DOC: Update change log

Author: bashtage

doc/source/change-log.rst

@@ -20,8 +20,9 @@ v1.19.0
 
 - Tested all bit generators out to at least 1TB `using PractRand`_.
 - Added :class:`randomgen.pcg64.PCG64DXSM` which is an alias for :class:`randomgen.pcg64.PCG64`
-  with ``variant="cm-dxsm"`` and ``mode="sequence"``. This is the 2.0 version of PCG64 and
+  with ``variant="dxsm"`` and ``mode="sequence"``. This is the 2.0 version of PCG64 and
   will likely become the default bit generator in NumPy in the near future.
+- Added :class:`randomgen.efiix64.EFIIX64` which is both fast and high-quality.
 - Added :class:`randomgen.sfc.SFC64` which supports generating streams using distinct
   Weyl constants.
 - Added a :class:`randomgen.pcg64.LCG128Mix` which supports setting the LCG multiplier,
@@ -33,8 +34,8 @@ v1.19.0
 - Added a :class:`randomgen.wrapper.UserBitGenerator` which allows bit generators to be written
   in Python or numba.
 - Added :class:`randomgen.generator.ExtendedGenerator` which contains features not in :class:`numpy.random.Generator`.
-- Added  support for the ``DXSM`` and ``CM-DXSM`` variants of :class:`randomgen.pcg64.PCG64`. The
-  ``CM-DXSM`` variant is the official PCG 2.0 generator.
+- Added  support for the ``dxsm`` and ``dxsm-128`` variants of :class:`randomgen.pcg64.PCG64`. The
+  ``dxsm`` variant is the official PCG 2.0 generator.
 - Added support for broadcasting inputs in :class:`randomgen.generator.ExtendedGenerator.multivariate_normal`.
 - Added support for the `++` variant of :class:`randomgen.xoroshiro128.Xoroshiro128`.
 - Fixed a bug the produced incorrect results in :func:`~randomgen.mt19937.MT19937.jumped`.

doc/source/performance.rst

@@ -10,15 +10,15 @@ although :class:`~randomgen.sfc64.SFC64` and :class:`~randomgen.xoshiro256.Xoshi
 are both excellent alternatives.
 
 For very large scale
-applications -- requiring 1,000+ streams,
-:class:`~randomgen.pcg64.PCG64DXSM`, :class:`~randomgen.sfc64.SFC64`
-using distinct Weyl increments (``k``), or one of the cryptography-based generators
-:class:`~randomgen.aes.AESCounter` (if you have hardware acceleration),
+applications -- requiring 1,000+ streams --
+:class:`~randomgen.pcg64.PCG64DXSM` combined with a :class:`~numpy.random.SeedSequence` and ``spawn``,
+:class:`~randomgen.sfc64.SFC64` initialized using distinct Weyl increments (``k``), or one of
+the cryptography-based generators :class:`~randomgen.aes.AESCounter` (if you have hardware acceleration),
 :class:`~randomgen.effix64.EFFIC64`, :class:`~randomgen.speck128.SPECK128`,
 :class:`~randomgen.philox.Philox`, or :class:`~randomgen.hc128.HC128` if you do not)
-are all excellent choices.
+initialized with distinct keys are all excellent choices.
 
-Unless you need backward compatibilyt, there are no longer good reasons to any
+Unless you need backward compatibility, there are no good reasons to use any
 of the Mersenne Twister PRNGS: :class:`~randomgen.mt19937.MT19937`, :class:`~randomgen.mt64.MT64`,
 :class:`~randomgen.sfmt.SFMT`, and :class:`~randomgen.dsfmt.DSFMT`.