py3: division

Signed-off-by: Igor Gnatenko <i.gnatenko.brain@gmail.com>

1 files changed, 14 insertions, 12 deletions

diff --git a/test/test_regression/test_regression_15.py b/test/test_regression/test_regression_15.py
index 1ce1290..42a39ea 100644
--- a/test/test_regression/test_regression_15.py
+++ b/test/test_regression/test_regression_15.py
@@ -8,6 +8,8 @@ Distributed under the BSD License
 
 """
 
+from __future__ import division
+
 import numpy as np
 from numpy.testing import assert_equal, assert_almost_equal, \
     assert_array_almost_equal
@@ -25,13 +27,13 @@ def test_regression_15_isi():
     dist_mat = spk.isi_distance_matrix(spike_trains)
     assert_equal(dist_mat.shape, (N, N))
 
-    ind = np.arange(N/2)
+    ind = np.arange(N//2)
     dist_mat = spk.isi_distance_matrix(spike_trains, ind)
-    assert_equal(dist_mat.shape, (N/2, N/2))
+    assert_equal(dist_mat.shape, (N//2, N//2))
 
-    ind = np.arange(N/2, N)
+    ind = np.arange(N//2, N)
     dist_mat = spk.isi_distance_matrix(spike_trains, ind)
-    assert_equal(dist_mat.shape, (N/2, N/2))
+    assert_equal(dist_mat.shape, (N//2, N//2))
 
 
 def test_regression_15_spike():
@@ -44,13 +46,13 @@ def test_regression_15_spike():
     dist_mat = spk.spike_distance_matrix(spike_trains)
     assert_equal(dist_mat.shape, (N, N))
 
-    ind = np.arange(N/2)
+    ind = np.arange(N//2)
     dist_mat = spk.spike_distance_matrix(spike_trains, ind)
-    assert_equal(dist_mat.shape, (N/2, N/2))
+    assert_equal(dist_mat.shape, (N//2, N//2))
 
-    ind = np.arange(N/2, N)
+    ind = np.arange(N//2, N)
     dist_mat = spk.spike_distance_matrix(spike_trains, ind)
-    assert_equal(dist_mat.shape, (N/2, N/2))
+    assert_equal(dist_mat.shape, (N//2, N//2))
 
 
 def test_regression_15_sync():
@@ -63,13 +65,13 @@ def test_regression_15_sync():
     dist_mat = spk.spike_sync_matrix(spike_trains)
     assert_equal(dist_mat.shape, (N, N))
 
-    ind = np.arange(N/2)
+    ind = np.arange(N//2)
     dist_mat = spk.spike_sync_matrix(spike_trains, ind)
-    assert_equal(dist_mat.shape, (N/2, N/2))
+    assert_equal(dist_mat.shape, (N//2, N//2))
 
-    ind = np.arange(N/2, N)
+    ind = np.arange(N//2, N)
     dist_mat = spk.spike_sync_matrix(spike_trains, ind)
-    assert_equal(dist_mat.shape, (N/2, N/2))
+    assert_equal(dist_mat.shape, (N//2, N//2))
 
 
 if __name__ == "__main__":