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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 __future__ import absolute_import
import pyspike
from pyspike import PieceWiseConstFunc
from pyspike.generic import _generic_profile_multi, _generic_distance_multi, \
_generic_distance_matrix
############################################################
# isi_profile
############################################################
def isi_profile(*args, **kwargs):
""" Computes the isi-distance profile :math:`I(t)` of the given
spike trains. Returns the profile as a PieceWiseConstFunc object. The
ISI-values are defined positive :math:`I(t)>=0`.
Valid call structures::
isi_profile(st1, st2) # returns the bi-variate profile
isi_profile(st1, st2, st3) # multi-variate profile of 3 spike trains
spike_trains = [st1, st2, st3, st4] # list of spike trains
isi_profile(spike_trains) # profile of the list of spike trains
isi_profile(spike_trains, indices=[0, 1]) # use only the spike trains
# given by the indices
The multivariate ISI distance profile for a set of spike trains is defined
as the average ISI-profile 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>
:returns: The isi-distance profile :math:`I(t)`
:rtype: :class:`.PieceWiseConstFunc`
"""
if len(args) == 1:
return isi_profile_multi(args[0], **kwargs)
elif len(args) == 2:
return isi_profile_bi(args[0], args[1])
else:
return isi_profile_multi(args)
############################################################
# isi_profile_bi
############################################################
def isi_profile_bi(spike_train1, spike_train2):
""" Specific function to compute a bivariate ISI-profile. This is a
deprecated function and should not be called directly. Use
:func:`.isi_profile` to compute ISI-profiles.
: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 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!"
# load cython implementation
try:
from .cython.cython_profiles import isi_profile_cython \
as isi_profile_impl
except ImportError:
if not(pyspike.disable_backend_warning):
print("Warning: isi_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 isi_distance_python \
as isi_profile_impl
times, values = isi_profile_impl(spike_train1.get_spikes_non_empty(),
spike_train2.get_spikes_non_empty(),
spike_train1.t_start, spike_train1.t_end)
return PieceWiseConstFunc(times, values)
############################################################
# isi_profile_multi
############################################################
def isi_profile_multi(spike_trains, indices=None):
""" Specific function to compute the multivariate ISI-profile for a set of
spike trains. This is a deprecated function and should not be called
directly. Use :func:`.isi_profile` to compute ISI-profiles.
: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_bi,
indices)
average_dist.mul_scalar(1.0/M) # normalize
return average_dist
############################################################
# isi_distance
############################################################
def isi_distance(*args, **kwargs):
""" 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.
In the multivariate case it is the integral over the multivariate
ISI-profile, i.e. the average profile over all spike train pairs:
.. 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>
Valid call structures::
isi_distance(st1, st2) # returns the bi-variate distance
isi_distance(st1, st2, st3) # multi-variate distance of 3 spike trains
spike_trains = [st1, st2, st3, st4] # list of spike trains
isi_distance(spike_trains) # distance of the list of spike trains
isi_distance(spike_trains, indices=[0, 1]) # use only the spike trains
# given by the indices
:returns: The isi-distance :math:`D_I`.
:rtype: double
"""
if len(args) == 1:
return isi_distance_multi(args[0], **kwargs)
elif len(args) == 2:
return isi_distance_bi(args[0], args[1], **kwargs)
else:
return isi_distance_multi(args, **kwargs)
############################################################
# _isi_distance_bi
############################################################
def isi_distance_bi(spike_train1, spike_train2, interval=None):
""" Specific function to compute the bivariate ISI-distance.
This is a deprecated function and should not be called directly. Use
:func:`.isi_distance` to compute ISI-distances.
: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
"""
if interval is None:
# distance over the whole interval is requested: use specific function
# for optimal performance
try:
from .cython.cython_distances import isi_distance_cython \
as isi_distance_impl
return isi_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 profile averaging
return isi_profile_bi(spike_train1, spike_train2).avrg(interval)
else:
# some specific interval is provided: use profile
return isi_profile_bi(spike_train1, spike_train2).avrg(interval)
############################################################
# isi_distance_multi
############################################################
def isi_distance_multi(spike_trains, indices=None, interval=None):
""" Specific function to compute the multivariate ISI-distance.
This is a deprecfated function and should not be called directly. Use
:func:`.isi_distance` to compute ISI-distances.
: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 _generic_distance_multi(spike_trains, isi_distance_bi, indices,
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_bi,
indices=indices, interval=interval)
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