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# Module containing several functions to compute the ISI profiles and distances
# Copyright 2014-2015, Mario Mulansky <mario.mulansky@gmx.net>
# Distributed under the BSD License
from pyspike import PieceWiseConstFunc
from pyspike.generic import _generic_profile_multi, _generic_distance_matrix
############################################################
# isi_profile
############################################################
def isi_profile(spike_train1, spike_train2):
""" Computes the isi-distance profile :math:`I(t)` of the two given
spike trains. Retruns the profile as a PieceWiseConstFunc object. The
ISI-values are defined positive :math:`I(t)>=0`.
:param spike_train1: First spike train.
:type spike_train1: :class:`.SpikeTrain`
:param spike_train2: Second spike train.
:type spike_train2: :class:`.SpikeTrain`
:returns: The isi-distance profile :math:`I(t)`
:rtype: :class:`.PieceWiseConstFunc`
"""
# check whether the spike trains are defined for the same interval
assert spike_train1.t_start == spike_train2.t_start, \
"Given spike trains seems not to have auxiliary spikes!"
assert spike_train1.t_end == spike_train2.t_end, \
"Given spike trains seems not to have auxiliary spikes!"
# load cython implementation
try:
from cython.cython_distance import isi_distance_cython \
as isi_distance_impl
except ImportError:
print("Warning: isi_distance_cython not found. Make sure that PySpike \
is installed by running\n 'python setup.py build_ext --inplace'!\n \
Falling back to slow python backend.")
# use python backend
from cython.python_backend import isi_distance_python \
as isi_distance_impl
times, values = isi_distance_impl(spike_train1.spikes, spike_train2.spikes,
spike_train1.t_start, spike_train1.t_end)
return PieceWiseConstFunc(times, values)
############################################################
# isi_distance
############################################################
def isi_distance(spike_train1, spike_train2, interval=None):
""" Computes the ISI-distance :math:`D_I` of the given spike trains. The
isi-distance is the integral over the isi distance profile
:math:`I(t)`:
.. math:: D_I = \\int_{T_0}^{T_1} I(t) dt.
:param spike_train1: First spike train.
:type spike_train1: :class:`.SpikeTrain`
:param spike_train2: Second spike train.
:type spike_train2: :class:`.SpikeTrain`
:param interval: averaging interval given as a pair of floats (T0, T1),
if None the average over the whole function is computed.
:type interval: Pair of floats or None.
:returns: The isi-distance :math:`D_I`.
:rtype: double
"""
return isi_profile(spike_train1, spike_train2).avrg(interval)
############################################################
# isi_profile_multi
############################################################
def isi_profile_multi(spike_trains, indices=None):
""" computes the multi-variate isi distance profile for a set of spike
trains. That is the average isi-distance of all pairs of spike-trains:
.. math:: <I(t)> = \\frac{2}{N(N-1)} \\sum_{<i,j>} I^{i,j},
where the sum goes over all pairs <i,j>
:param spike_trains: list of :class:`.SpikeTrain`
:param indices: list of indices defining which spike trains to use,
if None all given spike trains are used (default=None)
:type state: list or None
:returns: The averaged isi profile :math:`<I(t)>`
:rtype: :class:`.PieceWiseConstFunc`
"""
average_dist, M = _generic_profile_multi(spike_trains, isi_profile,
indices)
average_dist.mul_scalar(1.0/M) # normalize
return average_dist
############################################################
# isi_distance_multi
############################################################
def isi_distance_multi(spike_trains, indices=None, interval=None):
""" computes the multi-variate isi-distance for a set of spike-trains.
That is the time average of the multi-variate spike profile:
.. math:: D_I = \\int_0^T \\frac{2}{N(N-1)} \\sum_{<i,j>} I^{i,j},
where the sum goes over all pairs <i,j>
:param spike_trains: list of :class:`.SpikeTrain`
:param indices: list of indices defining which spike trains to use,
if None all given spike trains are used (default=None)
:param interval: averaging interval given as a pair of floats, if None
the average over the whole function is computed.
:type interval: Pair of floats or None.
:returns: The time-averaged multivariate ISI distance :math:`D_I`
:rtype: double
"""
return isi_profile_multi(spike_trains, indices).avrg(interval)
############################################################
# isi_distance_matrix
############################################################
def isi_distance_matrix(spike_trains, indices=None, interval=None):
""" Computes the time averaged isi-distance of all pairs of spike-trains.
:param spike_trains: list of :class:`.SpikeTrain`
:param indices: list of indices defining which spike trains to use,
if None all given spike trains are used (default=None)
:type indices: list or None
:param interval: averaging interval given as a pair of floats, if None
the average over the whole function is computed.
:type interval: Pair of floats or None.
:returns: 2D array with the pair wise time average isi distances
:math:`D_{I}^{ij}`
:rtype: np.array
"""
return _generic_distance_matrix(spike_trains, isi_distance,
indices, interval)
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