Relax-fit script mode - optimisation of exponential curves

Now that everything has been setup minimisation can be used to optimise the parameter values. Firstly a grid search is applied to find a rough starting position for the subsequent optimisation algorithm. Eleven increments per dimension of the model (in this case the two dimensions { R_x, I₀}) is sufficient. The user function for executing the grid search is

[firstnumber=62]
# Grid search.
minimise.grid_search(inc=11)

The next step is to select one of the minimisation algorithms to optimise the model parameters

[firstnumber=65]
# Minimise.
minimise.execute('newton', constraints=False)