From 07adbef36e4ed7c275a44836b6e30ab8f826a247 Mon Sep 17 00:00:00 2001 From: Bart Schilperoort Date: Wed, 8 Jan 2025 15:38:29 +0100 Subject: [PATCH] Move to Remote BMI & containerized model (#12) * Use remotebmi containerized model * Add Dockerfile * Add new demo notebook * Update dockerfile * Update README * Correct entrypoint, set ewatercycle minimum version * Update CMIP forcing notebook * Update formatting * Add link to parameter set download * Modify Dockerfile to allow any user to run the container --------- Co-authored-by: sverhoeven --- Dockerfile | 18 + README.md | 23 +- docs/demo.ipynb | 264 ++++++++++ docs/generate_cmip_forcing.ipynb | 278 +++-------- docs/wflowjl_local.ipynb | 451 ------------------ pyproject.toml | 15 +- src/ewatercycle_wflowjl/__init__.py | 3 +- .../forcing/diagnostic_script.py | 1 + src/ewatercycle_wflowjl/forcing/forcing.py | 1 + src/ewatercycle_wflowjl/forcing/makkink.py | 1 + src/ewatercycle_wflowjl/model.py | 45 +- src/ewatercycle_wflowjl/utils.py | 18 - 12 files changed, 387 insertions(+), 731 deletions(-) create mode 100644 Dockerfile create mode 100644 docs/demo.ipynb delete mode 100644 docs/wflowjl_local.ipynb delete mode 100644 src/ewatercycle_wflowjl/utils.py diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000..1832277 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,18 @@ +FROM ghcr.io/ewatercycle/remotebmi-julia:0.1.0 + +LABEL org.opencontainers.image.source="https://github.com/eWaterCycle/ewatercycle-wflowjl" + +# Install Wflow +RUN julia -e 'using Pkg; Pkg.add(PackageSpec(name="Wflow", version="0.8.1"))' + +RUN echo "using Wflow" > run.jl +RUN echo "import RemoteBMI.Server: run_bmi_server" >> run.jl +RUN echo "port = parse(Int, get(ENV, \"BMI_PORT\", \"50051\"))" >> run.jl +RUN echo "run_bmi_server(Wflow.Model, \"0.0.0.0\", port)" >> run.jl + +# chmod central depot path so all users can access it +RUN chmod -R 777 ${JULIA_DEPOT_PATH} + +# Expose port and start server +EXPOSE 50051 +CMD ["julia", "run.jl"] diff --git a/README.md b/README.md index a439417..ad98956 100644 --- a/README.md +++ b/README.md @@ -2,38 +2,29 @@ Wflow.jl plugin for [eWatercycle](https://ewatercycle.readthedocs.io/). -The Wflow.jl documentation is available at https://deltares.github.io/Wflow.jl/dev/ . +The Wflow.jl documentation is available at https://deltares.github.io/Wflow.jl/ . ## Installation -eWaterCycle must be installed in a [mamba](https://conda-forge.org/miniforge/) environment. The environment can be created with +Please first install ewatercycle, for more info see the [general ewatercycle documentation](https://ewatercycle.readthedocs.io/). -```console -wget https://raw.githubusercontent.com/eWaterCycle/ewatercycle/main/environment.yml -mamba env create --name ewatercycle-wflowjl --file environment.yml -conda activate ewatercycle-wflowjl -``` - -Install this package alongside your eWaterCycle installation +To install this package alongside your eWaterCycle installation, do: ```console pip install ewatercycle-wflowjl ``` -Then Wflow becomes available as one of the eWaterCycle models +Then Wflow becomes available as one of the eWaterCycle models: ```python -from ewatercycle.models import WflowJl +import ewatercycle.models +ewatercycle.models.sources["WflowJl"] ``` -Note that unlike other plugins, the WflowJl eWaterCycle model does not run in a container. - -This is due to limitations of the Julia language. - ## Usage Usage of Wflow.jl forcing generation and model execution is shown in -[docs/generate_era5_forcing.ipynb](https://github.com/eWaterCycle/ewatercycle-wflowjl/tree/main/docs/generate_era5_forcing.ipynb) and [docs/wflowjl_local.ipynb](https://github.com/eWaterCycle/ewatercycle-wflow/tree/main/docs/wflowjl_local.ipynb) respectively. +[docs/generate_era5_forcing.ipynb](https://github.com/eWaterCycle/ewatercycle-wflowjl/tree/main/docs/generate_era5_forcing.ipynb) and [docs/demo.ipynb](https://github.com/eWaterCycle/ewatercycle-wflow/tree/main/docs/demo.ipynb) respectively. ## License diff --git a/docs/demo.ipynb b/docs/demo.ipynb new file mode 100644 index 0000000..6792814 --- /dev/null +++ b/docs/demo.ipynb @@ -0,0 +1,264 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Wflow.jl in eWaterCycle\n", + "\n", + "This notebook showcases the use of the Wflow.jl model in eWaterCycle." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "import numpy as np" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `wflow_sbm + kinematic wave` parameter set can be downloaded from https://deltares.github.io/Wflow.jl/dev/getting_started/download_example_models.html ." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from ewatercycle.base.parameter_set import ParameterSet\n", + "\n", + "parameters_moselle = ParameterSet(\n", + " name=\"moselle\",\n", + " directory=Path(\"/data/wflow/sbm_moselle\"),\n", + " target_model=\"WflowJl\",\n", + " config=\"sbm_config.toml\" \n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/bart/miniconda3/envs/lock2/lib/python3.12/site-packages/esmvalcore/experimental/_warnings.py:13: UserWarning: \n", + " Thank you for trying out the new ESMValCore API.\n", + " Note that this API is experimental and may be subject to change.\n", + " More info: https://github.com/ESMValGroup/ESMValCore/issues/498\n" + ] + } + ], + "source": [ + "import ewatercycle.models\n", + "\n", + "model = ewatercycle.models.sources[\"WflowJl\"](\n", + " parameter_set=parameters_moselle,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "cfg_file,_ = model.setup()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Don't immediately run the next cell: the model needs time to set up. After a few seconds the server will be ready." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "model.initialize(cfg_file)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "After initialization we can interact with the model. For example requesting the river discarge:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/bart/git2/ewatercycle-wflowjl/src/ewatercycle_wflowjl/model.py:64: FutureWarning: the `pandas.MultiIndex` object(s) passed as 'loc' coordinate(s) or data variable(s) will no longer be implicitly promoted and wrapped into multiple indexed coordinates in the future (i.e., one coordinate for each multi-index level + one dimension coordinate). If you want to keep this behavior, you need to first wrap it explicitly using `mindex_coords = xarray.Coordinates.from_pandas_multiindex(mindex_obj, 'dim')` and pass it as coordinates, e.g., `xarray.Dataset(coords=mindex_coords)`, `dataset.assign_coords(mindex_coords)` or `dataarray.assign_coords(mindex_coords)`.\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "da = model.get_value_as_xarray(\"lateral.river.q_av\")\n", + "da.unstack().isel(time=0).plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can also request this discharge at two lat/lon locations along the river" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'discharge [m3/s]')" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Location A, Location B.\n", + "lats = [50.00, 49.5]\n", + "lons = [ 7.12, 6.37]\n", + "\n", + "ntimesteps = int(model._bmi.get_end_time() / model._bmi.get_time_step()) - 1\n", + "q_locs = np.zeros((ntimesteps, 2,))\n", + "dtimes = []\n", + "for tstep in range(q_locs.shape[0]):\n", + " model.update()\n", + " q_locs[tstep] = model.get_value_at_coords(\"lateral.river.q_av\", lats, lons)\n", + " dtimes.append(model.time_as_datetime)\n", + "\n", + "import matplotlib.pyplot as plt\n", + "plt.plot(dtimes, q_locs[:, 0])\n", + "plt.plot(dtimes, q_locs[:, 1])\n", + "plt.xlabel(\"time\")\n", + "plt.ylabel(\"discharge [m3/s]\")" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/bart/git2/ewatercycle-wflowjl/src/ewatercycle_wflowjl/model.py:64: FutureWarning: the `pandas.MultiIndex` object(s) passed as 'loc' coordinate(s) or data variable(s) will no longer be implicitly promoted and wrapped into multiple indexed coordinates in the future (i.e., one coordinate for each multi-index level + one dimension coordinate). If you want to keep this behavior, you need to first wrap it explicitly using `mindex_coords = xarray.Coordinates.from_pandas_multiindex(mindex_obj, 'dim')` and pass it as coordinates, e.g., `xarray.Dataset(coords=mindex_coords)`, `dataset.assign_coords(mindex_coords)` or `dataarray.assign_coords(mindex_coords)`.\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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jCXRIABEBhdIEI7daJhhN9nZ7fe7L40NdDFn5nqgRN6GaxoEg5CABRBAEQRABAsUAGQcJICKgUBNUyltJPK2wCfQYFiMtDZ7cNmrOI5ctWrydsA/i+CH37WZDy6+NwQUOTlGWbC3HE+WQACKCGn5y58IjJOUrAnFyVrtk2lc89SmX0E4JyhYdGIjFjtVL6wnCSkgAEUGHeLLOiLxXeByIogfwTYQYjVxslbuYlMPf19oscRjsmLG0/uTvyQiTsTI4dPVK8LhY+Z+e44lySAARIQHnMMbs6++J1i4lENxFpV3EpJXiMJhwX1rvqwg6+Xuy8Di1/mnZNuXvFb1fenHqdIHpOTbYIFFOEARBEETIQRYgIqjhLT85V1Ya0h8fZG32L1i7LXcHKt2JuaWrLB5JOUZbx8y0Jtnx/XS/j+Vig9wRtzl2Kln4Bf1Qw26GLVAgPEMWIOMgAUTYHm/1lNzbOqKiy594iVOxGvdJwJfXaSWZ0YMNE5R6MUusGN2vlZO/+32lqvaYQqJFd/dY4wanK/pUJ/ICtbq9nXAxDi6mYxWYjmODDRJAhO2REwmqvkA5B3KKl5syJj2/6IVf15wjYEQPYFwclV0xe3KWu4/98V6LxZf43L6Og48T+ulUCgAgTOY8fJ9q+lVqQ3FdhL/gGKPkDO4UFRUhPj4ehYWFiIuLs3o4hI9kxgwFANPEjxg1v67VuBMCgczowQCMcyfqxSxLij/dVVa4xuTOeehkA4SpqBElbtMi9Q+fzqGmrZr2dsQfcwZ/ju3f1Uf1GtrDdy9ddKFH699pfgNZgIgggxc//sKTC8uKit1mYSe3l9nuE3+6q9zvH39O/nmutTh0srI4aVqqcXW6fLGmBaLgsRInHHDqWL/kNHAsgQ4JIIIgCIIIEJjOGCBGMUACJICIoMMfri+r8Hd8BO/2sgvBvHpIbHny5TV++VsTn84z69dyN9b+Ew0xoclNlecn0wARYpAAIoICf7u+5BBPYFxYWMC7vsTixy7uLyC4g2TdXUf8812/NVU8pmuj45rOJYlNs/mKSaISWgZvHCSACMJA+AlLXBjULlmT1WJX4cOjRvgEukjixTT/Op4/5sDNjX/2ftzxawEA6U0OK7YRx6b5M54qUN8Lu+FkDjiZjhggWvYkQAKICAp4t5cdLEGAOYVBg9n94w1fJ1G5IFxfrp0d8tWIx7v91+bY/mtz4bncr3jxpJh3/FqPIsj9HGa+TvE55B4r4WlMofo5IIyFBBBhOv74BejPpe+q4QK70owdrT++4p4DR+/xVk28PRofVdUu53ia6j7FSQ398To95SNSak9UxQUOLh2rwFwq0h2ECiSACIIgCCJAoBgg4yABRJiKP9w2dnF7+YNgjKfw5TXpuZ+0HGuWVcSs95HPD/PPJt/5fKw/yrIE031LBD4kgAjTscqFYJeYmYzIew0pIBrsxSTNuk/kSjSoPYdeF5qaMXlr44lPjrUVHt/W9FtB+Gw63lpRBPFur3RH/8qVYMwlLYyqUH4m2O65QER/EDS5wHhIABGm4v5FasYv35zi5YpWICvjN3jRw1dRNwJh4lQor2Ek/sr+LCcGzCpIKkZvIK4RiAXWsCMnMbTZHlXn5YXPbU2/FR6LxVCYBy+H5DMhFkMKn009ApIwnvIYIB3FUMkFJkACiPAvFYHB7lWl9aAkfpTEl/s+f8CLICMsQUBlYUr+sRn4OwjamwvGvY0R57ODS3HYkZPC41U/dwIAjPAS8ywOgr2t6bdez+HNpaXGuqhUtNQTJJIIO0MCiCAIgiACBJfOWmC0CqwSEkCEIfj6azA9bKBuC4Yvwc/+cMWpwah4oGDH3TrjS/4YX89jRr++wLu9AGD5T52Fbat+7oQwlGdoHviPvbLHfnzsevRretBj/2otn74GQfuSkNKXYwjPUAyQcXCM0dVwp6ioCPHx8SgsLERcXJzVw7E1etxK4jgWLSLIiNw//p74xPFARgkhvddRCasrwMvdW2a+X3Ki2B+uODHLfuoKABjebJdk+5qfO8LBVS1XwQskALjrmgOSfUa5fCnuxzv+mDP4c6w62BrVaoRp7ufvi07ce/13NL+BLECETgxZGqtz0s6MGWqvBIgeEIse9+BorYJIHA9kBHwpDD3ixwihopTN2ezYJzUTvkQYcQ7T6765W4DW/tIBQFXRI4eR7wOJISKYIAFEhCRWljjgcRdDegKlhdU8BgaX2wXJUnQTxYYvZSGU3Lk+n9Pttah1bfS/Zp/qcxhlNSPBYw+cjIOT6UiEqOPYYIMEEBGQ6El+aMdfsbmlqwxdLq8VcSFUPRheWsGPZUV8zf2jRZDJvdfvHu2G+5vv9LkvJexybxPG4tQZBO2kIGiBwC5WRBAEQRAEoQGyABGWoDdmRRzz46s1yKzsvkahN1BarRtMHOsj91hvELSRlcbFLr5ggDmdANzf65145cdbAABPtPzMknER9sfFHHDpWAXmonVPAiSACMswKpZDnAlabTC0HZY/uyPOHG1WQLTYxcWLG/E2uf16kROcdrnmPO5Bzf4it3QVZn5/KwBg5ve3wsFFAwBe+fGWKm6O0S23+m1chH0hF5hxkAAi/IZZv97VWoDsbPUBjCmZ4c36Iyd6xFYfcRsjMTIrd0bEIABAbtlqYwYnMwYzLU3ivtPDBqJnRSLnZ1r9n7B99g//BABMStsEAFj0Yx8s+rEPABJCBGEUlsYATZ06FRzHSf6SkpKE/YwxTJ06FSkpKYiJiUHPnj3x/fffe+133bp1SEtLQ1RUFNLS0rB+/XozXwbhA3nONcKfUXhyh/ErdNwnND65np7q4EaTW7rKr0kSM6MHS1xf/J/ZuF97d0Hk8VjnGuSWrUZu2WpkRAyS/JmBkULIPflnnnMN8kpXocFX/0PL/3cayM8HKlxjk9I2IUz0S310y62C62PB4QzDxkQEHi5UrgTT8lc1m5RvzJ49GxzHYcyYMcI2NXN1SUkJRo0ahdq1ayM2Nha33347Tp06pXM0+rA8CLpVq1Y4ffq08Hfo0CFh37x58zB//ny88sor2Lt3L5KSkpCeno6LFy8q9rd7924MHDgQQ4cOxTfffIOhQ4diwIAB+PLLL/3xcgiCINTx0UdA48YYfv9u/GvCfqBXL6Bx4/LtBKGACw7df1rZu3cvlixZgrZt20q2q5mrx4wZg/Xr12P16tXYuXMnLl26hFtvvRXOCtFvBZZmgp46dSo2bNiAgwcPVtnHGENKSgrGjBmDCRMmAChXkPXq1cPcuXPxyCOPyPY5cOBAFBUVYfPmzcK2rKws1KpVCx988IGqcVEmaHMwK2MxILX8iC1CZiTNM3sZvZIrTI11yJc8QGa7vXjUxlnpiRMSW4CMdI0Bvt+33qxGec415SLn7rsB969friJHy4cfYl7Lt4TNT6dtFiw/m1rF2y6GKtTxZybo1/d3REx17dErxZeu4rH2e30e66VLl9C+fXu89tprmDFjBq6//nosXLhQ1VxdWFiIOnXqYPny5Rg4sPzz8ccffyA1NRWbNm1CZmam5tejB8tjgH766SekpKQgKioKnTp1wqxZs9C0aVMcP34cBQUFyMioNPdGRUWhR48e2LVrl6IA2r17N5566inJtszMTCxcuNDMlxHyeJrk+MmJc3CGT048vOjJjBkqiCFXaakpSfPUVM7Wg7vQMTs/kD/cXmquk1H12owWQ+IVaGpcYl7vOacTGD26qvgByrdxHDBmDJ4+fhwIKy958J/DmRh/bS4AYBMoI3Moo78WmLZjH3/8cfTt2xd9+vTBjBkzhO1q5up9+/ahrKxM0iYlJQWtW7fGrl27QlMAderUCe+//z6aN2+OM2fOYMaMGejatSu+//57FBQUAADq1asnOaZevXr47bffFPssKCiQPYbvT46SkhKUlJQIz4uKirS8HFugNUbFiHT53r6UzRI/7vBiyMxAVrn4FbMnokAtpKol7YCvItP93jIjJsgwMf3554Cn2AfGgJMny9v17AkAGH9tTuU4VASU22l1I2EsLnBwQXs2Z/5Y93kuKioKUVFRssesXr0a+/fvx969VYvyqpmrCwoKEBkZiVq1alVp42luNhtLBVB2drbwuE2bNujSpQuuueYaLFu2DJ07l1dF5jjpG80Yq7LNHV+PmT17NqZNm+br8G2J1i89I0ooeMv7khExyC8iKLP68PLxBEFJCLXWn0DIj+MvoSjGX/ecT5w+bVg7o6xmROBglAUoNTVVsn3KlCmYOnVqlfYnT57E6NGjkZubi+joaMV+tczVatqYieUuMDGxsbFo06YNfvrpJ9xxxx0AypVjcnKy0Obs2bNVlKaYpKSkKorS2zGTJk3C2LFjhedFRUVVbg5CO/wEJF6tY7YrDKgUQgCQc2mZKedTqhzu7wnI7okCfbXo6L2W/rjnRh+4p8q2Re28xxm+cfkNPKrmBKLvPTWQ6CF84eTJk5IYICXrz759+3D27Fl06NBB2OZ0OrFjxw688sorOHLkCADPc3VSUhJKS0tx/vx5iRXo7Nmz6Nq1q6GvyxcsXwUmpqSkBIcPH0ZycjKaNGmCpKQk5OXlCftLS0uxfft2jxesS5cukmMAIDc31+MxUVFRiIuLk/wRBEGYwfH2dXChXgyUalK6ACA1Fbj5Zn8OiwgQ+ESIev4AVJnzlARQ7969cejQIRw8eFD4u+GGGzB48GAcPHgQTZs29TpXd+jQAREREZI2p0+fxnfffWepALLUAjR+/HjcdtttaNiwIc6ePYsZM2agqKgIw4cPF/IMzJo1C82aNUOzZs0wa9YsVKtWDffeW+kWGDZsGOrXr4/Zs2cDAEaPHo3u3btj7ty56NevHz7++GNs3boVO3caV2QwGOEzCPtSVdzX1TF87hbAP66JnEvLJFagQEJrOQzO4bs5OTN6sJD9WG0mbS14zfvDOQDmkrTVi9H33Kj9lSvnXm5fae3hrUFiq5C7NWj8NxWfl7Aw1HxtBXD33WAcAyeOheY4OABMO9kAUyoCoAlCjItxcOmo6O7rsTVq1EDr1q0l22JjY5GYmChs9zZXx8fH44EHHsC4ceOQmJiIhIQEjB8/Hm3atEGfPn00vxa9WCqATp06hXvuuQfnzp1DnTp10LlzZ+zZsweNGjUCADz99NMoLi7GyJEjcf78eXTq1Am5ubmoUaOG0MeJEyfgcFQasrp27YrVq1fj2WefxXPPPYdrrrkGa9asQadOnfz++gINcRkFbyUV3JG05RyKsQhi14RfEK20yYwdJjzOufy+4acyo8aYWvEjvp5qJ3rx6i9f66nxaHFVecy6bEIZCvG1cL/vtAqil9tLV87Jub6eOig914LrK38kPI3+aP2fzhi24KQkIPpCvWhsfroNdo6rr2lcBGEFaubqBQsWIDw8HAMGDEBxcTF69+6NpUuXIsxCoW9pHiC7QnmAtCGeyLxZIsS/zP0SGC0SP4A5AggwLtCXtwD5KoC0Xks1AshVcqXKNqPjTuREt5nB7HJCnDmdiq+LtwC5CyBfmfjt3QCAOa3WlK/2On0aSE7G8zUXgoVx2HNdOMX0BBD+zAM0Z28PROvIA3Tl0lVM7Lid5jfYLAiaCGy8TVTiyUachM/f5Fx+XxBEZgkhPfi63N0Ia5o315dYIJk5McsFcxuxQlEJiUWywvqU51IWkbzwEbvCnKIlya+1X6HqvHPafggAeObbu4AElP8BmNl2Q/kDvfUKiKBFfzV4W4X+WgpdCYIgCIIgQg6yABF+w909w1uBMqMHm56NWMnSkxk7zFArkCQXEm9RUGm98NXtJcZ0N6KDgyMmxtxziBBfM/ciomaQW7bap4zb7i6wkfuHSP4D6qxBX10fRq4uwiec4CRWRy3HE+VQDJAMFAPkX5RqUhktTmTPbWJgtC+r5LRkeTaz/hWP2YHjvmJmPTk1AsiX92jk/iFeRRCVtAgO/BkDNO3LPrpjgKZ02krzG0gAyRIqAsiKdPlyk7Z4GxcZWeUYq0WQ3uvkHtgrN3H7uuzdH+IHgC1jpfjrKQ6091e2Z1+tdI/uK4+deqODcowVZW8OfEgABSYkgGQIFQEEmP/l62nZsdwkLlmtxXGSZexWCSEjf6UrWTC0CCCzJ31/WOCMwl8lLwZ/+RAAICasTLLdgfL7dMkN8hnHH9031KMIAqh+VyDjTwH0/Jd9EF09QnM/Vy6VYToJIAAUA2QYgforjgsv/yC5j9+TO4A5nT6dQ8lVITdhuU+47svXvWHGJGJW9Xctq5v8lj+pAjtagPzBPXseBgA4OOnvw7NdLgiP5e6Dh7+WJt50cOXLubyJH6X+CMIdWgVmHCSACIIgCCJAMKoYKkECyDDEq3+s/CXniyVKbOXhLUHeYhwyIu+VtVooWTP0FucU5+wRo+SuEltrfH0flM4l7ktvpmelDNu5pauEa+8pINrvmbRtjpHJNHmrDwB80HmJbJt0eH7/lVxgBEHYDxJABqHHBWa1aALUB3UqtVNy5ehZqcNfF17gqM3mLCdW1F5fuXMpCSxf+pWMz22JN4+jIgDcU1JCf2TPttvKL3+jJH7EWP15JUIXBg4uHUvZGS2DFyABZBCyFgK1dY0Mqn8kFlKerAi+5DvxF0qWFfFr8mShkUM8SfkqWsQTv7sgMKPml1gUibMum1mcVA12F0N8PJqaIOh/7RopPOaDlnnCHeri2kj4EFZDLjDjIAFkAGomQ0+WkIyIQT7/shdEDHMJx+S51vosbrQk3TMbJeECyFto1PbJ95Vd7zFsPvO6sC+7zqNV2m/+8w3JOfnzZcYOgyMxAeEN6lcZn15rkHA+kejJjBkqK4L8tepJfL3tKIYEwe/BJcgLn3VdX6uyr/+uxwCUW30G7q56HxAEEbyQACIIgiCIAMHFOLiYdjeWnmODDRJABqDXLC6ujK72lz1vucmIGKSYQ8abNchO1h9PQca+xlfJWXQAIDwxsbJNvfJf/nAxibWHP9a9D0f1WOHx5hMLkZ06urzP+inl+YoAZDccg80nFqoao2qYS8iULc6Sbab1R866o+QSDCTcrWn9dz2GtV3LLYFk/SECBScccOoo46nn2GCDBJBN8HV1jySJoNKKIRsJHH8hFi5iYaMW/pjsOo/i6l9/VdnPi7DNJxdVPXfDMT6fzxs5V1ZKSoWI7xN/ZT/mEQsfO+QHUpsN+1JZZXC5e3wVL3zWdPH9XiEIIrAhAWRDvMUDBdsSaE9xNErxQOF1aldacQDAVR7UqkX0yPUvNxZfURJEWq1E7kVj/bEiTO69sUuGaLHlVC1q4qsIws6QC8w4SADZDKVSEeJ9Wr747YivAcSOmBjB3SQOYjYSo1b5KLnDshuOEYSRWiHEi57M6MGCNYiLikLOJfNzzohdk3Z0fV3ZkgoA6L1trOz+T3vN93g8bxEiIUQECi444NLhxtJzbLBBAsjGuAsdfxXANBO9q6bMmPSNWtK++cRCQdxcPfW7YhseX2OGxNYfAMisXl52wV9CyG4usO6f/hs7er/osU16/lPI67kQAJC5fQxyeiwU9rm7xAiCCC1IABEEQRBEgOBkHJw63Fh6jg02SADZHDmXWKBafwB7J5IzYmy85UdNX2KLEf9cLdnXTvKL5UeMZCVYhfUps/pwVePonDMJezJnGz6mblufBgDs7DNP0/HsanlV98yYocLjQP58EcEPxQAZBwmgACLkv5g5TnZJuB6sLkPCix5xbJD7fnHMkOTxtZMq2x02XlyoxZsrjhc/nXMmye7nRBXXd2fMUX3eHb1fFASQJ9Lzn+LPJGxzj6HLKV5ualydkptVKau4nX8oENbCdFaDZ5QJWoBjjDHvzUKLoqIixMfHo7CwEHFxcVYPh6hAvPTbfUWUVowUQEb25esKMrEYqnKMn8QRL4QAqRhSa/3pkjtReOyLEALKLUHerEBqY+j0xNqJiwKL67wpZYK3WoATxuCPOYM/x8Pb+yOyeoTmfkovlWFJj7U0v4EsQIQO/PHlrfSr3D0/jlYxpKd6vJn4ulReLHKyr50kPPckjIxGLHoyqw/H+Q/Ly4V8laVOgO3OmCO8FzflTJDs+yJ9bpX2akSPO6qSjPqYmNS9jRrhI+y30T1HBAZOcHDqKGiq59hggwQQQRAEQQQILqYvjsdFPh8BEkCEbVEb9G1UPJAW9C7rNwve8mNVbFDOpWVos3GK5uPdLT435VVahPiYoZ195qmKAdIS2yPOuK3meN7q483iQxCEfSABRFiGt4klUIK+7SR8BGz0M8+IeC05FxigffWXWtTcg2IRbFdBTAQPLp1B0HqODTZIABE+IY5vAOeQPhc2c7ITh5Lg0SJ0xPE/RqE2pikQJrnNR3wLIvaVFh9NFx4rGeN/vGta+YMrvosg8XuhN9aMVYhBs6wzdr0HiODEBQ4uHXE8eo4NNkgAEQJKwZvuIkfNRCIndoy26Bjl+vJUid7bMXZk8+HZprjAxKLnyF3P+3SsOGjd0/smfi/IskIQhJmQACIAVP2VrSiGVIoEf7ivjMgJ5OvEavdly9ktKpaSO4z9ldfio+k+ix53xDXNvL1nRl5j8bJ0itEhAh3KBG0cJIAIgiAIIkCgGCDjIAEUROgp6un+i9tOv5Tl4owcEcbdur7E/djZ+sNjdvyPXpiLISPyXgBAbukqv503z7nGpxw9BEEENySAggh/TM7+FgDubgteiDCn0zA3mxpxEwjCx2yMKtmQW7pKEED+dimK3WEkhohAxAWdtcAoCFqABBARkIiz9eoVQiRuvMMYZ8p1sioTt7vgITFEBApM5yowRgJIgAQQYXsoyZx3hOBnt8d63WHN170AADj6r+d09SMmI/JeievLDgI0z7lGEGKeCpcShNVQNXjjIAFE2A6lZfdmuEv8Man5w83DCx1e/PDPr31+AQ5Pf0rxOHd4wcNjpPCxOyRwCCK0IAFEEARBEAFCqKwCS0hI8Kk9x3HYv38/GjVqpPoYEkCEbfHm8hLXa7Jz2QxxnIv7djFyq9089iu6Pjc8ML/8Qbe6uFyfw7XPLwAANJixC9fKHCu2CrX4aDqYyCweSlYfggg0QsUFduHCBSxcuBDx8fFe2zLGMHLkSDidTp/OQQKIMBylidxTdmmldmrILVttybJqX5AkmZSLNeEcPr9uQfQA+PqdsZJ9SoHFLacsEP6z6y4C8D2rs1aMClonCCI0GDRoEOrWrauq7ahRo3zunwQQIUu6oz/AlZtK1UzMaspouLcJ5pU3VTJrG7SEvOOIStHD/47b+95Y+cYy/Dit0vJzS++KAOm7fB4GQRAWESq1wFwul0/tL1686PM5SAAREsSWA8FS4W6tYRU3JlfpS1YSMJ6ETTCKHqXnRgTYdhwx36vY0ZMMkyAI+xMqLjB/EBjRUARBEARBECLOnz+P999/X/PxZAEiZFG7dNvXwF2tYwGUrSjueWX8jdmVynm3lxpXl1LAtTu39J6Dzz6dKHkOQLLNSPj4H4Ig9EEWoEpOnDiBESNGYNiwYZqOJwFESOAn8HRHf1VxK2a7sexefd2s8YljfXyJ8QHUizAhBshPUPAzQegnlARQUVGRx/1a4n7EkAAiZFGaRP0pSOwufvyFLxYgX5CzAJkJrQIjCMIXatasCY5TFmyMMY/7vUECiPAJdxeLGQLF10BecXFNf7jC/BFozIsdsSXISNxdXfxzd9eYUYhrt9k9bxNB2JlQsgDVqFEDzzzzDDp16iS7/6effsIjjzyiuX8SQITPiN1kRmN3q48VhTuNtvy440/rD0AWIILQA4O+pezMuKGYTvv27QEAPXr0kN1fs2ZNMKb9FZEAIgiCIIgAIZQsQPfeey+Ki4sV9yclJWHKlCma+ycBRGjGSCtIIOWv8Yf1x6y4HyXMWv0lhiw/BEH4wkMPPeRxf7169UgAEYGJUdmR/UEgCTS19L5ldvkDHUGEatC6BN4Kd6Odx0EQQGhZgOQ4deoUUlJS4HDoT2NIAoiwjECZUMwO+ubRs/TdV3rfMhuffjbJtP7F+aE4Byex/qSHDZSWS1EQl1qvtS/vl7e2wSh8icAm1AVQWloaDh48iKZNm+ruiwQQEfCkO/qDC48AUDXY1qil12atduP79Zf4Eaw+JiGXGJO5mHQfc5kuKtX2qSagP1CEOkGEAnqCnt0hAUQQBEEQAUKoW4CMhAQQEbCIf7Xz+X/EFiCjyi+YZQG4MLyLX91e6WEDge7Xm3oO3rUltgTlOddUcXuZOgZRriq1LjCy8hCBAmMcmA4Ro+dYOzB58mQkJCQY0hcJICJgkZu0xG4v/rnd8PcKL16MiAVI716z0btXuTvs023GxwK5ix1/iR937J5XiiAI35g0aRKcTicOHjyIRo0aoVatWpr7omrwRNBiR/Ejxqwsz2J4y4u7ADFD9NiJPNdan4QPBTsTgYILnO6/QGPMmDF45513AABOpxM9evRA+/btkZqaivz8fM39kgWICD64cl1vdZV4MXJix18WoFDGkzuMrENEIBKKMUAffvghhgwZAgD45JNPcOzYMfz44494//338cwzz+CLL77Q1C8JICLoEOKBKuqD2Q1/CB+51Vju8FYg3hXmqU2w4c3iI7gNSSARhOWcO3cOSUlJAIBNmzZhwIABaN68OR544AEsXrxYc7/kAiMIgiCIAIEPgtbzF2jUq1cPP/zwA5xOJ7Zs2YI+ffoAAP7++2+EhYVp7pcsQERQIbb6WO3+ElsZalb8z3Ot9evKLzXBx2Irj9gaFKzWH4IIZELRBTZixAgMGDAAycnJ4DgO6enpAIAvv/wSLVu21NwvCSAi6LBS+Pgra7TaMfjKp9smCSKod6/ZwSGCOBlDN+dQJQ79uXyfINQQisvgp06ditatW+PkyZPo378/oqKiAABhYWGYOFF7HUMSQIQlGB2Aapd4H2+vqeOI+X6JAdJ6bYPdAiSXEoAgCPtz9913V9k2fPhwXX2SACIswZdkdd6w02ovJfyZ+0fPtRVbgIINtdYcNQHkBGEVTKcLLBAtQGZBAogg/ITD5QLy84HTp4HkZODmmwEdAXwEQYQeDICecljGVdIKfGwjgGbPno3Jkydj9OjRWLhwIQDgzJkzmDBhAnJzc3HhwgV0794dL7/8Mpo1a6bYz9KlSzFixIgq24uLixEdHW3W8AkNiAtRqrVUyLm67G79AYBev32LcV9uAN4vrNzYoAGwaBFw112WjUsOYXm8yRXj/UFm9GA4Isq/5pjTqao8CrnHCCI0sIUA2rt3L5YsWYK2bdsK2xhjuOOOOxAREYGPP/4YcXFxmD9/Pvr06YMffvgBsbGxiv3FxcXhyJEjkm0kfuxFethAgLmkz93gHFVNtczpBGBedXYxhp3jo48wd9uyqr+8fv8duPtu4MMPDRNBRmQ0NrtivL/JubLS6iEQhGG4wIHTkc05EDNBm4XlAujSpUsYPHgw3nrrLcyYMUPY/tNPP2HPnj347rvv0KpVKwDAa6+9hrp16+KDDz7Agw8+qNgnx3FC0iTCepQmZbHAEAen8o/dS1mYXa5AMh5Hf2NWdDmdwOjR4ICqXzuMARwHjBkD9OtniDtMr2gLBqsPUG75AUj8EMFHKK4Cc+fMmTMoKSlBw4YNdfVjuQB6/PHH0bdvX/Tp00cigEpKSgBILTdhYWGIjIzEzp07PQqgS5cuoVGjRnA6nbj++uvxwgsvoF27dortS0pKhPMBQFFRkZ6XRIhQ694SVxG3gwtCrmyC0j6PfP45cOqU8n7GgJMny9v17OnjKH3jlvQ5QKXRDZ99WnX5KOPs8eWoRjQrkRk9mIQPQQQBFy9exGOPPYbPP/8cPXv2xFtvvYWnnnoKr7/+OjiOQ7du3fDJJ58gLi5OU/+WCqDVq1dj//792Lt3b5V9LVu2RKNGjTBp0iS8+eabiI2Nxfz581FQUIDTp08r9tmyZUssXboUbdq0QVFRERYtWoSbbroJ33zzjWLs0OzZszFt2jTDXhdhrLXGDrl13K1Dcttl8XCvamqng8/yJpaLoApu6T3HQ2trqSJAK6yCYlep2FrIOTjbF79Vg/vqPTvc+4S9cDEOXIgkQpw8eTL27duH8ePH46OPPsKAAQPwyy+/4PPPP4fL5cLIkSMxd+5czJw5U1P/lpXCOHnyJEaPHo0VK1bIxudERERg3bp1OHr0KBISElCtWjXk5+cjOzvbY+rrzp07Y8iQIbjuuutw880347///S+aN2+Ol19+WfGYSZMmobCwUPg7efKkIa+RIJCcbGw7giBCGsb0//nC66+/jrZt2yIuLg5xcXHo0qULNm/eLBoPw9SpU5GSkoKYmBj07NkT33//vaSPkpISjBo1CrVr10ZsbCxuv/12nPJkGa/g448/xmuvvYZRo0Zh5cqV2LhxI2bNmoWbbroJN998M+bOnYt169b59oJEcIzpWVCnnQ0bNuDOO++UiBmn0wmO4+BwOFBSUiLsKywsRGlpKerUqYNOnTrhhhtuwKuvvqr6XA899BBOnToledM8UVRUhPj4eBQWFmo2rYUyWpIcekpQZ1S+ICNRPSanE2jcuDzgWe6jxnHlq8GOH/f7kvheGXOFx9tyJ/j13HpwtwLx8Cu8uIossQCQc2mZ/wZmIJ4sqFo+B3b8DAUT/pgz+HO0WvNvhFWL8n6AAs6/S/D9wBdVj/WTTz5BWFgY/vGPfwAAli1bhhdffBEHDhxAq1atBAvM0qVL0bx5c8yYMQM7duzAkSNHUKNGDQDAY489hk8++QRLly5FYmIixo0bh//973/Yt2+fR4NGdHQ0fvrpJ6SmpgIAYmNjceDAATRv3hwA8NtvvyEtLQ2XL1/WdC0sc4H17t0bhw4dkmwbMWIEWrZsiQkTJkguSnx8PIDywOivv/4aL7zwgurzMMZw8OBBtGnTxpiBE17RIn6U4n7MDnzWisRFUVFqQfY1hIWVL3W/++5ysSMWQXy8zcKFluQDEoueXpmVYoi3kOdv8V0U+cNlo3SviIVPoCPnAiMIwP9B0Lfddpvk+cyZM/H6669jz549SEtLw8KFC/HMM8/groqVrMuWLUO9evWwatUqPPLIIygsLMQ777yD5cuXC0VMV6xYgdTUVGzduhWZmZmK505MTMSff/4pCKB+/fqhZs2awv5Lly4JZTG0YJkAqlGjBlq3bi3ZFhsbi8TERGH72rVrUadOHTRs2BCHDh3C6NGjcccddyAjI0M4ZtiwYahfvz5mzy5fujtt2jR07twZzZo1Q1FRERYvXoyDBw/6ZDEi/IxoObw7dv/Fmuda6z1z8F13lS91Hz1aGhDdoEG5+LFBHqBtOVXFTs+suT6JIKPLm/hCVlxl7q9AtfrIIQghHYsDrHxfCOMxSgC5L/aJioryKiacTifWrl2Ly5cvo0uXLjh+/DgKCgokc3JUVBR69OiBXbt24ZFHHsG+fftQVlYmaZOSkoLWrVtj165dHgVQ27ZtsXfvXrRv3x4AsGqVNOfb3r17ce2116p74TJYvgrME6dPn8bYsWNx5swZJCcnY9iwYXjuueckbU6cOAGHozKU6cKFC3j44YdRUFCA+Ph4tGvXDjt27MCNN97o7+ETQYycS8HjJHXXXUC/fnjktlF4c+jNAZEJOn/LBPTMnlf5fPPTFo7GO8EkfABlV5+qYyl4OmgxKgiat6rwTJkyBVOnTpU95tChQ+jSpQuuXLmC6tWrY/369UhLS8OuXbsAAPXq1ZO0r1evHn777TcAQEFBASIjI1GrVq0qbQoKCjyOdeXKlZL53Z169eppDoAGbCaA8vPzJc+ffPJJPPnkkz4ds2DBAixYsMDgkRGEAYSFYV/yP4B77rF6JARBhDgnT56UxAB5sv60aNECBw8exIULF7Bu3ToMHz4c27dvF/ZzbukzGGNVtrmjpk1CQoLH/dnZ2R73e8NWAogILewWmCl2FShlhZZzJwg5jBz9ccMD86v0+/U75hdANQux1afHP8utQds3PS3r9rP6feTdYFuK3tPdl10sKHpyYln9fhDmoGUll/vxAIRVXWqIjIwUgqBvuOEG7N27F4sWLcKECeUu8oKCAiSLVrKePXtWsAolJSWhtLQU58+fl1iBzp49i65du6oe95UrV/Dtt9/i7NmzcLmkYRO333676n7EkAAiLMGOwZ2eqqiLx5seNlB2cslzrcUND5YLoK/frhQ9He+fLwQWB7IY4rFLskp3jBA+gD1iZrReY0GYcpZlOCFMplwA6YkBMmIMDCUlJWjSpAmSkpKQl5cnJBsuLS3F9u3bMXdu+cKKDh06ICIiAnl5eRgwYACA8vCW7777DvPmzVM8h5gtW7Zg2LBhOHfuXJV9HMfBWVEiyVdIABGWYfUkI4fSmOTKdgDADQ/OF8TODQ/MlxU4e98dWymg3jFwsH6kZ/Y8bLd5DJBevAaz+xFxkkf+udrjAHu9FiKwmTx5MrKzs5GamoqLFy9i9erVyM/Px5YtW8BxHMaMGYNZs2ahWbNmaNasGWbNmoVq1arh3nvLC1fHx8fjgQcewLhx45CYmIiEhASMHz8ebdq0EVaFeeOJJ55A//798fzzz1eJN9IDCSDCr9jR8qMF3tJT693duAFV3V7ueHKhBQL5m58WAqK1BkPbxa0khx1XWeU51wi5jexqdSP8j7+XwZ85cwZDhw7F6dOnER8fj7Zt22LLli1IT08HADz99NMoLi7GyJEjcf78eXTq1Am5ublCDiCgPDY3PDwcAwYMQHFxMXr37o2lS5d6zAEk5uzZsxg7dqyh4gcgAUT4GbtNfFo4P6KT8NjX1xMMr79n9jxdK8Lscg0yoweDucr9AZxDeVLwZk3xx+sh8UPwsIo/Pcf7wjvveDZbcxyHqVOnKq4gA8oTGr788sseKzJ44u6770Z+fj6uueYaTccrQQKIIAiCIAjb8sorr6B///74/PPP0aZNG0REREj2e1strgQJIILQgDjIOVTgrT49s+f57A7zt+szM3qw1zbMxZBbWplYjXc3uaOYpdwPcTZ8gdeMiEGqir1S7E/w428XmB1YtWoVcnJyEBMTg/z8fMnyeY7jSAARBI/RsSYd76+M8WGO0BQ/YsTxQGrcYf5KdyAnenKurFR9vK/V5OUCjq10VVGcUIjgbx+YDXj22Wcxffp0TJw40WNiRF8hAUQEHZIVWwqWB75Nx/vnY++7lYJGnMeHq/iiEO9PDxsIvG3kaAMTufxA4X9fxaf5kwGYF/CcXedR2e1cVJRhy+B9Jc+5xtLgfrL6mIua9/YqK/PDSCrQaQFCAFqASktLMXDgQEPFD0ACiAhylCZf3qqz992xEgtPraW7vR4bSJi98iqr1oOIqXhcdl1T9O45q/xJj/b4dNskw87DC5/Nf75hWJ9mYOb15l10vlqqCP14ey/5Su2EOQwfPhxr1qzB5MmTDe2XBBARkvBWHXcLEN6tfGi3TNVaECd3NHK5dlatBwEAW84rm8N4McRbhXwhu86jYKIiuVvOLfG5D38id12NvN65ZasFAZQZPRiusqtVx0Dur5DAqEzQgYTT6cS8efOQk5ODtm3bVgmCnj/feyoSOUgAEQRBEESAEIpB0IcOHRIyTX/33XeSfd7qiXmCBBARMohdXTwS648K+Ay9gfprm48X0TJ+3urjvk3RCqTiiymr9sOi5pX+fbu7utRgtOWQEyWNC9T7L5AQx1Z5iyUkzGXbtm2m9EsCiAhqjBA9cugREv5ALhbFV+HmLng8ubt8RSx87O7esgt80kbx0n0xmdGDfVr1Riij9rPCf87WXfBjjRvG6QtkDkALkFmQACKClirxPT7gKX5DXKfJrtYgpbHz4+YcnCSYVs66Y6TgEaNW/Mj96g7VX9wZkffKPhbDOTghFQAJIW34uqKOvx+LiorMGI4soRIDdNddd2Hp0qWqK9YPHjwYCxYsQN26dVWfg2MsUC6H/+Aj+gsLC1VffEKKL6thjFw5I5k0OQcuDCsvW7H3Pd+FkNogaLtbg5QQJ/5zVK8uPHYWXQRg3OvpfctsMI5D5DfHACiLHnfBE6piRw/iXEgkgnxDTz4nf8wZ/Dkavf0cHNWiNffj+vsKfnvwBdvPb2FhYTh69Cjq1KnjtS1jDKmpqTh48CCaNm2q+hxkASIIgiCIQCFEEiEyxtC8eXNTz0ECiLAcpcSFai0AniwHHUdoWx7pC+KMwHa3AmXGDgMA5Fx+X3CBZcYOA5xOoY3Rr+fTz8rzAWXeMFX4n/N1+WM7V4gPRHirT2b0YHKHqcDd1W33zy8QOqvAtAQ+169f36f2JIAIUxACb33MkCsnhrz1ZdbEKT6vr2LMjpN5Zuww5Fx+v/xx9eGSfeIsyma59HjRk3nDVEEMOdq3kmznH5uNnd8nIxCLHvcSISSIpFAmbXvSo0cP089BAogwFXEiPl8nGznho3XC6jhivqY4IP6cal6D1SURlBBbfXhyLi2rFEHuy9UrEhCaZZ1xFzm8GBI/NksISeI8glT8uOMueDJjhlbuK17u7+FowsikkhI4h2xNN9sTIG4su0MCiDAdvULGCtGjhLcvYi1WIzPJrD5cInzE5FxaJrtdTS01I/GXBSgUxY8cYtGjJIaC3UImJqCED0LHBeYPSAARfsWfX6h73xsrxADpFUKBPBGI3V1KoieYCdRVev6AFz2ZMUP9br20g8gSp7QIGEIkCNofGFtalSAIgiAIIgAgCxAR1PCWH3FGaCMyQdudrLgRVbZpsf4EsuULMG9lnl1cnEbiiCrPLZNTvFxSQFeMntesp68811pdeXqUyIgYBM5R7hISJwa1N1zFn57jA4tp06ZhyJAhuOaaawztlwQQERIkfHAAF+5u57fz6Qn+1oO78AlFl5eZmPGe2sEVlFO8XAiWN1LcmRV3pcet6Z5JO3CETwUh6AJbt24dpk+fjo4dO2LIkCEYOHCgqgSJ3iABRCjiLWhZT84eM7/sxYGdPDnFy9FpqPk5gcxAzXXmhY94OXugkfP1VMmKMPd9vmBGXIehwsDG+Y+MGI8Z1hpxP76WoqkieirqqWVEDPJacoUylFvPt99+i++//x4rV67E/PnzMXbsWPTp0wdDhgzBHXfcgWrVqmnql0phyKAnrXkwmsYB4+sy6Z0A5EQOj7elvWIh9OVy89xhRos9pWuWFTcioIWPNzIiBoFr3aLK9pwD0xSPMTLwWe591PI5t7PoAYDsxk+VP7hSgs0Fr/l8PF9ahS/aCpgTeJ4RMUg4R55zTZXyH+Ln4rEoFZEVozXXmD9LYaS+NhWOGB2lMIqv4OTIqbYvheGJL774AqtWrcLatWtx5coVzbXYyAJEEARBEIECVYNHbGwsYmJiEBkZiYsXL2ruhwSQwVgV+2E2RueGUVP+wpOVB/A9iZu/LD9mIblmIhdDWKw286+/4N0U4uKrPGrjL+SsPZntpshuN9L95W7p0frZtotlOLvhGMV9m08sLG+T/Diykx+v3H76Va/9SgrrRkdpHp8auMhIIYw3M3qwbPkPAHCVXfXZAmWH94iQ5/jx41i1ahVWrlyJo0ePonv37pg6dSr699c+H5EAMgG7JcMzGqNfnyMyUnjsLnoCJVOtv8lzrhHy+zCXy+LRlCMRxlxlhg1e/IjFDj9huosiuTZKIinnwDRktpsiPM5q8wwAILxF5UqR7LTJYKJM11u+n+nTa9KDv11ean6YhDeoLwgdJcSCx10MuS5eAueomj3FERMDVlFPLufy+0JANf+f3+4L4tIt4r4UE3u6ZbxODxtoSiyS1TBW/qfn+ECjS5cu+Oqrr9CmTRuMGDEC9957r891v+QgAUTowtcveYnAqSi54K/aRLzVJ1CDocVkxY0QJiI7xv+4TzbuIkZJ1IgFkS+rc3jxAwCbf5il3K7VM4r75MSRXouuP38AeTqXEN/jI+7WH7XxZnIiRSyGxG3ct4v36xFQ7vegnGVQLrBa7lhbEYKrwHr16oW3334brVq1MrRfCoKWgQ8264l+COciNPcTjNYfJdSslFB0aTGXX0QQL3wC0f0lh3jJu91EkJnWT/5eE1sO9d4/noSRGDUWJDu6wMUCaPOvCzT3Y1TAvR5hYwSKblJW1Zqq5n30ZxB0g5en6Q6CPjVqSkAHQRsFWYA88HHh+7puELOSsJmJnEXHk2mdb+MpRkip3hC/3QoLUKCLILlEh3bArHIK4n658PIfJUbeN2pdY9lpk6tsE1uc7FgMFwBQsRrKm/vLKxxniHhxt+74GzXfy7Z9L0M0CPrUqVPYuHEjTpw4gdLSUsm++fO1WfVJABEEQRBEgMCx8j89xwcan376KW6//XY0adIER44cQevWrfHrr7+CMYb27dtr7pcEkMkEjF+5Am8rXpRWxbi3U7L6iLEqwPnL5WODwh3mvHQJgL1cLWqshr7ifo+JV/r4G7G1h7cGZbV6Bs7DR4Xtdno/3MluOMZnK5B7XJZRlhsrXF++YNvFLCEYAzRp0iSMGzcO06dPR40aNbBu3TrUrVsXgwcPRlZWluZ+SQCZSEBWGhYh96F33ya3gssRFe33AGdv2D0JnVoCKeOz3lgYpfdMvOzZfZtfcZbf41uOzKlMAuh02i4GKDt1tPB488lFPh2bHjZQsVaWWgHDv0+usqvSHTLxNu5YeQ3t9j6GMocPH8YHH3wAAAgPD0dxcTGqV6+O6dOno1+/fnjsscc09UsCyGR4q0+gL8n09qtbPAFlxgy1jfDhEa/mSXf0B4Z0sXhEwYmRQtPb8eJ7LCPyXlWZfo1k85E5AIDsFhNlV6xZLbp54eOr6AGUM2nzqReAqsvUhe0K3xVavvOsFCG2FT4hGAMUGxuLkpISAEBKSgp++eUXYUXYuXPnNPdLAshP8B9+uWRwYqz+0vSGGmFj19w9/PXsNHQ+vnw/cF1fgA3N8rD/vWsWm4/MQXaLicJjHnfR7fdronGBr5LVWhA/FXmVFAvtinJA5RQvF+pw6RGpoXpvyRKCLrDOnTvjiy++QFpaGvr27Ytx48bh0KFD+Oijj9C5c2fN/ZIAIgiCIAjCtsyfPx+XKmIep06dikuXLmHNmjX4xz/+gQULtKd1IAHkJ9yDQt0z49rxF45c3h5x6vlAJhCDoMVL38XWBf651Vg5htzSVYKlwd+uMACAQ96tYOn7UmEBym7wJDafWuzToXLuKt7iw1uxFd3inENiBRYqr7tVZFc1Dhvc17YjBC1ATZs2FR5Xq1YNr70mX6z3gw8+wO23347Y2FhV/ZIA0oivq1zkPshidxgXFgYAQjp5O2FXl5ZWxKKn07DAcoeJg59pcrAH2ddOsnoIAr7W8NKD2h9CWoQP4YEQFEBqeeSRR9CpUyeJYPIECSCNeJp81AbuydU94sLCpHFCFf50I3/VysUh8cnlhJUZXNV6P4T/sXO2ZzthRRC0mM2HZ1t2bh694kcp8NlIxGLIyveLCE58LWxBAsgEtPwy91b3yP1XlM9mZZGwkTuXe+FJOwbZhgri99QRHUXCxyYofSY2H54tWIHUCqHsepXLdjefeV3XuHjho8fiozZdh7dFHHKIhY6lbspgIQRXgZmFJgF0//33Y9GiRahRo4Zk++XLlzFq1Ci8++67hgyOqIRdLZN8+Yq/SLR+qaSHDRRcb+ActnS/mUWnYRUxQDZ1f4nfS6FkSJC5IgMRJdd3eIt/ACh3hymJIDnRI96mGa2rvRz9BUuvL1YfX4rUqhqHWHwxF/3w8kIoZoI2C01+jmXLlqG4uLjK9uLiYrz/vr2zexIEQRAEQfhkASoqKgJjDIwxXLx4EdHRlRVpnU4nNm3ahLp16xo+SKKqW01sIVBj+VEycfNWH3HCRrnzEeZAAaLeEd+7nMJqK6OtEnKo+UyoCYjefOZ1ieVHizssO2mkqnbe0BLv4+4u14L4vncfg91WN9oOCoI2DJ8EUM2aNcFxHDiOQ/Pmzavs5zgO06ZNM2xwhHYUffoeTMyBWL1eLV0HvCR5XvP/fVP+wAKDpS+BoOJUBGrqqwULgZw13RvZ9R6TFTrZ9R4TxJDsfpHo2VwgvwzYbHLLVmuKAxKOF93v/Hvs/r2jVGtQbj9BiGnUqBEiIiJUt/dJAG3btg2MMdxyyy1Yt24dEhIShH2RkZFo1KgRUlJSfOmSMBClSSNUf1F1HVgpenb9d5xEQLhKrgBQn87AyOvmSwB7TvFy2RigzJihQSOClMR6QAofTmqhkovxUbLyiC1DskKoItZHb9C0VvyxSsydUPq+UgsHnTFAho3Efnz33Xc+tfdJAPXo0QMAcPz4caSmpsLhoKXSdkNwZakUPYFcrFUOiehZM062ja/CwcjK5loIFqHjjYAUPDLwVeI3/zALSKxV+VgF7uJGTkApWZB8Ra24MM0aJyqGSoVHCU/UqlULHOddunEch7/++kt1v5pWgTVq1AgA8Pfff+PEiRMoLS2V7G/btq2WbgmCIAiC8EQILoN/7rnnMGPGDGRmZqJLl/JC1rt370ZOTg6ee+45iTfKFzQJoD///BMjRozA5s2bZfc7Q2g5tdWo+XWmJqdPoP/6VmP50Ypdf5XafXm8Fe5FK5C8Ts4hfJay0yYLlh+tVhur3F1yGPkdIf5OopxjPhKCQdBffPEFpk+fjieeeELY9uSTT+KVV17B1q1bsWHDBk39ahJAY8aMwfnz57Fnzx706tUL69evx5kzZzBjxgy89NJL3jsIEYz+YMu5q5S+lMS1otzH4P6FHUiIhY4Yo0WPmRix8ksSD2TT+mzBPKmpcTG7u708BTjblWBzkROBSU5ODubOnVtle2ZmJiZOnKi5X00C6LPPPsPHH3+Mjh07wuFwoFGjRkhPT0dcXBxmz56Nvn37ah5QIKL0S9eIgpW+iB73scidL5B/bZlp5fEXZi17dy9MaUdBFEz4+hmSBDi7reYyIpOzWeQ51xgqgrz9KAvU7ya/EoIWoMTERKxfvx7//ve/Jds3bNiAxMREzf1qEkCXL18W8v0kJCTgzz//RPPmzdGmTRvs379f82ACGaUPrvuSTm8fcPcvG1/Mzkr9B9MqMF+Fj1xFe39jdv0jd7GTEXkvlRywIWLLDy+CspMfF4SPPwuZWoGnH4qEekIxE/S0adPwwAMPID8/X4gB2rNnD7Zs2YK3335bc7+aBFCLFi1w5MgRNG7cGNdffz3efPNNNG7cGG+88QaSk5M1Dybo4RyVAoe5ZN1PvvrZg0ncKKHk9vKGeKm4khAy+voZUaJEL+JzU/FJeyKXx2fz6VcFESQWRsFEsH5HEeZy33334dprr8XixYvx0UcfgTGGtLQ0fPHFF+jUqZPmfjXHAJ0+fRoAMGXKFGRmZmLFihWIjIzEsmXLNA+GIAiCIAgPhKALDAA6deqElSuNde1zzNf68TL8/fff+PHHH9GwYUPUrl3biHFZSlFREeLj41FYWIi4uDhVxwSKDzvQYoC6DnxJc7yPe7JAs7PKZkTeK0lyaBeLix2sQO6rFcVJ9azI9muXz4HY7SXGTtafULAy60XLnKH1HI1fmAmHqAyVr7iuXMGvzz1j6lgDBdUWoLFj1VfNnj9/vqbBBDL0xeAdXycdPa4voOrycLPfI7HrSalmlRUIoixikKSOkxE1nTyhJHrEpQ/cxY8/P0d2EEFitxdEiWWz648COA6bTy22aGRVsfpaEYQ7ffr0wbFjx3Ds2DFNx6sWQAcOHFDVTk22RiJ08eXXJHMAuz/QvtpLEvfj4JBz2fzCX7zwYa5Kw6pdlqmLRY+4nlNGxCDNIsjd0sULQOZ0Volnk4tvs2pSdV+haSVy1p7sBk9aMJKq2OUaEZWEWhC00+nEzp070bZtW9SqVUuy784778S5c+c0922ICyzY8Ic50yrs8KuXR8lt2OWecsuPHvHjTmbsML8IIMk5K5am51xZWWWZOr/dDqgqbqmQL0ps9QLKhY87dk6yKUzwogSG/kYQOxxXWe/LzfJjtaXMivMGEv50gTWZNku3C+z4lMkBNb9FR0fj8OHDaNKkiaH9BlYWPIIgCIIIZZgBfwFGmzZtNLu5PKFpFRhBmAVv/TGanMvvIzN2mPDYH4gtPOLHvDXITq4xMb7GBnkLrNaT28pshHIMfs54nF3n0conUZEAgM0nF0nipCRYaKEiqw9hNTNnzsT48ePxwgsvoEOHDoiNjZXs12rJso0Amj17NiZPnozRo0dj4cKFAIAzZ85gwoQJyM3NxYULF9C9e3e8/PLLaNasmce+1q1bh+eeew6//PILrrnmGsycORN33nmnH16F/bHjl5nEvD+ws6GuLwkue/z04UWPnFvMDhgdFK200stOuGc8NlNsZNd7DKiIFRMnR8yMGSo5rzhYnCB4Qi0GCACysrIAALfffrskzpgxBo7jNNcftYUA2rt3L5YsWSKpIs8Ywx133IGIiAh8/PHHiIuLw/z589GnTx/88MMPVRQgz+7duzFw4EC88MILuPPOO7F+/XoMGDAAO3fu1JUwifCOqlgSEXJirMu9JtaSs9HKLB5xnJD7Nh47WIlCAWFlWthAyTJ9rYjj7STlL9xqgSkl6STxQ8gSgnmAtm3bZkq/lgdBX7p0Ce3bt8drr72GGTNm4Prrr8fChQtx9OhRtGjRAt999x1atWoFoDwavG7dupg7dy4efPBB2f4GDhyIoqIiSaX6rKws1KpVCx988IGqMQVzELTR6FlWLRZMF+/uCMDYwGcAgtsL8J/rSwviSTAQCp0GM1osL5J8PvxXquiXqpq8Pu55q4jAwZ9B0E2f1x8EfWx6YAVBm4XlFqDHH38cffv2RZ8+fTBjxgxhe0lJCYDy6G+esLAwREZGYufOnYoCaPfu3Xjqqack2zIzMwW3mhwlJSXC+YDyG41QRixceLGjZSm1uL3WnD9qcRUX23o1C0189kGtO0xsqXPUqgnAXgkMlQiUpK2EAjpdYIFoAQKAzz//HG+++SaOHTuGtWvXon79+li+fDmaNGmCbt26aerT0lVgq1evxv79+zF79uwq+1q2bIlGjRph0qRJOH/+PEpLSzFnzhwUFBQIZTjkKCgoQL169STb6tWrh4KCAsVjZs+ejfj4eOEvNTVV+4siCIIgCLMIwVVg69atQ2ZmJmJiYrB//37BYHHx4kXMmjVLc7+WWYBOnjyJ0aNHIzc3V2Ll4YmIiMC6devwwAMPICEhAWFhYejTpw+ys7O99u2ejJEPlFJi0qRJkkzXRUVFJILc8PaLWE/grJ5yF16pCHymX7uhhV5rn3swsvs2sWsyK+EhsJJSrUMVyClerugK1YudrZ8E4Y0ZM2bgjTfewLBhw7B6tchz0LUrpk+frrlfywTQvn37cPbsWXTo0EHY5nQ6sWPHDrzyyisoKSlBhw4dcPDgQRQWFqK0tBR16tRBp06dcMMNNyj2m5SUVMXac/bs2SpWITFRUVGIiorS/6KCDLmgZjMCM5nDnOSHwYA4iSLFAqlHPMn76vLJiBgkyeQtbBclfBSXOtnyv7eQlfCQ1qFK4EWPUmC0L5DoCVJCMAj6yJEj6N69e5XtcXFxuHDhguZ+LRNAvXv3xqFDhyTbRowYgZYtW2LChAkICwsTtsfHxwMAfvrpJ3z99dd44YUXFPvt0qUL8vLyJHFAubm56Nq1q8GvILiRi/Mxi+pr9uBy/86G92vEJGIV4smLC48AUD4B85mWaYWQeriK7xJfVikqxv0o1JnjVxhm1X4YW84t0TBK/aSHDQSYS3hOoic4CcVl8MnJyfj555/RuHFjyfadO3eiadOmmvu1TADVqFEDrVu3lmyLjY1FYmKisH3t2rWoU6cOGjZsiEOHDmH06NG44447kJGRIRwzbNgw1K9fX4gjGj16NLp37465c+eiX79++Pjjj7F161bs3LnTfy8ugPGn8JGjyz0v6bYCmeVGMBulquji90S8VFsVoglRD4E2mZqR00dPzTS1aBHtWpfsk4WICBQeeeQRjB49Gu+++y44jsMff/yB3bt3Y/z48Xj++ec192v5KjBPnD59GmPHjsWZM2eQnJyMYcOG4bnnnpO0OXHiBByiKspdu3bF6tWr8eyzz+K5557DNddcgzVr1lAOIBVYKX74GKAu97ykyR0mzvJspBvBbNRMQuKVdkLbELYAiSd8JSFo1fXRa/1xT4Eg2+bKSs0Cj0QPEYg8/fTTKCwsRK9evXDlyhV0794dUVFRGD9+PJ544gnN/dqqFlh+fr5kufqTTz6JkydPorS0FL/99hteeOEFREZGVjlm6dKlkm133303fvzxR5SWluLw4cO46667/DB6giAIgjAZP68Cmz17Njp27IgaNWqgbt26uOOOO3DkyBHpkBjD1KlTkZKSgpiYGPTs2RPff/+9pE1JSQlGjRqF2rVrIzY2FrfffjtOnTqlehwzZ87EuXPn8NVXX2HPnj34888/PYbDqMHWFiDCf/iaxFAv7u4ecQ0wPS4wceJDO2Z+dseXX+FygbnBjLhSuxixG9Aflh41LiauYozZdR7F5j/fMOS8SkHvmdGDhSBsT59XpfIjZPkJbPwdA7R9+3Y8/vjj6NixI65evYpnnnkGGRkZkooM8+bNw/z587F06VI0b94cM2bMQHp6Oo4cOYIaNWoAAMaMGYNPPvkEq1evRmJiIsaNG4dbb70V+/btk8T8yrFs2TLcfffdiI2N9bgIylcszwRtR4I9EzT/xci53XRmix815nctMUCZscMkWZ69ffEHqhsglGpD2ek98iXGJrvOo2AVcVdbzi1BVu2Hq7TR6yZzj0USr3Kz03ULJfyZCfofE2chTEcmaOeVK/h5jvZM0H/++Sfq1q2L7du3o3v37mCMISUlBWPGjMGECRMAlFt76tWrh7lz5+KRRx5BYWEh6tSpg+XLl2PgwPLP0x9//IHU1FRs2rQJmZmZHs9Zp04d/P3337jtttswZMgQZGVlITxcv/2GLEBBhtKXoRxii4I/JlZVX8gajDbiSu8A4IiJKX/gYkJMRbqjf1BMDkbUqAoE7PL+qBWdYmtVWK3yVati8aMkhowYH28hs3vBWcJALDRbFBYWAgASEhIAAMePH0dBQYFkcVJUVBR69OiBXbt24ZFHHsG+fftQVlYmaZOSkoLWrVtj165dXgXQ6dOnsWXLFnzwwQcYNGgQYmJi0L9/fwwZMkTXCm8SQAGO0peeuBAjoBw4apeJtPPgchfYnlXa3F9ydb7EQdB2mVCNIpSsQb6i1/Wj9vMhu2pPob2R4kdcd49zcJas1iQsxKA8QO4ln9Tkw2OMYezYsejWrZuwWpvPuydXgeG3334T2kRGRqJWrVpV2niq0sATHh6OW2+9Fbfeeiv+/vtvrF+/HqtWrUKvXr3QoEED/PLLL177kMNWQdAEQRAEQZhPamqqpASUXEkqd5544gl8++23soXFfa3AoLaNO9WqVUNmZiays7PRrFkz/Prrrz4dL4YsQAGOp1+1cr9kQ81yoJi4LgCRK89AVEXpM5Hu6F8loFqxDzWfEVFf3tob7QLjrT50H4QeRgVBnzx5UhID5M36M2rUKGzcuBE7duxAgwYNhO1JSUkAyq08ycnJwnZxBYakpCSUlpbi/PnzEivQ2bNnVbuweMvPypUrsXXrVqSmpuKee+7B2rXarfskgEIMu4qfPSvLXV+dB78kPNaLe20lX1E61g5iKs+5hoJfVSK5Ngbd/2p/SJgR9yNG4tJ2S3oZ6EH/hAIGucDi4uJUBUEzxjBq1CisX78e+fn5aNKkiWR/kyZNkJSUhLy8PLRr1w4AUFpaiu3bt2Pu3LkAgA4dOiAiIgJ5eXkYMGAAgPK4nu+++w7z5s3zOoZ77rkHn3zyCapVq4b+/fsjPz/fkOoOJICCDLlfhHYVPXLsWTmuMh7IICEE6BMz7m0yY4baQwSJJjia2JQx6tposbbwy+ONWhovh9Lnm4QPYQSPP/44Vq1ahY8//hg1atQQYnbi4+MRExMDjuMwZswYzJo1C82aNUOzZs0wa9YsVKtWDffee6/Q9oEHHsC4ceOQmJiIhIQEjB8/Hm3atEGfPn28joHjOKxZswaZmZmGrP7iIQEUpASS6KlChU+4y70vYbfGoGgeJaHCCyKxmPHFWmSnchs0uZmL1kUD2XUelTw2UwTJQfdFcOLvPECvv/46AKBnz56S7e+99x7uu+8+AOWZmouLizFy5EicP38enTp1Qm5urpADCAAWLFiA8PBwDBgwAMXFxejduzeWLl3qNQcQAKxatcq3QauE8gDJEGh5gMRLcANa+FTAr3C52L+jbgHkDXfRIyeGPAmczJihcJWWyu7z9l7Y1XJDlgNjaolZIXoIa/BnHqDm42YhLEpHHqCSKzj6kvY8QP5i8eLFePjhhxEdHY3Fixd7bPvkk09qOgdZgAiCIAiCsBULFizA4MGDER0djfnz5yuuFuM4jgRQqGJXK4KviAt9iuly70tgovveyLggQNm6o9qtxVxwRJR/jNxLF3hLTGfH9y09bKAtx2U27ivE9FhSs+s9Vv7AwSEjsjwGIrfUHBM+EYIYFARtd44fPy481rPU3RMkgAIU8QqgYBqHXFI3PijaTihV6hZj9XvjC7ScWp/oyUp4qMo2LiJcED4ZkfeSCCIMwd8xQFZTVlaGFi1a4P/+7/+QlpZmaN8kgAifES+7NXqSd69z1HnIfMOtPoYgsha4Sq4ACI7YmWCIIfMFowX8lv+9ZUg/BKFIiFiAeCIiIlBSUuJzwkQ1kAAKENzdKVZNsBJLAecwpDaV2P0VCGn9JdYfsdskQEWPJ+xiaTQLI16XnPWHh3eBqSE9bKAkl0+wXnOC8JVRo0Zh7ty5ePvtt2kZPEEQBEGEJCFmAQKAL7/8Ep9++ilyc3PRpk0bxMbGSvZ/9NFHmvolAWRz7OJWUVoWzG9Xs2zY3b2lxvKzZ8VYdB4yX3hsO0RuwMzowVUCoe2AYIVwyxQshnOUm5erxAKpLB0R6ii5vsQxQN4+Q4A0uaVdPvuEvQi1GCAAqFmzJv71r38Z3i8JIJthF1eXGE/iRk7sKK3oct8XCO4uOcQiJzN6cKVLjHPIBkdbKYrcRaeVhOKErhRc7u0HQ6hcH4JQw3vvvWdKvySAbIY/vvi0TES+xPiYNeF2HjJfsiT+y+U2sAi5W0hEz63MEM0LTTuIHyFOTMa6EcgTvafYH3dCLbicMJEQdIGZBQmgEEFJ9HjLVePe3gqUXF+dhs4XHlslhsQFV/UWXzUCIe+MDYSPO8FkARKLH1r5RfiTUHSBKTF58mQUFBTg3Xff1XQ8CaAQQWnCCeSJiFUYW6z+QIstPeLHYmEUKsiteuLCwgDmQm5Z4N5rcpDwIQhr+f3333Hy5EnNx5MAIgiCIIhAgVxgAsuWLdN1PAkgIqDg3SiFQ7vgq2U2iAHygLiwqtlWILHlxd8Zh/nAb+ZiwmoyucBvuYDgPOcazbmkAqIMTMXKu4AYKxEYkAAyDBJAREDBTyI33jcfN95XHgPEOACi4Oi979pLGLnHCZmKh6XuWvBa8kMU9M2ulnn8bpUTOOlhA4XtEoGk4nXkudb6PZhaHPuTFTcCALCl6D1kxd9f/rhQGougFG9HYoggPOOtArwYrcVQOcYY6UE3ioqKEB8fj8LCQsTFxVk9HMIHOt4/33YCSBIY7ZCmc8+5/H5lu9hh5Q9cTLG9V5zO8v9a8/c4uMo+4PsSfj2TfCBZSTIiBsEREyM831JUvkw3K/7+KiLInUB6nYQ6/DFn8OdIGzkLYVHRmvtxllzBD69Ntv381qRJE1XtOI7DsWPHNJ2DLEAhjqcJS2mFmB2/vLOufx4AUDM20uKRVEViARIJHkAkejiu/A+Aq7TEr8umM2OGwlVaKjzXc249ifzEFh21x1iJq7gYgHTF3ZbCdwVrEP9cDrnPlt1fL2ETQsQFJq4GbxYkgAiCIAgiQKBl8MZBLjAZQsUFJjbFq/1FakerEG/9AQBn9Sjk7XzGsrEYgZqyImae0+hzB6vLR02ySaXYICK48KcLrNWj+l1g379hfxeYO6dOncLGjRtx4sQJlIos1gAwf/58haM8QxagEEY8KanOCK3QTsuknXnD1MonMjo8Z980aft2U4THnKj9loPTpWPpNrN8HAEqhMQro/wlhsSByLJByTrOH8jiR6mUBefgfEo2Kb6uBKGLEHGBifn0009x++23o0mTJjhy5Ahat26NX3/9FYwxtG/fXnO/JIAIQ1CatPl9PJkdK0VNztdTZfvK7FAudMSCBwByDkyTa65IereZQrLErTukYkjr0mt/obRiSkLFSikjBYb4vO5jCMa4FSWBw6Pn/sisPlzzsQThkQAUMXqYNGkSxo0bh+nTp6NGjRpYt24d6tati8GDByMrK0tzvySACF2oCVrlJxlH+zTk7J0i20aCaAW0r6IHkFp++nSfKfznvvhWcWwe+3OusYXrT0mQ+KuAbqCLHU8YKYTFwifnUmWiNruLboKwK4cPH8YHH3wAAAgPD0dxcTGqV6+O6dOno1+/fnjsscc09UsCiNCFt0kxs8MUOK5vCQDqxA+0iR4luJ0HAQCs2/WaEu2J/wP2EgF2GgtRjifxQ8KHMIJQDIKOjY1FSUkJACAlJQW//PILWrVqBQA4d+6c5n5JABEEQRBEoBCCMUCdO3fGF198gbS0NPTt2xfjxo3DoUOH8NFHH6Fz586a+yUBRJgLxynG+piFnMWGd4X5AllYghu9VhkhhxMg5HASW33kzgeQC4wgfGX+/Pm4dOkSAGDq1Km4dOkS1qxZg3/84x9YsGCB5n5JABGmIA52Ngs1cTn8pMNuvs708RCBQ7qjv/Zs2TJ4Ej6AdJEAQegh1FxgTqcTJ0+eRNu2bQEA1apVw2uvvWZI3ySACMPJ7DhNdbyPVnyNy+FcDH16zAIAbN0+2bRxEfbGyNphfCZocUkMxfNSDBBhFCHmAgsLC0NmZiYOHz6MWrVqGdo3CSDCMPxp9fF1AuODoQEIQgggMRRq6BE+SqvtJLXelDC4SC1BhBJt2rTBsWPHVNcHU4txNmCCIAiCIEyFd4Hp+Qs0Zs6cifHjx+P//u//cPr0aRQVFUn+tEIWIEIXksSGJru9AN9/wcsmFHT0h6t7OwBA756z8Gm+f61ARrph7Iov8S52dw2FwvtFBBAh5gIDICQ7vP3228FVLDgAAMYYOI6D0+nU1C8JIEIVGZ1F5SZE1vxcP4geoxFPZL17zvLQ0jjsmkvIG3y9KzUwV+U3qy+ixsw6ZEag9H7xrq+c4uX+HA4R6oSgANq2bZsp/ZIACnGUVlIBlV/8GZ2nI3fP84rtAp3evWYDAD7dNsmwPqtM6hUrjqyc2DMi7/XeyC1WxZd6V1pRstIJ+20oGDNjhoJp/NVJEIRv9OjRw5R+SQCFOIrlKxz9BatPMIsfsfur9y2z8eln+kSQFZXc3VESOrmlq/w8Eu3YUfSIcZWWCu+v2EqmJBjzXGvJlUYYQqgtg+f5/PPP8eabb+LYsWNYu3Yt6tevj+XLl6NJkybo1q2bpj5JABGy5LnWSt1eBiAuTsocnGSfv+Nw5HBsP4hbes8BIK02D8CjMLKb6AkkoRMMiEVPRsQgjyKIIHQTgi6wdevWYejQoRg8eDD2798vlMW4ePEiZs2ahU2bNmnql1aBEQRBEARhW2bMmIE33ngDb731FiIiIoTtXbt2xf79+zX3SxYgwisZnacLgc+5X3l3h6XfNKPyiShiX1ylXUzvnrNMicNRi7cSBbf0niNYhj77dGKVY/1p9cmMHiw8Fgcd85D1x3p4l5g/4qeI0INjrIqF2tfjA40jR46ge/fuVbbHxcXhwoULmvslAUQowsf+iCf5jM7TJaKGVTzmGBMe5+161qfzfJo/Gb1vmW3EkH1GzXLtzz6dKAigW3rPAQvjEP5p+a8OveJHLGh4cq6slN3O7yPsS27ZakEAZUQM0rwyjiAUCUEXWHJyMn7++Wc0btxYsn3nzp1o2rSp5n5JABGKiFfieLOS6K1zxMI4743MQkWWXnfLT6+MuQCAW9LnVLbJk7aRQ0nYuLchoRO4KFl+lD4jJIwIwjOPPPIIRo8ejXfffRccx+GPP/7A7t27MX78eDz/vPZFOiSACK/kudYKX97pjv6ywZx6iz3y4qFXxlwhUBoch/zNT2vuUw15zjWC0FN6bXJsy51QZdst6XOE4G7GAVH531ZpQ8ImdJFd7h820PZL/gl7EYqrwJ5++mkUFhaiV69euHLlCrp3746oqCiMHz8eTzzxhOZ+SQARBEEQRKAQgi4woLwcxjPPPIMffvgBLpcLaWlpqF69uq4+SQARikh+jVa4idT8QvXFkuKOu2WlR995gntsx8Z/a+rTG0b96v4sbyJ6ZpW7xvK3TBDcY2pcY0RoIrYKeUpKShChzP33349FixahRo0auOGGG4Ttly9fxqhRo/Duu+9q6pdjLABDwk2mqKgI8fHxKCwsRFxcnNXDsQW+JHEzy6Tf/fYXhcc7Nv4bGTeK8hRVuM3skrTxlvQ5thM+2XUeld2++c83/DwS40kPG+iTSDfkfApojenR88OBsBZ/zBn8OdrfMxNhkdGa+3GWXsH+D54JqPktLCwMp0+fRt26dSXbz507h6SkJFy9elVTv2QBIgxHnPXWSHZs/De69ysXQRk3Tpddkp/R5QXhce7u5wwfg1o+y5voVwtQVu2Hhcccp5zeSyx2eEFURRhVxDFtPvO6sIniVKR4EjneFgwo9knXlVBDCLnAioqKwBgDYwwXL15EdHSl8HM6ndi0aVMVUeQLJIAIVdjlyzn2mz8AAJt/XSC7Xyx6Mrq8YLkIAnxfKeYrWbUfxpZzS3w+Tsnyk13vMeH/1T/PAbDP+y8mM2aoYPXhwsIAhAGQKQWisMrPtDw9Fecjiw5hBqEUBF2zZk1wHAeO49C8efMq+zmOw7Rp0zT3TwKICGrSu1YkZeSAvC98y09kFGLR0ytjruwKMi3wpUrC6iQi+9rKBJKbD+vLqSS2/IitRHZxlfGpBNSsqMuIvFdR6LhXuueLm+oVLfzxFNNDEPrYtm0bGGO45ZZbsG7dOiQkJAj7IiMj0ahRI6SkpGjunwQQQRAEQQQKIeQC46vAHz9+HKmpqXA4jK3eRQKICCh411d2wzHYfGKhx7bu7i++RIdVliAAgEH5HpVioABIrEGAPouQXMwQYy6PcUbuxxlJZsxQuEpLAShbWMQWHE+lQdwtQ+JcV3J9+Qq5vwizCCQ3lhE0atQIAPD333/jxIkTKK34DuBp27atpn5JABGmYNaXf3bDMZqP5YWPr7XKzKJn1lzkb9HuDuNXwbkLIbHgyb52kiCIdLvGVIgaxcBqlAsnAEDZVWwpLF+2mhV/P5iXFRw5l98vj/epwKx7iw9a1pvVnCAIY/nzzz8xYsQIbN68WXa/s8J97SskgIiA4uqp3wGUT4K8GPJmCXJHyQKU3m2m6SJoW84E9MqsyBUkegyUZ4+WRSTSIv+6AkBdUVqgqhji+9r8wyxfhq0aTyKJD04Oi49DVvz9wnZW8WtOKVYnM3YYcoqXGzhKgghgGCv/03N8gDFmzBicP38ee/bsQa9evbB+/XqcOXMGM2bMwEsvvaS5X8oDJAPlAQos1LjD1NKn+0zh8dYd/rUIeSM7+XFsPv2qvj4MsgZpQalKujgY2S4V1H3Je0UQ/swDdMPdMxAeoT0P0NWyK/j6w2cDan5LTk7Gxx9/jBtvvBFxcXH4+uuv0bx5c2zcuBHz5s3Dzp07NfVLFiAi4Nl8YqHENaZHDIlFjyCGOA5bt0/W3Ked4IWPkavG9MKLnoyIQYoiySoo/xFBWM/ly5eFfD8JCQn4888/0bx5c7Rp0wb79+/X3K+xIdUEQRAEQZgHM+AvwGjRogWOHDkCALj++uvx5ptv4vfff8cbb7yB5ORkzf2SC0wGcoEFLtkNxwCigLjNv7+su88+PSrjZay2BGUnPw4Aul1hgHXusIyIQapy89jFCkQQ3vCnC6zjnfpdYHvXB5YLbOXKlSgrK8N9992HAwcOIDMzE3/99RciIyOxdOlSDByobeGCbVxgs2fPxuTJkzF69GgsXLgQAHDp0iVMnDgRGzZswF9//YXGjRvjySefxGOPPabYz9KlSzFixIgq24uLiyVptInggg+wFS97zq4/ypC+xaKHF0NWCCFe/BhGRUB0dpr8azErUDq3bLWi0JFzh7m3IQgitBg8eLDwuF27dvj111/x448/omHDhqhdu7bmfm0hgPbu3YslS5ZUWcv/1FNPYdu2bVixYgUaN26M3NxcjBw5EikpKejXr59if3FxcYK5jIfET/BSpfSBiWzdPlliEfInm0+/KoggdzGkxSKkJHB4QeQujIwURN7ifsSPMyIGSZamay02ShBBQQglQlSiWrVqaN++ve5+LBdAly5dwuDBg/HWW29hxowZkn27d+/G8OHD0bNnTwDAww8/jDfffBNff/21RwHEcRySkpLMHDZhMWLR4ynZncQKxC8BP7VY9/l79ywXA5/m+9cSpCR0xIJIr3tMTuhkp00WBBHjOGz5fmaVNlrILVtdmYAwbKCsuBG3yXOuqRRDCjW+KFiZCGZCpRbY2LFjVbedP3++pnNYLoAef/xx9O3bF3369KkigLp164aNGzfi/vvvR0pKCvLz83H06FEsWrTIY5+XLl1Co0aN4HQ6cf311+OFF15Au3btFNuXlJSgpKREeF5UVKTvRREEQRCEGYRIHqADBw6oasdx2tPrWyqAVq9ejf3792Pv3r2y+xcvXoyHHnoIDRo0QHh4OBwOB95++21069ZNsc+WLVti6dKlaNOmDYqKirBo0SLcdNNN+Oabb9CsWTPZY2bPnq2roizhH9yLV6qKC+Frx4g+9NkNntRlBRInLOzdc5bfrUBy8Faf7OTHkZ00EpsLXjO2f5FVKKvVM8hqVZkuQK81SJyBWWzpkWsjt48giOBj27Ztpp/DslVgJ0+exA033IDc3Fxcd911AICePXvi+uuvF4Kg//Of/+Ctt97Cf/7zHzRq1Ag7duzApEmTsH79evTp00fVeVwuF9q3b4/u3btj8WL5SU/OApSamhpQUfKBTLqjv2IFbbE7w9PqISW0ZotWi10EkDvZSSMBwHAhJIdYDPFoFUWBGOvj6Z4lQgN/rgLrdNsLuleBffnJczS/wUIBtGHDBtx5550ICwsTtjmdTnAcB4fDgcLCQtSqVQvr169H3759hTYPPvggTp06hS1btqg+10MPPYRTp04p1hFxh5bB+xdPyebSHf3BVdwjWlYCmSWA0rtVTvCOr38AAORcWWnoOYyAF0KeMFIkya0o0xI8rabQqb9RqhEWKEKNMA+/CqBbDRBA/0cCCLDQBda7d28cOnRIsm3EiBFo2bIlJkyYAKfTibKyMjgc0lyNYWFhcLnkgx/lYIzh4MGDaNOmjSHjJoxHaVJLDxsIcA5bLoHma4ald5spCJ/M6MGyba0URkrixgw3GSAVO+LVZL6KIKutKHJih4QOQQQXlgmgGjVqoHXr1pJtsbGxSExMFLb36NED//73vxETE4NGjRph+/bteP/99yUR38OGDUP9+vUxe3Z5Mrdp06ahc+fOaNasGYqKirB48WIcPHgQr76qP3Ec4R+MdIPwlh8j64WJydv5jGANyhMJnczowbLCiKmoWmym4FNjETIKXvSIV5CJt9uVQHTDEaFDqKwC8weWrwLzxOrVqzFp0iQMHjwY//vf/9CoUSPMnDkTjz76qNDmxIkTEivRhQsX8PDDD6OgoADx8fFo164dduzYgRtvvNGKl0AQBEEQxhEiq8D8AZXCkIFigPyPP1wOZsUD+VJBXinXjRgtwd5q8WdwtOIYrp1keQFWOexWiJUIHPwZA9T5n9N1xwDt2fQ8zW+wuQWICG4kga5cuRXPHy4HI91hvXvOAr8q3pv4AaCYvM8dpeXgeuGFj1kxQIEGldsgAg1ygRkHCSDCcqwOePUVPgs0jyrhI4IXfkqvWzwRq7EYacUqa9Dmw7MtK8TKoymnFEHYASqFYRgkgAjL8Kfw4d1fgDEuMK25f3x9zeLSD0YKoc0FryGr9sMArBEDvPDhhZDSfqMxw+IjzmNFEETgQAKIIAiCIAIEcoEZBwkgIqgxOvDZkszPKuOGtOLucjMr/kgOd0sPbxESW4aMsgYZGVzuKXknQZiKi5X/6TmeAEACiAhyjMoDZFX1d3+QVfthbDm3BIDU5WZm/JEScmInu8VE+bZH5shuz4i8V3a7EeJHkiOIhA9hBRbEAO3YsQMvvvgi9u3bh9OnT2P9+vW44447KrtkDNOmTcOSJUtw/vx5dOrUCa+++ipatWoltCkpKcH48ePxwQcfoLi4GL1798Zrr72GBg0a6Hgx+iABRIQMWq1BvXvNDkrhw4seAEI80JZzS1QVJ/UnSkJHLIycx09I9uWWrjJ8HOL4IRI/RChx+fJlXHfddRgxYgT+9a9/Vdk/b948zJ8/H0uXLkXz5s0xY8YMpKen48iRI6hRowYAYMyYMfjkk0+wevVqJCYmYty4cbj11luxb98+SUksf0ICiAhaxG6K8Ab1LRyJPsSFYk2beGXM4hJrkA1dPpuPzEF20/EAgLAGKdh87D+mnEecH4i/Dna8HkRowEFnDJCGY7Kzs5GdnS27jzGGhQsX4plnnsFdd90FAFi2bBnq1auHVatW4ZFHHkFhYSHeeecdLF++XChkvmLFCqSmpmLr1q3IzMzU+nJ0QQKICDrEy8yzU0cD0B8D1LtXuWvm023yq5b8gT8m2qyEh7Dlf29VnlPG8mOnyV8sengxpFUICa4zt5grsevM6tdLEEZlgi4qKpJsjoqKQlRUlM/dHT9+HAUFBcjIyJD01aNHD+zatQuPPPII9u3bh7KyMkmblJQUtG7dGrt27bJMADm8NyEIgiAIIphITU1FfHy88MfX0/SVgoICAEC9evUk2+vVqyfsKygoQGRkJGrVqqXYxgrIAkQEHfyv9Oz6o4CKOnF6VgCJrT69e8221ApkFrzVJyvhIWQlPCTZ5o7drSDZTcfDeeoP4blSPJCZwdIEYRZGLYM/efKkpBSGFuuPpF9O6lxjjFXZ5o6aNmZCAogIajafXASgXAC5J/wDNEx2XIU7rOIz++lnwSWGtvzvLUEAubvD7A7v+spOHY2wOonl235/WVHoAOYESxOEqRi0CiwuLs6QWmBJSUkAyq08ycnJwvazZ88KVqGkpCSUlpbi/PnzEivQ2bNn0bVrV91j0AoJICLoyK4/CkD55MfjLnR4MZQRMQisIgBYzUond8HT+5bZQSmCeLxZg+yIs+AMwurWEZ6TyCEI82jSpAmSkpKQl5eHdu3aAQBKS0uxfft2zJ07FwDQoUMHREREIC8vDwMGDAAAnD59Gt999x3mzZtn2dhJABFBS3b9URIRJEbO8iNXkR6AJCjW3f3z6WeTcEvv8mXanCgwMdhEUVatB7Hl/NtWD6MKcu9ZnnONIIIJItjgGJN812g53lcuXbqEn3/+WXh+/PhxHDx4EAkJCWjYsCHGjBmDWbNmoVmzZmjWrBlmzZqFatWq4d57y62v8fHxeOCBBzBu3DgkJiYiISEB48ePR5s2bYRVYVZAAoggCIIgAgVXxZ+e433k66+/Rq9evYTnY8eOBQAMHz4cS5cuxdNPP43i4mKMHDlSSISYm5sr5AACgAULFiA8PBwDBgwQEiEuXbrUshxAAMAxpmc9XXBSVFSE+Ph4FBYWGuIjJfyH5Jc/x2HzqcWWjCNYXGO8hSWseiy2FL5bvs0my+DV5EXKrj8KVwvOyu9kLtsHdBOBgT/mDP4cN3efgvDwaM39XL16BZ/vmEbzG8gCRAQhSm4vfyJ2jX32qXwph0BAnBU6K/5+AEBY9erYUvSelcNSj9OpGNslFnIEEShY4QILVkgAEQGJJyuEXBC0FfDC55becwJaBAHSrNBhsdWQFTcCAMDKriKneLk1Y1JpvclOGgkA2FzwmqbjCcJWWFALLFghAUQEJOLJy+4Br599OhG3pFfUs3JBSD/6WV7giCJxYVRxOgEuLAyZ0YOF5zlXVvp9bJ7YXPCaIID4//x2gghIDMoETZAAIgIIxerkLpeQ8NBqq48SYrHDi6FAsAwJljauMmk8czHZ98FTvh0rEYsdQQzVewybz7xu1ZAIgrABJIAIgiAIIkAwKhM0QQKICADEVgilXD28RSI7aaTt3Rvh278FUJ6gr3fPWQDKv5TCvvwegL3cSEEXJ2Oh+d8uq+eIAIdcYIZBAoiwPWomC3F8h51xdxM5SuWTcojjang8CSN+crVyYs0tXSW8PrtmX+bdXtn1HvOrGyw9bCCJHoKwGSSACMLPiMVB3q5nAQDpXWcI25SCit1FEb9PTT4cIxGvCOOfu5MRea9tRRAAXD33P4TXTkBW7YeFbVvOLTH8PIrZxQlCI5yr/E/P8UQ5JICIoMLu7i9PeHN9uYshXhBZYVkQ8gO55dLhRU9G5L0BYw0CgKzaD0vEkBhfhZF4lZya+nIE4RPkAjMMh/cmBEEQBEEQwQVZgIigIjtpJOAst/Fu/vMNi0ejnrxdz0rcYLxrTAm+gr1dEccDWW0JklipKpbzu1tmlKw8mTFDkZXwEACAlZQg5/L7kn3lOyp9CszplC20SxCGQYkQDYMEEBEU8K4vccxFdp1H4bp0GQA8ZisWjrG4NpRY9PBiSEkI5ZauElwtYpcLIF/p3grEgicjYpAwTn+PT+97uuV/bwEoFzyC6BEhdk2mhw0U7idyfxFmQKUwjIMEEBGwyAWYiiedrLgRgvART1xiMSQJ5vWD+BELF71CQO74jIhBHgNvjZ6U1V6z3LLVVYSaN6xaNi4ncgDPIppHfH0VE3cSBGELSAARAYN7wK3SpMjXqRIX7BRPXpkxQ+EqLa3sx4aTFG/5yejyAnJ3P6f6OG+iSmztkpzPIsuXR7FmlTWOuYzJxcRouQ1hAhQEbRgkgIiAQe2EyFyeJ56c4uWWx6WoJXf3c17dYb5gpdjjxVlGxCAhhsmO4tMoKO8PYQoM5TUF9RxPACABRBAEQRABA8UAGQcJICIkEeer4V0VdgkeViJYYkrsfp0JgggNSAARQUtm9eHIubTMYxul1VRmTtK+LmHnKlx6DKAVRiZi12r2BCGBQWcMkGEjCXhIABEhj1js+FsM+YL7CiO57YR+7B4XRoQ4FARtGCSAiIBFaQWRIyYaALxaf+QQix2+f7PEhh6XlrgeV7C4xjzhLeWBXsj6QxChBwkgImBwz+grNwFmRg8WhI/7pOnrhGmaqKiIOdK7Skhcj0ttioBAJCNiEDgHB6BcoPKv1f01y6E6T5EoczVB2BoXAE7n8QQAEkAEQRAEETDQKjDjIAFEBAxqfs2LA4zdLTi8xcBK60i6o7/P58/d8zwAIOPG6cj96vkq++1o7eGTUQLShJRq8bQ6z+zXmxF5L8UBEUQIQAKICDqUkhzaQShoGUPGjdMBQFb82A25LNyZ1YcrtmelZbLbrRAgQmoEUd0yTyv2gj3uirApFARtGCSAiKAgUDI7a4EXPkoWILuQFX8/wFUNTvAUjJ4ZPdiYshMGIgmE92Cxo5QEhCWQADIMEkBEcEB1lywhK/5+4fGWwnd9Pj7nysqAFK9aXJkEQdgLEkAEQRAEESiQBcgwSAARRABhZTxQVq0Hyx+Iis1qsfq4Iy5LYjcrUJ5rrS2C5wlCgJbBGwYJICIo4OM2QiEpoCcyOk8XVo0ZQVbth8sfOI0VPUrY0R1GwoewE7QM3jg4xuhquFNUVIT4+HgUFhYiLi7O6uEQPiIkQGSuoJ28eEtQFRzl/4wQQVm1H8aWc0vKzycqDSKGuZg5GZkVYrrsUpYEsEdaBcIe+GPO4M/Rp/lYhIdFae7nqrMEW4/Op/kNZAEigpBQsAB5coFldFYQRyrhrT68+AGqCg9xlm1Jxm2dWa69WX7sVKONf40UEE34FYoBMgwSQAQRZOTueV4qgiqMKZ5EU3adRwEAjLkkwkcJq0RmbtlqScFaq0UQQfgdFwM4HSLGQ26rUMNh9QAIgiAIgiD8DVmACCIIEccAZXacVvlftILLceJMlePUWH+sRmz1sYNLjNxfhF8hF5hhkAAiiCCHHTwMoKpAyOwwBQDg+N9FYVt2k7HYfHy+/wanE0nWZsrMTIQEOgUQSADxkAAiiCBHqZ5Vzr5pstuzm4wFgIASQkCl8BEHZZMYIghCCRJABBHE+JoXiRc//ONAE0GAVPTwS9UBclURQQK5wAyDBBBBEARBBAouBl1uLFoFJkACiCCCGR+LxG4+Pl9iBTIbsYUGMN5KI+7P/VxmnI8giMCBBBBBEBJ4t1d2k7GmxQNZkUWZxA4RFDCXzz9sqhxPACABRBCEn5AEJ5MYIQhtUAyQYZAAIoggRovQELvAtFp+xPl5+FVotCKLIAyAYoAMgwQQQRCGiB53qEwFQRB2hgQQQRAEQQQK5AIzDBJABEEYgh3KUhBE0MOgUwAZNpKAhwQQQRDCF+rmXxfo6oaED0EQgYJtqsHPnj0bHMdhzJgxwrZLly7hiSeeQIMGDRATE4Nrr70Wr7/+ute+1q1bh7S0NERFRSEtLQ3r1683ceQEETxkN35K87GO+DhkxY0o/4u/X3ishXRHf+GPIAgRvAtMzx8BwCYWoL1792LJkiVo27atZPtTTz2Fbdu2YcWKFWjcuDFyc3MxcuRIpKSkoF+/frJ97d69GwMHDsQLL7yAO++8E+vXr8eAAQOwc+dOdOrUyR8vhyACDrHlRxBBotUim08sVDw2q/bDAKSV5MXCJytuBLYUvSdZBs+T51xDCQoJwhdcLgA6cvm4KA8Qj+UWoEuXLmHw4MF46623UKtWLcm+3bt3Y/jw4ejZsycaN26Mhx9+GNdddx2+/vprxf4WLlyI9PR0TJo0CS1btsSkSZPQu3dvLFy40ORXQhAEQRBEoGC5Bejxxx9H37590adPH8yYMUOyr1u3bti4cSPuv/9+pKSkID8/H0ePHsWiRYsU+9u9ezeeekpqxs/MzPQogEpKSlBSUiI8Lyoq0vZiCCIIkIsDym44Buzvv2Xbiy0/wrai94THWXEjJAHSkmKlYQMBzlFlu14EaxNzkTWJCC5oFZhhWCqAVq9ejf3792Pv3r2y+xcvXoyHHnoIDRo0QHh4OBwOB95++21069ZNsc+CggLUq1dPsq1evXooKChQPGb27NmYNm2athdBECEAu1AoPBaLG1XHll1VDI42RfSI+yfxQwQbJIAMwzIBdPLkSYwePRq5ubmIjo6WbbN48WLs2bMHGzduRKNGjbBjxw6MHDkSycnJ6NOnj2LfHMdJnjPGqmwTM2nSJIwdW5kIrqioCKmpqT6+IoIIbnwVPmIyY4Yip3i5gaORkh42kDJNEwThE5YJoH379uHs2bPo0KGDsM3pdGLHjh145ZVXUFhYiMmTJ2P9+vXo27cvAKBt27Y4ePAg/vOf/ygKoKSkpCrWnrNnz1axComJiopCVFSUAa+KIIITpiNwMqd4OTJjhiIzZqjw3AgktcVI/BChApXCMAzLBFDv3r1x6NAhybYRI0agZcuWmDBhApxOJ8rKyuBwSOO0w8LC4PLwZdylSxfk5eVJ4oByc3PRtWtXY18AQYQQOZeWIbP6cOGxz8dXiCAjIOFDhDKMucB0VHTXc2ywYZkAqlGjBlq3bi3ZFhsbi8TERGF7jx498O9//xsxMTFo1KgRtm/fjvfffx/z51fWKho2bBjq16+P2bNnAwBGjx6N7t27Y+7cuejXrx8+/vhjbN26FTt37vTfiyMIgiAIM2BMnxWHYoAELF8G74nVq1ejY8eOGDx4MNLS0jBnzhzMnDkTjz76qNDmxIkTOH36tPC8a9euWL16Nd577z20bdsWS5cuxZo1aygHEEHYhMzowbqOz3OuIcsPQRC64RgjOehOUVER4uPjUVhYiLi4OKuHQxCWw7u/AG0uMElfIgGUc2WlT8dmRN4LiEz4VHqDsAP+mDP4c/SOH4pwLlJzP1dZKT4tXE7zG2yQB4ggiADBoN9KYtHjbg3i92VE3it7bG7pKiqPQYQ2LhfA6YjjoRggARJABEF4JefSMmTGDgMAZMYOQ87l943p180CxAuf3NJVisdQbh+CIIyABBBBEARBBApM5zJ4inoRIAFEEIQqxFYf3hpklCWIx5PlhyCI8pxcTIcLjJbBV2LrVWAEQRAEQRBmQBYggiB8hrf8GBkPRBCECsgFZhgkgAiC0EzO5fdVZXg2sw4YQYQULgZwJICMgAQQQRC68CZuMmOG6sr9QxAEYQYkgAiCIAgiUGAMgJ48QGQB4iEBRBCEqfAWIt4KRNYggtAOczEwHS4wKv5QCQkggiD8gpzYyYi8l5a+E4QvMBf0WYBoGTwPCSCCICwjt3RVZdkLty9mqvNFEISZkAAiCMJSlCxAGRGDKtuQGCIIAOQCMxISQARBEAQRKJALzDBIAMnAK+SioiKLR0IQocuHfy0RHvdy3FX+QPTl/XEhJWAk7AE/V/jDunIVZbryIF5FmXGDCXBIAMlw8eJFAEBqaqrFIyEIQon4+Hirh0AQEi5evGjafRkZGYmkpCTsLNiku6+kpCRERkYaMKrAhmPkEKyCy+XCH3/8gRo1aoDjOKuHI0tRURFSU1Nx8uRJxMXFWT0crwTaeIHAGzON13wCbcyBNl4g8MbMj/eHH35AixYt4HCYV2LzypUrKC0t1d1PZGQkoqOjDRhRYEMWIBkcDgcaNGhg9TBUERcXFxBfEjyBNl4g8MZM4zWfQBtzoI0XCLwx169f31TxAwDR0dEkXAyEqsETBEEQBBFykAAiCIIgCCLkIAEUoERFRWHKlCmIioqyeiiqCLTxAoE3Zhqv+QTamANtvEDgjTnQxktUQkHQBEEQBEGEHGQBIgiCIAgi5CABRBAEQRBEyEECiCAIgiCIkIMEEEEQBEEQIQcJIIuZOnUqOI6T/CUlJSm2v++++6q05zgOrVq1EtosXbpUts2VK1cMG/fvv/+OIUOGIDExEdWqVcP111+Pffv2eTxm+/bt6NChA6Kjo9G0aVO88cYbVdqsW7cOaWlpiIqKQlpaGtavX2/JeD/66COkp6ejTp06iIuLQ5cuXZCTkyNpY+Z19nW8+fn5smP58ccfJe3Mur5axmzlvdy4cWPZfh9//HHFY6y8f7WM2ep72Nfx2uEe9nXMdvk+JrRBAsgGtGrVCqdPnxb+Dh06pNh20aJFkrYnT55EQkIC+vfvL2kXFxcnaXf69GnDMoieP38eN910EyIiIrB582b88MMPeOmll1CzZk3FY44fP45//vOfuPnmm3HgwAFMnjwZTz75JNatWye02b17NwYOHIihQ4fim2++wdChQzFgwAB8+eWXfh/vjh07kJ6ejk2bNmHfvn3o1asXbrvtNhw4cEDSzozrrGW8PEeOHJGMpVmzZsI+s66v1jFbeS/v3btX0l9eXh4AVDk3j5X3r9YxW3kPaxkvj1X3sJYx2+H7mNABIyxlypQp7LrrrtN8/Pr16xnHcezXX38Vtr333nssPj5e/+AUmDBhAuvWrZtPxzz99NOsZcuWkm2PPPII69y5s/B8wIABLCsrS9ImMzOTDRo0SPtgmbbxypGWlsamTZsmPDfrOmsZ77Zt2xgAdv78ecU2Zl1fxoy5xlbcyzyjR49m11xzDXO5XLL7rbx/lfA2Zjn8dQ/L4W28Vt/Dcvh6ja28hwnfIQuQDfjpp5+QkpKCJk2aYNCgQTh27JjqY9955x306dMHjRo1kmy/dOkSGjVqhAYNGuDWW2+t8qtPDxs3bsQNN9yA/v37o27dumjXrh3eeustj8fs3r0bGRkZkm2ZmZn4+uuvUVZW5rHNrl27/D5ed1wuFy5evIiEhATJdjOus57xtmvXDsnJyejduze2bdsm2WfW9dU7Zh4r7mUAKC0txYoVK3D//fcrFj+28v7VOmZ3/HkP6xmvVfewnjHzWHUPExqxWoGFOps2bWIffvgh+/bbb1leXh7r0aMHq1evHjt37pzXY//44w8WFhbG1qxZI9m+e/dutnz5cnbw4EG2Y8cO9q9//YvFxMSwo0ePGjLmqKgoFhUVxSZNmsT279/P3njjDRYdHc2WLVumeEyzZs3YzJkzJdu++OILBoD98ccfjDHGIiIi2MqVKyVtVq5cySIjI/0+XnfmzZvHEhIS2JkzZ4RtZl1nLeP98ccf2ZIlS9i+ffvYrl272GOPPcY4jmPbt28X2ph1fbWOWYxV9zJjjK1Zs4aFhYWx33//XbGNlfev1jG74897WMt4rb6HtYxZjJX3MKENEkA249KlS6xevXrspZde8tp21qxZLDExkZWUlHhs53Q62XXXXcdGjRplyBgjIiJYly5dJNtGjRolcQe406xZMzZr1izJtp07dzIA7PTp00K/q1atkrRZsWIFi4qK8vt4xaxatYpVq1aN5eXleWxn1HXWO16eW2+9ld12222Sfs24vnzfesZs1b3MGGMZGRns1ltv9djGyvtXDjVjFuPve9gdX8fL48972B1fx2zlPUxog1xgNiM2NhZt2rTBTz/95LEdYwzvvvsuhg4disjISI9tHQ4HOnbs6LVPtSQnJyMtLU2y7dprr8WJEycUj0lKSkJBQYFk29mzZxEeHo7ExESPberVq+f38fKsWbMGDzzwAP773/+iT58+HtsadZ31jFdM586dJWMx6/oC+sZs5b3822+/YevWrXjwwQc9trPy/tU6Zh4r7mExvo5XjD/vYTG+jtnKe5jQDgkgm1FSUoLDhw8jOTnZY7vt27fj559/xgMPPOC1T8YYDh486LVPtdx00004cuSIZNvRo0er+L3FdOnSRVhRwZObm4sbbrgBERERHtt07drV7+MFgA8++AD33XcfVq1ahb59+3o9j1HXWet43Tlw4IBkLGZdX0DfmK28l9977z3UrVvX6/tr5f2rdcyAdfewGF/G644/72Exvo7ZynuY0IF1xieCMcbGjRvH8vPz2bFjx9iePXvYrbfeymrUqCGsIpg4cSIbOnRoleOGDBnCOnXqJNvn1KlT2ZYtW9gvv/zCDhw4wEaMGMHCw8PZl19+aciYv/rqKxYeHs5mzpzJfvrpJ7Zy5UpWrVo1tmLFCqGN+7iPHTvGqlWrxp566in2ww8/sHfeeYdFRESwDz/8UGjzxRdfsLCwMDZnzhx2+PBhNmfOHBYeHs727Nnj9/GuWrWKhYeHs1dffZWdPn1a+Ltw4YLQxqzrrGW8CxYsYOvXr2dHjx5l3333HZs4cSIDwNatWye0Mev6ah0zj1X3stPpZA0bNmQTJkyoss9O96/WMVt5D2sZr9X3sJYx81j5fUxohwSQxQwcOJAlJyeziIgIlpKSwu666y72/fffC/uHDx/OevToITnmwoULLCYmhi1ZskS2zzFjxrCGDRuyyMhIVqdOHZaRkcF27dpl6Lg/+eQT1rp1axYVFcVatmxZZSxy487Pz2ft2rVjkZGRrHHjxuz111+v0u/atWtZixYtWEREBGvZsqXky8+f4+3RowcDUOVv+PDhQhszr7Ov4507dy675pprWHR0NKtVqxbr1q0b+3//7/9V6des66tlzIxZey/n5OQwAOzIkSNV9tnt/tUyZqvvYV/Ha4d72NcxM2aP72NCGxxjjPnf7kQQBEEQBGEdFANEEARBEETIQQKIIAiCIIiQgwQQQRAEQRAhBwkggiAIgiBCDhJABEEQBEGEHCSACIIgCIIIOUgAEQRBEAQRcpAAIggCANCzZ0+MGTPG6mEQBEH4BRJABEEQBEGEHCSACIIgCIIIOUgAEQRRhfPnz2PYsGGoVasWqlWrhuzsbPz000/C/qVLl6JmzZrIycnBtddei+rVqyMrKwunT5+2cNQEQRDqIQFEEEQV7rvvPnz99dfYuHEjdu/eDcYY/vnPf6KsrExo8/fff+M///kPli9fjh07duDEiRMYP368haMmCIJQT7jVAyAIwl789NNP2LhxI7744gt07doVALBy5UqkpqZiw4YN6N+/PwCgrKwMb7zxBq655hoAwBNPPIHp06dbNm6CIAhfIAsQQRASDh8+jPDwcHTq1EnYlpiYiBYtWuDw4cPCtmrVqgniBwCSk5Nx9uxZv46VIAhCKySACIKQwBhT3M5xnPA8IiJCsp/jOMVjCYIg7AYJIIIgJKSlpeHq1av48ssvhW1//fUXjh49imuvvdbCkREEQRgHCSCCICQ0a9YM/fr1w0MPPYSdO3fim2++wZAhQ1C/fn3069fP6uERBEEYAgkggiCq8N5776FDhw649dZb0aVLFzDGsGnTpipuL4IgiECFY+S0JwiCIAgixCALEEEQBEEQIQcJIIIgCIIgQg4SQARBEARBhBwkgAiCIAiCCDlIABEEQRAEEXKQACIIgiAIIuQgAUQQBEEQRMhBAoggCIIgiJCDBBBBEARBECEHCSCCIAiCIEIOEkAEQRAEQYQcJIAIgiAIggg5/j+7u8AaKmStBAAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "da = model.get_value_as_xarray(\"lateral.river.q_av\")\n", + "\n", + "da.unstack().isel(time=0).plot(x=\"lon\")\n", + "plt.scatter(lons, lats, marker=\"o\", c=\"red\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model.finalize()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "lock2", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.5" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/generate_cmip_forcing.ipynb b/docs/generate_cmip_forcing.ipynb index 52891d5..df2f946 100644 --- a/docs/generate_cmip_forcing.ipynb +++ b/docs/generate_cmip_forcing.ipynb @@ -14,15 +14,26 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/bart/miniconda3/envs/lock2/lib/python3.12/site-packages/esmvalcore/experimental/_warnings.py:13: UserWarning: \n", + " Thank you for trying out the new ESMValCore API.\n", + " Note that this API is experimental and may be subject to change.\n", + " More info: https://github.com/ESMValGroup/ESMValCore/issues/498\n" + ] + } + ], "source": [ "from pathlib import Path\n", - "import numpy as np\n", - "from ewatercycle_wflowjl.forcing.forcing import WflowJlForcing\n", - "from ewatercycle_wflowjl.model import WflowJl\n", - "from ewatercycle.base.parameter_set import ParameterSet" + "\n", + "import ewatercycle.forcing\n", + "import ewatercycle.models\n", + "import numpy as np\n" ] }, { @@ -38,7 +49,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -46,17 +57,27 @@ " \"dataset\": \"GFDL-ESM2G\",\n", " \"project\": \"CMIP5\",\n", " \"grid\": \"gr\",\n", - " \"exp\": [\"historical\",],\n", + " \"exp\": \"historical\",\n", " \"ensemble\": \"r1i1p1\",\n", "}\n", "\n", - "wflow_forcing = WflowJlForcing.generate(\n", + "wflow_forcing = ewatercycle.forcing.sources[\"WflowJlForcing\"].generate(\n", " dataset=cmip_dataset,\n", " start_time=\"1990-01-01T00:00:00Z\",\n", - " end_time=\"1995-12-31T00:00:00Z\",\n", - " shape=\"/home/bart/Documents/wflow_humber/shp/humber_catchment.shp\",\n", - " dem_file=\"/home/bart/Documents/wflow_humber/staticmaps.nc\",\n", - ")" + " end_time=\"1992-12-31T00:00:00Z\",\n", + " shape=Path(\"data/wflow/sbm_moselle/moselle.shp\"), # Doesn't need to exist if you specify extract_region.\n", + " dem_file=\"/data/wflow/sbm_moselle/staticmaps-moselle.nc\",\n", + " extract_region={\n", + " \"start_longitude\": 3,\n", + " \"end_longitude\": 11, \n", + " \"start_latitude\": 47, \n", + " \"end_latitude\": 51,\n", + " }\n", + ")\n", + "\n", + "# wflow_forcing = ewatercycle.forcing.sources[\"WflowJlForcing\"].load(\n", + "# \"/home/bart/esmvaltool_output/ewcrepvdu1tkfu_20241128_101417/work/diagnostic/script\"\n", + "# )" ] }, { @@ -67,7 +88,7 @@ "\n", "Wflow.jl requires parameter data to be able to run. Some example datasets are available on the Wflow.jl documentation.\n", "\n", - "Here we use a dataset for the Humber (UK) catchment." + "Here we use the example dataset for the Moselle catchment." ] }, { @@ -76,11 +97,13 @@ "metadata": {}, "outputs": [], "source": [ - "parameters_humber = ParameterSet(\n", - " name=\"humber\",\n", - " directory=Path(\"/home/bart/wflow_humber\"),\n", + "from ewatercycle.base.parameter_set import ParameterSet\n", + "\n", + "parameters_moselle = ParameterSet(\n", + " name=\"moselle\",\n", + " directory=Path(\"/data/wflow/sbm_moselle\"),\n", " target_model=\"WflowJl\",\n", - " config=\"wflow_sbm.toml\",\n", + " config=\"sbm_config.toml\" \n", ")" ] }, @@ -97,14 +120,34 @@ "metadata": {}, "outputs": [], "source": [ - "model = WflowJl(\n", - " parameter_set=parameters_humber,\n", + "model = ewatercycle.models.sources[\"WflowJl\"](\n", + " parameter_set=parameters_moselle,\n", " forcing=wflow_forcing\n", ")\n", "\n", "cfg_file,_ = model.setup()" ] }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/home/bart/ewatercycle/output/wflowjl_20241128_103401/wflow_ewatercycle.toml'" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cfg_file" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -114,180 +157,9 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[ Info: Initialize model variables for model type `sbm`.\n", - "[ Info: Cyclic parameters are provided by `/home/bart/wflow_humber/staticmaps.nc`.\n", - "[ Info: Forcing parameters are provided by `/home/bart/esmvaltool_output/ewcreplel9wopo_20231027_094138/work/diagnostic/script/wflow_GFDL-ESM2G_humber_catchment_1990_1995.nc`.\n", - "[ Info: Set `vertical.precipitation` using NetCDF variable `precip` as forcing parameter.\n", - "[ Info: Set `vertical.temperature` using NetCDF variable `temp` as forcing parameter.\n", - "[ Info: Set `vertical.potential_evaporation` using NetCDF variable `pet` as forcing parameter.\n", - "[ Info: Set `vertical.leaf_area_index` using NetCDF variable `LAI` as cyclic parameter.\n", - "┌ Info: General model settings\n", - "│ reservoirs = true\n", - "│ lakes = false\n", - "│ snow = true\n", - "│ masswasting = true\n", - "└ glacier = false\n", - "[ Info: Set `subcatchment` using NetCDF variable `wflow_subcatch`.\n", - "[ Info: Set `river_location` using NetCDF variable `wflow_river`.\n", - "[ Info: Set `lateral.river.width` using NetCDF variable `wflow_riverwidth`.\n", - "[ Info: Set `lateral.river.length` using NetCDF variable `wflow_riverlength`.\n", - "[ Info: Set `vertical.cfmax` using NetCDF variable `Cfmax`.\n", - "[ Info: Set `vertical.tt` using NetCDF variable `TT`.\n", - "[ Info: Set `vertical.tti` using NetCDF variable `TTI`.\n", - "[ Info: Set `vertical.ttm` using NetCDF variable `TTM`.\n", - "[ Info: Set `vertical.whc` using default value `0.1`.\n", - "[ Info: Set `vertical.w_soil` using default value `0.1125`.\n", - "[ Info: Set `vertical.cf_soil` using NetCDF variable `cf_soil`.