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.
8.5.2. nilearn.image.concat_imgs¶
nilearn.image.concat_imgs(niimgs, dtype=<class 'numpy.float32'>, ensure_ndim=None, memory=Memory(location=None), memory_level=0, auto_resample=False, verbose=0)¶Concatenate a list of 3D/4D niimgs of varying lengths.
The niimgs list can contain niftis/paths to images of varying dimensions (i.e., 3D or 4D) as well as different 3D shapes and affines, as they will be matched to the first image in the list if auto_resample=True.
Parameters: niimgs: iterable of Niimg-like objects or glob pattern
See http://nilearn.github.io/manipulating_images/input_output.html Niimgs to concatenate.
dtype: numpy dtype, optional
the dtype of the returned image
ensure_ndim: integer, optional
Indicate the dimensionality of the expected niimg. An error is raised if the niimg is of another dimensionality.
auto_resample: boolean
Converts all images to the space of the first one.
verbose: int
Controls the amount of verbosity (0 means no messages).
memory : instance of joblib.Memory or string
Used to cache the resampling process. By default, no caching is done. If a string is given, it is the path to the caching directory.
memory_level : integer, optional
Rough estimator of the amount of memory used by caching. Higher value means more memory for caching.
Returns: concatenated: nibabel.Nifti1Image
A single image.
See also
