Github Actions doc build after commit 548009b

bashtage · Sep 23, 2024 · e31f680 · e31f680
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diff --git a/_modules/index.html b/_modules/index.html
@@ -13,7 +13,7 @@
 
 
 
-        <title>Overview: module code - RandomGen 1.26.1</title>
+        <title>Overview: module code - RandomGen 2.0.0</title>
 
 
 
@@ -36,7 +36,7 @@
         <style>:root{--md-text-font:"Roboto";--md-code-font:"Roboto Mono"}</style>
 
 
-        <link rel="stylesheet" type="text/css" href="../_static/sphinx_immaterial_theme.af531f03affe68837.min.css?v=2410bb73" />
+        <link rel="stylesheet" type="text/css" href="../_static/sphinx_immaterial_theme.3625f807144f53acf.min.css?v=fbfc4466" />
     <script>__md_scope=new URL("..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script>
 
 
@@ -75,7 +75,7 @@
 
 <header class="md-header" data-md-component="header">
   <nav class="md-header__inner md-grid" aria-label="Header">
-    <a href="../index.html" title="RandomGen 1.26.1" class="md-header__button md-logo" aria-label="RandomGen 1.26.1" data-md-component="logo">
+    <a href="../index.html" title="RandomGen 2.0.0" class="md-header__button md-logo" aria-label="RandomGen 2.0.0" data-md-component="logo">
       <img src="../_static/casino.svg" alt="logo">
     </a>
     <label class="md-header__button md-icon" for="__drawer">
@@ -85,7 +85,7 @@
       <div class="md-header__ellipsis">
         <div class="md-header__topic">
           <span class="md-ellipsis">
-            RandomGen 1.26.1
+            RandomGen 2.0.0
           </span>
         </div>
         <div class="md-header__topic" data-md-component="header-topic">
@@ -172,10 +172,10 @@
 
 <nav class="md-nav md-nav--primary" aria-label="Navigation" data-md-level="0">
   <label class="md-nav__title" for="__drawer">
-    <a href="../index.html" title="RandomGen 1.26.1" class="md-nav__button md-logo" aria-label="RandomGen 1.26.1" data-md-component="logo">
+    <a href="../index.html" title="RandomGen 2.0.0" class="md-nav__button md-logo" aria-label="RandomGen 2.0.0" data-md-component="logo">
       <img src="../_static/casino.svg" alt="logo">
     </a>
-    RandomGen 1.26.1
+    RandomGen 2.0.0
   </label>
 
     <div class="md-nav__source">
@@ -496,8 +496,7 @@
 
 
 <h1>All modules for which code is available</h1>
-<ul><li><a href="randomgen/_seed_sequence.html">randomgen._seed_sequence</a></li>
-<li><a href="randomgen/aes.html">randomgen.aes</a></li>
+<ul><li><a href="randomgen/aes.html">randomgen.aes</a></li>
 <li><a href="randomgen/chacha.html">randomgen.chacha</a></li>
 <li><a href="randomgen/common.html">randomgen.common</a></li>
 <li><a href="randomgen/dsfmt.html">randomgen.dsfmt</a></li>
@@ -509,7 +508,6 @@ <h1>All modules for which code is available</h1>
 <li><a href="randomgen/lxm.html">randomgen.lxm</a></li>
 <li><a href="randomgen/mt19937.html">randomgen.mt19937</a></li>
 <li><a href="randomgen/mt64.html">randomgen.mt64</a></li>
-<li><a href="randomgen/mtrand.html">randomgen.mtrand</a></li>
 <li><a href="randomgen/pcg32.html">randomgen.pcg32</a></li>
 <li><a href="randomgen/pcg64.html">randomgen.pcg64</a></li>
 <li><a href="randomgen/philox.html">randomgen.philox</a></li>
@@ -555,7 +553,7 @@ <h1>All modules for which code is available</h1>
 
     Created using
     <a href="https://www.sphinx-doc.org/" target="_blank" rel="noopener">Sphinx</a>
-    7.2.6.
+    8.0.2.
      and
     <a href="https://github.com/jbms/sphinx-immaterial/" target="_blank" rel="noopener">Sphinx-Immaterial</a>
 

diff --git a/_sources/bit_generators/chacha.rst.txt b/_sources/bit_generators/chacha.rst.txt
@@ -16,15 +16,6 @@ Seeding and State
    ~ChaCha.seed
    ~ChaCha.state
 
