Auxiliary functions

This is a work in progress set of auxiliary functions in the spikeanalysis module. These functions don’t easily belong in a class, but will work well with class objects or other user inputs.

Kolmogorov-Smirnov Testing

This tests whether two empiric datasets are from the same distribution. Thus the null hypothesis is that two datasets are from the same distribution and pvalues will be returned for each neuron/unit. The user can choose their pvalue cutoff to reject the null.

ks_values = sa.kolmo_smir_stats([dataset1, dataset2], datatype = None)

Or with a spike analysis object (for example with isi values between baseline and stimulus)

# spiketrain is a SpikeAnalysis object
spiketrain.get_interspike_intervals()
spiketrain.compute_event_interspike_intervals()
isi_values = spiketrain.isi_values

ks_values = sa.kolmo_smir_stats(isi_values, datatype = "isi")