBhF5/KwWnd4Kdt67x3k6K9h5jch5elzP01nBzns3OU9nhbM9r+3aMwzDMAzDuEVMSBmGYRiGYdwi50FIveesD3CT2HnvHufprGDnNSLn6XE9T2cFO+/d5DydFc7wvGvvkTIMwzAMw1hXzkNFyjAMwzAMYy1ZGyElIm8RkT8Skc+JyH9zyvebIvKr6fsfFZEXn8ExV89zvfN+v4hcEZGPpz//6VmcM53lvSJyOeV9nfZ9EZH/Nd2XT4rIa+/1GVfOcr2zvlFE9lce13ff6zOeOM/DIvJhEfkDEfmMiPzIKbdZi8f3Bs+6Vo/veeI8XcPs+nX3OE/XsPN0/UpnWc9rmKqe+R/AA58HXkJMR/8E8PITt/nPgF9IH38v8Ktrft7vB37+rB/bdJbvBF4LfPpZvv8XgA8CQtyb+NE1PusbgQ+c9WO6cp4Hgdemj/vAH5/yXFiLx/cGz7pWj+95+XOermF2/Trz867N79h5un7dxHnv+eO7LhWp1wGfU9UvqOoM+MfA20/c5u3Ar6SP3wf82yIi9/CMq9zIedcGVf1tYPc5bvJ24O9p5CPApog8eG9Od5wbOOtaoapfU9WPpY8PgT8EHjpxs7V4fG/wrMatcZ6uYXb9uoucp2vYebp+wfpew9ZFSD0E/OnK51/hmQ/O4jaqWgD7wMV7crpnciPnBfiLqRT6PhF5+N4c7Za40fuzLrxBRD4hIh8UkVec9WEqUqvmm4GPnvjW2j2+z3FWWNPHd805T9cwu36dPWv3O3aerl+wXtewdRFSdeT/Bl6sqq8CPsTynahxe3yMGNX/auBvExdnnzki0gP+T+C/UtWDsz7Pc3Gds67l42vcc+z6dfdYu9+x83T9gvW7hq2LkPoqsPqO54Xpa6feRkQyYAPYuSeneybXPa+q7qjqNH36i8C33KOz3Qo38vivBap6oKrD9PE/B3IRuXSWZxKRnPhL/Q9V9ddOucnaPL7XO+s6Pr7nhPN0DbPr1xmybr9j5+n6Bet5DVsXIfW7wDeKyNeJSINoxHz/idu8H3hn+vgdwG9pcpadAdc974ke8tuIvdx15f3Af5SmM14P7Kvq1876UKchIg9UvhIReR3xOXxWgpp0ll8C/lBVf+5ZbrYWj++NnHXdHt9zxHm6htn16wxZp9+x83T9gvW9hmV384ffKKpaiMh/AfwL4kTJe1X1MyLyU8Djqvp+4oP390Xkc0Qj3/eu+Xn/SxF5G1Ck837/WZ1XRP534iTDJRH5CvA/ADmAqv4C8M+JkxmfA0bAf3w2J72hs74D+CERKYAx8L1nKKgB/gzwHwKfEpGPp6/9GPAIrN3jeyNnXbfH91xwnq5hdv26u5yza9h5un7Bml7DLNncMAzDMAzjFlmX1p5hGIZhGMa5w4SUYRiGYRjGLWJCyjAMwzAM4xYxIWUYhmEYhnGLmJAyDMMwDMO4RUxIGYZhGIZh3CImpIxnRUQuisjH05+nROSr6eOhiPydu/Dv/bKIfFFEfnDl83eccruvr85xp89gGEY9sOuXca9Yi0BOYz1R1R3gNQAi8hPAUFX/p7v8z/51VX3fdc71eeA1diEyDOPZsOuXca+wipRx04jIG0XkA+njnxCRXxGR/1dEnhCRf1dE/qaIfEpEfkPiXiRE5FtE5F+LyO+JyL84sYLiufhOEfn/ROQLp727MwzDuBns+mXcaUxIGXeCrwfeRNzJ9Q+AD6vqo8R4/remi9HfBt6hqt8CvBf4H2/wZz8IfAfwPcDfuNMHNwzjeY9dv4zbwlp7xp3gg6o6F5FPEXd3/Ub6+qeAFwMvA14JfCjtkvTAjS69/KeqGoA/EJH77+ipDcMw7Ppl3CYmpIw7wRRAVYOIzFcWRAbic0yAz6jqG271Zyfk9o5pGIbxDOz6ZdwW1toz7gV/BGyLyBsARCQXkVec8ZkMwzBuBLt+Gc+JCSnjrqOqM+AdwM+IyCeAjwPffqaHMgzDuAHs+mVcD1lWMQ3jbBGRXwY+cL3x4ZXbD1W1d3dPZRiGcX3s+vX8xSpSxjqxD/x0FWj3bFSBdsDT9+RUhmEY18euX89TrCJlGIZhGIZxi1hFyjAMwzAM4xYxIWUYhmEYhnGLmJAyDMMwDMO4RUxIGYZhGIZh3CImpAzDMAzDMG6R/x+4EEPluixgKAAAAABJRU5ErkJggg==\n", + "image/png": 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\n", 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\n", + "image/png": 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\n", 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" ] @@ -2322,67 +2169,67 @@ "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:55,885 - [NOTICE] simulation.solve(809): Cycle 1/10 (30.080 ms elapsed) --------------------\n", - "2021-09-17 01:13:55,885 - [NOTICE] simulation.solve(843): Cycle 1/10, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:55,941 - [NOTICE] simulation.solve(843): Cycle 1/10, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:55,992 - [NOTICE] simulation.solve(843): Cycle 1/10, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:56,032 - [NOTICE] simulation.solve(843): Cycle 1/10, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:56,255 - [NOTICE] simulation.solve(921): Capacity is now 4.943 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:56,255 - [NOTICE] simulation.solve(809): Cycle 2/10 (395.311 ms elapsed) --------------------\n", - "2021-09-17 01:13:56,255 - [NOTICE] simulation.solve(843): Cycle 2/10, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:56,291 - [NOTICE] simulation.solve(843): Cycle 2/10, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:56,317 - [NOTICE] simulation.solve(843): Cycle 2/10, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:56,342 - [NOTICE] simulation.solve(843): Cycle 2/10, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:56,366 - [NOTICE] simulation.solve(921): Capacity is now 4.917 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:56,366 - [NOTICE] simulation.solve(809): Cycle 3/10 (513.989 ms elapsed) --------------------\n", - "2021-09-17 01:13:56,366 - [NOTICE] simulation.solve(843): Cycle 3/10, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:56,398 - [NOTICE] simulation.solve(843): Cycle 3/10, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:56,427 - [NOTICE] simulation.solve(843): Cycle 3/10, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:56,443 - [NOTICE] simulation.solve(843): Cycle 3/10, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:56,496 - [NOTICE] simulation.solve(921): Capacity is now 4.891 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:56,497 - [NOTICE] simulation.solve(809): Cycle 4/10 (633.851 ms elapsed) --------------------\n", - "2021-09-17 01:13:56,498 - [NOTICE] simulation.solve(843): Cycle 4/10, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:56,529 - [NOTICE] simulation.solve(843): Cycle 4/10, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:56,548 - [NOTICE] simulation.solve(843): Cycle 4/10, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:56,584 - [NOTICE] simulation.solve(843): Cycle 4/10, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:56,608 - [NOTICE] simulation.solve(921): Capacity is now 4.867 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:56,608 - [NOTICE] simulation.solve(809): Cycle 5/10 (757.820 ms elapsed) --------------------\n", - "2021-09-17 01:13:56,608 - [NOTICE] simulation.solve(843): Cycle 5/10, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:56,647 - [NOTICE] simulation.solve(843): Cycle 5/10, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:56,675 - [NOTICE] simulation.solve(843): Cycle 5/10, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:56,698 - [NOTICE] simulation.solve(843): Cycle 5/10, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:56,742 - [NOTICE] simulation.solve(921): Capacity is now 4.842 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:56,743 - [NOTICE] simulation.solve(809): Cycle 6/10 (879.405 ms elapsed) --------------------\n", - "2021-09-17 01:13:56,744 - [NOTICE] simulation.solve(843): Cycle 6/10, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:56,771 - [NOTICE] simulation.solve(843): Cycle 6/10, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:56,799 - [NOTICE] simulation.solve(843): Cycle 6/10, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:56,828 - [NOTICE] simulation.solve(843): Cycle 6/10, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:56,867 - [NOTICE] simulation.solve(921): Capacity is now 4.818 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:56,868 - [NOTICE] simulation.solve(809): Cycle 7/10 (1.004 s elapsed) --------------------\n", - "2021-09-17 01:13:56,869 - [NOTICE] simulation.solve(843): Cycle 7/10, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:56,890 - [NOTICE] simulation.solve(843): Cycle 7/10, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:56,918 - [NOTICE] simulation.solve(843): Cycle 7/10, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:56,947 - [NOTICE] simulation.solve(843): Cycle 7/10, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:56,966 - [NOTICE] simulation.solve(921): Capacity is now 4.794 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:56,982 - [NOTICE] simulation.solve(809): Cycle 8/10 (1.119 s elapsed) --------------------\n", - "2021-09-17 01:13:56,982 - [NOTICE] simulation.solve(843): Cycle 8/10, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:57,009 - [NOTICE] simulation.solve(843): Cycle 8/10, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:57,037 - [NOTICE] simulation.solve(843): Cycle 8/10, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:57,066 - [NOTICE] simulation.solve(843): Cycle 8/10, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:57,109 - [NOTICE] simulation.solve(921): Capacity is now 4.771 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:57,109 - [NOTICE] simulation.solve(809): Cycle 9/10 (1.248 s elapsed) --------------------\n", - "2021-09-17 01:13:57,109 - [NOTICE] simulation.solve(843): Cycle 9/10, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:57,125 - [NOTICE] simulation.solve(843): Cycle 9/10, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:57,163 - [NOTICE] simulation.solve(843): Cycle 9/10, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:57,189 - [NOTICE] simulation.solve(843): Cycle 9/10, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:57,225 - [NOTICE] simulation.solve(921): Capacity is now 4.748 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:57,225 - [NOTICE] simulation.solve(809): Cycle 10/10 (1.363 s elapsed) --------------------\n", - "2021-09-17 01:13:57,225 - [NOTICE] simulation.solve(843): Cycle 10/10, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:57,256 - [NOTICE] simulation.solve(843): Cycle 10/10, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:57,280 - [NOTICE] simulation.solve(843): Cycle 10/10, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:57,302 - [NOTICE] simulation.solve(843): Cycle 10/10, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:57,341 - [NOTICE] simulation.solve(921): Capacity is now 4.725 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:57,341 - [NOTICE] simulation.solve(938): Finish experiment simulation, took 1.483 s\n" + "2021-11-19 15:29:04,352 - [NOTICE] simulation.solve(850): Cycle 1/10 (24.739 ms elapsed) --------------------\n", + "2021-11-19 15:29:04,352 - [NOTICE] simulation.solve(884): Cycle 1/10, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:04,391 - [NOTICE] simulation.solve(884): Cycle 1/10, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:04,424 - [NOTICE] simulation.solve(884): Cycle 1/10, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:04,463 - [NOTICE] simulation.solve(884): Cycle 1/10, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:04,633 - [NOTICE] simulation.solve(972): Capacity is now 4.940 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:04,634 - [NOTICE] simulation.solve(850): Cycle 2/10 (306.843 ms elapsed) --------------------\n", + "2021-11-19 15:29:04,634 - [NOTICE] simulation.solve(884): Cycle 2/10, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:04,657 - [NOTICE] simulation.solve(884): Cycle 2/10, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:04,675 - [NOTICE] simulation.solve(884): Cycle 2/10, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:04,697 - [NOTICE] simulation.solve(884): Cycle 2/10, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:04,726 - [NOTICE] simulation.solve(972): Capacity is now 4.913 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:04,726 - [NOTICE] simulation.solve(850): Cycle 3/10 (399.654 ms elapsed) --------------------\n", + "2021-11-19 15:29:04,727 - [NOTICE] simulation.solve(884): Cycle 3/10, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:04,750 - [NOTICE] simulation.solve(884): Cycle 3/10, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:04,768 - [NOTICE] simulation.solve(884): Cycle 3/10, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:04,790 - [NOTICE] simulation.solve(884): Cycle 3/10, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:04,819 - [NOTICE] simulation.solve(972): Capacity is now 4.885 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:04,820 - [NOTICE] simulation.solve(850): Cycle 4/10 (492.890 ms elapsed) --------------------\n", + "2021-11-19 15:29:04,820 - [NOTICE] simulation.solve(884): Cycle 4/10, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:04,843 - [NOTICE] simulation.solve(884): Cycle 4/10, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:04,861 - [NOTICE] simulation.solve(884): Cycle 4/10, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:04,884 - [NOTICE] simulation.solve(884): Cycle 4/10, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:04,913 - [NOTICE] simulation.solve(972): Capacity is now 4.858 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:04,913 - [NOTICE] simulation.solve(850): Cycle 5/10 (586.235 ms elapsed) --------------------\n", + "2021-11-19 15:29:04,913 - [NOTICE] simulation.solve(884): Cycle 5/10, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:04,937 - [NOTICE] simulation.solve(884): Cycle 5/10, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:04,955 - [NOTICE] simulation.solve(884): Cycle 5/10, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:04,977 - [NOTICE] simulation.solve(884): Cycle 5/10, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:05,006 - [NOTICE] simulation.solve(972): Capacity is now 4.832 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:05,007 - [NOTICE] simulation.solve(850): Cycle 6/10 (680.000 ms elapsed) --------------------\n", + "2021-11-19 15:29:05,007 - [NOTICE] simulation.solve(884): Cycle 6/10, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:05,028 - [NOTICE] simulation.solve(884): Cycle 6/10, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:05,045 - [NOTICE] simulation.solve(884): Cycle 6/10, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:05,065 - [NOTICE] simulation.solve(884): Cycle 6/10, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:05,097 - [NOTICE] simulation.solve(972): Capacity is now 4.806 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:05,097 - [NOTICE] simulation.solve(850): Cycle 7/10 (770.698 ms elapsed) --------------------\n", + "2021-11-19 15:29:05,098 - [NOTICE] simulation.solve(884): Cycle 7/10, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:05,121 - [NOTICE] simulation.solve(884): Cycle 7/10, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:05,141 - [NOTICE] simulation.solve(884): Cycle 7/10, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:05,162 - [NOTICE] simulation.solve(884): Cycle 7/10, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:05,197 - [NOTICE] simulation.solve(972): Capacity is now 4.780 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:05,198 - [NOTICE] simulation.solve(850): Cycle 8/10 (871.036 ms elapsed) --------------------\n", + "2021-11-19 15:29:05,198 - [NOTICE] simulation.solve(884): Cycle 8/10, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:05,221 - [NOTICE] simulation.solve(884): Cycle 8/10, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:05,241 - [NOTICE] simulation.solve(884): Cycle 8/10, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:05,263 - [NOTICE] simulation.solve(884): Cycle 8/10, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:05,298 - [NOTICE] simulation.solve(972): Capacity is now 4.755 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:05,299 - [NOTICE] simulation.solve(850): Cycle 9/10 (971.933 ms elapsed) --------------------\n", + "2021-11-19 15:29:05,299 - [NOTICE] simulation.solve(884): Cycle 