nrv.optim.optim_utils

Description

NeuRon Virtualizer, large scale modeling of Peripheral Nervous System with random stimulation waveforms optim utils submodule

Classes

context_modifier([extracel_context, ...])	Instantiate a context modifier: Callable object which modify a static context, regarding a vector of tunning parameters, to generate a new local context
stimulus_CM([stim_ID, interpolator, ...])	Generic context modifier which generate a stimulus from the input tuning parameters.
biphasic_stimulus_CM([stim_ID, start, ...])	Context modifier which generate a stimulus biphasic stimulus from the input tuning parameters.
harmonic_stimulus_CM([stim_ID, start, ...])	Context modifier which generate a stimulus harmonic stimulus from the input tuning parameters.
harmonic_stimulus_with_pw_CM([stim_ID, ...])
raster_count_CE()	Create a callable object which returne the number of spike from the result of a simulation
recrutement_count_CE([reverse])	Callable object which returns the number of triggered fibre in the results
charge_quantity_CE([id_elec, dt_res])	Create a callable object which return a value proportionnal to the charge quantity injected by stimulus.
stim_energy_CE([id_elec, dt_res])	Create a callable object which return a value proportionnal to the stimulus energy, assuming the electrode impedance is a constant.
optim_results([context])

Functions

interpolate(y[, x, scale, intertype, ...])
interpolate_amp(position[, t_sim, t_end, ...])	genarte a waveform from a particle position using interpolate where the position values are the output waveform amplitudes at constant sample rate
interpolate_Npts(position[, t_sim, dt, ...])	genarte a waveform from a particle position using interpolate where the position values are the coordonnate of N points which should be reached by the output waveform
cost_position_saver(data[, file_name])	Simple saver which can be used in a cost_function to save the cost and position in a .csv file (see .Optim.cost_function)