DOC: Fix docs

doc/requirements.txt

@@ -1,6 +1,7 @@
 numba>=0.49
 nbsphinx
 sphinx-immaterial
-sphinx>=5
-ipython>=6
-pygments>=2.7.4 # not directly required, pinned by Snyk to avoid a vulnerability
+sphinx>=8
+ipython>=8
+pickleshare
+pygments>=2.7.4 # not directly required, pinned by Snyk to avoid a vulnerability

doc/source/change-log.rst

@@ -140,12 +140,12 @@ 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`
+- 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'``

doc/source/conf.py

@@ -234,14 +234,12 @@
 
 # Example configuration for intersphinx: refer to the Python standard library.
 intersphinx_mapping = {
-    "statsmodels": ("https://www.statsmodels.org/dev/", None),
-    "matplotlib": ("https://matplotlib.org/stable/", None),
-    "scipy": ("https://docs.scipy.org/doc/scipy/", None),
-    "python": ("https://docs.python.org/3/", None),
-    "numpy": ("https://numpy.org/doc/stable/", None),
-    "np": ("https://numpy.org/doc/stable/", None),
-    "pandas": ("https://pandas.pydata.org/pandas-docs/stable/", None),
-    "pd": ("https://pandas.pydata.org/pandas-docs/stable/", None),
+    "statsmodels": ("https://www.statsmodels.org/dev", None),
+    "matplotlib": ("https://matplotlib.org/stable", None),
+    "scipy": ("https://docs.scipy.org/doc/scipy", None),
+    "python": ("https://docs.python.org/3", None),
+    "numpy": ("https://numpy.org/doc/stable", None),
+    "pandas": ("https://pandas.pydata.org/pandas-docs/stable", None),
 }
 
 

doc/source/generator.rst

@@ -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

doc/source/index.rst

@@ -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

doc/source/legacy.rst

@@ -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`.

randomgen/bounded_integers.pyx.in

@@ -249,7 +249,7 @@ cdef object _rand_{{nptype}}(object low, object high, object size,
 
     Returns
     -------
-    out : python scalar or ndarray of np.{{nptype}}
+    out : int or ndarray of np.{{nptype}}
           `size`-shaped array of random integers from the appropriate
           distribution, or a single such random int if `size` not provided.
 

randomgen/dsfmt.pyx

@@ -41,9 +41,6 @@ cdef class DSFMT(BitGenerator):
         ``None`` (the default). If `seed` is ``None``, then 764 32-bit unsigned
         integers are read from ``/dev/urandom`` (or the Windows analog) if
         available. If unavailable, a hash of the time and process ID is used.
-    mode : {None, "sequence"}, optional
-        The seeding mode to use. "sequence" uses a SeedSequence
-        to transforms the seed into an initial state.
 
     Attributes
     ----------

randomgen/entropy.pyx

@@ -117,7 +117,7 @@ def random_entropy(size=None, source="system"):
 
     Returns
     -------
-    entropy : scalar or ndarray
+    entropy : int or ndarray
         Entropy bits in 32-bit unsigned integers. A scalar is returned if size
         is `None`.
 

randomgen/generator.pyx

@@ -194,7 +194,7 @@ cdef class ExtendedGenerator:
 
         Returns
         -------
-        bit_generator : BitGenerator
+        bit_generator : numpy.random.BitGenerator
             The bit generator instance used by the generator
         """
         return self._bit_generator
@@ -239,7 +239,7 @@ cdef class ExtendedGenerator:
 
         Returns
         -------
-        out : uint or ndarray
+        out : integer or ndarray
             Drawn samples.
 
         Notes
@@ -561,7 +561,7 @@ cdef class ExtendedGenerator:
 
         Returns
         -------
-        out : ndarray or scalar
+        out : complex or ndarray
             Drawn samples from the parameterized complex normal distribution.
 
         See Also

randomgen/legacy/bounded_integers.pyx.in

@@ -64,7 +64,7 @@ cdef object _legacy_rand_{{nptype}}(object low, object high, object size,
 
     Returns
     -------
-    out : python scalar or ndarray of np.{{nptype}}
+    out : int or ndarray of np.{{nptype}}
           `size`-shaped array of random integers from the appropriate
           distribution, or a single such random int if `size` not provided.
 

randomgen/wrapper.pyx

@@ -36,9 +36,7 @@ cdef object raw_32_to_double(object func):
 
 cdef class UserBitGenerator(BitGenerator):
     """
-    UserBitGenerator(next_raw, bits=64, next_64=None, next_32=None,
-                     next_double=None, state=None, state_getter=None,
-                     state_setter=None)
+    UserBitGenerator(next_raw, bits=64, next_64=None, next_32=None, next_double=None, state=None, state_getter=None, state_setter=None)
 
     Construct a bit generator from  Python functions