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path: root/pyspike/cython/cython_distances.pyx
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2018-09-20Spike Order support (#39)0.6.0Mario Mulansky
* 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.
2016-02-03fixed spike-sync bugMario Mulansky
fixed ugly bugs in code for computing multi-variate spike sync profile and multi-variate spike sync value.
2015-12-22changed edge correction for single spikesMario Mulansky
Spike trains with single spikes now only get auxiliary spikes at the edges for the SPIKE distance instead of real spikes before.
2015-12-18bugfix for edge correctionMario Mulansky
fixed bug within new edge correction (auxiliary spike was ignored in some cases) added regression test with 10000 random spike train sets
2015-12-14improved edge correction for spike distanceMario Mulansky
Improvement following Eeros suggestions to use auxiliary spike at the edges consistently with the corresponding corrected ISI intervals.
2015-05-11bugfix: spike_sync=1 for empty spike trainsMario Mulansky
2015-05-11treatment of empty spike trains in spike syncMario Mulansky
2015-05-11performance improvement for spike syncMario Mulansky
Additional cython implementation for overall spike sync values. It is not necessary to compute the profile anymore if only the spike sync value is required. 3x performance gain.
2015-05-08introduce backend for distance functionMario Mulansky
isi- and spike distances over complete intervals are now computed without obtaining the profile first. This gives more than x2 performance improvements.