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Diffstat (limited to 'pyspike/isi_distance.py')
| -rw-r--r-- | pyspike/isi_distance.py | 134 |
1 files changed, 134 insertions, 0 deletions
diff --git a/pyspike/isi_distance.py b/pyspike/isi_distance.py new file mode 100644 index 0000000..c2ef8e8 --- /dev/null +++ b/pyspike/isi_distance.py @@ -0,0 +1,134 @@ +""" + +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 pyspike import PieceWiseConstFunc +from pyspike.generic import _generic_profile_multi, _generic_distance_matrix + + +############################################################ +# isi_profile +############################################################ +def isi_profile(spikes1, spikes2): + """ Computes the isi-distance profile :math:`S_{isi}(t)` of the two given + spike trains. Retruns the profile as a PieceWiseConstFunc object. The S_isi + values are defined positive S_isi(t)>=0. 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 isi-distance profile :math:`S_{isi}(t)` + :rtype: :class:`pyspike.function.PieceWiseConstFunc` + + """ + # check for auxiliary spikes - first and last spikes should be identical + assert spikes1[0] == spikes2[0], \ + "Given spike trains seems not to have auxiliary spikes!" + assert spikes1[-1] == spikes2[-1], \ + "Given spike trains seems not to have auxiliary spikes!" + + # load cython implementation + try: + from cython.cython_distance import isi_distance_cython \ + as isi_distance_impl + except ImportError: + print("Warning: isi_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 cython.python_backend import isi_distance_python \ + as isi_distance_impl + + times, values = isi_distance_impl(spikes1, spikes2) + return PieceWiseConstFunc(times, values) + + +############################################################ +# isi_distance +############################################################ +def isi_distance(spikes1, spikes2, interval=None): + """ Computes the isi-distance I of the given spike trains. The + isi-distance is the integral over the isi distance profile + :math:`S_{isi}(t)`: + + .. math:: I = \int_{T_0}^{T_1} S_{isi}(t) dt. + + :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 isi-distance I. + :rtype: double + """ + return isi_profile(spikes1, spikes2).avrg(interval) + + +############################################################ +# isi_profile_multi +############################################################ +def isi_profile_multi(spike_trains, indices=None): + """ computes the multi-variate isi distance profile for a set of spike + trains. That is the average isi-distance of all pairs of spike-trains: + S_isi(t) = 2/((N(N-1)) sum_{<i,j>} S_{isi}^{i,j}, + 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 state: list or None + :returns: The averaged isi profile :math:`<S_{isi}>(t)` + :rtype: :class:`pyspike.function.PieceWiseConstFunc` + """ + average_dist, M = _generic_profile_multi(spike_trains, isi_profile, + indices) + average_dist.mul_scalar(1.0/M) # normalize + return average_dist + + +############################################################ +# isi_distance_multi +############################################################ +def isi_distance_multi(spike_trains, indices=None, interval=None): + """ computes the multi-variate isi-distance for a set of spike-trains. + That is the time average of the multi-variate spike profile: + I = \int_0^T 2/((N(N-1)) sum_{<i,j>} S_{isi}^{i,j}, + 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) + :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 isi distance :math:`I` + :rtype: double + """ + return isi_profile_multi(spike_trains, indices).avrg(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 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 average isi distances + :math:`I_{ij}` + :rtype: np.array + """ + return _generic_distance_matrix(spike_trains, isi_distance, + indices, interval) |