diff options
Diffstat (limited to 'pyspike/cython/python_backend.py')
| -rw-r--r-- | pyspike/cython/python_backend.py | 108 |
1 files changed, 65 insertions, 43 deletions
diff --git a/pyspike/cython/python_backend.py b/pyspike/cython/python_backend.py index 5c4c75d..11fbe62 100644 --- a/pyspike/cython/python_backend.py +++ b/pyspike/cython/python_backend.py @@ -28,17 +28,17 @@ def isi_distance_python(s1, s2, t_start, t_end): isi_values = np.empty(len(spike_events) - 1) if s1[0] > t_start: # edge correction - nu1 = max(s1[0] - t_start, s1[1] - s1[0]) + nu1 = max(s1[0] - t_start, s1[1] - s1[0]) if N1 > 1 else s1[0]-t_start index1 = -1 else: - nu1 = s1[1] - s1[0] + nu1 = s1[1] - s1[0] if N1 > 1 else t_end-s1[0] index1 = 0 if s2[0] > t_start: # edge correction - nu2 = max(s2[0] - t_start, s2[1] - s2[0]) + nu2 = max(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 isi_values[0] = abs(nu1 - nu2) / max(nu1, nu2) @@ -52,7 +52,8 @@ def isi_distance_python(s1, s2, t_start, t_end): nu1 = s1[index1+1]-s1[index1] else: # edge correction - nu1 = max(t_end-s1[N1-1], s1[N1-1]-s1[N1-2]) + nu1 = max(t_end-s1[N1-1], s1[N1-1]-s1[N1-2]) if N1 > 1 \ + else t_end-s1[N1-1] elif (index2 < N2-1) and (index1 == N1-1 or s1[index1+1] > s2[index2+1]): @@ -62,7 +63,8 @@ def isi_distance_python(s1, s2, t_start, t_end): nu2 = s2[index2+1]-s2[index2] else: # edge correction - nu2 = max(t_end-s2[N2-1], s2[N2-1]-s2[N2-2]) + nu2 = max(t_end-s2[N2-1], s2[N2-1]-s2[N2-2]) if N2 > 1 \ + else t_end-s2[N2-1] else: # s1[index1 + 1] == s2[index2 + 1] index1 += 1 @@ -72,12 +74,14 @@ def isi_distance_python(s1, s2, t_start, t_end): nu1 = s1[index1+1]-s1[index1] else: # edge correction - nu1 = max(t_end-s1[N1-1], s1[N1-1]-s1[N1-2]) + nu1 = max(t_end-s1[N1-1], s1[N1-1]-s1[N1-2]) if N1 > 1 \ + else t_end-s1[N1-1] if index2 < N2-1: nu2 = s2[index2+1]-s2[index2] else: # edge correction - nu2 = max(t_end-s2[N2-1], s2[N2-1]-s2[N2-2]) + nu2 = max(t_end-s2[N2-1], s2[N2-1]-s2[N2-2]) if N2 > 1 \ + else t_end-s2[N2-1] # compute the corresponding isi-distance isi_values[index] = abs(nu1 - nu2) / \ max(nu1, nu2) @@ -144,36 +148,48 @@ def spike_distance_python(spikes1, spikes2, t_start, t_end): y_starts = np.empty(len(spike_events)-1) y_ends = np.empty(len(spike_events)-1) + t_aux1 = np.zeros(2) + t_aux2 = np.zeros(2) + t_aux1[0] = min(t_start, t1[0]-(t1[1]-t1[0])) if N1 > 1 else t_start + t_aux1[1] = max(t_end, t1[N1-1]+(t1[N1-1]-t1[N1-2])) if N1 > 1 else t_end + t_aux2[0] = min(t_start, t2[0]-(t2[1]-t2[0])) if N2 > 1 else t_start + t_aux2[1] = max(t_end, t2[N2-1]+(t2[N2-1]-t2[N2-2])) if N2 > 1 else t_end + 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] + + # print "t_aux1", t_aux1, ", t_aux2:", t_aux2 + spike_events[0] = t_start - t_p1 = t_start - t_p2 = t_start if t1[0] > t_start: t_f1 = t1[0] - dt_f1 = get_min_dist(t_f1, t2, 0, t_start, t_end) + dt_f1 = get_min_dist(t_f1, t2, 0, t_aux2[0], t_aux2[1]) dt_p1 = dt_f1 - isi1 = max(t_f1-t_start, t1[1]-t1[0]) - s1 = dt_p1*(t_f1-t_start)/isi1 + isi1 = max(t_f1-t_start, t1[1]-t1[0]) if N1 > 1 else t_f1-t_start + # s1 = dt_p1*(t_f1-t_start)/isi1 + s1 = dt_p1 index1 = -1 else: - dt_p1 = 0.0 - t_f1 = t1[1] - dt_f1 = get_min_dist(t_f1, t2, 0, t_start, t_end) - isi1 = t1[1]-t1[0] + # dt_p1 = t_start-t_p2 + t_f1 = t1[1] if