def test_merge_spike_trains():
# first load the data
spike_trains = spk.load_spike_trains_from_txt(TEST_DATA, edges=(0, 4000))
merged_spikes = spk.merge_spike_trains([spike_trains[0], spike_trains[1]])
# test if result is sorted
assert ((merged_spikes.spikes == np.sort(merged_spikes.spikes)).all())
# check merging
check_merged_spikes(merged_spikes.spikes,
[spike_trains[0].spikes, spike_trains[1].spikes])
merged_spikes = spk.merge_spike_trains(spike_trains)
# test if result is sorted
assert ((merged_spikes.spikes == np.sort(merged_spikes.spikes)).all())
# check merging
check_merged_spikes(merged_spikes.spikes,
[st.spikes for st in spike_trains])
def test_merge_empty_spike_trains():
# first load the data
spike_trains = spk.load_spike_trains_from_txt(TEST_DATA, edges=(0, 4000))
# take two non-empty trains, and one empty one
empty = spk.SpikeTrain([],[spike_trains[0].t_start,spike_trains[0].t_end])
merged_spikes = spk.merge_spike_trains([spike_trains[0], empty, spike_trains[1]])
# test if result is sorted
assert((merged_spikes.spikes == np.sort(merged_spikes.spikes)).all())
def test_merge_spike_trains():
# first load the data
spike_trains = spk.load_spike_trains_from_txt("test/PySpike_testdata.txt",
edges=(0, 4000))
merged_spikes = spk.merge_spike_trains([spike_trains[0], spike_trains[1]])
# test if result is sorted
assert((merged_spikes.spikes == np.sort(merged_spikes.spikes)).all())
# check merging
check_merged_spikes(merged_spikes.spikes, [spike_trains[0].spikes,
spike_trains[1].spikes])
merged_spikes = spk.merge_spike_trains(spike_trains)
# test if result is sorted
assert((merged_spikes.spikes == np.sort(merged_spikes.spikes)).all())
# check merging
check_merged_spikes(merged_spikes.spikes,
[st.spikes for st in spike_trains])
""" merge.py
Simple example showing the merging of two spike trains.
Copyright 2014, Mario Mulansky <*****@*****.**>
Distributed under the BSD License
"""
from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
import pyspike as spk
# first load the data, ending time = 4000
spike_trains = spk.load_spike_trains_from_txt("PySpike_testdata.txt", 4000)
merged_spike_train = spk.merge_spike_trains([spike_trains[0], spike_trains[1]])
print(merged_spike_train.spikes)
plt.plot(spike_trains[0], np.ones_like(spike_trains[0]), 'o')
plt.plot(spike_trains[1], np.ones_like(spike_trains[1]), 'x')
plt.plot(merged_spike_train.spikes,
2*np.ones_like(merged_spike_train), 'o')
plt.show()
""" merge.py
Simple example showing the merging of two spike trains.
Copyright 2014, Mario Mulansky <*****@*****.**>
Distributed under the BSD License
"""
from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
import pyspike as spk
# first load the data, ending time = 4000
spike_trains = spk.load_spike_trains_from_txt("PySpike_testdata.txt", 4000)
merged_spike_train = spk.merge_spike_trains([spike_trains[0], spike_trains[1]])
print(merged_spike_train.spikes)
plt.plot(spike_trains[0], np.ones_like(spike_trains[0]), 'o')
plt.plot(spike_trains[1], np.ones_like(spike_trains[1]), 'x')
plt.plot(merged_spike_train.spikes,
2*np.ones_like(merged_spike_train), 'o')
plt.show()