Merge branch 'master' into new_directionality

Conflicts:
	pyspike/__init__.py
	pyspike/cython/cython_directionality.pyx
	pyspike/cython/directionality_python_backend.py
	pyspike/spike_directionality.py
	setup.py

1 files changed, 21 insertions, 18 deletions

diff --git a/test/test_regression/test_regression_15.py b/test/test_regression/test_regression_15.py
index 1ce1290..54adf23 100644
--- a/test/test_regression/test_regression_15.py
+++ b/test/test_regression/test_regression_15.py
@@ -8,68 +8,71 @@ 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
 
 import pyspike as spk
 
+import os
+TEST_PATH = os.path.dirname(os.path.realpath(__file__))
+TEST_DATA = os.path.join(TEST_PATH, "..", "SPIKE_Sync_Test.txt")
+
 
 def test_regression_15_isi():
     # load spike trains
-    spike_trains = spk.load_spike_trains_from_txt("test/SPIKE_Sync_Test.txt",
-                                                  edges=[0, 4000])
+    spike_trains = spk.load_spike_trains_from_txt(TEST_DATA, edges=[0, 4000])
 
     N = len(spike_trains)
 
     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():
     # load spike trains
-    spike_trains = spk.load_spike_trains_from_txt("test/SPIKE_Sync_Test.txt",
-                                                  edges=[0, 4000])
+    spike_trains = spk.load_spike_trains_from_txt(TEST_DATA, edges=[0, 4000])
 
     N = len(spike_trains)
 
     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():
     # load spike trains
-    spike_trains = spk.load_spike_trains_from_txt("test/SPIKE_Sync_Test.txt",
-                                                  edges=[0, 4000])
+    spike_trains = spk.load_spike_trains_from_txt(TEST_DATA, edges=[0, 4000])
 
     N = len(spike_trains)
 
     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__":