#1080 require t_eval

CHANGELOG.md

@@ -7,7 +7,7 @@
 -   Added some new solvers for algebraic models ([#1059](https://github.com/pybamm-team/PyBaMM/pull/1059))
 -   Added `length_scales` attribute to models ([#1058](https://github.com/pybamm-team/PyBaMM/pull/1058))
 -   Added averaging in secondary dimensions ([#1057](https://github.com/pybamm-team/PyBaMM/pull/1057))
--   Added SEI reaction based on Yang et. al. 2017 and reduction in porosity ([#1009](https://github.com/pybamm-team/PyBaMM/issues/1009)) 
+-   Added SEI reaction based on Yang et. al. 2017 and reduction in porosity ([#1009](https://github.com/pybamm-team/PyBaMM/issues/1009))
 
 ## Optimizations
 
@@ -22,6 +22,8 @@
 
 ## Breaking changes
 
+-  The solution times `t_eval` must now be provided when solving a simulation without an experiment or drive cycle data ([]())
+
 # [v0.2.2](https://github.com/pybamm-team/PyBaMM/tree/v0.2.2) - 2020-06-01
 
 New SEI models, simplification of submodel structure, as well as optimisations and general bug fixes.

README.md

@@ -13,9 +13,9 @@ PyBaMM (Python Battery Mathematical Modelling) solves physics-based electrochemi
 The easiest way to use PyBaMM is to run a 1C constant-current discharge with a model of your choice with all the default settings:
 ```python3
 import pybamm
-model = pybamm.lithium_ion.DFN() # Doyle-Fuller-Newman model
+model = pybamm.lithium_ion.DFN()  # Doyle-Fuller-Newman model
 sim = pybamm.Simulation(model)
-sim.solve()
+sim.solve([0, 3600])  # solve for 1 hour
 sim.plot()
 ```
 or simulate an experiment such as CCCV:
@@ -42,7 +42,7 @@ For new users we recommend the [Getting Started](examples/notebooks/Getting%20St
 
 Further details can be found in a number of [detailed examples](examples/notebooks/README.md), hosted here on
 github. In addition, there is a [full API documentation](http://pybamm.readthedocs.io/),
-hosted on [Read The Docs](readthedocs.io). 
+hosted on [Read The Docs](readthedocs.io).
 Additional supporting material can be found
 [here](https://github.com/pybamm-team/pybamm-supporting-material/).
 

examples/notebooks/Getting Started/Tutorial 1 - How to run a model.ipynb

@@ -64,7 +64,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can then call 'solve' on our simulation object to solve the model (by default the the model is solved for a 1C constant current discharge):"
+    "We can then call 'solve' on our simulation object to solve the model, passing the window of time to solve for in seconds (here 1 hour):"
    ]
   },
   {
@@ -73,7 +73,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "sim.solve()"
+    "sim.solve([0, 3600])"
    ]
   },
   {

examples/notebooks/Getting Started/Tutorial 2 - Setting Parameter Values.ipynb

@@ -116,7 +116,7 @@
    "source": [
     "model = pybamm.lithium_ion.SPMe()\n",
     "sim = pybamm.Simulation(model, parameter_values=parameter_values)\n",
-    "sim.solve()\n",
+    "sim.solve([0, 3600])\n",
     "sim.plot()"
    ]
   },

examples/notebooks/Getting Started/Tutorial 3 - Basic Plotting.ipynb

@@ -35,7 +35,7 @@
     "import pybamm\n",
     "model = pybamm.lithium_ion.SPMe()\n",
     "sim = pybamm.Simulation(model)\n",
-    "sim.solve()"
+    "sim.solve([0, 3600])"
    ]
   },
   {

examples/notebooks/Getting Started/Tutorial 4 - Model Options.ipynb

@@ -72,7 +72,7 @@
     "parameter_values.update({\"Typical current [A]\": 3})\n",
     "sim.specs(parameter_values=parameter_values)\n",
     "\n",
-    "sim.solve()"
+    "sim.solve([0, 3600])"
    ]
   },
   {

examples/notebooks/rate-capability.ipynb

@@ -20,7 +20,15 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
    "source": [
     "%pip install pybamm -q    # install PyBaMM if it is not installed\n",
     "import pybamm\n",
@@ -153,7 +161,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.6.9"
   },
   "mimetype": "text/x-python",
   "name": "python",

examples/scripts/compare_lead_acid.py

@@ -17,7 +17,7 @@
 sims = []
 for model in models:
     sim = pybamm.Simulation(model)
-    sim.solve()
+    sim.solve([0, 3600])
     sims.append(sim)
 
