# algorithms.resample¶

## Module: algorithms.resample¶

Some simple examples and utility functions for resampling.

## Functions¶

nipy.algorithms.resample.resample(image, target, mapping, shape, order=3, mode='constant', cval=0.0)

Resample image to target CoordinateMap

Use a “world-to-world” mapping mapping and spline interpolation of a order.

Here, “world-to-world” refers to the fact that mapping should be a callable that takes a physical coordinate in “target” and gives a physical coordinate in “image”.

Parameters: image : Image instance image that is to be resampled. target : CoordinateMap coordinate map for output image. mapping : callable or tuple or array transformation from target.function_range to image.coordmap.function_range, i.e. ‘world-to-world mapping’. Can be specified in three ways: a callable, a tuple (A, b) representing the mapping y=dot(A,x)+b or a representation of this mapping as an affine array, in homogeneous coordinates. shape : sequence of int shape of output array, in target.function_domain. order : int, optional what order of interpolation to use in scipy.ndimage. mode : str, optional Points outside the boundaries of the input are filled according to the given mode (‘constant’, ‘nearest’, ‘reflect’ or ‘wrap’). Default is ‘constant’. cval : scalar, optional Value used for points outside the boundaries of the input if mode=’constant’. Default is 0.0. output : Image instance Image has interpolated data and output.coordmap == target.
nipy.algorithms.resample.resample_img2img(source, target, order=3, mode='constant', cval=0.0)

Resample source image to space of target image

This wraps the resample function to resample one image onto another. The output of the function will give an image with shape of the target and data from the source.

Parameters: source : Image Image instance that is to be resampled target : Image Image instance to which source is resampled. The output image will have the same shape as the target, and the same coordmap. order : int, optional What order of interpolation to use in scipy.ndimage. mode : str, optional Points outside the boundaries of the input are filled according to the given mode (‘constant’, ‘nearest’, ‘reflect’ or ‘wrap’). Default is ‘constant’. cval : scalar, optional Value used for points outside the boundaries of the input if mode=’constant’. Default is 0.0. output : Image Image with interpolated data and output.coordmap == target.coordmap

Examples

>>> from nipy.testing import funcfile, anatfile