Feature/samples summary in result #981
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rhayes777
reviewed
Mar 25, 2024
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| median_pdf_sample = Sample.from_lists( | ||
| model=self.model, | ||
| parameter_lists=[self.median_pdf(as_instance=False)], | ||
| log_likelihood_list=[self.max_log_likelihood_sample.log_likelihood], | ||
| log_prior_list=[self.max_log_likelihood_sample.log_prior], | ||
| weight_list=[self.max_log_likelihood_sample.weight], | ||
| )[0] |
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Seems silly to use a function called 'from_lists' only to take the first item
|
I guess it makes a lot of sense for Result to take Paths; it starts to look a lot like the SearchOutput class used by the agregator. What happens when a search has no name? |
rhayes777
approved these changes
Apr 8, 2024
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| # sample_list=samples_with_log_likelihood_list( | ||
| # self.sample_multiplier * fit, _make_samples(model) | ||
| # ), |
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| if self._samples is not None: | ||
| return self._samples |
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Not quite, this is because samples can be passed into __init__ meaning we dont load via csv (e.g. to avoid I/O)
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| try: | ||
| Samples.from_csv( | ||
| paths=self.paths, | ||
| model=self.model, | ||
| ) | ||
| except FileNotFoundError: | ||
| pass |
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Should the return type be Optional?
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Make it so that all internal results loading use the
SamplesSummaryobject instead of theSamplesobject wherever possible.This has two benefits:
-Loading
samples.csv/search_internal.dillin order to load results when resuming a model-fit was very slow.output.yamlmean autofit can now run without outputting asamples.csvfile orsearch_internal.dillfile at all (to save hard disk space). The samples summary file cannot be customized to not be output, meaning the information for resuming runs is always available.This is motivated for search chaining prior passing, which by using the
SamplesSummaryresumes previous fits much faster.