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Merge pull request #740 from ahojnnes/warp-fix
Fix doc string of warp functions
This commit is contained in:
Juan Nunez-Iglesias
@@ -962,8 +962,13 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
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Shape of the output image generated. By default the shape of the input
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image is preserved.
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order : int, optional
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The order of the spline interpolation, default is 3. The order has to
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be in the range 0-5.
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The order of interpolation. The order has to be in the range 0-5:
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* 0: Nearest-neighbor
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* 1: Bi-linear (default)
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* 2: Bi-quadratic
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* 3: Bi-cubic
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* 4: Bi-quartic
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* 5: Bi-quintic
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mode : string, optional
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Points outside the boundaries of the input are filled according
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to the given mode ('constant', 'nearest', 'reflect' or 'wrap').
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@@ -32,8 +32,8 @@ def resize(image, output_shape, order=1, mode='constant', cval=0.):
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Other parameters
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----------------
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order : int, optional
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The order of the spline interpolation, default is 3. The order has to
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be in the range 0-5.
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The order of the spline interpolation, default is 1. The order has to
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be in the range 0-5. See `skimage.transform.warp` for detail.
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mode : string, optional
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Points outside the boundaries of the input are filled according
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to the given mode ('constant', 'nearest', 'reflect' or 'wrap').
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@@ -116,8 +116,8 @@ def rescale(image, scale, order=1, mode='constant', cval=0.):
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Other parameters
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----------------
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order : int, optional
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The order of the spline interpolation, default is 3. The order has to
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be in the range 0-5.
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The order of the spline interpolation, default is 1. The order has to
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be in the range 0-5. See `skimage.transform.warp` for detail.
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mode : string, optional
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Points outside the boundaries of the input are filled according
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to the given mode ('constant', 'nearest', 'reflect' or 'wrap').
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@@ -172,8 +172,8 @@ def rotate(image, angle, resize=False, order=1, mode='constant', cval=0.):
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Other parameters
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----------------
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order : int, optional
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The order of the spline interpolation, default is 3. The order has to
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be in the range 0-5.
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The order of the spline interpolation, default is 1. The order has to
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be in the range 0-5. See `skimage.transform.warp` for detail.
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mode : string, optional
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Points outside the boundaries of the input are filled according
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to the given mode ('constant', 'nearest', 'reflect' or 'wrap').
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@@ -315,8 +315,8 @@ def swirl(image, center=None, strength=1, radius=100, rotation=0,
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Shape of the output image generated. By default the shape of the input
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image is preserved.
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order : int, optional
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The order of the spline interpolation, default is 3. The order has to
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be in the range 0-5.
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The order of the spline interpolation, default is 1. The order has to
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be in the range 0-5. See `skimage.transform.warp` for detail.
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mode : string, optional
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Points outside the boundaries of the input are filled according
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to the given mode ('constant', 'nearest', 'reflect' or 'wrap').
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@@ -40,22 +40,18 @@ def _warp_fast(cnp.ndarray image, cnp.ndarray H, output_shape=None,
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"""Projective transformation (homography).
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Perform a projective transformation (homography) of a
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floating point image, using bi-linear interpolation.
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floating point image, using interpolation.
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For each pixel, given its homogeneous coordinate :math:`\mathbf{x}
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= [x, y, 1]^T`, its target position is calculated by multiplying
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with the given matrix, :math:`H`, to give :math:`H \mathbf{x}`.
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E.g., to rotate by theta degrees clockwise, the matrix should be
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::
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E.g., to rotate by theta degrees clockwise, the matrix should be::
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[[cos(theta) -sin(theta) 0]
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[sin(theta) cos(theta) 0]
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[0 0 1]]
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or, to translate x by 10 and y by 20,
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::
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or, to translate x by 10 and y by 20::
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[[1 0 10]
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[0 1 20]
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@@ -69,12 +65,12 @@ def _warp_fast(cnp.ndarray image, cnp.ndarray H, output_shape=None,
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Transformation matrix H that defines the homography.
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output_shape : tuple (rows, cols), optional
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Shape of the output image generated (default None).
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order : {0, 1}, optional
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order : {0, 1, 2, 3}, optional
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Order of interpolation::
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* 0: Nearest-neighbour interpolation.
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* 1: Bilinear interpolation (default).
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* 2: Biquadratic interpolation.
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* 3: Bicubic interpolation.
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* 0: Nearest-neighbor
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* 1: Bi-linear (default)
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* 2: Bi-quadratic
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* 3: Bi-cubic
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mode : {'constant', 'reflect', 'wrap', 'nearest'}, optional
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How to handle values outside the image borders (default is constant).
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cval : string, optional (default 0)
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@@ -6,11 +6,11 @@ from skimage.util import img_as_float
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def _smooth(image, sigma, mode, cval):
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"""Return image with each channel smoothed by the gaussian filter."""
