hnn_core.optimization.Optimizer#

class hnn_core.optimization.Optimizer(initial_net, tstop, constraints, set_params, initial_params=None, solver='bayesian', obj_fun='dipole_rmse', max_iter=200)[source]#

Methods

`fit`(**obj_fun_kwargs)	Runs optimization routine.
`plot_convergence`([ax, show])	Convergence plot.

__repr__()[source]#: Return repr(self).

fit(**obj_fun_kwargs)[source]#

Runs optimization routine.

Parameters:

targetinstance of Dipole (Required if obj_fun=’dipole_rmse’): A dipole object with experimental data.
n_trialsint (Optional if obj_fun=’dipole_rmse’): Number of trials to simulate and average.
f_bandslist of tuples (Required if obj_fun=’maximize_psd’): Lower and higher limit for each frequency band.
relative_bandpowerlist of float | float (Required if obj_fun=’maximize_psd’): Weight for each frequency band in f_bands. If a single float is provided, the same weight is applied to all frequency bands.
scale_factorfloat, optional: The dipole scale factor.
smooth_window_lenfloat, optional: The smooth window length.