ENH: better docstring and test for warp_coords

This commit is contained in:
James Bergstra
2012-08-21 16:09:47 -04:00
committed by Johannes Schönberger
parent 5cce39a44a
commit c5dc55cd52
3 changed files with 37 additions and 12 deletions
+1 -1
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@@ -3,7 +3,7 @@ from .radon_transform import *
from .finite_radon_transform import *
from ._project import homography as fast_homography
from .integral import *
from ._geometric import (warp, estimate_transform,
from ._geometric import (warp, warp_coords, estimate_transform,
SimilarityTransform, AffineTransform,
ProjectiveTransform, PolynomialTransform)
from ._warps import swirl, homography
+19 -10
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@@ -699,19 +699,28 @@ def matrix_transform(coords, matrix):
def warp_coords(orows, ocols, bands, coord_transform_fn,
dtype='float64'):
"""
Return `coords` ndarray suitable for `scipy.ndimage.map_coordinates`, which will yield an
image of shape (orows, ocols, bands) by drawing from source points according to the
`coord_transform_fn`.
dtype=np.float64):
"""Build the source coordinates for the output pixels of an image warp.
Parameters
----------
orows: number of output rows
ocols: number of output columns
bands: number of color bands (aka channels)
coord_transform_fn: something like GeometricTransform.inverse_map
dtype: dtype for return value (should probably be 'float32' or 'float64')
orows : int
number of output rows
ocols : int
number of output columns
bands : int
number of color bands (aka channels)
coord_transform_fn : callable like GeometricTransform.inverse_map
Return input coordinates for given output coordinates
dtype : np.dtype or string
dtype for return value (sane choices: float32 or float64)
Returns
-------
coords : (orows * ocols, ) array
Coordinates for `scipy.ndimage.map_coordinates`, that will yield
an image of shape (orows, ocols, bands) by drawing from source
points according to the `coord_transform_fn`.
Notes
-----
+17 -1
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@@ -2,7 +2,7 @@ import sys
from numpy.testing import assert_array_almost_equal, run_module_suite
import numpy as np
from skimage.transform import (warp, fast_homography,
from skimage.transform import (warp, warp_coords, fast_homography,
AffineTransform,
ProjectiveTransform,
SimilarityTransform)
@@ -115,5 +115,21 @@ def test_warp_identity():
assert np.all(0 == warped_rgb_lena[:, :, 1])
def test_warp_coords_example():
from skimage import data
from scipy.ndimage import map_coordinates
def shift_right(xy):
print 'xyshape', xy.shape
xy[:, 0] -= 10
return xy
image = data.lena().astype(np.float32)
print 'testing'
print image.dtype, image.shape
coords = warp_coords(512, 512, 3, shift_right)
print 'warp_coords', coords.dtype, coords.shape
warped_image = map_coordinates(coords, image)
if __name__ == "__main__":
run_module_suite()