From 5cb4bda50c90d6f41007be740eab9a09c3823a89 Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Tue, 18 Dec 2018 11:38:50 -0500
Subject: [PATCH 01/18] Finalizes fix for #12202 from abandonned PR by @parul-l

---
 sklearn/feature_extraction/image.py | 41 ++++++++++++++++++++++++++++-
 1 file changed, 40 insertions(+), 1 deletion(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index b6e68537c091c..f6fe284e132f1 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -51,7 +51,7 @@ def _make_edges_3d(n_x, n_y, n_z=1):
 
 
 def _compute_gradient_3d(edges, img):
-    n_x, n_y, n_z = img.shape
+    _, n_y, n_z = img.shape
     gradient = np.abs(img[edges[0] // (n_y * n_z),
                       (edges[0] % (n_y * n_z)) // n_z,
                       (edges[0] % (n_y * n_z)) % n_z] -
@@ -499,6 +499,45 @@ def transform(self, X):
              `n_patches` is either `n_samples * max_patches` or the total
              number of patches that can be extracted.
 
+        Example
+        --------
+            from sklearn.datasets import load_sample_images
+            from sklearn.feature_extraction import image
+
+            # Use the array data from the second image in this dataset:
+            X = load_sample_images().images[1]
+            print(f'Image shape: {X.shape}')
+
+            pe = image.PatchExtractor(patch_size=(2, 2))
+            pe_fit = pe.fit(X)
+            pe_trans = pe.transform(X)
+
+            print(f'Patches shape: {pe_trans.shape}')
+            print(f'Shapes arrays:\n{pe_trans}')
+
+        output:
+            Image shape: (427, 640, 3)
+            Patches shape: (545706, 2, 2)
+            Shapes arrays:
+            [[[ 2. 19.]
+            [ 3. 18.]]
+
+            [[19. 13.]
+            [18. 13.]]
+
+            [[ 3. 18.]
+            [ 7. 20.]]
+
+            ...
+
+            [[46. 28.]
+            [45. 28.]]
+
+            [[ 8. 45.]
+            [ 9. 43.]]
+
+            [[45. 28.]
+            [43. 27.]]]
         """
         self.random_state = check_random_state(self.random_state)
         n_images, i_h, i_w = X.shape[:3]

From a39baedb9c9b80282886c038263f69370574674e Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Tue, 18 Dec 2018 11:43:01 -0500
Subject: [PATCH 02/18] Completes 12202 fix abandoned by @parul-l

---
 sklearn/feature_extraction/image.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index f6fe284e132f1..9569734603a8d 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -538,6 +538,7 @@ def transform(self, X):
 
             [[45. 28.]
             [43. 27.]]]
+            
         """
         self.random_state = check_random_state(self.random_state)
         n_images, i_h, i_w = X.shape[:3]

From a5b73bbf4be75d0dd243031fa25202e7cbb7658e Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Tue, 18 Dec 2018 11:51:50 -0500
Subject: [PATCH 03/18] Completes 12202 fix abandoned by @parul-l

---
 sklearn/feature_extraction/image.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index 9569734603a8d..e33acf6ed48e8 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -537,8 +537,7 @@ def transform(self, X):
             [ 9. 43.]]
 
             [[45. 28.]
-            [43. 27.]]]
-            
+            [43. 27.]]] 
         """
         self.random_state = check_random_state(self.random_state)
         n_images, i_h, i_w = X.shape[:3]

From e9f95948fb399b68ad4152dc5b5b7d5ea6366f04 Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Tue, 18 Dec 2018 13:03:47 -0500
Subject: [PATCH 04/18] Extends 12202 fix over feature_extraction/image.py

---
 sklearn/feature_extraction/image.py | 138 ++++++++++++++++------------
 1 file changed, 79 insertions(+), 59 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index e33acf6ed48e8..7ea993d8dabdc 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -339,25 +339,45 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
     Examples
     --------
 
