Spike Order support (#39)0.6.0

* 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.

1 files changed, 33 insertions, 0 deletions

diff --git a/pyspike/cython/cython_profiles.pyx b/pyspike/cython/cython_profiles.pyx
index 4a42cdb..aa24db4 100644
--- a/pyspike/cython/cython_profiles.pyx
+++ b/pyspike/cython/cython_profiles.pyx
@@ -450,3 +450,36 @@ def coincidence_profile_cython(double[:] spikes1, double[:] spikes2,
         c[1] = 1
 
     return st, c, mp
+
+
+############################################################
+# coincidence_single_profile_cython
+############################################################
+def coincidence_single_profile_cython(double[:] spikes1, double[:] spikes2,
+                                      double t_start, double t_end, double max_tau):
+
+    cdef int N1 = len(spikes1)
+    cdef int N2 = len(spikes2)
+    cdef int j = -1
+    cdef double[:] c = np.zeros(N1)   # coincidences
+    cdef double interval = t_end - t_start
+    cdef double tau
+    for i in xrange(N1):
+        while j < N2-1 and spikes2[j+1] < spikes1[i]:
+            # move forward until spikes2[j] is the last spike before spikes1[i]
+            # note that if spikes2[j] is after spikes1[i] we dont do anything
+            j += 1
+        tau = get_tau(spikes1, spikes2, i, j, interval, max_tau)
+        if j > -1 and fabs(spikes1[i]-spikes2[j]) < tau:
+            # current spike in st1 is coincident
+            c[i] = 1
+        if j < N2-1 and (j < 0 or spikes2[j] < spikes1[i]):
+            # in case spikes2[j] is before spikes1[i] it has to be the one 
+            # right before (see above), hence we move one forward and also 
+            # check the next spike
+            j += 1
+            tau = get_tau(spikes1, spikes2, i, j, interval, max_tau)
+            if fabs(spikes2[j]-spikes1[i]) < tau:
+                # current spike in st1 is coincident
+                c[i] = 1
+    return c