AliasSampler_t Derived Type

type, public :: AliasSampler_t

Alias Sampler class

Given an (un-normalized) array of weights, draws random numbers from this distribution. Has additional features compared to the AliasTable_t, like the stored probabilities.

Components

Type	Visibility	Attributes		Name		Initial
type(AliasTable_t),	private		::	table			alias table used for sampling
type(shared_array_real_t),	private		::	probs			the probabilities

Type-Bound Procedures

procedure, public :: setup => setup_AliasSampler_t

constructor

private subroutine setup_AliasSampler_t(this, rank_with_info, arr)

allocate the resources of this and load the probability distribution from arr into this want to use for sampling

Arguments

Type	Intent	Optional	Attributes		Name
class(AliasSampler_t),	intent(inout)			::	this
integer,	intent(in)			::	rank_with_info	The intra-node rank that contains the weights to be used all other arr of all other ranks are ignored (and can be allocated with size 0).
real(kind=dp),	intent(in)			::	arr(:)

procedure, private :: init => init_AliasSampler_t

only compute the data, i.e. bias tables etc., without allocation

private subroutine init_AliasSampler_t(this, rank_with_info, arr)

load the probability distribution from arr into this we only use this in the sampler array, but fortran has no friend classes, so its public want to use for sampling

Arguments

Type	Intent	Optional	Attributes		Name
class(AliasSampler_t),	intent(inout)			::	this
integer,	intent(in)			::	rank_with_info	The intra-node rank that contains the weights to be used all other arr of all other ranks are ignored (and can be allocated with size 0).
real(kind=dp),	intent(in)			::	arr(:)

procedure, private :: init_probs => init_probs_AliasSampler_t

initialize the probabilities

private subroutine init_probs_AliasSampler_t(this, rank_with_info, arr)

load the probability distribution from arr into this%probs want to use for sampling

Arguments

Type	Intent	Optional	Attributes		Name
class(AliasSampler_t),	intent(inout)			::	this
integer,	intent(in)			::	rank_with_info	The intra-node rank that contains the weights to be used all other arr of all other ranks are ignored (and can be allocated with size 0).
real(kind=dp),	intent(in)			::	arr(:)

procedure, public :: finalize => finalize_AliasSampler_t

destructor

private subroutine finalize_AliasSampler_t(this)

Arguments

Type	Intent	Optional	Attributes		Name
class(AliasSampler_t),	intent(inout)			::	this

procedure, public :: sample

get a random element and the generation probability

private subroutine sample(this, tgt, prob)

draw a random element from 1:size(this%probs) with the probabilities listed in prob

Arguments

Type	Intent	Optional	Attributes		Name
class(AliasSampler_t),	intent(in)			::	this
integer,	intent(out)			::	tgt	on return, this is a random number in the sampling range of this
real(kind=dp),	intent(out)			::	prob	on return, the probability of picking tgt

generic, public :: constrained_sample => constrained_sample_fast, constrained_sample_nI

get a random element from a constrained set and its normalized! generation probability

private subroutine constrained_sample_fast(this, contain, contain_ilut, renormalization, pos, val, prob)

draw a random element from 1:size(this%probs) with the probabilities listed in prob

Arguments

Type	Intent	Optional	Attributes		Name
class(AliasSampler_t),	intent(in)			::	this
integer,	intent(in)			::	contain(:)
integer(kind=n_int),	intent(in)			::	contain_ilut(0:)
real(kind=dp),	intent(in)			::	renormalization
integer,	intent(out)			::	pos	the position of tgt in `contain`
integer,	intent(out)			::	val	the position of tgt in `contain`
real(kind=dp),	intent(out)			::	prob	on return, the probability of picking tgt from constraint

private subroutine constrained_sample_nI(this, contain, renormalization, pos, tgt, prob)

draw a random element from 1:size(this%probs) with the probabilities listed in prob

Arguments

Type	Intent	Optional	Attributes		Name
class(AliasSampler_t),	intent(in)			::	this
integer,	intent(in)			::	contain(:)
real(kind=dp),	intent(in)			::	renormalization
integer,	intent(out)			::	pos	the position of tgt in `contain`
integer,	intent(out)			::	tgt	the position of tgt in `contain` on return, this is a random number in the sampling range of this
real(kind=dp),	intent(out)			::	prob	on return, the probability of picking tgt from constraint

procedure, private :: constrained_sample_fast

private subroutine constrained_sample_fast(this, contain, contain_ilut, renormalization, pos, val, prob)

draw a random element from 1:size(this%probs) with the probabilities listed in prob

