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| Name: ghc-random | Distribution: SUSE Linux Enterprise 15 |
| Version: 1.2.1.1 | Vendor: SUSE LLC <https://www.suse.com/> |
| Release: 150500.3.3.2 | Build date: Mon Jan 29 15:45:37 2024 |
| Group: Unspecified | Build host: h01-ch3d |
| Size: 954702 | Source RPM: ghc-random-1.2.1.1-150500.3.3.2.src.rpm |
| Packager: https://www.suse.com/ | |
| Url: https://hackage.haskell.org/package/random | |
| Summary: Pseudo-random number generation | |
This package provides basic pseudo-random number generation, including the ability to split random number generators. == "System.Random": pure pseudo-random number interface In pure code, use 'System.Random.uniform' and 'System.Random.uniformR' from "System.Random" to generate pseudo-random numbers with a pure pseudo-random number generator like 'System.Random.StdGen'. As an example, here is how you can simulate rolls of a six-sided die using 'System.Random.uniformR': >>> let roll = uniformR (1, 6) :: RandomGen g => g -> (Word, g) >>> let rolls = unfoldr (Just . roll) :: RandomGen g => g -> [Word] >>> let pureGen = mkStdGen 42 >>> take 10 (rolls pureGen) :: [Word] [1,1,3,2,4,5,3,4,6,2] See "System.Random" for more details. == "System.Random.Stateful": monadic pseudo-random number interface In monadic code, use 'System.Random.Stateful.uniformM' and 'System.Random.Stateful.uniformRM' from "System.Random.Stateful" to generate pseudo-random numbers with a monadic pseudo-random number generator, or using a monadic adapter. As an example, here is how you can simulate rolls of a six-sided die using 'System.Random.Stateful.uniformRM': >>> let rollM = uniformRM (1, 6) :: StatefulGen g m => g -> m Word >>> let pureGen = mkStdGen 42 >>> runStateGen_ pureGen (replicateM 10 . rollM) :: [Word] [1,1,3,2,4,5,3,4,6,2] The monadic adapter 'System.Random.Stateful.runStateGen_' is used here to lift the pure pseudo-random number generator 'pureGen' into the 'System.Random.Stateful.StatefulGen' context. The monadic interface can also be used with existing monadic pseudo-random number generators. In this example, we use the one provided in the <https://hackage.haskell.org/package/mwc-random mwc-random> package: >>> import System.Random.MWC as MWC >>> let rollM = uniformRM (1, 6) :: StatefulGen g m => g -> m Word >>> monadicGen <- MWC.create >>> replicateM 10 (rollM monadicGen) :: IO [Word] [2,3,6,6,4,4,3,1,5,4] See "System.Random.Stateful" for more details.
BSD-3-Clause
* Sat Sep 30 2023 [email protected]
- Update random to version 1.2.1.1 revision 1.
Upstream has revised the Cabal build instructions on Hackage.
* Mon May 09 2022 [email protected]
- Update random to version 1.2.1.1.
Upstream has not updated the file "CHANGELOG.md" since the last
release.
* Mon Sep 20 2021 [email protected]
- Update random to version 1.2.1.
[#] 1.2.1
* Fix support for ghc-9.2 [#99](https://github.com/haskell/random/pull/99)
* Fix performance regression for ghc-9.0 [#101](https://github.com/haskell/random/pull/101)
* Add `uniformEnumM` and `uniformEnumRM`
* Add `initStdGen` [#103](https://github.com/haskell/random/pull/103)
* Add `globalStdGen` [#117](https://github.com/haskell/random/pull/117)
* Add `runStateGenST_`
* Ensure that default implementation of `ShortByteString` generation uses
unpinned memory. [#116](https://github.com/haskell/random/pull/116)
* Fix [#54](https://github.com/haskell/random/issues/54) with
[#68](https://github.com/haskell/random/pull/68) - if exactly one value in the
range of floating point is infinite, then `uniformRM`/`randomR` returns that
value.
* Add default implementation of `uniformM` that uses `Generic`
[#70](https://github.com/haskell/random/pull/70)
* `Random` instance for `CBool` [#77](https://github.com/haskell/random/pull/77)
* Addition of `TGen` and `TGenM` [#95](https://github.com/haskell/random/pull/95)
* Addition of tuple instances for `Random` up to 7-tuple
[#72](https://github.com/haskell/random/pull/72)
* Thu Jul 15 2021 [email protected]
- Update random to version 1.2.0 revision 6.
Upstream has revised the Cabal build instructions on Hackage.
* Sat Jul 10 2021 [email protected]
- Update random to version 1.2.0 revision 5.
[#] 1.2.0
1. Breaking change which mostly maintains backwards compatibility, see
"Breaking Changes" below.
2. Support for monadic generators e.g. [mwc-random](https://hackage.haskell.org/package/mwc-random).
3. Monadic adapters for pure generators (providing a uniform monadic
interface to pure and monadic generators).
4. Faster in all cases except one by more than x18 (N.B. x18 not 18%) and
some cases (depending on the type) faster by more than x1000 - see
below for benchmarks.
