RandN.Core
0.2.0
See the version list below for details.
dotnet add package RandN.Core --version 0.2.0
NuGet\Install-Package RandN.Core -Version 0.2.0
<PackageReference Include="RandN.Core" Version="0.2.0" />
paket add RandN.Core --version 0.2.0
#r "nuget: RandN.Core, 0.2.0"
// Install RandN.Core as a Cake Addin #addin nuget:?package=RandN.Core&version=0.2.0 // Install RandN.Core as a Cake Tool #tool nuget:?package=RandN.Core&version=0.2.0
RandN
RandN is a .NET library for random number generation. It aims to rectify deficiencies in
System.Random
with adaptability and
extensibility in mind. RandN is heavily inspired by the design of the Rust crate
rand, and aims to maintain some level of
compatibility with it.
What's wrong with System.Random?
In short, the algorithm it uses is slow and biased. The API is very rigid and inflexible, and as a result is unsuited for many purposes.
RandN provides a clear and obvious API that is difficult to use incorrectly, unlike the API of
System.Random
. This is accomplished by clearly separating two concepts; generating randomness
with an IRng
, and turning that data into something useful with an IDistribution
.
Docs
The full documentation is available here.
Usage
Install the RandN package from NuGet for most use cases. If you just want to implement an random number generator (ex. you're publishing a package with a new RNG), instead depend on RandN.Core.
Examples
Creating an RNG
using RandN;
// Creates a cryptographically secure RNG
var rng = StandardRng.Create();
// Creates a non-cryptographically secure RNG that's fast and uses less memory
var insecureRng = SmallRng.Create();
A reproducible RNG can also be created by using an algorithm directly:
using RandN.Rngs;
// Use ThreadLocalRng to seed the RNG - this uses a cryptographically secure
// algorithm, so tight loops won't result in similar seeds
var seeder = ThreadLocalRng.Instance;
// Create the seed (Seeds can also be created manually)
var factory = ChaCha.GetChaCha8Factory();
var seed = factory.CreateSeed(seeder);
// Create the RNG from the seed
var rng = factory.Create(seed);
Getting random numbers
Once you have an RNG, you can either use it directly,
var num = rng.NextUInt32();
var bigNum = rng.NextUInt64();
var buffer = new Byte[1000];
rng.Fill(buffer);
or you can use it to sample a distribution:
Uniform.Int32 distribution = Uniform.NewInclusive(42, 54); // [42 - 54]
int answer = distribution.Sample(rng);
Bernoulli weightedCoin = Bernoulli.FromRatio(8, 10); // 80% chance of true
bool probablyHeads = weightedCoin.Sample(rng);
Shuffling a list is also easy:
var list = new List<Int32>() { 1, 2, 3, 4, 5, 6 };
rng.ShuffleInPlace(list);
Any type implementing IRng
can be wrapped with RandomShim
, which can be used as a drop-in
replacement for Random
.
using RandN.Compat;
Random random = RandomShim.Create(rng);
random.Next(2); // returns 0 or 1
Product | Versions Compatible and additional computed target framework versions. |
---|---|
.NET | net5.0 is compatible. net5.0-windows was computed. net6.0 was computed. net6.0-android was computed. net6.0-ios was computed. net6.0-maccatalyst was computed. net6.0-macos was computed. net6.0-tvos was computed. net6.0-windows was computed. net7.0 was computed. net7.0-android was computed. net7.0-ios was computed. net7.0-maccatalyst was computed. net7.0-macos was computed. net7.0-tvos was computed. net7.0-windows was computed. net8.0 was computed. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. |
.NET Core | netcoreapp2.0 was computed. netcoreapp2.1 was computed. netcoreapp2.2 was computed. netcoreapp3.0 was computed. netcoreapp3.1 is compatible. |
.NET Standard | netstandard2.0 is compatible. netstandard2.1 was computed. |
.NET Framework | net461 was computed. net462 was computed. net463 was computed. net47 was computed. net471 was computed. net472 was computed. net48 was computed. net481 was computed. |
MonoAndroid | monoandroid was computed. |
MonoMac | monomac was computed. |
MonoTouch | monotouch was computed. |
Tizen | tizen40 was computed. tizen60 was computed. |
Xamarin.iOS | xamarinios was computed. |
Xamarin.Mac | xamarinmac was computed. |
Xamarin.TVOS | xamarintvos was computed. |
Xamarin.WatchOS | xamarinwatchos was computed. |
-
.NETCoreApp 3.1
- NullGuard.Fody (>= 3.0.0)
-
.NETStandard 2.0
- NullGuard.Fody (>= 3.0.0)
- System.Memory (>= 4.5.4)
-
net5.0
- NullGuard.Fody (>= 3.0.0)
NuGet packages (1)
Showing the top 1 NuGet packages that depend on RandN.Core:
Package | Downloads |
---|---|
RandN
RandN is an alternative library for random number generation, designed to replace the standard Random type. |
GitHub repositories
This package is not used by any popular GitHub repositories.
Version | Downloads | Last updated |
---|---|---|
0.4.0 | 19,984 | 4/4/2023 |
0.4.0-alpha1 | 176 | 4/3/2023 |
0.3.0 | 31,084 | 6/20/2021 |
0.2.0 | 7,377 | 12/21/2020 |
0.1.0 | 4,627 | 6/20/2020 |
0.1.0-beta | 619 | 6/15/2020 |
Version 0.2.0
New APIs:
The marker-interface IPortableDistribution has been created to mark distributions that provide portable and repeatable results across all platforms. Currently, the Bernoulli, the uniform Decimal, the uniform TimeSpan, and all the uniform integer distributions are portable.
Added BlockBuffer32<TBlockRng, TBlockCounter>.BlockLength for consistency with BlockBuffer32.BlockLength.
Updated APIs:
Uniform distributions now live have been grouped into nested classes under the Uniform static class. For example, UniformInt32 has become Uniform.Int32.
Unit interval distributions now live in the Rand.Distributions.UnitInterval namespace and have been grouped into nested classes. For example, UnitInterval.OpenDouble has become UnitInterval.Open.Double.
Method arguments now have null-checks injected by NullGuard.Fody instead of relying on the honor system.
The TRng type parameter of IRngFactory and IReproducibleRngFactory<TRng, TSeed> is now covariant (IRngFactory<out TRng>).
BlockBuffer32<TBlockRng>.Length has been renamed to BlockLength.
Removed APIs:
Removed the Sample extension methods - these were questionably useful, and could be up to four times slower than their non-extension counterpart, IDistribution.Sample.
Bug fixes:
Distributions returning floating point numbers would sometimes sample a number outside the desired range on .NET Framework x86, which can use 80-bit floating point calculations, instead of 64-bit. Results are now forced to 64-bit precision before returning.
BitwiseExtensions.RotateRight now rotates bits right instead of left on .NET Core 3.1+.
All places where overflow is expected is now marked with unchecked.