#1477 update test_sensitivities to use a dae

Author: martinjrobins

tests/unit/test_solvers/test_base_solver.py

@@ -324,37 +324,43 @@ def test_extrapolation_warnings(self):
 
     def test_sensitivities(self):
 
-        def exact_diff_a(v, a, b):
-            return np.array([v**2 + 2 * a])
+        def exact_diff_a(y, a, b):
+            return np.array([
+                [y[0]**2 + 2 * a],
+                [y[0]]
+            ])
 
-        def exact_diff_b(v, a, b):
-            return np.array([v])
+        def exact_diff_b(y, a, b):
+            return np.array([[y[0]], [0]])
 
-        for f in ['', 'python', 'casadi', 'jax']:
+        for convert_to_format in ['', 'python', 'casadi', 'jax']:
             model = pybamm.BaseModel()
             v = pybamm.Variable("v")
+            u = pybamm.Variable("u")
             a = pybamm.InputParameter("a")
             b = pybamm.InputParameter("b")
             model.rhs = {v: a * v**2 + b * v + a**2}
-            model.initial_conditions = {v: 1}
-            model.convert_to_format = f
-            solver = pybamm.ScipySolver()
+            model.algebraic = {u: a * v - u}
+            model.initial_conditions = {v: 1, u: a * 1}
+            model.convert_to_format = convert_to_format
+            solver = pybamm.CasadiSolver()
             solver.set_up(model, calculate_sensitivites=True,
                           inputs={'a': 0, 'b': 0})
             all_inputs = []
             for v_value in [0.1, -0.2, 1.5, 8.4]:
-                for a_value in [0.12, 1.5]:
-                    for b_value in [0.82, 1.9]:
-                        y = np.array([v_value])
-                        t = 0
-                        inputs = {'a': a_value, 'b': b_value}
-                        all_inputs.append((t, y, inputs))
+                for u_value in [0.13, -0.23, 1.3, 13.4]:
+                    for a_value in [0.12, 1.5]:
+                        for b_value in [0.82, 1.9]:
+                            y = np.array([v_value, u_value])
+                            t = 0
+                            inputs = {'a': a_value, 'b': b_value}
+                            all_inputs.append((t, y, inputs))
             for t, y, inputs in all_inputs:
-                if f == 'casadi':
+                if model.convert_to_format == 'casadi':
                     use_inputs = casadi.vertcat(*[x for x in inputs.values()])
                 else:
                     use_inputs = inputs
-                if f == 'jax':
+                if model.convert_to_format == 'jax':
                     sens = model.sensitivities_eval(
                             t, y, use_inputs
                     )

tests/unit/test_solvers/test_idaklu_solver.py

@@ -68,7 +68,10 @@ def test_ida_roberts_klu_sensitivities(self):
 
             t_eval = np.linspace(0, 3, 100)
             a_value = 0.1
-            sol = solver.solve(model, t_eval, inputs={"a": a_value})
+            sol = solver.solve(
+                model, t_eval, inputs={"a": a_value},
+                calculate_sensitivities=True
+            )
 
             # test that final time is time of event
             # y = 0.1 t + y0 so y=0.2 when t=2