-    >>> from sklearn.feature_extraction import image
-    >>> one_image = np.arange(16).reshape((4, 4))
-    >>> one_image
-    array([[ 0,  1,  2,  3],
-           [ 4,  5,  6,  7],
-           [ 8,  9, 10, 11],
-           [12, 13, 14, 15]])
-    >>> patches = image.extract_patches_2d(one_image, (2, 2))
-    >>> print(patches.shape)
-    (9, 2, 2)
-    >>> patches[0]
-    array([[0, 1],
-           [4, 5]])
-    >>> patches[1]
-    array([[1, 2],
-           [5, 6]])
-    >>> patches[8]
-    array([[10, 11],
-           [14, 15]])
+        from sklearn.datasets import load_sample_images
+        from sklearn.feature_extraction import image
+
+        # Use the array data from the first image in this dataset:
+        one_image = load_sample_images().images[0]
+        print(f'Image shape: {one_image.shape}')
+
+        patches = image.extract_patches_2d(one_image, (2, 2))
+
+        print(f'Patches shape: {patches.shape}')
+
+        print(f'\nPatches 0:\n{patches[0]}')
+        print(f'\nPatches 1:\n{patches[1]}')
+        print(f'\nPatches 800:\n{patches[800]}')
+
+        # output:
+        Image shape: (427, 640, 3)
+        Patches shape: (272214, 2, 2, 3)
+
+        Patches 0:
+        [[[174 201 231]
+        [174 201 231]]
+
+        [[172 199 229]
+        [173 200 230]]]
+
+        Patches 1:
+        [[[174 201 231]
+        [174 201 231]]
+
+        [[173 200 230]
+        [173 200 230]]]
+
+        Patches 800:
+        [[[187 214 243]
+        [188 215 244]]
+
+        [[187 214 243]
+        [188 215 244]]]
     """
     i_h, i_w = image.shape[:2]
     p_h, p_w = patch_size
@@ -461,6 +481,46 @@ class PatchExtractor(BaseEstimator):
         If None, the random number generator is the RandomState instance used
         by `np.random`.
 
+    Examples
+    --------
+            from sklearn.datasets import load_sample_images
+            from sklearn.feature_extraction import image
+
+            # Use the array data from the second image in this dataset:
+            X = load_sample_images().images[1]
+            print(f'Image shape: {X.shape}')
+
+            pe = image.PatchExtractor(patch_size=(2, 2))
+            pe_fit = pe.fit(X)
+            pe_trans = pe.transform(X)
+
+            print(f'Patches shape: {pe_trans.shape}')
+            print(f'Shapes arrays:\n{pe_trans}')
+            
+            # output:
+
+            Image shape: (427, 640, 3)
+            Patches shape: (545706, 2, 2)
+            Shapes arrays:
+            [[[ 2. 19.]
+            [ 3. 18.]]
+
+            [[19. 13.]
+            [18. 13.]]
+
+            [[ 3. 18.]
+            [ 7. 20.]]
+
+            ...
+
+            [[46. 28.]
+            [45. 28.]]
+
+            [[ 8. 45.]
+            [ 9. 43.]]
+
+            [[45. 28.]
+            [43. 27.]]] 
     """
     def __init__(self, patch_size=None, max_patches=None, random_state=None):
         self.patch_size = patch_size
@@ -498,46 +558,6 @@ def transform(self, X):
              The collection of patches extracted from the images, where
              `n_patches` is either `n_samples * max_patches` or the total
              number of patches that can be extracted.
-
-        Example
-        --------
-            from sklearn.datasets import load_sample_images
-            from sklearn.feature_extraction import image
-
-            # Use the array data from the second image in this dataset:
-            X = load_sample_images().images[1]
-            print(f'Image shape: {X.shape}')
-
-            pe = image.PatchExtractor(patch_size=(2, 2))
-            pe_fit = pe.fit(X)
-            pe_trans = pe.transform(X)
-
-            print(f'Patches shape: {pe_trans.shape}')
-            print(f'Shapes arrays:\n{pe_trans}')
-
-        output:
-            Image shape: (427, 640, 3)
-            Patches shape: (545706, 2, 2)
-            Shapes arrays:
-            [[[ 2. 19.]
-            [ 3. 18.]]
-
-            [[19. 13.]
-            [18. 13.]]
-
-            [[ 3. 18.]
-            [ 7. 20.]]
-
-            ...
-
-            [[46. 28.]
-            [45. 28.]]
-
-            [[ 8. 45.]
-            [ 9. 43.]]
-
-            [[45. 28.]
-            [43. 27.]]] 
         """
         self.random_state = check_random_state(self.random_state)
         n_images, i_h, i_w = X.shape[:3]

From 35da14ab5fd279c1833c6ff7e6863ad9f4e4a81c Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Tue, 18 Dec 2018 13:19:26 -0500
Subject: [PATCH 05/18] Closes #12202; white space removal

---
 sklearn/feature_extraction/image.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index 7ea993d8dabdc..5acececcd987c 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -520,7 +520,7 @@ class PatchExtractor(BaseEstimator):
             [ 9. 43.]]
 
             [[45. 28.]
-            [43. 27.]]] 
+            [43. 27.]]]
     """
     def __init__(self, patch_size=None, max_patches=None, random_state=None):
         self.patch_size = patch_size

From 0730c7a3927786b6d4ad572736ddba9e8fdc1373 Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Tue, 18 Dec 2018 13:56:54 -0500
Subject: [PATCH 06/18] Closes #12202; white space removal2

---
 sklearn/feature_extraction/image.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index 5acececcd987c..24ca0b31bf68c 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -440,7 +440,6 @@ def reconstruct_from_patches_2d(patches, image_size):
     -------
     image : array, shape = image_size
         the reconstructed image
-
     """
     i_h, i_w = image_size[:2]
     p_h, p_w = patches.shape[1:3]
@@ -496,9 +495,8 @@ class PatchExtractor(BaseEstimator):
 
             print(f'Patches shape: {pe_trans.shape}')
             print(f'Shapes arrays:\n{pe_trans}')
-            
-            # output:
 
+            # output:
             Image shape: (427, 640, 3)
             Patches shape: (545706, 2, 2)
             Shapes arrays:

From f81beda87718223dca2f2554d685279e01d3c107 Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Tue, 18 Dec 2018 14:22:35 -0500
Subject: [PATCH 07/18] Closes #12202; 3.5 compliance; added >>> in docstring
 code.

