Commit graph

6 commits

Author SHA1 Message Date
szptvlfn
07cb2bf5f8 Update to 0.13.3.2
ChangeLog:
Changes in 0.13.3.1

  * primitive-0.6 compatibility


Changes in 0.13.3.0

  * Monadic variant of vector shuffle added: `uniformShuffleM`

  * Context on `uniformShuffle` loosened


Changes in 0.13.2.2

  * Fixed crash during gen. initialization on Windows when stderr
    is not available (#36).
2015-12-13 14:10:14 +00:00
agc
286ea2536c Add SHA512 digests for distfiles for math category
Problems found locating distfiles:
	Package dfftpack: missing distfile dfftpack-20001209.tar.gz
	Package eispack: missing distfile eispack-20001130.tar.gz
	Package fftpack: missing distfile fftpack-20001130.tar.gz
	Package linpack: missing distfile linpack-20010510.tar.gz
	Package minpack: missing distfile minpack-20001130.tar.gz
	Package odepack: missing distfile odepack-20001130.tar.gz
	Package py-networkx: missing distfile networkx-1.10.tar.gz
	Package py-sympy: missing distfile sympy-0.7.6.1.tar.gz
	Package quadpack: missing distfile quadpack-20001130.tar.gz

Otherwise, existing SHA1 digests verified and found to be the same on
the machine holding the existing distfiles (morden).  All existing
SHA1 digests retained for now as an audit trail.
2015-11-03 23:33:26 +00:00
szptvlfn
d54e19e0a8 Because this error:
ERROR: hs-primitive>=0.5.4 is not installed; can't buildlink files.
Bump PKGREVISION for hs-primitive-0.5.4.0
2015-05-09 11:22:25 +00:00
szptvlfn
9b07cabdd2 Bump PKGREVISION for hs-vector-0.10.12.1 2014-10-18 21:28:58 +00:00
szptvlfn
9da944d0cd make it clear what package depend on
discussed with wiz@.
2014-08-29 14:08:38 +00:00
szptvlfn
fd2ce923be Import mwc-random-0.13.2.0 as math/hs-mwc-random,
packaged for wip.

This package contains code for generating high quality random numbers that
follow either a uniform or normal distribution. The generated numbers are
suitable for use in statistical applications.

The uniform PRNG uses Marsaglia's MWC256 (also known as MWC8222)
multiply-with-carry generator, which has a period of 2^8222 and fares well
in tests of randomness. It is also extremely fast, between 2 and 3 times
faster than the Mersenne Twister.

Compared to the mersenne-random package, this package has a more convenient
API, is faster, and supports more statistical distributions.
2014-08-14 21:57:25 +00:00