MAINT: remove dSFMT

6 files changed, 5 insertions, 51 deletions

diff --git a/doc/source/reference/random/bit_generators/dsfmt.rst b/doc/source/reference/random/bit_generators/dsfmt.rst
deleted file mode 100644
index e7c6dbb31..000000000
--- a/doc/source/reference/random/bit_generators/dsfmt.rst
+++ /dev/null
@@ -1,36 +0,0 @@
-Double SIMD Mersenne Twister (dSFMT) 
-------------------------------------
-
-.. module:: numpy.random.dsfmt
-
-.. currentmodule:: numpy.random.dsfmt
-
-
-.. autoclass:: DSFMT
-	:exclude-members:
-
-Seeding and State
-=================
-
-.. autosummary::
-   :toctree: generated/
-
-   ~DSFMT.seed
-   ~DSFMT.state
-
-Parallel generation
-===================
-.. autosummary::
-   :toctree: generated/
-
-   ~DSFMT.jumped
-
-Extending
-=========
-.. autosummary::
-   :toctree: generated/
-
-   ~DSFMT.cffi
-   ~DSFMT.ctypes
-
-
diff --git a/doc/source/reference/random/bit_generators/index.rst b/doc/source/reference/random/bit_generators/index.rst
index 3a9294bfb..4d3d39ae2 100644
--- a/doc/source/reference/random/bit_generators/index.rst
+++ b/doc/source/reference/random/bit_generators/index.rst
@@ -18,7 +18,6 @@ Stable RNGs
 .. toctree::
    :maxdepth: 1
 
-   DSFMT <dsfmt>
    MT19937 <mt19937>
    PCG32 <pcg32>
    PCG64 <pcg64>
diff --git a/doc/source/reference/random/index.rst b/doc/source/reference/random/index.rst
index 3159f0e1c..42956590a 100644
--- a/doc/source/reference/random/index.rst
+++ b/doc/source/reference/random/index.rst
@@ -153,10 +153,6 @@ The included BitGenerators are:
 * MT19937 - The standard Python BitGenerator. Produces identical results to
   Python using the same seed/state. Adds a `~mt19937.MT19937.jumped` function
   that returns a new generator with state as-if ``2**128`` draws have been made.
-* dSFMT - SSE2 enabled versions of the MT19937 generator.  Theoretically
-  the same, but with a different state and so it is not possible to produce a
-  sequence identical to MT19937. Supports ``jumped`` and so can
-  be used in parallel applications. See the `dSFMT authors' page`_.
 * Xorshiro256** and Xorshiro512** - The most recently introduced XOR,
   shift, and rotate generator. Supports ``jumped`` and so can be used in
   parallel applications. See the documentation for
@@ -167,7 +163,6 @@ The included BitGenerators are:
   arbitrary number of steps or generating independent streams. See the
   `Random123`_ page for more details about this class of bit generators.
 
-.. _`dSFMT authors' page`: http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/
 .. _`PCG author's page`: http://www.pcg-random.org/
 .. _`xorshift, xoroshiro and xoshiro authors' page`:  http://xoroshiro.di.unimi.it/
 .. _`Random123`: https://www.deshawresearch.com/resources_random123.html
diff --git a/doc/source/reference/random/parallel.rst b/doc/source/reference/random/parallel.rst
index ffbaea62b..6c495cc29 100644
--- a/doc/source/reference/random/parallel.rst
+++ b/doc/source/reference/random/parallel.rst
@@ -64,8 +64,6 @@ are listed below.
 +-----------------+-------------------------+-------------------------+-------------------------+
 | BitGenerator    | Period                  |  Jump Size              | Bits                    |
 +=================+=========================+=========================+=========================+
-| DSFMT           | :math:`2^{19937}`       | :math:`2^{128}`         | 53                      |
-+-----------------+-------------------------+-------------------------+-------------------------+
 | MT19937         | :math:`2^{19937}`       | :math:`2^{128}`         | 32                      |
 +-----------------+-------------------------+-------------------------+-------------------------+
 | PCG64           | :math:`2^{128}`         | :math:`2^{64}`          | 64                      |
diff --git a/doc/source/reference/random/performance.py b/doc/source/reference/random/performance.py
index 54165226e..f1dc50c9d 100644
--- a/doc/source/reference/random/performance.py
+++ b/doc/source/reference/random/performance.py
@@ -4,10 +4,10 @@ from timeit import repeat
 import pandas as pd
 
 import numpy as np
-from numpy.random import MT19937, DSFMT, ThreeFry, PCG64, Philox, \
+from numpy.random import MT19937, ThreeFry, PCG64, Philox, \
     Xoshiro256, Xoshiro512
 
-PRNGS = [DSFMT, MT19937, PCG64, Philox, ThreeFry, Xoshiro256, Xoshiro512]
+PRNGS = [MT19937, PCG64, Philox, ThreeFry, Xoshiro256, Xoshiro512]
 
 funcs = OrderedDict()
 integers = 'integers(0, 2**{bits},size=1000000, dtype="uint{bits}")'
diff --git a/doc/source/reference/random/performance.rst b/doc/source/reference/random/performance.rst
index 07867ee07..014db19a3 100644
--- a/doc/source/reference/random/performance.rst
+++ b/doc/source/reference/random/performance.rst
@@ -23,8 +23,7 @@ specific distribution.  The original :class:`~mt19937.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 although `dSFMT` is slower since
-it generates 53-bit floating point values rather than integer values.
+Integer performance has a similar ordering.
 
 The pattern is similar for other, more complex generators. The normal
 performance of the legacy :class:`~mtrand.RandomState` generator is much
@@ -120,9 +119,8 @@ Normal                 115.3        100    135.6      60.3        93.6         1
 ~~~~~~~~~~~~~~
 
 The performance of 64-bit generators on 32-bit Windows is much lower than on 64-bit
-operating systems due to register width. DSFMT uses SSE2 when available, and so is less
-affected by the size of the operating system's register. MT19937, the generator that has been
-in NumPy since 2005, operates on 32-bit integers and so is close to DSFMT.
+operating systems due to register width. MT19937, the generator that has been
+in NumPy since 2005, operates on 32-bit integers.
 
 ===================  =======  =========  =======  ========  ==========  ============
 Distribution           DSFMT    MT19937    PCG64    Philox    ThreeFry    Xoshiro256