removed auxiliary_spike test, all tests pass

1 files changed, 16 insertions, 30 deletions

diff --git a/test/test_spikes.py b/test/test_spikes.py
index b12099e..6e11c07 100644
--- a/test/test_spikes.py
+++ b/test/test_spikes.py
@@ -14,38 +14,22 @@ from numpy.testing import assert_equal
 import pyspike as spk
 
 
-def test_auxiliary_spikes():
-    t = np.array([0.2, 0.4, 0.6, 0.7])
-    t_aux = spk.add_auxiliary_spikes(t, time_interval=(0.1, 1.0))
-    assert_equal(t_aux, [0.1, 0.2, 0.4, 0.6, 0.7, 1.0])
-    t_aux = spk.add_auxiliary_spikes(t_aux, time_interval=(0.0, 1.0))
-    assert_equal(t_aux, [0.0, 0.1, 0.2, 0.4, 0.6, 0.7, 1.0])
-
-
 def test_load_from_txt():
     spike_trains = spk.load_spike_trains_from_txt("test/PySpike_testdata.txt",
-                                                  time_interval=(0, 4000))
+                                                  interval=(0, 4000))
     assert len(spike_trains) == 40
 
     # check the first spike train
-    spike_times = [0, 64.886, 305.81, 696, 937.77, 1059.7, 1322.2, 1576.1,
+    spike_times = [64.886, 305.81, 696, 937.77, 1059.7, 1322.2, 1576.1,
                    1808.1, 2121.5, 2381.1, 2728.6, 2966.9, 3223.7, 3473.7,
-                   3644.3, 3936.3, 4000]
-    assert_equal(spike_times, spike_trains[0])
+                   3644.3, 3936.3]
+    assert_equal(spike_times, spike_trains[0].spikes)
 
     # check auxiliary spikes
     for spike_train in spike_trains:
-        assert spike_train[0] == 0.0
-        assert spike_train[-1] == 4000
+        assert spike_train.t_start == 0.0
+        assert spike_train.t_end == 4000
 
-    # load without adding auxiliary spikes
-    spike_trains2 = spk.load_spike_trains_from_txt("test/PySpike_testdata.txt",
-                                                   time_interval=None)
-    assert len(spike_trains2) == 40
-    # check auxiliary spikes
-    for i in xrange(len(spike_trains)):
-        assert len(spike_trains[i]) == len(spike_trains2[i])+2  # 2 spikes less
-    
 
 def check_merged_spikes(merged_spikes, spike_trains):
     # create a flat array with all spike events
@@ -65,21 +49,23 @@ 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",
-                                                  time_interval=(0, 4000))
+                                                  interval=(0, 4000))
 
-    spikes = spk.merge_spike_trains([spike_trains[0], spike_trains[1]])
+    merged_spikes = spk.merge_spike_trains([spike_trains[0], spike_trains[1]])
     # test if result is sorted
-    assert((spikes == np.sort(spikes)).all())
+    assert((merged_spikes.spikes == np.sort(merged_spikes.spikes)).all())
     # check merging
-    check_merged_spikes(spikes, [spike_trains[0], spike_trains[1]])
+    check_merged_spikes(merged_spikes.spikes, [spike_trains[0].spikes,
+                                               spike_trains[1].spikes])
 
-    spikes = spk.merge_spike_trains(spike_trains)
+    merged_spikes = spk.merge_spike_trains(spike_trains)
     # test if result is sorted
-    assert((spikes == np.sort(spikes)).all())
+    assert((merged_spikes.spikes == np.sort(merged_spikes.spikes)).all())
     # check merging
-    check_merged_spikes(spikes, spike_trains)
+    check_merged_spikes(merged_spikes.spikes,
+                        [st.spikes for st in spike_trains])
+
 
 if __name__ == "main":
-    test_auxiliary_spikes()
     test_load_from_txt()
     test_merge_spike_trains()