-Parallel generation
-===================
-.. autosummary::
-   :toctree: generated/
-
-   ~ChaCha.advance
-   ~ChaCha.jump
-   ~ChaCha.jumped
-
 Extending
 =========
 .. autosummary::

diff --git a/_sources/change-log.rst.txt b/_sources/change-log.rst.txt
@@ -3,15 +3,17 @@
 Change Log
 ----------
 
-.. container:: admonition danger
-
-  .. raw:: html
-
-      <p class="admonition-title"> Deprecated </p>
-
-  ``Generator`` and ``RandomState`` were **REMOVED** in 1.23.
-  You should be using :class:`numpy.random.Generator` or
-  :class:`numpy.random.RandomState` which are maintained. 
+v2.0.0
+======
+- Final compatibility with NumPy 2
+- Minimum NumPy is now 1.22.3.
+- Removed ``"legacy"`` seeding in favor of using :class:`~numpy.random.SeedSequence`.
+- Removed the vendored copy of ``SeedSequence``.
+- Deprecated using the ``mode`` keyword argument to set the seed mode, since only ``SeedSequences`` are supported.
+- Changed ``randomgen.common.BitGenerator`` to inherit from ``numpy.random.BitGenerator`` so that
+  numpy will recognize these as ``BitGenerators``.
+- Removed C distribution functions that are available in NumPy (see libnpyrandom)`.
+- General code cleanup and modernization.
 
 v1.26.1
 =======
@@ -54,7 +56,7 @@ v1.20.2
   :class:`~randomgen.mt19937.MT19937`, :class:`~randomgen.philox.Philox`, and
   :class:`~randomgen.sfc.SFC64`. When using this mode, the sequence generated is
   guaranteed to match the sequence produced using the NumPy implementations as long as
-  a :class:`~randomgen.seed_sequence.SeedSequence` or :class:`numpy.random.SeedSequence`
+  a ``randomgen.seed_sequence.SeedSequence`` or :class:`numpy.random.SeedSequence`
   is used with the same initial seed values.
 - Added :func:`~randomgen.generator.ExtendedGenerator.random` with support for
   ``dtype="longdouble"`` to produce extended precision random floats.
@@ -139,13 +141,13 @@ v1.18.0
 =======
 - ``choice`` pulled in upstream performance improvement that
   use a hash set when choosing without replacement and without user-provided probabilities.
-- Added support for :class:`~randomgen.seed_sequence.SeedSequence` (and NumPy's ``SeedSequence``).
-- Fixed a bug that affected both :class:`~randomgen.generator.Generator.randint`
+- Added support for ``randomgen.seed_sequence.SeedSequence`` (and NumPy's :class:`~numpy.random.SeedSequence`).
+- Fixed a bug that affected both ``randomgen.generator.Generator.randint``
   in ``Generator`` and ``randint``
   in  ``RandomState`` when ``high=2**32``.  This value is inbounds for
   a 32-bit unsigned closed interval generator, and so  should have been redirected to
   a 32-bit generator. It  was erroneously sent to the 64-bit path. The random values produced
-  are fully random but inefficient. This fix breaks the stream in :class:`~randomgen.generator.Generator
+  are fully random but inefficient. This fix breaks the stream in ``randomgen.generator.Generator``
   is the value for ``high`` is used. The fix restores ``RandomState`` to
   NumPy 1.16 compatibility.
   only affects the output if ``dtype`` is ``'int64'``

diff --git a/_sources/evolution.rst.txt b/_sources/evolution.rst.txt
@@ -48,5 +48,5 @@ The main changes are
 * Change ``jump`` which operated in-place to ``jumped`` which returns a new ``BitGenerator``.
 * Rename Basic RNG to bit generator, which impacts the API in multiple places where names
   like ``brng`` and ``basic_rng`` have been replaced by ``bitgen`` or ``bit_generator``.
-* Support for :class:`~randomgen.seed_sequence.SeedSequence` (also support NumPy ``SeedSequence`` instances)
+* Support for ``randomgen.seed_sequence.SeedSequence`` (also support NumPy :class:`~numpy.random.SeedSequence` instances)
 * Removed support for Python 2.7
diff --git a/_sources/generator.rst.txt b/_sources/generator.rst.txt
@@ -9,9 +9,6 @@ Random Generator
 
 .. danger::
 
-   ``Generator`` has been **removed**. You should be using  :class:`numpy.random.Generator`.
+   ``Generator`` has been completely **removed** in randomgen 2.0.0.
+   You should be using  :class:`numpy.random.Generator`.
 
