@pimms.value<EOL><INDENT>def image_dimensions(images):<DEDENT>
if images is None or len(images) == <NUM_LIT:0>: return None<EOL>if pimms.is_lazy_map(images):<EOL><INDENT>key = next((k for k in images.iterkeys() if not images.is_lazy(k)), None)<EOL>if key is None: key = next(images.iterkeys(), None)<EOL><DEDENT>else:<EOL><INDENT>key = next(images.iterkeys(), None)<EOL><DEDENT>img = images[key]<EOL>if img is None: return None<EOL>if is_image(img): img = img.get_data()<EOL>return np.asarray(img).shape<EOL>
sub.image_dimensions is a tuple of the default size of an anatomical image for the given
subject.