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std.contracts: added functions pointsTo() std.numeric: minor unittest fixes. std.bitmanip: fixed code bloat issue, reintroduced FloatRep and DoubleRep. std.conv: minor simplification of implementation. std.regexp: added reference to ECMA standard in the documentation. std.getopt: changed return type from bool to void, error is signaled by use of exceptions. std.functional: added unaryFun, binaryFun, adjoin. std.string: updated documentation, changed code to compile with warnings enabled. std.traits: changed FieldTypeTuple; added RepresentationTypeTuple, hasAliasing; fixed bug 1826; added call to flush() from within write; fixed unlisted bug in lines(). std.algorithm: added map, reduce, filter, inPlace, move, swap, overwriteAdjacent, find, findRange, findBoyerMoore, findAdjacent, findAmong, findAmongSorted, canFind, canFindAmong, canFindAmongSorted, count, equal, overlap, min, max, mismatch, EditOp, none, substitute, insert, remove, levenshteinDistance, levenshteinDistanceAndPath, copy, copyIf, iterSwap, swapRanges, reverse, rotate, SwapStrategy, Unstable, Semistable, Stable, eliminate, partition, nthElement, sort, schwartzSort, partialSort, isSorted, makeIndex, schwartzMakeIndex, lowerBound, upperBound, equalRange, canFindSorted. std.thread: fixed so it compiles with warnings enabled. std.file: made getSize() faster under Linux. std.random: fixed so it compiles with warnings enabled; improved function uniform so it deduces type generated from its arguments. std.format: added fixes to make formatting work with const data. std.path: minor documentation changes.
804 lines
22 KiB
D
804 lines
22 KiB
D
// Written in the D programming language
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/**
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Facilities for random number generation. The old-style functions
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$(D_PARAM rand_seed) and $(D_PARAM rand) will soon be deprecated as
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they rely on global state and as such are subjected to various
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thread-related issues.
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The new-style generator objects hold their own state so they are
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immune of threading issues. The generators feature a number of
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well-known and well-documented methods of generating random
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numbers. An overall fast and reliable means to generate random
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numbers is the $(D_PARAM Mt19937) generator, which derives its name
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from "$(LINK2 http://math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html,
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Mersenne Twister) with a period of 2 to the power of 19937". In
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memory-constrained situations,
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$(LINK2 http://en.wikipedia.org/wiki/Linear_congruential_generator,
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linear congruential) generators such as MinstdRand0 and MinstdRand
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might be useful. The standard library provides an alias $(D_PARAM
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Random) for whichever generator it finds the most fit for the
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target environment.
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Example:
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----
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Random gen;
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// Generate a uniformly-distributed integer in the range [0, 15]
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auto i = uniform!(int)(gen, 0, 15);
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// Generate a uniformly-distributed real in the range [0, 100$(RPAREN)
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auto r = uniform!(real)(gen, 0.0L, 100.0L);
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----
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In addition to random number generators, this module features
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distributions, which skew a generator's output statistical
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distribution in various ways. So far the uniform distribution for
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integers and real numbers have been implemented.
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Author:
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$(WEB erdani.org, Andrei Alexandrescu)
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Credits:
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The entire random number library architecture is derived from the
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excellent
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$(LINK2 http://open-std.org/jtc1/sc22/wg21/docs/papers/2007/n2461.pdf,
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C++0X) random number facility proposed by Jens Maurer and contrinuted
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to by researchers at the Fermi laboratory.
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Macros:
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WIKI = Phobos/StdRandom
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*/
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// random.d
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// www.digitalmars.com
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module std.random;
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import std.stdio, std.math, std.c.time, std.traits, std.contracts, std.conv,
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std.algorithm, std.process, std.date;
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// Segments of the code in this file Copyright (c) 1997 by Rick Booth
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// From "Inner Loops" by Rick Booth, Addison-Wesley
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// Work derived from:
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/*
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A C-program for MT19937, with initialization improved 2002/1/26.
