diff options
Diffstat (limited to 'test/test_distance.py')
| -rw-r--r-- | test/test_distance.py | 19 |
1 files changed, 8 insertions, 11 deletions
diff --git a/test/test_distance.py b/test/test_distance.py index ba19f5e..b54e908 100644 --- a/test/test_distance.py +++ b/test/test_distance.py @@ -15,12 +15,13 @@ from numpy.testing import assert_equal, assert_almost_equal, \ assert_array_almost_equal import pyspike as spk +from pyspike import SpikeTrain def test_isi(): # generate two spike trains: - t1 = np.array([0.2, 0.4, 0.6, 0.7]) - t2 = np.array([0.3, 0.45, 0.8, 0.9, 0.95]) + t1 = SpikeTrain([0.2, 0.4, 0.6, 0.7], 1.0) + t2 = SpikeTrain([0.3, 0.45, 0.8, 0.9, 0.95], 1.0) # pen&paper calculation of the isi distance expected_times = [0.0, 0.2, 0.3, 0.4, 0.45, 0.6, 0.7, 0.8, 0.9, 0.95, 1.0] @@ -32,8 +33,6 @@ def test_isi(): expected_isi_val = sum((expected_times[1:] - expected_times[:-1]) * expected_isi)/(expected_times[-1]-expected_times[0]) - t1 = spk.add_auxiliary_spikes(t1, 1.0) - t2 = spk.add_auxiliary_spikes(t2, 1.0) f = spk.isi_profile(t1, t2) # print("ISI: ", f.y) @@ -44,8 +43,8 @@ def test_isi(): assert_equal(spk.isi_distance(t1, t2), expected_isi_val) # check with some equal spike times - t1 = np.array([0.2, 0.4, 0.6]) - t2 = np.array([0.1, 0.4, 0.5, 0.6]) + t1 = SpikeTrain([0.2, 0.4, 0.6], [0.0, 1.0]) + t2 = SpikeTrain([0.1, 0.4, 0.5, 0.6], [0.0, 1.0]) expected_times = [0.0, 0.1, 0.2, 0.4, 0.5, 0.6, 1.0] expected_isi = [0.1/0.2, 0.1/0.3, 0.1/0.3, 0.1/0.2, 0.1/0.2, 0.0/0.5] @@ -55,8 +54,6 @@ def test_isi(): expected_isi_val = sum((expected_times[1:] - expected_times[:-1]) * expected_isi)/(expected_times[-1]-expected_times[0]) - t1 = spk.add_auxiliary_spikes(t1, 1.0) - t2 = spk.add_auxiliary_spikes(t2, 1.0) f = spk.isi_profile(t1, t2) assert_equal(f.x, expected_times) @@ -318,6 +315,6 @@ def test_multi_variate_subsets(): if __name__ == "__main__": test_isi() - test_spike() - test_multi_isi() - test_multi_spike() + # test_spike() + # test_multi_isi() + # test_multi_spike() |