---
 sklearn/feature_extraction/image.py | 75 ++++++++++++++---------------
 1 file changed, 37 insertions(+), 38 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index 24ca0b31bf68c..dcb6a0a083dba 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -338,21 +338,20 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
 
     Examples
     --------
+        >>> from sklearn.datasets import load_sample_images
+        >>> from sklearn.feature_extraction import image
 
-        from sklearn.datasets import load_sample_images
-        from sklearn.feature_extraction import image
+        >>> # Use the array data from the first image in this dataset:
+        >>> one_image = load_sample_images().images[0]
 
-        # Use the array data from the first image in this dataset:
-        one_image = load_sample_images().images[0]
-        print(f'Image shape: {one_image.shape}')
+        >>> print('Image shape: {}'.format(one_image.shape))
 
-        patches = image.extract_patches_2d(one_image, (2, 2))
+        >>> patches = image.extract_patches_2d(one_image, (2, 2))
 
-        print(f'Patches shape: {patches.shape}')
-
-        print(f'\nPatches 0:\n{patches[0]}')
-        print(f'\nPatches 1:\n{patches[1]}')
-        print(f'\nPatches 800:\n{patches[800]}')
+        >>> print('Patches shape: {}'.format(patches.shape))
+        >>> print('\nPatches 0:\n{}'.format(patches[0]))
+        >>> print('\nPatches 1:\n{}'.format(patches[1]))
+        >>> print('\nPatches 800:\n{}'.format(patches[800]))
 
         # output:
         Image shape: (427, 640, 3)
@@ -482,43 +481,43 @@ class PatchExtractor(BaseEstimator):
 
     Examples
     --------
-            from sklearn.datasets import load_sample_images
-            from sklearn.feature_extraction import image
+        >>> from sklearn.datasets import load_sample_images
+        >>> from sklearn.feature_extraction import image
 
-            # Use the array data from the second image in this dataset:
-            X = load_sample_images().images[1]
-            print(f'Image shape: {X.shape}')
+        >>> # Use the array data from the second image in this dataset:
+        >>> X = load_sample_images().images[1]
+        >>> print(f'Image shape: {X.shape}')
 
-            pe = image.PatchExtractor(patch_size=(2, 2))
-            pe_fit = pe.fit(X)
-            pe_trans = pe.transform(X)
+        >>> pe = image.PatchExtractor(patch_size=(2, 2))
+        >>> pe_fit = pe.fit(X)
+        >>> pe_trans = pe.transform(X)
 
-            print(f'Patches shape: {pe_trans.shape}')
-            print(f'Shapes arrays:\n{pe_trans}')
+        >>> print('Patches shape: {}'.format(pe_trans.shape))
+        >>> print('Shapes arrays:\n{}'.format(pe_trans))
 
-            # output:
-            Image shape: (427, 640, 3)
-            Patches shape: (545706, 2, 2)
-            Shapes arrays:
-            [[[ 2. 19.]
-            [ 3. 18.]]
+        # output:
+        Image shape: (427, 640, 3)
+        Patches shape: (545706, 2, 2)
+        Shapes arrays:
+        [[[ 2. 19.]
+        [ 3. 18.]]
 
-            [[19. 13.]
-            [18. 13.]]
+        [[19. 13.]
+        [18. 13.]]
 
-            [[ 3. 18.]
-            [ 7. 20.]]
+        [[ 3. 18.]
+        [ 7. 20.]]
 
-            ...
+        ...
 
-            [[46. 28.]
-            [45. 28.]]
+        [[46. 28.]
+        [45. 28.]]
 
-            [[ 8. 45.]
-            [ 9. 43.]]
+        [[ 8. 45.]
+        [ 9. 43.]]
 
-            [[45. 28.]
-            [43. 27.]]]
+        [[45. 28.]
+        [43. 27.]]]
     """
     def __init__(self, patch_size=None, max_patches=None, random_state=None):
         self.patch_size = patch_size

From 294ce613309f86ea6db93fd1aef2b18d10c4681e Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Tue, 18 Dec 2018 15:45:13 -0500
Subject: [PATCH 08/18] Closes #12202; indentation discrep.

