summaryrefslogtreecommitdiff
path: root/pyspike/spike_sync.py
diff options
context:
space:
mode:
Diffstat (limited to 'pyspike/spike_sync.py')
-rw-r--r--pyspike/spike_sync.py152
1 files changed, 111 insertions, 41 deletions
diff --git a/pyspike/spike_sync.py b/pyspike/spike_sync.py
index 3dc29ff..617dd86 100644
--- a/pyspike/spike_sync.py
+++ b/pyspike/spike_sync.py
@@ -15,11 +15,48 @@ from pyspike.generic import _generic_profile_multi, _generic_distance_matrix
############################################################
# spike_sync_profile
############################################################
-def spike_sync_profile(spike_train1, spike_train2, max_tau=None):
- """ 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.
+def spike_sync_profile(*args, **kwargs):
+ """ Computes the spike-synchronization profile S_sync(t) of the given
+ spike trains. Returns the profile as a DiscreteFunction object. In the
+ bivariate case, he S_sync values are either 1 or 0, indicating the presence
+ or absence of a coincidence. For multi-variate cases, each spike in the set
+ of spike trains, the 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).
+
+ Valid call structures::
+
+ spike_sync_profile(st1, st2) # returns the bi-variate profile
+ spike_sync_profile(st1, st2, st3) # multi-variate profile of 3 sts
+
+ sts = [st1, st2, st3, st4] # list of spike trains
+ spike_sync_profile(sts) # profile of the list of spike trains
+ spike_sync_profile(sts, indices=[0, 1]) # use only the spike trains
+ # given by the indices
+
+ In the multivariate case, the profile is defined as the number of
+ coincidences for each spike in the set of spike trains 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).
+
+ :returns: The spike-sync profile :math:`S_{sync}(t)`.
+ :rtype: :class:`pyspike.function.DiscreteFunction`
+ """
+ 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])
+ else:
+ return spike_sync_profile_multi(args)
+
+
+############################################################
+# spike_sync_profile_bi
+############################################################
+def spike_sync_profile_bi(spike_train1, spike_train2, max_tau=None):
+ """ Specific function to compute a bivariate SPIKE-Sync-profile. This is a
+ deprecated function and should not be called directly. Use
+ :func:`.spike_sync_profile` to compute SPIKE-Sync-profiles.
:param spike_train1: First spike train.
:type spike_train1: :class:`pyspike.SpikeTrain`
@@ -27,7 +64,7 @@ def spike_sync_profile(spike_train1, spike_train2, max_tau=None):
:type spike_train2: :class:`pyspike.SpikeTrain`
:param max_tau: Maximum coincidence window size. If 0 or `None`, the
coincidence window has no upper bound.
- :returns: The spike-distance profile :math:`S_{sync}(t)`.
+ :returns: The spike-sync profile :math:`S_{sync}(t)`.
:rtype: :class:`pyspike.function.DiscreteFunction`
"""
@@ -62,6 +99,31 @@ Falling back to slow python backend.")
############################################################
+# spike_sync_profile_multi
+############################################################
+def spike_sync_profile_multi(spike_trains, indices=None, max_tau=None):
+ """ Specific function to compute a multivariate SPIKE-Sync-profile.
+ This is a deprecated function and should not be called directly. Use
+ :func:`.spike_sync_profile` to compute SPIKE-Sync-profiles.
+
+ :param spike_trains: list of :class:`pyspike.SpikeTrain`
+ :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 max_tau: Maximum coincidence window size. If 0 or `None`, the
+ coincidence window has no upper bound.
+ :returns: The multi-variate spike sync profile :math:`<S_{sync}>(t)`
+ :rtype: :class:`pyspike.function.DiscreteFunction`
+
+ """
+ prof_func = partial(spike_sync_profile_bi, max_tau=max_tau)
+ average_prof, M = _generic_profile_multi(spike_trains, prof_func,
+ indices)
+ # average_dist.mul_scalar(1.0/M) # no normalization here!
