def test_morletf():
"""
Confirm consistency in morlet wavelet filtering
"""
# Load data
data = np.load(os.path.dirname(pacpy.__file__) + '/tests/exampledata.npy')
assert np.allclose(np.sum(np.abs(morletf(data, 21.5))),
40661855.060118973,
atol=10**-5)
assert len(morletf(data, 21.5)) == len(data)
def test_morletf():
"""
Confirm consistency in morlet wavelet filtering
"""
# Load data
data = np.load(os.path.dirname(pacpy.__file__) + "/tests/exampledata.npy")
assert np.allclose(np.sum(np.abs(morletf(data, 21.5))), 40125678.7918, atol=10 ** -4)
def _morletT(x, f0s, w=3, fs=1000, s=1):
"""
Calculate the time-frequency representation of the signal 'x' over the
frequencies in 'f0s' using morlet wavelets
Parameters
----------
x : array
time series
f0s : array
frequency axis
w : float
Length of the filter in terms of the number of cycles
of the oscillation whose frequency is the center of the
bandpass filter
Fs : float
Sampling rate
s : float
Scaling factor
Returns
-------
mwt : 2-D array
time-frequency representation of signal x
"""
if w <= 0:
raise ValueError(
'Number of cycles in a filter must be a positive number.')
T = len(x)
F = len(f0s)
mwt = np.zeros([F, T], dtype=complex)
for f in range(F):
mwt[f] = morletf(x, f0s[f], fs=fs, w=w, s=s)
return mwt
def test_morletf():
"""
Confirm consistency in morlet wavelet filtering
"""
# Load data
data = np.load(os.path.dirname(pacpy.__file__) + '/tests/exampledata.npy')
assert np.allclose(
np.sum(np.abs(morletf(data, 21.5))), 40125678.7918, atol=10 ** -4)
def _morletT(x, f0s, w=3, fs=1000, s=1):
"""
Calculate the time-frequency representation of the signal 'x' over the
frequencies in 'f0s' using morlet wavelets
Parameters
----------
x : array
time series
f0s : array
frequency axis
w : float
Length of the filter in terms of the number of cycles
of the oscillation whose frequency is the center of the
bandpass filter
Fs : float
Sampling rate
s : float
Scaling factor
Returns
-------
mwt : 2-D array
time-frequency representation of signal x
"""
if w <= 0:
raise ValueError(
'Number of cycles in a filter must be a positive number.')
T = len(x)
F = len(f0s)
mwt = np.zeros([F, T], dtype=complex)
for f in range(F):
mwt[f] = morletf(x, f0s[f], fs=fs, w=w, s=s)
return mwt