diff options
Diffstat (limited to 'pyspike/distances.py')
| -rw-r--r-- | pyspike/distances.py | 146 |
1 files changed, 107 insertions, 39 deletions
diff --git a/pyspike/distances.py b/pyspike/distances.py index 04ea77b..5476b6f 100644 --- a/pyspike/distances.py +++ b/pyspike/distances.py @@ -11,7 +11,7 @@ import numpy as np import threading from functools import partial -from pyspike import PieceWiseConstFunc, PieceWiseLinFunc +from pyspike import PieceWiseConstFunc, PieceWiseLinFunc, DiscreteFunction ############################################################ @@ -132,39 +132,57 @@ def spike_distance(spikes1, spikes2, interval=None): ############################################################ # spike_sync_profile ############################################################ -def spike_sync_profile(spikes1, spikes2, k=3): +def spike_sync_profile(spikes1, spikes2): + """ Computes the spike-synchronization profile S_sync(t) of the two given + spike trains. Returns the profile as a DiscreteFunction object. The S_sync + values are either 1 or 0, indicating the presence or absence of a + coincidence. The spike trains are expected to have auxiliary spikes at the + beginning and end of the interval. Use the function add_auxiliary_spikes to + add those spikes to the spike train. - assert k > 0 + :param spikes1: ordered array of spike times with auxiliary spikes. + :param spikes2: ordered array of spike times with auxiliary spikes. + :returns: The spike-distance profile :math:`S_{sync}(t)`. + :rtype: :class:`pyspike.function.DiscreteFunction` + + """ # cython implementation try: from cython_distance import coincidence_cython \ as coincidence_impl except ImportError: -# print("Warning: spike_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.") + print("Warning: spike_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 python_backend import coincidence_python \ as coincidence_impl - st, c = coincidence_impl(spikes1, spikes2) + times, coincidences, multiplicity = coincidence_impl(spikes1, spikes2) - dc = np.zeros(len(c)) - for i in xrange(2*k): - dc[k:-k] += c[i:-2*k+i] + return DiscreteFunction(times, coincidences, multiplicity) - for n in xrange(0, k): - for i in xrange(n+k): - dc[n] += c[i] - dc[-n-1] += c[-i-1] - for i in xrange(k-n-1): - dc[n] += c[i] - dc[-n-1] += c[-i-1] - dc *= 1.0/k +############################################################ +# spike_sync +############################################################ +def spike_sync(spikes1, spikes2, interval=None): + """ Computes the spike synchronization value SYNC of the given spike + trains. The spike synchronization value is the computed as the total number + of coincidences divided by the total number of spikes: - return PieceWiseConstFunc(st, dc) + .. math:: SYNC = \sum_n C_n / N. + + :param spikes1: ordered array of spike times with auxiliary spikes. + :param spikes2: ordered array of spike times with auxiliary spikes. + :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 synchronization value. + :rtype: double + """ + return spike_sync_profile(spikes1, spikes2).avrg(interval) ############################################################ @@ -201,8 +219,7 @@ def _generic_profile_multi(spike_trains, pair_distance_func, indices=None): for (i, j) in pairs[1:]: current_dist = pair_distance_func(spike_trains[i], spike_trains[j]) average_dist.add(current_dist) # add to the average - average_dist.mul_scalar(1.0/len(pairs)) # normalize - return average_dist + return average_dist, len(pairs) ############################################################ @@ -273,7 +290,10 @@ def isi_profile_multi(spike_trains, indices=None): :returns: The averaged isi profile :math:`<S_{isi}>(t)` :rtype: :class:`pyspike.function.PieceWiseConstFunc` """ - return _generic_profile_multi(spike_trains, isi_profile, indices) + average_dist, M = _generic_profile_multi(spike_trains, isi_profile, + indices) + average_dist.mul_scalar(1.0/M) # normalize + return average_dist ############################################################ @@ -314,39 +334,65 @@ def spike_profile_multi(spike_trains, indices=None): :rtype: :class:`pyspike.function.PieceWiseLinFunc` """ - return _generic_profile_multi(spike_trains, spike_profile, indices) + 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: + S_{spike} = \int_0^T 2/((N(N-1)) sum_{<i,j>} S_{spike}^{i, j} dt + where the sum goes over all pairs <i,j> + + :param spike_trains: list of spike trains + :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 spike distance S. + :rtype: double + """ + return spike_profile_multi(spike_trains, indices).avrg(interval) ############################################################ # spike_profile_multi ############################################################ -def spike_sync_profile_multi(spike_trains, indices=None, k=3): +def spike_sync_profile_multi(spike_trains, indices=None): """ Computes the multi-variate spike synchronization profile for a set of - spike trains. That is the average spike-distance of all pairs of spike - trains: - :math:`S_ss(t) = 2/((N(N-1)) sum_{<i,j>} S_{ss}^{i, j}`, - where the sum goes over all pairs <i,j> + spike trains. For each spike in the set of spike trains, the multi-variate + profile is defined as the number of coincidences divided by the number of + spike trains pairs involving the spike train of containing this spike, + which is the number of spike trains minus one (N-1). :param spike_trains: list of spike trains :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_{ss}>(t)` - :rtype: :class:`pyspike.function.PieceWiseConstFunc` + :returns: The multi-variate spike sync profile :math:`<S_{sync}>(t)` + :rtype: :class:`pyspike.function.DiscreteFunction` """ - prof_func = partial(spike_sync_profile, k=k) - return _generic_profile_multi(spike_trains, prof_func, indices) + prof_func = partial(spike_sync_profile) + average_dist, M = _generic_profile_multi(spike_trains, prof_func, + indices) + # average_dist.mul_scalar(1.0/M) # no normalization here! + 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: - S_{spike} = \int_0^T 2/((N(N-1)) sum_{<i,j>} S_{spike}^{i, j} dt - where the sum goes over all pairs <i,j> +def spike_sync_multi(spike_trains, indices=None, interval=None): + """ Computes the multi-variate spike synchronization value for a set of + spike trains. :param spike_trains: list of spike trains :param indices: list of indices defining which spike trains to use, @@ -355,10 +401,10 @@ def spike_distance_multi(spike_trains, indices=None, interval=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 spike distance S. + :returns: The multi-variate spike synchronization value SYNC. :rtype: double """ - return spike_profile_multi(spike_trains, indices).avrg(interval) + return spike_sync_profile_multi(spike_trains, indices).avrg(interval) ############################################################ @@ -434,3 +480,25 @@ def spike_distance_matrix(spike_trains, indices=None, interval=None): """ return _generic_distance_matrix(spike_trains, spike_distance, indices, interval) + + +############################################################ +# spike_sync_matrix +############################################################ +def spike_sync_matrix(spike_trains, indices=None, interval=None): + """ Computes the overall spike-synchronization value of all pairs of + spike-trains. + + :param spike_trains: list of spike trains + :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 spike synchronization values + :math:`SYNC_{ij}` + :rtype: np.array + """ + return _generic_distance_matrix(spike_trains, spike_sync, + indices, interval) |