diff options
Diffstat (limited to 'pyspike/cython/cython_distances.pyx')
-rw-r--r-- | pyspike/cython/cython_distances.pyx | 134 |
1 files changed, 86 insertions, 48 deletions
diff --git a/pyspike/cython/cython_distances.pyx b/pyspike/cython/cython_distances.pyx index c017bf9..f50700f 100644 --- a/pyspike/cython/cython_distances.pyx +++ b/pyspike/cython/cython_distances.pyx @@ -55,20 +55,27 @@ def isi_distance_cython(double[:] s1, double[:] s2, N2 = len(s2) # first interspike interval - check if a spike exists at the start time + # and also account for spike trains with single spikes if s1[0] > t_start: - # edge correction - nu1 = fmax(s1[0]-t_start, s1[1]-s1[0]) + # edge correction for the first interspike interval: + # take the maximum of the distance from the beginning to the first + # spike and the interval between the first two spikes. + # if there is only one spike, take the its distance to the beginning + nu1 = fmax(s1[0]-t_start, s1[1]-s1[0]) if N1 > 1 else s1[0]-t_start index1 = -1 else: - nu1 = s1[1]-s1[0] + # if the first spike is exactly at the start, take the distance + # to the next spike. If this is the only spike, take the distance to + # the end. + nu1 = s1[1]-s1[0] if N1 > 1 else t_end-s1[0] index1 = 0 if s2[0] > t_start: - # edge correction - nu2 = fmax(s2[0]-t_start, s2[1]-s2[0]) + # edge correction as above + nu2 = fmax(s2[0]-t_start, s2[1]-s2[0]) if N2 > 1 else s2[0]-t_start index2 = -1 else: - nu2 = s2[1]-s2[0] + nu2 = s2[1]-s2[0] if N2 > 1 else t_end-s2[0] index2 = 0 last_t = t_start @@ -86,8 +93,12 @@ def isi_distance_cython(double[:] s1, double[:] s2, if index1 < N1-1: nu1 = s1[index1+1]-s1[index1] else: - # edge correction - nu1 = fmax(t_end-s1[index1], nu1) + # edge correction for the last ISI: + # take the max of the distance of the last + # spike to the end and the previous ISI. If there was only + # one spike, always take the distance to the end. + nu1 = fmax(t_end-s1[index1], nu1) if N1 > 1 \ + else t_end-s1[index1] elif (index2 < N2-1) and ((index1 == N1-1) or (s1[index1+1] > s2[index2+1])): index2 += 1 @@ -95,8 +106,9 @@ def isi_distance_cython(double[:] s1, double[:] s2, if index2 < N2-1: nu2 = s2[index2+1]-s2[index2] else: - # edge correction - nu2 = fmax(t_end-s2[index2], nu2) + # edge correction for the end as above + nu2 = fmax(t_end-s2[index2], nu2) if N2 > 1 \ + else t_end-s2[index2] else: # s1[index1+1] == s2[index2+1] index1 += 1 index2 += 1 @@ -104,13 +116,15 @@ def isi_distance_cython(double[:] s1, double[:] s2, if index1 < N1-1: nu1 = s1[index1+1]-s1[index1] else: - # edge correction - nu1 = fmax(t_end-s1[index1], nu1) + # edge correction for the end as above + nu1 = fmax(t_end-s1[index1], nu1) if N1 > 1 \ + else t_end-s1[index1] if index2 < N2-1: nu2 = s2[index2+1]-s2[index2] else: - # edge correction - nu2 = fmax(t_end-s2[index2], nu2) + # edge correction for the end as above + nu2 = fmax(t_end-s2[index2], nu2) if N2 > 1 \ + else t_end-s2[index2] # compute the corresponding isi-distance