Univariate Random Sampling#

#include <raft/random/rng.cuh>

namespace raft::random

template<typename OutputValueType, typename IndexType> void uniform(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutputValueType, IndexType> out, OutputValueType start, OutputValueType end)#

Generate uniformly distributed numbers in the given range.

Template Parameters:

OutputValueType – Data type of output random number
Index – Data type used to represent length of the arrays

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] the output array
start – [in] start of the range
end – [in] end of the range

template<typename OutputValueType, typename IndexType> void uniformInt(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutputValueType, IndexType> out, OutputValueType start, OutputValueType end)#

Generate uniformly distributed integers in the given range.

Template Parameters:

OutputValueType – Integral type; value type of the output vector
IndexType – Type used to represent length of the output vector

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] the output vector of random numbers
start – [in] start of the range
end – [in] end of the range

template<typename OutputValueType, typename IndexType> void normal(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutputValueType, IndexType> out, OutputValueType mu, OutputValueType sigma)#

Generate normal distributed numbers with a given mean and standard deviation.

Template Parameters:

OutputValueType – data type of output random number
IndexType – data type used to represent length of the arrays

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] the output array
mu – [in] mean of the distribution
sigma – [in] std-dev of the distribution

template<typename OutputValueType, typename IndexType> void normalInt(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutputValueType, IndexType> out, OutputValueType mu, OutputValueType sigma)#

Generate normal distributed integers.

Template Parameters:

OutputValueType – Integral type; value type of the output vector
IndexType – Integral type of the output vector’s length

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] the output array
mu – [in] mean of the distribution
sigma – [in] standard deviation of the distribution

template<typename OutputValueType, typename IndexType> void normalTable(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<const OutputValueType, IndexType> mu_vec, std::variant<raft::device_vector_view<const OutputValueType, IndexType>, OutputValueType> sigma, raft::device_matrix_view<OutputValueType, IndexType, raft::row_major> out)#

Generate normal distributed table according to the given set of means and scalar standard deviations.

Each row in this table conforms to a normally distributed n-dim vector whose mean is the input vector and standard deviation is the corresponding vector or scalar. Correlations among the dimensions itself are assumed to be absent.

Template Parameters:

OutputValueType – data type of output random number
IndexType – data type used to represent length of the arrays

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
mu_vec – [in] mean vector (of length out.extent(1))
sigma – [in] Either the standard-deviation vector (of length out.extent(1)) of each component, or a scalar standard deviation for all components.
out – [out] the output table

template<typename OutputValueType, typename IndexType> void fill(raft::resources const &handle, RngState &rng_state, OutputValueType val, raft::device_vector_view<OutputValueType, IndexType> out)#

Fill a vector with the given value.

Template Parameters:

OutputValueType – Value type of the output vector
IndexType – Integral type used to represent length of the output vector

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
val – [in] value with which to fill the output vector
out – [out] the output vector

template<typename OutputValueType, typename IndexType, typename Type> void bernoulli(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutputValueType, IndexType> out, Type prob)#

Generate bernoulli distributed boolean array.

Template Parameters:

OutputValueType – Type of each element of the output vector; must be able to represent boolean values (e.g., bool)
IndexType – Integral type of the output vector’s length
Type – Data type in which to compute the probabilities

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] the output vector
prob – [in] coin-toss probability for heads

template<typename OutputValueType, typename IndexType> void scaled_bernoulli(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutputValueType, IndexType> out, OutputValueType prob, OutputValueType scale)#

Generate bernoulli distributed array and applies scale.

Template Parameters:

OutputValueType – Data type in which to compute the probabilities
IndexType – Integral type of the output vector’s length

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] the output vector
prob – [in] coin-toss probability for heads
scale – [in] scaling factor

template<typename OutputValueType, typename IndexType = int> void gumbel(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutputValueType, IndexType> out, OutputValueType mu, OutputValueType beta)#

Generate Gumbel distributed random numbers.

Note

https://en.wikipedia.org/wiki/Gumbel_distribution

Template Parameters:

OutputValueType – data type of output random number
IndexType – data type used to represent length of the arrays

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] output array
mu – [in] mean value
beta – [in] scale value

template<typename OutputValueType, typename IndexType> void lognormal(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutputValueType, IndexType> out, OutputValueType mu, OutputValueType sigma)#

Generate lognormal distributed numbers.

Template Parameters:

OutputValueType – data type of output random number
IndexType – data type used to represent length of the arrays

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] the output array
mu – [in] mean of the distribution
sigma – [in] standard deviation of the distribution

template<typename OutputValueType, typename IndexType = int> void logistic(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutputValueType, IndexType> out, OutputValueType mu, OutputValueType scale)#

Generate logistic distributed random numbers.

Template Parameters:

OutputValueType – data type of output random number
IndexType – data type used to represent length of the arrays

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] output array
mu – [in] mean value
scale – [in] scale value

template<typename OutputValueType, typename IndexType> void exponential(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutputValueType, IndexType> out, OutputValueType lambda)#

Generate exponentially distributed random numbers.

Template Parameters:

OutputValueType – data type of output random number
IndexType – data type used to represent length of the arrays

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] output array
lambda – [in] the exponential distribution’s lambda parameter

template<typename OutputValueType, typename IndexType> void rayleigh(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutputValueType, IndexType> out, OutputValueType sigma)#

Generate rayleigh distributed random numbers.

Template Parameters:

OutputValueType – data type of output random number
IndexType – data type used to represent length of the arrays

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] output array
sigma – [in] the distribution’s sigma parameter

template<typename OutputValueType, typename IndexType> void laplace(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutputValueType, IndexType> out, OutputValueType mu, OutputValueType scale)#

Generate laplace distributed random numbers.

Template Parameters:

OutputValueType – data type of output random number
IndexType – data type used to represent length of the arrays

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] output array
mu – [in] the mean
scale – [in] the scale

template<typename OutType, typename WeightType, typename IndexType> std::enable_if_t<std::is_integral_v<OutType>> discrete(raft::resources const &handle, RngState &rng_state, raft::device_vector_view<OutType, IndexType> out, raft::device_vector_view<const WeightType, IndexType> weights)#

Generate random integers, where the probability of i is weights[i]/sum(weights)

Usage example:

#include <raft/core/device_mdarray.hpp>
#include <raft/core/resources.hpp>
#include <raft/random/rng.cuh>

raft::resources handle;
...
raft::random::RngState rng(seed);
auto indices = raft::make_device_vector<int>(handle, n_samples);
raft::random::discrete(handle, rng, indices.view(), weights);

Template Parameters:

OutType – integer output type
WeightType – weight type
IndexType – data type used to represent length of the arrays

Parameters:

handle – [in] raft handle for resource management
rng_state – [in] random number generator state
out – [out] output array
weights – [in] weight array