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docstring fixes

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Gregory R. Lee
2015-05-15 14:09:03 -04:00
parent 9cb4b4bae6
commit d781fc5774
1 changed files with 13 additions and 13 deletions
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skimage/measure/_structural_similarity.py
+13 -13
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@@ -51,29 +51,29 @@ def structural_similarity(X, Y, win_size=None, gradient=False,
Parameters
----------
X, Y : ndarray
Images.
Image. Any dimensionality.
win_size : int or None
The side-length of the sliding window used in comparison. Must be an
odd value. Default is 11 if `gaussian_weights` is True, 7 otherwise.
gradient : bool
If True, also return the gradient.
dynamic_range : int
Dynamic range of the input image (distance between minimum and maximum
possible values). By default, this is estimated from the image
The dynamic range of the input image (distance between minimum and
maximum possible values). By default, this is estimated from the image
data-type.
multichannel : int or None
If True, treat the last dimension of the array as channels. Similarity
calculations are done independently for each channel then averaged.
Defaults to True only if X is 3D and X.shape[2] == 3.
Defaults to True only if X is 3D and ``X.shape[2] == 3``.
gaussian_weights : bool
If True, each patch (of size win_size) has its mean and variance
If True, each patch (of size `win_size`) has its mean and variance
spatially weighted by a normalized Gaussian kernel of width sigma=1.5.
full : bool
If True, return the full structural similarity image instead of the
mean value
image_content_weighting : bool
If True, weight the ssim mean is spatially weighted by image content as
proposed in Wang and Shang 2006 [3].
proposed in Wang and Shang 2006 [3]_.
Other Parameters
----------------
@@ -81,25 +81,25 @@ def structural_similarity(X, Y, win_size=None, gradient=False,
if True, normalize covariances by N-1 rather than, N where N is the
number of pixels within the sliding window.
K1 : float
algorithm parameter, K1 (small constant, see [1])
algorithm parameter, K1 (small constant, see [1]_)
K2 : float
algorithm parameter, K2 (small constant, see [1])
algorithm parameter, K2 (small constant, see [1]_)
sigma : float
sigma for the Gaussian when `gaussian_weights` is True.
Returns
-------
mssim : float or ndarray
mean structural similarity.
The mean structural similarity over the image.
grad : ndarray
Gradient of the structural similarity index between X and Y [2]. This
is only returned if `gradient` is set to True.
The gradient of the structural similarity index between X and Y [2]_.
This is only returned if `gradient` is set to True.
S : ndarray
Full SSIM image. This is only returned if `full` is set to True.
The full SSIM image. This is only returned if `full` is set to True.
Notes
-----
To exactly match the implementation of Wang et. al. [1], set
To exactly match the implementation of Wang et. al. [1]_, set
`gaussian_weights` to True, `win_size` to 11, and `use_sample_covariance`
to False.