---
 sklearn/feature_extraction/image.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index dcb6a0a083dba..b8daeeca1794d 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -331,10 +331,10 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
     Returns
     -------
     patches : array, shape = (n_patches, patch_height, patch_width) or
-         (n_patches, patch_height, patch_width, n_channels)
-         The collection of patches extracted from the image, where `n_patches`
-         is either `max_patches` or the total number of patches that can be
-         extracted.
+        (n_patches, patch_height, patch_width, n_channels)
+        The collection of patches extracted from the image, where `n_patches`
+        is either `max_patches` or the total number of patches that can be
+        extracted.
 
     Examples
     --------

From 4f123302fdcf3ffa0c5ffc6bc2eb1fefc6073862 Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Tue, 18 Dec 2018 17:06:32 -0500
Subject: [PATCH 09/18] Closes #12202; indentation discrep.2

---
 sklearn/feature_extraction/image.py | 70 ++++++++++++++---------------
 1 file changed, 35 insertions(+), 35 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index b8daeeca1794d..b54c2f37aabab 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -353,30 +353,30 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
         >>> print('\nPatches 1:\n{}'.format(patches[1]))
         >>> print('\nPatches 800:\n{}'.format(patches[800]))
 
-        # output:
-        Image shape: (427, 640, 3)
-        Patches shape: (272214, 2, 2, 3)
+        >>> # output:
+            Image shape: (427, 640, 3)
+            Patches shape: (272214, 2, 2, 3)
 
-        Patches 0:
-        [[[174 201 231]
-        [174 201 231]]
+            Patches 0:
+            [[[174 201 231]
+            [174 201 231]]
 
-        [[172 199 229]
-        [173 200 230]]]
+            [[172 199 229]
+            [173 200 230]]]
 
-        Patches 1:
-        [[[174 201 231]
-        [174 201 231]]
+            Patches 1:
+            [[[174 201 231]
+            [174 201 231]]
 
-        [[173 200 230]
-        [173 200 230]]]
+            [[173 200 230]
+            [173 200 230]]]
 
-        Patches 800:
-        [[[187 214 243]
-        [188 215 244]]
+            Patches 800:
+            [[[187 214 243]
+            [188 215 244]]
 
-        [[187 214 243]
-        [188 215 244]]]
+            [[187 214 243]
+            [188 215 244]]]
     """
     i_h, i_w = image.shape[:2]
     p_h, p_w = patch_size
@@ -495,29 +495,29 @@ class PatchExtractor(BaseEstimator):
         >>> print('Patches shape: {}'.format(pe_trans.shape))
         >>> print('Shapes arrays:\n{}'.format(pe_trans))
 
-        # output:
-        Image shape: (427, 640, 3)
-        Patches shape: (545706, 2, 2)
-        Shapes arrays:
-        [[[ 2. 19.]
-        [ 3. 18.]]
+        >>> # output:
+            Image shape: (427, 640, 3)
+            Patches shape: (545706, 2, 2)
+            Shapes arrays:
+            [[[ 2. 19.]
+            [ 3. 18.]]
 
-        [[19. 13.]
-        [18. 13.]]
+            [[19. 13.]
+            [18. 13.]]
 
-        [[ 3. 18.]
-        [ 7. 20.]]
+            [[ 3. 18.]
+            [ 7. 20.]]
 
-        ...
+            ...
 
-        [[46. 28.]
-        [45. 28.]]
+            [[46. 28.]
+            [45. 28.]]
 
-        [[ 8. 45.]
-        [ 9. 43.]]
+            [[ 8. 45.]
+            [ 9. 43.]]
 
-        [[45. 28.]
-        [43. 27.]]]
+            [[45. 28.]
+            [43. 27.]]]
     """
     def __init__(self, patch_size=None, max_patches=None, random_state=None):
         self.patch_size = patch_size

From 2a8d782d7e97969c7be7df61d945b80bda1b0809 Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Fri, 21 Dec 2018 13:24:33 -0500
Subject: [PATCH 10/18] Example output formating; @jnotham

---
 sklearn/feature_extraction/image.py | 57 +++++++++++++----------------
 1 file changed, 25 insertions(+), 32 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index b54c2f37aabab..b14489e5224a0 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -345,25 +345,15 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
         >>> one_image = load_sample_images().images[0]
 
         >>> print('Image shape: {}'.format(one_image.shape))
+        Image shape: (427, 640, 3)
 
         >>> patches = image.extract_patches_2d(one_image, (2, 2))
 
         >>> print('Patches shape: {}'.format(patches.shape))
-        >>> print('\nPatches 0:\n{}'.format(patches[0]))
-        >>> print('\nPatches 1:\n{}'.format(patches[1]))
-        >>> print('\nPatches 800:\n{}'.format(patches[800]))
-
-        >>> # output:
-            Image shape: (427, 640, 3)
-            Patches shape: (272214, 2, 2, 3)
-
-            Patches 0:
-            [[[174 201 231]
-            [174 201 231]]
-
-            [[172 199 229]
-            [173 200 230]]]
+        Patches shape: (272214, 2, 2, 3)
 
