c8280cd73ec4782188ab1d8d4d7f4ce349a07f6a,tests/test_effects.py,,test_trim,#,144

Before Change


    // construct 5 seconds of stereo silence
    // Stick a sine wave in the middle three seconds
    sr = float(22050)
    y = np.zeros((2, int(5 * sr)))
    y[0, sr:4*sr] = np.sin(2 * np.pi * 440 * np.arange(0, 3 * sr) / sr)

    for top_db in [60, 40, 20]:

After Change


    trim_duration = 3.0
    y = np.sin(2 * np.pi * 440. * np.arange(0, trim_duration * sr) / sr)
    y = librosa.util.pad_center(y, 5 * sr)
    y = np.vstack([y, np.zeros_like(y)])

    for top_db in [60, 40, 20]:
        for ref_power in [1, np.max]:
            // Test stereo
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 3

Instances


Project Name: librosa/librosa
Commit Name: c8280cd73ec4782188ab1d8d4d7f4ce349a07f6a
Time: 2016-11-02
Author: brian.mcfee@nyu.edu
File Name: tests/test_effects.py
Class Name:
Method Name: test_trim


Project Name: ANSSI-FR/SecuML
Commit Name: 39efccc696a1c20745a52cc50935cdc24f92230d
Time: 2019-05-09
Author: anael.beaugnon@ssi.gouv.fr
File Name: secuml/core/classif/classifiers/__init__.py
Class Name: Classifier
Method Name: _predict_streaming


Project Name: ANSSI-FR/SecuML
Commit Name: 39efccc696a1c20745a52cc50935cdc24f92230d
Time: 2019-05-09
Author: anael.beaugnon@ssi.gouv.fr
File Name: secuml/exp/data/features.py
Class Name: FeaturesFromExp
Method Name: get_matrix