Use sensitivities

[brosaplanella]

Use sensitivities to calculate the Jacobian of the cost function in order to speed up the fitting. See this notebook for an example.

[PipGrylls]

In the notebook this is passed as a parameter to a pybamm solver:

`solver = pybamm.CasadiSolver(mode="safe", atol=1e-6, rtol=1e-3)

solution = solver.solve(
model, t_eval,
inputs={"Current function [A]": 0.15652},
calculate_sensitivities=True
)`

Can you identify where a similar action is taken in our cost funtions and/or example scripts/notebooks?

[brosaplanella]

This would require the cost functions returning the Jacobian (which would depend on the sensitivity of the forward model), and feed that to the optimiser (e.g. jac argument in SciPy minimize).