def test_glm():
data = np.load("../examples/data/eeg_32chans_10secs.npy")
num_ts, ts_len = np.shape(data)
window_size = ts_len / 2.0
fb_lo = [4.0, 8.0]
fb_hi = [25.0, 40.0]
fs = 128.0
ts, ts_avg = glm(data,
fb_lo,
fb_hi,
fs,
pairs=None,
window_size=window_size)
expected = np.load("data/test_glm_ts.npy")
np.testing.assert_array_equal(ts, expected)
expected = np.load("data/test_glm_avg.npy")
np.testing.assert_array_equal(ts_avg, expected)
# -*- coding: utf-8 -*-
import numpy as np
np.set_printoptions(precision=3, linewidth=256)
from dyfunconn.fc import glm
if __name__ == "__main__":
data = np.load(
"/home/makism/Github/dyfunconn/examples/data/eeg_32chans_10secs.npy")
data = data[0:5, :]
num_ts, ts_len = np.shape(data)
pairs = [(r1, r2) for r1 in xrange(0, num_ts) for r2 in xrange(r1, num_ts)]
window_size = ts_len / 2.0
fb_lo = [4.0, 8.0]
fb_hi = [25.0, 40.0]
fs = 128.0
ts, ts_avg = glm(data,
fb_lo,
fb_hi,
fs,
pairs=pairs,
window_size=window_size)
print ts_avg