 # plot

examples/scripts/compare_lithium_ion.py

@@ -6,17 +6,13 @@
 # pybamm.set_logging_level("INFO")
 
 # load models
-models = [
-    pybamm.lithium_ion.SPM(),
-    pybamm.lithium_ion.SPMe(),
-    pybamm.lithium_ion.DFN(),
-]
+models = [pybamm.lithium_ion.SPM(), pybamm.lithium_ion.SPMe(), pybamm.lithium_ion.DFN()]
 
 # create and run simulations
 sims = []
 for model in models:
     sim = pybamm.Simulation(model)
-    sim.solve()
+    sim.solve([0, 3600])
     sims.append(sim)
 
 # plot

examples/scripts/nca_parameters.py

@@ -7,5 +7,5 @@
 parameter_values = pb.ParameterValues(chemistry=chemistry)
 
 sim = pb.Simulation(model, parameter_values=parameter_values, C_rate=1)
-sim.solve()
+sim.solve([0, 3600])
 sim.plot()

examples/scripts/run_simulation.py

@@ -3,5 +3,5 @@
 model = pybamm.lithium_ion.SPM()
 
 sim = pybamm.Simulation(model)
-sim.solve()
+sim.solve([0, 3600])
 sim.plot()

pybamm/simulation.py

@@ -68,7 +68,7 @@ class Simulation:
         A list of variables to plot automatically
     C_rate: float (optional)
         The C_rate at which you would like to run a constant current
-        experiment at.
+        (dis)charge at.
     """
 
     def __init__(
@@ -87,15 +87,20 @@ def __init__(
         self.parameter_values = parameter_values or model.default_parameter_values
 
         if experiment is None:
-            self.operating_mode = "without experiment"
-            if C_rate:
-                self.C_rate = C_rate
-                self._parameter_values.update(
-                    {
-                        "Current function [A]": self.C_rate
-                        * self._parameter_values["Cell capacity [A.h]"]
-                    }
-                )
+            # Check to see if the current is provided as data (i.e. drive cycle)
+            current = self._parameter_values.get("Current function [A]")
+            if isinstance(current, tuple):
+                self.operating_mode = "drive cycle"
+            else:
+                self.operating_mode = "without experiment"
+                if C_rate:
+                    self.C_rate = C_rate
+                    self._parameter_values.update(
+                        {
+                            "Current function [A]": self.C_rate
+                            * self._parameter_values["Cell capacity [A.h]"]
+                        }
+                    )
             self.model = model
         else:
             self.set_up_experiment(model, experiment)
@@ -324,11 +329,21 @@ def solve(
         Parameters
         ----------
         t_eval : numeric type, optional
-            The times at which to compute the solution. If None and the parameter
-            "Current function [A]" is not read from data the model will
-            be solved for a full discharge (1 hour / C_rate). If None and the
-            parameter "Current function [A]" is read from data the model will be
-            solved at the times provided in the data.
+            The times (in seconds) at which to compute the solution. Can be
+            provided as an array of times at which to return the solution, or as a
+            list `[t0, tf]` where `t0` is the initial time and `tf` is the final time.
+            If provided as a list the solution is returned at 100 points within the
+            interval `[t0, tf]`.
+
+            If not using an experiment or running a drive cycle simulation (current
+            provided as data) `t_eval` *must* be provided.
+
+            If running an experiment the values in `t_eval` are ignored, and the
+            solution times are specified by the experiment.
+
+            If None and the parameter "Current function [A]" is read from data
+            (i.e. drive cycle simulation) the model will be solved at the times
+            provided in the data.
         solver : :class:`pybamm.BaseSolver`
             The solver to use to solve the model.
         external_variables : dict
@@ -347,14 +362,36 @@ def solve(
         if solver is None:
             solver = self.solver
 
