baf417648e1e0275e11a28278e23797c274dff9b,plot_visualization.py,,,#,12

Before Change


import matplotlib.pyplot as plt

// Compute the mean EPI: we do the mean along the axis 3, which is time
mean_img = np.mean(fmri_data, axis=3)
// Note that this can also be done on Nifti images using
// nilearn.image.mean_img

// plt.figure() creates a new figure

After Change


import matplotlib.pyplot as plt

// Compute the mean EPI: we do the mean along the axis 3, which is time
mean_haxby = mean_img(haxby_files.func)

plot_epi(mean_haxby)

////// Extracting a brain mask //////////////////////////////////////////////////////////////////////////////////////////////////////
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 3

Instances


Project Name: nilearn/nilearn
Commit Name: baf417648e1e0275e11a28278e23797c274dff9b
Time: 2014-06-16
Author: chris.gorgolewski@gmail.com
File Name: plot_visualization.py
Class Name:
Method Name:


Project Name: nilearn/nilearn
Commit Name: 4d651b16bab2d31b8d0d172a285406195a3845bf
Time: 2014-04-22
Author: gael.varoquaux@normalesup.org
File Name: plot_ica_resting_state.py
Class Name:
Method Name:


Project Name: nilearn/nilearn
Commit Name: 4d651b16bab2d31b8d0d172a285406195a3845bf
Time: 2014-04-22
Author: gael.varoquaux@normalesup.org
File Name: plot_roi_extraction.py
Class Name:
Method Name: