pybamm-team#3630 fix interpolant shape error (pybamm-team#3761)

* pybamm-team#3630 fix interpolant shape error

* pybamm-team#3630 changelog

CHANGELOG.md

@@ -14,6 +14,7 @@
 - Added a `get_parameter_info` method for models and modified "print_parameter_info" functionality to extract all parameters and their type in a tabular and readable format ([#3361](https://github.com/pybamm-team/PyBaMM/pull/3584))
 ## Bug fixes
 
+- Fixed a bug that lead to a `ShapeError` when specifying "Ambient temperature [K]" as an `Interpolant` with an isothermal model ([#3761](https://github.com/pybamm-team/PyBaMM/pull/3761))
 - Fixed a bug where if the first step(s) in a cycle are skipped then the cycle solution started from the model's initial conditions instead of from the last state of the previous cycle ([#3708](https://github.com/pybamm-team/PyBaMM/pull/3708))
 - Fixed a bug where the lumped thermal model conflates cell volume with electrode volume  ([#3707](https://github.com/pybamm-team/PyBaMM/pull/3707))
 - Reverted a change to the coupled degradation example notebook that caused it to be unstable for large numbers of cycles ([#3691](https://github.com/pybamm-team/PyBaMM/pull/3691))

pybamm/models/submodels/thermal/isothermal.py

@@ -26,13 +26,17 @@ def get_fundamental_variables(self):
         # specified as a function of space (y, z) only and time
         y = pybamm.standard_spatial_vars.y
         z = pybamm.standard_spatial_vars.z
-        T_x_av = self.param.T_amb(y, z, pybamm.t)
+        # Broadcast t to be the same size as y and z (to catch cases where the ambient
+        # temperature is a function of time only)
+        t_broadcast = pybamm.PrimaryBroadcast(pybamm.t, "current collector")
+        T_x_av = self.param.T_amb(y, z, t_broadcast)
+        T_vol_av = self._yz_average(T_x_av)
 
         T_dict = {
             "negative current collector": T_x_av,
             "positive current collector": T_x_av,
             "x-averaged cell": T_x_av,
-            "volume-averaged cell": T_x_av,
+            "volume-averaged cell": T_vol_av,
         }
         for domain in ["negative electrode", "separator", "positive electrode"]:
             T_dict[domain] = pybamm.PrimaryBroadcast(T_x_av, domain)
@@ -50,15 +54,25 @@ def get_coupled_variables(self, variables):
                 "Ohmic heating [W.m-3]",
                 "X-averaged Ohmic heating [W.m-3]",
                 "Volume-averaged Ohmic heating [W.m-3]",
+                "Ohmic heating per unit electrode-pair area [W.m-2]",
+                "Ohmic heating [W]",
                 "Irreversible electrochemical heating [W.m-3]",
                 "X-averaged irreversible electrochemical heating [W.m-3]",
                 "Volume-averaged irreversible electrochemical heating [W.m-3]",
+                "Irreversible electrochemical heating per unit electrode-pair area [W.m-2]",
+                "Irreversible electrochemical heating [W]",
                 "Reversible heating [W.m-3]",
                 "X-averaged reversible heating [W.m-3]",
                 "Volume-averaged reversible heating [W.m-3]",
+                "Reversible heating per unit electrode-pair area [W.m-2]",
+                "Reversible heating [W]",
                 "Total heating [W.m-3]",
                 "X-averaged total heating [W.m-3]",
                 "Volume-averaged total heating [W.m-3]",
+                "Total heating per unit electrode-pair area [W.m-2]",
+                "Total heating [W]",
+                "Negative current collector Ohmic heating [W.m-3]",
+                "Positive current collector Ohmic heating [W.m-3]",
             ]:
                 # All variables are zero
                 variables.update({var: zero})

tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_tests.py

@@ -347,3 +347,25 @@ def test_basic_processing_msmr(self):
         model = self.model(options)
         modeltest = tests.StandardModelTest(model, parameter_values=parameter_values)
         modeltest.test_all(skip_output_tests=True)
+
+    def test_basic_processing_temperature_interpolant(self):
+        times = np.arange(0, 4000, 10)
+        tmax = max(times)
+
+        def temp_drive_cycle(y, z, t):
+            return pybamm.Interpolant(
+                times,
+                298.15 + 20 * (times / tmax),
+                t,
+            )
+
+        parameter_values = pybamm.ParameterValues("Chen2020")
+        parameter_values.update(
+            {
+                "Initial temperature [K]": 298.15,
+                "Ambient temperature [K]": temp_drive_cycle,
+            }
+        )
+        model = self.model()
+        modeltest = tests.StandardModelTest(model, parameter_values=parameter_values)
+        modeltest.test_all(skip_output_tests=True)