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Coded by Takuji Nishimura and Makoto Matsumoto.
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Before using, initialize the state by using init_genrand(seed)
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or init_by_array(init_key, key_length).
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Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions
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are met:
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1. Redistributions of source code must retain the above copyright
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notice, this list of conditions and the following disclaimer.
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2. Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in the
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documentation and/or other materials provided with the distribution.
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3. The names of its contributors may not be used to endorse or promote
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products derived from this software without specific prior written
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permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
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LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
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NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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Any feedback is very welcome.
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http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html
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email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space)
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*/
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version (Win32)
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{
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extern(Windows) int QueryPerformanceCounter(ulong *count);
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}
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version (linux)
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{
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private import std.c.linux.linux;
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}
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/**
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Linear Congruential generator.
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*/
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struct LinearCongruentialEngine(UIntType, UIntType a, UIntType c, UIntType m)
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{
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/// Alias for the generated type $(D_PARAM UIntType).
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alias UIntType ResultType;
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static invariant
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{
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/// Does this generator have a fixed range? ($(D_PARAM true)).
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bool hasFixedRange = true;
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/// Lowest generated value.
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ResultType min = ( c == 0 ? 1 : 0 );
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/// Highest generated value.
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ResultType max = m - 1;
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/**
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The parameters of this distribution. The random number is $(D_PARAM x =
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(x * a + c) % m).
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*/
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UIntType
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multiplier = a,
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///ditto
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increment = c,
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///ditto
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modulus = m;
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}
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static assert(isIntegral!(UIntType));
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static assert(m == 0 || a < m);
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static assert(m == 0 || c < m);
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static assert(m == 0 ||
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(cast(ulong)a * (m-1) + c) % m == (c < a ? c - a + m : c - a));
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/**
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Constructs a $(D_PARAM LinearCongruentialEngine) generator.
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*/
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static LinearCongruentialEngine opCall(UIntType x0 = 1)
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{
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LinearCongruentialEngine result;
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result.seed(x0);
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return result;
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}
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/**
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(Re)seeds the generator.
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*/
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void seed(UIntType x0 = 1)
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{
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static if (c == 0)
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{
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enforce(x0, "Invalid (zero) seed for "
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~LinearCongruentialEngine.stringof);
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}
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_x = modulus ? (x0 % modulus) : x0;
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}
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/**
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Returns the next number in the random sequence.
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*/
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UIntType next()
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{
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static if (m)
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_x = cast(UIntType) ((cast(ulong) a * _x + c) % m);
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else
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_x = a * _x + c;
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return _x;
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}
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/**
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Discards next $(D_PARAM n) samples.
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*/
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void discard(ulong n)
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{
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while (n--) next;
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}
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/**
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Compares against $(D_PARAM rhs) for equality.
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*/
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bool opEquals(LinearCongruentialEngine rhs)
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{
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return _x == rhs._x;
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}
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private UIntType _x = 1;
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};
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/**
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Define $(D_PARAM LinearCongruentialEngine) generators with "good"
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parameters.
