diff options
Diffstat (limited to 'pyspike/isi_distance.py')
| -rw-r--r-- | pyspike/isi_distance.py | 149 |
1 files changed, 110 insertions, 39 deletions
diff --git a/pyspike/isi_distance.py b/pyspike/isi_distance.py index 0ae7393..e91dce2 100644 --- a/pyspike/isi_distance.py +++ b/pyspike/isi_distance.py @@ -13,11 +13,48 @@ from pyspike.generic import _generic_profile_multi, _generic_distance_multi, \ ############################################################ # isi_profile ############################################################ -def isi_profile(spike_train1, spike_train2): - """ Computes the isi-distance profile :math:`I(t)` of the two given - spike trains. Retruns the profile as a PieceWiseConstFunc object. The +def isi_profile(*args, **kwargs): + """ Computes the isi-distance profile :math:`I(t)` of the given + spike trains. Returns the profile as a PieceWiseConstFunc object. The ISI-values are defined positive :math:`I(t)>=0`. + Valid call structures:: + + isi_profile(st1, st2) # returns the bi-variate profile + isi_profile(st1, st2, st3) # multi-variate profile of 3 spike trains + + spike_trains = [st1, st2, st3, st4] # list of spike trains + isi_profile(spike_trains) # profile of the list of spike trains + isi_profile(spike_trains, indices=[0, 1]) # use only the spike trains + # given by the indices + + The multivariate ISI distance profile for a set of spike trains is defined + as the average ISI-profile of all pairs of spike-trains: + + .. math:: <I(t)> = \\frac{2}{N(N-1)} \\sum_{<i,j>} I^{i,j}, + + where the sum goes over all pairs <i,j> + + + :returns: The isi-distance profile :math:`I(t)` + :rtype: :class:`.PieceWiseConstFunc` + """ + if len(args) == 1: + return isi_profile_multi(args[0], **kwargs) + elif len(args) == 2: + return isi_profile_bi(args[0], args[1]) + else: + return isi_profile_multi(args) + + +############################################################ +# isi_profile_bi +############################################################ +def isi_profile_bi(spike_train1, spike_train2): + """ Specific function to compute a bivariate ISI-profile. This is a + deprecated function and should not be called directly. Use + :func:`.isi_profile` to compute ISI-profiles. + :param spike_train1: First spike train. :type spike_train1: :class:`.SpikeTrain` :param spike_train2: Second spike train. @@ -52,15 +89,76 @@ Falling back to slow python backend.") ############################################################ +# isi_profile_multi +############################################################ +def isi_profile_multi(spike_trains, indices=None): + """ Specific function to compute the multivariate ISI-profile for a set of + spike trains. This is a deprecated function and should not be called + directly. Use :func:`.isi_profile` to compute ISI-profiles. + + + :param spike_trains: list of :class:`.SpikeTrain` + :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:`<I(t)>` + :rtype: :class:`.PieceWiseConstFunc` + """ + average_dist, M = _generic_profile_multi(spike_trains, isi_profile_bi, + indices) + average_dist.mul_scalar(1.0/M) # normalize + return average_dist + + +############################################################ # isi_distance ############################################################ -def isi_distance(spike_train1, spike_train2, interval=None): +def isi_distance(*args, **kwargs): """ Computes the ISI-distance :math:`D_I` of the given spike trains. The isi-distance is the integral over the isi distance profile :math:`I(t)`: .. math:: D_I = \\int_{T_0}^{T_1} I(t) dt. + In the multivariate case it is the integral over the multivariate + ISI-profile, i.e. the average profile over all spike train pairs: + + .. math:: D_I = \\int_0^T \\frac{2}{N(N-1)} \\sum_{<i,j>} I^{i,j}, + + where the sum goes over all pairs <i,j> + + + + Valid call structures:: + + isi_distance(st1, st2) # returns the bi-variate distance + isi_distance(st1, st2, st3) # multi-variate distance of 3 spike trains + + spike_trains = [st1, st2, st3, st4] # list of spike trains + isi_distance(spike_trains) # distance of the list of spike trains + isi_distance(spike_trains, indices=[0, 1]) # use only the spike trains + # given by the indices + + :returns: The isi-distance :math:`D_I`. + :rtype: double + """ + + if len(args) == 1: + return isi_distance_multi(args[0], **kwargs) + elif len(args) == 2: + return isi_distance_bi(args[0], args[1], **kwargs) + else: + return isi_distance_multi(args, **kwargs) + + +############################################################ +# _isi_distance_bi +############################################################ +def isi_distance_bi(spike_train1, spike_train2, interval=None): + """ Specific function to compute the bivariate ISI-distance. + This is a deprecated function and should not be called directly. Use + :func:`.isi_distance` to compute ISI-distances. + :param spike_train1: First spike train. :type spike_train1: :class:`.SpikeTrain` :param spike_train2: Second spike train. @@ -84,46 +182,19 @@ def isi_distance(spike_train1, spike_train2, interval=None): spike_train1.t_start, spike_train1.t_end) except ImportError: # Cython backend not available: fall back to profile averaging - return isi_profile(spike_train1, spike_train2).avrg(interval) + return isi_profile_bi(spike_train1, spike_train2).avrg(interval) else: # some specific interval is provided: use profile - return isi_profile(spike_train1, spike_train2).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: - - .. math:: <I(t)> = \\frac{2}{N(N-1)} \\sum_{<i,j>} I^{i,j}, - - where the sum goes over all pairs <i,j> - - :param spike_trains: list of :class:`.SpikeTrain` - :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:`<I(t)>` - :rtype: :class:`.PieceWiseConstFunc` - """ - average_dist, M = _generic_profile_multi(spike_trains, isi_profile, - indices) - average_dist.mul_scalar(1.0/M) # normalize - return average_dist + return isi_profile_bi(spike_train1, spike_train2).avrg(interval) ############################################################ # 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: - - .. math:: D_I = \\int_0^T \\frac{2}{N(N-1)} \\sum_{<i,j>} I^{i,j}, - - where the sum goes over all pairs <i,j> + """ Specific function to compute the multivariate ISI-distance. + This is a deprecfated function and should not be called directly. Use + :func:`.isi_distance` to compute ISI-distances. :param spike_trains: list of :class:`.SpikeTrain` :param indices: list of indices defining which spike trains to use, @@ -134,7 +205,7 @@ def isi_distance_multi(spike_trains, indices=None, interval=None): :returns: The time-averaged multivariate ISI distance :math:`D_I` :rtype: double """ - return _generic_distance_multi(spike_trains, isi_distance, indices, + return _generic_distance_multi(spike_trains, isi_distance_bi, indices, interval) @@ -155,5 +226,5 @@ def isi_distance_matrix(spike_trains, indices=None, interval=None): :math:`D_{I}^{ij}` :rtype: np.array """ - return _generic_distance_matrix(spike_trains, isi_distance, - indices, interval) + return _generic_distance_matrix(spike_trains, isi_distance_bi, + indices=indices, interval=interval) |