9/10, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:05,323 - [NOTICE] simulation.solve(884): Cycle 9/10, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:05,342 - [NOTICE] simulation.solve(884): Cycle 9/10, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:05,365 - [NOTICE] simulation.solve(884): Cycle 9/10, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:05,397 - [NOTICE] simulation.solve(972): Capacity is now 4.731 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:05,397 - [NOTICE] simulation.solve(850): Cycle 10/10 (1.070 s elapsed) --------------------\n", + "2021-11-19 15:29:05,397 - [NOTICE] simulation.solve(884): Cycle 10/10, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:05,420 - [NOTICE] simulation.solve(884): Cycle 10/10, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:05,438 - [NOTICE] simulation.solve(884): Cycle 10/10, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:05,460 - [NOTICE] simulation.solve(884): Cycle 10/10, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:05,492 - [NOTICE] simulation.solve(972): Capacity is now 4.706 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:05,493 - [NOTICE] simulation.solve(990): Finish experiment simulation, took 1.166 s\n" ] } ], @@ -2417,67 +2264,67 @@ "name": "stderr", "output_type": "stream", "text": [ - "2021-09-17 01:13:57,398 - [NOTICE] simulation.solve(809): Cycle 11/20 (38.041 ms elapsed) --------------------\n", - "2021-09-17 01:13:57,399 - [NOTICE] simulation.solve(843): Cycle 11/20, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:57,426 - [NOTICE] simulation.solve(843): Cycle 11/20, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:57,450 - [NOTICE] simulation.solve(843): Cycle 11/20, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:57,483 - [NOTICE] simulation.solve(843): Cycle 11/20, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:57,626 - [NOTICE] simulation.solve(921): Capacity is now 4.703 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:57,626 - [NOTICE] simulation.solve(809): Cycle 12/20 (278.438 ms elapsed) --------------------\n", - "2021-09-17 01:13:57,626 - [NOTICE] simulation.solve(843): Cycle 12/20, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:57,662 - [NOTICE] simulation.solve(843): Cycle 12/20, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:57,693 - [NOTICE] simulation.solve(843): Cycle 12/20, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:57,710 - [NOTICE] simulation.solve(843): Cycle 12/20, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:57,755 - [NOTICE] simulation.solve(921): Capacity is now 4.681 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:57,756 - [NOTICE] simulation.solve(809): Cycle 13/20 (395.994 ms elapsed) --------------------\n", - "2021-09-17 01:13:57,757 - [NOTICE] simulation.solve(843): Cycle 13/20, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:57,782 - [NOTICE] simulation.solve(843): Cycle 13/20, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:57,810 - [NOTICE] simulation.solve(843): Cycle 13/20, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:57,826 - [NOTICE] simulation.solve(843): Cycle 13/20, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:57,860 - [NOTICE] simulation.solve(921): Capacity is now 4.660 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:57,860 - [NOTICE] simulation.solve(809): Cycle 14/20 (513.670 ms elapsed) --------------------\n", - "2021-09-17 01:13:57,860 - [NOTICE] simulation.solve(843): Cycle 14/20, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:57,899 - [NOTICE] simulation.solve(843): Cycle 14/20, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:57,911 - [NOTICE] simulation.solve(843): Cycle 14/20, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:57,943 - [NOTICE] simulation.solve(843): Cycle 14/20, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:57,973 - [NOTICE] simulation.solve(921): Capacity is now 4.638 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:57,988 - [NOTICE] simulation.solve(809): Cycle 15/20 (628.549 ms elapsed) --------------------\n", - "2021-09-17 01:13:57,988 - [NOTICE] simulation.solve(843): Cycle 15/20, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:58,011 - [NOTICE] simulation.solve(843): Cycle 15/20, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:58,025 - [NOTICE] simulation.solve(843): Cycle 15/20, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:58,062 - [NOTICE] simulation.solve(843): Cycle 15/20, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:58,088 - [NOTICE] simulation.solve(921): Capacity is now 4.617 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:58,088 - [NOTICE] simulation.solve(809): Cycle 16/20 (743.130 ms elapsed) --------------------\n", - "2021-09-17 01:13:58,104 - [NOTICE] simulation.solve(843): Cycle 16/20, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:58,127 - [NOTICE] simulation.solve(843): Cycle 16/20, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:58,158 - [NOTICE] simulation.solve(843): Cycle 16/20, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:58,183 - [NOTICE] simulation.solve(843): Cycle 16/20, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:58,216 - [NOTICE] simulation.solve(921): Capacity is now 4.597 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:58,216 - [NOTICE] simulation.solve(809): Cycle 17/20 (861.188 ms elapsed) --------------------\n", - "2021-09-17 01:13:58,216 - [NOTICE] simulation.solve(843): Cycle 17/20, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:58,249 - [NOTICE] simulation.solve(843): Cycle 17/20, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:58,272 - [NOTICE] simulation.solve(843): Cycle 17/20, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:58,299 - [NOTICE] simulation.solve(843): Cycle 17/20, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:58,333 - [NOTICE] simulation.solve(921): Capacity is now 4.576 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:58,333 - [NOTICE] simulation.solve(809): Cycle 18/20 (976.535 ms elapsed) --------------------\n", - "2021-09-17 01:13:58,333 - [NOTICE] simulation.solve(843): Cycle 18/20, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:58,365 - [NOTICE] simulation.solve(843): Cycle 18/20, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:58,391 - [NOTICE] simulation.solve(843): Cycle 18/20, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:58,412 - [NOTICE] simulation.solve(843): Cycle 18/20, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:58,441 - [NOTICE] simulation.solve(921): Capacity is now 4.556 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:58,441 - [NOTICE] simulation.solve(809): Cycle 19/20 (1.094 s elapsed) --------------------\n", - "2021-09-17 01:13:58,441 - [NOTICE] simulation.solve(843): Cycle 19/20, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:58,487 - [NOTICE] simulation.solve(843): Cycle 19/20, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:58,499 - [NOTICE] simulation.solve(843): Cycle 19/20, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:58,538 - [NOTICE] simulation.solve(843): Cycle 19/20, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:58,575 - [NOTICE] simulation.solve(921): Capacity is now 4.536 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:58,575 - [NOTICE] simulation.solve(809): Cycle 20/20 (1.216 s elapsed) --------------------\n", - "2021-09-17 01:13:58,576 - [NOTICE] simulation.solve(843): Cycle 20/20, step 1/4: Discharge at 1C until 3.0V\n", - "2021-09-17 01:13:58,608 - [NOTICE] simulation.solve(843): Cycle 20/20, step 2/4: Rest for 1 hour\n", - "2021-09-17 01:13:58,634 - [NOTICE] simulation.solve(843): Cycle 20/20, step 3/4: Charge at 1C until 4.2V\n", - "2021-09-17 01:13:58,661 - [NOTICE] simulation.solve(843): Cycle 20/20, step 4/4: Hold at 4.2V until C/50\n", - "2021-09-17 01:13:58,691 - [NOTICE] simulation.solve(921): Capacity is now 4.516 Ah (originally 4.943 Ah, will stop at 3.954 Ah)\n", - "2021-09-17 01:13:58,691 - [NOTICE] simulation.solve(938): Finish experiment simulation, took 1.338 s\n" + "2021-11-19 15:29:05,527 - [NOTICE] simulation.solve(850): Cycle 11/20 (26.183 ms elapsed) --------------------\n", + "2021-11-19 15:29:05,528 - [NOTICE] simulation.solve(884): Cycle 11/20, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:05,553 - [NOTICE] simulation.solve(884): Cycle 11/20, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:05,571 - [NOTICE] simulation.solve(884): Cycle 11/20, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:05,595 - [NOTICE] simulation.solve(884): Cycle 11/20, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:05,939 - [NOTICE] simulation.solve(972): Capacity is now 4.682 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:05,939 - [NOTICE] simulation.solve(850): Cycle 12/20 (438.580 ms elapsed) --------------------\n", + "2021-11-19 15:29:05,940 - [NOTICE] simulation.solve(884): Cycle 12/20, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:05,963 - [NOTICE] simulation.solve(884): Cycle 12/20, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:05,980 - [NOTICE] simulation.solve(884): Cycle 12/20, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:05,999 - [NOTICE] simulation.solve(884): Cycle 12/20, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:06,032 - [NOTICE] simulation.solve(972): Capacity is now 4.659 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:06,032 - [NOTICE] simulation.solve(850): Cycle 13/20 (531.729 ms elapsed) --------------------\n", + "2021-11-19 15:29:06,033 - [NOTICE] simulation.solve(884): Cycle 13/20, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:06,053 - [NOTICE] simulation.solve(884): Cycle 13/20, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:06,070 - [NOTICE] simulation.solve(884): Cycle 13/20, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:06,089 - [NOTICE] simulation.solve(884): Cycle 13/20, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:06,121 - [NOTICE] simulation.solve(972): Capacity is now 4.636 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:06,121 - [NOTICE] simulation.solve(850): Cycle 14/20 (620.402 ms elapsed) --------------------\n", + "2021-11-19 15:29:06,121 - [NOTICE] simulation.solve(884): Cycle 14/20, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:06,142 - [NOTICE] simulation.solve(884): Cycle 14/20, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:06,160 - [NOTICE] simulation.solve(884): Cycle 14/20, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:06,178 - [NOTICE] simulation.solve(884): Cycle 14/20, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:06,210 - [NOTICE] simulation.solve(972): Capacity is now 4.613 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:06,211 - [NOTICE] simulation.solve(850): Cycle 15/20 (709.857 ms elapsed) --------------------\n", + "2021-11-19 15:29:06,211 - [NOTICE] simulation.solve(884): Cycle 15/20, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:06,232 - [NOTICE] simulation.solve(884): Cycle 15/20, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:06,249 - [NOTICE] simulation.solve(884): Cycle 15/20, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:06,269 - [NOTICE] simulation.solve(884): Cycle 15/20, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:06,301 - [NOTICE] simulation.solve(972): Capacity is now 4.590 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:06,302 - [NOTICE] simulation.solve(850): Cycle 16/20 (800.949 ms elapsed) --------------------\n", + "2021-11-19 15:29:06,302 - [NOTICE] simulation.solve(884): Cycle 16/20, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:06,324 - [NOTICE] simulation.solve(884): Cycle 16/20, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:06,342 - [NOTICE] simulation.solve(884): Cycle 16/20, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:06,362 - [NOTICE] simulation.solve(884): Cycle 16/20, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:06,394 - [NOTICE] simulation.solve(972): Capacity is now 4.568 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:06,395 - [NOTICE] simulation.solve(850): Cycle 17/20 (894.163 ms elapsed) --------------------\n", + "2021-11-19 15:29:06,395 - [NOTICE] simulation.solve(884): Cycle 17/20, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:06,418 - [NOTICE] simulation.solve(884): Cycle 17/20, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:06,436 - [NOTICE] simulation.solve(884): Cycle 17/20, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:06,457 - [NOTICE] simulation.solve(884): Cycle 17/20, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:06,489 - [NOTICE] simulation.solve(972): Capacity is now 4.546 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:06,490 - [NOTICE] simulation.solve(850): Cycle 18/20 (988.985 ms elapsed) --------------------\n", + "2021-11-19 15:29:06,490 - [NOTICE] simulation.solve(884): Cycle 18/20, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:06,512 - [NOTICE] simulation.solve(884): Cycle 18/20, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:06,530 - [NOTICE] simulation.solve(884): Cycle 18/20, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:06,552 - [NOTICE] simulation.solve(884): Cycle 18/20, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:06,584 - [NOTICE] simulation.solve(972): Capacity is now 4.524 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:06,585 - [NOTICE] simulation.solve(850): Cycle 19/20 (1.084 s elapsed) --------------------\n", + "2021-11-19 15:29:06,585 - [NOTICE] simulation.solve(884): Cycle 19/20, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:06,608 - [NOTICE] simulation.solve(884): Cycle 19/20, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:06,626 - [NOTICE] simulation.solve(884): Cycle 19/20, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:06,644 - [NOTICE] simulation.solve(884): Cycle 19/20, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:06,676 - [NOTICE] simulation.solve(972): Capacity is now 4.503 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:06,676 - [NOTICE] simulation.solve(850): Cycle 20/20 (1.176 s elapsed) --------------------\n", + "2021-11-19 15:29:06,677 - [NOTICE] simulation.solve(884): Cycle 20/20, step 1/4: Discharge at 1C until 3.0V\n", + "2021-11-19 15:29:06,697 - [NOTICE] simulation.solve(884): Cycle 20/20, step 2/4: Rest for 1 hour\n", + "2021-11-19 15:29:06,715 - [NOTICE] simulation.solve(884): Cycle 20/20, step 3/4: Charge at 1C until 4.2V\n", + "2021-11-19 15:29:06,735 - [NOTICE] simulation.solve(884): Cycle 20/20, step 4/4: Hold at 4.2V until C/50\n", + "2021-11-19 15:29:06,773 - [NOTICE] simulation.solve(972): Capacity is now 4.482 Ah (originally 4.940 Ah, will stop at 3.952 Ah)\n", + "2021-11-19 15:29:06,774 - [NOTICE] simulation.solve(990): Finish experiment simulation, took 1.273 s\n" ] } ], @@ -2558,7 +2405,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -2572,7 +2419,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.0" + "version": "3.8.12" }, "toc": { "base_numbering": 1, @@ -2590,4 +2437,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/examples/notebooks/spatial_methods/finite-volumes.ipynb b/examples/notebooks/spatial_methods/finite-volumes.ipynb index 3558253ba1..499faad44e 100644 --- a/examples/notebooks/spatial_methods/finite-volumes.ipynb +++ b/examples/notebooks/spatial_methods/finite-volumes.ipynb @@ -119,7 +119,7 @@ "}\n", "\n", "var = pybamm.standard_spatial_vars\n", - "var_pts = {"x_n": 15, "x_s": 10, "x_p": 15, "r_n": 10, "r_p": 10}\n", + "var_pts = {var.x_n: 15, var.x_s: 10, var.x_p: 15, var.r_n: 10, var.r_p: 10}\n", "mesh = pybamm.Mesh(geometry, submesh_types, var_pts)" ] }, @@ -1292,7 +1292,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1306,7 +1306,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.6" + "version": "3.8.12" }, "toc": { "base_numbering": 1, From 4f36fa3406487d482e53ab8639ef8f0ac275fcbd Mon Sep 17 00:00:00 2001 From: Valentin Sulzer Date: Wed, 24 Nov 2021 15:40:06 -0500 Subject: [PATCH 5/8] #1810 coverage --- pybamm/parameters/parameter_values.py | 3 +++ .../test_effective_current_collector.py | 10 ++++++++++ tests/unit/test_parameters/test_parameter_values.py | 5 +++++ 3 files changed, 18 insertions(+) diff --git a/pybamm/parameters/parameter_values.py b/pybamm/parameters/parameter_values.py index 76476967a4..f4279d9f63 100644 --- a/pybamm/parameters/parameter_values.py +++ b/pybamm/parameters/parameter_values.py @@ -120,6 +120,9 @@ def __delitem__(self, key): def __repr__(self): return pformat(self._dict_items, width=1) + def __eq__(self, other): + return self._dict_items == other._dict_items + def keys(self): """Get the keys of the dictionary""" return self._dict_items.keys() diff --git a/tests/unit/test_models/test_submodels/test_current_collector/test_effective_current_collector.py b/tests/unit/test_models/test_submodels/test_current_collector/test_effective_current_collector.py index 90460719fb..6397c0d6d9 100644 --- a/tests/unit/test_models/test_submodels/test_current_collector/test_effective_current_collector.py +++ b/tests/unit/test_models/test_submodels/test_current_collector/test_effective_current_collector.py @@ -14,6 +14,12 @@ def test_well_posed(self): model = pybamm.current_collector.EffectiveResistance({"dimensionality": 2}) model.check_well_posedness() + def test_default_parameters(self): + model = pybamm.current_collector.EffectiveResistance({"dimensionality": 1}) + self.assertEqual( + model.default_parameter_values, pybamm.ParameterValues("Marquis2019") + ) + def test_default_geometry(self): model = pybamm.current_collector.EffectiveResistance({"dimensionality": 1}) self.assertTrue("current collector" in model.default_geometry) @@ -23,6 +29,10 @@ def test_default_geometry(self): self.assertTrue("current collector" in model.default_geometry) self.assertNotIn("negative electrode", model.default_geometry) + def test_default_var_pts(self): + model = pybamm.current_collector.EffectiveResistance({"dimensionality": 1}) + self.assertEqual(model.default_var_pts, {"y": 32, "z": 32}) + def test_default_solver(self): model = pybamm.current_collector.EffectiveResistance({"dimensionality": 1}) self.assertIsInstance(model.default_solver, pybamm.CasadiAlgebraicSolver) diff --git a/tests/unit/test_parameters/test_parameter_values.py b/tests/unit/test_parameters/test_parameter_values.py index 7e22b8aaa8..23d60e4bb2 100644 --- a/tests/unit/test_parameters/test_parameter_values.py +++ b/tests/unit/test_parameters/test_parameter_values.py @@ -75,6 +75,11 @@ def test_repr(self): self.assertEqual(repr(param), "{'a': 1}") self.assertEqual(param._ipython_key_completions_(), ["a"]) + def test_eq(self): + self.assertEqual( + pybamm.ParameterValues({"a": 1}), pybamm.ParameterValues({"a": 1}) + ) + def test_update_from_chemistry(self): # incomplete chemistry with self.assertRaisesRegex(KeyError, "must provide 'cell' parameters"): From 3fd8fc87f242c70ef1f9984c2bf91a8bb71e8979 Mon Sep 17 00:00:00 2001 From: Valentin Sulzer Date: Wed, 24 Nov 2021 16:00:20 -0500 Subject: [PATCH 6/8] #1810 coverage --- .../effective_resistance_current_collector.py | 228 +++++++----------- 1 file changed, 91 insertions(+), 137 deletions(-) diff --git a/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py b/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py index 0f61502c66..6de02c5388 100644 --- a/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py +++ b/pybamm/models/submodels/current_collector/effective_resistance_current_collector.py @@ -4,7 +4,93 @@ import pybamm -class EffectiveResistance(pybamm.BaseModel): +class BaseEffectiveResistance(pybamm.BaseModel): + @property + def default_parameter_values(self): + return pybamm.ParameterValues("Marquis2019") + + @property + def default_geometry(self): + geometry = {} + param = self.param + if self.options["dimensionality"] == 1: + geometry["current collector"] = { + "z": {"min": 0, "max": 1}, + "tabs": { + "negative": {"z_centre": param.centre_z_tab_n}, + "positive": {"z_centre": param.centre_z_tab_p}, + }, + } + elif self.options["dimensionality"] == 2: + geometry["current collector"] = { + "y": {"min": 0, "max": param.l_y}, + "z": {"min": 0, "max": param.l_z}, + "tabs": { + "negative": { + "y_centre": param.centre_y_tab_n, + "z_centre": param.centre_z_tab_n, + "width": param.l_tab_n, + }, + "positive": { + "y_centre": param.centre_y_tab_p, + "z_centre": param.centre_z_tab_p, + "width": param.l_tab_p, + }, + }, + } + return pybamm.Geometry(geometry) + + @property + def default_var_pts(self): + return {"y": 32, "z": 32} + + @property + def default_submesh_types(self): + if self.options["dimensionality"] == 1: + return {"current collector": pybamm.Uniform1DSubMesh} + elif self.options["dimensionality"] == 2: + return { + "current collector": pybamm.MeshGenerator(pybamm.ScikitUniform2DSubMesh) + } + + @property + def default_spatial_methods(self): + if self.options["dimensionality"] == 1: + return {"current collector": pybamm.FiniteVolume()} + elif self.options["dimensionality"] == 2: + return {"current collector": pybamm.ScikitFiniteElement()} + + @property + def options(self): + return self._options + + @options.setter + def options(self, extra_options): + default_options = {"dimensionality": 1} + extra_options = extra_options or {} + + options = pybamm.FuzzyDict(default_options) + # any extra options overwrite the default options + for name, opt in extra_options.items(): + if name in default_options: + options[name] = opt + else: + raise pybamm.OptionError( + "Option '{}' not recognised. Best matches are {}".format( + name, options.get_best_matches(name) + ) + ) + + if options["dimensionality"] not in [1, 2]: + raise pybamm.OptionError( + "Dimension of current collectors must be 1 or 2, not {}".format( + options["dimensionality"] + ) + ) + self._options = options + + +class EffectiveResistance(BaseEffectiveResistance): """ A model which calculates the effective Ohmic resistance of the current collectors in the limit of large electrical conductivity. For details see [1]_. @@ -30,7 +116,7 @@ class EffectiveResistance(pybamm.BaseModel): .. [1] R Timms, SG Marquis, V Sulzer, CP Please and SJ Chapman. “Asymptotic Reduction of a Lithium-ion Pouch Cell Model”. Submitted, 2020. - **Extends:** :class:`pybamm.BaseModel` + **Extends:** :class:`BaseEffectiveResistance` """ def __init__( @@ -210,107 +296,20 @@ def V_cc_dim(t, z, y=None): } return processed_vars - @property - def default_parameter_values(self): - return pybamm.ParameterValues("Marquis2019") - @property - def default_geometry(self): - geometry = {} - param = self.param - if self.options["dimensionality"] == 1: - geometry["current collector"] = { - "z": {"min": 0, "max": 1}, - "tabs": { - "negative": {"z_centre": param.centre_z_tab_n}, - "positive": {"z_centre": param.centre_z_tab_p}, - }, - } - elif self.options["dimensionality"] == 2: - geometry["current collector"] = { - "y": {"min": 0, "max": param.l_y}, - "z": {"min": 0, "max": param.l_z}, - "tabs": { - "negative": { - "y_centre": param.centre_y_tab_n, - "z_centre": param.centre_z_tab_n, - "width": param.l_tab_n, - }, - "positive": { - "y_centre": param.centre_y_tab_p, - "z_centre": param.centre_z_tab_p, - "width": param.l_tab_p, - }, - }, - } - return pybamm.Geometry(geometry) - - @property - def default_var_pts(self): - return {"y": 32, "z": 32} - - @property - def default_submesh_types(self): - if self.options["dimensionality"] == 1: - return {"current collector": pybamm.Uniform1DSubMesh} - elif self.options["dimensionality"] == 2: - return { - "current collector": pybamm.MeshGenerator(pybamm.ScikitUniform2DSubMesh) - } - - @property - def default_spatial_methods(self): - if self.options["dimensionality"] == 1: - return {"current collector": pybamm.FiniteVolume()} - elif self.options["dimensionality"] == 2: - return {"current collector": pybamm.ScikitFiniteElement()} - - @property - def default_solver(self): - return pybamm.CasadiAlgebraicSolver() - - @property - def options(self): - return self._options - - @options.setter - def options(self, extra_options): - default_options = {"dimensionality": 1} - extra_options = extra_options or {} - - options = pybamm.FuzzyDict(default_options) - # any extra options overwrite the default options - for name, opt in extra_options.items(): - if name in default_options: - options[name] = opt - else: - raise pybamm.OptionError( - "Option '{}' not recognised. Best matches are {}".format( - name, options.get_best_matches(name) - ) - ) - - if options["dimensionality"] not in [1, 2]: - raise pybamm.OptionError( - "Dimension of current collectors must be 1 or 2, not {}".format( - options["dimensionality"] - ) - ) - self._options = options - - -class AlternativeEffectiveResistance2D(pybamm.BaseModel): +class AlternativeEffectiveResistance2D(BaseEffectiveResistance): """ A model which calculates the effective Ohmic resistance of the 2D current collectors in the limit of large electrical conductivity. This model assumes a uniform *current density* at the tabs and the solution is computed by first solving and auxilliary problem which is the related to the resistances. - **Extends:** :class:`pybamm.BaseModel` + **Extends:** :class:`BaseEffectiveResistance` """ def __init__(self): super().__init__() + self.options = {"dimensionality": 2} self.name = "Effective resistance in current collector model (2D)" self.param = pybamm.LithiumIonParameters() @@ -463,48 +462,3 @@ def V_cc_dim(t, y, z): "Terminal voltage [V]": V_dim, } return processed_vars - - @property - def default_parameter_values(self): - return pybamm.ParameterValues("Marquis2019") - - @property - def default_geometry(self): - param = self.param - geometry = { - "current collector": { - "y": {"min": 0, "max": param.l_y}, - "z": {"min": 0, "max": param.l_z}, - "tabs": { - "negative": { - "y_centre": param.centre_y_tab_n, - "z_centre": param.centre_z_tab_n, - "width": param.l_tab_n, - }, - "positive": { - "y_centre": param.centre_y_tab_p, - "z_centre": param.centre_z_tab_p, - "width": param.l_tab_p, - }, - }, - } - } - return pybamm.Geometry(geometry) - - @property - def default_var_pts(self): - return {"y": 32, "z": 32} - - @property - def default_submesh_types(self): - return { - "current collector": pybamm.MeshGenerator(pybamm.ScikitUniform2DSubMesh) - } - - @property - def default_spatial_methods(self): - return {"current collector": pybamm.ScikitFiniteElement()} - - @property - def default_solver(self): - return pybamm.CasadiAlgebraicSolver() From a894c890ab13a14af09b0aabef6c76652526418e Mon Sep 17 00:00:00 2001 From: Valentin Sulzer Date: Thu, 25 Nov 2021 12:17:28 -0500 Subject: [PATCH 7/8] #1810 update tests and examples previously missed --- .../Tutorial 9 - Changing the mesh.ipynb | 3 +-- examples/notebooks/batch_study.ipynb | 3 +-- .../DFN-with-particle-size-distributions.ipynb | 8 ++++---- .../scripts/compare_lithium_ion_half_cell.py | 17 ++++------------- tests/integration/test_experiments.py | 4 +--- .../test_lead_acid/test_compare_basic_models.py | 4 +--- .../test_lithium_ion/base_lithium_ion_tests.py | 8 ++------ .../test_basic_half_cell_models.py | 6 ++---- .../test_lithium_ion/test_thermal_models.py | 3 +-- .../test_simulation_with_experiment.py | 4 +--- .../test_lithium_ion/test_electrode_soh.py | 12 +++--------- .../test_lead_acid_parameters.py | 8 ++------ .../test_parameter_sets/test_LFP_Prada2013.py | 3 +-- .../test_parameter_sets/test_LGM50_Chen2020.py | 3 +-- .../test_LGM50_ORegan2021.py | 3 +-- .../test_parameter_sets/test_NCA_Kim2011.py | 3 +-- .../test_parameter_sets/test_NCO_Ecker2015.py | 3 +-- .../test_NMChalfcell_Xu2019.py | 3 +-- .../test_parameter_sets/test_UMBL_Mohtat2020.py | 3 +-- .../test_plot_summary_variables.py | 4 +--- 20 files changed, 31 insertions(+), 74 deletions(-) diff --git a/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb b/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb index a35c147988..27d1d6c720 100644 --- a/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb +++ b/examples/notebooks/Getting Started/Tutorial 9 - Changing the mesh.ipynb @@ -209,8 +209,7 @@ "source": [ "# choose model and parameters\n", "model = pybamm.lithium_ion.DFN()\n", - "chemistry = pybamm.parameter_sets.Ecker2015\n", - "parameter_values = pybamm.ParameterValues(chemistry=chemistry)\n", + "parameter_values = pybamm.ParameterValues(\"Ecker2015\")\n", "\n", "# choose solver \n", "solver = pybamm.CasadiSolver(mode=\"fast\")\n", diff --git a/examples/notebooks/batch_study.ipynb b/examples/notebooks/batch_study.ipynb index 0d09f1a72f..0eeea03b40 100644 --- a/examples/notebooks/batch_study.ipynb +++ b/examples/notebooks/batch_study.ipynb @@ -501,7 +501,6 @@ "}\n", "\n", "# populating a dictionary with 3 same parameter values (Mohtat2020 chemistry)\n", - "mohtat2020 = pybamm.parameter_sets.Mohtat2020\n", "parameter_values = {\n", " \"Mohtat2020_1\": pybamm.ParameterValues(\"Mohtat2020\"),\n", " \"Mohtat2020_2\": pybamm.ParameterValues(\"Mohtat2020\"),\n", @@ -548,7 +547,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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", 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" ] diff --git a/examples/notebooks/models/DFN-with-particle-size-distributions.ipynb