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Merge pull request #564 from ahojnnes/warp-example
DOC: Improve doc strings of geometric transformation functions.
This commit is contained in:
Stefan van der Walt
@@ -493,8 +493,8 @@ class SimilarityTransform(ProjectiveTransform):
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for param in (scale, rotation, translation))
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if params and matrix is not None:
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raise ValueError("You cannot specify the transformation matrix and "
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"the implicit parameters at the same time.")
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raise ValueError("You cannot specify the transformation matrix and"
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" the implicit parameters at the same time.")
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elif matrix is not None:
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if matrix.shape != (3, 3):
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raise ValueError("Invalid shape of transformation matrix.")
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@@ -946,7 +946,7 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
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Parameters
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----------
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image : 2-D array
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image : 2-D or 3-D array
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Input image.
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inverse_map : transformation object, callable ``xy = f(xy, **kwargs)``
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Inverse coordinate map. A function that transforms a (N, 2) array of
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@@ -955,15 +955,16 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
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inverse).
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map_args : dict, optional
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Keyword arguments passed to `inverse_map`.
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output_shape : tuple (rows, cols)
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Shape of the output image generated.
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order : int
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Order of splines used in interpolation. See
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`scipy.ndimage.map_coordinates` for detail.
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mode : string
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How to handle values outside the image borders. See
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`scipy.ndimage.map_coordinates` for detail.
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cval : float
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output_shape : tuple (rows, cols), optional
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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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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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cval : float, optional
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Used in conjunction with mode 'constant', the value outside
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the image boundaries.
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@@ -971,6 +972,7 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
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--------
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Shift an image to the right:
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>>> from skimage.transform import warp
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>>> from skimage import data
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>>> image = data.camera()
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>>>
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@@ -980,6 +982,12 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
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>>>
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>>> warp(image, shift_right)
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Use a geometric transform to warp an image:
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>>> from skimage.transform import SimilarityTransform
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>>> tform = SimilarityTransform(scale=0.1, rotation=0.1)
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>>> warp(image, tform)
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"""
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# Backward API compatibility
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if reverse_map is not None:
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+66
-35
@@ -13,7 +13,7 @@ def resize(image, output_shape, order=1, mode='constant', cval=0.):
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Input image.
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output_shape : tuple or ndarray
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Size of the generated output image `(rows, cols[, dim])`. If `dim` is
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not provided, the number of channels are preserved. In case the number
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not provided, the number of channels is preserved. In case the number
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of input channels does not equal the number of output channels a
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3-dimensional interpolation is applied.
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@@ -24,16 +24,24 @@ 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
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Order of splines used in interpolation. See
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`scipy.ndimage.map_coordinates` for detail.
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mode : string
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How to handle values outside the image borders. See
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`scipy.ndimage.map_coordinates` for detail.
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cval : string
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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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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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cval : float, optional
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Used in conjunction with mode 'constant', the value outside
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the image boundaries.
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Examples
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--------
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>>> from skimage import data
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>>> from skimage.transform import resize
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>>> image = data.camera()
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>>> resize(image, (100, 100)).shape
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(100, 100)
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"""
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rows, cols = output_shape[0], output_shape[1]
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@@ -95,16 +103,26 @@ 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
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Order of splines used in interpolation. See
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`scipy.ndimage.map_coordinates` for detail.
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mode : string
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How to handle values outside the image borders. See
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`scipy.ndimage.map_coordinates` for detail.
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cval : string
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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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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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cval : float, optional
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Used in conjunction with mode 'constant', the value outside
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the image boundaries.
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Examples
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--------
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>>> from skimage import data
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>>> from skimage.transform import resize
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>>> image = data.camera()
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>>> rescale(image, 0.1).shape
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(51, 51)
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>>> rescale(image, 0.5).shape
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(256, 256)
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"""
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try:
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@@ -141,16 +159,28 @@ 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
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Order of splines used in interpolation. See
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`scipy.ndimage.map_coordinates` for detail.
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mode : string
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How to handle values outside the image borders. See
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`scipy.ndimage.map_coordinates` for detail.
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cval : string
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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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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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cval : float, optional
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Used in conjunction with mode 'constant', the value outside
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the image boundaries.
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Examples
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--------
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>>> from skimage import data
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>>> from skimage.transform import rotate
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>>> image = data.camera()
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>>> rotate(image, 2).shape
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(512, 512)
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>>> rotate(image, 2, resize=True).shape
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(530, 530)
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>>> rotate(image, 90, resize=True).shape
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(512, 512)
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"""
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rows, cols = image.shape[0], image.shape[1]
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@@ -211,14 +241,14 @@ def swirl(image, center=None, strength=1, radius=100, rotation=0,
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----------
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image : ndarray
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Input image.
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center : (x,y) tuple or (2,) ndarray
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center : (x,y) tuple or (2,) ndarray, optional
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Center coordinate of transformation.
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strength : float
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strength : float, optional
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The amount of swirling applied.
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radius : float
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radius : float, optional
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The extent of the swirl in pixels. The effect dies out
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rapidly beyond `radius`.
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rotation : float
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rotation : float, optional
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Additional rotation applied to the image.
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Returns
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@@ -228,15 +258,16 @@ def swirl(image, center=None, strength=1, radius=100, rotation=0,
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Other parameters
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----------------
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output_shape : tuple or ndarray
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Size of the generated output image.
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order : int
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Order of splines used in interpolation. See
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`scipy.ndimage.map_coordinates` for detail.
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mode : string
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How to handle values outside the image borders. See
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`scipy.ndimage.map_coordinates` for detail.
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cval : string
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output_shape : tuple (rows, cols), optional
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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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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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cval : float, optional
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Used in conjunction with mode 'constant', the value outside
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the image boundaries.
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@@ -35,8 +35,8 @@ cdef inline void _matrix_transform(double x, double y, double* H, double *x_,
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y_[0] = yy / zz
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def _warp_fast(cnp.ndarray image, cnp.ndarray H, output_shape=None, int order=1,
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mode='constant', double cval=0):
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def _warp_fast(cnp.ndarray image, cnp.ndarray H, output_shape=None,
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int order=1, mode='constant', double cval=0):
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"""Projective transformation (homography).
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Perform a projective transformation (homography) of a
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@@ -75,7 +75,7 @@ def _warp_fast(cnp.ndarray image, cnp.ndarray H, output_shape=None, int order=1,
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* 1: Bilinear interpolation (default).
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* 2: Biquadratic interpolation (default).
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* 3: Bicubic interpolation.
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mode : {'constant', 'reflect', 'wrap'}
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mode : {'constant', 'reflect', 'wrap', 'nearest'}
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How to handle values outside the image borders.
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cval : string
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Used in conjunction with mode 'C' (constant), the value
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