From be9eeb2e48115134b93ec0cd9035d97117bd019e Mon Sep 17 00:00:00 2001 From: Mario Mulansky Date: Tue, 3 Feb 2015 10:45:32 +0100 Subject: split distance.py into 3 separate modules --- pyspike/spike_sync.py | 136 ++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 136 insertions(+) create mode 100644 pyspike/spike_sync.py (limited to 'pyspike/spike_sync.py') diff --git a/pyspike/spike_sync.py b/pyspike/spike_sync.py new file mode 100644 index 0000000..f7cbe1d --- /dev/null +++ b/pyspike/spike_sync.py @@ -0,0 +1,136 @@ +""" + +Module containing several functions to compute SPIKE-Synchronization profiles +and distances + +Copyright 2014-2015, Mario Mulansky + +Distributed under the BSD License +""" + +from functools import partial +from pyspike import DiscreteFunc +from pyspike.generic import _generic_profile_multi, _generic_distance_matrix + + +############################################################ +# spike_sync_profile +############################################################ +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. + + :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.") + # use python backend + from python_backend import coincidence_python \ + as coincidence_impl + + times, coincidences, multiplicity = coincidence_impl(spikes1, spikes2) + + return DiscreteFunc(times, coincidences, multiplicity) + + +############################################################ +# 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: + + .. 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) + + +############################################################ +# spike_sync_profile_multi +############################################################ +def spike_sync_profile_multi(spike_trains, indices=None): + """ Computes the multi-variate spike synchronization profile for a set of + 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 multi-variate spike sync profile :math:`(t)` + :rtype: :class:`pyspike.function.DiscreteFunction` + + """ + 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_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, + 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 multi-variate spike synchronization value SYNC. + :rtype: double + """ + return spike_sync_profile_multi(spike_trains, indices).avrg(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) -- cgit v1.2.3