Note
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_design_matrix_correlation¶
- nilearn.plotting.plot_design_matrix_correlation(design_matrix, tri='full', cmap='bwr', output_file=None, **kwargs)[source]¶
Compute and plot the correlation between regressor of a design matrix.
The drift and constant regressors are omitted from the plot.
Added in version 0.11.0.
- Parameters:
- design_matrix
pandas.DataFrame
_description_
- tri{‘full’, ‘diag’}, default=’full’
Which triangular part of the matrix to plot:
‘diag’: Plot the lower part with the diagonal
‘full’: Plot the full matrix
- %(cmap)s
Default=`bwr`. This must be a diverging colormap as the correlation matrix will be centered on 0. The allowed colormaps are:
“bwr”
“RdBu_r”
“seismic_r”
- %(output_file)s
- kwargsextra keyword arguments, optional
Extra keyword arguments are sent to
nilearn.plotting.plot_matrix
- design_matrix
- Returns:
- display
matplotlib.axes.Axes
Axes image.
- display
Examples using nilearn.plotting.plot_design_matrix_correlation
¶
Examples of design matrices