5830eee2522cc9c00056f876e0e3a8debd184e7c,examples/03_connectivity/plot_signal_extraction.py,,,#,29

Before Change


import numpy as np
from matplotlib import pyplot as plt
from nilearn import plotting
fig, ax = plt.subplots(1, 1, figsize=(10, 10))
// Mask the main diagonal for visualization:
np.fill_diagonal(correlation_matrix, 0)
plotting.plot_matrix(correlation_matrix, ax=ax, labels=labels,
                     vmax=0.8, vmin=-0.8)

After Change


// Mask the main diagonal for visualization:
np.fill_diagonal(correlation_matrix, 0)

plotting.plot_matrix(correlation_matrix, figure=(10, 8), labels=labels[1:],
                     vmax=0.8, vmin=-0.8, title="No confounds")

plotting.show()
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 3

Instances


Project Name: nilearn/nilearn
Commit Name: 5830eee2522cc9c00056f876e0e3a8debd184e7c
Time: 2017-07-30
Author: gael.varoquaux@normalesup.org
File Name: examples/03_connectivity/plot_signal_extraction.py
Class Name:
Method Name:


Project Name: scikit-learn-contrib/imbalanced-learn
Commit Name: 153f6e0ff5729fc22b68d5f6e0fd05edf96d8c2c
Time: 2019-11-17
Author: g.lemaitre58@gmail.com
File Name: examples/datasets/plot_make_imbalance.py
Class Name:
Method Name:


Project Name: kymatio/kymatio
Commit Name: 4f1e7f2f936bf5f3e6d1da8d8be843dc3273fe67
Time: 2018-11-21
Author: janden@flatironinstitute.org
File Name: examples/1d/plot_filters.py
Class Name:
Method Name: