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# Module containing functions to compute the PSTH profile
# Copyright 2015, Mario Mulansky <mario.mulansky@gmx.net>
# Distributed under the BSD License
import numpy as np
from pyspike import PieceWiseConstFunc
# Computes the peri-stimulus time histogram of a set of spike trains
def psth(spike_trains, bin_size):
""" Computes the peri-stimulus time histogram of a set of
:class:`.SpikeTrain`. The PSTH is simply the histogram of merged spike
events. The :code:`bin_size` defines the width of the histogram bins.
:param spike_trains: list of :class:`.SpikeTrain`
:param bin_size: width of the histogram bins.
:return: The PSTH as a :class:`.PieceWiseConstFunc`
"""
bin_count = int((spike_trains[0].t_end - spike_trains[0].t_start) /
bin_size)
bins = np.linspace(spike_trains[0].t_start, spike_trains[0].t_end,
bin_count+1)
# N = len(spike_trains)
combined_spike_train = spike_trains[0].spikes
for i in range(1, len(spike_trains)):
combined_spike_train = np.append(combined_spike_train,
spike_trains[i].spikes)
vals, edges = np.histogram(combined_spike_train, bins, density=False)
bin_size = edges[1]-edges[0]
return PieceWiseConstFunc(edges, vals) # /(N*bin_size))
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