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Example:
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----
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// seed with a constant
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auto rnd0 = MinstdRand0(1);
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auto n = rnd0.next; // same for each run
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// Seed with an unpredictable value
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rnd0.seed(unpredictableSeed);
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n = rnd0.next; // different across runs
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----
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*/
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alias LinearCongruentialEngine!(uint, 16807, 0, 2147483647) MinstdRand0;
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/// ditto
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alias LinearCongruentialEngine!(uint, 48271, 0, 2147483647) MinstdRand;
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unittest
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{
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// The correct numbers are taken from The Database of Integer Sequences
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// http://www.research.att.com/~njas/sequences/eisBTfry00128.txt
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auto checking0 = [
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16807UL,282475249,1622650073,984943658,1144108930,470211272,
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101027544,1457850878,1458777923,2007237709,823564440,1115438165,
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1784484492,74243042,114807987,1137522503,1441282327,16531729,
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823378840,143542612 ];
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auto rnd0 = MinstdRand0(1);
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foreach (e; checking0)
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{
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assert(rnd0.next == e);
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}
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// Test the 10000th invocation
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// Correct value taken from:
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// http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2007/n2461.pdf
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rnd0.seed;
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rnd0.discard(9999);
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assert(rnd0.next == 1043618065);
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// Test MinstdRand
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auto checking = [48271UL,182605794,1291394886,1914720637,2078669041,
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407355683];
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auto rnd = MinstdRand(1);
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foreach (e; checking)
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{
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assert(rnd.next == e);
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}
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// Test the 10000th invocation
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// Correct value taken from:
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// http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2007/n2461.pdf
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rnd.seed;
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rnd.discard(9999);
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assert(rnd.next == 399268537);
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}
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/**
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The $(LINK2 http://math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html,
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Mersenne Twister generator).
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*/
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struct MersenneTwisterEngine(
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UIntType, size_t w, size_t n, size_t m, size_t r,
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UIntType a, size_t u, size_t s,
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UIntType b, size_t t,
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UIntType c, size_t l)
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{
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/// Result type (an alias for $(D_PARAM UIntType)).
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alias UIntType ResultType;
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/**
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Parameter for the generator.
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*/
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static invariant
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{
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size_t wordSize = w;
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size_t stateSize = n;
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size_t shiftSize = m;
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size_t maskBits = r;
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UIntType xorMask = a;
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UIntType temperingU = u;
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size_t temperingS = s;
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UIntType temperingB = b;
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size_t temperingT = t;
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UIntType temperingC = c;
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size_t temperingL = l;
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}
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/// Smallest generated value (0).
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static invariant UIntType min = 0;
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/// Largest generated value.
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static invariant UIntType max =
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w == UIntType.sizeof * 8 ? UIntType.max : (1u << w) - 1;
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/// The default seed value.
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static invariant UIntType defaultSeed = 5489u;
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static assert(1 <= m && m <= n);
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static assert(0 <= r && 0 <= u && 0 <= s && 0 <= t && 0 <= l);
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static assert(r <= w && u <= w && s <= w && t <= w && l <= w);
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static assert(0 <= a && 0 <= b && 0 <= c);
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static assert(a <= max && b <= max && c <= max);
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/**
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Constructs a MersenneTwisterEngine object
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*/
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static MersenneTwisterEngine opCall(ResultType value)
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{
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MersenneTwisterEngine result;
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result.seed(value);
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return result;
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}
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/**
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Constructs a MersenneTwisterEngine object
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*/
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void seed(ResultType value = defaultSeed)
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{
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static if (w == ResultType.sizeof * 8)
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{
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mt[0] = value;
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}
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else
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{
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static assert(max + 1 > 0);
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mt[0] = value % (max + 1);
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}
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for (mti = 1; mti < n; ++mti) {
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mt[mti] =
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cast(UIntType)
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(1812433253UL * (mt[mti-1] ^ (mt[mti-1] >> (w - 2))) + mti);
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/* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
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/* In the previous versions, MSBs of the seed affect */
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/* only MSBs of the array mt[]. */
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/* 2002/01/09 modified by Makoto Matsumoto */
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mt[mti] &= ResultType.max;
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/* for >32 bit machines */
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}
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}
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/**
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Returns the next random value.
