Dataset.analysis

Dataset.analysis(analyzer: AnalysisCallback, n_files: int | None = None, flag_fromscratch: bool = False, **kwargs)[source]

We take already sampled samples, and analyze them. Only compute those files for which we don’t have performance attributes. This means that we can run new sampling campaigns later, and then come back and perform the analysis.

Parameters:

  • analyzer (AnalysisCallback) – The callback function created with the analysis function. It feeds the design parameters to the analysis function, obtains the performance attributes, and ensures they are returned in the correct format.

  • n_files (int, optional, default=None) – Out of all the files with design parameters which have not been analyzed, how many we want to analyze. In case the process is quite computationally expensive, and we prefer to proceed in batches. If None, it analyzes all the files.

  • flag_fromscratch (bool, optional, default=False) – To remove all existing performance attributes files, and perform the analysis again on all sets of design parameters. This is useful if the analysis function has changed.

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