5. Passes a large number of random number test suites:
* [dieharder](http://webhome.phy.duke.edu/~rgb/General/dieharder.php "venerable")
* [TestU01 (SmallCrush, Crush, BigCrush)](http://simul.iro.umontreal.ca/testu01/tu01.html "venerable")
* [PractRand](http://pracrand.sourceforge.net/ "active")
* [gjrand](http://gjrand.sourceforge.net/ "active")
* See [random-quality](https://github.com/tweag/random-quality)
for details on how to do this yourself.
6. Better quality split as judged by these
[tests](https://www.cambridge.org/core/journals/journal-of-functional-programming/article/evaluation-of-splittable-pseudorandom-generators/3EBAA9F14939C5BB5560E32D1A132637). Again
see [random-quality](https://github.com/tweag/random-quality) for
details on how to do this yourself.
7. Unbiased generation of ranges.
8. Updated tests and benchmarks.
9. [Continuous integration](https://travis-ci.org/github/haskell/random).
[#]## Breaking Changes
Version 1.2.0 introduces these breaking changes:
* requires `base >= 4.8` (GHC-7.10)
* `StdGen` is no longer an instance of `Read`
* `randomIO` and `randomRIO` were extracted from the `Random` class into
separate functions
In addition, there may be import clashes with new functions, e.g. `uniform` and
`uniformR`.
[#]## Deprecations
Version 1.2.0 introduces `genWord64`, `genWord32` and similar methods to the
`RandomGen` class. The significantly slower method `next` and its companion
`genRange` are now deprecated.
[#]## Issues Addressed
Issue Number | Description | Comment
- -------------|-------------|--------
[25](https://github.com/haskell/random/issues/25) | The seeds generated by split are not independent | Fixed: changed algorithm to SplitMix, which provides a robust split operation
[26](https://github.com/haskell/random/issues/26) | Add Random instances for tuples | Addressed: added `Uniform` instances for up to 6-tuples
[44](https://github.com/haskell/random/issues/44) | Add Random instance for Natural | Addressed: added UniformRange instance for Natural
[51](https://github.com/haskell/random/issues/51) | Very low throughput | Fixed: see benchmarks below
[53](https://github.com/haskell/random/issues/53) | incorrect distribution of randomR for floating-point numbers | (\*)
[55](https://github.com/haskell/random/issues/55) | System/Random.hs:43:1: warning: [-Wtabs] | Fixed: No more tabs
[58](https://github.com/haskell/random/issues/58) | Why does random for Float and Double produce exactly 24 or 53 bits? | (\*)
[59](https://github.com/haskell/random/issues/59) | read :: StdGen fails for strings longer than 6 | Addressed: StdGen is no longer an instance of Read
[#]### Comments
(\*) 1.2 samples more bits but does not sample every `Float` or
`Double`. There are methods to do this but they have some downsides;
see [here](https://github.com/idontgetoutmuch/random/issues/105) for a
fuller discussion.
[#]# Benchmarks
Here are some benchmarks run on a 3.1 GHz Intel Core i7. The full
benchmarks can be run using e.g. `stack bench`. The benchmarks are
measured in milliseconds per 100,000 generations. In some cases, the
performance is over x1000 times better; the minimum performance
increase for the types listed below is more than x36.
Name | 1.1 Mean | 1.2 Mean
- -----------|----------|----------
Float | 27.819 | 0.305
Double | 50.644 | 0.328
Integer | 42.332 | 0.332
Word | 40.739 | 0.027
Int | 43.847 | 0.028
Char | 17.009 | 0.462
Bool | 17.542 | 0.027
* Thu Dec 17 2020 [email protected]
- disable %{ix86} build
* Mon Aug 31 2020 [email protected]
- Update random to version 1.1 revision 1.
Upstream has revised the Cabal build instructions on Hackage.
* Tue Aug 18 2020 [email protected]
- Replace %setup -q with the more modern %autosetup macro.
* Tue Jun 16 2020 [email protected]
- Re-generate file with latest version of spec-cleaner.
* Fri Nov 08 2019 [email protected]
- Drop obsolete group attributes.
* Sat Oct 20 2018 [email protected]
- Use https URL to refer to bugs.opensuse.org.
* Wed Jul 18 2018 [email protected]
- Cosmetic: replace tabs with blanks, strip trailing white space,
and update copyright headers with spec-cleaner.
* Wed May 16 2018 [email protected]
- Prefer the new %license attribute over %doc.
* Thu Aug 03 2017 [email protected]
- Updated with latest spec-cleaner version 0.9.8-8-geadfbbf.
* Thu Jan 26 2017 [email protected]
- Update to version 1.1 revision 1 with cabal2obs.
* Sun Jul 10 2016 [email protected]
- Update to version 1.1 revision 0 with cabal2obs.
* Thu Apr 09 2015 [email protected]
- update to 1.1
* breaking change to `randomIValInteger` to improve RNG quality and performance
* correct documentation about generated range of Int32 sized values of type Int
* fix memory leaks by using strict fields and strict atomicModifyIORef'
* support for base < 4.6 (which doesnt provide strict atomicModifyIORef')
* fix C type in test suite https://github.com/haskell/random/pull/9
/usr/lib64/ghc-8.10.7/random-1.2.1.1 /usr/lib64/ghc-8.10.7/random-1.2.1.1/libHSrandom-1.2.1.1-9f2WqozEL1a6Li1yjXx21b-ghc8.10.7.so /usr/share/licenses/ghc-random /usr/share/licenses/ghc-random/LICENSE
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