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.image.new_img_like¶

nilearn.image.new_img_like(ref_niimg, data, affine=None, copy_header=False)[source]¶

Create a new image of the same class as the reference image.

Parameters:

ref_niimgNiimg-like object: Reference image. The new image will be of the same type.
datanumpy.ndarray: Data to be stored in the image. If data dtype is a boolean, then data is cast to ‘uint8’ by default.

Changed in version 0.9.2: Changed default dtype casting of booleans from ‘int8’ to ‘uint8’.
affine4x4 numpy.ndarray, optional: Transformation matrix.
copy_headerbool, default=False: Indicated if the header of the reference image should be used to create the new image.

Returns:

Niimg-like object: A loaded image with the same file type (and, optionally, header) as the reference image.

Examples using `nilearn.image.new_img_like`¶

Visualizing global patterns with a carpet plot

Searchlight analysis of face vs house recognition

Comparing connectomes on different reference atlases

Computing a Region of Interest (ROI) mask manually

Copying headers from input images with math_img

NeuroVault meta-analysis of stop-go paradigm studies

nilearn.image.new_img_like¶

Examples using nilearn.image.new_img_like¶

Examples using `nilearn.image.new_img_like`¶