Merge pull request scipy#16717 from tupui/seed_docstrings

DOC: reformat seed docstrings
rgommers · Jul 29, 2022 · b423701 · b423701
2 parents ef7ef36 + b67df6a
commit b423701
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Showing 10 changed files with 22 additions and 65 deletions.
diff --git a/scipy/_lib/_util.py b/scipy/_lib/_util.py
@@ -178,9 +178,7 @@ def check_random_state(seed):
 
     Parameters
     ----------
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None (or `np.random`), the `numpy.random.RandomState`
         singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used,

diff --git a/scipy/cluster/vq.py b/scipy/cluster/vq.py
@@ -360,9 +360,7 @@ def kmeans(obs, k_or_guess, iter=20, thresh=1e-5, check_finite=True,
         (crashes, non-termination) if the inputs do contain infinities or NaNs.
         Default: True
 
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         Seed for initializing the pseudo-random number generator.
         If `seed` is None (or `numpy.random`), the `numpy.random.RandomState`
         singleton is used.
@@ -666,9 +664,7 @@ def kmeans2(data, k, iter=10, thresh=1e-5, minit='random',
         Disabling may give a performance gain, but may result in problems
         (crashes, non-termination) if the inputs do contain infinities or NaNs.
         Default: True
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         Seed for initializing the pseudo-random number generator.
         If `seed` is None (or `numpy.random`), the `numpy.random.RandomState`
         singleton is used.

diff --git a/scipy/linalg/_sketches.py b/scipy/linalg/_sketches.py
@@ -26,9 +26,7 @@ def cwt_matrix(n_rows, n_columns, seed=None):
         Number of rows of S
     n_columns : int
         Number of columns of S
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None (or `np.random`), the `numpy.random.RandomState`
         singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used,
@@ -73,9 +71,7 @@ def clarkson_woodruff_transform(input_matrix, sketch_size, seed=None):
         Input matrix, of shape ``(n, d)``.
     sketch_size : int
         Number of rows for the sketch.
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None (or `np.random`), the `numpy.random.RandomState`
         singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used,

diff --git a/scipy/optimize/_differentialevolution.py b/scipy/optimize/_differentialevolution.py
@@ -101,9 +101,7 @@ def differential_evolution(func, bounds, args=(), strategy='best1bin',
         denoted by CR. Increasing this value allows a larger number of mutants
         to progress into the next generation, but at the risk of population
         stability.
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None (or `np.random`), the `numpy.random.RandomState`
         singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used,
@@ -471,9 +469,7 @@ class DifferentialEvolutionSolver:
         denoted by CR. Increasing this value allows a larger number of mutants
         to progress into the next generation, but at the risk of population
         stability.
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None (or `np.random`), the `numpy.random.RandomState`
         singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used,

diff --git a/scipy/optimize/_dual_annealing.py b/scipy/optimize/_dual_annealing.py
@@ -486,9 +486,7 @@ def dual_annealing(func, bounds, args=(), maxiter=1000,
         algorithm is in the middle of a local search, this number will be
         exceeded, the algorithm will stop just after the local search is
         done. Default value is 1e7.
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None (or `np.random`), the `numpy.random.RandomState`
         singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used,

diff --git a/scipy/optimize/_optimize.py b/scipy/optimize/_optimize.py
@@ -986,9 +986,7 @@ def check_grad(func, grad, x0, *args, epsilon=_epsilon,
         using `func`. By default it is ``'all'``, in which case, all
         the one hot direction vectors are considered to check `grad`.
         If `func` is a vector valued function then only ``'all'`` can be used.
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None (or `np.random`), the `numpy.random.RandomState`
         singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used,

diff --git a/scipy/stats/_distn_infrastructure.py b/scipy/stats/_distn_infrastructure.py
@@ -1717,9 +1717,7 @@ class rv_continuous(rv_generic):
         subclass has no docstring of its own. Note: `extradoc` exists for
         backwards compatibility and will be removed in SciPy 1.11.0, do not
         use for new subclasses.
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None (or `np.random`), the `numpy.random.RandomState`
         singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used,
@@ -3038,9 +3036,7 @@ class rv_discrete(rv_generic):
         subclass has no docstring of its own. Note: `extradoc` exists for
         backwards compatibility and will be removed in SciPy 1.11.0, do not
         use for new subclasses.
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None (or `np.random`), the `numpy.random.RandomState`
         singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used,

