diff options
-rw-r--r-- | examples/isi_matrix.py | 8 | ||||
-rw-r--r-- | examples/test_merge.py | 7 | ||||
-rw-r--r-- | test/test_distance.py | 16 |
3 files changed, 12 insertions, 19 deletions
diff --git a/examples/isi_matrix.py b/examples/isi_matrix.py index a149cd6..0d6e185 100644 --- a/examples/isi_matrix.py +++ b/examples/isi_matrix.py @@ -5,12 +5,8 @@ import matplotlib.pyplot as plt import pyspike as spk -# first load the data -spike_trains = [] -spike_file = open("SPIKY_testdata.txt", 'r') -for line in spike_file: - spike_trains.append(spk.add_auxiliary_spikes( - spk.spike_train_from_string(line), 4000)) +# first load the data, interval ending time = 4000, start=0 (default) +spike_trains = spk.load_spike_trains_from_txt("SPIKY_testdata.txt", 4000) print(len(spike_trains)) diff --git a/examples/test_merge.py b/examples/test_merge.py index 1186062..0c34608 100644 --- a/examples/test_merge.py +++ b/examples/test_merge.py @@ -6,11 +6,8 @@ import matplotlib.pyplot as plt import pyspike as spk -# first load the data -spike_trains = [] -spike_file = open("SPIKY_testdata.txt", 'r') -for line in spike_file: - spike_trains.append(spk.spike_train_from_string(line)) +# first load the data, ending time = 4000 +spike_trains = spk.load_spike_trains_from_txt("SPIKY_testdata.txt", 4000) spikes = spk.merge_spike_trains([spike_trains[0], spike_trains[1]]) diff --git a/test/test_distance.py b/test/test_distance.py index 92b99ae..84d0af9 100644 --- a/test/test_distance.py +++ b/test/test_distance.py @@ -23,8 +23,8 @@ def test_isi(): expected_isi = [-0.1/0.3, -0.1/0.3, 0.05/0.2, 0.05/0.2, -0.15/0.35, -0.25/0.35, -0.05/0.35, 0.2/0.3, 0.25/0.3, 0.25/0.3] - t1 = spk.add_auxiliary_spikes(t1, (0.0,1.0)) - t2 = spk.add_auxiliary_spikes(t2, (0.0,1.0)) + t1 = spk.add_auxiliary_spikes(t1, 1.0) + t2 = spk.add_auxiliary_spikes(t2, 1.0) f = spk.isi_distance(t1, t2) # print("ISI: ", f.y) @@ -39,8 +39,8 @@ def test_isi(): 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] - t1 = spk.add_auxiliary_spikes(t1, (0.0,1.0)) - t2 = spk.add_auxiliary_spikes(t2, (0.0,1.0)) + t1 = spk.add_auxiliary_spikes(t1, 1.0) + t2 = spk.add_auxiliary_spikes(t2, 1.0) f = spk.isi_distance(t1, t2) assert_equal(f.x, expected_times) @@ -64,8 +64,8 @@ def test_spike(): expected_y1 = (s1[:-1]*isi2+s2[:-1]*isi1) / (0.5*(isi1+isi2)**2) expected_y2 = (s1[1:]*isi2+s2[1:]*isi1) / (0.5*(isi1+isi2)**2) - t1 = spk.add_auxiliary_spikes(t1, (0.0,1.0)) - t2 = spk.add_auxiliary_spikes(t2, (0.0,1.0)) + t1 = spk.add_auxiliary_spikes(t1, 1.0) + t2 = spk.add_auxiliary_spikes(t2, 1.0) f = spk.spike_distance(t1, t2) assert_equal(f.x, expected_times) @@ -84,8 +84,8 @@ def test_spike(): expected_y1 = (s1[:-1]*isi2+s2[:-1]*isi1) / (0.5*(isi1+isi2)**2) expected_y2 = (s1[1:]*isi2+s2[1:]*isi1) / (0.5*(isi1+isi2)**2) - t1 = spk.add_auxiliary_spikes(t1, (0.0,1.0)) - t2 = spk.add_auxiliary_spikes(t2, (0.0,1.0)) + t1 = spk.add_auxiliary_spikes(t1, 1.0) + t2 = spk.add_auxiliary_spikes(t2, 1.0) f = spk.spike_distance(t1, t2) assert_equal(f.x, expected_times) |