1 files changed, 95 insertions, 0 deletions
diff --git a/test/test_sync_filter.py b/test/test_sync_filter.py
new file mode 100644
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+++ b/test/test_sync_filter.py
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+""" test_sync_filter.py
+
+Tests the spike sync based filtering
+
+Copyright 2015, Mario Mulansky <mario.mulansky@gmx.net>
+
+Distributed under the BSD License
+
+"""
+
+from __future__ import print_function
+import numpy as np
+from numpy.testing import assert_equal, assert_almost_equal, \
+    assert_array_almost_equal
+
+import pyspike as spk
+from pyspike import SpikeTrain
+
+
+def test_single_prof():
+    st1 = np.array([1.0, 2.0, 3.0, 4.0])
+    st2 = np.array([1.1, 2.1, 3.8])
+    st3 = np.array([0.9, 3.1, 4.1])
+
+    # cython implementation
+    try:
+        from pyspike.cython.cython_profiles import \
+            coincidence_single_profile_cython as coincidence_impl
+    except ImportError:
+        from pyspike.cython.python_backend import \
+            coincidence_single_python as coincidence_impl
+
+    sync_prof = spk.spike_sync_profile(SpikeTrain(st1, 5.0),
+                                       SpikeTrain(st2, 5.0))
+
+    coincidences = np.array(coincidence_impl(st1, st2, 0, 5.0, 0.0))
+    print(coincidences)
+    for i, t in enumerate(st1):
+        assert_equal(coincidences[i], sync_prof.y[sync_prof.x == t],
+                     "At index %d" % i)
+
+    coincidences = np.array(coincidence_impl(st2, st1, 0, 5.0, 0.0))
+    for i, t in enumerate(st2):
+        assert_equal(coincidences[i], sync_prof.y[sync_prof.x == t],
+                     "At index %d" % i)
+
+    sync_prof = spk.spike_sync_profile(SpikeTrain(st1, 5.0),
+                                       SpikeTrain(st3, 5.0))
+
+    coincidences = np.array(coincidence_impl(st1, st3, 0, 5.0, 0.0))
+    for i, t in enumerate(st1):
+        assert_equal(coincidences[i], sync_prof.y[sync_prof.x == t],
+                     "At index %d" % i)
+
+    st1 = np.array([1.0, 2.0, 3.0, 4.0])
+    st2 = np.array([1.0, 2.0, 4.0])
+
+    sync_prof = spk.spike_sync_profile(SpikeTrain(st1, 5.0),
+                                       SpikeTrain(st2, 5.0))
+
+    coincidences = np.array(coincidence_impl(st1, st2, 0, 5.0, 0.0))
+    for i, t in enumerate(st1):
+        expected = sync_prof.y[sync_prof.x == t]/sync_prof.mp[sync_prof.x == t]
+        assert_equal(coincidences[i], expected,
+                     "At index %d" % i)
+
+
+def test_filter():
+    st1 = SpikeTrain(np.array([1.0, 2.0, 3.0, 4.0]), 5.0)
+    st2 = SpikeTrain(np.array([1.1, 2.1, 3.8]), 5.0)
+    st3 = SpikeTrain(np.array([0.9, 3.1, 4.1]), 5.0)
+
+    # filtered_spike_trains = spk.filter_by_spike_sync([st1, st2], 0.5)
+
+    # assert_equal(filtered_spike_trains[0].spikes, [1.0, 2.0, 4.0])
+    # assert_equal(filtered_spike_trains[1].spikes, [1.1, 2.1, 3.8])
+
+    # filtered_spike_trains = spk.filter_by_spike_sync([st2, st1], 0.5)
+
+    # assert_equal(filtered_spike_trains[0].spikes, [1.1, 2.1, 3.8])
+    # assert_equal(filtered_spike_trains[1].spikes, [1.0, 2.0, 4.0])
+
+    filtered_spike_trains = spk.filter_by_spike_sync([st1, st2, st3], 0.75)
+
+    for st in filtered_spike_trains:
+        print(st.spikes)
+
+    assert_equal(filtered_spike_trains[0].spikes, [1.0, 4.0])
+    assert_equal(filtered_spike_trains[1].spikes, [1.1, 3.8])
+    assert_equal(filtered_spike_trains[2].spikes, [0.9, 4.1])
+
+
+if __name__ == "main":
+    test_single_prof()
+    test_filter()