aixd.sampler.sampler_definitions.sampler_custom

aixd.sampler.sampler_definitions.sampler_custom(dobjects: List[DataObject], engine: SamplingEngine, data: DataFrame | array | None = None) → SamplesGenerator[source]

A sampler to sample from all design parameters, given some data containing the distributions we are intending For each column, aka dataobject, we can just specify a different distribution.

Parameters:

  • dobjects (List[DataObject]) – List of DataObjects to sample from

  • engine (SamplingEngine) – To use for sampling

  • data (Union[pd.DataFrame, np.array], optional, default=None) – Just a quantile strategy for sampler that is fitted to some data, in order to provide samples that follow, in an univariate fashion, the distribution of the data.

Returns:

SamplesGenerator – The sampler object

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