This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.


nilearn.plotting.plot_img_comparison(ref_imgs, src_imgs, masker, plot_hist=True, log=True, ref_label='image set 1', src_label='image set 2', output_dir=None, axes=None)[source]#

Creates plots to compare two lists of images and measure correlation.

The first plot displays linear correlation between voxel values. The second plot superimposes histograms to compare values distribution.


Reference images.


Source images.

maskerNiftiMasker object

Mask to be used on data.

plot_histBoolean, optional

If True then histograms of each img in ref_imgs will be plotted along-side the histogram of the corresponding image in src_imgs. Default=True.

logBoolean, optional

Passed to plt.hist. Default=True.

ref_labelstr, optional

Name of reference images. Default=’image set 1’.

src_labelstr, optional

Name of source images. Default=’image set 2’.

output_dirstring, optional

Directory where plotted figures will be stored.

axeslist of two matplotlib Axes objects, optional

Can receive a list of the form [ax1, ax2] to render the plots. By default new axes will be created.


Pearson correlation between the images.

Examples using nilearn.plotting.plot_img_comparison#

First level analysis of a complete BIDS dataset from openneuro

First level analysis of a complete BIDS dataset from openneuro