Gaussian distribution bounded by a hypercube. More...
#include <prob_dens_func.h>
Definition at line 1314 of file prob_dens_func.h.
Public Member Functions | |
prob_dens_mdim_bound_gaussian () | |
Create an empty distribution. | |
prob_dens_mdim_bound_gaussian (size_t p_ndim, vec_t &p_peak, mat_t &covar, vec_t &p_low, vec_t &p_high) | |
Create a distribution with the specified peak, covariance matrix, lower limits, and upper limits. | |
void | set (size_t p_ndim, vec_t &p_peak, mat_t &covar, vec_t &p_low, vec_t &p_high) |
Set the peak, covariance matrix, lower limits, and upper limits. More... | |
virtual double | pdf (const vec_t &x) const |
Compute the probability density function (arbitrary normalization) | |
virtual double | log_pdf (const vec_t &x) const |
Compute the natural log of the probability density function (arbitrary normalization) | |
virtual void | operator() (vec_t &x) const |
Sample the distribution. | |
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const mat_t & | get_chol () |
Get the Cholesky decomposition. | |
const mat_t & | get_covar_inv () |
Get the inverse of the covariance matrix. | |
const vec_t & | get_peak () |
Get the peak location. | |
const double & | get_norm () |
Get the normalization. | |
virtual size_t | dim () const |
The dimensionality. | |
prob_dens_mdim_gaussian () | |
Create an empty distribution. | |
prob_dens_mdim_gaussian (const prob_dens_mdim_gaussian &pdmg) | |
Copy constructor. | |
prob_dens_mdim_gaussian & | operator= (const prob_dens_mdim_gaussian &pdmg) |
Copy constructor with operator=. | |
template<class mat2_t , class vec2_t , class mat2_col_t = const_matrix_column_gen<mat2_t>> | |
prob_dens_mdim_gaussian (size_t p_mdim, size_t n_pts, const mat2_t &pts, const vec2_t &vals) | |
Create a distribution from a set of samples from a multidimensional Gaussian. | |
prob_dens_mdim_gaussian (size_t p_ndim, vec_t &p_peak, mat_t &covar) | |
Create a distribution from the covariance matrix. | |
void | set (size_t p_ndim, vec_t &p_peak, mat_t &covar) |
Set the peak and covariance matrix for the distribution. More... | |
void | set_alt (size_t p_ndim, vec_t &p_peak, mat_t &p_chol, mat_t &p_covar_inv, double p_norm) |
Alternate set function for use when covariance matrix has already been decomposed and inverted. | |
template<class vec_vec_t , class mat_col_t , class func_t > | |
void | set_gproc (size_t n_dim, size_t n_init, vec_vec_t &x, vec_t &y, func_t &fcovar) |
Given a data set and a covariance function, construct probability distribution based on a Gaussian process which includes noise. More... | |
Public Attributes | |
size_t | samp_max |
Maximum number of samples. | |
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o2scl::prob_dens_gaussian | pdg |
Standard normal. | |
Protected Attributes | |
vec_t | low |
Lower limits. | |
vec_t | high |
Upper limits. | |
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mat_t | chol |
Cholesky decomposition. | |
mat_t | covar_inv |
Inverse of the covariance matrix. | |
vec_t | peak |
Location of the peak. | |
double | norm |
Normalization factor, ![]() | |
size_t | ndim |
Number of dimensions. | |
vec_t | q |
Temporary storage 1. | |
vec_t | vtmp |
Temporary storage 2. | |
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inline |
Definition at line 1354 of file prob_dens_func.h.
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