6704c535b8c59ab3b9b98c0489a051654c1ee727,nisl/signals.py,,_standardize,#Any#Any#Any#,12
Before Change
=======
std_signals: copy of signals, normalized.
signals = np.array(signals).astype(np.float)
buf = signals.T
buf -= signals.mean(axis=-1)
if normalize:
After Change
if normalize:
// remove mean if not already detrended
if not detrend:
signals -= signals.mean(axis=0)
std = np.sqrt((signals ** 2).sum(axis=0))
std[std < np.finfo(np.float).eps] = 1. // avoid numerical problems
signals /= std
return signals
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 3
Instances
Project Name: nilearn/nilearn
Commit Name: 6704c535b8c59ab3b9b98c0489a051654c1ee727
Time: 2013-04-05
Author: philippe.gervais@inria.fr
File Name: nisl/signals.py
Class Name:
Method Name: _standardize
Project Name: pymc-devs/pymc3
Commit Name: d41939a04dffd9737252dc9e58ab2de11f4e663e
Time: 2016-05-11
Author: chris.fonnesbeck@vanderbilt.edu
File Name: pymc3/model.py
Class Name:
Method Name: as_tensor
Project Name: dmlc/gluon-nlp
Commit Name: d63abb86304d5ceca8ec14109a4812258f9839ea
Time: 2019-09-24
Author: linhaibin.eric@gmail.com
File Name: scripts/bert/finetune_classifier.py
Class Name:
Method Name: evaluate