+        >>> # Here are just two of these patches:
+        >>> print('\nPatches 1:\n{}'.format(patches[1]))
             Patches 1:
             [[[174 201 231]
             [174 201 231]]
@@ -371,6 +361,7 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
             [[173 200 230]
             [173 200 230]]]
 
+        >>> print('\nPatches 800:\n{}'.format(patches[800]))
             Patches 800:
             [[[187 214 243]
             [188 215 244]]
@@ -378,6 +369,7 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
             [[187 214 243]
             [188 215 244]]]
     """
+    
     i_h, i_w = image.shape[:2]
     p_h, p_w = patch_size
 
@@ -486,39 +478,40 @@ class PatchExtractor(BaseEstimator):
 
         >>> # Use the array data from the second image in this dataset:
         >>> X = load_sample_images().images[1]
+
         >>> print(f'Image shape: {X.shape}')
+        Image shape: (427, 640, 3)
 
         >>> pe = image.PatchExtractor(patch_size=(2, 2))
         >>> pe_fit = pe.fit(X)
         >>> pe_trans = pe.transform(X)
 
         >>> print('Patches shape: {}'.format(pe_trans.shape))
-        >>> print('Shapes arrays:\n{}'.format(pe_trans))
+        Patches shape: (545706, 2, 2)
 
-        >>> # output:
-            Image shape: (427, 640, 3)
-            Patches shape: (545706, 2, 2)
-            Shapes arrays:
-            [[[ 2. 19.]
-            [ 3. 18.]]
+        >>> print('Shapes arrays:\n{}'.format(pe_trans))
+        Shapes arrays:
+        [[[ 2. 19.]
+        [ 3. 18.]]
 
-            [[19. 13.]
-            [18. 13.]]
+        [[19. 13.]
+        [18. 13.]]
 
-            [[ 3. 18.]
-            [ 7. 20.]]
+        [[ 3. 18.]
+        [ 7. 20.]]
 
-            ...
+        ...
 
-            [[46. 28.]
-            [45. 28.]]
+        [[46. 28.]
+        [45. 28.]]
 
-            [[ 8. 45.]
-            [ 9. 43.]]
+        [[ 8. 45.]
+        [ 9. 43.]]
 
-            [[45. 28.]
-            [43. 27.]]]
+        [[45. 28.]
+        [43. 27.]]]
     """
+
     def __init__(self, patch_size=None, max_patches=None, random_state=None):
         self.patch_size = patch_size
         self.max_patches = max_patches

From d14b3b6fea16648f40bca6d9971e5cc5f0c65426 Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Fri, 21 Dec 2018 13:53:41 -0500
Subject: [PATCH 11/18] Example output formating; forgot flake8

---
 sklearn/feature_extraction/image.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index b14489e5224a0..d019c781e9f81 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -369,7 +369,7 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
             [[187 214 243]
             [188 215 244]]]
     """
-    
+
     i_h, i_w = image.shape[:2]
     p_h, p_w = patch_size
 

From 3f8b0b1c9cd12c0eb966c8fe46833553ca13f67d Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Sat, 5 Jan 2019 12:40:47 -0500
Subject: [PATCH 12/18] Closes #12202; Removed excessive indentation in
 docstring (#wimlds)

---
 sklearn/feature_extraction/image.py | 44 ++++++++++++++---------------
 1 file changed, 22 insertions(+), 22 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index d019c781e9f81..46587a95b05e4 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -338,36 +338,36 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
 
     Examples
     --------
-        >>> from sklearn.datasets import load_sample_images
-        >>> from sklearn.feature_extraction import image
+    >>> from sklearn.datasets import load_sample_images
+    >>> from sklearn.feature_extraction import image
 
-        >>> # Use the array data from the first image in this dataset:
-        >>> one_image = load_sample_images().images[0]
+    >>> # Use the array data from the first image in this dataset:
+    >>> one_image = load_sample_images().images[0]
 
-        >>> print('Image shape: {}'.format(one_image.shape))
-        Image shape: (427, 640, 3)
+    >>> print('Image shape: {}'.format(one_image.shape))
+    Image shape: (427, 640, 3)
 
-        >>> patches = image.extract_patches_2d(one_image, (2, 2))
+    >>> patches = image.extract_patches_2d(one_image, (2, 2))
 
-        >>> print('Patches shape: {}'.format(patches.shape))
-        Patches shape: (272214, 2, 2, 3)
+    >>> print('Patches shape: {}'.format(patches.shape))
+    Patches shape: (272214, 2, 2, 3)
 
-        >>> # Here are just two of these patches:
-        >>> print('\nPatches 1:\n{}'.format(patches[1]))
-            Patches 1:
-            [[[174 201 231]
-            [174 201 231]]
+    >>> # Here are just two of these patches:
+    >>> print('\nPatches 1:\n{}'.format(patches[1]))
+        Patches 1:
+        [[[174 201 231]
+        [174 201 231]]
 
