def test_plv():
data = np.load("../examples/data/eeg_32chans_10secs.npy")
ts, avg = plv(data)
ts = np.float32(ts)
avg = np.float32(avg)
expected_ts = np.load("data/test_plv_ts.npy")
expected_ts = np.float32(expected_ts)
np.testing.assert_array_equal(ts, expected_ts) # , rtol=1e-10, atol=0.0)
expected_avg = np.load("data/test_plv_avg.npy")
expected_avg = np.float32(expected_avg)
np.testing.assert_array_equal(avg, expected_avg) # , rtol=1e-10, atol=0.0)
def test_fisher_z_plv():
""" WIP """
from dyconnmap.fc import plv
np.set_printoptions(precision=2, linewidth=256)
# print ""
data = np.load("../examples/data/eeg_32chans_10secs.npy")
ts, avg = plv(data, [1.0, 4.0], 128.0)
symm_avg = avg + avg.T
np.fill_diagonal(symm_avg, 1.0)
# print symm_avg
ts = fisher_z_plv(avg)
import numpy as np
np.set_printoptions(precision=3, linewidth=160, suppress=True)
from dyconnmap.fc import plv, PLV, pac, PAC
from dyconnmap import tvfcg, tvfcg_ts, tvfcg_cfc
if __name__ == '__main__':
data = np.load("../examples/data/eeg_32chans_10secs.npy")
# PLV
fb = [1.0, 4.0]
fs = 128.0
now = time.time()
ts, avg = plv(data, fb, fs)
print("Finished in", time.time() - now, "sec")
# TVFCGs from time seriess
now = time.time()
fcgs = tvfcg_ts(ts, [1.0, 4.0], 128)
print("Finished in", time.time() - now, "sec")
# TVFCGs
fb = [1.0, 4.0]
fs = 128.0
estimator = PLV(fb, fs)
fcgs = tvfcg(data, estimator, fb, fs)
# PAC
# -*- coding: utf-8 -*-
import numpy as np
np.set_printoptions(precision=3, linewidth=256)
from dyconnmap.fc import plv, PLV
if __name__ == "__main__":
data = np.load("/home/makism/Github/dyconnmap/examples/data/eeg_32chans_10secs.npy")
data = data[0:5, ]
ts, avg = plv(data, [1.0, 4.0], 128.0)
print(avg)
# p = PLV([1.0, 4.0], 128.0, pairs=None)
# a = data[0, :]
# b = data[1, :]
#
# tmp, tmp2 = p.estimate_pair(a, b)
# print tmp, tmp2
#
# tmp, tmp2 = p.estimate(data[0:2, :])
# print tmp, tmp2