b/examples/notebooks/models/DFN-with-particle-size-distributions.ipynb index c37a02a640..d2c8a39024 100644 --- a/examples/notebooks/models/DFN-with-particle-size-distributions.ipynb +++ b/examples/notebooks/models/DFN-with-particle-size-distributions.ipynb @@ -195,7 +195,7 @@ "outputs": [ { "data": { - "image/png": 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N/yis50aCu2RU55tu27n7ewS9ovcRbJ/zCG4x9GUGZUq671OknQB8L2xM11Uf4E0z20JwwcSP3P2DcN6twKNh3b7j7n8mGKs3leAH2pEEp+6j+/Aegn3SDZhL8CWTym0EF3J9RtDAfqoe5a9yMMEwoE0EF9X9hTBQh18GWz243VtD+z5BY3cRwedrCtAhnPcgwbGxAJhP0KDdAex0980EPxQnh8t9l2D/ABkdt7j7FwTb9EyCHzdV0zcTNLaHEvT2fMLuC2/qWofo+tLlex3BEJE5BEPK/ovgOoLPCcZI/zWsy4kpyvFDgh/F7xOccZtI0OiGYFu+SHCW4C32/CxlVAdpmtLE6pYE303rCD7TBwI/SZJHpp/jJ9jzmEz3fZoo5Xd6QpnS5ftzghjzEkHsfIjgbBMkxP8U5biTIM4vIDi23wqn4e4vEFyI90pY1lfqUweJT9XVpCJ5zcwmElxk8oe4ywLVQ1VWEFxk92q69Dkuy1TgIXefHmc50gl7ice7e6e0iUVERHJIDWSRLAlPj71JcApyFMEwiyPcfVusBWukLLjn52kEvTcHEfTMv+HuI+Msl4iISOwX6YkUkJMILhisOkV5gRrHtTKCYSYbCIZYLCYYwyciIhIr9SCLiIiIiESoB1lEREREJKKxPCikUdh///29pKQk7mKISAGZN2/eOnc/IO5y5AvFYRHJtvrEYTWQI0pKSpg7d27cxRCRAmJmtT1FUxIoDotIttUnDmuIhYiIiIhIhBrIIiIiIiIRaiCLiIiIiERoDLJIDn311VesWLGC7du3x10UybFWrVpx2GGH0bx587iLIiIiX1PsDWQzOxv4H6AI+I27350w/1jgt0AvYLS7jwmnHwNMiiQ9ArjF3cea2a3A5cDacN5PGvtjdqUwrVixguLiYkpKSjCzuIsjOeLufPrpp6xYsYLOnTvHXZx6USwWEdkt1gaymRUB9wMDgBXAHDOb5u6LIsnWA9cCF0SXdff3gLJIPh8DT0eS/KIqgIvEZfv27WocNwFmxn777cfatWvTJ26EFItFRGqKewxyX2Cpu7/v7l8CTwKDowncfY27zwG+qiWfM4B/uLtupySNjhrHTUOe72fFYhGRiLgbyIcCyyPvV4TT6moo8ETCtGvMbIGZPWxm7VMtaGZXmNlcM5ubr70/IiJfU6yxWHFYRBqbuMcgJ+ty8TplYNYCOB+4MTL5AeCOMK87gHuB4cmWd/cJwASA8vLyOq27qdr8yqtp0xSffloDlCT//GnR6qzmd2a3g7KaX0MbNGgQEydOpF27dinTVFRUMGbMGMrLy2tMr6ysZOXKlQwaNKhO60yVXxMXayxWHK67TOIwKBaL1FfcPcgrgI6R94cBK+uYxznAW+5e3fJw99XuvtPddwEPEpw+FJEkdu7cGdu6p0+fXmvjuDaVlZVMn67rvbJEsVhEJCLuBvIcoIuZdQ57H4YC0+qYxzASTumZWYfI2wuBhV+rlCJ57IILLqB37950796dCRMmANCmTRtuueUWTjjhBGbNmsXvfvc7+vbtS1lZGSNGjKhuNF911VWUl5fTvXt3fvrTnybN/wc/+AHTpgWH7YUXXsjw4UEH4UMPPcRNN90EkDL/kpIS1q1bB8Add9zBsccey4ABAxg2bBhjxuy+ruv3v/89ffv25eijj+b111/nyy+/5JZbbmHSpEmUlZUxadIktm7dyvDhw+nTpw89e/bkmWeeAWDbtm0MHTqU0tJShgwZwrZt27K9iQuBYrGISESsDWR33wFcA7wILAYmu/s7ZnalmV0JYGYHm9kK4MfATWa2wsz2Dee1Jrjq+qmErO8xs7+b2QLgNOD/NVCVRBqdhx9+mHnz5jF37lzGjRvHp59+ytatWznuuON488032W+//Zg0aRJ//etfqayspKioiMcffxyAu+66i7lz57JgwQL+8pe/sGDBgj3y79+/P6+//joAH3/8MYsWBTc+mDlzJv369WPx4sUp868yd+5cpk6dyvz583nqqaeYO3dujfk7duxg9uzZjB07lttuu40WLVpw++23M2TIECorKxkyZAh33XUXp59+OnPmzOHVV19l1KhRbN26lQceeIDWrVuzYMECRo8ezbx583KxmfOaYrGISE1xj0EmvCfm9IRp4yOvPyE43Zds2c+B/ZJMvzjLxZQ60jjlxmPcuHE8/XRw163ly5ezZMkSioqK+Od//mcA/vznPzNv3jz69OkDBD2uBx54IACTJ09mwoQJ7Nixg1WrVrFo0SJKS0tr5N+vXz/Gjh3LokWL6NatGxs2bGDVqlXMmjWLcePG8eijj6bMv8rMmTMZPHgwe++9NwDnnXdejfnf+ta3AOjduzfLli1LWs+XXnqJadOmVfc8b9++nY8++ojXXnuNa6+9FoDS0tI9yi8BxeLCpFgsUj+xN5BFJHdmzJjBn/70J2bNmkXr1q2pqKhg+/bttGrViqKiIiB4yMUll1zCz372sxrLfvDBB4wZM4Y5c+bQvn17Lr30UrZv386bb77JiBEjALj99ts5//zz2bBhA3/84x/p378/69evZ/LkybRp04bi4uKU+Ue5135dVsuWLQEoKipix44dKfOYOnUqxxxzzB7z8vwWbCIi0sDiHoMsIjn02Wef0b59e1q3bs27777LG2+8sUeaM844gylTprBmzRoA1q9fz4cffsimTZvYZ599aNu2LatXr+aFF14A4IQTTqCyspLKykrOP/98AE466STGjh1L//796devH2PGjKFfv3615h91yimn8Oyzz7J9+3a2bNnC888/n7ZuxcXFbN68ufr9WWedxX333Vfd2J4/fz4QDAGpGtKxcOHCpMNEREREotSDLNKAGvq2bGeffTbjx4+ntLSUY445hhNPPHGPNN26dePOO+9k4MCB7Nq1i+bNm3P//fdz4okn0rNnT7p3784RRxzBySefnHI9/fr146WXXuKoo46iU6dOrF+/vrqBnCr/Tp06VS/fp08fzj//fI4//ng6depEeXk5bdu2rbVup512GnfffTdlZWXceOON3HzzzYwcOZLS0lLcnZKSEp577jmuuuoqLrvsMkpLSykrK6NvX91IQUREamfpTm02JeXl5Z54cZDsKdP7b6bTFMa9LV68mK5du8ZdjLywZcsW2rRpw+eff07//v2ZMGECvXr1irtYdZJsf5vZPHfXTZczpDicmWzFYWgasViatvrEYfUgi0ijcMUVV7Bo0SK2b9/OJZdckneNYxERKRxqIItIozBx4sS4iyAiIgLoIj0RERERkRrUQBYRERERiVADWUREREQkQg1kEREREZEIXaQn0oCyeWsmiO/2TBUVFYwZM4by8njvXjZo0CAmTpxIu3btUqZJVdbKykpWrlzJoEGD6rTOxlJ3ERHJHfUgi0iDSvWo6PqYPn16rY3j2lRWVjJ9+vSslUVERAqHGsgiBWzZsmV07dqVyy+/nO7duzNw4EC2bdtGRUUFVQ9jWLduHSUlJQA88sgjXHDBBZx33nl07tyZX/7yl/z85z+nZ8+enHjiiaxfv74679/97nd885vf5LjjjmP27NkAbN26leHDh9OnTx969uzJM888U53vt7/9bc477zwGDhxYo4w/+MEPmDZtGgAXXnghw4cPB+Chhx7ipptuql5X3759KSsrY8SIEezcuROAkpIS1q1bB8Add9zBsccey4ABAxg2bBhjxoypXsfvf/97+vbty9FHH83rr7/Ol19+yS233MKkSZMoKytj0qRJKcu+bds2hg4dSmlpKUOGDGHbtm3Z20EiItIoqYEsUuCWLFnC1VdfzTvvvEO7du2YOnVqrekXLlzIxIkTmT17NqNHj6Z169bMnz+fk046iccee6w63datW/nb3/7Gr371q+pG7V133cXpp5/OnDlzePXVVxk1ahRbt24FYNasWTz66KO88sorNdbXv39/Xn/9dQA+/vhjFi1aBMDMmTPp168fixcvZtKkSfz1r3+lsrKSoqIiHn/88Rp5zJ07l6lTpzJ//nyeeuopEp/EtmPHDmbPns3YsWO57bbbaNGiBbfffjtDhgyhsrKSIUOGpCz7Aw88QOvWrVmwYAGjR49m3rx59dgLIiKSTzQGWaTAde7cmbKyMgB69+7NsmXLak1/2mmnUVxcTHFxMW3btuW8884DoEePHixYsKA63bBhw4Cggbtp0yY2btzISy+9xLRp06p7b7dv385HH30EwIABA/jGN76xx/r69evH2LFjWbRoEd26dWPDhg2sWrWKWbNmMW7cOB599FHmzZtHnz59gKBH98ADD6yRx8yZMxk8eDB77703QHWZq3zrW99KW/9UZX/ttde49tprASgtLaW0tLTW7SciIvlPDWSRAteyZcvq10VFRWzbto299tqLXbt2AUFDMFX6Zs2aVb9v1qxZjfHDZlZjOTPD3Zk6dSrHHHNMjXlvvvkm++yzT/XrESNGAHD77bdz/vnns2HDBv74xz/Sv39/1q9fz+TJk2nTpg3FxcW4O5dccgk/+9nPUtbR3TPaBkVFRSnHQKcqe7K6iohIYdMQC5EmqKSkpHqowJQpU+qVx6RJk4Cg97Zt27a0bduWs846i/vuu6+6wTp//vw9ljvhhBOorKyksrKS888/H4CTTjqJsWPH0r9/f/r168eYMWPo168fAGeccQZTpkxhzZo1AKxfv54PP/ywRp6nnHIKzz77LNu3b2fLli08//zzactfXFzM5s2bq9+nKnv//v2rh3QsXLiwRi+6iIgUJvUgizSguG7Llui6667jO9/5Dv/7v//L6aefXq882rdvzze/+U02bdrEww8/DMDNN9/MyJEjKS0txd0pKSnhueeeS5tXv379eOmllzjqqKPo1KkT69evr24gd+vWjTvvvJOBAweya9cumjdvzv3330+nTp2ql+/Tpw/nn38+xx9/PJ06daK8vJy2bdvWus7TTjuNu+++m7KyMm688caUZb/qqqu47LLLKC0tpaysjL59+9Zre4mISP6wdKcmm5Ly8nJPvLhH9pSte/k2lsZiLi1evJiuXbvGXYwmYcuWLbRp04bPP/+c/v37M2HCBHr16tWgZUi2v81snrvrpskZUhzOTDbvqd4UYrE0bfWJw+pBFpGCcMUVV7Bo0SK2b9/OJZdc0uCNYxERKRyxN5DN7Gzgf4Ai4DfufnfC/GOB3wK9gNHuPiYybxmwGdgJ7Kj6dWBm3wAmASXAMuA77r4h13URkfhMnDgx7iLkNcViEZHdYr1Iz8yKgPuBc4BuwDAz65aQbD1wLTCG5E5z97KErvMbgD+7exfgz+F7ERFJQrFYRKSmuO9i0RdY6u7vu/uXwJPA4GgCd1/j7nOAr+qQ72Dg0fD1o8AFWSiriEihUiwWEYmIu4F8KLA88n5FOC1TDrxkZvPM7IrI9IPcfRVA+P/ApEsDZnaFmc01s7lr166tw6pFRApGrLFYcVhEGpu4xyAnu/t+XW6rcbK7rzSzA4GXzexdd3+tLgVw9wnABAiunq7LsoUmm1dFZ3N9usJaJOdijcWKwzU1xlisOCxNTdwN5BVAx8j7w4CVmS7s7ivD/2vM7GmC04SvAavNrIO7rzKzDsCaLJZZsuTt5RszSndKbovRoGYsn5HV/Co6VmQtr2XLlnHuueeycOHCrOWZK3PnzuWxxx5j3LhxKdPUVp9HHnmEgQMHcsghh2S8znzaPvWgWNyEZRKLCykOi2Qi7iEWc4AuZtbZzFoAQ4FpmSxoZvuYWXHVa2AgUPXNNQ24JHx9CfBMVkstIrEqLy+vtXGcziOPPMLKlRm3/5oCxWIRkYhYG8juvgO4BngRWAxMdvd3zOxKM7sSwMwONrMVwI+Bm8xshZntCxwEzDSzt4HZwPPu/scw67uBAWa2BBgQvhdpcq6//np+9atfVb+/9dZbuffeexk1ahTHHXccPXr0qH5kdNQjjzzCNddcU/3+3HPPZcaMGQC0adOG66+/nt69e3PmmWcye/ZsKioqOOKII5g2LWhT7dy5k1GjRtGnTx9KS0v59a9/vcc6du7cyRFHHIG7s3HjRpo1a8ZrrwVn5fv168fSpUvZunUrw4cPp0+fPvTs2ZNnngnaVzNmzODcc88FYO3atQwYMIBevXoxYsQIOnXqxLp166rXcfnll9O9e3cGDhzItm3bmDJlCnPnzuV73/seZWVlbNu2jXnz5nHqqafSu3dvzjrrLFatWgXAvHnzOP744znppJO4//77v+7uaLQUi0VEaoq7Bxl3n+7uR7v7ke5+VzhtvLuPD19/4u6Hufu+7t4ufL0pvNr6+PCve9Wy4TKfuvsZ7t4l/L8+rvqJxGno0KE1GsCTJ09m//33p7Kykrfffps//elPjBo1qrpBmImtW7dSUVHBvHnzKC4u5qabbuLll1/m6aef5pZbbgHgoYceom3btsyZM4c5c+bw4IMP8sEHH9TIp6ioiKOPPppFixYxc+ZMevfuzeuvv84XX3zBihUrOOqoo7jrrrs4/fTTmTNnDq+++iqjRo1i69atNfK57bbbOP3003nrrbe48MIL+eijj6rnLVmyhKuvvpp33nmHdu3aMXXqVC666CLKy8t5/PHHqaysZK+99uKHP/whU6ZMYd68eQwfPpzRo0cDcNlllzFu3DhmzZpV522fbxSLRUR2i3sMsojkUM+ePVmzZg0rV65k7dq1tG/fnsrKSoYNG0ZRUREHHXQQp556KnPmzKG0tDSjPFu0aMHZZ58NQI8ePWjZsiXNmzenR48eLFu2DICXXnqJBQsWMGXKFAA+++wzlixZQufOnWvk1a9fP1577TU++OADbrzxRh588EFOPfVU+vTpU53PtGnTGDMmuPXu9u3bazSAAWbOnMnTTz8NwNlnn0379u2r53Xu3JmysjIAevfuXV2+qPfee4+FCxcyYMAAIOh17tChA5999hkbN27k1FNPBeDiiy/mhRdeyGgbiYhIflMDWaTAXXTRRUyZMoVPPvmEoUOH8o9//CPtMnvttRe7du2qfr99+/bq182bN8csuOlBs2bNaNmyZfXrHTt2AODu3HfffZx11lk18h09ejTPP/88AJWVlfTr14/x48ezcuVKbr/9dv77v/+bGTNm0L9//+p8pk6dyjHHHFMjn9WrV1e/dk9904OqskHQY71t27Y90rg73bt336OXeOPGjdX1FBGRpiX2IRYikltDhw7lySefZMqUKVx00UX079+fSZMmsXPnTtauXctrr71G3759ayxTUlJCZWUlu3btYvny5cyePbtO6zzrrLN44IEH+Oqr4JkS//d//8fWrVu56667qKyspLKyEoATTjiBv/3tbzRr1oxWrVpRVlbGr3/9a/r161edz3333VfdCJ4/f/4e6zrllFOYPHkyEPQ4b9iQ/knGxcXFbN68GYBjjjmGtWvXVjeQv/rqq+ohGW3btmXmzJkAPP7443XaBiIikr/UgyzSgLJ5W7ZMde/enc2bN3PooYfSoUMHLrzwQmbNmsXxxx+PmXHPPfdw8MEH1xh+cPLJJ9O5c2d69OjBcccdR69eveq0zn/7t39j2bJl9OrVC3fngAMO4A9/+MMe6Vq2bEnHjh058cQTgWDIxRNPPEGPHj0AuPnmmxk5ciSlpaW4OyUlJTz33HM18vjpT3/KsGHDmDRpEqeeeiodOnSguLiYLVu2pCzfpZdeypVXXsnee+/NrFmzmDJlCtdeey2fffYZO3bsYOTIkXTv3p3f/va3DB8+nNatW+/RGy4iIoXLajs92dSUl5f73Llz4y5GbBr65vSZ3gd5e59vpk1zZreDvmZpcmPx4sV07do17mIUtC+++IKioiL22msvZs2axVVXXVXdQ93Qku1vM5vn7uWxFCgPNfU4DI0zFudzHBapTxxWD7KI5LWPPvqI73znO+zatYsWLVrw4IMPxl0kERHJc2ogi0he69KlS9KxySIiIvWlBrLkRKbDJ5oCd9fdEJoADVeTxkixWKR+dBcLkRxq1aoVn376qRpPBc7d+fTTT2nVqlXcRRERkSxQD7JIDh122GGsWLGCtWvXxl0UybFWrVpx2GGHxV0MERHJAjWQpdFbuDH9Y37P5ILcF6QemjdvvsfT40RE8k0+x2GR+tAQCxERERGRCDWQRUREREQi1EAWEREREYlQA1lEREREJEINZBERERGRCDWQRUREREQidJs3KQgzls9Im6aiY0WuiyEi0mRlEodBsVjygxrIEpsFvJthyq45LYeISFOWWSxWHJamRUMsREREREQiYm8gm9nZZvaemS01sxuSzD/WzGaZ2Rdmdl1kekcze9XMFpvZO2b2o8i8W83sYzOrDP8GNVR9RETykWKxiMhusQ6xMLMi4H5gALACmGNm09x9USTZeuBa2OMZljuAf3f3t8ysGJhnZi9Hlv2Fu4/JbQ1ERPKfYrGISE1x9yD3BZa6+/vu/iXwJDA4msDd17j7HOCrhOmr3P2t8PVmYDFwaMMUW0SkoCgWi4hExH2R3qHA8sj7FcAJdc3EzEqAnsCbkcnXmNn3gbkEvRsbUix7BXAFwOGHH17XVUsjUbl8Y9o0FR1zXw6RPBVrLFYcLgyZxGFQLJb8EHcPsiWZ5nXKwKwNMBUY6e6bwskPAEcCZcAq4N5Uy7v7BHcvd/fyAw44oC6rFhEpFLHGYsVhEWls4m4grwCivyUPA1ZmurCZNScIyI+7+1NV0919tbvvdPddwIMEpw9FRCQ5xWIRkYi4G8hzgC5m1tnMWgBDgWmZLGhmBjwELHb3nyfM6xB5eyGwMEvlFREpRIrFIiIRsY5BdvcdZnYN8CJQBDzs7u+Y2ZXh/PFmdjDB2LV9gV1mNhLoBpQCFwN/N7PKMMufuPt04B4zKyM4RbgMGNFglRIRyTOKxSIiNcV9kR5hEJ2eMG185PUnBKf7Es0k+bg53P3ibJZRRKTQKRaLiOwW9xALEREREZFGJfYeZJF0WixZnDbNl126NkBJRESaJsVhaWrUgywiIiIiEqEeZGkyZiyfkTZNRceKXBdDRKRJUyyWfKAeZBERERGRCDWQRUREREQi1EAWEREREYlQA1lEREREJEIX6Umdvb18Y9xFEBFp0hSHRXJLPcgiIiIiIhFqIIuIiIiIRGiIheTEAt6NuwgiIk2eYrFI/agHWUREREQkQg1kEREREZEINZBFRERERCIyGoNsZq9lmN92dx/4NcojIiJJKA6LiDScTC/S6wNcmSaNAf/z9YojIiIpKA6LiDSQTBvIf3P3R9MlMrPvfs3yiIhIcorDIiINJKMxyO5+RobpdFpPRCQHFIdFRBpOve6DbGbfd/fHsl0YkVyqzODRrBUdc18OkWxQHJZ8pVgs+aDWHmQz65bkrzswIlsFMLOzzew9M1tqZjckmX+smc0ysy/M7LpMljWzb5jZy2a2JPzfPlvlFRFpSA0Rh8P1KBaLiITS9SC/AUwhuPAjqlM2Vm5mRcD9wABgBTDHzKa5+6JIsvXAtcAFdVj2BuDP7n53GKxvAK7PRplFRBpYTuMwKBaLiCRK10BeDIxy90+jE83s+Sytvy+w1N3fD/N9EhgMVAdld18DrDGzf6rDsoOBijDdo8AMFJRFJD/lOg6DYrGISA3pGsgDgK2JE909MUDW16HA8sj7FcAJWVj2IHdfBeDuq8zswFSZmNkVwBUAhx9+eIarzj+bX3k17iKISP3kOg5DzLG4qcRhUCwWyRe1NpDdfVP0vZkdGPYiZEviKUMAb4Bldy/gPgGYAFBeXl7n5aWwzFg+I6N0FR0rclkMkWoNEIch5lisOCyJMonFisOSS3V91PSULK9/BRC9VvUwYGUWll1tZh0Awv/Z/jIREYlLtuMwKBaLiNRQ1wZysp6Cr2MO0MXMOptZC2AoMC0Ly04DLglfXwI8k8Uyi4jEKdtxGBSLRURqqOt9kLN66svdd5jZNcCLQBHwsLu/Y2ZXhvPHm9nBwFxgX2CXmY0Eurn7pmTLhlnfDUw2s38FPgK+nc1yi4jEKOtDEBSLRURqqteDQrLJ3acD0xOmjY+8/oTglF1Gy4bTPwUyeuqUiIgoFouIRMU9xEJEROpGcVhEJMfq2kC+KCelEBGRTCkOi4jkWJ0ayO6+OlcFERGR9BSHRURyr85jkM2sLcHjRnsCbaLz3H1glsolIiIpKA6LiORWfS7S+z3BlcpPA9uyWxwREcmA4rCISA7Vp4F8IrCfu3+V7cKIiEhGFIdFRHKorhfpAcwEuma7ICIikjHFYRGRHKpPD/KlwHQzexOocbGIu9+ejUKJ1FWLJYvTpvmyi9oTUjAuRXFYGplM4jAoFkt+qE8D+S6gI7CM4IlKVbL+dCcREUlKcVhEJIfq00AeChzt7quyXRgREcmI4rCISA7VZwzy+4AuDBERiY/isIhIDtWnB/l/gWlmdh97jn17JSulEhGR2igOi4jkUH0ayFeH//8zYboDR3y94oiISAYUh0VEcqjODWR375yLgoiISGYUh0VEcqvOY5DNrEUuCiIiIplRHBYRya36DLHYYmbvAm8DleH/ZcBod78se0UTaXiVyzdmlK6iY27LIZKG4rAUtExiseKw5FJ9GsgHAmXh3/HANcDhBFdVizQJM5bPSJumomNFroshTZfisDR5isOSS/UZg7wRmBH+AWBmdwK6H2cTsYB34y6CSJOmOCyKwyK5VZ/7ICdzJ3BDlvISEZG6UxwWEcmSOvcgm9n9BGPeKoG/u/t2oAPweVZLJiIiSSkOi4jkVn16kD8GTgd+C6w3syWEF4mY2YVmdqyZFWWamZmdbWbvmdlSM9uj98MC48L5C8ysVzj9GDOrjPxtMrOR4bxbzezjyLxB9ainiEhjldU4DIrFIiJR9RmDXH1jejNrDnQDeoR/l4f/DwBapcsrDOD3AwOAFcAcM5vm7osiyc4BuoR/JwAPACe4+3sEF6hU5fMx8HRkuV+4+5i61k9EpLHLZhwO81AsFhGJyKiBbGZ3uPvNidPd/SuC2wu9Haa7zd0HmVm7DNffF1jq7u+Hyz8JDAaiQXkw8Ji7O/CGmbUzsw7uHr0Y5QzgH+7+YYbrlSTezvAWZyLS8HIYh0GxuFFRLBaJX6ZDLEaaWWczO6K2P+BaqL7COhOHAssj71eE0+qaZijwRMK0a8LTgA+bWftUBTCzK8xsrpnNXbt2bYbFFhFpcLmKwxBzLFYcFpHGJtMG8j7A0gz+MjqdF2FJpnld0oRPlDof+H1k/gPAkQSn/VYB96YqgLtPcPdydy8/4IADMiy2iEiDy1UchphjseKwiDQ2GQ2xcPds3Q4u0Qog+iycw4CVdUxzDvCWu6+umhB9bWYPAs9lq8AiInHIYRwGxWIRkRpyGXAzMQfoEp42bEFwem5aQpppwPfDK6hPBD5LGPM2jIRTembWIfL2QmBh9osuIlIwFItFRCLq86jprHH3HWZ2DfAiUAQ87O7vmNmV4fzxwHRgEMGpw8+By6qWN7PWBFddj0jI+h4zKyM4/bcsyXwREQkpFouI1BRrAxnA3acTBN7otPGR1w5cnWLZz4H9kky/OMvFFBEpaIrFIiK7xT3EQkRERESkUVEDWUREREQkQg1kEREREZEINZBFRERERCLUQBYRERERiVADWUREREQkQg1kEREREZGI2O+DLNJQWixZnDbNl126Zm19M5bPSJumomNF1tYnIpIPGjIWZxKHQbFY9qQGskg9VC7fmDZNWcd2OS+HiEhTpTgsuaQhFiIiIiIiEWogi4iIiIhEqIEsIiIiIhKhBrKIiIiISIQayCIiIiIiEWogi4iIiIhEqIEsIiIiIhKhBrKIiIiISIQayCIiIiIiEWogi4iIiIhEqIEsIiIiIhIRewPZzM42s/fMbKmZ3ZBkvpnZuHD+AjPrFZm3zMz+bmaVZjY3Mv0bZvaymS0J/7dvqPqIiOQjxWIRkd1ibSCbWRFwP3AO0A0YZmbdEpKdA3QJ/64AHkiYf5q7l7l7eWTaDcCf3b0L8OfwvYiIJKFYLCJSU9w9yH2Bpe7+vrt/CTwJDE5IMxh4zANvAO3MrEOafAcDj4avHwUuyGKZRUQKjWKxiEhE3A3kQ4HlkfcrwmmZpnHgJTObZ2ZXRNIc5O6rAML/B6YqgJldYWZzzWzu2rVr61kNEZG8FmssVhwWkcZmr5jXb0mmeR3SnOzuK83sQOBlM3vX3V+rSwHcfQIwAaC8vDxx3SI5NWP5jLRpKjpW5LoYIrHGYsVhiZtisSSKuwd5BdAx8v4wYGWmady96v8a4GmC04QAq6tO/YX/12S95CIihUOxWEQkIu4e5DlAFzPrDHwMDAW+m5BmGnCNmT0JnAB85u6rzGwfoJm7bw5fDwRujyxzCXB3+P+Z3Fcl/y3g3biLICLxUCxuRBSLReIXawPZ3XeY2TXAi0AR8LC7v2NmV4bzxwPTgUHAUuBz4LJw8YOAp80MgnpMdPc/hvPuBiab2b8CHwHfbqAqxWLzK6/GXQRJonL5xrRpyjq2y3k5RNJRLP76FIcbp0ziMCgWy57i7kHG3acTBN7otPGR1w5cnWS594HjU+T5KXBGdksqIlK4FItFRHaLewyyiIiIiEijogayiIiIiEhE7EMsRBqTFksWZ5Tuyy5dc1wSEZGmK5NYrDgsuaQeZBERERGRCDWQRUREREQi1EAWEREREYlQA1lEREREJEINZBERERGRCN3Fool4O8OnCYmISO4oFovkB/Ugi4iIiIhEqAdZpJGbsXxGRukqOlbkshgiIk1aJrFYcbhwqAdZRERERCRCDWQRERERkQgNsRCJUWUGF+yUdWyX83KIiDRlisWSSD3IIiIiIiIRaiCLiIiIiESogSwiIiIiEqEGsoiIiIhIhC7SE6mHFksWp03zZZeuDVASEZGmSXFYckk9yCIiIiIiEbE3kM3sbDN7z8yWmtkNSeabmY0L5y8ws17h9I5m9qqZLTazd8zsR5FlbjWzj82sMvwb1JB1EhHJN4rFIiK7xTrEwsyKgPuBAcAKYI6ZTXP3RZFk5wBdwr8TgAfC/zuAf3f3t8ysGJhnZi9Hlv2Fu49pqLqIxE2PQZX6UiwWyY5M4jAoFueDuHuQ+wJL3f19d/8SeBIYnJBmMPCYB94A2plZB3df5e5vAbj7ZmAxcGhDFl5EpEAoFouIRMTdQD4UWB55v4I9A2vaNGZWAvQE3oxMviY8DfiwmbVPVQAzu8LM5prZ3LVr19ajCiIieS/WWKw4LCKNTdx3sbAk07wuacysDTAVGOnum8LJDwB3hOnuAO4FhicrgLtPACYAlJeXJ65bJHaZPAIV9BhU+VpijcWKw5IP9DjqpiXuHuQVQMfI+8OAlZmmMbPmBAH5cXd/qiqBu692953uvgt4kOD0oYiIJKdYLCISEXcDeQ7Qxcw6m1kLYCgwLSHNNOD74RXUJwKfufsqMzPgIWCxu/88uoCZdYi8vRBYmLsqiIjkPcViEZGIWIdYuPsOM7sGeBEoAh5293fM7Mpw/nhgOjAIWAp8DlwWLn4ycDHwdzOrDKf9xN2nA/eYWRnBab1lwIgGqZCISB5SLBYRqSnuMciEQXR6wrTxkdcOXJ1kuZkkHxOHu1+c5WLmvQW8G3cRRKQRUyxuGIrFIvkh9gayiDQc3StZRCR+isWNnxrIIjnSYsnitGm+7NK1AUoiItI0ZRKHQbFY9hT3RXoiIiIiIo2KGsgiIiIiIhEaYiFSIHQTexGReOnBToVDPcgiIiIiIhFqIIuIiIiIRGiIhYjUoNsPiYjET7E4XmogF4C3MxzzJCIiuaE4LFJY1EBu5Da/8mrcRZAc0r2SRRo/xeHCp1gsidRAFmlCdKcLEZH4KRY3fmogi0idZTI2DjQ+TkQklzROOXd0FwsRERERkQg1kEVEREREIjTEQqSRy+TiEcjeBSQaGycisqeGvpBPsTheaiCLSM5ofJyISLx0zUj9qIFcABbwbtxFEBFp0hSHRQqLGsgiBaIhT/9lcuoPMjv9p15mESkU+TwkTrG4Jl2kJyIiIiISoR5kkSYkXy8y0Rg6ESkkOuPX+MXeQDazs4H/AYqA37j73QnzLZw/CPgcuNTd36ptWTP7BjAJKAGWAd9x9w0NUZ9sezvDD7ZIvtIpwsZBsTg1xWFpChqyQyMf4nCsDWQzKwLuBwYAK4A5ZjbN3RdFkp0DdAn/TgAeAE5Is+wNwJ/d/W4zuyF8f31D1SsTm195Ne4iiCSV6Ri6TORrD0gm8iHAZ0qxWKTxyVYszuezgpnIVSyOuwe5L7DU3d8HMLMngcFANCgPBh5zdwfeMLN2ZtaBoEci1bKDgYpw+UeBGTSyoJwpXRkt+Sybje1MVJK9L4K061r+hwZbVwNQLK6F4rDks0KOw5C7WBx3A/lQYHnk/QqCnol0aQ5Ns+xB7r4KwN1XmdmBqQpgZlcAV4RvvzCzhXWtRJ7YH1gXdyFyqJDrV8h1g8Kv3zFxFyADscbiJhSHobA/74VcN1D98lmd43DcDWRLMs0zTJPJsmm5+wRgAoCZzXX38rrmkQ8KuW5Q2PUr5LpB06hf3GXIQKyxuKnEYSjs+hVy3UD1y2f1icNx3+ZtBdAx8v4wYGWGaWpbdnV46o/w/5oslllEpNAoFouIRMTdQJ4DdDGzzmbWAhgKTEtIMw34vgVOBD4LT9nVtuw04JLw9SXAM7muiIhIHlMsFhGJiHWIhbvvMLNrgBcJbg/0sLu/Y2ZXhvPHA9MJbiu0lODWQpfVtmyY9d3AZDP7V+Aj4NsZFmlCdmrWKBVy3aCw61fIdQPVL3aNLBY3+u31NRVy/Qq5bqD65bM6182CC5JFRERERATiH2IhIiIiItKoqIEsIiIiIhKhBjLBY1LN7D0zWxo+7amgmNkyM/u7mVXmyS2namVmD5vZmui9Us3sG2b2spktCf+3j7OM9ZWibrea2cfh/qs0s0FxlrG+zKyjmb1qZovN7B0z+1E4vVD2Xar6FcT+awiFHIsVh/OLYnH+7r9sxeImPwbZgsek/h+Rx6QCwxIesZrXzGwZUO7uBXEDcDPrD2wheKrXceG0e4D1kUfatnf3vHtiV4q63QpscfcxcZbt6wpv89XB3d8ys2JgHnABcCmFse9S1e87FMD+y7VCj8WKw/lFsTh/91+2YrF6kCOPWHX3L4Gqx6RKI+XurwHrEyYPJniULeH/CxqyTNmSom4Fwd1Xuftb4evNwGKCp7AVyr5LVT/JjGJxHinkOAyKxeTx/stWLFYDOfXjUwuJAy+Z2TwLHulaiGo80hZI+XjxPHWNmS0IT/vl5WmvKDMrAXoCb1KA+y6hflBg+y9HCj0WKw4XhoI6lhWLU1MDOUuPrG7kTnb3XsA5wNXhqSPJHw8ARwJlwCrg3lhL8zWZWRtgKjDS3TfFXZ5sS1K/gtp/OVTosVhxOP8V1LGsWFz7/lMDObNHrOY1d18Z/l8DPE1wKrPQFOwjbd19tbvvdPddwIPk8f4zs+YEAetxd38qnFww+y5Z/Qpp/+VYQcdixeH8V0jHsmJx+v2nBnJmj1jNW2a2TzhIHTPbBxgILKx9qbxUsI+0rQpYoQvJ0/1nZgY8BCx2959HZhXEvktVv0LZfw2gYGOx4nBhKJRjWbEYyGD/Nfm7WACEt/oYy+7HpN4Vb4myx8yOIOitgODR4hPzvX5m9gRQAewPrAZ+CvwBmAwcTvhIW3fPuwssUtStguCUkAPLgBFV48TyiZmdArwO/B3YFU7+CcHYsELYd6nqN4wC2H8NoVBjseJw/lEszt/9l61YrAayiIiIiEiEhliIiIiIiESogSwiIiIiEqEGsoiIiIhIhBrIIiIiIiIRaiCLiIiIiESogSwiIiIiEqEGsoiIiKRlZu+YWUUG6ZaZ2ZkNvd44mJmb2VYzy8l9rc3sFTPbbmYzc5G/pKYGsuQFBeY9KTCLSFQY/7aZ2RYzW21mvzWzNl8jrxqx1N27u/uMrBS2DnKxXjNrH8bQLWb2uZl9aGb/Ws/sjnf30dksXxV3Px24Mhd5S+3UQJasUGDOnAKziOTQee7eBugF9AFuqsvCZrZXTkrV+JQB69y9jbu3Bm4Efm1m+8dbLGks1ECWbFJgzkwZCswikkPu/jHwAnAcgJndYGb/MLPNZrbIzC6sSht2SlxvZguAreFjlg8Hng1/yP9HJN2Z4euOZvaUma01s0/N7JfJymFmh5jZ1DDdB2Z2baoyh2X4OCzje2Z2RpL1DgnLVPX3hZnNqOu6COLwW5H3fyF4xHn72rZrJsxstJk9EHnf3sy+MrNWYV1GmdmC8AzgQ2Z2kJm9ENb7T2b2tcsgX58ayJJ1CswKzCISLzPrCAwC5oeT/gH0A9oCtwG/M7MOkUWGAf8EtHP3YcBHhJ0e7n5PQt5FwHPAh0AJcCjwZJIyNAOeBd4O05wBjDSzs5KkPQa4Bujj7sXAWcCyxHTuPiksUxvgEOB94Im6rCvUE5gXrrsd8LPw/dIU6euiB1AZeV8GvOfu28P3/wwMAI4GziP4vvwJsD9Bu6y27w9pIGogS9YpMCswi0hs/mBmG4GZBD++/xPA3X/v7ivdfZe7TwKWAH0jy41z9+Xuvi2DdfQliIGj3H2ru29392TXKvQBDnD32939S3d/H3gQGJok7U6gJdDNzJq7+zJ3/0eqAoRxdyIww91/Xcd1QRAbf2Rmm4ANwIHA2e7uGdQ/nWRx+O3I+/vcfXXYmfQ68Ka7z3f3L4CnCb4jJGZqIEs2KTArMItIvC5w93bu3sndf1AVV83s+2ZWaWYbwzh9HMEP4yrL67COjsCH7r4jTbpOwCFV6wzX+xPgoMSE7r4UGAncCqwxsyfN7JBa8r4LKGb3j/qM12VmLYGuQKm77wtcBJwIfJWmPmmZWQvgSODvkcnHUzMur4683pbkfb2u35HsUgNZskmBWYFZRBoZM+tE8KP9GmA/d28HLAQskizxB3ptP9iXA4db+utGlgMfhN8LVX/F7j4oWWJ3n+jupxDEVAf+K0V9hhKcebzI3atiZ13WdRzwBcFZQNx9KsGZy3+OrKPCzJ41s2lmNtfMjk9T1yrdgI/d/fMwHwMqqNlRIXlADWTJKQXmPWQamJ8Jx1m/bWbHpalrFQVmEUlmH4K4thbAzC4jvEakFquBI1LMmw2sAu42s33CaxxOTpFuU3iNx95mVmRmx5lZn8SEZnaMmZ0ediJsJ/jBvjNJup7AfQQdMmvrsy6CM2ULE87aTQfOT0jXHhgMXAzcmWJbJOoBHGhmR5rZ3sAdBN8ryzJcXhoJNZAl1xSYa8o0MLdx928BNwDDU2yLRArMIrIHd18E3AvMIoivPYC/plnsZ8BN4Vmx6xLy20lwDcNRBD/wVwBDkqy3Kl0Z8AGwDvgNwfUoiVoCd4dpPiEYevaTJOkGEzRcZ9ruC6ZfqOO6yoAFCdP+CAwws1aRafM9sBg4OEk+yfQAXiS4vmMpwfZ+H8jJ7Tgld5rKbbUkJu6+yMyqAvMu4DEyC8z3mdk9wJ3uPiaS304zOw8YRxCYnWA8cI08I+nuJQiWLYH3SH7ruarA3JVgqMPfgCuSpIsG5qppr7v7OXVYVxnJA/MPzaxV5GK6yvD/cjK/u0U0MO8T1qkqMF+SYR4ikqfcvaSWeaNJ0UhLtpy7PwM8kyqdu38EXJAuP3dfSXDWrVbuvoCa16akyu9WguFwydJluq5rkkybQRA3o8rCM3FHEzTak/kCmGdm49z9ZoI4/Bt3vyiS5r7IekoS1vsvCe9/Q9CwB8DMXiYYhje79lpJtll2rgsSkWyx4Ml957r7deHwiuvc/dIk6bYTBOdx7n6zmb1AEJinZqkc1YHZ3c/IRp4iIvkgjMNVPecHA5e7+/yUC+xebgUwMOy1lzymHmSRPOXurRIm9QAWZzH/AdnKS0QkD73r7telTxaw4D7yBxLcqUnynHqQRQpAGJhXA/tELh4UEZF6iJ7Ji7koEhM1kEVEREREInQXCxERERGRCDWQRUREREQi1EAWEREREYlQA1lEREREJEINZBERERGRCDWQRUREREQi1EAWEREREYlQA1lEREREJOL/A0O76V+4YFKMAAAAAElFTkSuQmCC\n", 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", 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VqRCR/IldHsSuTVPKGPOwm7GISFHsVeRmxpg9bsQSKDxeMwGGAhuMMe9nY/6fY6/0p7r2llJJ+arsEdtN8gljzMKspqUsEckLxBtj4pxWq4/S0ZXSm/m3xr6n16VxqFJKKZf41RgvP3atiDyLfb22knqXF1+bKLbPfx7gVa10pcs9ItID+5ot4cLYJqX8nT+VPSp15YHxTje/c9iWVKWUUuo/2uKllFJKKaWUUj7mT2O8lFJKKaWUUipH0oqX+o+IvCwiT4jIK2Kni07puBtEpFYqj/cVke7O/WkiEpOBGAqJyH0e26VFRMdGKZUDaZmjlBK7XmDiZCp7RGSnx3YeL+UxO+2jUjz3c7mwZmJWYvivbBKR57KaXjry6yki+0XkUxHJJyIHxa4L6HnMTyJyq4jcJiIbRSTZtfWU92jFS13CGNPfGPNnKofcgF2A8xIiEmKMGZ50DagMKISdhTAxll3GmCwXeEop/6VljlK5lzHmoMfyDsOB9z2W8jiX0nniLKOSzjyapn1UtvJ5xcvxjTHmbmPMSeyyDDckPuBUwppjJ//6BrtoufIxrXjlciLyvIisE5E/gerOvv+u7ojIQBFZ7Uzj+46INAU6AW87V6OqOFdxXheR6cDDiVexPbK5U0RmO9NRxzrpXnSM81hF7FTIVZy03xaRis70zYhImIiMEpEVIrJERNo4+3uKyA8iMklENojIW75/5ZRSmaFljlIqLSLSSESmi8giEZksdl1CkvnfnyYi74vIDBFZIyKXO/+bG0Tk/zzSS5wdtrVzzncislZExor8tz5ffxFZ4JQNHyfuTyG+miIy32O7othlEhCRdk55sUJERoqd8dTz3IFAuFPmjHX2/eQ811Ui0sfj2N4ist6J+RMRGeLsjxKR7514F4hIs3S8rOO4eD3IG4FJxphT6ThXeYnOapiLiV0UtwvQEPtZWAws8ni8CPYfs4YxxohIIWPMERGZgMf06E7ZVMgY08rZfjlJVvmMMU1FpCV2HZk6qYT1DFAncRpmubDwMcD9AMaYumIXsP1DLizY28B5HmeBdSLyoTFmewZeDqWUj2mZo5RKBwE+BDobY/aLXRvwNeAu53HP//3rgXPGmJYi8jDwM9AIOARsEpH3nbUwPTUEagO7sOvaNcOuDzrEGPOKk+4Y4Drgl+QCNMasEZE8IlLZGPMvdsHy8SIShl0Pr50xZr2IfAH0AwZ5nPuMiDyQZLmJu4wxh8Sun7dARL4H8mLXPL0Muybg38Ay5/gPsC2Ds0SkPHaR95ppvK6TgE9FpKjzmnRxXmeVjbTFK3drgV1g85Qx5hgwIcnjx4Az2H/U/wGpXRVJbkHNROMAjDEzgAJip8PPjObAGCettdjptRN/BP1ljDnqLEy8GqiQyTyUUr6jZY5SKi15sRdLpohdXPwFoKzH40n/9xPLkRXAKmPMbmdR9H+BcsmkP98Ys8MYk4BdqLyis7+NiMwTkRVAW2zlLDXjgVud+7c5cVUHNhtj1jv7RwMt00gH4CGxi5PPdWKOBmKB6caYQ8aY88C3Hse3B4Y4r88EbDkXmVoGTrfNCcDNIlIMe/Hoj3TEprxIW7xUiusJOAuBxgLtsFdGHsAWRsk5mYE8DBDHxRX/sLRDJcVmf+xV50Tx6GdbKX+lZY5SKjWCrUA1SeHxpP/7if+LCVz8f5lA8v+Xl/zvOi1Vw4AYY8x2pxU9rTLiG+BbEfkBMMaYDSLSII1zLiF28fP2QBNjzCmxC9yHkXr5E+QcfzqD2Y3DVmQF+Nmp0KlspC1eudsM4EYRCXeulFzv+aCI5AcKGmN+Ax7BXh0B2+Sd6pWVJG5z0msOHDXGHAW2YJvPEZHLgErpSHsG0NU5pxp2wdJ1GYhDKeUuLXOUUmk5C0SJSBMAEQkVkbRan7IqsZJ1wCmH0pxgxxizCVtxe5ELrXBrgYoiUtXZ7gZMT+b08yIS6twvCBx2Kl01gMbO/vlAKxEpLHYikZs8zv8De2EKgAxU+KZiW9Pux+kZoLKXXqHLxYwxi0XkG2xT+1ZgZpJDIoGfnStBAjzq7P8a+EREHiIdhRNwWOxUrgW40Ef7e6C700y+AFjvxHRQRP4RO7j9d2CoRzrDgOFON4A4oKcx5mwq41+VUn5EyxylVDokYP/PB4udeS8EO0Zqla8ydMaSfoLtrrgFW0akxzfA2zgXcowxZ0SkF7YlLMRJZ3gy530MLBeRxdgyqq/YyTnWYbsbYozZKSKvA/Ow49FWA0ed8x8ChjrnhGAvEvVNx/NMcMaP3eKco7KZGJNirw+llFJKKaWUC0QkvzHmhFOJ+xEYaYz5MZ3n9sR2nXwgrWOd41sDTxhjrstkuCodtKuhUkoppZRS/udlp5V+JbAZ+CkD554GrhaRT9M60Jk5chhwOBMxqgzQFi+llFJKKaWU8jFt8VJKKaVUriR2kez5IrJM7OK1A5I5pqCI/OJxTC83YlVKBT5t8VJKKaVUriR2ppR8zjiaUOxCug8bY+Z6HPMcdrbNp0UkCjsBQklnXSSllEo312Y1LFasmKlYsaJb2SulssmiRYsOGGOi3I5Dyxylcr6MljfGXn0+4WyGOrfk1oGLdCpp+YFD2FkuUxQaGmrq16+f7riVUoEpo2WOaxWvihUrsnDhQreyV0plExHZ6nYMoGWOUrlBZsobEQkGFgFVgaHGmHlJDhkCTMBO6R0J3GaMSUgmnT5AH4By5cppeaNULpDRMkfHeCmllFIq1zLGxBtjGgBlgVgRqZPkkKuwa8+Vxi7qPURECiSTzsfGmBhjTEzx4sV9G7RSKiBpxUsppZRSuZ4x5ggwDeiY5KFewA/G2oid1rtGamnt37/fFyEqpQKcVryUUkoplSuJSJSIFHLuhwPtgbVJDtsGtHOOKQFUB/5NLd1Dhw55PValVOBzbYyXUkoppZTLSgGjnXFeQcB4Y8xEEekLYIwZDrwKfC4iKwABnjbGHHAtYqVUwNKKl1JKKaVyJWPMcqBhMvuHe9zfBVyZnXEppXImrXjlNPHx8O+/zPthJ/NnnOHB/KNg5Uq2l21C6V9GEJwn2O0IlVI5ycGDsHLlhduKFbB7N3z3HTS85PesUrlC3Jl4t0NQSvkhHeOVE3z9Nd+0Gkbj/CuIy18IqlXj12dm8Nhv7Ti7YDmbI+tR+4/3eO+GGW5HqpQKdBs3wqOPQocOUKoUFCsGrVvDAw/A119DUBCcOAF33gmnT7sdrVKuOBMXzLzxfrGShlLKj2jFK9AtWgS3307o0gUUyHuOwz0egc8+47G/ruPInrPk/XcNFWd/xVO1f+WWKX1g6VK3I1ZKBSpj4LbbYNgwOHwYrroK3nkHJk2CHTvg0CGYMQO+/BJWr4bnnnM7YqVcUS0omCsGd4WES5b7UkrlYml2NRSRkcB1wD5jTNK1LTyPuxyYi11Y8DvvhahS8+3Ds2iVrxL/2zaI/xUsCDQCoJDHMRIkvDD9SqjzGNx5JwnzFxIUEeZGuEqlScscPzZ9OixeDCNGQJ8+KR/XoYNtARs0CK67Dtq1y7YQlfIHkeULwz//cOTtTyj09L1uh6OU8hPpafH6nEvXtLiIMxvQm8BkL8Sk0unAku10/acfb9ccCQULpn5w0aIkfDqSu1Y9xlMt52ZPgEplzudomeOf3nkHoqKgW7e0j33zTaheHXr2hCNHfB2ZUn5l7/nzzL7iUSo804UfXlvjdjhKKT+RZsXLGDMDSGtBigeB74F93ghKpU+xL95jRXBDHh8ena7jg669mnx1KhOxaCbm76k+jk6pzNEyx0+tXg2//mpbssLD0z4+IsJ2Odyzx56jVC5y5OhRGo55jNsif6PlCy3h8cd1zKNSKutjvESkDHAjMDwdx/YRkYUislBXdc+iw4fhk0+o3qUhJRuVSfdpg+dczivRY5CePeDoUR8GqJRvaJnjknffhbAwuO++9J8TEwMvvghjx8I33/guNqX8UHh0WT7edT3F+t2Cee89uhT7k0+6z4Tz590OTSnlEm9MrjEIu5hgmnOnGmM+NsbEGGNioqKivJB17vVB90X0PfkOcY88kaHzJH8+GDOGJTuL81JLbfVSAWkQWuZkr927betVr152FsOMeO45iI2Ffv1g507fxKeUv8qfH4YN49TEqRwJKcapMd9BtWqYwR8Sd+SE29EppbKZNypeMcDXIrIFuBkYJiI3eCFdlZJz5zgwbQW7itUnJKZBxs+/4gp+bv42nyyPZf9nE7wenlI+pmVOdhsyxF6lf+yxjJ8bEgJjxsDZs3DXXXZmRKVymXzXtmbSkcY8+MtVULIkvz48mepF97Oh90DYtMnt8JRS2STLFS9jTCVjTEVjTEXgO+A+Y8xPWU1XpWLcOF498Rg/jzmW6SSe/705Kxt0I+qpXvZqtlIBQsucbHbiBHz0Edx4I1Stmrk0qlWzE3P88Yedil6pHC4oKJmfVyIEXXcNzJlDgWFv0qDUPiqOHgBVq7Kk6f0cGP2rdkNUKodLs+IlIuOAOUB1EdkhIr1FpK+I9PV9eCopk2DY9NrXUKcOctWVmU4nNCKUIuOGYk6e4ufrPsEk6FVo5R+0zPEzo0bZMaVPZKxb8yX69oWOHeHJJ2HtWu/EppSfio5OfdKrlv1q8/2OKwjdtgnz8gDuXPAQnXsWgvLl4ZlnYN267AlUKZWt0lzHyxhze3oTM8b0zFI0Kk2TX1/ENRt+ZcpTU2gnkrXEatTgp27f879Pr+Gn+yfR+aNUZ/BWKltomeNH4uLg/fehaVNo0iRraYnAyJFQp46djn72bAgN9U6cSgWq0qWRl/oz/oY4jv5xAGbFcvbtwdzwZiueqvUhbR6uB7fcAoULux2pUsoLvDHGS2WjhpMH8mrk27R4sY1X0uv8UUd+qD+ATqNvgh07vJKmUiqH+PFH2Lw5661diUqVsosvL1xoZ0lUKofancEu/LXrh9D0yWbw889snbGVLcVjiTt+Gu69lwMlarOg3TOYH3+yYyWVUgFLK16BZMkSSsz6nudfEPLkz+OVJINCgrjxx+7I2TN2HIdSSoGdBOPtt+24rk6dvJfuzTfbLocffADnznkvXaX8yLFjmR+DXa1ZFKv3FKX9lk9hwQJGXv4RsX8PZPP/HoOSJUnofQ/8+adtkVZKBRSteAWQwfesYG54G+jTx7sJV6rET41e5Yq3/sfZY3o1TSkFzJoFCxbYmQyDg72b9oMP2oWVf/zRu+kqlUOIgAQJxMTQ59fOfPdNPJUnfQTXX88DY66gU4dTmFKl7dhJrYQpFTC04hUgTq3fwWuLrmJ8zf5QqJDX089345WExx1n78hfvZ62UioAvf22XbOrRw/vp92xI1SuDEOHej9tpTJARMJEZL6ILBORVSIyIJljnhSRpc5tpYjEi0iR7IqxUCG46dZguOoq+OILqr3Wg9r/q460awtffskLHebyS5EedrmGiRPhzJnsCk0plUFpTq6h/EPEx4P4N+hjzo1a5ZP0Ozx9GR0+rwnfFIFH/ueTPJRSAWLtWvjlF3jpJYiI8H76QUFw33127Njy5VCvnvfzUCp9zgJtjTEnRCQUmCUivxtj5iYeYIx5G3gbQESuBx41xhxyJ1x45MlQoDrwNWcOneKrmgYpPoXrf+hJwqjPGZ2nD9d2OEfx29rANddA0aJuhaqUSkJbvAJA/KGj8PHH5LvtOgrXK+ebTJwfQifmrmDP5GW+yUMpFRjeew/CwmzlyFd69bJ5aKuXcpGxTjiboc4ttfVVbgfGpZVuSEj2XNcOKxLBpj35eG7+DbBvH0s+/Ie7zg1n8qx80L07x6Mqs7pRN8ybb8GqVbqAuVIu04pXAHiv2xKaHf+dk/c/5dN8zt/Rg+qynucezPygYKVUgNu7F774wnYxLF7cd/kUKQJ33AFffglHjvguH6XSICLBIrIU2AdMMcbMS+G4CKAj8H0Kj/cRkYUisrBAgQI+i/fSfCE8HMiTh8vub8Ly5dB5ywcwfz4TOn1K7cVjWPzMN1CnDkcq1Of0PQ/ZFu0TJ9JMWynlXVrx8nfnzlFyzo9UK3mcfM0a+DSr0KhCvNZqCn22vgAHD/o0L6WUnxo61M42+Oijvs/r/vvh1CkYPdr3eSmVAmNMvDGmAVAWiBWROikcej3wT0rdDI0xHxtjYowxMVFRUT6KNnUiULcuFCgUBJdfTrvht/DJJ9Bw688wYgTvhT9P8U9f42SnLlCkCCdaXoMZ+CYsWQIJCa7ErFRuohUvf/fzz3Q7PJhRn2VPgdhz8GU0PjfDLnSqlMpd4uPtshLXXw/Vq/s+v8suswszDx2qP/qU64wxR4Bp2Fat5HQhHd0MAXbu3OmdoLKoZEm4+24IKl8W+vTh6s9vY8Cb4eT7cwI88gi9lz9Mk2db2f/FkiU5fUt3+PRTu36fUsrrdHINP7flxyWUKVCU0Kuuyp4M69Zl5xX/Y8wbhicfjic4j5enkVZK+a+lS+HAAejSJfvyfOAB6NrVTol95ZXZl69SgIhEAeeNMUdEJBxoD7yZzHEFgVbAnelJ94SfduNr0gSaNAkB2kG7dnSqD4e3HIXyX8Aff9Dk66e57Lt5jKQyVKzIiRZXk//KptC6NZQt63b4SgU8bfHyc1d+dw9dIiZ4fx2dVMxu8jjPHX6CRUPmZFueSik/MG2a/duqVfbledNNdizZkCHZl6dSF5QCporIcmABdozXRBHpKyJ9PY67EfjDGHPSlSh9pGtXeOD5gtCtG+aLMdz5ei2ueudK+PBDztePofSYgfxft7VQrhxUqcLuLo/arsH//qsTdSiVCWJc+seJiYkxCxcudCXvQGF27uL7sg9R+N7baDf8lmzL9/yp8+ys2IyKjYrC779nW74qZxKRRcaYGLfj0DInHa6/Htavh3XrsjffF16A11+3P+YqVszevFWO4i/lTWRkpDl+/LjbYWTJiRMweFACzUttouWxiWz9fTUVp3zCZ9zFXYziVMnKbKp3I7WurkBwi6ZQvz5k02yOSvmLjJY5abZ4ichIEdknIitTeLyriCx3brNFpH5GAlYpkxnTuZnvadenSrbmGxoRSsX7r4VJk2DjxmzNWyktc1wSHw8zZtguRdnt3nvtkhbDh2d/3kqpZOXPD8+9EETL3tHw6KNEjP2Ed99JoOXEp2HoUGbVuJt6f7zD349OgJgYtkfW4td6z3LqyZfsrIn79rn9FJTyO+m5NPE5MAT4IoXHNwOtjDGHReRq4GPgCu+El7vN+WYbZSJrU75+9v+uNPf0oc+AskTdsYXX51fN9vxVrvY5WuZkv6VL4dgxdype5cpB5852UP/LL9v1vZQKYHny5HE7BK+LioLHHg/CLt5cnQY3w+hJ0PjyUbBsFj8PD+HB6TezdXVlyr/zCrNoxvwiV9OvzVrCmzaE2Fho2BDy5XP7qSjlmjRbvIwxM4AUV2g3xsw2xhx2Nudip2NVXtDzt1t5IOKzbB3flUhKl7JdfpYvh5M5qku78nNa5rjEjfFdnu6/3y5j8c037uSvlBdVqlTJ7RB8rnhx6N4dImuWhS5d6PXrzcyYAeWOroSZM5nU7m1ePPo4ofP/gccfZ1iLr+iV/1tM3Xpw110kfDgU5s6F06fdfipKZRtvT67RG0hxUJDn4oL79+/3ctY5zK5dfHe+EwPuWO9aCJ+MzsPrZx+Hr75yLQal0qBljrdMmwbVqkHp0u7k36YN1Kypk2woFaDy5YMWLUDyRUDz5vzfn03YsT+MkG3/wu7dHLjjIXZUaoGUKwsTJ9L1oSK0a3ISIiOhbl1WdHqe3QM+hunT4ehRt5+OUj7htVGQItIG+yOoeUrHGGM+xnYLIiYmRqfDSc306dRlJXSt5V4MzZtD3bpsfG8CVXrfjQSJe7EolYSWOV6UOL4rO6eRT0rEtno98ADMn2+7JSkVoLZv3+52CH6hcGHnTsmS9B9b0tn4DYyhzZuHObJmF5R/FhYvpufvt1H0lz38QWsAhhR9iejqQVx1FXbijvr1oUIFW1YoFaC8UvESkXrAp8DVxpiD3kgzt/tx1BEKR1xD6wYN3AtChF9avEWnYR2ZNWI5zfrVcy8WpTxomeNlbo7v8tS9Ozz7rF1QWSteKoCdOnXK7RD8mwh9nikCFAHqAPDhbEjYVxry/oZZvIT/+7/7uGnVr1w1p5utqPE3XcIGce/li6F+fXZXaEzJltWQOrUhIsLVp6NUemW5q6GIlAd+ALoZY9zrF5fDvDC9Pe/mf8mV8V2e2r7UgoFhL1F9inb/Uf5ByxwfcHt8V6LISFv5+vpr0K6hSuUqTZtC8xuKwdVXI88/x47jhXhjW1c4dowz0+aSv24l8jS+DOLiOD7yW0o/2ZW3rvgOIiM5W60un14+gm1PD7XL4OzereuMKb+UZouXiIwDWgPFRGQH8BIQCmCMGQ70B4oCw8Q2/8b5wxoaAW3XLuada8jBu98D3L3qm694Pp6+9ygM+xz2vAIlS6Z5jlJZoWWOC9we3+Xpvvtsi9dnn8Ezz7gdjVLKJSEhUKAAQH7CWl3BL8sBKgLd4WgCQwftp1nklXA0jDUzjnHPtHv5euFtlH/rAbZQgefyvsezjf6gbsvCmMsaITGN7KRh2lVRuUgXUPZH48bBHXfAwoXQqJHb0cD69fxdvS+Hu9zHTeNudjsaFWD8ZUFTLXNSEB8PRYrY8V0jRrgdjdWuHWzaZBdUDvL2HFAqJ/OX8iYnLKAcSBISYPNmKBZyhIJbl/PPD3vp+lkbfij1AJdt/p7f49pzH8OYWPBOajctyIkGzQlpdgVhLS5PrN0plSkZLXN0iXE/NGJYPCFh99PbzfFdnqpV49VC73LyxyBuMkavFimVk/jL+C5P99wDt99uW+LatnU7GqUyLEzXostWQUFQpQpAIajQkmYtYcsggK/hzBkKfbWZy4cmUK5WA1g6g5G/7+UJWrBDylO8YRn2NrqGfO0ak79jcyhY0MVnonI6vZToh75dXJmfCnR3fXyXp9EvbGTm2ViYM8ftUJRS3uQv47s8de5sr0J/kdIa2kr5twoVKrgdgkoUFkaTu2oyflEVCowZCitW0OTv13ix+zaKv3gvFCzIKyPLUL5LE+KLREHTpux/8i0SZs+1PQKU8iKtePmbXbv481QzvnnEvyo45ft0JG9ECIwe7XYoSilv8qfxXYnCw+HWW+G77+DECbejUUrlMJe3yc+Lo6vCgAHw9990+/su3n1qH8HPPQ3x8dz+zmW0aXYWoqLg1ls5O3wUbNvmdtgqB9CKl7+ZPh2AiCtTXJrIHZGR/N30Ba4ceRtnjpxxOxqllDckrt/lT90ME/XoASdPwo8/uh2JUhm2detWt0NQGdC4ZR56vVkDXn0V5s3jnk+uoO+DeeCGGzAzZ1G9XxuerTAWqleHfv2IH/s17NzpdtgqAGnFy8+89l44z+V5B/xlfJeHhPZXsiuuONs+/9vtUJRS3uCP47sSNWsGlStrK7sKSGfO6AXKQHbb3ZHcPrgJjBzJuc076XFvOE1714KqVTn65S8UufNqPi/7PFSoQPwtXTg1cLDtPXD0qNuhKz+nk2v4me0bznC0WIxfje9K1O7xBqwYXAH5swE8co3b4Silssofx3clErFreg0YANu3Q7lybkekciARCQNmAHmxv4m+M8a8lMxxrYFB2KUtDhhj/PCfRvlC3jBhwPASQGegM6d3xNH98UPUKn0V7DrN0unHueK7+5jIdXRkMgfL1mdThbbUbxxO3jrRULMmREfb2WNVrqcVL3+yaxfDj94OL74D+F+ZLiHB0O1O4t9+j/Nb9xJWoYTbISmlssIfx3d56tYNXn4ZvvwSnn3W7WhUznQWaGuMOSEiocAsEfndGDM38QARKQQMAzoaY7aJSHGXYlV+oGTZED78pjhwO3A7hf+FZ4ecpF7MM7C1FX/8kp87/nmQZfMaUS/udeZzOb9xDY8UGk2h6Cg7/WLlynZNscRbuXKgM2HmClrx8ifO+C6/7PbjONy5J3XefJAnHl7Doz9pxUupgJU4vqtLF7cjSVnlytCihe1u+MwzupSF8jpjFzNNnMEl1LklXeD0DuAHY8w255x92Reh8neVK8Or7+UDWgOtaX83fD8TanScBzs3M++dM/zfp7V54qYjsHUV70+pw9CDt7GcekRwmuXUZT9RtC22AilfzlbCypaFMmXsRbHEv6VKQaFCWg4GOK14+ZFH3yjO9pCf+M4Px3clKtykBl1KjKXeiunYQkYpFZCWLfPf8V2eune363otWACxsW5Ho3IgEQkGFgFVgaHGmHlJDqkGhIrINCAS+MAYk+paBxEREb4IVQWAqCj43/8AQiA6mgdHQJ/BkDfvIAAq/wytfkogYsBa2LKF4QNKMG52eQ7d8DDs3MFbc1uy8lBpvjh/OwAbqEoezlGBbbZVrFQpeytZ8tK/iRW0qCi/HLKitOLlV0ruXoIpF+33/yzvvnAYHvwElt0P9eu7HY5SKjP8eXyXp1tugQcftK1eWvFSPmCMiQcaOF0KfxSROsaYlR6HhACNgHZAODBHROYaY9Z7piMifYA+AOXLl8+W2FVgyJv3wv3OnaFz5yCgPJQvT/+x0Gs7yOUfA3DmFTi1HPiiE+zcyWM9irB1RzDLH/4M9uzhlT+uIGTPUZ478h5MncqOwxEU5SDheEzoEhwMJUpc3GJWpoy9lS1rW9XKlQO9QJDttOLlL3bv5ukDT8Iz77gdSdq6dOHQo6+yduAMmo7TipdSAcnfx3clKlgQbrgBvv4a3nvv4l8wSnmRMeaI06rVEfCseO3ATqhxEjgpIjOA+sD6JOd/DHwMEBMTk7S7olLJKlnS3hL17594LwKio+n/gTNZYvvHAVizA0JCgDG9Abi+QQKlCp/ht9eXwe7d/N+o0tTIs5mbC06BXbuI37SF4Jkz4dChSzMvWhTK2wogFSrYW6VKdtxZ5cq2/FVepRUvP3FmykzyAuLv3X4AihWjT/EfmTW+KjtGxRESph8jpQJK4viu225zO5L06d7dVrx+/TWxD49SXiEiUcB5p9IVDrQH3kxy2M/AEBEJAfIAVwDvp5bu5s2bfRGuyoUuv/zi7XHjLt5+sX8Q+fJFQJMmAIx+Gq66qjE3D7FdFcuWgrv6wmsvnIadO/lmzDliCqynyrk1dsbYbdtg40b4669LF6wvUsRWwKpWtZOCREfbC3bVqtlKm8qwNH8xi8hI4DpgnzGmTjKPC/ABcA1wCuhpjFns7UBzuocHlmR20EqW169BIAybfPHx0yQ8fhXBf70G1+rU8sp7tMzJBsuW2UuogXChB6BDB3tJ+IsvtOKlvK0UMNoZ5xUEjDfGTBSRvgDGmOHGmDUiMglYDiQAnybpiniJc+fO+TpupYBLi8QNGyAuzt6Pi4O77nLqZOHhHI2qSpdX4I03avHMszdw+rS9/vbQIGjfzmAOHSZh02aCt2+Bf/+FzZth0yY7xvbbb+1Fu0RFi0KNGvZWq5a91aljuzPqBCApSk9TxefAECClgaRXA9HO7QrgI+evyoC2R36kUrUGSEhtt0NJl/oPtIDXt8OYL7Tipbztc7TM8a1AGd+VKCQEunaFDz6A/fvtwHGlvMAYsxxomMz+4Um23wbezq64lMqKkJALf1977cL+/Plh7VooUMBu791r61XHjwMirNtfhMtaF2H8+EZc96Sdf2ndOqhXD/IGnbcVsQ0b7M5162xiEybAZ59dyKRQIVsBq1/f3ho2tNs6XT6QjoqXMWaGiFRM5ZDOwBfOlKxzRaSQiJQyxuz2VpA53u7d3LZ7EDweAOO7EuXJw7br7mPolwV4dutRClXQfsDKO7TMyQaBMr7LU48e8O67tsvhgw+6HY1SSgWc4GCoXv3CdsWKsGrVhe2wMOjXzzZigV3lqFMnmDULmjULZZ2pxj97q3Hz3df+V3kD4MABWL0aVq60t+XLbQ+F48ft4yEhULu27Td5+eVwxRW2Mubnk8n5QpAX0igDbPfY3uHsu4SI9BGRhSKycP/+/V7IOmfY/dM8jhEZON1+HHvbdOG9+IeZ+95st0NRuYuWOVmROL4rwMob6taFBg3s7IZKKaW8rmJFe32ralW73aSJ7WHY0GkT/u036N0bzjgTKE6ebCcDOZ2vGLRsCffdB8OG2ZrakSN27Nh338FTT9nu4j/8APfea8vyQoWgXTt4+WU7vuzUqWx/vm7wRsUruY6cyc7mY4z52BgTY4yJidKuIv8Z8GERKskWEuo1cDuUDInpVpPd0a3ouPh1t0NRuYuWORmQ2NcfYMwYeKnfPhKOBsD6Xcnp0QMWLbr4Eq1Sfih//vxuh6BUlhUrBjfffGHW+Ycftj0Nixe323PnwvDhFyabHTYMnnwSjAGCguyEHDfdZPs7TppkW8Y2boQvv7Tl+eHD8Oqr0L69rYi1agUDBsCcORePJ8tBvFHx2gGU89guC+zyQrq5Rs+TQxlU/3OCQgOryVWChGJ3OW3Qmza5HY7KPbTMScHatRd3te/RAxo1urD9ww+wcu4JgjDQqhV79mR/jFly++22a8oXqa5dq5TrypRJthFeqYAWFHShNQzgpZfsxIhBTm1i/XpYvPjC3BpPPw0DB3okIGIrY127wpAh9uBDh2xT2qOP2lavAQOgaVNb6+vSBb76ylbQcghvVLwmAN3Fagwc1bEWGbB7N423jafbnYG55Ef87XdyK9/wep8tboeicg8tc1LwxhvwyCPO1UbgqqugW7cLj3/9NXxX4XGoVo3dUppKlWDoUFdCzZwSJeDqq+3V0hx6NVQppQKJ59KKgwbBn39e2N68GbZuvbB977226+JFCha05fqbb9rZEw8cgG++ses3TptmK2nFi0PHjjByZPLrkQWQNCteIjIOmANUF5EdItJbRPomTrUK/Ab8C2wEPgHu81m0OdC6cYtZSn0SWrZ2O5RMCa5QltCSRQlasggSEtwOR+UAWuZk3ief2F54iVcb77gDnnjiwuN5Q+KRmXZ8V0QEPPec/S4DO3Pw1KkXKm1+q3t32LXLjglQyk9t0l4gKpfynEl+/Hj46CN7/9Qp24MwcYm78+fh8cftXBwXKVIEbr0VRo2yZf2cOfbADRvsALNSpWz/x4kTL+5LHyDEuPQtGxMTYxYuXOhK3v6kb60ZjFtTn4Nn8hOSN7C6Gv7nyy/tZfUZM6BFC7ejUX5GRBYZY2LcjiOnljkzZ9quHOPHQ758aRy8eLHte/jVV7bbnoeHHrIVtx07/HxdzDNn7BfvtdfaskcpD/5S3kRGRprjiTO6KaX+k5BguyYuX24nNxw3zjZu7d9vh/C2awehocmcaIw9YOxYW/YfOABly9pmtLvvtpN3uCCjZY43uhqqLHgu/lV+vvy1wK10Adx4I+TPz56PfnQ7EqVynd27bVeOdP3G++cf+7d580seeust+OOPC5Wubdu8F6NXhYXZFT9/+MEuMqOUUipgJI4Hq1fP1p2ucZaC/fZb2+Nw/Xq7fepUkh4YIhATA++/Dzt32u+AmjXhxRehQgXo08e2ivk5rXi56fhxym/4i9bXRLgdSdbky0f/Kl9SbdzLnNx30u1olMoVTjr/arfeCkuWpPNi3/z5trWobNlLHgoLu9Bg/dNPdgD1jBleC9e7evSA06eTGSyglFIqUOTLB3ny2Pu9e9uLf7Vr2+3nn7dLfSXbmzBPHnvR/48/7ELOvXvbSZeqV4c777R95/2UVrxctGHCGr42t3KiXlO3Q8myTveV4zWeh59/djsUpXK86dOhcmVbj4IUumUkZ/5827dDkpuR/4I2bWyX+iuuyFqcPtO4sf2CHTnS7UiUUkp5Qd680KHDhe3mze2khiEhdvv99y902rhItWp2HvutW+2g5u+/tytAP/SQX86GqBUvF/301Slu52vO1G6U9sF+LuaehjxYdRL5xn7sdihK5XjR0bZ1qnLlDJx0+LDtwxEbm+ahBQvaGRLz5rXdPYYN87NJN0TsFc7Zs+0c+kr5mQIFCrgdglIB7aabbC9CsN9DAwfa3hiJLpnYtkQJ22d+40bo1ctO2Vu9Oowe7VdfYFrxctEjYcNZUfZqilX355Hs6STC+R538/P0gmydvsXtaJTKkVatst8fpUvDd9/ZZU7SLXFikXRUvDx9+SU88ICd5devdOtm1/TSVi/lh0qVKuV2CErlGBERdjbE55+324sW2e7wyc6XVaYMjBhx4aCePW1T2o4d2RlyirTi5aLQBbOp07yQ22F4zf6ru/M/fmD0ixvdDkWpHGfbNjsh4YcfZjKBxH6JMRmb8O2ee+ypGayv+V7JknZmwy++sPMSK6WUyrEiIqBQIXs/Pt42ZkVH2+2DB5NZ0ahBA5g1y1bC5s6FunXtYpYu04qXS/av3Msr23uyuUp7t0PxmtKNSvFP06d4dmNvXdxUKS8rXhzefttOu5sp8+bZfu8FC2botMSJpMBWwDp0sF9yfqF3b9i7F37/3e1IlLrIhgCYXU2pQBUbC5Mm2a8zY+w8G506JXNgUJCd7XDpUvv9d/vtduyXixfrtOLlkmU/bOJlXmZXmcvdDsWrGj/ejNDd22DyZLdDUSpHCQuDBx+E8uUzcbIxXmm22rPHzuLrNw1MV19t+/Vrd0PlZxIuufyulPKVu++GO+64sH3qVJIDqla1i14++qjtNnLVVXYuexdoxcsl7c/9xpGgosR2jXY7FO+67jpGRT7IM4+edTsSpXKM//s/+PXXLCSwfbttGcpixatTJ7voZcmSti53+nSWksu60FA7tfzEibZWqFQGiUiYiMwXkWUiskpEBiRzTGsROSoiS51bfzdiVUpdSgS6d79Q8fruOzvRYeJ6YP8JCYH33rOTbcyeDc2a2e/GbKYVL7fMn0+B+pUILRDudiTelScPK6JvYuaGEsTv2e92NEoFvDNnYOxY+PvvLCSSOL7LC/PDJ07t+9xz0LZtMlcWs1uvXrZr85gxLgeiAtRZoK0xpj7QAOgoIo2TOW6mMaaBc3slWyNUSqVbxYp2SZQUZ/3t3h3++sterGvRws6CmI204uWChLgEek/vxt9lurkdik+8+WlR/jHNCB73pduhKBXwwsJgxQoYcMl1+AyYP98uOFmvntfiio219biwMK8lmTk1akDTpra7oR9NGawCg7FOOJuhzk0/SEoFqJgYex0uJMReGOzRw05OdZFmzezVzBMnbOVr06Zsi08rXi7YO+dfJp9rw5ZiGZtdLFCENqwDsbGc+2Q0JkG/v5TKrIMHIS7OfoHkz5+FhObPh4YNbeXLS268EQYNsmOXDx6Es272Lu7d267nNWeOi0GoQCUiwSKyFNgHTDHGzEvmsCZOd8TfRaR2Cun0EZGFIrIwJLFpWCnlmpUrbU/0VauSebBRI5g+Hc6ds+OFs2nMV7oqXiLSUUTWichGEXkmmccLisgvHn2ke3k/1Jyj1JY57KAcPR8t7HYoPjOn9bOUWTOFhV+sdjsUFWC0vLng3nuhceNkpsnNiPh4u9iJj+aDP3MGWra0dR/X3HIL5Munk2yoTDHGxBtjGgBlgVgRqZPkkMVABac74ofATymk87ExJsYYE1OlShVfhqyUSofYWNiyxdarIJkZeWvXhl9+sWO9OnXKloHLaVa8RCQYGApcDdQCbheRWkkOux9Y7RRKrYF3RcR7l1ZzmvnzIX9+gmrXdDsSn6l1fxs6BP9N3l9/cDsUFUC0vLlY9+628hWUlb4Jq1fDyZM+q3iFhcF999n1vlwTGQm33grffGO7jiiVCcaYI8A0oGOS/ccSuyMaY34DQkUkI8uXK6VcEhlp/y5YAJUqJTPpdtOmdiD13Ln2CqKPu6yn5+s8FthojPnXGHMO+BronOQYA0SKiAD5gUNAnFcjzUHu+vpKPiz5GgQHux2KzxQsX5Cv7viVen+84wej71UA0fLGQ6dOXqjQJE6s4cMVkO+/H1q1sveXLHFpqFXv3rbS9e23LmSuApWIRIlIIed+ONAeWJvkmJJOeYOIxGJ/O6W6mt26det8Eq9SKnOqV4ebb7a97i/xv//Bq6/CuHHwpW/nJ0hPxasM4Dnf4g5nn6chQE1gF7ACeNgYc0nnGM/+z/v3584Z78yZs+w+mIfDJWq4HYrv9e7N3mNhrPrgT7cjUYHDa+UNBG6Zs3ixXWrEK+Om5s+HQoXsOiY+tny5rd8NHuzzrC7VtKn9ZtXuhipjSgFTRWQ5sAA7xmuiiPQVkb7OMTcDK0VkGTAY6GKMzuSiVCApUMB+PRQvbi8Obt6c5IBnnrH95u+/P5kHvSc9FS9JZl/SAucqYClQGjsd6xARKXDJSR79n6OiojIYas4gy5fxu+lI/0ePux2Kz5kWLWkd+g/3v5mZFV9VLuW18gYCt8wZP97OYnjunBcSS1w4OUv9FdOnbl074UYvN0bdicBdd8GsWcks4KJU8owxy40xDY0x9YwxdRKnijfGDDfGDHfuDzHG1DbG1DfGNDbGzHY3aqVUVrz0kr1Wd9F8GsHB8MUX9ruyWzc7s5UPpOebeAdQzmO7LPZKs6dewA/OtKwbgc1ALmjSyYRs6PbjLyRIGHLnPD46enu2TtWpApqWN8Abb8DSpRf6pmfaqVN2LvpsKm9E7MXCAgXsd9Zff2VLthd062a/PLXVSymlVApuuQUefRSKFEnyQIUKMHQo/POPz75H0lPxWgBEi0glZwB7F2BCkmO2Ae0ARKQEUB3415uB5hQPDqnOnWHfQdmyboeSLdq90oqaQeth1Ci3Q1GBIdeXNydP2gqMV4qIJUvsrIYuXOh5+23o0MHO7ZFtSpWCa66B0aN9drVSKaVUYKtbF556yjZuXdKz5I47bHPYgAE+maMgzYqXMSYOeACYDKwBxhtjViXp//wq0FREVgB/AU8bY7JnQvwAE3VgDSXKhNhfVrlB2bKsa3YXz3xQivhz8W5Ho/xcbi9vpk6F8uXt7EteMc9Zjujyy72UYPo98ojtMlkr6ZyUvta7N+zZA5MmZXPGSl1Q5JJL6Uopf7NuHdSocaEzGmB/nw8cCLt22cHWXpauFf6c6VN/S7JvuMf9XcCV3g0tBzpyhP4HH4bHXuPSidpyrhWX38WgmQ25/dO51L+vmdvhKD+Xm8ubqCi49lqok3QVocyaP9/W5EqW9FKC6RcebmeQAvvldvw4xGTHmvHXXGNHT3/2GVx3XTZkqNSlAmlMqVK5VenSULmy7RhykRYt7HfJwIHQpw8U9t66u74fba3+kzB/ob2TC8Z3eer08mXsLlyb+lMHuR2KUn6tTh07tjc83EsJJk6s4SJjoEcP6NkziwtBp1doqF0AbeJE2Ls3GzJU6lIJ2fJhV0plRWQk/PknNGmSzINvvAFHj8Jbb3k1T614ZaOBbwdTiX85Uyc7Lvv6jzyReSncoxP8/DNmX+BM6a1Udpo4EbZvT/u4dNu/306Je8UVXkw040Tssig//pgtEytad91lx3iNGZNNGSp1sQ0bNrgdglIqnc6eheHDk4z3qlcPbroJPv7YS1MMW1rxyka1j86mU6GZhJUs5HYo2e5s93u4/vz3vNV9pduhKOV3zpyBLl3g//7Pi4kmDhTzgxb2qlUhOtre/+ILOJjq0rNeULMmNGsGH32UTB8SpZRS6oIZM6BfP5iQdCqvXr3g0CH47bdkz8sMrXhlF2PovO1DPrg+dy4mnLdhLQqUjCBizl9evXKgVE4QFgbLltn1G71m/nzbxHTZZV5MNGu2bLHd5QcNyobMHnkE/v0XfvklGzJTSikVqNq3t3NRJY5L/s+VV9oxw17sPaEVr2xyZuMOTu095nq3HzeN/ewsDx57Db791u1QlPI7VapApUpeTHD+fKhdG/Ln92KiWVOxol3f+KWXsiGzG26wa7K8/342ZKaUUipQiaTQOSQkxE4v/8svtuXLC7TilU0mjthJAY6xokgrt0NxT8eOmGrVmf9/f2ASjNvRKOUXDh6Evn3Bq0NCjPGLiTWSExNjv8uOHoVXX/VhT8CQEHjoIduHZPFiH2WilFIqpxgwAPr3T7Kze3c4f96uj+IFWvHKJrUO/8OzQW9R7dpot0NxT1AQ41t8yBVrRzNz6HK3o1HKLyxdaiefOHHCi4n++6+t0flhxSvRzz/DK6/AwoU+zKR3b9vip61eKpsVK1bM7RCUUhm0ZQts3ZpkZ4MGtvfIF194JQ+teGWTWpt+4dWYn8lbIK/bobjq+oHN+DjiEWL+eN3tUJTyC+3awb59tmz3msTVIP244tW9O6xe7ePe1wUL2srX11/Dzp0+zEipixUtWtTtEJRSGTRyJIwenWSniP3CmjMHNm7Mch5a8coG8efiWTn/FPExuXd8V6KIYhHc80g+In79FjZtcjscpVxlnB63ERG2bPea+fPtYmBeW4nZNxJnOpw6Fd5910eZPPSQ7c84dKiPMlDqUnFxcW6HoJTKoMTv4dOnkzyQOOvG5MlZzkMrXtlgza//Uvf0fL6Kv9XtUPzD/ffzQ9DNDOm9xO1IlHLVe+/Z2ZQuKeSzav58aNTIjnMKAF9+CZ9/7oPXAaByZTvRxogRcOqUDzJQ6lKb9MKiUgFp9GgoUSLJsieVKkHZsjBzZpbT14pXNii9fR5f0I12XUu5HYp/KF2aH8s/xMiZVUk4fNTtaJRyTYECUKyYbZzymvPn7WQSftzNMKnhw+0cGF59HTw9+qidkcpLffRVziEiYSIyX0SWicgqERmQyrGXi0i8iCSddFoplUNcdhncc49dX/M/ItCihf2iMlmbHE4rXtmgyOpZdCs0kdLNvDlXdGD7cFQkCxIaETTyU7dDUco199xjhx951YoV9hsjgCpeoaFQuDAkJNiegb/+6uUMmje3LYCDBtlMlLrgLNDWGFMfaAB0FJHGSQ8SkWDgTSDrfY2UUn6rbl3b9b1MmSQPtGwJu3dneZhMuipeItJRRNaJyEYRSXaJTxFpLSJLnStG07MUVQ7z55+wp96VdjFTBUChVvUJbtmc+A+GEH9W+8KrC3JLebNzZ5YvnCUvACbWSMmpUzB7Nsyd6+WEReCxx2DdOpg0ycuJq0BmrMQ5RUOdW3L/mQ8C3wP7sis2pZQ7jIFt25LsbNHC/s1id8M0awLOVZ6hwNVALeB2EamV5JhCwDCgkzGmNnBLlqLKQU4fPEXHTUMYEt/P7VD8zpauz1Nt+5/88OwCt0NRfiK3lDfG2Itn3bv7IPH5823/xYoVfZC4b+XPb3tyvPqq3fZqxfSWW+wlTJ1aXiUhIsEishRbqZpijJmX5PEywI3AcBfCU0pls4ED7bCuY8c8dtasCUWL2i+pLEhPE0wssNEY868x5hzwNdA5yTF3AD8YY7YBGGP0ipAjdOUS/qEZd3XXVp2kyvVsR2y+1RSbPNbtUJT/yBXlTXw8vPSSDytesbFeniYx+0RE2L/bttnegYkNeFkWGgoPPGC7IKxY4aVEVU5gjIk3xjQAygKxIpJ0OtBBwNPGmFSX+xaRPiKyUEQWhoWF+SZYpZTPXXcdfPRRkq/RoCDbbd3XLV5AGWC7x/YOZ5+nakBhEZkmIotEJNmfE56F0v79+zMXcYAJWTyfK5hP5U7+Pa2zG4LzBDPujS20WT0U5s1L+wSVG3itvAH/LXNCQmylq0MHLyd8/Hg2LI6VPUR8UHfs08fW7AYN8nLCKicwxhwBpgEdkzwUA3wtIluAm4FhInJDMud/bIyJMcbEVKhQwbfBKqV8pm5d+3URGZnkgZYt7RivXbsynXZ6Kl7JffUl7QASAjQCrgWuAl4UkWqXnORRKEVFRWU42ED08w/xzClxA5Qs6XYo/qlXL04WKMXkp/5yOxLlH7xW3oB/ljlxcfDVV7aO5HWLFtn+eQE4viupcuVg4cILT+WoNyZALVIEevSAsWNh714vJKgCnYhEOd2XEZFwoD2w1vMYY0wlY0xFY0xF4DvgPmPMT6mle+7cOZ/Eq5TKHocP2zHHF/HCOK/0VLx2AOU8tssCSat6O4BJxpiTxpgDwAygfqajykEem3sL74U85XYY/it/fl6rOYZrZzzFrgU73Y5GuS/HlzczZkDXrjBlig8ST+yXd/nlPkg8+yW2eI0fD1Wq2Ma8LHv4YTh71vYjUQpKAVNFZDmwADvGa6KI9BWRvplNdPPmzV4LUCmV/QYMsOtsXnQNpWFDyJcvS+O80lPxWgBEi0glEckDdAEmJDnmZ6CFiISISARwBbAm01HlFPv2sSCuIe90X+52JH7t/sE1mB7UllLfDHI7FOW+HF/etG4Ns2bBNdf4IPE5c2wNpWhRHyTunthYuP56L80XUr06XHstDBuWZKEWlRsZY5YbYxoaY+oZY+oYY15x9g83xlwymYYxpqcx5rvsj1QplZ3uvRd+/z3JhOQhIdC0KfzzT6bTTbPiZYyJAx7Arl2xBhhvjFnleTXIGLMGmAQsB+YDnxpjVmY6qpxi+nSKcJgKnRu4HYlfKxNbhmY3l0I+/QROnEj7BJVj5YbyJigImjUDr4+9T0iwV+FatvRywu6rWBFGjbLDs86ehQ0bspjgo4/C/v22z6dSSimVRM2a0KqVrWtdpGFD2/3i/PlMpZuuhaWMMb8ZY6oZY6oYY15z9l10NcgY87YxppZzxWhQpqLJYT7/6DRf5u1tl8FWqYp78FH6H32MUX3muB2KcllOLm/++ANefhlOnvRB4itWwKFDtkktB7v/fltxPXIkC4m0bQv16tmp5XVBZaWUUslYvhx+/jnJzjp1bKVr/fpMpakr+vrQ53NrMDayr53GWKUqpHljphfoxKKft/voV6lS7ps9Gz75xAetXQBTp9q/bdr4IHH/8cwz8O67UKhQFhIRgSefhJUr7QAypZRSKok33rDDgi9St679uzJzHW204uUre/Yw9fQVfPNQ5vuB5jaTfzrNkFO94b333A5FKZ94+WXbTS442AeJT5tmx3eVK5fmoYGsalXo1s3eX7TIjpfLlNtvh/r14fnnk4yeVirrSupMxkoFvNdeS+Y7pkYN+yWeyfUgteLlK9OmIUCBjk3djiRghLVpAv/7HzsHjuHgWv9Zc0kpbzDOpPiJCwR7VXw8TJ+e47sZejLGXom891779DMsOBjefBP+/ReGXzKHglJZUrBgQbdDUEplUeXKULZskp1hYRAdrRUvf/Pm+3kYkPc1OwhPpduRZwZS89RCBty2yu1QlPKqm2+GZ5/1UeLLltlBTzm8m6EnEfjhB5gwIQstiFdeCe3awSuveGmhMKWsMzpjplIBLy7OTux0yXpedetqV0N/s3atYUXh5KZDUakpdHk0g1v/yKOr7vHC1GVK+QdjoESJLI5LSs20afZvLqp4ARQvbntXgu3GOWRIBhMQsa1eBw/CW295OzyVi23dutXtEJRSWRQcbHtWfP11kgfq1rW9JTIxE7dWvHxh1y5GHbuZbx+f63YkAannuKuoFLbbjr1QKgcQsctGPf20jzKYOhWqVYPSpX2UgX+Lj4elS2HJkgtdOtOtUSM73uv992GnLuKulFLKEoFVq+zXw0Xq1LF/V2W8d5ZWvHzBufosbXPX1WevKVmSA/1epMe31zJ/lHY5VIHv2DEfJh4XZ9fvykXju5IKDobvvoMRI+wX5ZEjGZwl/rXX7Ov48ss+ilAppVQgKlcume7sWZjZUCtePvD4G8W4M/QbO2OWypS8j97HtKC2LB/4WyYuYSvlP+LjbXe4557zUQZLl9qaXS7rZphUSIi9nT5tX4p7783AyZUq2QXCRo60C2MqpZRS2FEvzz8P+/Z57Kxc2c6UlYkJNrTi5QMFd66mcNkIH80ZnTtElo5k/bsTuXv9U/Dbb26Ho1SmnTtnl4xq395HGSSu35WLW7w8hYVBly52MpMMef55yJ/fLhSmlFJKAbt326HAa9d67AwKgtq1tcXLL2zfTv/Dj/LhQxvdjiTg5b3/boiOZtnDI4k/l5n5opVyX3g4PPUUtG3rowymTrXriui6QYDtavj003DVVXb7xx9h+fJ0nFismK10/fILzJzp0xhVzleqVCm3Q1BKeUHTpnDyJLRsmeSBOnW0xcsfnP9zur2Ty7v9eEVoKPN6DafBpu8Z0y/pXJ5KBYbZs+H8eR8lfv68rSRoeZOs8+dta2O6p/F/+GEoU8bWlLWLs8qCAgUKuB2CUsoLQkIgb95kHqhbN0n/w/TRipeX3ftGBRoHL7gw8E5lSezTbfiwwjvc+HsfOHXK7XCUypB//4VmzeyMhj6xeLGdzlYrXskKDbX10lGj7Pbp02ksthwRYdf0mjvXLhKmVCad0u8rpXKMr79OZlbiTP7OT1fFS0Q6isg6EdkoIil2gBeRy0UkXkQy2rs+x2h1+Gc6V19r+3+qLJMg4YEvYim4ey0MHux2OCob5KTyplQp29Utw+ON0itxfFerVj7KIPCVKmXX+zIGevSAzp3TmPGwRw/bd//ZZ33YVKlyuu3bt7sdglLKS5YsgYkTk3SEqFMHqlbNcFpp1g5EJBgYClwN1AJuF5FaKRz3JjA5w1HkFFu30uPAuzzb97DbkeQsLVuyqtV9XP9iAw5uOOR2NMqHclp5Ex4ON9xge6/5xNSptpJQvLiPMsg5ROwEJ+3apXFdLDgYBg60U1l98km2xafcISJhIjJfRJaJyCoRGZDMMZ1FZLmILBWRhSLS3I1YlVLuGDjQLtkl4rGzZEn7PZFB6WmWiQU2GmP+NcacA74GOidz3IPA90DGOzzmEHt/msNpwnR2MV949FEWx9VlzQtj3Y5E+VaOKW+OHYOPPoL9+32UwfnzMGuWdjPMgD594NFH7f0FC+D771M48Npr7UjqAQPg+PFsi0+54izQ1hhTH2gAdBSRxkmO+Quob4xpANwFfJqtESqlXHVRhSuL0lPxKgN4tpnvcPZ5BCRlgBuB4aklJCJ9nKtFC/f77NeIe576sCxVg/7F1Krtdig5Tu3OVdnS6xWa//CYHdeiciqvlTfOsa6VOdOmwX33JZmC1psWLLDjHvVCT6a8+aadeOPs2WQeFIG337YDp9M9M4cKRMY64WyGOjeT5JgTxvzXyShf0seVUjlbXBx07w7jxmU9rfRUvJKr5yUtdAYBTxtjUp3z2xjzsTEmxhgTExUVlc4QA4Qx9Dr+IW80+g4J1vFdvhD6zhuY4iX45vovOXVABy7nUF4rb8DdMuf66+1avE2a+CgDHd+VJWPHwh9/2Nmq4uNhzZokB8TGwiOPwNChMGmSGyGqbCIiwSKyFNuCPsUYMy+ZY24UkbXAr9hWr+TS+e9Cz3kdH6hUjhESAsuWwa5dWU8rPTWEHUA5j+2yQNKsY4CvRWQLcDMwTERuyHp4AWTzZlrvG0/3Hlrp8pkiRVje/zu67HqPj2/83e1olG/kmPJGBGrWtAW2T0ybBvXq2fWnVIblzXthXPSQIVC/vu3Df5E33rBj6Hr1ggMHsj1GlT2MMfFON8KyQKyI1EnmmB+NMTWAG4BXU0jnvws9FStW9GHESqnstmwZPP541tNJTy1hARAtIpVEJA/QBZjgeYAxppIxpqIxpiLwHXCfMeanrIcXONZ8tYQ11MC01vEWvlT/3sb8ffMwHpx1K/yula8cKEeUN4sW2bFEe/f6KIOzZ+Gff3R8l5d06wZvvQW1nGlc/ptyPizMNo0dOgT33KNre+VwxpgjwDSgYyrHzACqiEiqVzzy58/v1diUUjlDmhUvY0wc8AB29rA1wHhjzCoR6SsifX0dYKB4fWQJWssMe4lb+VSbMXcRXKcWx3o+xKH1ehU6J8kp5c2yZfDZZ/Z3u0/Mn28XpdLxXV5RpIjtVSgCe/bYCth/vQvr14fXXoOffrqwIJjKMUQkSkQKOffDgfbA2iTHVBWxw+tF5DIgD3AwtXRPnDiR2sNKqQDz/ff2WmdcXNbSSVcnGGPMb8BvSfYlO7DdGNMzayEFIGN45dST9Gx5DRL0otvR5HxhYZz/fCyxMXmp02Y93+0o6t0pZ5SrckJ5c9dd0LVrCqvde8O0afYzr+O7vO7sWShbFipU8Nj52GPw22/w8MP2Na9SxbX4lNeVAkY7S1QEYS/2TEy80OOUPTcB3UXkPHAauM1jso1k7dy508dhK6WyU3y8vR05krUe/pJG2eEzMTExZuHCha7k7XUbN0J0tJ07um/AXJQPeKNum0T18a/Q9NPe0Lu32+GoFIjIImNMjNtx5Kgyp21bW/rrDJ8+99JLtgXstqbboW5duzFjhg8H76ms8JfyJjIy0hzXpQiUyvEyWuboTBBeMOfTVfxEZ+Jb6niL7NRr3JU0bRMGDz9M/PpNboejFADDh9tloE6f9lEGZ87A7NnazTAbnDtnuxzOng2UK2cvrs2ZYyfdUEoppTJIK15e8NE3RegXNIKgGtXcDiV3CQqC0aMZnHA/bWOOEXcmix1vlfKCxF6v4eE+ymDePNsfTifW8Lk8eWyla+BAu72q3u28Wnc8Z19+w46zU0oplWtcfbVdAzIrtOKVVcbwyZluTLv6LSRIxxllu3LlKHFPJ0oc38DpV99xOxqluPde+PVXH2Ywdaq96NCihQ8zUYmCgy9Uon/6CQbtuInjJaPhzjvh5ElXY1NKKZV9ChXK+kVVrXhl1fr15N2zleqda7gdSa512wfN+OaOCUS++YJtDVDKJadPZ8OM41OnQsOG9htAZavnn4dVq4MoNvYDzIaNvNfhN/btczsq5Y/KlSuX9kFKqYAybhw89FDW0tCKVxb9/uFGBvI055u1djuUXE2GDmF3iQbce+VmTuzRaXyVO+69F5o29WEGp0/D3LnazdBFJUsCrVuzptdbPDOnM9/2X+F2SMoPRUREuB2CUsoPacUri/6cYhga/BAhNaq6HUruVqgQ65/6lLHHrmPp9S/aMTBKZbMOHeCWW3yYwZw5dsYHrXi5rtZHD7Ki5m3c82UrWLCAyZPt3BtZXeNF5QzHjh1zOwSllJd9/z1UqgQHsrCErFa8ssIY3j16N2tv6a/ju/xAq4cbsPmDX2i+cBDcfrv+AlLZrls3u+STz0ydagcdNW/uw0xUuuTNS/U/h5KneCHo2JHxIw7zwQduB6X8xe7du90OQSnlZSVK2F4tWbm2rxWvrFi7FvbuJV/7Jm5HohxRD90Ogwbx249n6Ft7BglxCW6HpHKJNWuyYa6FadOgUSMoUMDHGal0KV0a/vwT8ubl0zm1mfHFFkJC4Px5uPVW20CplFIqZ2jeHMaOhTJlMp+GVryyYNSAbdzFZ5xu0tbtUJSnhx9mSdsnWLC+IMfvfyYbZjtQCm66yd585uBBO3mMdjP0L5Urw5QpyPlzFL+tDezcyb//2qF4Bw/aQ+LjtRhSSimlFa/Mi49n+x+r2VawLuG1KrkdjUriuSltmPXgeAp+/Dbmxf5uh6NyOGPgww/h2Wd9mMnHH9umlDvv9GEmKlNq17YrLR88CB06UL3IfjZssAtpAwweDE2awPHj7oaplFIqa5o3txNpZZZWvDJrwgT6H