DOC: clean up for moved references, remove ISeedSequence

6 files changed, 37 insertions, 48 deletions

diff --git a/doc/source/reference/random/bit_generators/bitgenerators.rst b/doc/source/reference/random/bit_generators/bitgenerators.rst
deleted file mode 100644
index 11d80e7df..000000000
--- a/doc/source/reference/random/bit_generators/bitgenerators.rst
+++ /dev/null
@@ -1,11 +0,0 @@
-:orphan:
-
-BitGenerator
-------------
-
-.. currentmodule:: numpy.random._bit_generator
-
-.. autosummary::
-   :toctree: generated/
-
-    BitGenerator
diff --git a/doc/source/reference/random/bit_generators/index.rst b/doc/source/reference/random/bit_generators/index.rst
index e4646dce5..c5b6123aa 100644
--- a/doc/source/reference/random/bit_generators/index.rst
+++ b/doc/source/reference/random/bit_generators/index.rst
@@ -1,5 +1,3 @@
-.. _bit_generator:
-
 .. currentmodule:: numpy.random
 
 Bit Generators
@@ -35,14 +33,18 @@ The included BitGenerators are:
 .. _`Random123`: https://www.deshawresearch.com/resources_random123.html
 .. _`SFC author's page`: http://pracrand.sourceforge.net/RNG_engines.txt
 
+.. autosummary::
+   :toctree: generated/
+
+    BitGenerator
+
 .. toctree::
    :maxdepth: 1
 
-   BitGenerator <bitgenerators>
-   MT19937 <mt19937>
-   PCG64 <pcg64>
-   Philox <philox>
-   SFC64 <sfc64>
+    MT19937 <mt19937>
+    PCG64 <pcg64>
+    Philox <philox>
+    SFC64 <sfc64>
 
 Seeding and Entropy
 -------------------
@@ -53,7 +55,7 @@ seed. All of the provided BitGenerators will take an arbitrary-sized
 non-negative integer, or a list of such integers, as a seed. BitGenerators
 need to take those inputs and process them into a high-quality internal state
 for the BitGenerator. All of the BitGenerators in numpy delegate that task to
-`~SeedSequence`, which uses hashing techniques to ensure that even low-quality
+`SeedSequence`, which uses hashing techniques to ensure that even low-quality
 seeds generate high-quality initial states.
 
 .. code-block:: python
@@ -107,6 +109,3 @@ convenient ways.
    :toctree: generated/
 
     SeedSequence
-    _bit_generator.ISeedSequence
-    _bit_generator.ISpawnableSeedSequence
-    _bit_generator.SeedlessSeedSequence
diff --git a/doc/source/reference/random/index.rst b/doc/source/reference/random/index.rst
index b0283f3a7..9b19620d8 100644
--- a/doc/source/reference/random/index.rst
+++ b/doc/source/reference/random/index.rst
@@ -123,7 +123,7 @@ The `Generator` is the user-facing object that is nearly identical to
   rg.random()
 
 One can also instantiate `Generator` directly with a `BitGenerator` instance.
-To use the older `~mt19937.MT19937` algorithm, one can instantiate it directly
+To use the older `MT19937` algorithm, one can instantiate it directly
 and pass it to `Generator`.
 
 .. code-block:: python
diff --git a/doc/source/reference/random/new-or-different.rst b/doc/source/reference/random/new-or-different.rst
index 0f1bf5f7b..23b93de04 100644
--- a/doc/source/reference/random/new-or-different.rst
+++ b/doc/source/reference/random/new-or-different.rst
@@ -10,9 +10,10 @@ What's New or Different
   The Box-Muller method used to produce NumPy's normals is no longer available
   in `Generator`.  It is not possible to reproduce the exact random
   values using ``Generator`` for the normal distribution or any other
-  distribution that relies on the normal such as the `gamma` or
-  `standard_t`. If you require bitwise backward compatible
-  streams, use `RandomState`.
+  distribution that relies on the normal such as the `Generator.gamma` or
+  `Generator.standard_t`. If you require bitwise backward compatible
+  streams, use `RandomState`, i.e. `RandomState.gamma` or
+  `RandomState.standard_t`.
 
 Quick comparison of legacy `mtrand <legacy>`_ to the new `Generator`
 
@@ -20,9 +21,9 @@ Quick comparison of legacy `mtrand <legacy>`_ to the new `Generator`
 Feature            Older Equivalent     Notes
 ------------------ -------------------- -------------
 `~.Generator`      `~.RandomState`      ``Generator`` requires a stream
-                                        source, called a `BitGenerator
-                                        <_bit_generators>` A number of these
-                                        are provided.  ``RandomState`` uses
+                                        source, called a `BitGenerator`
+                                        A number of these are provided.
+                                        ``RandomState`` uses
                                         the Mersenne Twister `~.MT19937` by
                                         default, but can also be instantiated
                                         with any BitGenerator.
diff --git a/doc/source/reference/random/parallel.rst b/doc/source/reference/random/parallel.rst
index 2f79f22d8..d72d9685e 100644
--- a/doc/source/reference/random/parallel.rst
+++ b/doc/source/reference/random/parallel.rst
@@ -18,10 +18,10 @@ a `~BitGenerator`. It uses hashing techniques to ensure that low-quality seeds
 are turned into high quality initial states (at least, with very high
 probability).
 
