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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_allclose, 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_allclose(coincidences[i], sync_prof.y[sync_prof.x == t],
err_msg="At index %d" % i)
coincidences = np.array(coincidence_impl(st2, st1, 0, 5.0, 0.0))
for i, t in enumerate(st2):
assert_allclose(coincidences[i], sync_prof.y[sync_prof.x == t],
err_msg="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_allclose(coincidences[i], sync_prof.y[sync_prof.x == t],
err_msg="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_allclose(coincidences[i], expected,
err_msg="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_allclose(filtered_spike_trains[0].spikes, [1.0, 2.0, 4.0])
# assert_allclose(filtered_spike_trains[1].spikes, [1.1, 2.1, 3.8])
# filtered_spike_trains = spk.filter_by_spike_sync([st2, st1], 0.5)
# assert_allclose(filtered_spike_trains[0].spikes, [1.1, 2.1, 3.8])
# assert_allclose(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_allclose(filtered_spike_trains[0].spikes, [1.0, 4.0])
assert_allclose(filtered_spike_trains[1].spikes, [1.1, 3.8])
assert_allclose(filtered_spike_trains[2].spikes, [0.9, 4.1])
if __name__ == "__main__":
test_single_prof()
test_filter()
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