models Package

models Package

models

Enables an easy interface similar to scikit-learn to estimate models from data.

gLIF Module

Wrapper class for gLIF methods.

class fit_neuron.models.gLIF.gLIF_model(t_bin=[0.0001, 0.0002, 0.0003, 0.0004, 0.0005, 0.0006, 0.0008, 0.001, 0.00125, 0.0015, 0.002, 0.003, 0.004, 0.005, 0.01, 0.015, 0.02, 0.025, 0.03, 0.05, 0.08, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, 0.7, 0.9, 1.2])

fit(X_list, Y_list, dt=0.0001)

Fits a gLIF model using default parameters values. A fit_neuron.optimize.neuron_base_obj.Neuron instance is returned but is not necessary to use the predicted model.

Parameters:

• X_list – list of arrays of recorded current injections.
• Y_list – list of arrays of recorded membrane voltages corresponding to input_current_list input.
• dt – time increment between consecutive current / voltage values

Returns:

fit_neuron.optimize.neuron_base_obj.Neuron instance.

is_fitted = None

bool reflecting whether the fit() method has been called on this object

predict(X_list)

Given new input current, predict the output of the neuron.