Merge branch 'develop' of github.com:mariomulansky/PySpike into develop

3 files changed, 36 insertions, 31 deletions

diff --git a/test/test_distance.py b/test/test_distance.py
index 626b438..8cf81e2 100644
--- a/test/test_distance.py
+++ b/test/test_distance.py
@@ -17,6 +17,8 @@ from numpy.testing import assert_equal, assert_almost_equal, \
 import pyspike as spk
 from pyspike import SpikeTrain
 
+import os
+TEST_PATH = os.path.dirname(os.path.realpath(__file__))
 
 def test_isi():
     # generate two spike trains:
@@ -294,8 +296,8 @@ def test_multi_spike_sync():
                         expected, decimal=15)
 
     # multivariate regression test
-    spike_trains = spk.load_spike_trains_from_txt("test/SPIKE_Sync_Test.txt",
-                                                  edges=[0, 4000])
+    spike_trains = spk.load_spike_trains_from_txt(
+        os.path.join(TEST_PATH, "SPIKE_Sync_Test.txt"), edges=[0, 4000])
     # extract all spike times
     spike_times = np.array([])
     for st in spike_trains:
@@ -328,10 +330,10 @@ def check_dist_matrix(dist_func, dist_matrix_func):
 
     f_matrix = dist_matrix_func(spike_trains)
     # check zero diagonal
-    for i in xrange(4):
+    for i in range(4):
         assert_equal(0.0, f_matrix[i, i])
-    for i in xrange(4):
-        for j in xrange(i+1, 4):
+    for i in range(4):
+        for j in range(i+1, 4):
             assert_equal(f_matrix[i, j], f_matrix[j, i])
     assert_equal(f12, f_matrix[1, 0])
     assert_equal(f13, f_matrix[2, 0])
@@ -371,8 +373,8 @@ def test_regression_spiky():
 
     # multivariate check
 
-    spike_trains = spk.load_spike_trains_from_txt("test/PySpike_testdata.txt",
-                                                  (0.0, 4000.0))
+    spike_trains = spk.load_spike_trains_from_txt(
+        os.path.join(TEST_PATH, "PySpike_testdata.txt"), (0.0, 4000.0))
     isi_dist = spk.isi_distance_multi(spike_trains)
     # get the full precision from SPIKY
     assert_almost_equal(isi_dist, 0.17051816816999129656, decimal=15)
@@ -409,8 +411,8 @@ def test_regression_spiky():
 
 
 def test_multi_variate_subsets():
-    spike_trains = spk.load_spike_trains_from_txt("test/PySpike_testdata.txt",
-                                                  (0.0, 4000.0))
+    spike_trains = spk.load_spike_trains_from_txt(
+        os.path.join(TEST_PATH, "PySpike_testdata.txt"), (0.0, 4000.0))
     sub_set = [1, 3, 5, 7]
     spike_trains_sub_set = [spike_trains[i] for i in sub_set]
 
diff --git a/test/test_regression/test_regression_15.py b/test/test_regression/test_regression_15.py
index 1ce1290..dcacae2 100644
--- a/test/test_regression/test_regression_15.py
+++ b/test/test_regression/test_regression_15.py
@@ -8,68 +8,70 @@ 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__":
diff --git a/test/test_spikes.py b/test/test_spikes.py
index d4eb131..609a819 100644
--- a/test/test_spikes.py
+++ b/test/test_spikes.py
@@ -13,10 +13,12 @@ from numpy.testing import assert_equal
 
 import pyspike as spk
 
+import os
+TEST_PATH = os.path.dirname(os.path.realpath(__file__))
+TEST_DATA = os.path.join(TEST_PATH, "PySpike_testdata.txt")
 
 def test_load_from_txt():
-    spike_trains = spk.load_spike_trains_from_txt("test/PySpike_testdata.txt",
-                                                  edges=(0, 4000))
+    spike_trains = spk.load_spike_trains_from_txt(TEST_DATA, edges=(0, 4000))
     assert len(spike_trains) == 40
 
     # check the first spike train
@@ -48,8 +50,7 @@ def check_merged_spikes(merged_spikes, spike_trains):
 
 def test_merge_spike_trains():
     # first load the data
-    spike_trains = spk.load_spike_trains_from_txt("test/PySpike_testdata.txt",
-                                                  edges=(0, 4000))
+    spike_trains = spk.load_spike_trains_from_txt(TEST_DATA, edges=(0, 4000))
 
     merged_spikes = spk.merge_spike_trains([spike_trains[0], spike_trains[1]])
     # test if result is sorted