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Posted to issues@commons.apache.org by "Alex Herbert (Jira)" <ji...@apache.org> on 2021/05/03 20:14:00 UTC
[jira] [Updated] (RNG-134) BoxSampler to sampler uniformly from a
box (or hyperrectangle)
[ https://issues.apache.org/jira/browse/RNG-134?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Alex Herbert updated RNG-134:
-----------------------------
Description:
Create a sampler to sample uniformly within a [hyperrectangle|https://en.wikipedia.org/wiki/Hyperrectangle].
Alternative names for a hyperrectangle are a box or an orthotope. Below I use the term box for simplicity and to match the BallSampler for an n-ball.
{code:java}
public abstract class BoxSampler implements
SharedStateSampler<BoxSampler> {
public static BoxSampler of(double[] a,
double[] b,
UniformRandomProvider rng);
}
{code}
Inputs {{a}} and {{b}} are the minimum and maximum of the box in each dimension.
Sampling can be performed using the same method as the LineSampler but using a uniform deviate for each dimension (instead of the same deviate for all dimensions):
{noformat}
p = a + u * (b - a)
= a + ub - ua
= (1 - u)a + ub
{noformat}
This will produce the same results as using an instance of the the {{ContinuousUniformSampler}} for each dimension with all samplers using a common RNG.
was:
Create a sampler to sample uniformly within a [hyperrectangle|https://en.wikipedia.org/wiki/Hyperrectangle].
Alternative names for a hyperrectangle are a box or an orthotope. Below I use the term box for simplicity and to match the BallSampler for an n-ball.
{code:java}
public abstract class BoxSampler implements
SharedStateSampler<BoxSampler> {
public static BoxSampler of(double[] a,
double[] b,
UniformRandomProvider rng);
}
{code}
Inputs {{a}} and {{b}} are the minimum and maximum of the box in each dimension.
Sampling can be performed using the same method as the LineSampler but using a uniform deviate for each dimension (instead of the same deviate for all dimensions):
{noformat}
p = a + u * (b - a)
= a + ub - ua
= (1 - u)a + ub
{noformat}
This will produce the same results as using an instance of the the {{ContinuousUniformSampler}} for each dimension with all samplers using a common RNG.
> BoxSampler to sampler uniformly from a box (or hyperrectangle)
> --------------------------------------------------------------
>
> Key: RNG-134
> URL: https://issues.apache.org/jira/browse/RNG-134
> Project: Commons RNG
> Issue Type: New Feature
> Components: sampling
> Affects Versions: 1.4
> Reporter: Alex Herbert
> Assignee: Alex Herbert
> Priority: Minor
> Time Spent: 10m
> Remaining Estimate: 0h
>
> Create a sampler to sample uniformly within a [hyperrectangle|https://en.wikipedia.org/wiki/Hyperrectangle].
> Alternative names for a hyperrectangle are a box or an orthotope. Below I use the term box for simplicity and to match the BallSampler for an n-ball.
>
> {code:java}
> public abstract class BoxSampler implements
> SharedStateSampler<BoxSampler> {
> public static BoxSampler of(double[] a,
> double[] b,
> UniformRandomProvider rng);
> }
> {code}
> Inputs {{a}} and {{b}} are the minimum and maximum of the box in each dimension.
> Sampling can be performed using the same method as the LineSampler but using a uniform deviate for each dimension (instead of the same deviate for all dimensions):
> {noformat}
> p = a + u * (b - a)
> = a + ub - ua
> = (1 - u)a + ub
> {noformat}
> This will produce the same results as using an instance of the the {{ContinuousUniformSampler}} for each dimension with all samplers using a common RNG.
>
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