isi_value += curr_isi * (curr_t - last_t) curr_isi = fabs(nu1 - nu2) / fmax(nu1, nu2) @@ -178,44 +192,60 @@ def spike_distance_cython(double[:] t1, double[:] t2, cdef double t_p1, t_f1, t_p2, t_f2, dt_p1, dt_p2, dt_f1, dt_f2 cdef double isi1, isi2, s1, s2 cdef double y_start, y_end, t_last, t_current, spike_value + cdef double[:] t_aux1 = np.empty(2) + cdef double[:] t_aux2 = np.empty(2) spike_value = 0.0 N1 = len(t1) N2 = len(t2) + # we can assume at least one spikes per spike train + assert N1 > 0 + assert N2 > 0 + + with nogil: # release the interpreter to allow multithreading t_last = t_start - t_p1 = t_start - t_p2 = t_start + # auxiliary spikes for edge correction - consistent with first/last ISI + t_aux1[0] = fmin(t_start, 2*t1[0]-t1[1]) if N1 > 1 else t_start + t_aux1[1] = fmax(t_end, 2*t1[N1-1]-t1[N1-2]) if N1 > 1 else t_end + t_aux2[0] = fmin(t_start, 2*t2[0]-t2[1]) if N2 > 1 else t_start + t_aux2[1] = fmax(t_end, 2*t2[N2-1]+-t2[N2-2]) if N2 > 1 else t_end + # print "aux spikes %.15f, %.15f ; %.15f, %.15f" % (t_aux1[0], t_aux1[1], t_aux2[0], t_aux2[1]) + t_p1 = t_start if (t1[0] == t_start) else t_aux1[0] + t_p2 = t_start if (t2[0] == t_start) else t_aux2[0] if t1[0] > t_start: # dt_p1 = t2[0]-t_start t_f1 = t1[0] - dt_f1 = get_min_dist_cython(t_f1, t2, N2, 0, t_start, t_end) - isi1 = fmax(t_f1-t_start, t1[1]-t1[0]) + dt_f1 = get_min_dist_cython(t_f1, t2, N2, 0, t_aux2[0], t_aux2[1]) + isi1 = fmax(t_f1-t_start, t1[1]-t1[0]) if N1 > 1 else t_f1-t_start dt_p1 = dt_f1 - s1 = dt_p1*(t_f1-t_start)/isi1 + # s1 = dt_p1*(t_f1-t_start)/isi1 + s1 = dt_p1 index1 = -1 - else: - t_f1 = t1[1] - dt_f1 = get_min_dist_cython(t_f1, t2, N2, 0, t_start, t_end) - dt_p1 = 0.0 - isi1 = t1[1]-t1[0] + else: # t1[0] == t_start + t_f1 = t1[1] if N1 > 1 else t_end + dt_f1 = get_min_dist_cython(t_f1, t2, N2, 0, t_aux2[0], t_aux2[1]) + dt_p1 = get_min_dist_cython(t_p1, t2, N2, 0, t_aux2[0], t_aux2[1]) + isi1 = t_f1-t1[0] s1 = dt_p1 index1 = 0 if t2[0] > t_start: # dt_p1 = t2[0]-t_start t_f2 = t2[0] - dt_f2 = get_min_dist_cython(t_f2, t1, N1, 0, t_start, t_end) + dt_f2 = get_min_dist_cython(t_f2, t1, N1, 0, t_aux1[0], t_aux1[1]) dt_p2 = dt_f2 - isi2 = fmax(t_f2-t_start, t2[1]-t2[0]) - s2 = dt_p2*(t_f2-t_start)/isi2 + isi2 = fmax(t_f2-t_start, t2[1]-t2[0]) if N2 > 1 else t_f2-t_start + # s2 = dt_p2*(t_f2-t_start)/isi2 + s2 = dt_p2 index2 = -1 - else: - t_f2 = t2[1] - dt_f2 = get_min_dist_cython(t_f2, t1, N1, 0, t_start, t_end) - dt_p2 = 0.0 - isi2 = t2[1]-t2[0] + else: # t2[0] == t_start + t_f2 = t2[1] if N2 > 1 else t_end + dt_f2 = get_min_dist_cython(t_f2, t1, N1, 0, t_aux1[0], t_aux1[1]) + # dt_p2 = t_start-t_p1 # 0.0 + dt_p2 = get_min_dist_cython(t_p2, t1, N1, 0, t_aux1[0], t_aux1[1]) + isi2 = t_f2-t2[0] s2 = dt_p2 index2 = 0 @@ -237,7 +267,7 @@ def spike_distance_cython(double[:] t1, double[:] t2, if index1 < N1-1: t_f1 = t1[index1+1] else: - t_f1 = t_end + t_f1 = t_aux1[1] t_curr = t_p1 s2 = (dt_p2*(t_f2-t_p1) + dt_f2*(t_p1-t_p2)) / isi2 y_end = (s1*isi2 + s2*isi1)/isi_avrg_cython(isi1, isi2) @@ -249,14 +279,17 @@ def spike_distance_cython(double[:] t1, double[:] t2, # now the next interval start value if index1 < N1-1: dt_f1 = get_min_dist_cython(t_f1, t2, N2, index2, - t_start, t_end) + t_aux2[0], t_aux2[1]) isi1 = t_f1-t_p1 s1 = dt_p1 else: dt_f1 = dt_p1 - isi1 = fmax(t_end-t1[N1-1], t1[N1-1]-t1[N1-2]) + isi1 = fmax(t_end-t1[N1-1], t1[N1-1]-t1[N1-2]) if N1 > 1 \ + else t_end-t1[N1-1] # s1 needs adjustment due to change of isi1 - s1 = dt_p1*(t_end-t1[N1-1])/isi1 + # s1 = dt_p1*(t_end-t1[N1-1])/isi1 + # Eero's correction: no adjustment + s1 = dt_p1 # s2 is the same as above, thus we can compute y2 immediately y_start = (s1*isi2 + s2*isi1)/isi_avrg_cython(isi1, isi2) # alternative definition without second normalization @@ -272,7 +305,7 @@ def spike_distance_cython(double[:] t1, double[:] t2, if index2 < N2-1: t_f2 = t2[index2+1] else: - t_f2 = t_end + t_f2 = t_aux2[1] t_curr = t_p2 s1 = (dt_p1*(t_f1-t_p2) + dt_f1*(t_p2-t_p1)) / isi1 y_end = (s1*isi2 + s2*isi1) / isi_avrg_cython(isi1, isi2) @@ -284,14 +317,17 @@ def spike_distance_cython(double[:] t1, double[:] t2, # now the next interval start value if index2 < N2-1: dt_f2 = get_min_dist_cython(t_f2, t1, N1, index1, - t_start, t_end) + t_aux1[0], t_aux1[1]) isi2 = t_f2-t_p2 s2 = dt_p2 else: dt_f2 = dt_p2 - isi2 = fmax(t_end-t2[N2-1], t2[N2-1]-t2[N2-2]) + isi2 = fmax(t_end-t2[N2-1], t2[N2-1]-t2[N2-2]) if N2 > 1 \ + else t_end-t2[N2-1] # s2 needs adjustment due to change of isi2 - s2 = dt_p2*(t_end-t2[N2-1])/isi2 + # s2 = dt_p2*(t_end-t2[N2-1])/isi2 + # Eero's correction: no adjustment + s2 = dt_p2 # s1 is the same as above, thus we can compute y2 immediately y_start = (s1*isi2 + s2*isi1)/isi_avrg_cython(isi1, isi2) # alternative definition without second normalization @@ -311,27 +347,29 @@ def spike_distance_cython(double[:] t1, double[:] t2, if index1 < N1-1: t_f1 = t1[index1+1] dt_f1 = get_min_dist_cython(t_f1, t2, N2, index2, - t_start, t_end) + t_aux2[0], t_aux2[1]) isi1 = t_f1 - t_p1 else: - t_f1 = t_end + t_f1 = t_aux1[1] dt_f1 = dt_p1 - isi1 = fmax(t_end-t1[N1-1], t1[N1-1]-t1[N1-2]) + isi1 = fmax(t_end-t1[N1-1], t1[N1-1]-t1[N1-2]) if N1 > 1 \ + else t_end-t1[N1-1] if index2 < N2-1: t_f2 = t2[index2+1] dt_f2 = get_min_dist_cython(t_f2, t1, N1, index1, - t_start, t_end) + t_aux1[0], t_aux1[1]) isi2 = t_f2 - t_p2 else: - t_f2 = t_end + t_f2 = t_aux2[1] dt_f2 = dt_p2 - isi2 = fmax(t_end-t2[N2-1], t2[N2-1]-t2[N2-2]) + isi2 = fmax(t_end-t2[N2-1], t2[N2-1]-t2[N2-2]) if N2 > 1 \ + else t_end-t2[N2-1] index += 1 t_last = t_curr # isi1 = max(t_end-t1[N1-1], t1[N1-1]-t1[N1-2]) # isi2 = max(t_end-t2[N2-1], t2[N2-1]-t2[N2-2]) - s1 = dt_f1*(t_end-t1[N1-1])/isi1 - s2 = dt_f2*(t_end-t2[N2-1])/isi2 + s1 = dt_f1 # *(t_end-t1[N1-1])/isi1 + s2 = dt_f2 # *(t_end-t2[N2-1])/isi2 y_end = (s1*isi2 + s2*isi1) / isi_avrg_cython(isi1, isi2) # alternative definition without second normalization # y_end = (s1 + s2) / isi_avrg_cython(isi1, isi2) |