36MKZ9sdTsSlQwJEsI/GEjcXX3o9VoV3rlumtshqRxMBNq1g1atfJTBuXO2ZtehA9Sp46NMVJbExMAvv8DmzdCxI3nPHP1vMe2SJaFGDYiMtNsLF+r8P0opFYjatoXLL8/8+emqeIlIRxFZJyIbReSZZB7vKiLLndtsEamf+ZACw7Y3xkKFCsiNN7gdikqJCPLRME6Xq8bpX/+CTz5xOyKVDoFW3uzcCS++eKFbmU+MHw+7d8Ojj/owE5VlrVrZaa+WL4frr4dTpwA718/nn9tDjh+H9u3h/vvdC1P5XoUKFdwOQSnlA6+8Anffnfnz06x4iUgwMBS4GqgF3C4itZIcthloZYypB7wKfJz5kPzfwi9WU3HBeH5sMxhCQtwOR6UiOE8w49bH8OLVi+Deezn35Xi3Q1KpCMTy5s8/YeBA8Nns0cbA++9DzZpw1VU+ykR5zTXXwJdfwqxZdtDfuXMXPZw/P3z33YU69Pbt8MgjsGNH9oeqfCcsLMztEJRSPmJM5sftpqfFKxbYaIz51xhzDvga6HxxAGa2MeawszkXKJu5cAJDhZ8H83KeN2j3amu3Q1HpEBSWB777jn9jbqVWt8v4/cXZboekUhZw5U2PHvbHcyVfDfWcORMWL7a/zoO0d3hAuO02GDHCjvvq2vWifoUitsWrdm27PW+ePfT8ebu9d+9/DWUqgB09etTtEJRSPjByJISFZb6XS3q+xcsA2z22dzj7UtIb+D25B0Skj4gsFJGF+/fvT3+U/mTnTqImfEb/+w5QoKxO6RwwIiIo9sPHVChwmPL/dw/072+nGlP+xmvlDfi+zElcKq5kSa8nfcF770HRonaRMBU47rkH3n3XNm81bw5bkx8PfPPNtrKVWHF/9lmoXl2XIcwuIhImIvNFZJmIrBKRAckck+HuzXv27PFNwEopV9WpY6+DSiaX701PxSu5pJNtYBORNtgfQk8n97gx5mNjTIwxJiYqKir9UfqRr/rNZFZ8E3joIbdDURlUoGwB/txdh9o9Y+HVVxld/z0OrPPlwByVCV4rb8C3ZU5cHNSrZ+tFPrNxI0yYAP36QXi4DzNSPvHYY/Djj7B+PVx2mW0BS4bnsmx33QUvv3yhF/ujj8JPP/k80tzsLNDWGFMfaAB0FJHGSY7xq+7NSin3xMbCm2/a66GZkZ6K1w6gnMd2WWBX0oNEpB7wKdDZGJMjf80mHD/JS79ezqDSb/qwX5HyJYkIh5Ej2fHmWPqueoB3Lv/G9vVR/iJgypuTJ6FFC4iO9mEmg51xpPfd58NMlE/dcIOdxrBsWTv+a8AASEh5YffmzaF3b3v/5EmYPBlWrLDb8fHw2WcQqB1G/JGxTjiboc7NJDnGr7o3K6XclZBwyfDddEtPxWsBEC0ilUQkD9AFmOB5gIiUB34Auhlj1mcuFP8XNGY0yxLqMnioTqgR0EQo+9QdzBu3mZcLfwAtWnDs3U8wCbrCqR8ImPKmYEE7Nuf6632UwZEjtjP57bdDqVI+ykRli+homDPHdhd9+WW7wFc6BgjkywerVsHTTpvu/Pl2Nq2//7bbJ06A9mjLOhEJFpGlwD5gijEmtatxqXZvVkrlbOfPQ0SEnVQrM9KseBlj4oAHgMnAGmC8MWaViPQVkb7OYf2BosAwEVkqIgszF47/MvEJMGgQEZfXoXSnGLfDUV5Qr0stwpbM4Wy7a2j7REPur/GXvcSsXBMo5c3atbb3mE998on9POoU8jlDRISdU37ECFtzuuwyWLAgzdNEIE8ee79xY1i2DK67zm6PHw+lS9vPI8Dp05mfaSs3M8bEG2MaYFuyYkUk2cXy0ure7Dmm9HzibClKqRwlNBSee872TsgMMS6V0jExMWbhwsCpn/3y4nze+L84vhlygHL3d3I7HOVFCXEJvN5xBnX/GkTn2hvhhx+gWjW3w8oxRGSRMcb1qxXeLHNuuQWmTbNreCX+KPaquDioXBmqVr3QvKFyjoUL7awau3fb7qR9+mRqpPamTXb812OP2dOfeQa+/ho2bLA/DhISct9EmFktb0TkJeCkMeadJPvrAT8CV6enpb1evXpm+fLlmQ1DKRUgMlrm5LIiOfMSfppA3rxQstfVboeivCwoJIgX/mxN5z/uh717GVX3Pfq3nMb5wyfSPlnlSkOG2B+4Pql0gV2Ed/t2be3KqWJiYNEiaNsW+va167MtW5bhZKpUgccfv1Bna9YMevWylS6ws9p36XLheG0Nu5SIRIlIIed+ONAeWJvkmAx3b87js8JBKeW2hAQ4dChz52rFKz2WLqXzyteY+sosQiNC3Y5G+UqHDrBkCYvK38D0mUJIjaq2W5DO66ySKFEC2rXzUeLG2KkSo6PtWCCVMxUtCr/+CoMG2Rawhg2hZ88sraR8/fXw0ksXtmNibI/GRI0awfPPX9jW3nAAlAKmishy7BjTKcaYiVnt3nz48OG0DlFKBaj77oOaNTN3rla80mHxiz8SHxFp12VROVvZsgzZ0JHJ08ORatEc7fsULQssZdbAWXq5WHHwoG1FWLPGh5nMmWNnUdAFk3O+oCB4+GHbZ/CJJ2wzanS0HUDghQV4n34annrK3o+Ph1atLvxYOHMGihWDDz+02wkJsG9flrMMOMaY5caYhsaYesaYOsaYV5z9w40xw537dxtjChtjGji3NLsV7cuNL6ZSucQtt9jlYDNDv9XTsGfZXppMfI6Xa42HwoXdDkdlk7CWsTBjBtsH/cD++MKEP/swtG6NmZ/2YHiVc61YAX/9leps4Fn3/vu2rOnRw4eZKL9SuDC89RasWwc33QRvvGHH9w0Z4rVmqeBg+9G68067ffq07eXYoIHd3rDBtuR+9ZXdPnoUpk6FU6e8kr1SSuUY7drB/fdn7lyteKWh2PhhjOVOer1Zw+1QVHYToc7D7Vh1rDyNhvaGNWt49oq/6FlpOixe7HZ0ygWtW9sJNWrX9lEGW7bYyV369LFziavcpUIF+PJL2/Wwbl148EH7YfvyS9tE5UWFC9tFQFu0sNsFC8I770DTpnZ7xgw7BC2xqFu1Ct59N/PjGpRSKqdISLBLeWRmImyteKXm9GlCRgzl5s7nqdy2otvRKJcE5Q21HXo3biSydQxB27fawRING/JLn184tEn78ucGiT848+b1YSYffmi7nz3wgA8zUX6vUSPbtDpxop0po1s3u5bbAw/47KJPyZJ2oo6KFe12y5bw++82FICZM21vyMQGuK++sld9jxyx24cP23XFlFIqp1uxwhbJv2diRT+teKXi+0dn8dHBW4h/SGcWU0CBAjw/tT2f7bsehg7lQEIRbvzkat6q9il06YL5YwoJcb7sg6bcYoxtGejd24eZHDtm1+669VYoW9aHGamAIGInV1mxAv78E665Bj799L+LPnz4oU+bnwoWhI4dITzcbvftC/v32+6IiRIS7HEAr78OUVEXuuH+/DMMHeqz8JRSyjWVK9ue4IldtTNCK14p+eMPZn6+iU/DHyKodUu3o1F+RIoUhvvuo9iyv1j09UYe6HEc/viDRVc9S6WwXSzs87Edq6GTceQYcXHQrx907uyjDA4etKN1jx/XKeTVxYKCbNPS2LF23a+hQ+2+hx6yl1y7dIFJk7zeFTE5xYpduH/HHXYMWOJU9jfcYCdoTJwP5rvvLkzcAXbCxmuuubA9YULmrhYHiipVqrgdglLKRyIj7RivqlUzfq5WvJIwCYbD/d+Hjh15s8rHfP97BBKU8YUtVe5Q/7YalB35CuzahXntDeoW3kn0J09BjRp8H9WXu6rN5MTI8bB3r9uhqkw4fRrmzrW9vR54ADr5Yu30JUvsvN/TptkWjRjX15pW/qqwvejDokX2c3PvvfDHH3D11VCkiF0P7O237WM+nQHmUs2a2XASffEFLPCYi6hRI7jiigvbr79ux4wlat8e7rrrwvaIEXa2/URHjwbWtayQkBC3Q1BK+dC+fbB1a8bP05LB0/Hj9K47n2VbWzL75jvI+/kIKuoAd5UeYWFc/lwHJj4HbFsOv/3G9o/yMn9lMfL1ti2mH5Z+g11lLueNAedsv7X8+d2NWaXp4YftDN9bttjftV43ZoydSKNYMTuIJjbWB5moHKlBAxg82M6G+OefMGWK/Zs4f3yxYralrH17e0scvJVNROxV4UQPPnjx43/8YRt4E7VqdfHEwa+/Dm3aXFjKrnZtW6/87DO73bOnnfyje3e7PXEi1PCjObAOHjzodghKKR+68cbMjfkW49IlpJiYGLNwYZprEGaftWvhxhuZsL46m657hEd+bKUtXSrLTFw8snQJ/Pkn9w+pyaZd4UwyV0FQEPcW+IpipfLw2p1roH59DldoQKFapXPc505EFqVn3RtfS2+ZY4ztWhgaateyXbnSjnXxqnPn7EwGQ4bYX5zjx0Px4l7OROVKu3bZiTn+/NPedu2y+4sXh3r1oH59e6tXzy7qlSePu/GmIC7O9p5MvD41bBhUqWIrX8bYhuFbb7VrlcXH26fx/PPw6qv+Ud5ERkaa4541S6VUjjJ5MoSEQPv2GStztOIF/PTsPM4PGsotkZPgm2/sZTalfMCcOo3M/gdmzODu0S2IOrqBN47axSCqsJEWeebzedOPoV49Rh3sRP2YUC5rV9hOM12ggMvRZ04gVbyMsVfQRWxXKZ/Ys8eO55o1Cx57zM7prd2SlC8YYy8q/vWXnQ1x+XJ7JeHsWft4SIitfNWvD7Vq2VaxChXs35IlA2YB74QE+9SKFIEKFfyjvNGKl1K5Q0Z/46Tr215EOgIfAMHAp8aYgUkeF+fxa4BTQE9jjP8vdBQfT8KLL/HewCsJjnyImxe+hpQv53ZUKgeTiPD/uv58+gpABzjaFbN8BU8M3U6Fowfg8GniPhnFPaff5emxb3IZLxBPEKVlN8+X/pyHLp9DfPlKDPq3E+2vOE79RiHEFy3OzviSlKhZhLyFwt1+mlniZnkjAtWr27/GXJg4wGvmzLEL5B49CuPG2YkRlPIVEVuxqlnzwr64OFi/3tZUli2zf6dOtWuFecqTB8qXv1AZq1DBtpoVL26nL4yKsvcLFfLBP0rGBAVlbnYxpZTKrGPH7MLzGZVmxUtEgoGhQAdgB7BARCYYY1Z7HHY1EO3crgA+cv76FXP8BPLvJo6t2MqIcQVou3ccjRZ9zA9dT5B/yECkUJjbIarcqGBBpEVz+rUAaA08SHCCYefqAwTt6AjHojmzfic3f72G6PATsH49uyev4onT7/HRxL7UZwS7KUMFdjCCPvTJP46dhetw46FP+b/qX3JlpQ3sDinHW+s60+uK1dSLPs2h4CimbK5Kq5iTlCwTzAny8++hQlSJDiJfsXDi8kQQFxpO3gJ5s7XroxvlzcmTMHCgnZWtUSN44YVMh3+xuDjYvh02bYKNG2H1ahg+3P6YnTTJdvVSKruFhNjWrVq1Lq74nzgB27bZAY1bt9q/ifcnTkx5gqCQkAsVscKFbct8gQJ2nvnE+4nbkZF2fvqICHtLej88HIKDs+FFUEqprJk4Ebp2zfh56WnxigU2GmP+BRCRr4HOgOcPoc7AF8b2W5wrIoVEpJQxZndKiUZva8CfT0yifW17yE+Ly1Mg/Dxta9rt7xdWoFjkGVpVt4X9twsqUrLgaVpUs9tfz61IucInaFZlDyQkMOqfaKoWPUKLyjshIYEh0+sSU3Qzjc/N4OT6nVSdP5YnEt7icd4DInmKY7yX/28ajRhBsT59MvaqKeVjEiSUqBMFdaKARuQDhr4A0Ap4hTIJhqO7jhF86Ek42YPIzYf4ZPJMWhRtBCYf5zZDkVmnyXvmKKxZw94Dx/ls3wDaL32bevzGWprQhdlM4ipK8geLaElrpvMXbWnLVKbSniuZwiya0SzPQiYHXc0dZ0fyV9HbaJB/I1POt+axA8/xfZWnqBa5m79ONub1nd35vO57lCtwlGlHGvDR1qv58IqxGX3qPilvAK4/cABGjQLgyKk87DgUQZ2yR8gbL3z64a2cWbiJRrem0hXRGNunKaXb+fP2h2tiRWvLlgurzYIdhdupk12ry3MWAaX8Qf78FypkyTl7Fg4csFN57d9vb0nvHzliLzYcO2ZbdY8etRcgMiIkxLa25clj/2eS3g8NvfA36c1Px6sppXKeVq3gp5/sRduMSE/Fqwyw3WN7B5deXU7umDLART+ERKQP0AfgMhbywbu7aI+dP/ZFllON9bR1tp9lHTEspJWz/SSbac00Wjjbj7GT6/mFZvQF4AkOcAdf0YKHAHiG4/RkNY3L/k2+KlW4ucZKasfGwjXjKVC1KkejjlGg7CvpePpK+R8JEgqULQBlCwBVKNgE7r4DoAUAlYBJANhuxw2AYwAJv8CJEzTce4yVqzdSvuDrIM9Ra3cc3y+eS92K/SD0dqpsC+GNBdOoWPNGCGtJ6Z1FuH3pCorWuQxCS5NvVzmiVx0krGQhCDlF/OlQzsUHI8eOwvGdHDpQhWV7SxI/f1FGn5rXyhu4uMxJgP/mq76eGZwgP0u4jBBgPQ8SOelE4ouWeZGRdmGPBg1sl8KqVe2MAFWrQunSATNmRqlL5M0LZcrYW3oZYytsR4/aytjx43aNhlOnUv577pw9J6W/58/b++fP29k3zp+/+OYnoqOj3Q5BKeVDGS0OE6U5uYaI3AJcZYy529nuBsQaYx70OOZX4A1jzCxn+y/gKWNMir+62tdoY74a+wXFi9m1RnbtDSY0xBBV1G7v3BNMntAL2zt2BxOW11CsyIXt8AihaFEgKIi9B0MIjxAKFBQICuLo8SDCCuYlb0HtPqiUmzIy8NRX5Q1A/rB/zaEVweTJA9Pn5iU8zHB5/XMZG54SHGwrT8ndgoNtq4HL412Uys0CaTIfpVTg88XkGjsAzxknygK7MnHMRY7kP07xRhdOKV3h4sfLJNkum8Z2iVIXbxfUnjxKBSKflDcAeSI2crjAlZQoAa0qpHW0Ukpl3v79+90OQSnlh9LT72UBEC0ilUQkD9AFmJDkmAlAd7EaA0fTGm+hlFLJ8Fl5U7nyc5Qo4f2AlVKBS0TCRGS+iCwTkVUiMiCZY2qIyBwROSsiT6Qn3UOHDnk/WKVUwEuzxcsYEyciDwCTsdM7jzTGrBKRvs7jw4HfsFM7b8RO79zLdyErpXIqLW+UUtnsLNDWGHNCREKBWSLyuzFmrscxh4CHgBvcCFAplXOkax0vY8xv2B87nvuGe9w3wP3eDU0plRtpeaOUyi5OeXLC2Qx1bibJMfuAfSJybTaHp5TKYXSKLaWUUkrlWiISLCJLgX3AFGPMvEym00dEForIwvN+NMOiUsp/aMVLKaWUUrmWMSbeGNMAO1FPrIjUyWQ6HxtjYowxMaGhoV6NUSmVM6Srq6EvLFq06ISIrHMrf3WJYsABt4NQF8kp74lfzCGoZY7fySmf75wip7wfmS5vjDFHRGQa0BFYmZUgTpw4oeVN4Mgpn/3cwt/erwyVOa5VvIB1/rDWhrJEZKG+H/5F3xOv0zLHj+jn27/k1vdDRKKA806lKxxoD7zphaS1vAkQufWzH6gC/f1ys+KllFJKKeWmUsBoEQnGDr8Yb4yZ6DmTqoiUBBYCBYAEEXkEqGWMOeZW0EqpwKQVL6WUUkrlSsaY5UDDZPZ7zqS6Bzv+SymlssTNyTU+djFvdSl9P/yPvifepa+nf9H3w7/o++Fd+noGDn2vAktAv19il7BQSimllFJKKeUrOp28UkoppZRSSvmYVryUUkoppZRSysdcqXiJSEcRWSciG0XkGTdiyM1EZKSI7BORlR77iojIFBHZ4Pwt7GaMuYmIlBORqSKyRkRWicjDzn59T7xAyxv3aZnjP7S88S0tb/xDCmXOyyKyU0SWOrdrPB571nnP1onIVR77G4nICuexwSIi2f1ccjoRCROR+SKyzCmTBjj7UyyTAvn9yvaKlzNl61DgaqAWcLuI1MruOHK5z7ELRHp6BvjLGBMN/OVsq+wRBzxujKkJNAbud/4n9D3JIi1v/MbnaJnjL7S88REtb/zK51xa5gC8b4xp4Nx+A3Deoy5AbeecYc57CfAR0AeIdm7Jpamy5izQ1hhTH2gAdBSRxqRQJgX6++VGi1cssNEY868x5hzwNdDZhThyLWPMDOBQkt2dgdHO/dHADdkZU25mjNltjFns3D8OrAHKoO+JN2h54we0zPEfWt74lJY3fiKFMiclnYGvjTFnjTGbgY1ArIiUAgoYY+YYOxPdF+j/hdcZ64SzGercDCmXSQH9frlR8SoDbPfY3uHsU+4qYYzZDfaLGSjucjy5kohUxK4pMw99T7xByxv/pZ9vl2l543Va3vi/B0RkudMVMbHrWkrvWxnnftL9ystEJFhElgL7gCnGmNTKpIB+v9yoeCXX31LntFe5nojkB74HHjHGHHM7nhxCyxulkqHljU9oeePfPgKqYLuz7Qbedfan9L7p+5lNjDHxxpgG2IXKY0WkTiqHB/T75UbFawdQzmO7LLDLhTjUxfY6zbQ4f/e5HE+uIiKh2B9BY40xPzi79T3JOi1v/Jd+vl2i5Y3PaHnjx4wxe50f+AnAJ9iuoZDy+7bDuZ90v/IRY8wRYBp2bFZKZVJAv19uVLwWANEiUklE8mAHyE1wIQ51sQlAD+d+D+BnF2PJVZxZdz4D1hhj3vN4SN+TrNPyxn/p59sFWt74lJY3fizxR7zjRiBxxsMJQBcRySsilbCTMsx3urcdF5HGzv9Nd/T/wutEJEpECjn3w4H2wFpSLpMC+v0SO/4smzO1U3gOAoKBkcaY17I9iFxMRMYBrYFiwF7gJeAnYDxQHtgG3GKMSe/AVJUFItIcmAmsABKc3c9hx13oe5JFWt64T8sc/6HljW9peeMfUihzWmO7GRpgC3Bv4hgiEXkeuAs76+cjxpjfnf0x2BkSw4HfgQeNGz+cczARqYedPCMY2yA03hjziogUJYUyKZDfL1cqXkoppZRSSimVm7iygLJSSimllFJK5SZa8VJKKaWUUkopH9OKl1JKKaWUUkr5mFa8lFJKKaWUUsrHtOKllFJKKaWUUj6mFS+llFJKKaWU8jGteCmllFJKqVxFRIqKyFLntkdEdjr3T4jIMB/k97mIbBaRvqkc00JEVovIypSOUYFNK14qQ0Qk3imYVorIL4mrjSc5pqKInBaRpV7KM9zJ85yIFPNGmkop/6fljVLKV4wxB40xDYwxDYDhwPvOdn5jzH0+yvZJY8zwVGKaCVzjo7yVH9CKl8qo007BVAc4BNyfwnGbnMIsy4wxp520dnkjPaVUwNDyRimVrUSktYhMdO6/LCKjReQPEdkiIv8TkbdEZIWITBKRUOe4RiIyXUQWichkESmVjnxucS4qLRORGb5+Xso/aMVLZcUcoEx6DhSRaSJS3blf1ClsKorIWhH51NkeKyLtReQfEdkgIrE+jV4pFUi0vFFKuaEKcC3QGfgSmGqMqQucBq51Kl8fAjcbYxoBI4HX0pFuf+AqY0x9oJNPIld+RyteKlNEJBhoB0xI5ylVgQ3O/XrACo/9Hzj7agB3AM2BJ4DnvBWvUipwaXmjlHLR78aY89hyJBiY5OxfAVQEqgN1gClOl+cXgLLpSPcf4HMRucdJV+UCIW4HoAJOuFOwVAQWAVPSOkFEKgA7jTEJzq56wHLn/mZjzArnuFXAX8YYIyKJBZpSKvfS8kYp5bazAMaYBBE5b4wxzv4E7O9oAVYZY5pkJFFjTF8RuQLbmrZURBoYYw56M3Dlf7TFS2VU4viHCkAeUh5z4akBF374ADTy2D7rsT/BYzuxQFNK5V5a3iil/N06IEpEmgCISKiI1E7rJBGpYoyZZ4zpDxwAyvk4TuUHtOKlMsUYcxR4CHgicXBpKuoDYQAiEo3tJ70i1TOUUsqh5Y1Syl8ZY84BNwNvisgyYCnQNB2nvu1M0rESmAEs812Uyl/oFT6VacaYJU4h0wUYk8qhDYDTzrHLgTVAjzTOUUqp/2h5o5TyFWPMyx73pwHTku53tvOncM5SoGUG8/xfxiNVgU4rXipDPAsdZ/v6dJxWD2hojDmezGN1PNLq6XF/i+djSqncR8sbpVQOchR4VUSKpbSWl4i0AIZhux6qHEgrXsoX4oGCzqD4FkBCCj+C0kVEwrFTSYdix2IopVQiLW+UUn7PGPNwOo6ZCdTNhnCUS+TC5CxKKaWUUkoppXxBJ9dQSimllFJKKR/TipdSSimllFJK+ZhWvJRSSimllFLKx7TipZRSSimllFI+phUvpZRSSimllPIxrXgppZRSSimllI9pxUsppZRSSimlfEwrXkoppZRSSinlY1rxUkoppZRSSikf04qXUkoppZRSSvmYVryUUkoppZRSyse04qWUUkoppZRSPqYVL6WUUkoppZTysRC3A1BKKaWUUionWbRoUfGQkJBPgTpoQ0dulACsjIuLu7tRo0b7EndqxUsppZRSSikvCgkJ+bRkyZI1o6KiDgcFBRm341HZKyEhQfbv319rz549nwKdEvdrDVwppZRSSinvqhMVFXVMK125U1BQkImKijqKbfG8sN+leJRSSimllMqpgrTSlbs57/9FdS2teCmllFJKKaWUj2nFSymllFJKqRzsscceK92/f/8SqR2za9eukHr16tWoWbNmrUmTJuXPaB6DBw8u2r179/IAY8aMKbRo0aKwzMbir9atW5cnOjq6dmbP18k1lFJKKaWUyuUmTpwYWbVq1TM//PDDlqym9dNPPxWKi4s72qhRozNeCM1r4uLiCAlxr/qjLV5KKaWUUkrlME8//XTJihUr1mnatGm1DRs25E3cv2rVqrwtWrSIrl27ds1GjRpVX7JkSdjs2bPDX3rppbJTp04tWKNGjVonTpyQrl27lq9Tp07NqlWr1n700UdLJ55fpkyZurt37w4BmDFjRkRsbGx1z3ynTJmS788//yz0wgsvlK1Ro0atVatW5SUFs2fPDq9fv36NatWq1erQoUOV/fv3BwNMnz49olq1arUaNGhQ49577y2b2Mo0ePDgoldeeWWVFi1aRFeoUKFO3759yyamNWLEiCLVqlWrFR0dXbtfv35lEvdHREQ0fOSRR0rXq1evxl9//ZU/IiKiYb9+/crUrl27ZtOmTatNnTo1IjY2tnrZsmXrjh07tiDYlq1GjRpVr1WrVs1atWrVnDJlSr6ksS9cuDCsbt26NWvUqFGrWrVqtVasWJHi80ykLV5KKaWUUkr5yl13lWPlygivplmnzilGjtye0sMzZ86M+PHHH4usWLFi9fnz52nQoEGthg0bngK4++67K3z88cdb69ate/bvv//O169fv/Jz585d/+yzz+5auHBhvi+++GIbwHvvvbezRIkS8XFxcTRt2rT6vHnzwq+44orTaYXWoUOHk+3btz9y3XXXHe3Vq9fh1I7t2bNnpffff3/btddee+KRRx4p/fTTT5ceOXLk9rvvvrvSsGHDtnTo0OHkfffdV8bznNWrV0csW7ZsdXh4eELVqlXrPPHEE3tDQkJ4+eWXyyxatGhNVFRUXIsWLaqNGTOmULdu3Y6cPn06qE6dOqcHDRq0C+D06dNBbdq0Of7RRx/t7NChQ5UXXnihzMyZM9cvXrw4rFevXpW6du16tHTp0nEzZ85cHxERYVasWJH39ttvr7xy5co1nnF8+OGHUffdd9/efv36HTpz5ozExcWl9dJoxUsppZRSSqmcZOrUqfmvueaaI5GRkQkAV1555RGAo0ePBi1ZsiT/LbfcUiXx2HPnzklyaYwePbrI559/XiwuLk72798fumzZsrD0VLzS6+DBg8HHjx8Pvvbaa08A3HPPPQdvueWWygcOHAg+efJkUIcOHU4C9OjR49CUKVMKJZ7XvHnzY0WLFo0HqFq16plNmzbl3b9/f0jjxo2Ply5dOg7gtttuOzR9+vT83bp1OxIcHEzPnj3/qwCGhoaam2+++RhA7dq1T+fNmzchb968JjY29vTOnTvzJL4mvXv3rrB69erwoKAgtm7deklrVpMmTU6+8847pXbs2JGnS5cuh+vWrXs2reesFS+llFJKKaV8JZWWKV8SubQ+FR8fT2RkZNzatWtXp3bu2rVr8wwZMqSE04IUf9NNN1U8c+ZMEEBwcLBJSEgAbOuRt+M2JvVZ+PPkyfPfAcHBweb8+fOS2jl58uRJ8BzXFRISYoKCbNhBQUHkzZvXOGkRHx8vAK+99lqJ4sWLn//+++83JyQkEB4e3ihpun379j3UokWLkz/++GPBq6++utqwYcO2dOrU6XhqsesYL6WUUkoppXKQtm3bnvj1118LnThxQg4fPhyU2GJUpEiRhLJly54bOXJkYYCEhATmzJkTnvT8w4cPB4eHhycUKVIkfvv27SHTpk0rmPhY2bJlz/3zzz8RAOPHjy+cXP758+ePP3bsWKr1jKJFi8YXKFAgPnEGxc8++6xokyZNTkRFRcXny5cv4a+//soHMGbMmCJpPd+WLVuenDdvXuTu3btD4uLi+Pbbb4u0bt36RFrnpeTo0aPBpUqVOh8cHMywYcOKxsfHX3LM6tWr89SsWfPsCy+8sO/KK688snTp0ktex6S04qWUUkoppVQO0rx581M33njjoTp16tS+7rrrqsTGxv5XCRk3bty/o0aNKla9evVa0dHRtb///vtCSc9v0qTJ6Tp16pyKjo6u3a1bt4qNGjX67/z+/fvveuqpp8o3atSoenBwcLJNTV27dj00ePDgkjVr1kx1co1Ro0Ztfvrpp8tWq1at1vLly8MHDhy4C2DEiBFb+vXrV6FBgwY1jDFERkZeWvPxUKFChfP9+/ff2apVq2o1a9asXa9evVN33nnnkbRfqeQ98sgj+8aNG1e0fv36NdavXx8WHh6ekPSYMWPGFKlWrVrtGjVq1NqwYUPYvffeezCtdFNtmlNKKaWUUkplzLJly7bUr1//gNtxBKqjR48GFSxYMAHgueeeK7l79+7QUaNGudJlMyuWLVtWrH79+hUTt3WMl1JKKaWUUspvjB8/vuC7775bKj4+XsqUKXP2q6++2uJ2TN6gFS+llFJKKaWU37jnnnsO33PPPalORR+IdIyXUkoppZRSSvmYVryUUkoppZRSyse04qWUUkoppZRSPqYVL6WUUkoppZTyMa14KaWUUkoppS7yzDPPlHQ7hpxGK15KKaWUUkqpiwwePLiU2zHkNFrxUkoppZRSKocZMmRI0WrVqtWqXr16rRtuuKHSTTfdVHHUqFGFEx+PiIhoCLB169bQmJiY6jVq1KgVHR1de9KkSfnvu+++MmfPng2qUaNGrU6dOlUCePnll0tER0fXjo6Orv3KK68UB1i3bl2eSpUq1b7tttsqREdH1+7UqVOln376KfKyyy6rUaFChTpTp06NcOfZ+yeteCmllFJKKeVDsbFUHzyYogBnzyKxsVQfNowiAMePExQbS/VPPqEwwMGDBMfGUn30aAoB7N5NSGws1b/6ioIA27alvQ7vwoULw955551S06dPX79u3brVI0aM2JbSsSNHjizSrl27o2vXrl29Zs2aVVdcccWpYcOG7cybN2/C2rVrV0+YMGHzzJkzI7766quiixYtWrNw4cI1X3zxRdQ///wTDrB9+/awxx9/fN/atWtXbdq0KWzs2LFFFy5cuPa1117b8dprr2mrmQeteCmllFJKKZWDTJ48ucD1119/uFSpUnEAJUqUiE/p2MaNG58cN25csccee6z0/PnzwwsXLpyQ9Jhp06blv+aaa44UKFAgoWDBggnXXnvt4alTp0YClClT5mxsbOzp4OBgqlWrdrpt27bHgoKCuOyyy07t2LEjr++eZeBJs8aslFJKKaWUyrz581mXeD9vXozndmQkCZ7bRYsS77ldqhRxntvlyxOXVn7GGETEeO4LCQkx8fG2/pWQkMD58+cF4Oqrrz4xY8aMdd9//33Bnj17VnrooYf2PvDAAweTppeSPHny/PdgUFAQYWFhBiA4OJj4+HhJK9bcRFu8lFJKKaWUykE6dux4bMKECUX27NkTDLB3797gChUqnFu0aFEEwNixYwvFxcUJwPr16/OUKVPm/OOPP37gzjvvPLB48eIIsBW1s2fPCkDbtm1P/Pbbb4WOHz8edOzYsaDffvutcJs2bY679fwClbZ4KaWUUkoplYPExMScefzxx3e3aNGiRlBQkKlTp86pQYMG7bjuuuuq1q1bt2bLli2PhYeHJwBMnjw5cvDgwSVDQkJMRERE/NixYzcDdO3adX/NmjVr1alT59SECRM233HHHQcvu+yymgDdunXb36xZs9Pr1q3L4+bzDDSSWtOhUkoppZRSKmOWLVu2pX79+gfcjkO5a9myZcXq169fMXFbuxoqpZRSSimllI9pxUsppZRSSimlfEwrXkoppZRSSnlXQkJCgs7ol4s57/9FU/NrxUsppZRSSinvWrl///6CWvnKnRISEmT//v0FgZWe+3VWQ6WUUkoppbwoLi7u7j179ny6Z8+eOmhDR26UAKyMi4u723OnzmqolFJKKaWUUj6mNXCllFJKKaWU8jGteCmllFJKKaWUj2nFSymllFJKKaV87P8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"text/plain": [ "
