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# Module containing several functions to compute SPIKE profiles and distances
# Copyright 2014-2015, Mario Mulansky <mario.mulansky@gmx.net>
# Distributed under the BSD License
from pyspike import PieceWiseLinFunc
from pyspike.generic import _generic_profile_multi, _generic_distance_multi, \
_generic_distance_matrix
############################################################
# spike_profile
############################################################
def spike_profile(spike_train1, spike_train2):
""" Computes the spike-distance profile :math:`S(t)` of the two given spike
trains. Returns the profile as a PieceWiseLinFunc object. The SPIKE-values
are defined positive :math:`S(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 spike-distance profile :math:`S(t)`.
:rtype: :class:`.PieceWiseLinFunc`
"""
# check whether the spike trains are defined for the same interval
assert spike_train1.t_start == spike_train2.t_start, \
"Given spike trains are not defined on the same interval!"
assert spike_train1.t_end == spike_train2.t_end, \
"Given spike trains are not defined on the same interval!"
# cython implementation
try:
from cython.cython_profiles import spike_profile_cython \
as spike_profile_impl
except ImportError:
print("Warning: spike_profile_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 spike_distance_python \
as spike_profile_impl
times, y_starts, y_ends = spike_profile_impl(
spike_train1.get_spikes_non_empty(),
spike_train2.get_spikes_non_empty(),
spike_train1.t_start, spike_train1.t_end)
return PieceWiseLinFunc(times, y_starts, y_ends)
############################################################
# spike_distance
############################################################
def spike_distance(spike_train1, spike_train2, interval=None):
""" Computes the spike-distance :math:`D_S` of the given spike trains. The
spike-distance is the integral over the isi distance profile :math:`S(t)`:
.. math:: D_S = \int_{T_0}^{T_1} S(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 spike-distance.
:rtype: double
"""
if interval is None:
# distance over the whole interval is requested: use specific function
# for optimal performance
try:
from cython.cython_distances import spike_distance_cython \
as spike_distance_impl
return spike_distance_impl(spike_train1.get_spikes_non_empty(),
spike_train2.get_spikes_non_empty(),
spike_train1.t_start,
spike_train1.t_end)
except ImportError:
# Cython backend not available: fall back to average profile
return spike_profile(spike_train1, spike_train2).avrg(interval)
else:
# some specific interval is provided: compute the whole profile
return spike_profile(spike_train1, spike_train2).avrg(interval)
############################################################
# spike_profile_multi
############################################################
def spike_profile_multi(spike_trains, indices=None):
""" Computes the multi-variate spike distance profile for a set of spike
trains. That is the average spike-distance of all pairs of spike-trains:
.. math:: <S(t)> = \\frac{2}{N(N-1)} \\sum_{<i,j>} S^{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 indices: list or None
:returns: The averaged spike profile :math:`<S>(t)`
:rtype: :class:`.PieceWiseLinFunc`
"""
average_dist, M = _generic_profile_multi(spike_trains, spike_profile,
indices)
average_dist.mul_scalar(1.0/M) # normalize
return average_dist
############################################################
# spike_distance_multi
############################################################
def spike_distance_multi(spike_trains, indices=None, interval=None):
""" Computes the multi-variate spike distance for a set of spike trains.
That is the time average of the multi-variate spike profile:
.. math:: D_S = \\int_0^T \\frac{2}{N(N-1)} \\sum_{<i,j>}
S^{i, j} dt
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 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: The averaged multi-variate spike distance :math:`D_S`.
:rtype: double
"""
return _generic_distance_multi(spike_trains, spike_distance, indices,
interval)
############################################################
# spike_distance_matrix
############################################################
def spike_distance_matrix(spike_trains, indices=None, interval=None):
""" Computes the time averaged spike-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 spike distances
:math:`D_S^{ij}`
:rtype: np.array
"""
return _generic_distance_matrix(spike_trains, spike_distance,
indices, interval)
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