Arguments

Type	Intent	Optional	Attributes		Name
class(AliasSampler_t),	intent(in)			::	this
integer,	intent(in)			::	contain(:)
integer(kind=n_int),	intent(in)			::	contain_ilut(0:)
real(kind=dp),	intent(in)			::	renormalization
integer,	intent(out)			::	pos	the position of tgt in `contain`
integer,	intent(out)			::	val	the position of tgt in `contain`
real(kind=dp),	intent(out)			::	prob	on return, the probability of picking tgt from constraint

procedure, private :: constrained_sample_nI

private subroutine constrained_sample_nI(this, contain, renormalization, pos, tgt, prob)

draw a random element from 1:size(this%probs) with the probabilities listed in prob

Arguments

Type	Intent	Optional	Attributes		Name
class(AliasSampler_t),	intent(in)			::	this
integer,	intent(in)			::	contain(:)
real(kind=dp),	intent(in)			::	renormalization
integer,	intent(out)			::	pos	the position of tgt in `contain`
integer,	intent(out)			::	tgt	the position of tgt in `contain` on return, this is a random number in the sampling range of this
real(kind=dp),	intent(out)			::	prob	on return, the probability of picking tgt from constraint

procedure, public :: get_prob => get_prob_AliasSampler_t

get the probability to produce a given value

private elemental function get_prob_AliasSampler_t(this, tgt) result(prob)

Returns the probability to draw tgt from this sampler

Arguments

Type	Intent	Optional	Attributes		Name
class(AliasSampler_t),	intent(in)			::	this
integer,	intent(in)			::	tgt	the number for which we request the probability of sampling

Return Value real(kind=dp)

the probability of drawing tgt with the sample routine

procedure, public :: constrained_getProb

get the probability to draw a given value from a constrained set

private pure function constrained_getProb(this, contain, renorm, tgt) result(prob)

Returns the probability to draw tgt from this sampler (has to be a set, i.e. unique and ordered) the probability of drawing anything from an empty sampler is 0

Arguments

Type	Intent	Optional	Attributes		Name
class(AliasSampler_t),	intent(in)			::	this
integer,	intent(in)			::	contain(:)
real(kind=dp),	intent(in)			::	renorm
integer,	intent(in)			::	tgt	the number for which we request the probability of sampling

Return Value real(kind=dp)

This loosened threshhold might be a good idea if the renormalization was calculated via the complement, i.e. \Sum{ p_i } {i \in D_i} = 1 - \Sum{ p_i } {i \notin D_i}

the probability of picking tgt from constraint

procedure, public :: get_memory_demand => get_memory_demand_AliasSampler

private elemental function get_memory_demand_AliasSampler(this) result(res)

Arguments

Type	Intent	Optional	Attributes		Name
class(AliasSampler_t),	intent(in)			::	this

Return Value type(ByteSize_t)

Source Code

    type :: AliasSampler_t
        !! Alias Sampler class
        !!
        !! Given an (un-normalized) array of weights, draws
        !! random numbers from this distribution.
        !! Has additional features compared to the AliasTable_t,
        !! like the stored probabilities.
        private
        type(AliasTable_t) :: table
            !! alias table used for sampling
        ! WARNING: DO NOT MANUALLY RE-ASSIGN THIS POINTER, THIS WILL MOST LIKELY BREAK STUFF
        type(shared_array_real_t) :: probs
            !! the probabilities

    contains
        private
        procedure, public:: setup => setup_AliasSampler_t
            !! constructor
        procedure :: init => init_AliasSampler_t
            !! only compute the data, i.e. bias tables etc., without allocation
        procedure :: init_probs => init_probs_AliasSampler_t
            !! initialize the probabilities
        procedure, public :: finalize => finalize_AliasSampler_t
            !! destructor
        procedure, public :: sample
            !! get a random element and the generation probability
        generic, public :: constrained_sample => constrained_sample_fast, constrained_sample_nI
            !! get a random element from a constrained set and its normalized! generation probability
        procedure, private :: constrained_sample_nI, constrained_sample_fast
        procedure, public :: get_prob => get_prob_AliasSampler_t
            !! get the probability to produce a given value
        procedure, public :: constrained_getProb
            !! get the probability to draw a given value from a constrained set
        procedure, public :: get_memory_demand => get_memory_demand_AliasSampler
    end type AliasSampler_t