#191 try again to remove ida import

pybamm/solvers/scikits_dae_solver.py

@@ -7,16 +7,14 @@
 
 import numpy as np
 import importlib
-from scipy.sparse import issparse
+import scipy.sparse as sparse
 
 scikits_odes_spec = importlib.util.find_spec("scikits")
 if scikits_odes_spec is not None:
     scikits_odes_spec = importlib.util.find_spec("scikits.odes")
     if scikits_odes_spec is not None:
         scikits_odes = importlib.util.module_from_spec(scikits_odes_spec)
         scikits_odes_spec.loader.exec_module(scikits_odes)
-else:
-    jac_class = object
 
 
 class ScikitsDaeSolver(pybamm.DaeSolver):
@@ -81,10 +79,20 @@ def rootfn(t, y, ydot, return_root):
         extra_options = {"old_api": False, "rtol": self.tol, "atol": self.tol}
 
         if jacobian:
-            # Put the user-supplied Jacobian into the SUNDIALS Class
-            jacfn = JacobianFunctionIDA()
-            jacfn.set_jacobian(mass_matrix, jacobian)
-            extra_options.update({"jacfn": jacfn})
+            jac_y0_t0 = jacobian(t_eval[0], y0)
+            if sparse.issparse(jac_y0_t0):
+                def jacfn(t, y, ydot, residuals, cj, J):
+                    jac_eval = jacobian(t, y) - cj * mass_matrix
+                    J[:][:] = jac_eval.toarray()
+
+            else:
+                def jacfn(t, y, ydot, residuals, cj, J):
+                    jac_eval = jacobian(t, y) - cj * mass_matrix
+                    J[:][:] = jac_eval
+
+            extra_options.update({
+                "jacfn": jacfn
+            })
 
         if events:
             extra_options.update({"rootfn": rootfn, "nr_rootfns": len(events)})
@@ -98,30 +106,3 @@ def rootfn(t, y, ydot, return_root):
 
         # return solution, we need to tranpose y to match scipy's interface
         return sol.values.t, np.transpose(sol.values.y)
-
-
-class JacobianFunctionIDA(jac_class):
-    def set_jacobian(self, mass_matrix, jacobian):
-        """
-        Sets the user supplied mass matrix and Jacobian function for the DAE model.
-
-        Parameters
-        ----------
-        mass_matrix : array_like
-            The (sparse) mass matrix for the chosen spatial method.
-        jacobian : method
-            A function that takes in t and y and returns the Jacobian.
-
-        """
-        self.mass_matrix = mass_matrix
-        self.jacobian = jacobian
-
-    def evaluate(self, t, y, ydot, residuals, cj, return_jacobian):
-        # scikits_odes requires the full (dense) jacobian
-        jac_eval = self.jacobian(t, y) - cj * self.mass_matrix
-        if issparse(jac_eval):
-            return_jacobian[:][:] = jac_eval.toarray()
-        else:
-            return_jacobian[:][:] = jac_eval
-
-        return 0