From 34bd30415dd93a2425ce566627e24ee9483ada3e Mon Sep 17 00:00:00 2001 From: Mario Mulansky Date: Thu, 20 Sep 2018 10:49:42 -0700 Subject: Spike Order support (#39) * reorganized directionality module * further refactoring of directionality * completed python directionality backend * added SPIKE-Sync based filtering new function filter_by_spike_sync removes spikes that have a multi-variate Spike Sync value below some threshold not yet fully tested, python backend missing. * spike sync filtering, cython sim ann Added function for filtering out events based on a threshold for the spike sync values. Usefull for focusing on synchronous events during directionality analysis. Also added cython version of simulated annealing for performance. * added coincidence single profile to python backend missing function in python backend added, identified and fixed a bug in the implementation as well * updated test case to new spike sync behavior * python3 fixes * another python3 fix * reorganized directionality module * further refactoring of directionality * completed python directionality backend * added SPIKE-Sync based filtering new function filter_by_spike_sync removes spikes that have a multi-variate Spike Sync value below some threshold not yet fully tested, python backend missing. * spike sync filtering, cython sim ann Added function for filtering out events based on a threshold for the spike sync values. Usefull for focusing on synchronous events during directionality analysis. Also added cython version of simulated annealing for performance. * added coincidence single profile to python backend missing function in python backend added, identified and fixed a bug in the implementation as well * updated test case to new spike sync behavior * python3 fixes * another python3 fix * Fix absolute imports in directionality measures * remove commented code * Add directionality to docs, bump version * Clean up directionality module, add doxy. * Remove debug print from tests * Fix bug in calling Python backend * Fix incorrect integrals in PieceWiseConstFunc (#36) * Add (some currently failing) tests for PieceWiseConstFunc.integral * Fix implementation of PieceWiseConstFunc.integral Just by adding a special condition for when we are only taking an integral "between" two edges of a PieceWiseConstFunc All tests now pass. Fixes #33. * Add PieceWiseConstFunc.integral tests for ValueError * Add testing bounds of integral * Raise ValueError in function implementation * Fix incorrect integrals in PieceWiseLinFunc (#38) Integrals of piece-wise linear functions were incorrect if the requested interval lies completely between two support points. This has been fixed, and a unit test exercising this behavior was added. Fixes #38 * Add Spike Order example and Tutorial section Adds an example computing spike order profile and the optimal spike train order. Also adds a section on spike train order to the tutorial. --- pyspike/spike_sync.py | 55 ++++++++++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 52 insertions(+), 3 deletions(-) (limited to 'pyspike/spike_sync.py') diff --git a/pyspike/spike_sync.py b/pyspike/spike_sync.py index 80f7805..95ef454 100644 --- a/pyspike/spike_sync.py +++ b/pyspike/spike_sync.py @@ -8,7 +8,7 @@ from __future__ import absolute_import import numpy as np from functools import partial import pyspike -from pyspike import DiscreteFunc +from pyspike import DiscreteFunc, SpikeTrain from pyspike.generic import _generic_profile_multi, _generic_distance_matrix @@ -45,9 +45,9 @@ def spike_sync_profile(*args, **kwargs): if len(args) == 1: return spike_sync_profile_multi(args[0], **kwargs) elif len(args) == 2: - return spike_sync_profile_bi(args[0], args[1]) + return spike_sync_profile_bi(args[0], args[1], **kwargs) else: - return spike_sync_profile_multi(args) + return spike_sync_profile_multi(args, **kwargs) ############################################################ @@ -290,3 +290,52 @@ def spike_sync_matrix(spike_trains, indices=None, interval=None, max_tau=None): dist_func = partial(spike_sync_bi, max_tau=max_tau) return _generic_distance_matrix(spike_trains, dist_func, indices, interval) + + +############################################################ +# filter_by_spike_sync +############################################################ +def filter_by_spike_sync(spike_trains, threshold, indices=None, max_tau=None, + return_removed_spikes=False): + """ Removes the spikes with a multi-variate spike_sync value below + threshold. + """ + N = len(spike_trains) + filtered_spike_trains = [] + removed_spike_trains = [] + + # cython implementation + try: + from .cython.cython_profiles import coincidence_single_profile_cython \ + as coincidence_impl + except ImportError: + if not(pyspike.disable_backend_warning): + print("Warning: coincidence_single_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 coincidence_single_python \ + as coincidence_impl + + if max_tau is None: + max_tau = 0.0 + + for i, st in enumerate(spike_trains): + coincidences = np.zeros_like(st) + for j in range(N): + if i == j: + continue + coincidences += coincidence_impl(st.spikes, spike_trains[j].spikes, + st.t_start, st.t_end, max_tau) + filtered_spikes = st[coincidences > threshold*(N-1)] + filtered_spike_trains.append(SpikeTrain(filtered_spikes, + [st.t_start, st.t_end])) + if return_removed_spikes: + removed_spikes = st[coincidences <= threshold*(N-1)] + removed_spike_trains.append(SpikeTrain(removed_spikes, + [st.t_start, st.t_end])) + if return_removed_spikes: + return [filtered_spike_trains, removed_spike_trains] + else: + return filtered_spike_trains -- cgit v1.2.3