#1100 remove ProcessedSymbolicVariable

Author: valentinsulzer

CHANGELOG.md

@@ -11,7 +11,8 @@
 
 ## 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))
+-   Changed sensitivity API. Removed `ProcessedSymbolicVariable`, all sensitivity now handled within the solvers and `ProcessedVariable` ()
+-   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))
 
 
 # [v0.2.3](https://github.com/pybamm-team/PyBaMM/tree/v0.2.3) - 2020-07-01

docs/source/solvers/processed_variable.rst

@@ -3,6 +3,3 @@ Post-Process Variables
 
 .. autoclass:: pybamm.ProcessedVariable
   :members:
-
-.. autoclass:: pybamm.ProcessedSymbolicVariable
-  :members:

pybamm/__init__.py

@@ -206,7 +206,6 @@ def version(formatted=False):
 #
 from .solvers.solution import Solution, _BaseSolution
 from .solvers.processed_variable import ProcessedVariable
-from .solvers.processed_symbolic_variable import ProcessedSymbolicVariable
 from .solvers.base_solver import BaseSolver
 from .solvers.dummy_solver import DummySolver
 from .solvers.algebraic_solver import AlgebraicSolver

pybamm/solvers/casadi_algebraic_solver.py

@@ -59,10 +59,7 @@ def _integrate(self, model, t_eval, inputs=None):
         t_eval : :class:`numpy.array`, size (k,)
             The times at which to compute the solution
         inputs : dict, optional
-            Any input parameters to pass to the model when solving. If any input
-            parameters that are present in the model are missing from "inputs", then
-            the solution will consist of `ProcessedSymbolicVariable` objects, which must
-            be provided with inputs to obtain their value.
+            Any input parameters to pass to the model when solving.
         """
         # Record whether there are any symbolic inputs
         inputs = inputs or {}

pybamm/solvers/processed_symbolic_variable.py

@@ -80,12 +80,9 @@ def __init__(self, base_variable, solution, known_evals=None, warn=True):
 
             # The symbolic_inputs will be used for sensitivity
             symbolic_inputs = casadi.vertcat(*symbolic_inputs_dict.values())
-            try:
-                var_casadi = base_variable.to_casadi(
-                    t_MX, y_MX, inputs=symbolic_inputs_dict
-                )
-            except:
-                n = 1
+            var_casadi = base_variable.to_casadi(
+                t_MX, y_MX, inputs=symbolic_inputs_dict
+            )
             self.base_variable_sym = casadi.Function(
                 "variable", [t_MX, y_MX, symbolic_inputs], [var_casadi]
             )

pybamm/solvers/processed_variable.py

@@ -239,19 +239,12 @@ def update(self, variables):
         # Process
         for key in variables:
             pybamm.logger.debug("Post-processing {}".format(key))
-            # If there are symbolic inputs then we need to make a
-            # ProcessedSymbolicVariable
-            if self.has_symbolic_inputs is True:
-                var = pybamm.ProcessedSymbolicVariable(self.model.variables[key], self)
-
-            # Otherwise a standard ProcessedVariable is ok
-            else:
-                var = pybamm.ProcessedVariable(
-                    self.model.variables[key], self, self._known_evals
-                )
-                # Update known_evals in order to process any other variables faster
-                for t in var.known_evals:
-                    self._known_evals[t].update(var.known_evals[t])
+            var = pybamm.ProcessedVariable(
+                self.model.variables[key], self, self._known_evals
+            )
+            # Update known_evals in order to process any other variables faster
+            for t in var.known_evals:
+                self._known_evals[t].update(var.known_evals[t])
 
             # Save variable and data
             self._variables[key] = var