Loading sails/wavelet.py +7 −2 Original line number Diff line number Diff line from scipy import signal #!/usr/bin/python # vim: set expandtab ts=4 sw=4: import numpy as np from scipy import signal def morlet(x, freqs, sample_rate, win_len=4, ncycles=5, ret_basis=False, Loading Loading @@ -29,6 +33,7 @@ def morlet(x, freqs, sample_rate, win_len=4, ncycles=5, ret_basis=False, ------- 2D array Array containing morlet wavelet transformed data [nfreqs x nsamples] """ orig_dim = x.ndim if orig_dim == 1: Loading Loading @@ -86,6 +91,7 @@ def cross_morlet(x, freqs, sample_rate, win_len=4, ncycles=5, normalise=False): ------- 4D array Array containing morlet cross wavelet transformed data [nfreqs x nsamples x nchannels x nchannels]. """ wt = morlet(x, freqs, sample_rate, win_len=win_len, ncycles=ncycles, ret_mode='complex', normalise=normalise) Loading Loading @@ -118,7 +124,6 @@ def get_morlet_basis(freq, ncycles, win_len, sample_rate, normalise): Complex valued arrays containing morlet wavelets """ m = [] for ii in range(len(freq)): # Sigma controls the width of the gaussians applied to each wavelet. This Loading Loading
sails/wavelet.py +7 −2 Original line number Diff line number Diff line from scipy import signal #!/usr/bin/python # vim: set expandtab ts=4 sw=4: import numpy as np from scipy import signal def morlet(x, freqs, sample_rate, win_len=4, ncycles=5, ret_basis=False, Loading Loading @@ -29,6 +33,7 @@ def morlet(x, freqs, sample_rate, win_len=4, ncycles=5, ret_basis=False, ------- 2D array Array containing morlet wavelet transformed data [nfreqs x nsamples] """ orig_dim = x.ndim if orig_dim == 1: Loading Loading @@ -86,6 +91,7 @@ def cross_morlet(x, freqs, sample_rate, win_len=4, ncycles=5, normalise=False): ------- 4D array Array containing morlet cross wavelet transformed data [nfreqs x nsamples x nchannels x nchannels]. """ wt = morlet(x, freqs, sample_rate, win_len=win_len, ncycles=ncycles, ret_mode='complex', normalise=normalise) Loading Loading @@ -118,7 +124,6 @@ def get_morlet_basis(freq, ncycles, win_len, sample_rate, normalise): Complex valued arrays containing morlet wavelets """ m = [] for ii in range(len(freq)): # Sigma controls the width of the gaussians applied to each wavelet. This Loading