-For example, `~mt19937.MT19937` has a state consisting of 624
+For example, `MT19937` has a state consisting of 624
 `uint32` integers. A naive way to take a 32-bit integer seed would be to just set
 the last element of the state to the 32-bit seed and leave the rest 0s. This is
-a valid state for `~mt19937.MT19937`, but not a good one. The Mersenne Twister
+a valid state for `MT19937`, but not a good one. The Mersenne Twister
 algorithm `suffers if there are too many 0s`_. Similarly, two adjacent 32-bit
 integer seeds (i.e. ``12345`` and ``12346``) would produce very similar
 streams.
@@ -91,15 +91,15 @@ territory ([2]_).
 .. [2] In this calculation, we can ignore the amount of numbers drawn from each
        stream. Each of the PRNGs we provide has some extra protection built in
        that avoids overlaps if the `~SeedSequence` pools differ in the
-       slightest bit. `~pcg64.PCG64` has :math:`2^{127}` separate cycles
+       slightest bit. `PCG64` has :math:`2^{127}` separate cycles
        determined by the seed in addition to the position in the
        :math:`2^{128}` long period for each cycle, so one has to both get on or
        near the same cycle *and* seed a nearby position in the cycle.
-       `~philox.Philox` has completely independent cycles determined by the seed.
-       `~sfc64.SFC64` incorporates a 64-bit counter so every unique seed is at
+       `Philox` has completely independent cycles determined by the seed.
+       `SFC64` incorporates a 64-bit counter so every unique seed is at
        least :math:`2^{64}` iterations away from any other seed. And
-       finally, `~mt19937.MT19937` has just an unimaginably huge period. Getting
-       a collision internal to `~SeedSequence` is the way a failure would be
+       finally, `MT19937` has just an unimaginably huge period. Getting
+       a collision internal to `SeedSequence` is the way a failure would be
        observed.
 
 .. _`implements an algorithm`: http://www.pcg-random.org/posts/developing-a-seed_seq-alternative.html
@@ -113,10 +113,10 @@ territory ([2]_).
 Independent Streams
 -------------------
 
-:class:`~philox.Philox` is a counter-based RNG based which generates values by
+`Philox` is a counter-based RNG based which generates values by
 encrypting an incrementing counter using weak cryptographic primitives. The
 seed determines the key that is used for the encryption. Unique keys create
-unique, independent streams. :class:`~philox.Philox` lets you bypass the
+unique, independent streams. `hilox` lets you bypass the
 seeding algorithm to directly set the 128-bit key. Similar, but different, keys
 will still create independent streams.
 
diff --git a/doc/source/reference/random/performance.rst b/doc/source/reference/random/performance.rst
index 2d5fca496..d70dd064a 100644
--- a/doc/source/reference/random/performance.rst
+++ b/doc/source/reference/random/performance.rst
@@ -5,21 +5,21 @@ Performance
 
 Recommendation
 **************
-The recommended generator for general use is :class:`~pcg64.PCG64`. It is
+The recommended generator for general use is `PCG64`. It is
 statistically high quality, full-featured, and fast on most platforms, but
 somewhat slow when compiled for 32-bit processes.
 
-:class:`~philox.Philox` is fairly slow, but its statistical properties have
+`Philox` is fairly slow, but its statistical properties have
 very high quality, and it is easy to get assuredly-independent stream by using
 unique keys. If that is the style you wish to use for parallel streams, or you
 are porting from another system that uses that style, then
-:class:`~philox.Philox` is your choice.
+`Philox` is your choice.
 
-:class:`~sfc64.SFC64` is statistically high quality and very fast. However, it
+`SFC64` is statistically high quality and very fast. However, it
 lacks jumpability. If you are not using that capability and want lots of speed,
 even on 32-bit processes, this is your choice.
 
-:class:`~mt19937.MT19937` `fails some statistical tests`_ and is not especially
+`MT19937` `fails some statistical tests`_ and is not especially
 fast compared to modern PRNGs. For these reasons, we mostly do not recommend
 using it on its own, only through the legacy `~.RandomState` for
 reproducing old results. That said, it has a very long history as a default in
@@ -31,20 +31,20 @@ Timings
 *******
 
 The timings below are the time in ns to produce 1 random value from a
-specific distribution.  The original :class:`~mt19937.MT19937` generator is
+specific distribution.  The original `MT19937` generator is
 much slower since it requires 2 32-bit values to equal the output of the
 faster generators.
 
 Integer performance has a similar ordering.
 
 The pattern is similar for other, more complex generators. The normal
-performance of the legacy :class:`~.RandomState` generator is much
+performance of the legacy `RandomState` generator is much
 lower than the other since it uses the Box-Muller transformation rather
 than the Ziggurat generator. The performance gap for Exponentials is also
 large due to the cost of computing the log function to invert the CDF.
 The column labeled MT19973 is used the same 32-bit generator as
-:class:`~.RandomState` but produces random values using
-:class:`~Generator`.
+`RandomState` but produces random values using
+`Generator`.
 
 .. csv-table::
     :header: ,MT19937,PCG64,Philox,SFC64,RandomState
@@ -61,7 +61,7 @@ The column labeled MT19973 is used the same 32-bit generator as
     Poissons,67.6,52.4,69.2,46.4,78.1
 
 The next table presents the performance in percentage relative to values
-generated by the legacy generator, `RandomState(MT19937())`. The overall
+generated by the legacy generator, ``RandomState(MT19937())``. The overall
 performance was computed using a geometric mean.
 
 .. csv-table::