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.regions.signals_to_img_labels#

nilearn.regions.signals_to_img_labels(signals, labels_img, mask_img=None, background_label=0, order='F')[source]#

Create image from region signals defined as labels.

The same region signal is used for each voxel of the corresponding 3D volume.

labels_img, mask_img must have the same shapes and affines.

Parameters

signalsnumpy.ndarray: 2D array with shape: (scan number, number of regions in labels_img).
labels_imgNiimg-like object: See http://nilearn.github.io/manipulating_images/input_output.html Region definitions using labels.
mask_imgNiimg-like object, optional: Boolean array giving voxels to process. integer arrays also accepted, In this array, zero means False, non-zero means True.
background_labelnumber, optional: Label to use for “no region”. Default=0.
orderstr, optional: Ordering of output array (“C” or “F”). Default=”F”.

Returns

imgnibabel.nifti1.Nifti1Image: Reconstructed image. dtype is that of “signals”, affine and shape are those of labels_img.