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Using Box-Muller for truncated normal sampling #4

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Using Box-Muller for truncated normal sampling #4

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25 changes: 25 additions & 0 deletions THRandom.c
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Original file line number Diff line number Diff line change
Expand Up @@ -241,6 +241,31 @@ double THRandom_normal(THGenerator *_generator, double mean, double stdv)
return _generator->normal_rho*sin(2.*M_PI*_generator->normal_x)*stdv+mean;
}

double THRandom_normal_truncated(THGenerator *_generator, double mean, double stdv)
{
THArgCheck(stdv > 0, 2, "standard deviation must be strictly positive");

/* Using Box-Muller for truncated normal sampling
between -2*std and 2*std.
(based on Martino, L.; Luengo, D.; Míguez, J.
"Efficient sampling from truncated bivariate Gaussians
via Box-Muller transformation")*/
if(!_generator->normal_is_valid)
{
_generator->normal_x = __uniform__(_generator);
_generator->normal_y = __uniform__(_generator, 0, 1-exp(-2));
_generator->normal_rho = sqrt(-2. * log(1.0-_generator->normal_y));
_generator->normal_is_valid = 1;
}
else
_generator->normal_is_valid = 0;

if(_generator->normal_is_valid)
return _generator->normal_rho*cos(2.*M_PI*_generator->normal_x)*stdv+mean;
else
return _generator->normal_rho*sin(2.*M_PI*_generator->normal_x)*stdv+mean;
}

double THRandom_exponential(THGenerator *_generator, double lambda)
{
return(-1. / lambda * log(1-__uniform__(_generator)));
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