-            [[173 200 230]
-            [173 200 230]]]
+        [[173 200 230]
+        [173 200 230]]]
 
-        >>> print('\nPatches 800:\n{}'.format(patches[800]))
-            Patches 800:
-            [[[187 214 243]
-            [188 215 244]]
+    >>> print('\nPatches 800:\n{}'.format(patches[800]))
+        Patches 800:
+        [[[187 214 243]
+        [188 215 244]]
 
-            [[187 214 243]
-            [188 215 244]]]
+        [[187 214 243]
+        [188 215 244]]]
     """
 
     i_h, i_w = image.shape[:2]

From 236dafb6104d94d24ef027f72333f5f45a7e4e9d Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Sat, 5 Jan 2019 15:32:47 -0500
Subject: [PATCH 13/18] Closes #12202; Fixed inconsistent indentation in
 docstring (#wimlds)

---
 sklearn/feature_extraction/image.py | 40 ++++++++---------------------
 1 file changed, 11 insertions(+), 29 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index 251e8ecb28804..73707a8d11a8f 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -338,11 +338,7 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
 
     Examples
     --------
-<<<<<<< HEAD
     >>> from sklearn.datasets import load_sample_images
-=======
-    >>> import numpy as np
->>>>>>> 301c18e31038d83e531a33b83b885f01df6e5c63
     >>> from sklearn.feature_extraction import image
 
     >>> # Use the array data from the first image in this dataset:
@@ -352,40 +348,26 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
     Image shape: (427, 640, 3)
 
     >>> patches = image.extract_patches_2d(one_image, (2, 2))
-<<<<<<< HEAD
 
     >>> print('Patches shape: {}'.format(patches.shape))
     Patches shape: (272214, 2, 2, 3)
 
     >>> # Here are just two of these patches:
     >>> print('\nPatches 1:\n{}'.format(patches[1]))
-        Patches 1:
-        [[[174 201 231]
-        [174 201 231]]
+    Patches 1:
+    [[[174 201 231]
+    [174 201 231]]
 
-        [[173 200 230]
-        [173 200 230]]]
+    [[173 200 230]
+    [173 200 230]]]
 
     >>> print('\nPatches 800:\n{}'.format(patches[800]))
-        Patches 800:
-        [[[187 214 243]
-        [188 215 244]]
-
-        [[187 214 243]
-        [188 215 244]]]
-=======
-    >>> patches.shape
-    (9, 2, 2)
-    >>> patches[0]
-    array([[0, 1],
-           [4, 5]])
-    >>> patches[1]
-    array([[1, 2],
-           [5, 6]])
-    >>> patches[8]
-    array([[10, 11],
-           [14, 15]])
->>>>>>> 301c18e31038d83e531a33b83b885f01df6e5c63
+    Patches 800:
+    [[[187 214 243]
+    [188 215 244]]
+
+    [[187 214 243]
+    [188 215 244]]]
     """
 
     i_h, i_w = image.shape[:2]

From 0bbbea4ad2c6ab029be65efa22d99527f4838dae Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Wed, 9 Jan 2019 11:43:09 -0500
Subject: [PATCH 14/18] Closes #12202 (#wimlds); intentation, v3.5 compliance

---
 sklearn/feature_extraction/image.py | 53 +++++++++++++++--------------
 1 file changed, 27 insertions(+), 26 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index 73707a8d11a8f..52c3e859e0b2a 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -432,6 +432,7 @@ def reconstruct_from_patches_2d(patches, image_size):
     image : array, shape = image_size
         the reconstructed image
     """
+    
     i_h, i_w = image_size[:2]
     p_h, p_w = patches.shape[1:3]
     img = np.zeros(image_size)
@@ -473,43 +474,43 @@ class PatchExtractor(BaseEstimator):
 
     Examples
     --------
-        >>> from sklearn.datasets import load_sample_images
-        >>> from sklearn.feature_extraction import image
+    >>> from sklearn.datasets import load_sample_images
+    >>> from sklearn.feature_extraction import image
 
-        >>> # Use the array data from the second image in this dataset:
-        >>> X = load_sample_images().images[1]
+    >>> # Use the array data from the second image in this dataset:
+    >>> X = load_sample_images().images[1]
 
-        >>> print(f'Image shape: {X.shape}')
-        Image shape: (427, 640, 3)
+    >>> print('Image shape: {}'.format(X.shape))
+    Image shape: (427, 640, 3)
 
-        >>> pe = image.PatchExtractor(patch_size=(2, 2))
-        >>> pe_fit = pe.fit(X)
-        >>> pe_trans = pe.transform(X)
+    >>> pe = image.PatchExtractor(patch_size=(2, 2))
+    >>> pe_fit = pe.fit(X)
+    >>> pe_trans = pe.transform(X)
 
-        >>> print('Patches shape: {}'.format(pe_trans.shape))
-        Patches shape: (545706, 2, 2)
+    >>> print('Patches shape: {}'.format(pe_trans.shape))
+    Patches shape: (545706, 2, 2)
 
-        >>> print('Shapes arrays:\n{}'.format(pe_trans))
-        Shapes arrays:
-        [[[ 2. 19.]
-        [ 3. 18.]]
+    >>> print('Shapes arrays:\n{}'.format(pe_trans))
+    Shapes arrays:
+    [[[ 2. 19.]
+    [ 3. 18.]]
 
