def test_window_rms(self):
data = num.random.randn(5000)
ws = data.size / 5
t0 = time()
data_stds = utility.running_window_rms(data, window_size=ws)
t1 = time()
data_stds2 = num.array([
num.sqrt((data[i:i + ws] ** 2).sum() / ws)
for i in range(data.size - ws + 1)])
t2 = time()
print('Convolution %f [s], loop %f [s]' % (t1 - t0, t2 - t1))
num.testing.assert_allclose(data_stds, data_stds2, rtol=0., atol=1e-6)
data_stds = utility.running_window_rms(
data, window_size=ws, mode='same')
print(data_stds.shape)
def toeplitz_covariance(data, window_size):
"""
Get Toeplitz banded matrix for given data.
Returns
-------
toeplitz : :class:`numpy.ndarray` 2-d, (size data, size data)
stds : :class:`numpy.ndarray` 1-d, size data
of running windows
"""
stds = running_window_rms(data, window_size=window_size, mode='same')
coeffs = autocovariance(data / stds)
return toeplitz(coeffs), stds