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paradox

SamplerHierarchical

SamplerHierarchical Class

Description

Hierarchical sampling for arbitrary param sets with dependencies, where the user specifies 1D samplers per param. Dependencies are topologically sorted, parameters are then sampled in topological order, and if dependencies do not hold, values are set to NA in the resulting data.table.

Super class

paradox::Sampler -> SamplerHierarchical

Public fields

samplers

(list())
List of Sampler1D objects that gives a Sampler for each Param in the param_set.

Methods

Public methods

Method new()

Creates a new instance of this R6 class.

Usage
SamplerHierarchical$new(param_set, samplers)
Arguments
param_set

(ParamSet)
Domain / support of the distribution we want to sample from. ParamSet is cloned on construction.

samplers

(list())
List of Sampler1D objects that gives a Sampler for each Param in the param_set.

Method clone()

The objects of this class are cloneable with this method.

Usage
SamplerHierarchical$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

paradox

Define and Work with Parameter Spaces for Complex Algorithms

v0.7.1
LGPL-3
Authors
Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Xudong Sun [aut] (<https://orcid.org/0000-0003-3269-2307>), Martin Binder [aut], Marc Becker [ctb] (<https://orcid.org/0000-0002-8115-0400>)
Initial release

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