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Change example scaling. Fix ref in doc.
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@@ -46,11 +46,11 @@ fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(8, 5))
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plt.gray()
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ax[0].imshow(lena)
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ax[0].imshow(lena, vmin=deconvolved.min(), vmax=deconvolved.max())
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ax[0].axis('off')
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ax[0].set_title('Data')
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ax[1].imshow(deconvolved, vmax=lena.max())
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ax[1].imshow(deconvolved)
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ax[1].axis('off')
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ax[1].set_title('Self tuned restoration')
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@@ -153,8 +153,8 @@ def unsupervised_wiener(image, psf, reg=None, user_params=None):
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Return the deconvolution with a Wiener-Hunt approach, where the
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hyperparameters are automatically estimated. The algorithm is a
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stochastic iterative process (Gibbs sampler) described in [1]. See
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also `wiener` function.
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stochastic iterative process (Gibbs sampler) described in ref
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belo]. See also `wiener` function.
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Parameters
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----------
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