d8ab8131e19498c2b9bed8d218e4e46eedc7cf21,librosa/tf_agc.py,,tf_agc,#,106
Before Change
f2a = melfb(sample_rate, len(frame), num_frequency_bands, mel_filter_width)
f2a = f2a[:,:(round(len(frame)/2) + 1)]
n = f2a.shape[0]
// initialze the state vector
state = numpy.zeros( (n, 1) )
fbg = numpy.zeros( (n, 1) )
After Change
// fbg(:,i) = state;
// ...
//
state = numpy.maximum(alpha * state, audiogram)
//E = diag(1./(sf2a+(sf2a==0))) * f2a" * fbg;
E = normalize_f2a * numpy.dot(f2a.T, state);
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 3
Instances
Project Name: librosa/librosa
Commit Name: d8ab8131e19498c2b9bed8d218e4e46eedc7cf21
Time: 2012-10-20
Author: brm2132@columbia.edu
File Name: librosa/tf_agc.py
Class Name:
Method Name: tf_agc
Project Name: hyperspy/hyperspy
Commit Name: 99f1fe50a8f08740243f23a73b7af65e196ab3ac
Time: 2020-08-31
Author: eric.prestat@gmail.com
File Name: hyperspy/misc/lowess_smooth.py
Class Name:
Method Name: lowess
Project Name: librosa/librosa
Commit Name: 14056d4584a7ba3ac9446814e1d7f4613080b618
Time: 2013-03-22
Author: brm2132@columbia.edu
File Name: librosa/__init__.py
Class Name:
Method Name: logamplitude