" ] @@ -377,7 +377,7 @@ "]\n", "\n", "# parameters\n", - "params = pybamm.ParameterValues(chemistry=pybamm.parameter_sets.Marquis2019)\n", + "params = pybamm.ParameterValues(\"Marquis2019\")\n", "params = pybamm.get_size_distribution_parameters(params) \n", "\n", "# define current function\n", @@ -406,7 +406,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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", 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" ] diff --git a/examples/scripts/compare_lithium_ion_half_cell.py b/examples/scripts/compare_lithium_ion_half_cell.py index 810091a7d2..b6396724f4 100644 --- a/examples/scripts/compare_lithium_ion_half_cell.py +++ b/examples/scripts/compare_lithium_ion_half_cell.py @@ -7,24 +7,15 @@ # load models models = [ - pybamm.lithium_ion.SPM( - {"working electrode": "positive", "SEI": "ec reaction limited"} - ), - pybamm.lithium_ion.SPMe( - {"working electrode": "positive", "SEI": "ec reaction limited"} - ), - pybamm.lithium_ion.DFN( - {"working electrode": "positive", "SEI": "ec reaction limited"} - ), + pybamm.lithium_ion.SPM({"working electrode": "positive"}), + pybamm.lithium_ion.SPMe({"working electrode": "positive"}), + pybamm.lithium_ion.DFN({"working electrode": "positive"}), ] -chemistry = pybamm.parameter_sets.Xu2019 -param = pybamm.ParameterValues(chemistry) - # create and run simulations sims = [] for model in models: - sim = pybamm.Simulation(model, parameter_values=param) + sim = pybamm.Simulation(model) sim.solve([0, 3600]) sims.append(sim) diff --git a/tests/integration/test_experiments.py b/tests/integration/test_experiments.py index 314f34ce95..ea72fc052c 100644 --- a/tests/integration/test_experiments.py +++ b/tests/integration/test_experiments.py @@ -36,9 +36,7 @@ def test_rest_discharge_rest(self): ["Rest for 5 minutes", "Discharge at 0.1C until 3V", "Rest for 30 minutes"], period="1 minute", ) - parameter_values = pybamm.ParameterValues( - chemistry=pybamm.parameter_sets.Chen2020 - ) + parameter_values = pybamm.ParameterValues("Chen2020") model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation( model, diff --git a/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_compare_basic_models.py b/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_compare_basic_models.py index efbd706ec5..47420bb0fc 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_compare_basic_models.py +++ b/tests/integration/test_models/test_full_battery_models/test_lead_acid/test_compare_basic_models.py @@ -12,9 +12,7 @@ def test_compare_full(self): basic_full = pybamm.lead_acid.BasicFull() full = pybamm.lead_acid.Full({"convection": "uniform transverse"}) - parameter_values = pybamm.ParameterValues( - chemistry=pybamm.parameter_sets.Sulzer2019 - ) + parameter_values = pybamm.ParameterValues("Sulzer2019") parameter_values["Current function [A]"] = 10 # Solve basic Full mode diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py index 58159124fd..adf918b4cf 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py @@ -63,17 +63,13 @@ def test_set_up(self): def test_charge(self): options = {"thermal": "isothermal"} - parameter_values = pybamm.ParameterValues( - chemistry=pybamm.parameter_sets.Marquis2019 - ) + parameter_values = pybamm.ParameterValues("Marquis2019") parameter_values.update({"Current function [A]": -1}) self.run_basic_processing_test(options, parameter_values=parameter_values) def test_zero_current(self): options = {"thermal": "isothermal"} - parameter_values = pybamm.ParameterValues( - chemistry=pybamm.parameter_sets.Marquis2019 - ) + parameter_values = pybamm.ParameterValues("Marquis2019") parameter_values.update({"Current function [A]": 0}) self.run_basic_processing_test(options, parameter_values=parameter_values) diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_basic_half_cell_models.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_basic_half_cell_models.py index 9d41932edb..6b953e78d9 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_basic_half_cell_models.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_basic_half_cell_models.py @@ -16,8 +16,7 @@ def test_runs_Xu2019(self): geometry = model.default_geometry # load parameter values - chemistry = pybamm.parameter_sets.Xu2019 - param = pybamm.ParameterValues(chemistry) + param = pybamm.ParameterValues("Xu2019") param["Current function [A]"] = 2.5e-3 @@ -47,8 +46,7 @@ def test_runs_Chen2020(self): geometry = model.default_geometry # load parameter values - chemistry = pybamm.parameter_sets.Chen2020_plating - param = pybamm.ParameterValues(chemistry) + param = pybamm.ParameterValues("Chen2020_plating") param["Current function [A]"] = 2.5 diff --git a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_thermal_models.py b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_thermal_models.py index 8c249fad27..5be748996b 100644 --- a/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_thermal_models.py +++ b/tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_thermal_models.py @@ -35,8 +35,7 @@ def test_consistent_cooling(self): for model_name, model in models.items(): var_pts = {"x_n": 3, "x_s": 3, "x_p": 3, "r_n": 3, "r_p": 3, "y": 5, "z": 5} - chemistry = pybamm.parameter_sets.NCA_Kim2011 - parameter_values = pybamm.ParameterValues(chemistry) + parameter_values = pybamm.ParameterValues("NCA_Kim2011") # high thermal and electrical conductivity in current collectors parameter_values.update( diff --git a/tests/unit/test_experiments/test_simulation_with_experiment.py b/tests/unit/test_experiments/test_simulation_with_experiment.py index 0575d743a4..bd3de80c88 100644 --- a/tests/unit/test_experiments/test_simulation_with_experiment.py +++ b/tests/unit/test_experiments/test_simulation_with_experiment.py @@ -376,9 +376,7 @@ def test_run_experiment_half_cell(self): sim = pybamm.Simulation( model, experiment=experiment, - parameter_values=pybamm.ParameterValues( - chemistry=pybamm.parameter_sets.Xu2019 - ), + parameter_values=pybamm.ParameterValues("Xu2019"), ) sim.solve() diff --git a/tests/unit/test_models/test_full_battery_models/test_lithium_ion/test_electrode_soh.py b/tests/unit/test_models/test_full_battery_models/test_lithium_ion/test_electrode_soh.py index 7fa603cd2d..540c02277c 100644 --- a/tests/unit/test_models/test_full_battery_models/test_lithium_ion/test_electrode_soh.py +++ b/tests/unit/test_models/test_full_battery_models/test_lithium_ion/test_electrode_soh.py @@ -10,9 +10,7 @@ def test_known_solution(self): model = pybamm.lithium_ion.ElectrodeSOH() param = pybamm.LithiumIonParameters() - parameter_values = pybamm.ParameterValues( - chemistry=pybamm.parameter_sets.Mohtat2020 - ) + parameter_values = pybamm.ParameterValues("Mohtat2020") sim = pybamm.Simulation(model, parameter_values=parameter_values) V_min = 3 @@ -43,9 +41,7 @@ def test_known_solution(self): model = pybamm.lithium_ion.ElectrodeSOHHalfCell("positive") param = pybamm.LithiumIonParameters({"working electrode": "positive"}) - parameter_values = pybamm.ParameterValues( - chemistry=pybamm.parameter_sets.Xu2019 - ) + parameter_values = pybamm.ParameterValues("Xu2019") sim = pybamm.Simulation(model, parameter_values=parameter_values) V_min = 3 @@ -63,9 +59,7 @@ def test_known_solutions(self): model = pybamm.lithium_ion.ElectrodeSOH() param = pybamm.LithiumIonParameters() - parameter_values = pybamm.ParameterValues( - chemistry=pybamm.parameter_sets.Mohtat2020 - ) + parameter_values = pybamm.ParameterValues("Mohtat2020") sim = pybamm.Simulation(model, parameter_values=parameter_values) V_min = parameter_values.evaluate(param.voltage_low_cut_dimensional) diff --git a/tests/unit/test_parameters/test_lead_acid_parameters.py b/tests/unit/test_parameters/test_lead_acid_parameters.py index 54a68c80a2..e23067b457 100644 --- a/tests/unit/test_parameters/test_lead_acid_parameters.py +++ b/tests/unit/test_parameters/test_lead_acid_parameters.py @@ -66,9 +66,7 @@ def test_concatenated_parameters(self): ) # process parameters and discretise - parameter_values = pybamm.ParameterValues( - chemistry=pybamm.parameter_sets.Sulzer2019 - ) + parameter_values = pybamm.ParameterValues("Sulzer2019") disc = get_discretisation_for_testing() processed_s = disc.process_symbol(parameter_values.process_symbol(s_param)) @@ -143,9 +141,7 @@ def test_functions_lead_acid(self): "U_p_0.5": param.U_p(pybamm.Scalar(0.5), pybamm.Scalar(0)), } # Process - parameter_values = pybamm.ParameterValues( - chemistry=pybamm.parameter_sets.Sulzer2019 - ) + parameter_values = pybamm.ParameterValues("Sulzer2019") param_eval = parameter_values.print_parameters(parameters) param_eval = {k: v[0] for k, v in param_eval.items()} diff --git a/tests/unit/test_parameters/test_parameter_sets/test_LFP_Prada2013.py b/tests/unit/test_parameters/test_parameter_sets/test_LFP_Prada2013.py index b0e06b069a..e8d9c62034 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_LFP_Prada2013.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_LFP_Prada2013.py @@ -26,8 +26,7 @@ def test_load_params(self): def test_standard_lithium_parameters(self): - chemistry = pybamm.parameter_sets.Prada2013 - parameter_values = pybamm.ParameterValues(chemistry) + parameter_values = pybamm.ParameterValues("Prada2013") model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_LGM50_Chen2020.py b/tests/unit/test_parameters/test_parameter_sets/test_LGM50_Chen2020.py index 76d49b1d2a..935041a5f0 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_LGM50_Chen2020.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_LGM50_Chen2020.py @@ -40,8 +40,7 @@ def test_load_params(self): def test_standard_lithium_parameters(self): - chemistry = pybamm.parameter_sets.Chen2020 - parameter_values = pybamm.ParameterValues(chemistry) + parameter_values = pybamm.ParameterValues("Chen2020") model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_LGM50_ORegan2021.py b/tests/unit/test_parameters/test_parameter_sets/test_LGM50_ORegan2021.py index 5b965cf62e..dc5f8a0416 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_LGM50_ORegan2021.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_LGM50_ORegan2021.py @@ -127,8 +127,7 @@ def test_functions(self): def test_standard_lithium_parameters(self): - chemistry = pybamm.parameter_sets.ORegan2021 - parameter_values = pybamm.ParameterValues(chemistry) + parameter_values = pybamm.ParameterValues("ORegan2021") model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_NCA_Kim2011.py b/tests/unit/test_parameters/test_parameter_sets/test_NCA_Kim2011.py index 080dcdd45f..c907ca2312 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_NCA_Kim2011.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_NCA_Kim2011.py @@ -41,8 +41,7 @@ def test_load_params(self): def test_standard_lithium_parameters(self): - chemistry = pybamm.parameter_sets.NCA_Kim2011 - parameter_values = pybamm.ParameterValues(chemistry) + parameter_values = pybamm.ParameterValues("NCA_Kim2011") model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_NCO_Ecker2015.py b/tests/unit/test_parameters/test_parameter_sets/test_NCO_Ecker2015.py index a6db637374..75e87de580 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_NCO_Ecker2015.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_NCO_Ecker2015.py @@ -43,8 +43,7 @@ def test_load_params(self): def test_standard_lithium_parameters(self): - chemistry = pybamm.parameter_sets.Ecker2015 - parameter_values = pybamm.ParameterValues(chemistry) + parameter_values = pybamm.ParameterValues("Ecker2015") model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_NMChalfcell_Xu2019.py b/tests/unit/test_parameters/test_parameter_sets/test_NMChalfcell_Xu2019.py index f629435a10..a68016eca1 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_NMChalfcell_Xu2019.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_NMChalfcell_Xu2019.py @@ -43,8 +43,7 @@ def test_load_params(self): def test_standard_lithium_parameters(self): - chemistry = pybamm.parameter_sets.Xu2019 - parameter_values = pybamm.ParameterValues(chemistry) + parameter_values = pybamm.ParameterValues("Xu2019") model = pybamm.lithium_ion.BasicDFNHalfCell({"working electrode": "positive"}) sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_parameters/test_parameter_sets/test_UMBL_Mohtat2020.py b/tests/unit/test_parameters/test_parameter_sets/test_UMBL_Mohtat2020.py index 67e5962775..c9ec41cb28 100644 --- a/tests/unit/test_parameters/test_parameter_sets/test_UMBL_Mohtat2020.py +++ b/tests/unit/test_parameters/test_parameter_sets/test_UMBL_Mohtat2020.py @@ -42,8 +42,7 @@ def test_load_params(self): def test_standard_lithium_parameters(self): - chemistry = pybamm.parameter_sets.Mohtat2020 - parameter_values = pybamm.ParameterValues(chemistry) + parameter_values = pybamm.ParameterValues("Mohtat2020") model = pybamm.lithium_ion.DFN() sim = pybamm.Simulation(model, parameter_values=parameter_values) diff --git a/tests/unit/test_plotting/test_plot_summary_variables.py b/tests/unit/test_plotting/test_plot_summary_variables.py index d7bfe9f47e..331d5615df 100644 --- a/tests/unit/test_plotting/test_plot_summary_variables.py +++ b/tests/unit/test_plotting/test_plot_summary_variables.py @@ -6,9 +6,7 @@ class TestPlotSummaryVariables(unittest.TestCase): def test_plot(self): model = pybamm.lithium_ion.SPM({"SEI": "ec reaction limited"}) - parameter_values = pybamm.ParameterValues( - chemistry=pybamm.parameter_sets.Mohtat2020 - ) + parameter_values = pybamm.ParameterValues("Mohtat2020") experiment = pybamm.Experiment( [ ( From cc21e58a47b18c6e4f3e3956323ba21ed1b574ac Mon Sep 17 00:00:00 2001 From: Valentin Sulzer Date: Thu, 25 Nov 2021 12:18:33 -0500 Subject: [PATCH 8/8] #1810 more examples --- examples/scripts/cycling_ageing.py | 2 +- examples/scripts/nca_parameters.py | 3 +-- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/examples/scripts/cycling_ageing.py b/examples/scripts/cycling_ageing.py index 956a5c443e..c649e8e7dd 100644 --- a/examples/scripts/cycling_ageing.py +++ b/examples/scripts/cycling_ageing.py @@ -11,7 +11,7 @@ } ) -param = pb.ParameterValues(pb.parameter_sets.Mohtat2020) +param = pb.ParameterValues("Mohtat2020") experiment = pb.Experiment( [ diff --git a/examples/scripts/nca_parameters.py b/examples/scripts/nca_parameters.py index a1e32f9402..20b374bc16 100644 --- a/examples/scripts/nca_parameters.py +++ b/examples/scripts/nca_parameters.py @@ -3,8 +3,7 @@ pb.set_logging_level("INFO") model = pb.lithium_ion.DFN() -chemistry = pb.parameter_sets.NCA_Kim2011 -parameter_values = pb.ParameterValues(chemistry) +parameter_values = pb.ParameterValues("NCA_Kim2011") sim = pb.Simulation(model, parameter_values=parameter_values, C_rate=1) sim.solve([0, 3600])