neurotools.stats.modefind module

Routines for finding the mode of distributions.

neurotools.stats.modefind.modefind(points, burst=10)[source]

Locate post-event mode in one-dimensional point-processes with refractoriness, mainly for neuroscience data.

Removes intervals shorter than 10.

Finds peak using log-KDE approximation

Parameters:

  • points (np.array)

  • burst (int) – Default is 10. Points smaller than this are excluded

Returns:

Estimated mode of the distribution

Return type:

float

neurotools.stats.modefind.logmodeplot(points, K=5, burst=None)[source]

Accepts list of ISI times. Finds the mode using a log-KDE density estimate Plots this along with histogram

Parameters:

  • points (np.array)

  • burst (int) – Default is None. If a number, points smaller than this are excluded

neurotools.stats.modefind.logmode(points, K=5, burst=None)[source]

Accepts list of ISI times. Finds the mode using a log-KDE density estimate

Parameters:

  • points (np.array)

  • burst (int) – Default is None. If a number, points smaller than this are excluded

neurotools.stats.modefind.peakfinder5(st, K=5)[source]