8000 Add a docstring example for sparsefuncs functions by divakshu04 · Pull Request #28544 · scikit-learn/scikit-learn · GitHub
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Add a docstring example for sparsefuncs functions #28544

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Add a docstring example for sparsefuncs functions #28544

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62 changes: 62 additions & 0 deletions sklearn/utils/sparsefuncs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -93,6 +93,26 @@ def inplace_csr_row_scale(X, scale):

scale : ndarray of float of shape (n_samples,)
Array of precomputed sample-wise values to use for scaling.

Examples
--------
>>> from sklearn.utils import sparsefuncs
>>> from scipy import sparse
>>> import numpy as np
>>> indptr = np.array([0, 3, 6, 9])
>>> indices = np.array([0, 1, 2, 0, 1, 2, 0, 1, 2])
>>> data = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> scale = np.array([2, 3, 2])
>>> csr = sparse.csr_matrix((data, indices, indptr))
>>> csr.todense()
matrix([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
>>> sparsefuncs.inplace_csr_row_scale(csr, scale)
>>> csr.todense()
matrix([[ 2, 6, 6],
[12, 15, 12],
[14, 16, 18]])
"""
assert scale.shape[0] == X.shape[0]
X.data *= np.repeat(scale, np.diff(X.indptr))
Expand Down Expand Up @@ -394,6 +414,28 @@ def inplace_swap_row_csc(X, m, n):

n : int
Index of the row of X to be swapped.

Examples
--------
>>> import scipy as sparse
>>> import numpy as np
>>> indptr = np.array([0, 2, 4, 4, 5])
>>> indices = np.array([0, 1, 0, 1, 2])
>>> data = np.array([8, 2, 5, 3, 1])
>>> csc = sparse.csc_matrix((data, indices, indptr))
>>> csc.todense()
matrix([[8, 0, 0],
[2, 0, 0],
[5, 0, 0],
[3, 0, 1],
[0, 0, 0]])
>>> inplace_swap_row_csc(csc, 0, 2)
>>> csc.todense()
matrix([[5, 0, 0],
[2, 0, 0],
[8, 0, 0],
[3, 0, 1],
[0, 0, 0]])
"""
for t in [m, n]:
if isinstance(t, np.ndarray):
Expand Down Expand Up @@ -423,6 +465,26 @@ def inplace_swap_row_csr(X, m, n):

n : int
Index of the row of X to be swapped.

Examples
--------
>>> from scipy import sparse
>>> import numpy as np
>>> indptr = np.array([0, 2, 3, 3, 3])
>>> indices = np.array([0, 2, 2])
>>> data = np.array([8, 2, 5])
>>> csr = sparse.csr_matrix((data, indices, indptr))
>>> csr.todense()
matrix([[8, 0, 2],
[0, 0, 5],
[0, 0, 0],
[0, 0, 0]])
>>> inplace_swap_row_csr(csr, 0, 1)
>>> csr.todense()
matrix([[0, 0, 5],
[8, 0, 2],
[0, 0, 0],
[0, 0, 0]])
"""
for t in [m, n]:
if isinstance(t, np.ndarray):
Expand Down
0