-.. currentmodule:: randomgen.generator
-
-.. autoclass::
-   Generator
diff --git a/_sources/index.rst.txt b/_sources/index.rst.txt
@@ -29,7 +29,7 @@ Seed information is directly passed to the bit generator.
 
 .. code-block:: python
 
-  rg = Generator(AESCounter(12345, mode="sequence"))
+  rg = Generator(AESCounter(12345))
   rg.random()
 
 History

diff --git a/_sources/legacy.rst.txt b/_sources/legacy.rst.txt
@@ -10,10 +10,7 @@ Legacy Random Generation
 
 .. danger::
 
-   ``RandomState`` has been **removed**. You should be using :class:`numpy.random.Generator`,
-   or if you must have backward compatibility with NumPy before 1.17, :class:`numpy.random.RandomState`.
-
-.. currentmodule:: randomgen.mtrand
-
-.. autoclass::
-   RandomState
+   ``RandomState`` has been completely **removed** in randomgen 2.0.0.
+   You should be using :class:`numpy.random.Generator`, or if you must
+   have full stability (e.g., for writing tests) or backward compatibility
+   with NumPy before 1.17, :class:`numpy.random.RandomState`.
diff --git a/_sources/multithreading.rst.txt b/_sources/multithreading.rst.txt
@@ -1,32 +1,33 @@
 Multithreaded Generation
 ========================
 
-The four core distributions all allow existing arrays to be filled using the
-``out`` keyword argument.  Existing arrays need to be contiguous and
-well-behaved (writable and aligned).  Under normal circumstances, arrays
-created using the common constructors such as :meth:`numpy.empty` will satisfy
-these requirements.
+The four core distributions in :class:`~numpy.random.Generator` all allow
+existing arrays to be filled using the ``out`` keyword argument.
+Existing arrays need to be contiguous and well-behaved (writable and aligned).
+Under normal circumstances, arrays created using the common constructors such
+as :func:`numpy.empty` will satisfy these requirements.
 
 This example makes use of Python 3 :mod:`concurrent.futures` to fill an array
 using multiple threads.  Threads are long-lived so that repeated calls do not
 require any additional overheads from thread creation. The underlying PRNG is
-xorshift2014 which is fast, has a long period and supports using ``jumped`` to
+xorshift256 which is fast, has a long period and supports using ``jumped`` to
 advance the state. The random numbers generated are reproducible in the sense
 that the same seed will produce the same outputs.
 
 .. code-block:: ipython
 
-    from randomgen import Xoshiro256
     import multiprocessing
     import concurrent.futures
     import numpy as np
     import warnings
 
-    warnings.filterwarnings("ignore", "Generator", FutureWarning)
+    from numpy.random import Generator
+
+    from randomgen import Xoshiro256
 
     class MultithreadedRNG(object):
         def __init__(self, n, seed=None, threads=None):
-            last_bg = Xoshiro256(seed, mode="sequence")
+            last_bg = Xoshiro256(seed)
             if threads is None:
                 threads = multiprocessing.cpu_count()
             self.threads = threads

diff --git a/_sources/new-or-different.rst.txt b/_sources/new-or-different.rst.txt
@@ -63,96 +63,6 @@ Differences from NumPy (1.17+)
     * :class:`~randomgen.xoshiro256.Xoshiro256`
     * :class:`~randomgen.xoshiro512.Xoshiro512`
 