+ return average_prof
+
+
+############################################################
# _spike_sync_values
############################################################
def _spike_sync_values(spike_train1, spike_train2, interval, max_tau):
@@ -87,24 +149,58 @@ def _spike_sync_values(spike_train1, spike_train2, interval, max_tau):
return c, mp
except ImportError:
# Cython backend not available: fall back to profile averaging
- return spike_sync_profile(spike_train1, spike_train2,
- max_tau).integral(interval)
+ return spike_sync_profile_bi(spike_train1, spike_train2,
+ max_tau).integral(interval)
else:
# some specific interval is provided: use profile
- return spike_sync_profile(spike_train1, spike_train2,
- max_tau).integral(interval)
+ return spike_sync_profile_bi(spike_train1, spike_train2,
+ max_tau).integral(interval)
############################################################
# spike_sync
############################################################
-def spike_sync(spike_train1, spike_train2, interval=None, max_tau=None):
+def spike_sync(*args, **kwargs):
""" 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.
+
+ Valid call structures::
+
+ spike_sync(st1, st2) # returns the bi-variate spike synchronization
+ spike_sync(st1, st2, st3) # multi-variate result for 3 spike trains
+
+ spike_trains = [st1, st2, st3, st4] # list of spike trains
+ spike_sync(spike_trains) # spike-sync of the list of spike trains
+ spike_sync(spike_trains, indices=[0, 1]) # use only the spike trains
+ # given by the indices
+
+ The multivariate SPIKE-Sync is again defined as the overall ratio of all
+ coincidence values divided by the total number of spikes.
+
+ :returns: The spike synchronization value.
+ :rtype: `double`
+ """
+
+ if len(args) == 1:
+ return spike_sync_multi(args[0], **kwargs)
+ elif len(args) == 2:
+ return spike_sync_bi(args[0], args[1], **kwargs)
+ else:
+ return spike_sync_multi(args, **kwargs)
+
+
+############################################################
+# spike_sync_bi
+############################################################
+def spike_sync_bi(spike_train1, spike_train2, interval=None, max_tau=None):
+ """ Specific function to compute a bivariate SPIKE-Sync value.
+ This is a deprecated function and should not be called directly. Use
+ :func:`.spike_sync` to compute SPIKE-Sync values.
+
:param spike_train1: First spike train.
:type spike_train1: :class:`pyspike.SpikeTrain`
:param spike_train2: Second spike train.
@@ -123,38 +219,12 @@ def spike_sync(spike_train1, spike_train2, interval=None, max_tau=None):
############################################################
-# spike_sync_profile_multi
-############################################################
-def spike_sync_profile_multi(spike_trains, indices=None, max_tau=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 :class:`pyspike.SpikeTrain`
- :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 max_tau: Maximum coincidence window size. If 0 or `None`, the
- coincidence window has no upper bound.
- :returns: The multi-variate spike sync profile :math:`<S_{sync}>(t)`
- :rtype: :class:`pyspike.function.DiscreteFunction`
-
- """
- prof_func = partial(spike_sync_profile, max_tau=max_tau)
- average_prof, M = _generic_profile_multi(spike_trains, prof_func,
- indices)
- # average_dist.mul_scalar(1.0/M) # no normalization here!
- return average_prof
-
-
-############################################################
# spike_sync_multi
############################################################
def spike_sync_multi(spike_trains, indices=None, interval=None, max_tau=None):
- """ Computes the multi-variate spike synchronization value for a set of
- spike trains.
+ """ Specific function to compute a multivariate SPIKE-Sync value.
+ This is a deprecated function and should not be called directly. Use
+ :func:`.spike_sync` to compute SPIKE-Sync values.
:param spike_trains: list of :class:`pyspike.SpikeTrain`
:param indices: list of indices defining which spike trains to use,
@@ -211,6 +281,6 @@ def spike_sync_matrix(spike_trains, indices=None, interval=None, max_tau=None):
:rtype: np.array
"""
- dist_func = partial(spike_sync, max_tau=max_tau)
+ dist_func = partial(spike_sync_bi, max_tau=max_tau)
return _generic_distance_matrix(spike_trains, dist_func,
indices, interval)