brainpy.measure module

This module aims to provide commonly used analysis methods for simulated neuronal data. You can access them through brainpy.measure.XXX.

cross_correlation(spikes, bin[, dt])	Calculate cross correlation index between neurons.
matrix_correlation(x, y)	Pearson correlation of the lower triagonal of two matrices.
functional_connectivity(activities)	Functional connectivity matrix of timeseries activities.
raster_plot(sp_matrix, times)	Get spike raster plot which displays the spiking activity of a group of neurons over time.
firing_rate(sp_matrix, width[, dt, numpy])	Calculate the mean firing rate over in a neuron group.
voltage_fluctuation(potentials)	Calculate neuronal synchronization via voltage variance.
weighted_correlation(x, y, w)	Weighted Pearson correlation of two data series.