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.

.. versionchanged:: 0.9.2dev

Changed default dtype casting of booleans from ‘int8’ to ‘uint8’.

affine4x4 numpy.ndarray, optional

Transformation matrix.

copy_headerbool, optional

Indicated if the header of the reference image should be used to create the new image. Default=False.

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

Visualizing global patterns with a carpet plot

Visualizing global patterns with a carpet plot
Searchlight analysis of face vs house recognition

Searchlight analysis of face vs house recognition

Searchlight analysis of face vs house recognition
Computing a Region of Interest (ROI) mask manually

Computing a Region of Interest (ROI) mask manually

Computing a Region of Interest (ROI) mask manually
NeuroVault meta-analysis of stop-go paradigm studies.

NeuroVault meta-analysis of stop-go paradigm studies.

NeuroVault meta-analysis of stop-go paradigm studies.