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author | Mario Mulansky <mario.mulansky@gmx.net> | 2015-12-14 14:24:14 +0100 |
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committer | Mario Mulansky <mario.mulansky@gmx.net> | 2015-12-14 14:24:14 +0100 |
commit | 776d8d686f9c19a729038270f69872801bba43a2 (patch) | |
tree | 0b4f2bc756bd0fe434360a8af5a920e76c5352f8 /test | |
parent | b970055641b215d30b671ee810e29c6a55e6214a (diff) | |
parent | 0dbdc0096dacc1f6233600ed6e36487bbab6b718 (diff) |
Merge branch 'develop' of github.com:mariomulansky/PySpike into develop
Diffstat (limited to 'test')
-rw-r--r-- | test/test_distance.py | 20 | ||||
-rw-r--r-- | test/test_regression/test_regression_15.py | 38 | ||||
-rw-r--r-- | test/test_spikes.py | 9 |
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 |