neurodynex.spike_train_variability package

Submodules

neurodynex.spike_train_variability.spike_train_variability module

neurodynex.spike_train_variability.spike_train_variability.Binomial_SampleGenerator(ro, delta_t)
neurodynex.spike_train_variability.spike_train_variability.CDF_values(ro, d_t, t)
neurodynex.spike_train_variability.spike_train_variability.ExpDist_SampleGenerator(cdf_values, d_t)
neurodynex.spike_train_variability.spike_train_variability.forward_sampling(ro=30, delta_t=0.001, n_spikes=100000, n_bins=30, show_plt=True)

{ro: firing rate, hazard function in HZ delta_t:time steps in s n_spikes:number of spikes to be generates n_bins: number of bins for plotting the histogram }

neurodynex.spike_train_variability.spike_train_variability.forward_sampling_with_refractoriness(ro=30, delta_abs=0.02, delta_t=0.001, n_spikes=100000, n_bins=30, show_plt=True)

{ro: firing rate, hazard function in HZ delta_abs: absolute refractory period in s delta_t:time steps in s n_spikes:number of spikes to be generates n_bins: number of bins for plotting the histogram }

neurodynex.spike_train_variability.spike_train_variability.inverse_transform_sampling(ro=30, d_t=0.001, n_spikes=10000, n_bins=30, show_plt=True)

{ro: firing rate, hazard function in HZ d_t: n_spikes:number of spikes to be generates n_bins: number of bins for plotting the histogram }

neurodynex.spike_train_variability.spike_train_variability.inverse_transform_sampling_with_refractoriness(ro=30, delta_abs=0.02, d_t=0.001, n_spikes=100000, n_bins=30, show_plt=True)

{ro: firing rate, hazard function in HZ delta_abs: absolute refractory period in s d_t:time step used for sampling from CDF of exponential distribution in s n_spikes:number of spikes to be generates n_bins: number of bins for plotting the histogram }

neurodynex.spike_train_variability.spike_train_variability.plots(ro, delta_t, d_t, d_t_pdf, n_spikes, n_bins, t=0.3)

{ro: firing rate, hazard function in HZ delta_t:time step for forward sampling in s d_t: time step used for sampling from CDF of exponential distribution in s d_t_pdf: time step used for sampling from PDF of exponential distribution in s n_spikes:number of spikes to be generates n_bins: number of bins for plotting the histogram t: time period during which exponential distribution is plotted, in s }

neurodynex.spike_train_variability.spike_train_variability.plots_with_refractoriness(ro, delta_abs, delta_t, d_t, d_t_pdf, n_spikes, n_bins, t=0.3)

{ro: firing rate, hazard function in HZ delta_abs: absolute refractory period in s delta_t:time step for forward sampling in s d_t: time step used for sampling from CDF of exponential distribution in s d_t_pdf: time step used for sampling from PDF of exponential distribution in s n_spikes:number of spikes to be generates n_bins: number of bins for plotting the histogram t: time period during which analytical distribution is plotted, in s }

Module contents