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*/
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uint next()
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{
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static invariant ResultType
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upperMask = ~((cast(ResultType) 1u <<
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(ResultType.sizeof * 8 - (w - r))) - 1),
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lowerMask = (cast(ResultType) 1u << r) - 1;
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ulong y = void;
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static invariant ResultType mag01[2] = [0x0UL, a];
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if (mti >= n)
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{
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/* generate N words at one time */
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if (mti == n + 1) /* if init_genrand() has not been called, */
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seed(5489UL); /* a default initial seed is used */
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int kk = 0;
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for (; kk < n - m; ++kk)
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{
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y = (mt[kk] & upperMask)|(mt[kk + 1] & lowerMask);
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mt[kk] = cast(UIntType) (mt[kk + m] ^ (y >> 1)
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^ mag01[cast(UIntType) y & 0x1U]);
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}
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for (; kk < n - 1; ++kk)
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{
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y = (mt[kk] & upperMask)|(mt[kk + 1] & lowerMask);
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mt[kk] = cast(UIntType) (mt[kk + (m -n)] ^ (y >> 1)
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^ mag01[cast(UIntType) y & 0x1U]);
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}
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y = (mt[n -1] & upperMask)|(mt[0] & lowerMask);
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mt[n - 1] = cast(UIntType) (mt[m - 1] ^ (y >> 1)
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^ mag01[cast(UIntType) y & 0x1U]);
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mti = 0;
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}
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y = mt[mti++];
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/* Tempering */
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y ^= (y >> temperingU);
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y ^= (y << temperingS) & temperingB;
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y ^= (y << temperingT) & temperingC;
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y ^= (y >> temperingL);
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return cast(UIntType) y;
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}
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/**
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Discards next $(D_PARAM n) samples.
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*/
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void discard(ulong n)
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{
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while (n--) next;
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}
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private ResultType mt[n];
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private size_t mti = n + 1; /* means mt is not initialized */
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}
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/**
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A $(D_PARAM MersenneTwisterEngine) instantiated with the parameters
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of the original engine
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$(LINK2 http://math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html,MT19937),
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generating uniformly-distributed 32-bit numbers with a period of 2
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to the power of 19937. Recommended for random number generation
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unless memory is severely restricted, in which case a $(D_PARAM
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LinearCongruentialEngine) would be the generator of choice.
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Example:
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----
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// seed with a constant
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Mt19937 gen;
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auto n = gen.next; // same for each run
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// Seed with an unpredictable value
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gen.seed(unpredictableSeed);
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n = gen.next; // different across runs
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----
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*/
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alias MersenneTwisterEngine!(uint, 32, 624, 397, 31, 0x9908b0df, 11, 7,
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0x9d2c5680, 15, 0xefc60000, 18)
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Mt19937;
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unittest
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{
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Mt19937 gen;
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gen.discard(9999);
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assert(gen.next == 4123659995);
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}
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/**
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The "default", "favorite", "suggested" random number generator on
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the current platform. It is a typedef for one of the
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previously-defined generators. You may want to use it if (1) you
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need to generate some nice random numbers, and (2) you don't care
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for the minutiae of the method being used.
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*/
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alias Mt19937 Random;
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/**
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A "good" seed for initializing random number engines. Initializing
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with $(D_PARAM unpredictableSeed) makes engines generate different
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random number sequences every run.
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Example:
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----
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auto rnd = Random(unpredictableSeed);
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auto n = rnd.next;
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...
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----
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*/
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uint unpredictableSeed()
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{
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return cast(uint) (getpid ^ getUTCtime);
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}
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/**
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Generates uniformly-distributed numbers within a range using an
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external generator. The $(D_PARAM leftLim) and $(D_PARAM rightLim)
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parameters control the shape of the interval (open vs. closed on
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either side). The default interval is [a, b$(RPAREN).
