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DOC Ensures that sklearn.feature_extraction.image.grid_to_graph passes numpydoc validation #23052

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merged 2 commits into from
Apr 7, 2022
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DOC Ensures that sklearn.feature_extraction.image.grid_to_graph passes numpydoc validation #23052

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b2878f8
removed function from docstring ignore list
henrymooresc Apr 5, 2022
34c3736
fixed docstring errors
henrymooresc Apr 5, 2022
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15 changes: 10 additions & 5 deletions sklearn/feature_extraction/image.py
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Original file line number Diff line number Diff line change
Expand Up @@ -177,26 +177,31 @@ def img_to_graph(img, *, mask=None, return_as=sparse.coo_matrix, dtype=None):
def grid_to_graph(
n_x, n_y, n_z=1, *, mask=None, return_as=sparse.coo_matrix, dtype=int
):
"""Graph of the pixel-to-pixel connections
"""Graph of the pixel-to-pixel connections.

Edges exist if 2 voxels are connected.

Parameters
----------
n_x : int
Dimension in x axis
Dimension in x axis.
n_y : int
Dimension in y axis
Dimension in y axis.
n_z : int, default=1
Dimension in z axis
Dimension in z axis.
mask : ndarray of shape (n_x, n_y, n_z), dtype=bool, default=None
An optional mask of the image, to consider only part of the
pixels.
return_as : np.ndarray or a sparse matrix class, \
default=sparse.coo_matrix
The class to use to build the returned adjacency matrix.
dtype : dtype, default=int
The data of the returned sparse matrix. By default it is int
The data of the returned sparse matrix. By default it is int.

Returns
-------
graph : np.ndarray or a sparse matrix class
The computed adjacency matrix.

Notes
-----
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1 change: 0 additions & 1 deletion sklearn/tests/test_docstrings.py
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Expand Up @@ -27,7 +27,6 @@
"sklearn.decomposition._nmf.non_negative_factorization",
"sklearn.externals._packaging.version.parse",
"sklearn.feature_extraction.image.extract_patches_2d",
"sklearn.feature_extraction.image.grid_to_graph",
"sklearn.feature_extraction.image.img_to_graph",
"sklearn.feature_extraction.text.strip_accents_ascii",
"sklearn.feature_extraction.text.strip_accents_unicode",
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