A disabled default is present on this object. To use it, use one of the other constructors or a factory function.
Constructor (RNG instances can only be initialized with a specified seed).
Copying this object is disabled.
A postblit is present on this object, but not explicitly documented in the source.
Provides a copy of this RNG instance with identical internal state.
Range primitives
Jump function, equivalent to 2 ^^ 512 calls to popFront(); can be used to generate 2 ^^ 512 non-overlapping subsequences for parallel computation.
Range primitives
(Re)seeds the generator.
Range primitives
Marks this range as a uniform random number generator
Largest generated value
Smallest generated value (0)
1 import std.array : array; 2 import std.random : isUniformRNG, randomCover, uniform; 3 import std.range : iota, take; 4 import dxorshift.xorshift1024star; 5 6 // xorshift1024* generators must be initialized 7 // with a specified seed 8 auto gen = Xorshift1024star(123456); 9 10 // verify it is indeed a uniform RNG as defined 11 // in the standard library, whether accessed 12 // directly or via a pointer 13 static assert(isUniformRNG!(typeof(gen))); 14 static assert(isUniformRNG!(typeof(&gen))); 15 16 // since the postblit is disabled, we must 17 // pass a pointer to any functionality that 18 // would otherwise copy the RNG by value 19 assert((&gen).take(2).array == [1060672336872339994uL, 20 1269657541839679748uL]); 21 22 // this means, of course, that we must guarantee 23 // the lifetime of the pointer is valid for the 24 // lifetime of any functionality that uses it 25 auto sample = iota(100).randomCover(&gen).array; 26 27 // however, we can pass the RNG as-is to any 28 // functionality that takes it by ref and does 29 // not try to copy it by value 30 auto val = uniform!"[]"(0.0, 1.0, gen); 31 32 // in circumstances where we really want to 33 // copy the RNG state, we can use `dup` 34 auto gen2 = gen.dup; 35 assert((&gen).take(6).array == (&gen2).take(6).array);
This code is ported from the public-domain reference implementation by Sebastiano Vigna, available online at http://xorshift.di.unimi.it/xorshift1024star.c
See also the research paper introducing the xorshift* family of generators: http://vigna.di.unimi.it/ftp/papers/xorshift.pdf
Xorshift* generators extend the basic xorshift generation mechanism by scrambling its output through multiplication by a constant factor, without touching the underlying state. The result is an extremely fast family of generators with very high-quality statistical properties.
The xorshift1024* generator offers a long (2 ^^ 1024 - 1) period, making it suitable for many massively parallel applications, while its speed and quality makes it useful as a good general purpose random number generator.
If 1024 bits of state are too much, then it is suggested to use the Xoroshiro128+ generator instead.