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[MRG] Added an example to the sklearn.feature_extraction.image.PatchExtractor #12202

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[MRG] Added an example to the sklearn.feature_extraction.image.PatchExtractor #12202

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c8bc3ac
Added an example to the sklearn.feature_extraction.image.PatchExtract…
parul-l Sep 29, 2018
478d403
Used built-in image and intialized class with random_state
parul-l Sep 29, 2018
edb8e00
Removed trailing white space
parul-l Sep 29, 2018
4f11459
Modified patch_size
parul-l Sep 29, 2018
136fad4
Assigned .fit output to self and fixed removed extra spacing
parul-l Oct 4, 2018
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52 changes: 32 additions & 20 deletions sklearn/feature_extraction/image.py
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Expand Up @@ -501,30 +501,42 @@ def transform(self, X):

Examples
--------

>>> import scipy as sp
>>> from sklearn.feature_extraction.image import PatchExtractor
>>> X = np.random.randint(10, size=(2, 2, 2))
>>> X
array([[[5, 0],
[9, 6]],

[[2, 0],
[5, 2]]])

>>> pe = PatchExtractor(patch_size=(2, 1))
>>> pe.fit(X)
>>> pe.transform(X)
array([[[ 5.],
[ 9.]],
>>> X = sp.misc.face()
>>> X.shape
(768, 1024, 3)

[[ 0.],
[ 6.]],
>>> X[0]
array([[121, 112, 131],
[138, 129, 148],
[153, 144, 165],
...,
[119, 126, 74],
[131, 136, 82],
[139, 144, 90]], dtype=uint8)

[[ 2.],
[ 5.]],

[[ 0.],
[ 2.]]])
>>> pe = PatchExtractor(patch_size=(1024, 2), random_state=1234)
>>> pe.fit(X)
>>> X_transform = pe.transform(X)
>>> X_transform[0]
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maybe just show the shape of X_transform? And maybe use a different patch size? this seems strange.

array([[ 121., 112.],
[ 138., 129.],
[ 153., 144.],
...,
[ 119., 126.],
[ 131., 136.],
[ 139., 144.]])

>>> X_transform[1]
array([[ 112., 131.],
[ 129., 148.],
[ 144., 165.],
...,
[ 126., 74.],
[ 136., 82.],
[ 144., 90.]])
"""
self.random_state = check_random_state(self.random_state)
n_images, i_h, i_w = X.shape[:3]
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