gaussian_mv#
Generates random numbers from multivariate normal distribution.
Description#
The class object is used in the generate function to provide random numbers
with d-variate normal (Gaussian) distribution with mean (a) and variance-covariance matrix
C, where a ∈ Rd ; C is d x d symmetric positive-definite matrix.
The probability density function is given by:
where x``∈ ``Rd .
Matrix C can be represented as C = TTT, where T is
a lower triangular matrix - Cholesky factor of C.
API#
Syntax#
namespace oneapi::mkl::rng {
template<typename RealType = float, layout Layout = layout::packed,
typename Method = gaussian_mv_method::by_default>
class gaussian_mv {
public:
using method_type = Method;
using result_type = RealType;
static constexpr layout layout_type = Layout;
explicit gaussian_mv(std::uint32_t dimen, sycl::span<RealType> mean,
sycl::span<RealType> matrix);
explicit gaussian_mv(const param_type& pt);
std::uint32_t dimen() const;
sycl::span<RealType> mean() const;
sycl::span<RealType> matrix() const;
param_type param() const;
void param(const param_type& pt);
};
}
Devices supported: CPU and GPU.
Include Files#
oneapi/mkl/rng.hpp
Template Parameters#
Name |
Description |
|---|---|
|
Type of the produced values. The specific values are as follows:
|
|
Type of the matrix storage. The specific values are as follows:
See brief descriptions of the methods in Distributions Template Parameter Method. |
|
Generation method. The specific values are as follows:
See brief descriptions of the methods in Distributions Template Parameter Method. |
Input Parameters#
Name |
Type |
Description |
|---|---|---|
dimen |
|
Dimension of output random vectors |
mean |
|
Mean span |
matrix |
|
Variance-covariance matrix |
Note
When passing a
sycl::spanthat is constructed over a user’s memory to the constructor, users must manage the memory under sycl::span by themselves. They must not destroy the memory while data are processed.