Improve inverse_map description

This commit is contained in:
Johannes Schönberger
2014-09-15 23:54:40 -04:00
parent 15ffd52299
commit ca9a155cf2
+15 -6
View File
@@ -1006,14 +1006,23 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
e.g. `skimage.transform.SimilarityTransform`, or its inverse.
- For 2-D images, you can pass a (3, 3) homogeneous transformation
matrix, e.g. `skimage.transform.SimilarityTransform.params`
- For M-D images, a function that transforms a (N, M) coordinates.
In case of 2-D images this means a function that transforms a
(N, 2) array of ``(x, y)`` coordinates in the *output image* into
their corresponding coordinates in the *source image*. Extra
- For M-D images, a function that transforms a (N, M) coordinate
matrix in the output image to their corresponding coordinates in
the source image, where N is the total number of pixels in the
output image. In case of 2-D images this means a function that
transforms a (N, 2) array of ``(x, y)`` coordinates. Extra
parameters to the function can be specified through `map_args`.
- For M-D images, you can directly pass an array of coordinates.
See `scipy.ndimage.map_coordinates`. Note, that a (3, 3) matrix
is interpreted as a homogeneous transformation matrix.
The first dimension specifies the coordinates in the source image,
while the subsequent dimensions determine the position in the
output image. In case of 2-D images, you need to pass an array of
shape ``(2, rows, cols)``, where `rows` and `cols` determine the
shape of the output image, and the first dimension contains the
``(row, col)`` coordinate in the source image. Note, that a
``(3, 3)`` matrix is interpreted as a homogeneous transformation
matrix, so you cannot interpolate values from a 3-D input, if the
output is of shape ``(3, )``. See `scipy.ndimage.map_coordinates`
for further documentation.
See example section for usage.
map_args : dict, optional