\n", - "[ Info: Set `vertical.g_tt` using default value `0.0`.\n", - "[ Info: Set `vertical.g_cfmax` using default value `3.0`.\n", - "[ Info: Set `vertical.g_sifrac` using default value `0.001`.\n", - "[ Info: Set `vertical.glacierfrac` using default value `0.0`.\n", - "[ Info: Set `vertical.glacierstore` using default value `5500.0`.\n", - "[ Info: Set `vertical.theta_s` using NetCDF variable `thetaS`.\n", - "[ Info: Set `vertical.theta_r` using NetCDF variable `thetaR`.\n", - "[ Info: Set `vertical.kv_0` using NetCDF variable `KsatVer`.\n", - "[ Info: Set `vertical.f` using NetCDF variable `f`.\n", - "[ Info: Set `vertical.hb` using default value `10.0`.\n", - "[ Info: Set `vertical.soilthickness` using NetCDF variable `SoilThickness`.\n", - "[ Info: Set `vertical.infiltcappath` using NetCDF variable `InfiltCapPath`.\n", - "[ Info: Set `vertical.infiltcapsoil` using NetCDF variable `InfiltCapSoil`.\n", - "[ Info: Set `vertical.maxleakage` using NetCDF variable `MaxLeakage`.\n", - "[ Info: Set `vertical.c` using NetCDF variable `c`.\n", - "[ Info: Set `vertical.kvfrac` using default value `1.0`.\n", - "[ Info: Set `vertical.waterfrac` using NetCDF variable `WaterFrac`.\n", - "[ Info: Set `vertical.pathfrac` using NetCDF variable `PathFrac`.\n", - "[ Info: Set `vertical.rootingdepth` using NetCDF variable `RootingDepth`.\n", - "[ Info: Set `vertical.rootdistpar` using NetCDF variable `rootdistpar`.\n", - "[ Info: Set `vertical.cap_hmax` using default value `2000.0`.\n", - "[ Info: Set `vertical.cap_n` using default value `2.0`.\n", - "[ Info: Set `vertical.et_reftopot` using default value `1.0`.\n", - "[ Info: Set `vertical.specific_leaf` using NetCDF variable `Sl`.\n", - "[ Info: Set `vertical.storage_wood` using NetCDF variable `Swood`.\n", - "[ Info: Set `vertical.kext` using NetCDF variable `Kext`.\n", - "[ Info: Set `lateral.river.reservoir.locs` using NetCDF variable `wflow_reservoirlocs`.\n", - "[ Info: Set `lateral.river.reservoir.areas` using NetCDF variable `wflow_reservoirareas`.\n", - "[ Info: Set `lateral.river.reservoir.demand` using NetCDF variable `ResDemand`.\n", - "[ Info: Set `lateral.river.reservoir.maxrelease` using NetCDF variable `ResMaxRelease`.\n", - "[ Info: Set `lateral.river.reservoir.maxvolume` using NetCDF variable `ResMaxVolume`.\n", - "[ Info: Set `lateral.river.reservoir.area` using NetCDF variable `ResSimpleArea`.\n", - "[ Info: Set `lateral.river.reservoir.targetfullfrac` using NetCDF variable `ResTargetFullFrac`.\n", - "[ Info: Set `lateral.river.reservoir.targetminfrac` using NetCDF variable `ResTargetMinFrac`.\n", - "[ Info: Read `3` reservoir locations.\n", - "[ Info: Set `ldd` using NetCDF variable `wflow_ldd`.\n", - "[ Info: Set `lateral.land.slope` using NetCDF variable `Slope`.\n", - "[ Info: Set `lateral.subsurface.ksathorfrac` using NetCDF variable `KsatHorFrac`.\n", - "┌ Info: Kinematic wave approach is used for overland flow.\n", - "└ iterate = true\n", - "[ Info: Using a fixed sub-timestep (seconds) 3600 for kinematic wave overland flow.\n", - "[ Info: Set `lateral.land.n` using NetCDF variable `N`.\n", - "┌ Info: Kinematic wave approach is used for river flow.\n", - "└ iterate = true\n", - "[ Info: Using a fixed sub-timestep (seconds) 900 for kinematic wave river flow.\n", - "[ Info: Set `lateral.river.n` using NetCDF variable `N_River`.\n", - "[ Info: Set `lateral.river.bankfull_depth` using NetCDF variable `RiverDepth`.\n", - "[ Info: Set `lateral.river.slope` using NetCDF variable `RiverSlope`.\n", - "[ Info: Create an output NetCDF file `/home/bart/git/pywflow/wflowjl_20231027_094648/run_default/output.nc` for grid data, using compression level `0`.\n", - "[ Info: Create a state output NetCDF file `/home/bart/git/pywflow/wflowjl_20231027_094648/run_default/outstate/outstates.nc`.\n", - "[ Info: Create an output NetCDF file `/home/bart/git/pywflow/wflowjl_20231027_094648/run_default/outstate/outstates.nc` for scalar data.\n", - "[ Info: Set `gauges_src` using NetCDF variable `wflow_gauges_src`.\n", - "[ Info: Set `gauges_src` using NetCDF variable `wflow_gauges_src`.\n", - "┌ Info: Adding scalar output for a map with a reducer function.\n", - "│ fileformat = \"NetCDF\"\n", - "│ param = \"lateral.river.q\"\n", - "│ mapname = \"gauges_src\"\n", - "└ reducer_name = \"only\"\n", - "[ Info: Create an output CSV file `/home/bart/git/pywflow/wflowjl_20231027_094648/run_default/output.csv` for scalar data.\n", - "[ Info: Set `gauges` using NetCDF variable `wflow_gauges`.\n", - "[ Info: Set `gauges_src` using NetCDF variable `wflow_gauges_src`.\n", - "[ Info: Set `gauges_src` using NetCDF variable `wflow_gauges_src`.\n", - "[ Info: Set `gauges` using NetCDF variable `wflow_gauges`.\n", - "┌ Info: Adding scalar output for a map with a reducer function.\n", - "│ fileformat = \"CSV\"\n", - "│ param = \"lateral.river.q_av\"\n", - "│ mapname = \"gauges\"\n", - "└ reducer_name = \"only\"\n", - "[ Info: Set `gauges_src` using NetCDF variable `wflow_gauges_src`.\n", - "┌ Info: Adding scalar output for a map with a reducer function.\n", - "│ fileformat = \"CSV\"\n", - "│ param = \"lateral.river.q_av\"\n", - "│ mapname = \"gauges_src\"\n", - "└ reducer_name = \"only\"\n", - "[ Info: Set `gauges_src` using NetCDF variable `wflow_gauges_src`.\n", - "┌ Info: Adding scalar output for a map with a reducer function.\n", - "│ fileformat = \"CSV\"\n", - "│ param = \"vertical.precipitation\"\n", - "│ mapname = \"gauges_src\"\n", - "└ reducer_name = \"only\"\n", - "[ Info: Set initial conditions from state file `/home/bart/wflow_humber/instate/instates.nc`.\n", - "┌ Warning: The unit of `ssf` (lateral subsurface flow) is now m3 d-1. Please update your input state file if it was produced with a Wflow version up to v0.5.2.\n", - "└ @ Wflow ~/.julia/packages/Wflow/aXumd/src/sbm_model.jl:457\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"satwaterdepth\"\n", - "└ state = (:vertical, :satwaterdepth)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"ssf\"\n", - "└ state = (:lateral, :subsurface, :ssf)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"h_av_land\"\n", - "└ state = (:lateral, :land, :h_av)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"canopystorage\"\n", - "└ state = (:vertical, :canopystorage)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"q_river\"\n", - "└ state = (:lateral, :river, :q)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"volume_reservoir\"\n", - "└ state = (:lateral, :river, :reservoir, :volume)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"h_land\"\n", - "└ state = (:lateral, :land, :h)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"tsoil\"\n", - "└ state = (:vertical, :tsoil)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"h_river\"\n", - "└ state = (:lateral, :river, :h)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"snowwater\"\n", - "└ state = (:vertical, :snowwater)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"ustorelayerdepth\"\n", - "└ state = (:vertical, :ustorelayerdepth)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"h_av_river\"\n", - "└ state = (:lateral, :river, :h_av)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"q_land\"\n", - "└ state = (:lateral, :land, :q)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"snow\"\n", - "└ state = (:vertical, :snow)\n", - "[ Info: Initialized model\n" - ] - } - ], + "outputs": [], "source": [ "model.initialize(cfg_file)" ] @@ -301,7 +173,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -317,15 +189,15 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# Location A, Location B.\n", - "lats = [53.274166, 53.765833,]\n", - "lons = [-0.761666, -0.986666,]\n", + "lats = [50.00, 49.5]\n", + "lons = [ 7.12, 6.37]\n", "\n", - "ntimesteps = int(model._bmi.get_end_time() / model._bmi.get_time_step()) - 1\n", + "ntimesteps = int(model.end_time / model.time_step) - 1\n", "q_locs = np.zeros((ntimesteps, 2,))\n", "dtimes = []\n", "for tstep in range(ntimesteps):\n", @@ -343,7 +215,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -352,13 +224,13 @@ "Text(0, 0.5, 'discharge [m3/s]')" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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" ] @@ -378,7 +250,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "lock2", "language": "python", "name": "python3" }, @@ -392,7 +264,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.0" + "version": "3.12.5" } }, "nbformat": 4, diff --git a/docs/wflowjl_local.ipynb b/docs/wflowjl_local.ipynb deleted file mode 100644 index 4e52fa2..0000000 --- a/docs/wflowjl_local.ipynb +++ /dev/null @@ -1,451 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Wflow.jl in eWaterCycle\n", - "\n", - "This notebook showcases the use of the Wflow.jl model in eWaterCycle.\n", - "\n", - "To install Wflow.jl, uncomment this first block before running the rest of the code:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "# from ewatercycle_wflowjl.model import install_wflow\n", - "# install_wflow()" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "hwloc/linux: Ignoring PCI device with non-16bit domain.\n", - "Pass --enable-32bits-pci-domain to configure to support such devices\n", - "(warning: it would break the library ABI, don't enable unless really needed).\n", - "/home/bart/micromamba/envs/ewatercycle/lib/python3.10/site-packages/esmvalcore/experimental/_warnings.py:13: UserWarning: \n", - " Thank you for trying out the new ESMValCore API.\n", - " Note that this API is experimental and may be subject to change.\n", - " More info: https://github.com/ESMValGroup/ESMValCore/issues/498\n" - ] - } - ], - "source": [ - "from pathlib import Path\n", - "import ewatercycle\n", - "import numpy as np\n", - "from IPython.display import clear_output\n", - "\n", - "from ewatercycle_wflowjl.forcing.forcing import WflowJlForcing\n", - "from ewatercycle_wflowjl.model import WflowJl\n", - "from ewatercycle_wflowjl.utils import get_geojson_locs" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "from ewatercycle.base.parameter_set import ParameterSet\n", - "\n", - "parameters_humber = ParameterSet(\n", - " name=\"humber\",\n", - " directory=Path(\"/home/bart/wflow_humber\"),\n", - " target_model=\"WflowJl\",\n", - " config=\"wflow_sbm.toml\" \n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "model = WflowJl(\n", - " parameter_set=parameters_humber,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "cfg_file,_ = model.setup()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[ Info: Initialize model variables for model type `sbm`.\n", - "[ Info: Cyclic parameters are provided by `/home/bart/wflow_humber/staticmaps.nc`.\n", - "[ Info: Forcing parameters are provided by `/home/bart/wflow_humber/inmaps-era5-2013_xaver.nc`.\n", - "[ Info: Set `vertical.precipitation` using NetCDF variable `precip` as forcing parameter.\n", - "[ Info: Set `vertical.temperature` using NetCDF variable `temp` as forcing parameter.\n", - "[ Info: Set `vertical.potential_evaporation` using NetCDF variable `pet` as forcing parameter.\n", - "[ Info: Set `vertical.leaf_area_index` using NetCDF variable `LAI` as cyclic parameter.\n", - "┌ Info: General model settings\n", - "│ reservoirs = true\n", - "│ lakes = false\n", - "│ snow = true\n", - "│ masswasting = true\n", - "└ glacier = false\n", - "[ Info: Set `subcatchment` using NetCDF variable `wflow_subcatch`.\n", - "[ Info: Set `river_location` using NetCDF variable `wflow_river`.\n", - "[ Info: Set `lateral.river.width` using NetCDF variable `wflow_riverwidth`.\n", - "[ Info: Set `lateral.river.length` using NetCDF variable `wflow_riverlength`.\n", - "[ Info: Set `vertical.cfmax` using NetCDF variable `Cfmax`.\n", - "[ Info: Set `vertical.tt` using NetCDF variable `TT`.\n", - "[ Info: Set `vertical.tti` using NetCDF variable `TTI`.\n", - "[ Info: Set `vertical.ttm` using NetCDF variable `TTM`.\n", - "[ Info: Set `vertical.whc` using default value `0.1`.\n", - "[ Info: Set `vertical.w_soil` using default value `0.1125`.\n", - "[ Info: Set `vertical.cf_soil` using NetCDF variable `cf_soil`.\n", - "[ Info: Set `vertical.g_tt` using default value `0.0`.\n", - "[ Info: Set `vertical.g_cfmax` using default value `3.0`.\n", - "[ Info: Set `vertical.g_sifrac` using default value `0.001`.\n", - "[ Info: Set `vertical.glacierfrac` using default value `0.0`.\n", - "[ Info: Set `vertical.glacierstore` using default value `5500.0`.\n", - "[ Info: Set `vertical.theta_s` using NetCDF variable `thetaS`.\n", - "[ Info: Set `vertical.theta_r` using NetCDF variable `thetaR`.\n", - "[ Info: Set `vertical.kv_0` using NetCDF variable `KsatVer`.\n", - "[ Info: Set `vertical.f` using NetCDF variable `f`.\n", - "[ Info: Set `vertical.hb` using default value `10.0`.\n", - "[ Info: Set `vertical.soilthickness` using NetCDF variable `SoilThickness`.\n", - "[ Info: Set `vertical.infiltcappath` using NetCDF variable `InfiltCapPath`.\n", - "[ Info: Set `vertical.infiltcapsoil` using NetCDF variable `InfiltCapSoil`.\n", - "[ Info: Set `vertical.maxleakage` using NetCDF variable `MaxLeakage`.\n", - "[ Info: Set `vertical.c` using NetCDF variable `c`.\n", - "[ Info: Set `vertical.kvfrac` using default value `1.0`.\n", - "[ Info: Set `vertical.waterfrac` using NetCDF variable `WaterFrac`.\n", - "[ Info: Set `vertical.pathfrac` using NetCDF variable `PathFrac`.\n", - "[ Info: Set `vertical.rootingdepth` using NetCDF variable `RootingDepth`.\n", - "[ Info: Set `vertical.rootdistpar` using NetCDF variable `rootdistpar`.\n", - "[ Info: Set `vertical.cap_hmax` using default value `2000.0`.\n", - "[ Info: Set `vertical.cap_n` using default value `2.0`.\n", - "[ Info: Set `vertical.et_reftopot` using default value `1.0`.\n", - "[ Info: Set `vertical.specific_leaf` using NetCDF variable `Sl`.\n", - "[ Info: Set `vertical.storage_wood` using NetCDF variable `Swood`.\n", - "[ Info: Set `vertical.kext` using NetCDF variable `Kext`.\n", - "[ Info: Set `lateral.river.reservoir.locs` using NetCDF variable `wflow_reservoirlocs`.\n", - "[ Info: Set `lateral.river.reservoir.areas` using NetCDF variable `wflow_reservoirareas`.\n", - "[ Info: Set `lateral.river.reservoir.demand` using NetCDF variable `ResDemand`.\n", - "[ Info: Set `lateral.river.reservoir.maxrelease` using NetCDF variable `ResMaxRelease`.\n", - "[ Info: Set `lateral.river.reservoir.maxvolume` using NetCDF variable `ResMaxVolume`.\n", - "[ Info: Set `lateral.river.reservoir.area` using NetCDF variable `ResSimpleArea`.\n", - "[ Info: Set `lateral.river.reservoir.targetfullfrac` using NetCDF variable `ResTargetFullFrac`.