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Example:
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----
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auto a = new double[20];
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Random gen;
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auto rndIndex = UniformDistribution!(uint)(0, a.length);
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auto rndValue = UniformDistribution!(double)(0, 1);
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// Get a random index into the array
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auto i = rndIndex.next(gen);
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// Get a random probability, i.e., a real number in [0, 1$(RPAREN)
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auto p = rndValue.next(gen);
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// Assign that value to that array element
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a[i] = p;
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auto digits = UniformDistribution!(char, '[', ']')('0', '9');
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auto percentages = UniformDistribution!(double, '$(LPAREN)', ']')(0.0, 100.0);
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// Get a digit in ['0', '9']
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auto digit = digits.next(gen);
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// Get a number in $(LPAREN)0.0, 100.0]
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auto p = percentages.next(gen);
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----
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*/
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struct UniformDistribution(NumberType, char leftLim = '[', char rightLim = ')')
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{
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static assert((leftLim == '[' || leftLim == '(')
|
|
&& (rightLim == ']' || rightLim == ')'));
|
|
|
|
alias NumberType InputType;
|
|
alias NumberType ResultType;
|
|
/**
|
|
Constructs a $(D_PARAM UniformDistribution) able to generate
|
|
numbers in the interval [$(D_PARAM min), $(D_PARAM max)) if
|
|
$(D_PARAM closedRight) is $(D_PARAM false).
|
|
*/
|
|
static UniformDistribution opCall(NumberType a, NumberType b)
|
|
{
|
|
UniformDistribution result;
|
|
static if (leftLim == '(')
|
|
result._a = nextLarger(a);
|
|
else
|
|
result._a = a;
|
|
static if (rightLim == ')')
|
|
result._b = nextSmaller(b);
|
|
else
|
|
result._b = b;
|
|
enforce(result._a <= result._b,
|
|
"Invalid distribution range: " ~ leftLim ~ to!(string)(a)
|
|
~ ", " ~ to!(string)(b) ~ rightLim);
|
|
return result;
|
|
}
|
|
/**
|
|
Returns the smallest random value generated.
|
|
*/
|
|
ResultType a() { return leftLim == '[' ? _a : nextSmaller(_a); }
|
|
|
|
/**
|
|
Returns the largest random value generated.
|
|
*/
|
|
ResultType b() { return rightLim == ']' ? _b : nextLarger(_b); }
|
|
|
|
/**
|
|
Does nothing (provided for conformity with other distributions).
|
|
*/
|
|
void reset()
|
|
{
|
|
}
|
|
|
|
/**
|
|
Returns a random number using $(D_PARAM
|
|
UniformRandomNumberGenerator) as back-end.
|
|
*/
|
|
ResultType next(UniformRandomNumberGenerator)
|
|
(ref UniformRandomNumberGenerator urng)
|
|
{
|
|
static if (isIntegral!(NumberType))
|
|
{
|
|
auto myRange = _b - _a;
|
|
if (!myRange) return _a;
|
|
assert(urng.max - urng.min >= myRange,
|
|
"UniformIntGenerator.next not implemented for large ranges");
|
|
unsigned!(typeof((urng.max - urng.min + 1) / (myRange + 1)))
|
|
bucketSize = 1 + (urng.max - urng.min - myRange) / (myRange + 1);
|
|
assert(bucketSize, to!(string)(myRange));
|
|
ResultType r = void;
|
|
do
|
|
{
|
|
r = (urng.next - urng.min) / bucketSize;
|
|
}
|
|
while (r > myRange);
|
|
return _a + r;
|
|
}
|
|
else
|
|
{
|
|
return _a + (_b - _a) * cast(NumberType) (urng.next - urng.min)
|
|
/ (urng.max - urng.min);
|
|
}
|
|
}
|
|
|
|
private:
|
|
NumberType _a = 0, _b = NumberType.max;
|
|
|
|
static NumberType nextLarger(NumberType x)
|
|
{
|
|
static if (isIntegral!(NumberType))
|
|
return x + 1;
|
|
else
|
|
return nextafter(x, x.infinity);
|
|
}
|
|
|
|
static NumberType nextSmaller(NumberType x)
|
|
{
|
|
static if (isIntegral!(NumberType))
|
|
return x - 1;
|
|
else
|
|
return nextafter(x, -x.infinity);
|
|
}
|
|
}
|
|
|
|
unittest
|
|
{
|
|
MinstdRand0 gen;
|
|
auto rnd1 = UniformDistribution!(int)(0, 15);
|
|
foreach (i; 0 .. 20)
|
|
{
|
|
auto x = rnd1.next(gen);
|
|
assert(0 <= x && x <= 15);
|
|
//writeln(x);
|
|
}
|
|
}
|
|
|
|
unittest
|
|
{
|
|
MinstdRand0 gen;
|
|
foreach (i; 0 .. 20)
|
|
{
|
|
auto x = uniform!(double)(gen, 0., 15.);
|
|
assert(0 <= x && x <= 15);
|
|
//writeln(x);
|
|
}
|
|
}
|
|
|
|
/**
|
|
Convenience function that generates a number in an interval by
|
|
forwarding to $(D_PARAM UniformDistribution!(T, leftLim,
|
|
rightLim)(a, b).next).