N1 > 1 else t_end + dt_p1 = get_min_dist(t_p1, t2, 0, t_aux2[0], t_aux2[1]) + dt_f1 = get_min_dist(t_f1, t2, 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(t_f2, t1, 0, t_start, t_end) + dt_f2 = get_min_dist(t_f2, t1, 0, t_aux1[0], t_aux1[1]) dt_p2 = dt_f2 - isi2 = max(t_f2-t_start, t2[1]-t2[0]) - s2 = dt_p2*(t_f2-t_start)/isi2 + isi2 = max(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: - dt_p2 = 0.0 - t_f2 = t2[1] - dt_f2 = get_min_dist(t_f2, t1, 0, t_start, t_end) - isi2 = t2[1]-t2[0] + t_f2 = t2[1] if N2 > 1 else t_end + dt_p2 = get_min_dist(t_p2, t1, 0, t_aux1[0], t_aux1[1]) + dt_f2 = get_min_dist(t_f2, t1, 0, t_aux1[0], t_aux1[1]) + isi2 = t_f2-t2[0] s2 = dt_p2 index2 = 0 @@ -193,20 +209,23 @@ def spike_distance_python(spikes1, spikes2, t_start, t_end): if index1 < N1-1: t_f1 = t1[index1+1] else: - t_f1 = t_end + t_f1 = t_aux1[1] spike_events[index] = t_p1 s2 = (dt_p2*(t_f2-t_p1) + dt_f2*(t_p1-t_p2)) / isi2 y_ends[index-1] = (s1*isi2 + s2*isi1) / (0.5*(isi1+isi2)**2) # now the next interval start value if index1 < N1-1: - dt_f1 = get_min_dist(t_f1, t2, index2, t_start, t_end) + dt_f1 = get_min_dist(t_f1, t2, index2, t_aux2[0], t_aux2[1]) isi1 = t_f1-t_p1 s1 = dt_p1 else: dt_f1 = dt_p1 - isi1 = max(t_end-t1[N1-1], t1[N1-1]-t1[N1-2]) + isi1 = max(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_starts[index] = (s1*isi2 + s2*isi1) / (0.5*(isi1+isi2)**2) elif (index2 < N2-1) and (t_f1 > t_f2 or index1 == N1-1): @@ -220,20 +239,23 @@ def spike_distance_python(spikes1, spikes2, t_start, t_end): if index2 < N2-1: t_f2 = t2[index2+1] else: - t_f2 = t_end + t_f2 = t_aux2[1] spike_events[index] = t_p2 s1 = (dt_p1*(t_f1-t_p2) + dt_f1*(t_p2-t_p1)) / isi1 y_ends[index-1] = (s1*isi2 + s2*isi1) / (0.5*(isi1+isi2)**2) # now the next interval start value if index2 < N2-1: - dt_f2 = get_min_dist(t_f2, t1, index1, t_start, t_end) + dt_f2 = get_min_dist(t_f2, t1, index1, t_aux1[0], t_aux1[1]) isi2 = t_f2-t_p2 s2 = dt_p2 else: dt_f2 = dt_p2 - isi2 = max(t_end-t2[N2-1], t2[N2-1]-t2[N2-2]) + isi2 = max(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 adjustment: no correction + s2 = dt_p2 # s2 is the same as above, thus we can compute y2 immediately y_starts[index] = (s1*isi2 + s2*isi1) / (0.5*(isi1+isi2)**2) else: # t_f1 == t_f2 - generate only one event @@ -248,31 +270,31 @@ def spike_distance_python(spikes1, spikes2, t_start, t_end): y_starts[index] = 0.0 if index1 < N1-1: t_f1 = t1[index1+1] - dt_f1 = get_min_dist(t_f1, t2, index2, t_start, t_end) + dt_f1 = get_min_dist(t_f1, t2, index2, 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 = max(t_end-t1[N1-1], t1[N1-1]-t1[N1-2]) + isi1 = max(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(t_f2, t1, index1, t_start, t_end) + dt_f2 = get_min_dist(t_f2, t1, index1, 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 = max(t_end-t2[N2-1], t2[N2-1]-t2[N2-2]) + isi2 = max(t_end-t2[N2-1], t2[N2-1]-t2[N2-2]) if N2 > 1 \ + else t_end-t2[N2-1] index += 1 + # the last event is the interval end if spike_events[index-1] == t_end: index -= 1 else: spike_events[index] = t_end - # the ending value of the last interval - 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_ends[index-1] = (s1*isi2 + s2*isi1) / (0.5*(isi1+isi2)**2) # use only the data added above |