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.check_niimg_4d¶

nilearn.image.check_niimg_4d(niimg, return_iterator=False, dtype=None)[source]¶

Check that niimg is a proper 4D niimg-like object and load it.

Parameters:

niimg4D Niimg-like object: See Input and output: neuroimaging data representation. If niimgs is an iterable, checks if data is really 4D. Then, considering that it is a list of niimg and load them one by one. If niimgs is a string, consider it as a path to Nifti image and call nibabel.load on it. If it is an object, check if the affine attribute present and that nilearn.image.get_data returns a result, raise TypeError otherwise.
return_iteratorbool, default=False: If True, an iterator of 3D images is returned. This reduces the memory usage when niimgs contains 3D images. If False, a single 4D image is returned. When niimgs contains 3D images they are concatenated together.
dtypedtype like, “auto” or None, default=None: Data type toward which the data should be converted. If “auto”, the data will be converted to int32 if dtype is discrete and float32 if it is continuous. If None, data will not be converted to a new data type..

Returns:

niimg: 4D nibabel.Nifti1Image or iterator of 3D nibabel.Nifti1Image

Notes

This function is the equivalent to nilearn.image.check_niimg_3d for Niimg-like objects with a run level.

Its application is idempotent.