-        [[19. 13.]
-        [18. 13.]]
+    [[19. 13.]
+    [18. 13.]]
 
-        [[ 3. 18.]
-        [ 7. 20.]]
+    [[ 3. 18.]
+    [ 7. 20.]]
 
-        ...
+    ...
 
-        [[46. 28.]
-        [45. 28.]]
+    [[46. 28.]
+    [45. 28.]]
 
-        [[ 8. 45.]
-        [ 9. 43.]]
+    [[ 8. 45.]
+    [ 9. 43.]]
 
-        [[45. 28.]
-        [43. 27.]]]
+    [[45. 28.]
+    [43. 27.]]]
     """
 
     def __init__(self, patch_size=None, max_patches=None, random_state=None):

From f173bf649cd8b0555ba07b851ab62172aaaf17fe Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Wed, 16 Jan 2019 11:50:25 -0500
Subject: [PATCH 15/18] Closes #12202 (#wimlds); Output format issue solved
 with addition of # doctest: +NORMALIZE_WHITESPACE +DONT_ACCEPT_BLANKLINE
 +ELLIPSIS for print statements.

---
 sklearn/feature_extraction/image.py | 58 +++++++----------------------
 1 file changed, 13 insertions(+), 45 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index 52c3e859e0b2a..98892fa93c584 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -340,34 +340,27 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
     --------
     >>> from sklearn.datasets import load_sample_images
     >>> from sklearn.feature_extraction import image
-
+    >>>
     >>> # Use the array data from the first image in this dataset:
     >>> one_image = load_sample_images().images[0]
-
     >>> print('Image shape: {}'.format(one_image.shape))
     Image shape: (427, 640, 3)
-
+    >>>
     >>> patches = image.extract_patches_2d(one_image, (2, 2))
-
     >>> print('Patches shape: {}'.format(patches.shape))
     Patches shape: (272214, 2, 2, 3)
-
+    >>>
     >>> # Here are just two of these patches:
-    >>> print('\nPatches 1:\n{}'.format(patches[1]))
-    Patches 1:
+    >>> print(patches[1]) # doctest: +NORMALIZE_WHITESPACE +DONT_ACCEPT_BLANKLINE
     [[[174 201 231]
-    [174 201 231]]
-
-    [[173 200 230]
-    [173 200 230]]]
-
-    >>> print('\nPatches 800:\n{}'.format(patches[800]))
-    Patches 800:
+      [174 201 231]]
+     [[173 200 230]
+      [173 200 230]]]
+    >>> print(patches[800]) # doctest: +NORMALIZE_WHITESPACE +DONT_ACCEPT_BLANKLINE
     [[[187 214 243]
-    [188 215 244]]
-
-    [[187 214 243]
-    [188 215 244]]]
+      [188 215 244]]
+     [[187 214 243]
+      [188 215 244]]]
     """
 
     i_h, i_w = image.shape[:2]
@@ -432,7 +425,6 @@ def reconstruct_from_patches_2d(patches, image_size):
     image : array, shape = image_size
         the reconstructed image
     """
-    
     i_h, i_w = image_size[:2]
     p_h, p_w = patches.shape[1:3]
     img = np.zeros(image_size)
@@ -476,41 +468,17 @@ class PatchExtractor(BaseEstimator):
     --------
     >>> from sklearn.datasets import load_sample_images
     >>> from sklearn.feature_extraction import image
-
+    >>>
     >>> # Use the array data from the second image in this dataset:
     >>> X = load_sample_images().images[1]
-
     >>> print('Image shape: {}'.format(X.shape))
     Image shape: (427, 640, 3)
-
+    >>>
     >>> pe = image.PatchExtractor(patch_size=(2, 2))
     >>> pe_fit = pe.fit(X)
     >>> pe_trans = pe.transform(X)
-
     >>> print('Patches shape: {}'.format(pe_trans.shape))
     Patches shape: (545706, 2, 2)
-
-    >>> print('Shapes arrays:\n{}'.format(pe_trans))
-    Shapes arrays:
-    [[[ 2. 19.]
-    [ 3. 18.]]
-
-    [[19. 13.]
-    [18. 13.]]
-
-    [[ 3. 18.]
-    [ 7. 20.]]
-
-    ...
-
-    [[46. 28.]
-    [45. 28.]]
-
-    [[ 8. 45.]
-    [ 9. 43.]]
-
-    [[45. 28.]
-    [43. 27.]]]
     """
 
     def __init__(self, patch_size=None, max_patches=None, random_state=None):

From aeae3b0b14358cd670e2ce167aabf3f0f395ee4a Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Wed, 16 Jan 2019 15:14:02 -0500
Subject: [PATCH 16/18] Closes #12202 (#wimlds); Output format issue solved
 with addition of # doctest: +NORMALIZE_WHITESPACE +DONT_ACCEPT_BLANKLINE for
 print statements.

