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#include <time.h> |
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#include <math.h> |
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#include <vector> |
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namespace oopse { |
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namespace OpenMD { |
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class MTRand { |
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// Data |
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// reading 624 consecutive values. |
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// Access to 32-bit random numbers |
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double rand(); // real number in [0,1] |
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double rand( const double& n ); // real number in [0,n] |
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double randExc(); // real number in [0,1) |
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double randExc( const double& n ); // real number in [0,n) |
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double randDblExc(); // real number in (0,1) |
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double randDblExc( const double& n ); // real number in (0,n) |
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RealType rand(); // real number in [0,1] |
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RealType rand( const RealType& n ); // real number in [0,n] |
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RealType randExc(); // real number in [0,1) |
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RealType randExc( const RealType& n ); // real number in [0,n) |
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RealType randDblExc(); // real number in (0,1) |
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RealType randDblExc( const RealType& n ); // real number in (0,n) |
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uint32 randInt(); // integer in [0,2^32-1] (modified for striding) |
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uint32 rawRandInt(); // original randInt |
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uint32 randInt( const uint32& n ); // integer in [0,n] for n < 2^32 |
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double operator()() { return rand(); } // same as rand() |
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RealType operator()() { return rand(); } // same as rand() |
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// Access to 53-bit random numbers (capacity of IEEE double precision) |
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double rand53(); // real number in [0,1) |
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// Access to 53-bit random numbers (capacity of IEEE RealType precision) |
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RealType rand53(); // real number in [0,1) |
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// Access to nonuniform random number distributions |
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double randNorm( const double& mean = 0.0, const double& variance = 0.0 ); |
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RealType randNorm( const RealType mean = 0.0, const RealType variance = 0.0 ); |
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// Re-seeding functions with same behavior as initializers |
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void seed( const uint32 oneSeed ); |
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seed(); |
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} |
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inline double MTRand::rand() |
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{ return double(randInt()) * (1.0/4294967295.0); } |
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inline double MTRand::rand( const double& n ) |
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{ return rand() * n; } |
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inline double MTRand::randExc() |
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{ return double(randInt()) * (1.0/4294967296.0); } |
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inline RealType MTRand::rand() |
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{ return RealType(randInt()) * (1.0/4294967295.0); } |
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inline double MTRand::randExc( const double& n ) |
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inline RealType MTRand::rand( const RealType& n ) |
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{ return rand() * n; } |
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inline RealType MTRand::randExc() |
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{ return RealType(randInt()) * (1.0/4294967296.0); } |
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inline RealType MTRand::randExc( const RealType& n ) |
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{ return randExc() * n; } |
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inline double MTRand::randDblExc() |
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{ return ( double(randInt()) + 0.5 ) * (1.0/4294967296.0); } |
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inline RealType MTRand::randDblExc() |
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{ return ( RealType(randInt()) + 0.5 ) * (1.0/4294967296.0); } |
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inline double MTRand::randDblExc( const double& n ) |
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inline RealType MTRand::randDblExc( const RealType& n ) |
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{ return randDblExc() * n; } |
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inline double MTRand::rand53() |
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inline RealType MTRand::rand53() |
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{ |
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uint32 a = randInt() >> 5, b = randInt() >> 6; |
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return ( a * 67108864.0 + b ) * (1.0/9007199254740992.0); // by Isaku Wada |
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} |
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inline double MTRand::randNorm( const double& mean, const double& variance ) |
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inline RealType MTRand::randNorm( const RealType mean, const RealType variance ) |
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{ |
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// Return a real number from a normal (Gaussian) distribution with given |
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// mean and variance by Box-Muller method |
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double r = sqrt( -2.0 * log( 1.0-randDblExc()) ) * variance; |
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double phi = 2.0 * 3.14159265358979323846264338328 * randExc(); |
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assert(variance > 0); |
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RealType r = sqrt( -2.0 * log( 1.0-randDblExc()) * variance); |
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RealType phi = 2.0 * 3.14159265358979323846264338328 * randExc(); |
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return mean + r * cos(phi); |
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} |
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* number in the stride sequence. |
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*/ |
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inline MTRand::uint32 MTRand::randInt() { |
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std::vector<uint32> ranNums(nstrides_); |
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for (int i = 0; i < nstrides_; ++i) { |