|
|
|
|
Example:
|
|
|
|
----
|
|
Random gen(unpredictableSeed);
|
|
// Generate an integer in [0, 1024]
|
|
auto a = uniform(gen, 0, 1024);
|
|
// Generate a float in [0, 1$(RPAREN)
|
|
auto a = uniform(gen, 0.0f, 1.0f);
|
|
----
|
|
*/
|
|
|
|
T1 uniform(T1, char leftLim = '[', char rightLim = ')',
|
|
UniformRandomNumberGenerator, T2)
|
|
(ref UniformRandomNumberGenerator gen, T1 a, T2 b)
|
|
{
|
|
alias typeof(return) Result;
|
|
auto dist = UniformDistribution!(Result, leftLim, rightLim)(a, b);
|
|
return dist.next(gen);
|
|
}
|
|
|
|
unittest
|
|
{
|
|
auto gen = Mt19937(unpredictableSeed);
|
|
auto a = uniform(gen, 0, 1024);
|
|
assert(0 <= a && a <= 1024);
|
|
auto b = uniform(gen, 0.0f, 1.0f);
|
|
assert(0 <= b && b < 1, to!(string)(b));
|
|
}
|
|
|
|
/**
|
|
Shuffles elements of $(D_PARAM array) using $(D_PARAM r) as a
|
|
shuffler.
|
|
*/
|
|
|
|
void randomShuffle(T, SomeRandomGen)(T[] array, ref SomeRandomGen r)
|
|
{
|
|
foreach (i; 0 .. array.length)
|
|
{
|
|
// generate a random number i .. n
|
|
invariant which = i + uniform!(size_t)(r, 0u, array.length - i);
|
|
swap(array[i], array[which]);
|
|
}
|
|
}
|
|
|
|
unittest
|
|
{
|
|
auto a = ([ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]).dup;
|
|
auto b = a.dup;
|
|
Mt19937 gen;
|
|
randomShuffle(a, gen);
|
|
//assert(a == expectedA);
|
|
assert(a.sort == b.sort);
|
|
}
|
|
|
|
/* ===================== Random ========================= */
|
|
|
|
// BUG: not multithreaded
|
|
|
|
private uint seed; // starting seed
|
|
private uint index; // ith random number
|
|
|
|
/**
|
|
* The random number generator is seeded at program startup with a random value.
|
|
This ensures that each program generates a different sequence of random
|
|
numbers. To generate a repeatable sequence, use rand_seed() to start the
|
|
sequence. seed and index start it, and each successive value increments index.
|
|
This means that the $(I n)th random number of the sequence can be directly
|
|
generated
|
|
by passing index + $(I n) to rand_seed().
|
|
|
|
Note: This is more random, but slower, than C's rand() function.
|
|
To use C's rand() instead, import std.c.stdlib.
|
|
|
|
BUGS: Shares a global single state, not multithreaded.
|
|
SCHEDULED FOR DEPRECATION.
|
|
*/
|
|
|
|
void rand_seed(uint seed, uint index)
|
|
{
|
|
.seed = seed;
|
|
.index = index;
|
|
}
|
|
|
|
/**
|
|
* Get the next random number in sequence.
|
|
* BUGS: Shares a global single state, not multithreaded.