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"""Return image with each channel smoothed by the Gaussian filter."""
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smoothed = np.empty(image.shape, dtype=np.double)
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if image.ndim == 3: # apply gaussian filter to all dimensions independently
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if image.ndim == 3: # apply Gaussian filter to all dimensions independently
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for dim in range(image.shape[2]):
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ndimage.gaussian_filter(image[..., dim], sigma,
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output=smoothed[..., dim],
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@@ -38,13 +38,13 @@ def pyramid_reduce(image, downscale=2, sigma=None, order=1,
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downscale : float, optional
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Downscale factor.
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sigma : float, optional
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Sigma for gaussian filter. Default is `2 * downscale / 6.0` which
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Sigma for Gaussian filter. Default is `2 * downscale / 6.0` which
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corresponds to a filter mask twice the size of the scale factor that
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covers more than 99% of the gaussian distribution.
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covers more than 99% of the Gaussian distribution.
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order : int, optional
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Order of splines used in interpolation of downsampling. See
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`scipy.ndimage.map_coordinates` for detail.
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mode : {'reflect', 'constant', 'nearest', 'mirror', 'wrap'}, optional
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`skimage.transform.warp` for detail.
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mode : {'reflect', 'constant', 'nearest', 'mirror', 'wrap'}, optional
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The mode parameter determines how the array borders are handled, where
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cval is the value when mode is equal to 'constant'.
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cval : float, optional
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@@ -92,13 +92,13 @@ def pyramid_expand(image, upscale=2, sigma=None, order=1,
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upscale : float, optional
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Upscale factor.
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sigma : float, optional
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Sigma for gaussian filter. Default is `2 * upscale / 6.0` which
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Sigma for Gaussian filter. Default is `2 * upscale / 6.0` which
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corresponds to a filter mask twice the size of the scale factor that
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covers more than 99% of the gaussian distribution.
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covers more than 99% of the Gaussian distribution.
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order : int, optional
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Order of splines used in interpolation of upsampling. See
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`scipy.ndimage.map_coordinates` for detail.
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mode : {'reflect', 'constant', 'nearest', 'mirror', 'wrap'}, optional
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`skimage.transform.warp` for detail.
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mode : {'reflect', 'constant', 'nearest', 'mirror', 'wrap'}, optional
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The mode parameter determines how the array borders are handled, where
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cval is the value when mode is equal to 'constant'.
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cval : float, optional
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@@ -137,7 +137,7 @@ def pyramid_expand(image, upscale=2, sigma=None, order=1,
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def pyramid_gaussian(image, max_layer=-1, downscale=2, sigma=None, order=1,
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mode='reflect', cval=0):
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"""Yield images of the gaussian pyramid formed by the input image.
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"""Yield images of the Gaussian pyramid formed by the input image.
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Recursively applies the `pyramid_reduce` function to the image, and yields
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the downscaled images.
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@@ -157,13 +157,13 @@ def pyramid_gaussian(image, max_layer=-1, downscale=2, sigma=None, order=1,
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downscale : float, optional
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Downscale factor.
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sigma : float, optional
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Sigma for gaussian filter. Default is `2 * downscale / 6.0` which
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Sigma for Gaussian filter. Default is `2 * downscale / 6.0` which
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corresponds to a filter mask twice the size of the scale factor that
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covers more than 99% of the gaussian distribution.
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covers more than 99% of the Gaussian distribution.
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order : int, optional
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Order of splines used in interpolation of downsampling. See
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`scipy.ndimage.map_coordinates` for detail.
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mode : {'reflect', 'constant', 'nearest', 'mirror', 'wrap'}, optional
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`skimage.transform.warp` for detail.
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mode : {'reflect', 'constant', 'nearest', 'mirror', 'wrap'}, optional
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The mode parameter determines how the array borders are handled, where
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cval is the value when mode is equal to 'constant'.
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cval : float, optional
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@@ -238,13 +238,13 @@ def pyramid_laplacian(image, max_layer=-1, downscale=2, sigma=None, order=1,
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downscale : float, optional
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Downscale factor.
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sigma : float, optional
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Sigma for gaussian filter. Default is `2 * downscale / 6.0` which
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Sigma for Gaussian filter. Default is `2 * downscale / 6.0` which
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corresponds to a filter mask twice the size of the scale factor that
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covers more than 99% of the gaussian distribution.
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covers more than 99% of the Gaussian distribution.
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order : int, optional
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Order of splines used in interpolation of downsampling. See
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`scipy.ndimage.map_coordinates` for detail.
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mode : {'reflect', 'constant', 'nearest', 'mirror', 'wrap'}, optional
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`skimage.transform.warp` for detail.
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mode : {'reflect', 'constant', 'nearest', 'mirror', 'wrap'}, optional
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The mode parameter determines how the array borders are handled, where
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cval is the value when mode is equal to 'constant'.
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cval : float, optional
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