diff options
Diffstat (limited to 'pyspike/generic.py')
| -rw-r--r-- | pyspike/generic.py | 18 |
1 files changed, 11 insertions, 7 deletions
diff --git a/pyspike/generic.py b/pyspike/generic.py index 41affcb..5ad06f1 100644 --- a/pyspike/generic.py +++ b/pyspike/generic.py @@ -7,6 +7,7 @@ Copyright 2015, Mario Mulansky <mario.mulansky@gmx.net> Distributed under the BSD License """ +from __future__ import division import numpy as np @@ -37,13 +38,15 @@ def _generic_profile_multi(spike_trains, pair_distance_func, indices=None): """ L1 = len(pairs1) if L1 > 1: - dist_prof1 = divide_and_conquer(pairs1[:L1/2], pairs1[L1/2:]) + dist_prof1 = divide_and_conquer(pairs1[:L1//2], + pairs1[L1//2:]) else: dist_prof1 = pair_distance_func(spike_trains[pairs1[0][0]], spike_trains[pairs1[0][1]]) L2 = len(pairs2) if L2 > 1: - dist_prof2 = divide_and_conquer(pairs2[:L2/2], pairs2[L2/2:]) + dist_prof2 = divide_and_conquer(pairs2[:L2//2], + pairs2[L2//2:]) else: dist_prof2 = pair_distance_func(spike_trains[pairs2[0][0]], spike_trains[pairs2[0][1]]) @@ -63,8 +66,8 @@ def _generic_profile_multi(spike_trains, pair_distance_func, indices=None): L = len(pairs) if L > 1: # recursive iteration through the list of pairs to get average profile - avrg_dist = divide_and_conquer(pairs[:len(pairs)/2], - pairs[len(pairs)/2:]) + avrg_dist = divide_and_conquer(pairs[:len(pairs)//2], + pairs[len(pairs)//2:]) else: avrg_dist = pair_distance_func(spike_trains[pairs[0][0]], spike_trains[pairs[0][1]]) @@ -135,12 +138,13 @@ def _generic_distance_matrix(spike_trains, dist_function, assert (indices < len(spike_trains)).all() and (indices >= 0).all(), \ "Invalid index list." # generate a list of possible index pairs - pairs = [(indices[i], j) for i in range(len(indices)) - for j in indices[i+1:]] + pairs = [(i, j) for i in range(len(indices)) + for j in range(i+1, len(indices))] distance_matrix = np.zeros((len(indices), len(indices))) for i, j in pairs: - d = dist_function(spike_trains[i], spike_trains[j], interval) + d = dist_function(spike_trains[indices[i]], spike_trains[indices[j]], + interval) distance_matrix[i, j] = d distance_matrix[j, i] = d return distance_matrix |