-.. container:: admonition danger
-
-  .. raw:: html
-
-      <p class="admonition-title"> Deprecated </p>
-
-  ``Generator`` is **deprecated**. You should be using
-  :class:`numpy.random.Generator`.
-
-* randomgen's ``Generator`` continues to expose legacy
-  methods ``random_sample``, ``randint``, ``random_integers``, ``rand``, ``randn``,
-  and ``tomaxint``. **Note**: These should not be used, and their modern replacements are preferred:
-
-  * ``random_sample``, ``rand` → ``random``
-  * ``random_integers``, ``randint`` → ``integers``
-  * ``randn`` → ``standard_normal``
-  * ``tomaxint`` → ``integers`` with ``dtype`` set to ``int``
-
-* randomgen's bit generators remain seedable and the convenience function
-  ``seed` is exposed as part of``Generator``. Additionally, the convenience
-  property ``state`` is available to get or set the state of the underlying bit generator.
-
-* :func:`numpy.random.Generator.multivariate_hypergeometric` was added after
-  ``Generator`` was merged into NumPy and will not be ported over.
-
-* :func:`numpy.random.Generator.shuffle` and :func:`numpy.random.Generator.permutation`
-  support ``axis`` keyword to operator along an axis other than 0.
-
-* ``integers`` supports the keyword argument ``use_masked`` to switch between masked
-  generation of bounded integers and Lemire's superior method.
-
-Differences from NumPy before 1.17
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-* The normal, exponential and gamma generators use 256-step Ziggurat
-  methods which are 2-10 times faster than NumPy's default implementation in
-  ``standard_normal``, ``standard_exponential`` or ``standard_gamma``.
-
-* The Box-Muller used to produce NumPy's normals is no longer available.
-* All bit generators functions to produce doubles, uint64s and
-  uint32s via CTypes (:meth:`~randomgen.xoroshiro128.Xoroshiro128.ctypes`)
-  and CFFI (:meth:`~randomgen.xoroshiro128.Xoroshiro128.cffi`).  This allows
-  the bit generators to be used in numba or in other low-level applications
-* The bit generators can be used in downstream projects via Cython.
-* Optional ``dtype`` argument that accepts ``np.float32`` or ``np.float64``
-  to produce either single or double prevision uniform random variables for
-  select core distributions
-
-  * Uniforms (``random`` and ``rand``)
-  * Normals (``standard_normal`` and ``randn``)
-  * Standard Gammas (``standard_gamma``)
-  * Standard Exponentials (``standard_exponential``)
-
-* Optional ``out`` argument that allows existing arrays to be filled for
-  select core distributions
-
-  * Uniforms (``random``)
-  * Normals (``standard_normal``)
-  * Standard Gammas (``standard_gamma``)
-  * Standard Exponentials (``standard_exponential``)
-
-  This allows multithreading to fill large arrays in chunks using suitable
-  PRNGs in parallel.
-
-
-* ``integers`` supports broadcasting inputs.
-
-* ``integers`` supports drawing from open (default, ``[low, high)``) or closed
-  (``[low, high]``) intervals using the keyword argument
-  ``endpoint``. Closed intervals are simpler to use when the
-  distribution may include the maximum value of a given integer type.
-
-
-* The closed interval is particularly helpful when using arrays since
-  it avoids object-dtype arrays when sampling from the full range.
-
-
-* Support for Lemire’s method of generating uniform integers on an
-  arbitrary interval by setting ``use_masked=True`` in
-  (``integers``).
-
-
-* ``multinomial`` supports multidimensional values of ``n``
-
-
-* ``choice``  is much faster when sampling small amounts from large arrays
-
-
-* ``choice`` supports the ``axis`` keyword to work with multidimensional arrays.
-
-
 * For changes since the previous release, see the :ref:`change-log`
 
 .. _the demonstration notebook: custom-bit-generators.ipynb
diff --git a/_sources/seed_sequence.rst.txt b/_sources/seed_sequence.rst.txt
@@ -1,31 +1,12 @@
 Seed Sequences
 --------------
 
-.. module:: randomgen._seed_sequence
-
-.. currentmodule:: randomgen._seed_sequence
-
 .. note::
 
-  randomgen imports ``SeedSequece`` from NumPy if available, and only falls back to a vendored
-  copy if not.  The correct import location is ``randomgen.seed_sequence`` which handles to
-  selection of the correct ``SeedSequence``.
-
-.. autoclass:: SeedSequence
-
-Using a SeedSequence
-====================
-
-.. autosummary::
-   :toctree: generated/
-
-   ~SeedSequence.generate_state
-   ~SeedSequence.spawn
-
-State
-=====
+  randomgen imports :class:`~numpy.random.SeedSequence` from NumPy. As of version 2.0.0, randomgen does not provide
+  a vendored copy of ``SeedSequence``.
 
-.. autosummary::
-   :toctree: generated/
+.. deprecated:: 2.0.0
 
-   ~SeedSequence.state
+   ``SeedSequence`` is now available in NumPy. Use :class:`~numpy.random.SeedSequence`
+   instead. Importing ``SeedSequence`` from randomgen will be removed in a future version.