DOC Ensures that svd_flip passes numpydoc validation (#24581)

mansi1597 · thomasjpfan · web-flow · commit 97057d329da1 · 2022-10-11T10:41:58.000-04:00
Co-authored-by: Thomas J. Fan &lt;thomasjpfan@gmail.com&gt;
diff --git a/sklearn/tests/test_docstrings.py b/sklearn/tests/test_docstrings.py
@@ -14,7 +14,6 @@
 FUNCTION_DOCSTRING_IGNORE_LIST = [
     "sklearn.utils.extmath.fast_logdet",
     "sklearn.utils.extmath.randomized_svd",
-    "sklearn.utils.extmath.svd_flip",
     "sklearn.utils.gen_batches",
     "sklearn.utils.metaestimators.if_delegate_has_method",
 ]
diff --git a/sklearn/utils/extmath.py b/sklearn/utils/extmath.py
@@ -740,12 +740,12 @@ def svd_flip(u, v, u_based_decision=True):
     Parameters
     ----------
     u : ndarray
-        u and v are the output of `linalg.svd` or
+        Parameters u and v are the output of `linalg.svd` or
         :func:`~sklearn.utils.extmath.randomized_svd`, with matching inner
         dimensions so one can compute `np.dot(u * s, v)`.
 
     v : ndarray
-        u and v are the output of `linalg.svd` or
+        Parameters u and v are the output of `linalg.svd` or
         :func:`~sklearn.utils.extmath.randomized_svd`, with matching inner
         dimensions so one can compute `np.dot(u * s, v)`.
         The input v should really be called vt to be consistent with scipy's
@@ -756,11 +756,13 @@ def svd_flip(u, v, u_based_decision=True):
         Otherwise, use the rows of v. The choice of which variable to base the
         decision on is generally algorithm dependent.
 
-
     Returns
     -------
-    u_adjusted, v_adjusted : arrays with the same dimensions as the input.
+    u_adjusted : ndarray
+        Array u with adjusted columns and the same dimensions as u.
 
+    v_adjusted : ndarray
+        Array v with adjusted rows and the same dimensions as v.
     """
     if u_based_decision:
         # columns of u, rows of v

Original file line number	Diff line number	Diff line change
`@@ -14,7 +14,6 @@`
`14`	`14`	`FUNCTION_DOCSTRING_IGNORE_LIST = [`
`15`	`15`	`"sklearn.utils.extmath.fast_logdet",`
`16`	`16`	`"sklearn.utils.extmath.randomized_svd",`
`17`		`- "sklearn.utils.extmath.svd_flip",`
`18`	`17`	`"sklearn.utils.gen_batches",`
`19`	`18`	`"sklearn.utils.metaestimators.if_delegate_has_method",`
`20`	`19`	`]`