6eabf1eeaa3c9d64b67d3f29b3c546baa8235671,seglearn/features.py,,_compute_features,#Any#Any#,186
Before Change
D = X["ts"].shape[2]
Nuv = len(features)
fts = np.zeros((N, Nuv * D))
// computed features
for i in range(Nuv):
fts[:, i * D:((i + 1) * D)] = features[i](X["ts"])
// static features
hnames = [h for h in X.dtype.names if h != "ts"]
for h in hnames:
fts = np.column_stack([fts,np.full(N,X[h])])
return fts
def mean_crossings(X):
After Change
N = X["ts"].shape[0]
Xt = np.atleast_3d(X["ts"])
// computed features
fts = [features[i](Xt) for i in range(len(features))]
// static features
s_fts = [np.full(N,X[s]) for s in X.dtype.names if s!= "ts"]
fts = np.column_stack(fts+s_fts)
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 9
Instances Project Name: dmbee/seglearn
Commit Name: 6eabf1eeaa3c9d64b67d3f29b3c546baa8235671
Time: 2018-03-06
Author: david.mo.burns@gmail.com
File Name: seglearn/features.py
Class Name:
Method Name: _compute_features
Project Name: automl/auto-sklearn
Commit Name: d067fe9dc7d264ce61effcb3d309b613a8df4484
Time: 2016-05-02
Author: feurerm@informatik.uni-freiburg.de
File Name: test/test_pipeline/test_classification.py
Class Name: SimpleClassificationPipelineTest
Method Name: test_predict_proba_batched
Project Name: automl/auto-sklearn
Commit Name: d067fe9dc7d264ce61effcb3d309b613a8df4484
Time: 2016-05-02
Author: feurerm@informatik.uni-freiburg.de
File Name: test/test_pipeline/test_classification.py
Class Name: SimpleClassificationPipelineTest
Method Name: test_predict_proba_batched_sparse