From 8bd846f5ea3bfe6256a7c0d9b9fdc08934de6ddd Mon Sep 17 00:00:00 2001 From: Robert Kern Date: Thu, 20 Apr 2023 00:30:00 -0400 Subject: DOC: fix formatting and references. --- doc/source/reference/random/index.rst | 4 ++-- doc/source/reference/random/new-or-different.rst | 6 +++--- 2 files changed, 5 insertions(+), 5 deletions(-) (limited to 'doc/source') diff --git a/doc/source/reference/random/index.rst b/doc/source/reference/random/index.rst index 10ab7bd46..486ebc000 100644 --- a/doc/source/reference/random/index.rst +++ b/doc/source/reference/random/index.rst @@ -53,7 +53,7 @@ pseudo-randomness was good for in the first place. The pseudo-random number generators implemented in this module are designed for statistical modeling and simulation. They are not suitable for security - or cryptographic purposes. See the :py:module:`secrets` module from the + or cryptographic purposes. See the :py:mod:`secrets` module from the standard library such use cases. Seeds should be large positive integers. `default_rng` can take positive @@ -149,7 +149,7 @@ Concepts Legacy Generator (RandomState) BitGenerators, SeedSequences Upgrading PCG64 with PCG64DXSM - random-compatibility + compatibility Features -------- diff --git a/doc/source/reference/random/new-or-different.rst b/doc/source/reference/random/new-or-different.rst index 3c443025c..9b5bf38e5 100644 --- a/doc/source/reference/random/new-or-different.rst +++ b/doc/source/reference/random/new-or-different.rst @@ -64,11 +64,11 @@ Feature Older Equivalent Notes * `~.Generator.integers` is now the canonical way to generate integer random numbers from a discrete uniform distribution. This replaces both ``randint`` and the deprecated ``random_integers``. -* The ``rand`` and ``randn`` methods are only available through the legacy +* The ``rand`` and ``randn`` methods are only available through the legacy `~.RandomState`. * `Generator.random` is now the canonical way to generate floating-point random numbers, which replaces `RandomState.random_sample`, - `RandomState.sample`, and `RandomState.ranf`. This is consistent with + `sample`, and `ranf`, all of which were aliases. This is consistent with Python's `random.random`. * All bit generators can produce doubles, uint64s and uint32s via CTypes (`~PCG64.ctypes`) and CFFI (`~PCG64.cffi`). @@ -76,7 +76,7 @@ Feature Older Equivalent Notes * The bit generators can be used in downstream projects via Cython. * All bit generators use `SeedSequence` to :ref:`convert seed integers to - initialized states `. + initialized states `. * Optional ``dtype`` argument that accepts ``np.float32`` or ``np.float64`` to produce either single or double precision uniform random variables for select distributions. `~.Generator.integers` accepts a ``dtype`` argument -- cgit v1.2.1