PLearn 0.1
Namespaces | Functions
random.h File Reference
#include "TMat.h"
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Namespaces

namespace  PLearn
 

< for swap


Functions

real PLearn::log_gamma (real xx)
real PLearn::log_beta (real x, real y)
real PLearn::incomplete_beta (real z, real x, real y)
real PLearn::student_t_cdf (real t, int nb_degrees_of_freedom)
void PLearn::seed ()
void PLearn::manual_seed (int32_t x)
int32_t PLearn::get_seed ()
real PLearn::uniform_sample ()
real PLearn::bounded_uniform (real a, real b)
real PLearn::expdev ()
real PLearn::gaussian_01 ()
real PLearn::normal_sample ()
real PLearn::gaussian_mu_sigma (real mu, real sigma)
real PLearn::gaussian_mixture_mu_sigma (Vec &w, const Vec &mu, const Vec &sigma)
real PLearn::gamdev (int ia)
real PLearn::poidev (real xm)
real PLearn::bnldev (real pp, int n)
real PLearn::binomial_sample (real prob1)
 alias
int PLearn::multinomial_sample (const Vec &distribution)
int PLearn::uniform_multinomial_sample (int N)
 return an integer between 0 and N-1 with equal probabilities
template<class T >
void PLearn::bootstrap_rows (const TMat< T > &source, TMat< T > destination)
 sample with replacement the rows of source and put them in destination.
void PLearn::fill_random_uniform (const Vec &dest, real minval=0, real maxval=1)
 sample each element from uniform distribution U[minval,maxval]
void PLearn::fill_random_discrete (const Vec &dest, const Vec &set)
 sample each element from the given set
void PLearn::fill_random_normal (const Vec &dest, real mean=0, real stdev=1)
 sample each element from Normal(mean,sdev^2) distribution
void PLearn::fill_random_normal (const Vec &dest, const Vec &mean, const Vec &stdev)
 sample each element from multivariate Normal(mean,diag(sdev^2)) distribution
void PLearn::fill_random_uniform (const Mat &dest, real minval, real maxval)
void PLearn::fill_random_normal (const Mat &dest, real mean, real sdev)
void PLearn::random_subset_indices (const TVec< int > &dest, int n)
 Fill dest with dest.length() unique indices of entries in (0,1,...n-1), chosen uniformly i.e.
template<class T >
void PLearn::shuffleElements (const TVec< T > &vec)
 randomly shuffle the entries of the TVector
template<class T >
void PLearn::shuffleRows (const TMat< T > &mat)
template<class T >
TVec< intPLearn::computeRanks (const TMat< T > &mat, TMat< T > &ranks, bool ignore_missing=false)
 For each column of 'mat', sort the elements and put in the 'ranks' matrix (of the same dimensions) the rank of original elements.
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