-        if self.operating_mode == "without experiment":
-            # For drive cycles (current provided as data) we perform additional tests
-            # on t_eval (if provided) to ensure the returned solution captures the
-            # input. If the current is provided as data then the "Current function [A]"
-            # is the tuple (filename, data).
-            # First, read the current function (if provided, otherwise return None)
-            current = self._parameter_values.get("Current function [A]")
-            if isinstance(current, tuple):
+        if self.operating_mode in ["without experiment", "drive cycle"]:
+            # If t_eval is provided as [t0, tf] return the solution at 100 points
+            if isinstance(t_eval, list):
+                if len(t_eval) != 2:
+                    raise pybamm.SolverError(
+                        "'t_eval' can be provided as an array of times at which to "
+                        "return the solution, or as a list [t0, tf] where t0 is the "
+                        "initial time and tf is the final time, but has been provided "
+                        "as a list of length {}.".format(len(t_eval))
+                    )
+                else:
+                    t_eval = np.linspace(t_eval[0], t_eval[-1], 100)
+
+            if self.operating_mode == "without experiment":
+                if t_eval is None:
+                    raise pybamm.SolverError(
+                        "'t_eval' must be provided if not using an experiment or "
+                        "simulating a drive cycle. 't_eval' can be provided as an "
+                        "array of times at which to return the solution, or as a "
+                        "list [t0, tf] where t0 is the initial time and tf is the "
+                        "final time. "
+                        "For a constant current (dis)charge the suggested 't_eval'  "
+                        "is [0, 4000/C] where C is the C-rate."
+                    )
+
+            elif self.operating_mode == "drive cycle":
+                # For drive cycles (current provided as data) we perform additional
+                # tests on t_eval (if provided) to ensure the returned solution
+                # captures the input. If the current is provided as data then the
+                # "Current function [A]" is the tuple (filename, data).
                 filename = self._parameter_values["Current function [A]"][0]
                 time_data = self._parameter_values["Current function [A]"][1][:, 0]
                 # If no t_eval is provided, we use the times provided in the data.
@@ -363,10 +400,10 @@ def solve(
                         "Setting t_eval as specified by the data '{}'".format(filename)
                     )
                     t_eval = time_data
-                # If t_eval is provided we first check if it contains all of the times
-                # in the data to within 10-12. If it doesn't, we then check
-                # that the largest gap in t_eval is smaller than the smallest gap in the
-                # time data (to ensure the resolution of t_eval is fine enough).
+                # If t_eval is provided we first check if it contains all of the
+                # times in the data to within 10-12. If it doesn't, we then check
+                # that the largest gap in t_eval is smaller than the smallest gap in
+                # the time data (to ensure the resolution of t_eval is fine enough).
                 # We only raise a warning here as users may genuinely only want
                 # the solution returned at some specified points.
                 elif (
@@ -398,24 +435,6 @@ def solve(
                             ),
                             pybamm.SolverWarning,
                         )
-            # If not using a drive cycle and t_eval is not provided, set t_eval
-            # to correspond to a single discharge
-            elif t_eval is None:
-                if current is None:
-                    t_end = 1
-                else:
-                    # Get C-rate, return None if it doesn't exist
-                    capacity = self.parameter_values["Cell capacity [A.h]"]
-                    if isinstance(current, pybamm.InputParameter):
-                        C_rate = inputs["Current function [A]"] / capacity
-                        t_end = 3600 / C_rate
-                    else:
-                        try:
-                            C_rate = current / capacity
-                            t_end = 3600 / C_rate
-                        except TypeError:
-                            t_end = 3600
-                t_eval = np.linspace(0, t_end, 100)
 
             self.t_eval = t_eval
             self._solution = solver.solve(
@@ -472,6 +491,7 @@ def solve(
                     timer.format(timer.time())
                 )
             )
+
         return self.solution
 
     def step(
@@ -489,7 +509,7 @@ def step(
             The solver to use to solve the model.
         npts : int, optional
             The number of points at which the solution will be returned during
-            the step dt. default is 2 (returns the solution at t0 and t0 + dt).
+            the step dt. Default is 2 (returns the solution at t0 and t0 + dt).
         external_variables : dict
             A dictionary of external variables and their corresponding
             values at the current time. The variables must correspond to