---
 sklearn/feature_extraction/image.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index 98892fa93c584..8d4ee26d7f392 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -351,18 +351,19 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
     Patches shape: (272214, 2, 2, 3)
     >>>
     >>> # Here are just two of these patches:
-    >>> print(patches[1]) # doctest: +NORMALIZE_WHITESPACE +DONT_ACCEPT_BLANKLINE
+    >>> print(patches[1]) # doctest: +NORMALIZE_WHITESPACE \
+                                     +DONT_ACCEPT_BLANKLINE
     [[[174 201 231]
       [174 201 231]]
      [[173 200 230]
       [173 200 230]]]
-    >>> print(patches[800]) # doctest: +NORMALIZE_WHITESPACE +DONT_ACCEPT_BLANKLINE
+    >>> print(patches[800])# doctest: +NORMALIZE_WHITESPACE \
+                                      +DONT_ACCEPT_BLANKLINE
     [[[187 214 243]
       [188 215 244]]
      [[187 214 243]
       [188 215 244]]]
     """
-
     i_h, i_w = image.shape[:2]
     p_h, p_w = patch_size
 

From e38bca92f5f12cdb98e8cb2550ad40c4673f5fd9 Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Fri, 25 Jan 2019 15:22:37 -0500
Subject: [PATCH 17/18] Closes #12202 (#wimlds); Testing doctest direc.:
 removed DONT_ACCEPT_BLANKLINE (@jnothmam, @reshamas)

---
 sklearn/feature_extraction/image.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index 8d4ee26d7f392..4e6ee8e258d84 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -351,14 +351,12 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
     Patches shape: (272214, 2, 2, 3)
     >>>
     >>> # Here are just two of these patches:
-    >>> print(patches[1]) # doctest: +NORMALIZE_WHITESPACE \
-                                     +DONT_ACCEPT_BLANKLINE
+    >>> print(patches[1]) # doctest: +NORMALIZE_WHITESPACE
     [[[174 201 231]
       [174 201 231]]
      [[173 200 230]
       [173 200 230]]]
-    >>> print(patches[800])# doctest: +NORMALIZE_WHITESPACE \
-                                      +DONT_ACCEPT_BLANKLINE
+    >>> print(patches[800])# doctest: +NORMALIZE_WHITESPACE
     [[[187 214 243]
       [188 215 244]]
      [[187 214 243]

From f9352abd78e17739a6e94f12f3242e206d03d86e Mon Sep 17 00:00:00 2001
From: Cat Chenal <catchenal@gmail.com>
Date: Wed, 30 Jan 2019 13:30:41 -0500
Subject: [PATCH 18/18] Closes #12202 (#wimlds); Removed blank lines in doctest
 example.

---
 sklearn/feature_extraction/image.py | 5 -----
 1 file changed, 5 deletions(-)

diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py
index 4e6ee8e258d84..7bb9e6a14effc 100644
--- a/sklearn/feature_extraction/image.py
+++ b/sklearn/feature_extraction/image.py
@@ -340,16 +340,13 @@ def extract_patches_2d(image, patch_size, max_patches=None, random_state=None):
     --------
     >>> from sklearn.datasets import load_sample_images
     >>> from sklearn.feature_extraction import image
-    >>>
     >>> # Use the array data from the first image in this dataset:
     >>> one_image = load_sample_images().images[0]
     >>> print('Image shape: {}'.format(one_image.shape))
     Image shape: (427, 640, 3)
-    >>>
     >>> patches = image.extract_patches_2d(one_image, (2, 2))
     >>> print('Patches shape: {}'.format(patches.shape))
     Patches shape: (272214, 2, 2, 3)
-    >>>
     >>> # Here are just two of these patches:
     >>> print(patches[1]) # doctest: +NORMALIZE_WHITESPACE
     [[[174 201 231]
@@ -467,12 +464,10 @@ class PatchExtractor(BaseEstimator):
     --------
     >>> from sklearn.datasets import load_sample_images
     >>> from sklearn.feature_extraction import image
-    >>>
     >>> # Use the array data from the second image in this dataset:
     >>> X = load_sample_images().images[1]
     >>> print('Image shape: {}'.format(X.shape))
     Image shape: (427, 640, 3)
-    >>>
     >>> pe = image.PatchExtractor(patch_size=(2, 2))
     >>> pe_fit = pe.fit(X)
     >>> pe_trans = pe.transform(X)