Merge pull request #1113 from pybamm-team/issue-1108-list-to-solver

#1108 change t_eval list to linspace

CHANGELOG.md

@@ -2,13 +2,17 @@
 
 ## Features
 
+-   Added support for sensitivity calculations to the casadi solver ([#1109](https://github.com/pybamm-team/PyBaMM/pull/1109))
 -   Added support for index 1 semi-explicit dae equations and sensitivity calculations to JAX BDF solver ([#1107](https://github.com/pybamm-team/PyBaMM/pull/1107))
 -   Allowed keyword arguments to be passed to `Simulation.plot()` ([#1099](https://github.com/pybamm-team/PyBaMM/pull/1099))
 
 ## Optimizations
 
 ## Bug fixes
 
+-   `t_eval` now gets changed to a `linspace` if a list of length 2 is passed ([#1113](https://github.com/pybamm-team/PyBaMM/pull/1113))
+-   Fixed bug when setting a function with an `InputParameter` ([#1111](https://github.com/pybamm-team/PyBaMM/pull/1111))
+
 ## Breaking changes
 
 -  Renamed `quick_plot_vars` to `output_variables` in `Simulation` to be consistent with `QuickPlot`. Passing `quick_plot_vars` to `Simulation.plot()` has been deprecated and `output_variables` should be passed instead ([#1099](https://github.com/pybamm-team/PyBaMM/pull/1099))

pybamm/simulation.py

@@ -330,17 +330,6 @@ def solve(
             solver = self.solver
 
         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:
@@ -403,13 +392,13 @@ def solve(
                             pybamm.SolverWarning,
                         )
 
-            self.t_eval = t_eval
             self._solution = solver.solve(
                 self.built_model,
                 t_eval,
                 external_variables=external_variables,
                 inputs=inputs,
             )
+            self.t_eval = self._solution.t * self.model.timescale.evaluate()
 
         elif self.operating_mode == "with experiment":
             if t_eval is not None:

pybamm/solvers/base_solver.py

@@ -510,6 +510,19 @@ def solve(self, model, t_eval=None, external_variables=None, inputs=None):
                 t_eval = np.array([0])
             else:
                 raise ValueError("t_eval cannot be None")
+        # If t_eval is provided as [t0, tf] return the solution at 100 points
+        elif isinstance(t_eval, list):
+            if len(t_eval) == 1 and self.algebraic_solver is True:
+                pass
+            elif 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)
 
         # Make sure t_eval is monotonic
         if (np.diff(t_eval) < 0).any():

tests/unit/test_simulation.py

@@ -370,7 +370,7 @@ def test_t_eval(self):
 
         # tets list gets turned into np.linspace(t0, tf, 100)
         sim.solve(t_eval=[0, 10])
-        np.testing.assert_array_equal(sim.t_eval, np.linspace(0, 10, 100))
+        np.testing.assert_array_almost_equal(sim.t_eval, np.linspace(0, 10, 100))
 
 
 if __name__ == "__main__":