\n", - "[ Info: Set `lateral.river.reservoir.targetminfrac` using NetCDF variable `ResTargetMinFrac`.\n", - "[ Info: Read `3` reservoir locations.\n", - "[ Info: Set `ldd` using NetCDF variable `wflow_ldd`.\n", - "[ Info: Set `lateral.land.slope` using NetCDF variable `Slope`.\n", - "[ Info: Set `lateral.subsurface.ksathorfrac` using NetCDF variable `KsatHorFrac`.\n", - "┌ Info: Kinematic wave approach is used for overland flow.\n", - "└ iterate = true\n", - "[ Info: Using a fixed sub-timestep (seconds) 3600 for kinematic wave overland flow.\n", - "[ Info: Set `lateral.land.n` using NetCDF variable `N`.\n", - "┌ Info: Kinematic wave approach is used for river flow.\n", - "└ iterate = true\n", - "[ Info: Using a fixed sub-timestep (seconds) 900 for kinematic wave river flow.\n", - "[ Info: Set `lateral.river.n` using NetCDF variable `N_River`.\n", - "[ Info: Set `lateral.river.bankfull_depth` using NetCDF variable `RiverDepth`.\n", - "[ Info: Set `lateral.river.slope` using NetCDF variable `RiverSlope`.\n", - "[ Info: Create an output NetCDF file `/home/bart/git/pywflow/wflowjl_20231027_125448/run_default/output.nc` for grid data, using compression level `0`.\n", - "[ Info: Create a state output NetCDF file `/home/bart/git/pywflow/wflowjl_20231027_125448/run_default/outstate/outstates.nc`.\n", - "[ Info: Create an output NetCDF file `/home/bart/git/pywflow/wflowjl_20231027_125448/run_default/outstate/outstates.nc` for scalar data.\n", - "[ Info: Set `gauges_src` using NetCDF variable `wflow_gauges_src`.\n", - "[ Info: Set `gauges_src` using NetCDF variable `wflow_gauges_src`.\n", - "┌ Info: Adding scalar output for a map with a reducer function.\n", - "│ fileformat = \"NetCDF\"\n", - "│ param = \"lateral.river.q\"\n", - "│ mapname = \"gauges_src\"\n", - "└ reducer_name = \"only\"\n", - "[ Info: Create an output CSV file `/home/bart/git/pywflow/wflowjl_20231027_125448/run_default/output.csv` for scalar data.\n", - "[ Info: Set `gauges` using NetCDF variable `wflow_gauges`.\n", - "[ Info: Set `gauges_src` using NetCDF variable `wflow_gauges_src`.\n", - "[ Info: Set `gauges_src` using NetCDF variable `wflow_gauges_src`.\n", - "[ Info: Set `gauges` using NetCDF variable `wflow_gauges`.\n", - "┌ Info: Adding scalar output for a map with a reducer function.\n", - "│ fileformat = \"CSV\"\n", - "│ param = \"lateral.river.q_av\"\n", - "│ mapname = \"gauges\"\n", - "└ reducer_name = \"only\"\n", - "[ Info: Set `gauges_src` using NetCDF variable `wflow_gauges_src`.\n", - "┌ Info: Adding scalar output for a map with a reducer function.\n", - "│ fileformat = \"CSV\"\n", - "│ param = \"lateral.river.q_av\"\n", - "│ mapname = \"gauges_src\"\n", - "└ reducer_name = \"only\"\n", - "[ Info: Set `gauges_src` using NetCDF variable `wflow_gauges_src`.\n", - "┌ Info: Adding scalar output for a map with a reducer function.\n", - "│ fileformat = \"CSV\"\n", - "│ param = \"vertical.precipitation\"\n", - "│ mapname = \"gauges_src\"\n", - "└ reducer_name = \"only\"\n", - "[ Info: Set initial conditions from state file `/home/bart/wflow_humber/instate/instates.nc`.\n", - "┌ Warning: The unit of `ssf` (lateral subsurface flow) is now m3 d-1. Please update your input state file if it was produced with a Wflow version up to v0.5.2.\n", - "└ @ Wflow ~/.julia/packages/Wflow/aXumd/src/sbm_model.jl:457\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"satwaterdepth\"\n", - "└ state = (:vertical, :satwaterdepth)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"ssf\"\n", - "└ state = (:lateral, :subsurface, :ssf)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"h_av_land\"\n", - "└ state = (:lateral, :land, :h_av)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"canopystorage\"\n", - "└ state = (:vertical, :canopystorage)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"q_river\"\n", - "└ state = (:lateral, :river, :q)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"volume_reservoir\"\n", - "└ state = (:lateral, :river, :reservoir, :volume)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"h_land\"\n", - "└ state = (:lateral, :land, :h)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"tsoil\"\n", - "└ state = (:vertical, :tsoil)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"h_river\"\n", - "└ state = (:lateral, :river, :h)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"snowwater\"\n", - "└ state = (:vertical, :snowwater)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"ustorelayerdepth\"\n", - "└ state = (:vertical, :ustorelayerdepth)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"h_av_river\"\n", - "└ state = (:lateral, :river, :h_av)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"q_land\"\n", - "└ state = (:lateral, :land, :q)\n", - "┌ Info: Setting initial state from NetCDF.\n", - "│ ncpath = \"/home/bart/wflow_humber/instate/instates.nc\"\n", - "│ ncvarname = \"snow\"\n", - "└ state = (:vertical, :snow)\n", - "[ Info: Initialized model\n" - ] - } - ], - "source": [ - "model.initialize(cfg_file)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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owt44w1XNfFalF4nIfAeGjQzISnGUH5G5jHQiv7L+lWa+oqIiJCYm+l6Pi4sLuZ7HEzgKUJKkSq+FW977+tmzZ9GvXz8sXLgQycnJmuovEtcEU9704ujRowNe15NeXLRoES5duoRq1apVWufixYsBKc7S0lITak9ERGSuK32mDDzo+D/rJiYmBgRTSpKTk1G1atVKWajjx49Xyj55paamyi4fExODq666Ct999x0OHjyIe+6553/rVVEBAIiJicH+/ftx3XXXadovJ7gmmLIivZiWllZpnalTp2LChAnmVZzIRcx+aLKW0X5EJLbY2Fi0atUK69evR8+ePX2vr1+/Hj169JBdJzs7Gx999FHAa+vWrUPr1q1RrVo1NGnSBHv37g14/+9//zvOnj2Ll19+GfXr1zd/Ryzgqj5TgLnpRTljxoxBSUmJ76+oqMhgjYnIn51NfAzgKJJV/OfZfHr/9IwEHDFiBF577TW8/vrr2LdvH5555hkUFhZi8ODBAK7cQx955BHf8oMHD8ahQ4cwYsQI7Nu3D6+//joWLVqEUaNGAQDi4+PRrFmzgL/atWsjISEBzZo1Q2xsrDkHy2KuyUxZkV6UExcXF7a9mIiIyGlm9ZnSok+fPjh16hQmTpyIo0ePolmzZli9ejUyMjIAAEePHg0YFJaZmYnVq1fjmWeewdy5c5Geno7Zs2dHXL9l1wRTVqQXicgeZjcfEtGVzJTd80wBwJAhQzBkyBDZ95YsWVLptZycHHz11Veqy5crQ3SuCaaAK+nF/v37o3Xr1sjOzsarr75aKb14+PBhvPHGGwCupBfnzJmDESNGYODAgcjPz8eiRYvw1ltvObkbRMKyKuDxH9lnZ1AVPKLQ/3UiIrO4KphiepHInZzMTMnNzO5EYEdktnLJg3LJwIOODaxLgVwVTAHWpxeJKDIpjSxkYEVu5e1Irn99fc18VJnrgikiIrOwLxcRmYHBFBERkQtVSFVQYWA0X4WO0Xwkj8EUEVnOqQ7o4YhUFyKt2MwnDgZTRBR1GEQRkZkYTBGRK4iY2SJyUgWMjcirMK8qUY/BFBEJL1I6ijMgJDMZn7TTdU+UExaPJBHZ4sCwkYqTaKpZt9Hsf/BZe0QkJGamiIiIXMj4s/mYTzELgykisgWzSkTmqoAHFTDSZ4ozoJuFwRQR2ULusS5EpB8zU+JgMEVEwouUDuhEFJkYTBERBVEadeefVWNwR04zPmknM1NmYTBFRETkQhWSBxVG5pkysC4FYjBFRMKye16mUNtjVoqIlDCYIiJbifqcPiUMokhUFQab+Thpp3kYTBGRrdR0Jnci2ApXLzPq4j+ikYEZGVUhVUGFgRF5RtalQDySREQKOI0DEanBzBQRmSJcNskNTXvBddT7+BsiO5TDg3IDE28aWZcCMZgiIiJyITbziYPBFBEZ5t8HiJkcIoo2DKaIyFRynazd0uHaroDQDceCxFcOY0115eZVJeoxmCIiw+SCA//XtAQPTgVecv2jGPSQyNjMJw4GU0QkBKc7qLOpktyGDzoWB4MpInKcCM2AHLlHRHoxmCIiInIhCR5UGOgzJXFqBNMwmCIixzjdtKdEtPoQyWEznzgYTBGRYxi0EFEkYDBFRETkQhWSBxWS/qY6I+tSIAZTROQqVnZWlytXrlN6JGTUROj0T8aUowrKDTxi18i6FIjBFBG5glMj7SIp4OBoRSJrMJgiIiJyITbziYPBFBG5iv98UJGUNbKS0vHicXS3ClRBhYGmOiPrUiAGU0TkCnKPp2G/H2N47IjMwWCKiFzNaHZFz/pKfY8YnJCdyiUPyg001RlZlwIxmCIi1zL6CBj/dcNludQ8BFn0ZjNm8iIL+0yJg8EUERGRC0lSFVQYmMVc4gzopmEwRUQRQUtWSG7ZRrP/EbKMSMjoRMI+EImIwRQRRRQ1zX5KwZJ3Xb3NdewYT3YqhwflBh5WbGRdCsRgiogiglIfJi1BjVkBkAiBlH9QKUJ9yHwVkrF+TxWSiZWJcmwwJSLXCpeFcmsQYeZM5W49BkRuwswUESkSfXQaYF/dmOkh0VQY7IBuZF0KxGCKiIjIhSrgQYWBfk9G1qVADKaIiFQIHvknanYqXBNhqPdF3Sci0TGYIiLSyOrnA5pRvtzIwnATj4ocJFJlnAFdHAymiMi1nLzxBwcoSg8RDl5eDTVBTbhH2gTP7q60HLkX+0yJg8EUEUUtMzMxoTJAZgoO3rSMaFSzLDvaE2nHYIqIyAClYMVIE5pSM59SGXKBlVwzn5rty+0PgyoxVcDgs/nYAd00DKaIiIhcSDI4mk9iMGUaBlNEFHWsbIYDlDM5ajM9Rpof5fbN6ONx7MAsmHYVksHMFDugm4bBFBFFHbVNc0r09I/SO7WClvqFC+JExucakpsxmCKiqKa307jRAMXIfFD+7zPwiF4czadO3bp1NS3v8Xjw1VdfISMjQ/U6DKaIyDEiBQRmPBBZT5ZKaT0to/DUbo9Zn8jCZj51zpw5g1mzZiEpKSnsspIkYciQISgvL9e0DQZTRKQLb8yVmRW08LgSmevBBx9EvXr1VC379NNPay6fwRQREZEL8dl86lRUVGha/uzZs5q3wWCKiMhkRh8BQ6QGm/nEwWCKiGSxGU9s/GyIzHP69Gl89NFHeOSRR3Stz2CKiGRZ+TBfUYfqi9Qh3irRsI/Rgpkp8xQWFuKxxx5jMEVE5rPqWXN2PMPOjbQ8QkZPucGvMaByNwZT6pWWloZ8X08/KX8MpoiIiCii1a5dGx6PcvAoSVLI98NhMEVEsoKzGcwmWceuY6s0v5UIGSqR6uIWzEypl5CQgHHjxqFt27ay7//0008YNGiQ7vKjY/pTItLM/6YW/P/+N3/vn1fwv8lZ3uY8/z5wXv6fJbmPhP+dHkHPn6Rzu/PmzUNmZibi4+PRqlUrbN68OeTymzZtQqtWrRAfH49GjRph/vz5Ae8vXLgQHTp0QJ06dVCnTh107twZO3bs0Fk7eTfffDMAICcnR/bvlltugSTpPSLMTBFRCKFutOFm8dbzzDvvetF6gzdzvxnQRj4nMlMrVqzA8OHDMW/ePNx6661YsGABunXrhu+//x4NGjSotHxBQQHuvPNODBw4EG+++Sa2bNmCIUOG4Oqrr0avXr0AABs3bsRDDz2E9u3bIz4+HtOnT0eXLl3w3Xff4ZprrtG9f/769u2L33//XfH91NRUjB8/Xnf5rgmmTp8+jWHDhmHVqlUAgO7du+OVV15B7dq1FdcZMGAAli5dGvBa27ZtsW3bNiurShSVQjVV6Q2soplZzV5uON7RHEC7zYwZM/DEE0/gySefBADMmjULa9euxT//+U9MnTq10vLz589HgwYNMGvWLABA06ZN8eWXX+Kll17yBVPLli0LWGfhwoV499138dlnn+keXRds4MCBId9PSUmJjmCqb9+++PXXX7FmzRoAwFNPPYX+/fvjo48+Crlebm4uFi9e7Pt3bGyspfUkoiuUMlfMmKgTDUEUGWNWZip4pFtcXBzi4uIqLV9WVoZdu3Zh9OjRAa936dIFW7duld1Gfn4+unTpEvBa165dsWjRIly6dAnVqlWrtM758+dx6dIlzQ8o1urXX39Feno6qlQx3uPJFcHUvn37sGbNGmzbts3XeWzhwoXIzs7G/v370bhxY8V14+LikJqaaldViYiIbGFWMFW/fv2A18ePH4+8vLxKy588eRLl5eVISUkJeD0lJQXFxcWy2yguLpZd/vLlyzh58iTS0tIqrTN69Ghcc8016Ny5s5bd0SwrKwt79uxBo0aNDJflimAqPz8fSUlJAb3w27Vrh6SkJGzdujVkMLVx40bUq1cPtWvXRk5ODiZPnhzyYYcXL17ExYsXff8ONzcFEV0RrlkqeO4kuXWdxKYmilZFRUVITEz0/VsuK+UveAqBcNMKyC0v9zoATJ8+HW+99RY2btyI+Pj4sHU3wkiH82CuCKaKi4tlA6B69eopRsMA0K1bN/Tu3RsZGRkoKCjAs88+iz/+8Y/YtWuX4skydepUTJgwwbS6E0ULLYFIcP+q4EBLLrhioGOclbPak/3MykwlJiYGBFNKkpOTUbVq1Ur33ePHj1fKPnmlpqbKLh8TE4Orrroq4PWXXnoJU6ZMwaeffooWLVpo2RXHORpM5eXlhQ1cdu7cCUA+gg0XDffp08f3/82aNUPr1q2RkZGBTz75BPfdd5/sOmPGjMGIESN8/y4tLa2UAiUic8jd0JVu8lYFWCJkxYj0kCQPJAPBlNZ1Y2Nj0apVK6xfvx49e/b0vb5+/Xr06NFDdp3s7OxKfZvXrVuH1q1bB/SXevHFF/H8889j7dq1aN26taZ66TV27FjT+mU5GkwNHToUDz74YMhlGjZsiG+++QbHjh2r9N6JEycUo2E5aWlpyMjIwE8//aS4jFLHOyJyllzgZHSUoH/THoMqovBGjBiB/v37o3Xr1sjOzsarr76KwsJCDB48GMCVhMThw4fxxhtvAAAGDx6MOXPmYMSIERg4cCDy8/OxaNEivPXWW74yp0+fjmeffRbLly9Hw4YNfZmsWrVqoVatWpbty5gxY1BeXo49e/YgIyMDderU0V2Wo8FUcnIykpOTwy6XnZ2NkpIS7NixA23atAEAbN++HSUlJWjfvr3q7Z06dQpFRUWyHd6IyH1C9cMiinTeyTeNrK9Vnz59cOrUKUycOBFHjx5Fs2bNsHr1amRkZAAAjh49isLCQt/ymZmZWL16NZ555hnMnTsX6enpmD17tm9aBODKJKBlZWW4//77A7al1BHeiOHDh6N58+Z44oknUF5ejpycHGzduhU1atTAxx9/jI4dO+oq1xV9ppo2bYrc3FwMHDgQCxYsAHBlaoS77747oPN5kyZNMHXqVPTs2RPnzp1DXl4eevXqhbS0NBw8eBBjx45FcnJyQHqSiIjIjZx6nMyQIUMwZMgQ2feWLFlS6bWcnBx89dVXiuUdPHhQVz30ePfdd9GvXz8AwEcffYQDBw7ghx9+wBtvvIFx48Zhy5Ytusp1RTAFXJnUa9iwYb75Krp37445c+YELLN//36UlJQAAKpWrYq9e/fijTfewJkzZ5CWloZOnTphxYoVSEhIsL3+RGQtNX2t2On6f/G4UDQ6efKkb7qk1atX44EHHsCNN96IJ554ArNnz9ZdrmuCqbp16+LNN98MuYz/MMfq1atj7dq1VleLiAThP0qNowHD8z9OHOHnTnZ3QI8EKSkp+P7775GWloY1a9Zg3rx5AK5MFFq1alXd5bommCKKBkr9fniTC8+/IzmPV3jsfO9+TjXzudljjz2GBx54AGlpafB4PLjjjjsAXOmH3aRJE93lMpgiEkDwzYwdq/VjIBWafwDFc8vdmJnSLi8vD82aNUNRURF69+7tG71ftWrVSo/J0YLBFBEREUWN4FGDAPDoo48aKpPBFJFD1HYA5qzV9oi24xxt+xuJJIPNfNGYmbIKgykiGxjtEM3+QEQUTAJg5PFy5j2ZjhhMEVkkVH8UBkTiYL8hIjKKwRSRSdSMxOONW1xynxODXhJZBTzw2DwDOsljMEWkU6gReHZslzd660RbsyrPKXfiaD7jjh07hosXL6JBgwaGyqliUn2IiIiIhHT27Fn069cPGRkZePTRR1FWVoY///nPSEtLQ2ZmJnJyclBaWqq7fAZTRDp4Mxb+f3aQ204kNx1yLiRr2XnuhqsHP2vtvJN2GvmLFmPHjsWuXbswatQoFBYW4oEHHsD/+3//D5s3b8bGjRvx22+/Ydq0abrLZzMfmU5uyL+ZF0k1z2BTs7weIjWHyD0+RYR6uQ2PWfQ1a0YKSTI4mi+KhvN9+OGHWLp0KTp16oRevXrh2muvxYcffohbb70VADBt2jSMGDECkydP1lU+gykyTaggSksn7OCLefDySo/BUMramBVoiPKrOXjfRakXEZGojh8/juuvvx4AkJ6ejurVq6Nx48a+92+66SYUFRXpLp/BFJlGLlhR+1qoX8RywZWeCS/1UrstNetbTe442vW8P7kO+UaPnVP0fGbM6pDd2AFdvauuugonTpxA/fr1AQA9evRA7dq1fe+fO3fO92gZPRhMkRD0TGBpF6MBlNX1Dc76hQpqggMcM5sH5YI4vc28ojRbKgWmbFo1FwNRfRhMqdeiRQvs3LkTN998MwBg+fLlAe/v3LkTTZs21V0+gykiIiIXqpA88BgIiKKpA/qyZctQpYrymLuUlBTd/aUABlNElrFz3invttQ2lQavZwX/st2SyQnVP0/pdfZZIxJf3bp1Q77frVs3Q+UzmKKowaaEK5wOAtzwOYQ7RsGBYqSIpH2JBhzNp8+FCxfwzTff4Pjx46ioqAh4r3v37rrKZDBFEc//xmh1dsSJAMUtN0C1n4NowZYbMmoUna4EU0b6TJlYGZdYs2YNHnnkEZw8ebLSex6PB+Xl5brKZTBFUcOMkX1y3DpizSlufQYem/OI3G/o0KHo3bs3nnvuOaSkpJhWLoMpikpGb+KREEC5td5GyAVE4SaslGvyi4TP323cFHjbhaP5tDt+/DhGjBhhaiAF8HEyREREriSZ8Bdt7r//fmzcuNH0cpmZooikNB+Qkc7XcvM3kfjCZaPCnQtKGZHgGejtPh+YqSHSbs6cOejduzc2b96M5s2bo1q1agHvDxs2TFe5DKYoYig9zsbM0Wsi3bjUPlIn0qkNcsPNxh8q6ApVXrjH+lg103wkfNbsh2YMm/m0W758OdauXYvq1atj48aN8Hj+9xh4PB4GU0ReSsPWtTwf0J/VF3yjo9eC9ysSbrJ6GA2a9c6FpdTnyorMVTR/viTDaFtdFLbz/f3vf8fEiRMxevTokJN4asVgilSJlIu4kRubVftv9oSWkZC5EPFz0ircMxK11DMSPtNQ1Iy0VZpGI9T7Ec9gZgpRmJkqKytDnz59TA2kAHZAJyIioijx6KOPYsWKFaaXy8wUqSb6r2NR62Unq+bSslO4fXBrltTINBxu3N9g4R4SrTdT5/bz3QjOgK5deXk5pk+fjrVr16JFixaVOqDPmDFDV7kMpkiVaLtoRdO+ikDN8Va6gUZCoBHplOboMkM0f/7sgK7d3r170bJlSwDAt99+G/Cef2d0rRhMUdTT01fDDUQOOOT6D8llKyL1s/Fn1yhApzn9TEgiANiwYYMl5TKYIlfT2wRitJnBDZTmUjJzP/U0/YabaTzca0a45ZmAkZIJVjreRo6zSJ+T4ySPsU7kUZiZsgqDKVIt+JelXRe0UDcVrSPh5EZY2bEfVk/4GSqrE3xj1jqfUijhHsUiej87kfGYUTjsM6XOfffdhyVLliAxMVHV8g8//DBmzpyJevXqqd4GgykiIiKKWB9++CFOnDihallJkvDRRx9h0qRJDKYoclidOXIiK6X0mhnl+tMyQ7rRZkA1I/AinZH5wiIxCxXqu8uMpUk4aacqkiThxhtvtHQbDKZINzuayLQ03Yl2gQ7XP8fL/yasJegIV66e5s9QzYHhygn1viid4UU9V6KB0uOegl9Tuy5xNJ9aejqdX3PNNZqWZzBFmimNtuJFLlC4YCfUa1ofEWPm56BUltrgysw+WZEsUrN14QJVuQxecBDPoJfMlJOTY/k2GEyRKUS+2Fl9QQ4XyKgJTuQemut9Tc9z4vQKtb7Woe0inxNK+2L0XAnXIV+vSAsq5Eb3hZvUkxRESVOd6BhMkSFW3TzMovSL1wpK/Yb0ZPL0zAbtNDfeAJVu4lYLdy5aPfpTZKJeS0TEZj5xMJgiIiJyI3ZAFwaDKTJEpGyE0zMsB/f1MCvzpIadx19uH92cTbCi3npndFcqS0TBn7nR753cJLOi7jtRMAZTFHFCdd7W0onayPB2p6ZcsJPSZKC8AQbSOzjATcfRzGDaTfvtPM9//oysH10mTJiAfv364brrrjO1XAZTFNFCjSgCQj8XLdzM61po7bSt5eYkwlQDgPPBnVEizWnmlk7Ybv/MXY/NfJqtXLkSEydOxC233IJ+/fqhT58+uPrqqw2Xy2CK6D/UzPdk5Wg5coZVQUukftZGJyZ1c5Mwud8333yD7777DsuWLcOMGTMwYsQIdO7cGf369cO9996LGjVq6Cq3isn1JCIiIjtIJvxFoZtuuglTpkzBgQMHsGHDBmRmZmL48OFITU3VXSYzUxQ15H4RG5kcU64MtduNRJEw0WIkTDjq5uNPGkmeK39G1o9yNWvWRPXq1REbG4uzZ8/qLofBFJlC5IBB7WNd1Jbj5XT/GlGPtx3MajJSWl+uL1g0H285InznI2l0JNmnoKAAy5cvx7Jly/Djjz/i9ttvR15eHnr37q27TAZTZIjT0xEoCVcfrQ//DV5Wzf6KdkyosnADDUT4DEUKWg4MG2nKd95IBtDojxoRjqdZJOnKn5H1o012djZ27NiB5s2b47HHHkPfvn01P4dPDoMpimjhLpp6M0CROsQ9GplxjlhBT9BidvAX6hl6eill/SLhMUW242g+zTp16oTXXnsNN910k6nlMpgiQ9zWBKK2vmbfNKIJR205S0uGRy5IEnHiWT7rkMwyZcoUS8plMEVERORG7ICuy6+//opVq1ahsLAQZWVlAe/NmDFDV5kMpsgUImUhlOqidSLM4DmnRNk/t4qEkXKi0nKOhmpaM3uyWrOYud1IOuc80pU/I+tHm88++wzdu3dHZmYm9u/fj2bNmuHgwYOQJAk333yz7nIZTJEhonZAl2NkkkHvfyPpQuyUcJOjmnGM9T7CRVThvl96mva0rEeCYp8pzcaMGYORI0di4sSJSEhIwMqVK1GvXj08/PDDyM3N1V0ugykyxA1BlB5KN2NmqcKTOyfUjMDSey5Z0UlaNE49yNqq8z34M7Jz2hGKbvv27cNbb70FAIiJicHvv/+OWrVqYeLEiejRowf+9Kc/6SqXwRSZQoSLnxkXfgZL5rIjQxSqE7UZZUfCOaF3PiarmrqNBr6RlnnUjX2mNKtZsyYuXrwIAEhPT8cvv/ziG9l38uRJ3eUymCLXi8RMhFPMbMp08iYnUgCkpy6hgoVQWRyzR+BZ3dStFAiH20e1y0Y8NvNp1q5dO2zZsgVZWVm46667MHLkSOzduxfvvfce2rVrp7tcBlNEREQUFWbMmIFz584BAPLy8nDu3DmsWLEC119/PWbOnKm7XAZTFMBtnazNrK/b9t0qejuFG8kGmXHs7f7s1I6E0zLvltIx1DJLuxWd+q3qR6WUgZPLiMktp7Rs1HyPmZnSrFGjRr7/r1GjBubNmye73FtvvYXu3bujZs2aqsplMEWmsOMCZsfILy3rOH3BVppoUU64TvRKr6kNBJw6Hk71aZKb8DJc85P/MmoeY2O0L5gVx0XLTOV6y1UKqtTOVB9Vzf4MpiwzaNAgtG3bNiD4CoXBFAUQucOtFTNra71RiXrBDvWZ+WcTtKxnx+dv9FwTIahV2r5SBgXQFvSG2oaeepnFzmOv9brEDupklKTxwYUMpsgUdt54zWbkRm5kfbso1c/M42k0CBchKFLDrGOmJXAXjdMTd2rtZB/RHdQ5mk8YuoKpY8eOYdSoUfjss89w/PjxShFceXm5KZUjZ1iRAdJLpKa94DpwhvT/pfdcMZrpsyOTauXUC1SZmmBJy2ceKrhy++fIGdDFoSuYGjBgAAoLC/Hss88iLS0NHg+jWyIiIopOVfSs9MUXX2DZsmX405/+hHvvvRc9evQI+LPC5MmT0b59e9SoUQO1a9dWtY4kScjLy0N6ejqqV6+Ojh074rvvvrOkfmS9A8NGGv4lGdx/yPsrV++khk78svXW13/7euriXcfIPvjXxWl6P0e1RNhHCqT3exsxJBP+dJg3bx4yMzMRHx+PVq1aYfPmzSGX37RpE1q1aoX4+Hg0atQI8+fPr7TMypUrkZWVhbi4OGRlZeH999/XVzmH6Aqm6tevr7lzllFlZWXo3bu3pqnep0+fjhkzZmDOnDnYuXMnUlNTcccdd+Ds2bMW1pTMZMYN3ys4APG+ZpS3TNE6pZvJSNBpNSs+UxKb3DVBy/np1A+hSLBixQoMHz4c48aNw+7du9GhQwd069YNhYWFsssXFBTgzjvvRIcOHbB7926MHTsWw4YNw8qVK33L5Ofno0+fPujfvz++/vpr9O/fHw888AC2b99u125VkpGRgWrVqqleXlcz36xZszB69GgsWLAADRs21FOEZhMmTAAALFmyRNXykiRh1qxZGDduHO677z4AwNKlS5GSkoLly5dj0KBBVlU1aoiSkdDDipuvW4+Fk8w49lrnezKC/aesp6VPVKT/iAnHA4N9pnSsM2PGDDzxxBN48sknAVyJB9auXYt//vOfmDp1aqXl58+fjwYNGmDWrFkAgKZNm+LLL7/ESy+9hF69evnKuOOOOzBmzBgAVx5GvGnTJsyaNcv3HD27ffvtt5qW1xVM9enTB+fPn8d1112HGjVqVIrefvvtNz3FmqqgoADFxcXo0qWL77W4uDjk5ORg69atDKYoojjVCd6swQpm11tpigizthPtN3GRyGWoGOBqU1paGvDvuLg4xMXFVVqurKwMu3btwujRowNe79KlC7Zu3Spbdn5+fsB9GAC6du2KRYsW4dKlS6hWrRry8/PxzDPPVFrGG4CZqU6dOqr6eXs8Hpw6dUp1ubozU6IrLi4GAKSkpAS8npKSgkOHDimud/HiRd9DEIHKJxkREZEQTJoaoX79+gEvjx8/Hnl5eZUWP3nyJMrLy2Xvq957brDi4mLZ5S9fvoyTJ08iLS1NcRmlMo149tln8fzzz6Nr167Izs4GcCXgW7t2LZ599lnUrVtXV7m6gqlHH31U18aC5eXl+ZrvlOzcuROtW7fWvY3gCFSSpJBR6dSpU8PWKdq59Re5yBOShqKmScnu2b+d3L5I245kdmd4zJoQ163fc11MmgG9qKgIiYmJvpflslL+tN5X5ZYPfl1rmXpt2bIFEydOxNChQ32vDRs2DHPmzMGnn36KDz74QFe5uiftLC8vxwcffIB9+/bB4/EgKysL3bt3R9WqVVWXMXToUDz44IMhl9HbJys1NRXAlag4LS3N9/rx48crRcD+xowZgxEjRvj+XVpaWilqpyvcdqFSujmINK+WP6XHkcjNrG3HzUPU2d/JXHKPvHFqUl692xf1Oy2qxMTEgGBKSXJyMqpWrVopYxTqvpqamiq7fExMDK666qqQy4S6V+u1du1aTJs2rdLrXbt2rdR8qYWuYOrnn3/GnXfeicOHD6Nx48aQJAk//vgj6tevj08++QTXXXedqnKSk5ORnJyspwphZWZmIjU1FevXr0fLli0BXGnv3bRpk+yB9FJqKybeRO2kdBMQ6TMwOqWC0TKcJPfsPDP3JdTn7NZjFo5cABSVDy/WwuZn88XGxqJVq1ZYv349evbs6Xt9/fr1itMiZWdn46OPPgp4bd26dWjdurWvv3V2djbWr18f0G9q3bp1aN++vbYKqnDVVVfh/fffx1//+teA1z/44ANfcKeHrmBq2LBhuO6667Bt2zZf++KpU6fQr18/DBs2DJ988onuCikpLCzEb7/9hsLCQpSXl2PPnj0AgOuvvx61atUCADRp0gRTp05Fz5494fF4MHz4cEyZMgU33HADbrjhBkyZMgU1atRA3759Ta9fJFL6Zeqmi5rIF+FQDypWmrXZzNnfnToudgaEWral5VyxowO63IhTux/VY2XAGGqbHGGrjhMzoI8YMQL9+/dH69atkZ2djVdffRWFhYUYPHgwgCutO4cPH8Ybb7wBABg8eDDmzJmDESNGYODAgcjPz8eiRYsCRun95S9/we23345p06ahR48e+PDDD/Hpp5/iiy++0L9zCiZMmIAnnngCGzdu9PWZ2rZtG9asWYPXXntNd7m6gqlNmzYFBFLAlWjvhRdewK233qq7MqE899xzWLp0qe/f3mzThg0b0LFjRwDA/v37UVJS4lvmb3/7G37//XcMGTIEp0+fRtu2bbFu3TokJCRYUkcridZPRXT+x0vL3DNW3zTCPXDYasG/+tXup9n1s/rcDRWoKi1rpCnJanqDKD3riHBdcSKII3X69OmDU6dOYeLEiTh69CiaNWuG1atXIyMjAwBw9OjRgDmnMjMzsXr1ajzzzDOYO3cu0tPTMXv2bN+0CADQvn17vP322/j73/+OZ599Ftdddx1WrFiBtm3bml7/AQMGoGnTppg9ezbee+89SJKErKwsbNmyxdD2dAVTcXFxshNfnjt3DrGxsborE8qSJUvCzjEVPJGox+NBXl6e7KgEIiIiV7O5mc9ryJAhGDJkiOx7cvfpnJwcfPXVVyHLvP/++3H//ffrq5BGbdu2xbJly0wtU1cwdffdd+Opp57CokWL0KZNGwDA9u3bMXjwYHTv3t3UClIgp0dtuYFoEyqqqY/Vx1pL86FSXcx4lI8Z5ajZjpZtGO2sHC5DpaVMM46RljK0ZG29y5v5+amZlNOK7UYMh4IpqkxXMDV79mw8+uijyM7O9nUgu3TpEnr06OGKOahIHf9mL7ddzMy48dt50wi1XLi6GAkCwnV0dlNArSZgtCugc8OxE+1HB5GTOnfujAMHDuDAgQO61tcVTNWuXRsffvghfv75Z+zbt8/X5nj99dfrqgSRKKJ1+L9/kGFFNsDKYNysAElvsBUuI6WU/bPieGgdBSp6EBVt30OtnOiA7mbl5eX44osv0KJFC9SpUyfgvZ49e+LkyZO6y1YdTPnPvSRn48aNvv+fMWOG7gqRmES+6IZ6NpuRUUyid35VW79QN263P4rDyfqGOu+cnNoiEqdVcGu9LWfSDOjRomrVqujatSv27dtXKZj685//bKhs1cHU7t27VS1nxYyl5Ay33FhFDQhED8bk6G2ekpsbyFueWURqlgpXF7mpRMwOpOSaL5XqYxY3/MiIKuwzpVnz5s1x4MABZGZmmlqu6mBqw4YNpm6YiIiIyE6TJ0/GqFGjMGnSJLRq1Qo1a9YMeF/NTPBydD9OhijS2fXLW2smTUvznprljAjVuduMTIzSfFFmzQ0VvL6W+Y2MDArQWu9Q88wpZQUp8rHPlHa5ubkAgO7duwe0pHmfBVheXq6rXAZTLmHnEGG3XpBFa35wuh56zxktN2a55ix/es8luf5IolPT9Kd24tBQ+x/qPTua4Zz4LERpuhcOm/k0s6qVjcFUlAh3gdUyYzQ5x87PxOiN2Yybn1wQYWa5IsybJJdZUhs8RTpei8hsOTk5lpTLYCrKBN88tEzaaDXRMksUveyeLDISR+CZiR3fFRhs5ovGzBQAbN68GQsWLMCBAwfwzjvv4JprrsG//vUvZGZm4rbbbtNVJoOpKKN1rhurR2bxwqhdpB8zO5t0zNiO3hnHQ/WDMkJLvy830nt+uHWurZDYzKfZypUr0b9/fzz88MP46quvcPHiRQDA2bNnMWXKFKxevVpXuVXMrCQRERGRqJ5//nnMnz8fCxcu9D3BBbjysOVwzw8MhZkplzGa7tbSqTg4KxWpv3SdorYfm90djJ1iRfOy0TKVOo2b3c/Kin23u6nSauG6IoQbAKHle+YazExptn//ftx+++2VXk9MTMSZM2d0l8tgKkoYHdkVXIbc+06Jps6p0bCvIpxTSkJN0Knmu6VmtJ7ZIjEADxVYaT22bj4mnBpBu7S0NPz8889o2LBhwOtffPEFGjVqpLtcBlMRKFo7s7pp34xkC5zoE2N1dsMNQaKakbBkP1F/5JGYBg0ahL/85S94/fXX4fF4cOTIEeTn52PUqFF47rnndJfLYCrCuO2CYmZA4KZf31o6/odjZaBj59D0UM00WgdOyLHqOOk5RlY17RFRaH/7299QUlKCTp064cKFC7j99tsRFxeHUaNGYejQobrLZTBFRETkRuwzpcvkyZMxbtw4fP/996ioqEBWVhZq1aplqEwGUy6k9pEYeqnN8JjRF0OpT5aezqRuyEhpEW4+MP/jpaczu5PU9msxownHyD5HSudtr0jbH3/ROMEn+0xpt3TpUtx///2oWbMmWrdubVq5DKYigBlNe0plqA1gzLxIBwdpcjdetzVnqqXnRqAl6BXtuIlQB6fZEeBoCTREC7yJzDRq1CgMGTIE99xzD/r164fc3FzExBgPhRhMRQijQVS4zID/skrLWXER1jK0Obg+cu+FqpuTgYadz1Nz4y93p/oYaTmvtX4H7MykyE0WqqbfnlsDKtF+NFgqCrNLRhw9ehRr1qzBW2+9hQcffBDVq1dH79690a9fP7Rv3153uQymIoAZ2SgztmNmlkrPcHOvUM1eoR4o69RFV8vcX05xevtamRWgWBlQ2BUcyj37LxS3N5cFB94RnWljnynNYmJicPfdd+Puu+/G+fPn8f7772P58uXo1KkTrr32Wvzyyy/6yjW5nmQDKx74aiYzs1RW9Z0SIYjyZ2cdnN5fvTdpM+ZzEomWPm9mbMf7//5Nvk6fC1ZROzKUoluNGjXQtWtXnD59GocOHcK+fft0l8XHyRAREbmQtwO6kb9odP78eSxbtgx33nkn0tPTMXPmTNx777349ttvdZfJzFSUES0jY7do3GcRRernYLSp247siRuydlaIyHOOzXyaPfTQQ/joo49Qo0YN9O7dGxs3bjTUV8qLwZTLmNkfichObmpmMWPKDyOd0Z1sgrM6yIrk5kUSn8fjwYoVK9C1a1dTRvF5MZhyITfdlKwSzfse7awcYecEpTpaVW+5ztnhljWjDqJ/Dm7Eeaa0W758uSXlMphyISPNB3bjxZjcJJqavrTMJ8fvnqDYzKfK7Nmz8dRTTyE+Ph6zZ88OueywYcN0bYPBlEuYdZG342IoNxSbqX1yA6f6EwVv18rpGEKVbVdfLV4LyE4zZ87Eww8/jPj4eMyYMQMej0d2OY/Hw2CKiIgoqjAzpUpBQYHv/w8ePGjJNhhMCUxpZm9RU+56ZiJX+0y54NdE23cjImlf1Ii0z88qVk8WqqV8uayS3pHBIl/D3IZ9prS5dOkSGjdujI8//hhZWVmmls1gSkBu7bdhVROJ0izm5C52TVIpCiP7ZmXAGe6RSmoeMxOunFDLMpg2ETNTmlSrVg0XL15UbOYzgsGUwJQ6grrpQqQ0csi7D0r9KKLhZhttQj28OprZ8Z1We7y1jI7Uu31+p8lJTz/9NKZNm4bXXnuNUyNEMjt+GdpJqXlAqfmOSCR2/XiRawY367ur5tl8Rp6FqYbaa5qRbUQlZqY02759Oz777DOsW7cOzZs3R82aNQPef++993SVy2CKiIjIhdhnSrvatWujV69eppfLYMpltMwNI6pwnc3VNCWEW9ZNxyOaOZ05VWJ1k3NwBsiuZj7Rstmifv4UuRYvXmxJuQymXCzSLkBq98c/gJJrlghuRoy04xQJjA5WcOIzNaPJT8vs40ZHzekRCT/Wogqb+YTBYEowZl+07JoMUE09zKyDnsDLrG2TepFw7M0apRrcd0nvOWwXM7bLiTqtxWY+84wdOxbFxcV4/fXXda3PYCpK2HkhC/U4CifqEKrjOy/w1hHhBipCHfw59aNG7/ZE+TFGZLXDhw+jqKhI9/oMpsg2dl6I5S7+bp1qwm3ZnUi98RrNrtqdYTJzW8wwCYrNfKZZunSpofUZTBEREbkRgylhMJgiW2j5NWtWPw1vWWbO2+UEszsFW5HpEjV7ZtV8TXZiNojImNmzZ6telg86pohk9Y0kVKAiYpBldMi+lfso0nHyJ2q9rGJXv0CrAmhRA3MRef7zZ2T9aDBz5kxVy3k8HgZTFFnMeo6blnWUAiulOa1EudBrzeSFGiBg1z5xtnttjDyc2Mq6+E9RYmW5WubHUrt8RGAznyoFBQWWb4PBFJEMucBKtOYWtR3qQ9U73LJReYMSjNaO61aOwNP6g0Kp3sF1CzeJqdapJKIFp0YQB4MpEobSCDynsxhuuDgrZdL8/6unLLnX3XA8zCTSfmvpAyiCcBlmtcfWyJMOQh0PET5Tst+vv/6KVatWobCwEGVlZQHvzZgxQ1eZDKaIiIjciM18mn322Wfo3r07MjMzsX//fjRr1gwHDx6EJEm4+eabdZfrkSQpCg+neqWlpUhKSkJJSQkSExOdrk5EC/crVaQMgUisan5U6qwux8yRhaI1p5rZ1Gm0LDXr2/U90fo5yfWJMnreKDVJ+7P7XLLjnuHdxk2DpqBqbLzucsrLLuC7BWOj6v7Wpk0b5ObmYuLEiUhISMDXX3+NevXq4eGHH0Zubi7+9Kc/6SqXmSkSgmg3UD0iYR/8Be+LkX4s4bYRPDt9pAfORvZLTZMYIO4xNKMZMtQjfuzYX1GPLYW3b98+vPXWWwCAmJgY/P7776hVqxYmTpyIHj16MJgidxKpf4dbiTqNgxZK++D0fpk9lYQZ++H0MTHK7A7x0Ywd0LWrWbMmLl68CABIT0/HL7/8gptuugkAcPLkSd3lMpgiIUT7RZHEJdK5KcKADL1EbcZ1NfaZ0qxdu3bYsmULsrKycNddd2HkyJHYu3cv3nvvPbRr1053uQymiIiCiBqwiFovLSIhk0ruNWPGDJw7dw4AkJeXh3PnzmHFihW4/vrrVU/uKYfBFBERkQuxmU+b8vJyFBUVoUWLFgCAGjVqYN68eaaUzWCKSCB6HxFj5y/8aM0qONk8JdIxj4TsWMRgM58mVatWRdeuXbFv3z7UqVPH1LKrmFoakUrBo7e0rhupDgwb6Zp+MW6oo17ezyH4NSPnrRn0bNvM+kbyZ07RoXnz5jhw4IDp5TIzJQinf3na+dgQvRfkUMOhRWHWcdQSUNn9PD2znptI2oWbW0puWau+L5FyrXLzOcxmPu0mT56MUaNGYdKkSWjVqhVq1qwZ8L7e+bYYTEUAMy8udlxQ1Ey05wbBdQ/eLzOH0Ycqy47mJ7ltuCWDpke4CSBFHpFmxYOslR72bSelqTNE/RxswWY+zXJzcwEA3bt3h8fj8b0uSRI8Hg/Ky8t1lctgioiIyI0YTGm2YcMGS8plMCUYPb+0/H8tGnnEgxP0/tJ3ot6hMlHBouXXslWZGlEyXqJ8jmqPs9x7wdeHUMtqKdcIrTOYh8oUavleypUn+nWHzJWTk2NJuQymBGG0f4Pa9fVceESjt6nBbc2hardn5bw9oj7nzextA9r30c4ba7hthQu2RG1a1xI4hStDbcAYSU2D7DOlz+bNm7FgwQIcOHAA77zzDq655hr861//QmZmJm677TZdZTKYEoSdFzgRLyR2TeTntiAqWjkx2EDLTVbk/mLhHgIs+jkcrpO90r7I7a+on5Fp2Myn2cqVK9G/f388/PDD+Oqrr3yPljl79iymTJmC1atX6yqXwZRg9AYVShcNt1xM7GgmEv0mIgo954xbj63/eef0tAdmUAryzAxOneqEr2UfQmXizPjhxuY+93r++ecxf/58PPLII3j77bd9r7dv3x4TJ07UXS6DKUGYNQInXDOAaMxo1rQ6i+GGG6xZn2/wDVKUfbcr2Bb9JqnmOAR/H4KzN1r2UZTP35/WrGDwfvqvq7Xbg2jTs3gkCR5Jf3rJyLputX//ftx+++2VXk9MTMSZM2d0l+uaSTsnT56M9u3bo0aNGqhdu7aqdQYMGACPxxPwZ+RBhkRERMKQTPiLMmlpafj5558rvf7FF1+gUaNGust1TWaqrKwMvXv3RnZ2NhYtWqR6vdzcXCxevNj379jYWCuqZyqzfv3o/TXvxK9zI9tSW99wcwcFlyU3SWWkEjUjY/fEk6LtfzA9WWozsnpmdBS3gp6+YKGWE/V74EanT5/GsGHDsGrVKgBX5nV65ZVXQiZDJEnChAkT8Oqrr+L06dNo27Yt5s6di5tuugkA8Ntvv2H8+PFYt24dioqKkJycjHvvvReTJk1CUlKSqnoNGjQIf/nLX/D666/D4/HgyJEjyM/Px6hRo/Dcc8/p3l/XBFMTJkwAACxZskTTenFxcUhNTbWgRvaJpNEnVtBzbML1kwnVFBBJ1O6b1R2Y1TSv8EZnDrVBlprrjhN9E4PPRSu+n24510Qezde3b1/8+uuvWLNmDQDgqaeeQv/+/fHRRx8prjN9+nTMmDEDS5YswY033ojnn38ed9xxB/bv34+EhAQcOXIER44cwUsvvYSsrCwcOnQIgwcPxpEjR/Duu++qqtff/vY3lJSUoFOnTrhw4QJuv/12xMXFYdSoURg6dKju/XVNMKXXxo0bUa9ePdSuXRs5OTmYPHky6tWrp7j8xYsXfb37AaC0tNSOasqSu+Hrzb6o5VTgpne7Wm6y4eakUXNzcdOoqHDU7EskZOWsmr07VN8ksznV6TuU4OPpxPEwe7uhpllQ2r6jBB3Nt2/fPqxZswbbtm1D27ZtAQALFy5EdnY29u/fj8aNG1euiiRh1qxZGDduHO677z4AwNKlS5GSkoLly5dj0KBBaNasGVauXOlb57rrrsPkyZPRr18/XL58GTEx6kKayZMnY9y4cfj+++9RUVGBrKws1KpVy9A+R3Qw1a1bN/Tu3RsZGRkoKCjAs88+iz/+8Y/YtWsX4uLiZNeZOnWqLwsmCjU3AbmbnjBf+BDMvFkbvZiq7Xzq3ZZbfr2GorfZSOu6TlEaoOCGupvFymatUIMVgo+9m465m+pqhuCkQVxcnOI9Uo38/HwkJSX5AikAaNeuHZKSkrB161bZYKqgoADFxcXo0qVLQD1ycnKwdetWDBo0SHZbJSUlSExMVB1IPf7443j55ZeRkJCA1q1b+17/97//jaeffhqvv/662t0M4GgwlZeXFzZw2blzZ8AOa9GnTx/f/zdr1gytW7dGRkYGPvnkE1/kG2zMmDEYMWKE79+lpaWoX7++ru2bKdxFycxf3G66WQLyo3XUZlqM3ETcnK0BjN9A3XCDdFufKDtZnakLZtZ1RW8WNRI/e7Oa+YLvcePHj0deXp7ucouLi2VbgOrVq4fi4mLFdQAgJSUl4PWUlBQcOnRIdp1Tp05h0qRJioGWnKVLl+KFF15AQkJCwOu///473njjDXcGU0OHDsWDDz4YcpmGDRuatr20tDRkZGTgp59+UlzGaERORERkC5Oa+YqKipCYmOh7WekeqDYBAiDgIcK+zf3nYcKhBL+vtE5paSnuuusuZGVlYfz48SHL9C4vSRIkScLZs2cRHx/ve6+8vByrV68O2QUoHEeDqeTkZCQnJ9u2vVOnTqGoqAhpaWm2bdMKah8toUekZFzs7sdi9bbIHFZ8Vm7K1NnNiWtJuL5c/q+5nVmZqcTExIBgSonaBMg333yDY8eOVXrvxIkTlTJPXt6BYsXFxQH36OPHj1da5+zZs8jNzUWtWrXw/vvvo1q1amHrXrt2bd8USTfeeGOl9z0ej6EuPq7pM1VYWIjffvsNhYWFKC8vx549ewAA119/va/jWJMmTTB16lT07NkT586dQ15eHnr16oW0tDQcPHgQY8eORXJyMnr27Ongnhjjf6Gw6uIQCTcHt9bbbZwIJI2cl1YH16Gm1jDCjQG7Ul3tDGpCdVQn7dQmQLKzs1FSUoIdO3agTZs2AIDt27ejpKQE7du3l10nMzMTqampWL9+PVq2bAngypRImzZtwrRp03zLlZaWomvXroiLi8OqVasCMkyhbNiwAZIk4Y9//CNWrlyJunXr+t6LjY1FRkYG0tPTVZUlxzXB1HPPPYelS5f6/u092Bs2bEDHjh0BXJnZtKSkBABQtWpV7N27F2+88QbOnDmDtLQ0dOrUCStWrKjUVuo2oWb0JXWs+LXq5uBTj+DA3q59V8o8KHEq4BOd2kEtZpP7QWj39yZislSCjuZr2rQpcnNzMXDgQCxYsADAlakR7r777oDO5/4JEI/Hg+HDh2PKlCm44YYbcMMNN2DKlCmoUaMG+vbtC+BKRqpLly44f/483nzzTZSWlvo6z1999dWoWrWqYp1ycnIAXOnoXr9+fVSpYu6c5a4JppYsWRJ2jinJb2r86tWrY+3atRbXitzOjGZNPVNYRAo7991NWYZo+fy9tH4OTn5+oUYgupGVc0UZsWzZMgwbNsw3Oq979+6YM2dOwDL+CRDgyhxQv//+O4YMGeKbtHPdunW+BMiuXbuwfft2AFdapfwVFBSo6mOdkZEBADh//jwKCwtRVlYW8H6LFi207eh/uCaYIiIiIneoW7cu3nzzzZDLSEHPBvR4PMjLy1McSdixY8dK62h14sQJPPbYY/if//kf2ffLy8t1lctgiug/zHzshtYHqLpBqMxTuL58kXg8IoEVE156uWUCYFdnkyXpyp+R9aPM8OHDcfr0aWzbtg2dOnXC+++/j2PHjuH555/HP/6hP1PJYCoC2DV6LVJZMXGo2eU6TcvEsf6s3nc1574TAyrc0H/OikEretfTe7zMaKJ38/dT5MfJiOrzzz/Hhx9+iFtuuQVVqlRBRkYG7rjjDiQmJmLq1Km46667dJVrbg8sIo2Uno3nBDMnExT9RmqXA8NGRs3Emd6AIFL3TytvoGLl91spS0qk5N///rdvPqm6devixIkTAIDmzZvjq6++0l0uM1MRIhKmM4hUkZI5NNokFKnz/YjyY8DtrH4cVEQSdDSfyBo3boz9+/ejYcOG+K//+i8sWLAADRs2xPz58w3NQclgKsK45cYdXMdIuSFZ/RibSOHE8bDzu2Hmtqz8blhdttp9N9LcFqlBuhqeiit/RtaPNsOHD8fRo0cBXHlsTteuXbFs2TLExsaGnTEgFAZTREREFBUefvhh3/+3bNkSBw8exA8//IAGDRoYeiILgymqxM5sQaRkpKKR3iZls88rp7MQdmRX7Zwp3Cgtx8HMbFJUzvfGZj7DatSogZtvvtlwOQymyHZyF9vgifTkJtaL+AujS5gZPNjd18/O5kWztuWWpvtgWupq9sjCaPmRxtF86owYMUL1sjNmzNC1DQZTEUy0PgShLnDB74lWd7NYEYg4Rev23RgQaKEU9LhhcEikfzahuOHzUcR5plTZvXu3quU8Ho/ubTCYEoArv8Qahcs2RWrwpERugkO514PfD7WMyETLFlh9A3XLd9rKJspQx0Ckc8FfNAeVkWzDhg2Wb4PBVASSC1rsvkiEmvHaLTcakah9nphbj6tTTVlmb9etx99uIo7ilZvFX/TPk8184mAwRURE5EbsgC4MBlMCsPJXuZ2/AMN1LNdSjui/CJ2k1EQY/P+h1qErRMqMiMDM51N6ywt+zartmkHEjBm5A4MpQbi6E+R/hNsHtQ/K9V9WaflIYsbzxbRsQ8Tj6eTNy+rjYea+WXV9sDqIUKp3uOZrEc9VkbCZTxwMpsgWWmdD9l8vVP+rSBMJGcpwddD7vluZPf+Rm74PWs47uWVF/xHgOI7mEwaDKUFY3eHRqcyXmVmXcGW5pdOonOAbiZszlG7gf6448YgZPesCgeeF2RkvkYQKrPi9IBExmCLTGE3Thwv4lKZREO1GoFao42XVLM5unQDSSm5vYjez3qLtv5YfU9GIzXziYDBFRETkRhzNJwwGUzrJ/RoMlTFxenJKO3/V2dFc4mXm8RQpM+HmjJtb2ZG105sFCzezuujZRjPrZef3lH22SC0GUxpoaV5Ss6zcBTDc0PZwFxKl7ZrZ3BZqe3Zz8wVO7RBykYI8Ek+0BN5OB49OX+vksJlPHAymVGox/xVUiY+X/WWoRqipAsJdCIODIrUXTr0XWC1zw/jXkcxl1Qg8p7OkcpzefjDRMz1mUzrXRNx/O4JHpR+Uws2QXiFd+TOyPpmCwZQGZjcDaLmAaQni9AReSvUKlTVz/EJiknCfaSTPfxMqYIuUfdTCraMqwwXeeqYl8S/PDcfATEr7LcIUIwHYZ0oYVZyuABEREZGbMTOl0jeDn7bl14hIvwCVMlsi1dFK0bTvSk0Zkbq/Xmpm5nYrM7Mo0ZqhEp0HBvtMmVYTYjClgX9wYfRGo9RkZna5wa9r6eweXC+rCZM6DxKtNxC3zkmlpi+Y0801SqN9Qy0PhL8+mP05OX2clNg1N5iaOe8c/W5wBnRhMJjSyIoRJVZdAP3/X+1MwqEe5WBX50s33bjt5tTF2/GbhgZm/uixkpZAxch3zq1BsRFmXpOj7diRPgymbOb0F1PrzcXOLJXTv/ZE+/XtFZzFMDOIDzd/kaiZiXDC3QxFeEyJlmPq9HcjWqnJBDp5TefUCOJgMKWT1pFywctadVEMd4NUw+mAz06iTA/g1LaDg6VQzWKhznc3nCtKn7UVgaKW77fWY2fk+8lgzHyOBroczScMjuYjIiIiMoCZKZsozd9i5bb0/FIS5Ver1dkxLR31RRCqf5uZdZXLoHq3IdoxUcvOzIGWvolG+z9pXS+4fnrXd+t5oIfTzXjheCQJHgOdyI2sS4EYTGlkVbOQmcGVXf1brGyqtHobcoJvhCJePK2i1MfIDR25zWLmPoragdlocGBHcCFSACP8eV/xnz8j65MpGExpYEf/GjPKtbOjuCgXPb2U6u22DtdmcmpqDC3Unndq6m3mPoYbRi8Cs76rVgYaWvqbiXQNajT7H6i4cMHpapADGEyp1GL+Kzj4t3GWb8fsC5RIFxq3UZoLjJwVPMpQ7RxNTrO607tdIunHlBpq99H7fmlpKZL+798trxfAZj6RMJhySHDfByt+vertXxGOXJmijIoLR8uFMXhZLVkOMp/SZxcNN3R/akdg2lEPp4NCq6e4EGEfQ+JoPmEwmCIiInIjzoAuDAZTDgn1a8fpX5x6ONVpXAutvzDDZQDkMldOfHZ2HG8RPs9Q/ZEA+Y7zWrnxu+ekaB3lRxSMwZRK3wx+2vQy5ZqPhE8r+1Gqq8gXVT2Tl6oty6nRbyIfbzvJ3dj1BtCknVOBqGgd/O3EGdDFwWAqgtkxdUEkC75Ia+nsHC2dc0Wkd0Zx0i/4h4T3NSdEVZaMzXzCYDBlEz3P4TJKtGHDbqXnl6+VzZ68+ZvLzsxGJH92en58EEUKBlM2cHKkmygjf4zQOkWB0g3LjH3X81k6PRcPhWZngBMNTVJOZWfNPLZu+Xw8FVf+jKxP5mAwRURE5EZs5hMGgymbRGIWQW6OF8D8eV6Ct6HUfGDHYy6Ct0WRIxK/o05y02AaL7kRujwvSA0GUxYS8UJi9vPH7HyOm1zzgRxRZi53y0SmkcjMx81Yxc1N72qFa3qL5H23BSftFAaDKROJchOXY0dfDTv7g4Tall0ZpFCfd/Dw/Gi4cbqR3Ci04Pet3LZ3u5F+XijN0aaXVU92CDXdiYifER8nIw4GUybQ8mVzOltl9qgypy8wWh4Lo2Z5f6E+K6UmDLXBndPHLZJpPS+dCGr8t2P0hi3C91ArswbG2N2x3W3HmezDYIqIiMiN2AFdGAymTKDn10okd2a2OjWutXyjzY9K25BrulA7qSeRPz2ZmkhoRnZbJk644ywBMDK9AWMp0zCYskm4G3mkdla24uIjarpdxDqRNsLdLFVQ6vfF5mVziXjs2GdKHAymbCb3hYzELJXVndGj+eYQjftsBzcO5fdSmkIk+H1Rf4gQuR2DKQtFarZJD6umZCDycnOAbccoW7dz8+drGQkG+0yZVpOox2DKBm4Y5aeHmr5LVmWo9P7SNtLXihdxspoZGaRoP09Fn87AVOyALowqTleAiIiIyM2YmTKZ3qa9aHgAqtP0Ng9G/K9bl3N7FsLu+a3knlrg/76I7DhGrsxoVQDwGFyfTMFgykTR2LlTbbOEaBcqkepC+pn54yN41nrA2vMj1Dbs+L4oHTuRvhsi1UVEHM0nDgZTJjLjCy9a0GEFMx/bYfecUyQeI9+T4PPAru+elh9eZv9IkytLaTZ/p69BTm+fSC0GU2QKrZ3RtTyrixdUUqL33FBq6hJp0IGdgb/ctqL5eyfC568KO6ALg8EUmU5Nk5+a17xlWUmEX99kH61Z0Wg8P6Jtf+W4Zl4uBlPC4Gg+IiIiIgOYmSLTsD8SiU5tlsHqc1nrSF+7mp2ioc9mRGFmShgMpgQkUr8NpylNZ+B/TIw8JNZ/PbXrUvSIxuDCNU1cQaz4Hiv1qRMGp0YQBoMpF1BzUYvkC75cZ3Uz95cZNSJSIvL1gVMjiMMVwdTBgwcxadIkfP755yguLkZ6ejr69euHcePGITY2VnE9SZIwYcIEvPrqqzh9+jTatm2LuXPn4qabbrKx9vqpfeq7235BGhV8XOSCLT3HIxqzECQ+EW/iInHLxKMU2VzRAf2HH35ARUUFFixYgO+++w4zZ87E/PnzMXbs2JDrTZ8+HTNmzMCcOXOwc+dOpKam4o477sDZs2dtqjkREZFFvH2mjPxZ5PTp0+jfvz+SkpKQlJSE/v3748yZM2F2R0JeXh7S09NRvXp1dOzYEd99953ist26dYPH48EHH3xg/g5o5IpgKjc3F4sXL0aXLl3QqFEjdO/eHaNGjcJ7772nuI4kSZg1axbGjRuH++67D82aNcPSpUtx/vx5LF++3Mbam+PAsJGV2u+9zV38JXaF9xgBgU2BRKSd93oj8vdI5LrZokIy/meRvn37Ys+ePVizZg3WrFmDPXv2oH///iHX0ZIAmTVrFjweIx3GzOWKYEpOSUkJ6tatq/h+QUEBiouL0aVLF99rcXFxyMnJwdatWxXXu3jxIkpLSwP+ROMfRDGQqhw4KXUuJ6LIE3wdtPI7L3pwKYp9+/ZhzZo1eO2115CdnY3s7GwsXLgQH3/8Mfbv3y+7jpYEyNdff40ZM2bg9ddft2N3VHFFn6lgv/zyC1555RX84x/KJ3VxcTEAICUlJeD1lJQUHDp0SHG9qVOnYsKECeZU1CRu7BMgV2cr+iOpGe2nh9AjeMhWIo1uc+q8dFNfQqvqqLYPq60EnRohPz8fSUlJaNu2re+1du3aISkpCVu3bkXjxo0rrRMuATJo0CAAwPnz5/HQQw9hzpw5SE1NtaT+ejgaTOXl5YUNXHbu3InWrVv7/n3kyBHk5uaid+/eePLJJ8NuIzgNKElSyNTgmDFjMGLECN+/S0tLUb9+/bDbsZpc85XjX2QFchcdK3/NmTmVhNFfuAzCIptTn6/ciDI7rgMij2QDlKdIiZ7vntF+T1fWDW6BiYuLQ1xcnO5Si4uLUa9evUqv16tXz5fokFsHCJ8AeeaZZ9C+fXv06NFDd/2s4GgwNXToUDz44IMhl2nYsKHv/48cOYJOnTohOzsbr776asj1vBFrcXEx0tLSfK8fP3680oflz+hJZDX/TIzoQZW/cCPwRKbnOLtp/0g9p4OLcKN5rf5uue27q0Uk71s4wQmD8ePHIy8vr9JyahMgQOVEBhA+mSG3nv86q1atwueff47du3eHLMMJjgZTycnJSE5OVrXs4cOH0alTJ7Rq1QqLFy9GlSqhu3tlZmYiNTUV69evR8uWLQEAZWVl2LRpE6ZNm2a47kRERI4yqZmvqKgIiYmJvpeVEgpqEyDffPMNjh07Vum9EydOKCYz1CRAPv/8c/zyyy+oXbt2wLq9evVChw4dsHHjxpB1s5Ir+kwdOXIEHTt2RIMGDfDSSy/hxIkTvvf820ybNGmCqVOnomfPnvB4PBg+fDimTJmCG264ATfccAOmTJmCGjVqoG/fvk7shmZKv37d8OspVDbHyv5T3m1bMZlncAYgeDkiK4Q7v5T6DVpRB6XBHtGc1XFUhQRvU53+9YHExMSAYEqJ2gRIdnY2SkpKsGPHDrRp0wYAsH37dpSUlKB9+/ay66hJgIwePbpS957mzZtj5syZuOeee8LWy0quCKbWrVuHn3/+GT///DOuvfbagPckv6h8//79KCkp8f37b3/7G37//XcMGTLEN2nnunXrkJCQYFvdtbL7Ju2mpkKnqG3aEbVfCRnjpu+IHc/u8woOrNw4UEYvBpGhNW3aFLm5uRg4cCAWLFgAAHjqqadw9913B3Q+15oASU1Nle103qBBA2RmZtqzcwpcEUwNGDAAAwYMCLucFJTu9Hg8yMvLk237FVW0fDHd+PxBNRkAN+wHGSd3LkTbZ2/VkwiMsvvB0I6SKq78GVnfIsuWLcOwYcN8o/O6d++OOXPmBCwTCQkQL48UHIFQgNLSUiQlJaGkpERVGtStzL74qL3RWJWJs/piKtfkx8fRRB4tAYEIWQon6yB37jv1fdCzXbOOnR33DO82Otf/E2Kq6B8wdbniIj4t+mfE39/s4IrMFLmP2qYxq0ZHOTVs3embKZnDzU22Igb0/G5YxKQ+U2Sca2dAJyIiIhIBM1NEJuEv78jDucXUk2v2dnperogn6Azo0YjBVJSzc0h1qJsN+xsRmUPEwR3BHfZFqFNEkGAwmDKtJlGPwRQBsLajNhHZz6k50ZR+QLnpkVhEWjGYIs2ULs6hHjjMoIrIeSJ0BHfrI7GExGY+YTCYItXkpjsI96tXy8XSTbOLi1ovMofbPt9w3zMRpivwZ+WcVMETibrts9SkogKAgbmiKqybZyracDQfERERkQHMTJEqStkiNc8N866v9heiHc8aI4oUWr8rdmaA7cyCReXkuWzmEwaDqSimNQXOiTCJxKTnO2LHo1bs+FEUNYGTHAZTwmAzH9nCe2HVc3HVux5RNIjKIOI/eF0gUTAzRYpEuFCxyY/IGKVmLzuyvnZkmK18pqfwmXE+TkYYDKaIiIhcSJIqIEn6R+QZWZcCMZiKMmqyPKJlguyc0dkN0zIQaaXU6dypDuJy9dNTFzPrLTf/lfAkyVh2iX2mTMNgKkpomWhTbjn/ZfVcwNww9wsDKYp0wed1uEl1zfoeuKW5Xu6aF9Ud3Ek1BlMRTE1wYOXkeaG2ZeRXqNl15MWSop0I576I/ZSEDwIlg32mmJkyDYOpCGbmcGmjF5Rwv4i1BlWhHl1DRBQVKioAj4F+T+wzZRoGUyQEI3NeBQdWocpiEEbkDC2T9hK5DYMpIiIiN2IznzAYTJEqVvUd8G/uM5o10lI//volIreTKiogGWjm49QI5mEwRapZPUWB2lGGodbzrivX+V6kjq1ERBQ5+DgZ0s3MTJWRx83IleWPj6MhoojkfTafkT8yBTNTpFm4uWn0MDvYYQaKKHpFTTa6QgI87DMlAmamSDcrs0lezCgRkVbMRpPdmJkiIiJyI0kCYGSeKWamzMJgigyxIoXun5rn4xyIyEkiX3ekCgmSgWY+icGUadjMR8I4MGyk4kzpREQURKow/kemYGaKiIgiitHngBJpxWCKhGf1/FZEFLki+XrBZj5xMJgiIiJyI6kCxjqgs5nPLAymwvBG7qWlpQ7XJHpUXLgge7z3DBgIAGg4fXLA698MftqWehERheO9dtmR9bmMS4YezXcZl8yrTJTzSMzzhfTrr7+ifv36TleDiIhcpKioCNdee60lZV+4cAGZmZkoLi42XFZqaioKCgoQHx9vQs2iF4OpMCoqKnDkyBEkJCTA4/GYWnZpaSnq16+PoqIiJCYmmlq2Hdxcf9bdOW6uv5vrDri7/m6puyRJOHv2LNLT01GlinUD5i9cuICysjLD5cTGxjKQMgGb+cKoUqWKZb8uvBITE4W+OITj5vqz7s5xc/3dXHfA3fV3Q92TkpIs30Z8fDyDIIFwnikiIiIiAxhMERERERnAYMpBcXFxGD9+POLi4pyuii5urj/r7hw319/NdQfcXX83150iHzugExERERnAzBQRERGRAQymiIiIiAxgMEVERERkAIMpIiIiIgMYTOmQl5cHj8cT8JeamgoAuHTpEv7v//2/aN68OWrWrIn09HQ88sgjOHLkSMgylyxZUqlMj8eDCxcuBCw3b948ZGZmIj4+Hq1atcLmzZuFqH/Hjh1l63/XXXep2q4Zdfe+36RJE9SsWRN16tRB586dsX379rDlrly5EllZWYiLi0NWVhbef//9SstYfez11n/hwoXo0KED6tSp41tnx44dmrbrVN3tOu+tqLtd57zWcgYNGgSPx4NZs2aFLdeO896Kutt1zhOpxWBKp5tuuglHjx71/e3duxcAcP78eXz11Vd49tln8dVXX+G9997Djz/+iO7du4ctMzExMaDMo0ePBsxwu2LFCgwfPhzjxo3D7t270aFDB3Tr1g2FhYWO1/+9994LKO/bb79F1apV0bt3b1XbNaPuAHDjjTdizpw52Lt3L7744gs0bNgQXbp0wYkTJxTLy8/PR58+fdC/f398/fXX6N+/Px544IGAm6kdx15v/Tdu3IiHHnoIGzZsQH5+Pho0aIAuXbrg8OHDqrfrVN0B+857s+tu5zmvtpwPPvgA27dvR3p6etjy7Dzvza67nec8kSoSaTZ+/HjpD3/4g+rld+zYIQGQDh06pLjM4sWLpaSkpJDltGnTRho8eHDAa02aNJFGjx6tui6SZE39g82cOVNKSEiQzp07p3u7crSWUVJSIgGQPv30U8VlHnjgASk3Nzfgta5du0oPPvig799OHXs19Q92+fJlKSEhQVq6dKnu7cqxou52nfd2HHerznm15fz666/SNddcI3377bdSRkaGNHPmzJDL23XeW1H3YFad80RqMTOl008//YT09HRkZmbiwQcfxIEDBxSXLSkpgcfjQe3atUOWee7cOWRkZODaa6/F3Xffjd27d/veKysrw65du9ClS5eAdbp06YKtW7cKUX9/ixYtwoMPPoiaNWvq3q7RupeVleHVV19FUlIS/vCHPyiWl5+fX+m4du3a1XdcnTr2ausf7Pz587h06RLq1q2ra7t2192u897q427lOR+unIqKCvTv3x9//etfcdNNN6kqz87z3uy6B7PynCdSg8GUDm3btsUbb7yBtWvXYuHChSguLkb79u1x6tSpSsteuHABo0ePRt++fUM+nLNJkyZYsmQJVq1ahbfeegvx8fG49dZb8dNPPwEATp48ifLycqSkpASsl5KSguLiYsfr72/Hjh349ttv8eSTT+rerpG6f/zxx6hVqxbi4+Mxc+ZMrF+/HsnJyYplFhcXhzyudh97rfUPNnr0aFxzzTXo3Lmzpu06UXe7znurj7uV57yacqZNm4aYmBgMGzZMdZl2nfdW1D2YVec8kWpOp8Yiwblz56SUlBTpH//4R8DrZWVlUo8ePaSWLVtKJSUlmsosLy+X/vCHP0hPP/20JEmSdPjwYQmAtHXr1oDlnn/+ealx48ZC1f+pp56SmjVrpnu7WsiVce7cOemnn36S8vPzpccff1xq2LChdOzYMcUyqlWrJi1fvjzgtTfffFOKi4uTJMn+Y6+1/v6mTZsm1alTR/r66681b9fpukuSfee92XW385wPLufLL7+UUlJSpMOHD/veV9NU5tR5b0bd/dl5zhMpYWbKBDVr1kTz5s19v6aBK6PiHnjgARQUFGD9+vWqszpeVapUwS233OIrMzk5GVWrVq30i/D48eOVfjk6Wf/z58/j7bffrvQLXe12zah7zZo1cf3116Ndu3ZYtGgRYmJisGjRIsUyUlNTQx5Xu4+91vp7vfTSS5gyZQrWrVuHFi1aaN6uk3X3suu8N7Pudp/zweVs3rwZx48fR4MGDRATE4OYmBgcOnQII0eORMOGDRXLcOq8N6PuXnaf80RKGEyZ4OLFi9i3bx/S0tIA/G8g8tNPP+HTTz/FVVddpblMSZKwZ88eX5mxsbFo1aoV1q9fH7Dc+vXr0b59e2Hq/9///d+4ePEi+vXrp3m7ZtRdjiRJuHjxouL72dnZlY7runXrfMfVzmMvJ1z9AeDFF1/EpEmTsGbNGrRu3dqU7ZpRhpq6By9vx3lvZt3tPueDy+nfvz+++eYb7Nmzx/eXnp6Ov/71r1i7dq1iGU6d92bUHXDmnCdS5GRazK1Gjhwpbdy4UTpw4IC0bds26e6775YSEhKkgwcPSpcuXZK6d+8uXXvttdKePXuko0eP+v4uXrzoK6N///4BI2Ly8vKkNWvWSL/88ou0e/du6bHHHpNiYmKk7du3+5Z5++23pWrVqkmLFi2Svv/+e2n48OFSzZo1pYMHDzpef6/bbrtN6tOnj+btmlH3c+fOSWPGjJHy8/OlgwcPSrt27ZKeeOIJKS4uTvr2228V675lyxapatWq0gsvvCDt27dPeuGFF6SYmBhp27ZtvmXsOPZ66z9t2jQpNjZWevfddwM+r7Nnzwp/7O06762ou5fV57yecuSaypw6762ou13nPJFaDKZ06NOnj5SWliZVq1ZNSk9Pl+677z7pu+++kyRJkgoKCiQAsn8bNmzwlZGTkyM9+uijvn8PHz5catCggRQbGytdffXVUpcuXSr1VZAkSZo7d66UkZEhxcbGSjfffLO0adMmIeovSZK0f/9+CYC0bt06zds1o+6///671LNnTyk9PV2KjY2V0tLSpO7du0s7duwIKEOu7u+8847UuHFjqVq1alKTJk2klStXVtq21cdeb/0zMjJkP6/x48er2q6TdbfrvLfqvLHjnNdTjlxA4tR5b0Xd7TrnidTySJIk2ZcHIyIiIoos7DNFREREZACDKSIiIiIDGEwRERERGcBgioiIiMgABlNEREREBjCYIiIiIjKAwRQRERGRAQymiEhRx44dMXz4cKerQUQkNAZTRGSKjRs3wuPx4MyZM05XhYjIVgymiIiIiAxgMEVEqrz55pto3bo1EhISkJqair59++L48eMAgIMHD6JTp04AgDp16sDj8WDAgAEO1paIyD4MpohIlbKyMkyaNAlff/01PvjgAxQUFPgCpvr162PlypUAgP379+Po0aN4+eWXHawtEZF9YpyuABG5w+OPP+77/0aNGmH27Nlo06YNzp07h1q1aqFu3boAgHr16qF27doO1ZKIyH7MTBGRKrt370aPHj2QkZGBhIQEdOzYEQBQWFjobMWIiBzGYIqIwvr3v/+NLl26oFatWnjzzTexc+dOvP/++wCuNP8REUUzNvMRUVg//PADTp48iRdeeAH169cHAHz55ZcBy8TGxgIAysvLba8fEZGTmJkiorAaNGiA2NhYvPLKKzhw4ABWrVqFSZMmBSyTkZEBj8eDjz/+GCdOnMC5c+ccqi0Rkb0YTBFRWFdffTWWLFmCd955B1lZWXjhhRfw0ksvBSxzzTXXYMKECRg9ejRSUlIwdOhQh2pLRGQvjyRJktOVICIiInIrZqaIiIiIDGAwRURERGQAgykiIiIiAxhMERERERnAYIqIiIjIAAZTRERERAYwmCIiIiIygMEUERERkQEMpoiIiIgMYDBFREREZACDKSIiIiIDGEwRERERGfD/Aeou5hrWNTTTAAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "da = model.get_value_as_xarray(\"lateral.river.q_av\")\n", - "da.unstack().isel(time=0).plot()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'discharge [m3/s]')" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Location A, Location B.\n", - "lats = [53.274166, 53.765833,]\n", - "lons = [-0.761666, -0.986666,]\n", - "\n", - "ntimesteps = int(model._bmi.get_end_time() / model._bmi.get_time_step()) - 1\n", - "q_locs = np.zeros((ntimesteps, 2,))\n", - "dtimes = []\n", - "for tstep in range(q_locs.shape[0]):\n", - " model.update()\n", - " q_locs[tstep] = model.get_value_at_coords(\"lateral.river.q_av\", lats, lons)\n", - " dtimes.append(model.time_as_datetime)\n", - "\n", - "import matplotlib.pyplot as plt\n", - "plt.plot(dtimes, q_locs[:, 0])\n", - "plt.plot(dtimes, q_locs[:, 1])\n", - "plt.xlabel(\"time\")\n", - "plt.ylabel(\"discharge [m3/s]\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can load model coupling locations from a geojson file, and get the discharge at those locations:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([32.40296702, 58.92205788, 9.40452881, 9.14641328, 3.28022101,\n", - " 1.21642889, 1.95702639, 1.23389226, 0.77603632, 0.33483819,\n", - " 0.33075614, 0.24121365, 0.21427417, 0.10258944, 0.09825702,\n", - " 0.10319047, 0.30268187, 0.20068187, 0.26775474, 0.29128219,\n", - " 0.18014927, 0.18577489, 0.09252461, 0.09873827, 0.07020488])" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "lats, lons = get_geojson_locs(\"/home/bart/Downloads/gauges_src.geojson\")\n", - "\n", - "model.get_value_at_coords(\"lateral.river.q_av\", lats, lons)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As a validation of the locations we can plot them on the discharge map:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "da = model.get_value_as_xarray(\"lateral.river.q_av\")\n", - "da.unstack().isel(time=0).plot(x=\"lon\")\n", - "plt.scatter(lons, lats, marker=\"o\", c=\"red\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "model.finalize()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.0" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/pyproject.toml b/pyproject.toml index 7197b49..90825a8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -26,8 +26,8 @@ dynamic = ["version"] # Include here only the dependencies for the eWaterCycle wrapped model dependencies = [ - "ewatercycle>=2.0.0b2", - "grpc4bmi[julia]", + "ewatercycle>=2.4.0", + "remotebmi", "toml", ] @@ -42,9 +42,13 @@ dev = [ WflowJl = "ewatercycle_wflowjl.model:WflowJl" [project.entry-points."ewatercycle.forcings"] -WflowJlForcing = "ewatercycle_wflow.forcing.forcing:WflowJlForcing" +WflowJlForcing = "ewatercycle_wflowjl.forcing.forcing:WflowJlForcing" [tool.ruff] +target-version = "py310" +extend-exclude = ["*.ipynb"] + +[tool.ruff.lint] select = ["E", "F", "B", "D", "C90", "I", "N", "UP", "PLE", "PLR", "PLW"] extend-select = ["D401", "D400", "D404", "TID252"] ignore = [ @@ -53,12 +57,11 @@ ignore = [ "N813", ] dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$" -target-version = "py310" -[tool.ruff.pydocstyle] +[tool.ruff.lint.pydocstyle] convention = "google" -[tool.ruff.isort] +[tool.ruff.lint.isort] known-first-party = ["ewatercycle_wflow"] force-single-line = true lines-after-imports = 2 diff --git a/src/ewatercycle_wflowjl/__init__.py b/src/ewatercycle_wflowjl/__init__.py index b34f0f3..2b64363 100644 --- a/src/ewatercycle_wflowjl/__init__.py +++ b/src/ewatercycle_wflowjl/__init__.py @@ -1,2 +1,3 @@ """eWaterCycle plugin for Wflow.jl.""" -__version__ = "0.0.1" + +__version__ = "0.2.0" diff --git a/src/ewatercycle_wflowjl/forcing/diagnostic_script.py b/src/ewatercycle_wflowjl/forcing/diagnostic_script.py index 145a8b2..f0bc6ad 100644 --- a/src/ewatercycle_wflowjl/forcing/diagnostic_script.py +++ b/src/ewatercycle_wflowjl/forcing/diagnostic_script.py @@ -1,4 +1,5 @@ """wflow diagnostic.""" + import logging from pathlib import Path diff --git a/src/ewatercycle_wflowjl/forcing/forcing.py b/src/ewatercycle_wflowjl/forcing/forcing.py index 1945098..82294d7 100644 --- a/src/ewatercycle_wflowjl/forcing/forcing.py +++ b/src/ewatercycle_wflowjl/forcing/forcing.py @@ -1,4 +1,5 @@ """Forcing related functionality for wflow.""" + from datetime import datetime from pathlib import Path diff --git a/src/ewatercycle_wflowjl/forcing/makkink.py b/src/ewatercycle_wflowjl/forcing/makkink.py index e723aa7..53f4cfd 100644 --- a/src/ewatercycle_wflowjl/forcing/makkink.py +++ b/src/ewatercycle_wflowjl/forcing/makkink.py @@ -1,4 +1,5 @@ """Makkink formula for potential evaporation, implemented for Iris.""" + import logging from pathlib import Path diff --git a/src/ewatercycle_wflowjl/model.py b/src/ewatercycle_wflowjl/model.py index 5be852d..42da5ae 100644 --- a/src/ewatercycle_wflowjl/model.py +++ b/src/ewatercycle_wflowjl/model.py @@ -1,21 +1,20 @@ """Wflow.jl eWaterCycle Model.""" + import datetime from collections.abc import Iterable from pathlib import Path +from typing import Literal import numpy as np import pandas as pd import toml import xarray as xr -from bmipy import Bmi -from ewatercycle.base.model import LocalModel +from ewatercycle.base.model import ContainerizedModel from ewatercycle.base.model import eWaterCycleModel from ewatercycle.base.parameter_set import ParameterSet +from ewatercycle.container import ContainerImage from ewatercycle.util import geographical_distances from ewatercycle.util import get_time -from grpc4bmi.bmi_julia_model import BmiJulia -from juliacall import JuliaError -from juliacall import Main as jl from pydantic import PrivateAttr from pydantic import model_validator @@ -201,39 +200,13 @@ def _make_cfg_file(self, **kwargs) -> Path: return config_file -def install_wflow(): - """Install Wflow.jl with the BMI branch.""" - jl.seval("import Pkg") - jl.Pkg.add(name="Wflow", rev="BMI") - jl.Pkg.add("BasicModelInterface") - - -def check_wflow_install(): - """Check if Wflow is installed in the Juliacall environment.""" - try: - jl.seval("using Wflow") - except JuliaError as e: - if "not found in current path" in str(e): - install_wflow() - else: - raise - - -class WflowBmi(BmiJulia): - """Wflow.jl Basic Model Interface.""" - - def __init__(self): - """Wflow.jl Basic Model Interface.""" - check_wflow_install() - - m = self.from_name("Wflow.Model", implementation_name="Wflow.BMI") - super().__init__(m.model, m.implementation) - - -class WflowJl(WflowJlMixins, LocalModel): +class WflowJl(WflowJlMixins, ContainerizedModel): """Wflow.jl eWaterCycle LocalModel.""" - bmi_class: type[Bmi] = WflowBmi + bmi_image: ContainerImage = ContainerImage( + "ghcr.io/ewatercycle/wflowjl-remotebmi:0.2.0" + ) + protocol: Literal["grpc", "openapi"] = "openapi" def get_latlon_grid(self, name: str) -> tuple[np.ndarray, np.ndarray, np.ndarray]: """Grid latitude, longitude and shape for variable. diff --git a/src/ewatercycle_wflowjl/utils.py b/src/ewatercycle_wflowjl/utils.py deleted file mode 100644 index f2d86ab..0000000 --- a/src/ewatercycle_wflowjl/utils.py +++ /dev/null @@ -1,18 +0,0 @@ -"""Utility functions for the ewatercycle_wflowjl plugin.""" -import json -from pathlib import Path - -import numpy as np - - -def get_geojson_locs(fname: str | Path) -> tuple[np.ndarray, np.ndarray]: - """Gets the latitude and longitude values for points in a Geojson file.""" - with Path(fname).open(mode="r") as f: - data = json.loads(f.read()) - - npoints = len(data["features"]) - lats = np.zeros((npoints,)) - lons = np.zeros((npoints,)) - for ix in range(npoints): - lons[ix], lats[ix] = data["features"][ix]["geometry"]["coordinates"] - return lats, lons