forked from github/server
guassian distribution has no endless loops.
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5778bc2c93
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@ -14,6 +14,7 @@
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#define NO_STRDUP
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#define NO_STRDUP
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#define NO_MKDIR
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#define NO_MKDIR
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#define _CRT_SECURE_NO_WARNINGS
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#define _CRT_SECURE_NO_WARNINGS
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#define _USE_MATH_DEFINES
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#pragma warning(disable: 4710 4820)
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#pragma warning(disable: 4710 4820)
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#pragma warning(disable: 4100) // unreferenced formal parameter
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#pragma warning(disable: 4100) // unreferenced formal parameter
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#pragma warning(disable: 4456) // declaration hides previous
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#pragma warning(disable: 4456) // declaration hides previous
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@ -36,23 +36,27 @@ int lovar(double xpct_x2)
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return (rng_int() % n + rng_int() % n) / 1000;
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return (rng_int() % n + rng_int() % n) / 1000;
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}
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}
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/* NormalRand aus python, random.py geklaut, dort ist Referenz auf
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/* gaussian distribution
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* den Algorithmus. mu = Mittelwert, sigma = Standardabweichung.
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* taken from http://c-faq.com/lib/gaussian.html
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* http://de.wikipedia.org/wiki/Standardabweichung#Diskrete_Gleichverteilung.2C_W.C3.BCrfel
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*/
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*/
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double normalvariate(double mu, double sigma)
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double normalvariate(double mu, double sigma)
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{
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{
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static const double NV_MAGICCONST = 1.7155277699214135;
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static double U, V;
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double z;
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static int phase = 0;
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for (;;) {
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double Z;
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double u1 = rng_double();
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double u2 = rng_double();
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if (phase == 0) {
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z = NV_MAGICCONST * (u1 - 0.5) / u2;
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U = (rng_int() + 1.) / (RNG_RAND_MAX + 2.);
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if (z * z / 4.0 <= -log(u2)) {
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V = rng_int() / (RNG_RAND_MAX + 1.);
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break;
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Z = sqrt(-2 * log(U)) * sin(2 * M_PI * V);
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}
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}
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}
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return mu + z * sigma;
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else {
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Z = sqrt(-2 * log(U)) * cos(2 * M_PI * V);
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}
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phase = 1 - phase;
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return mu + Z *sigma;
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}
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}
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int ntimespprob(int n, double p, double mod)
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int ntimespprob(int n, double p, double mod)
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