diff --git a/scipy/stats/_kde.py b/scipy/stats/_kde.py
@@ -452,9 +452,7 @@ def resample(self, size=None, seed=None):
             The number of samples to draw.  If not provided, then the size is
             the same as the effective number of samples in the underlying
             dataset.
-        seed : {None, int, `numpy.random.Generator`,
-                `numpy.random.RandomState`}, optional
-
+        seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
             If `seed` is None (or `np.random`), the `numpy.random.RandomState`
             singleton is used.
             If `seed` is an int, a new ``RandomState`` instance is used,

diff --git a/scipy/stats/_multivariate.py b/scipy/stats/_multivariate.py
@@ -722,9 +722,7 @@ def __init__(self, mean=None, cov=1, allow_singular=False, seed=None,
             distribution.
         allow_singular : bool, default: ``False``
             Whether to allow a singular covariance matrix.
-        seed : {None, int, `numpy.random.Generator`,
-                `numpy.random.RandomState`}, optional
-
+        seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
             If `seed` is None (or `np.random`), the `numpy.random.RandomState`
             singleton is used.
             If `seed` is an int, a new ``RandomState`` instance is used,
@@ -1173,9 +1171,7 @@ class matrix_normal_frozen(multi_rv_frozen):
     Parameters
     ----------
     %(_matnorm_doc_default_callparams)s
-    seed : {None, int, `numpy.random.Generator`,
-        `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is `None` the `~np.random.RandomState` singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used, seeded
         with seed.
@@ -2276,9 +2272,7 @@ class wishart_frozen(multi_rv_frozen):
         Degrees of freedom of the distribution
     scale : array_like
         Scale matrix of the distribution
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None (or `np.random`), the `numpy.random.RandomState`
         singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used,
@@ -3267,9 +3261,7 @@ class multinomial_frozen(multi_rv_frozen):
         number of trials
     p: array_like
         probability of a trial falling into each category; should sum to 1
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None (or `np.random`), the `numpy.random.RandomState`
         singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used,
@@ -3489,9 +3481,7 @@ def __init__(self, dim=None, seed=None):
         ----------
         dim : scalar
             Dimension of matrices
-        seed : {None, int, `numpy.random.Generator`,
-                `numpy.random.RandomState`}, optional
-
+        seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
             If `seed` is None (or `np.random`), the `numpy.random.RandomState`
             singleton is used.
             If `seed` is an int, a new ``RandomState`` instance is used,
@@ -3647,9 +3637,7 @@ def __init__(self, dim=None, seed=None):
         ----------
         dim : scalar
             Dimension of matrices
-        seed : {None, int, `numpy.random.Generator`,
-                `numpy.random.RandomState`}, optional
-
+        seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
             If `seed` is None (or `np.random`), the `numpy.random.RandomState`
             singleton is used.
             If `seed` is an int, a new ``RandomState`` instance is used,
@@ -3688,9 +3676,7 @@ class random_correlation_gen(multi_rv_generic):
     ----------
     eigs : 1d ndarray
         Eigenvalues of correlation matrix
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None (or `np.random`), the `numpy.random.RandomState`
         singleton is used.
         If `seed` is an int, a new ``RandomState`` instance is used,
@@ -3904,9 +3890,7 @@ def __init__(self, eigs, seed=None, tol=1e-13, diag_tol=1e-7):
         ----------
         eigs : 1d ndarray
             Eigenvalues of correlation matrix
-        seed : {None, int, `numpy.random.Generator`,
-                `numpy.random.RandomState`}, optional
-
+        seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
             If `seed` is None (or `np.random`), the `numpy.random.RandomState`
             singleton is used.
             If `seed` is an int, a new ``RandomState`` instance is used,
@@ -4069,8 +4053,7 @@ def __init__(self, dim=None, seed=None):
         ----------
         dim : scalar
             Dimension of matrices
-        seed : {None, int, `numpy.random.Generator`,
-                `numpy.random.RandomState`}, optional
+        seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
             If `seed` is None (or `np.random`), the `numpy.random.RandomState`
             singleton is used.
             If `seed` is an int, a new ``RandomState`` instance is used,

diff --git a/scipy/stats/_qmc.py b/scipy/stats/_qmc.py
@@ -67,9 +67,7 @@ def check_random_state(seed=None):
 
     Parameters
     ----------
-    seed : {None, int, `numpy.random.Generator`,
-            `numpy.random.RandomState`}, optional
-
+    seed : {None, int, `numpy.random.Generator`, `numpy.random.RandomState`}, optional
         If `seed` is None the `numpy.random.Generator` singleton is used.
         If `seed` is an int, a new ``Generator`` instance is used,
         seeded with `seed`.