|
|
* SCHEDULED FOR DEPRECATION.
|
|
*/
|
|
|
|
uint rand()
|
|
{
|
|
static uint xormix1[20] =
|
|
[
|
|
0xbaa96887, 0x1e17d32c, 0x03bcdc3c, 0x0f33d1b2,
|
|
0x76a6491d, 0xc570d85d, 0xe382b1e3, 0x78db4362,
|
|
0x7439a9d4, 0x9cea8ac5, 0x89537c5c, 0x2588f55d,
|
|
0x415b5e1d, 0x216e3d95, 0x85c662e7, 0x5e8ab368,
|
|
0x3ea5cc8c, 0xd26a0f74, 0xf3a9222b, 0x48aad7e4
|
|
];
|
|
|
|
static uint xormix2[20] =
|
|
[
|
|
0x4b0f3b58, 0xe874f0c3, 0x6955c5a6, 0x55a7ca46,
|
|
0x4d9a9d86, 0xfe28a195, 0xb1ca7865, 0x6b235751,
|
|
0x9a997a61, 0xaa6e95c8, 0xaaa98ee1, 0x5af9154c,
|
|
0xfc8e2263, 0x390f5e8c, 0x58ffd802, 0xac0a5eba,
|
|
0xac4874f6, 0xa9df0913, 0x86be4c74, 0xed2c123b
|
|
];
|
|
|
|
uint hiword, loword, hihold, temp, itmpl, itmph, i;
|
|
|
|
loword = seed;
|
|
hiword = index++;
|
|
for (i = 0; i < 4; i++) // loop limit can be 2..20, we choose 4
|
|
{
|
|
hihold = hiword; // save hiword for later
|
|
temp = hihold ^ xormix1[i]; // mix up bits of hiword
|
|
itmpl = temp & 0xffff; // decompose to hi & lo
|
|
itmph = temp >> 16; // 16-bit words
|
|
temp = itmpl * itmpl + ~(itmph * itmph); // do a multiplicative mix
|
|
temp = (temp >> 16) | (temp << 16); // swap hi and lo halves
|
|
hiword = loword ^ ((temp ^ xormix2[i]) + itmpl * itmph); //loword mix
|
|
loword = hihold; // old hiword is loword
|
|
}
|
|
return hiword;
|
|
}
|
|
|
|
static this()
|
|
{
|
|
ulong s;
|
|
|
|
version(Win32)
|
|
{
|
|
QueryPerformanceCounter(&s);
|
|
}
|
|
version(linux)
|
|
{
|
|
// time.h
|
|
// sys/time.h
|
|
|
|
timeval tv;
|
|
|
|
if (gettimeofday(&tv, null))
|
|
{ // Some error happened - try time() instead
|
|
s = std.c.linux.linux.time(null);
|
|
}
|
|
else
|
|
{
|
|
s = cast(ulong)((cast(long)tv.tv_sec << 32) + tv.tv_usec);
|
|
}
|
|
}
|
|
rand_seed(cast(uint) s, cast(uint)(s >> 32));
|
|
}
|
|
|
|
|
|
unittest
|
|
{
|
|
static uint results[10] =
|
|
[
|
|
0x8c0188cb,
|
|
0xb161200c,
|
|
0xfc904ac5,
|
|
0x2702e049,
|
|
0x9705a923,
|
|
0x1c139d89,
|
|
0x346b6d1f,
|
|
0xf8c33e32,
|
|
0xdb9fef76,
|
|
0xa97fcb3f
|
|
];
|
|
int i;
|
|
uint seedsave = seed;
|
|
uint indexsave = index;
|
|
|
|
rand_seed(1234, 5678);
|
|
for (i = 0; i < 10; i++)
|
|
{ uint r = rand();
|
|
//printf("0x%x,\n", rand());
|
|
assert(r == results[i]);
|
|
}
|
|
|
|
seed = seedsave;
|
|
index = indexsave;
|
|
}
|