Draft: Add distribution tests to look for specific error modes#47
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mstoeckl wants to merge 1 commit intorust-random:masterfrom
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Draft: Add distribution tests to look for specific error modes#47mstoeckl wants to merge 1 commit intorust-random:masterfrom
mstoeckl wants to merge 1 commit intorust-random:masterfrom
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Directly testing that the probability of an event is as expected can be considerably more powerful and can require less memory than performing a Kolmogorov-Smirnov test; however, this approach is much less flexible.
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CHANGELOG.mdentrySummary
This introduces a file in distr_test to add tests focused on detecting cases where a distribution sampler is biased on a particular event.
Motivation
Some of the distribution sampling issues that I have found are hard to discover with a Kolmogorov-Smirnov or similar general distribution test, because the issues only occur with large input parameters or low probabilities, and would require a lot of time and memory to detect with a general test.
This is marked as draft for now, as the changes are still a bit rough.
Details
The last bit tests systematically confirm that the floating point precision issue for Binomial indeed only occurs at n > 2^53; and that the Geometric sampler has no equivalent issue.
test_binomial_endpointscan be used to confirm that the change in endpoint rounding for the BTPE method in #43 is reasonable -- currently the probability of 0 or 20 being sampled is ~50% higher than expected on Binomial(20, 0.5), while with #43 the event does not occur at a rate clearly distinguishable from the ideal probability.Since rand_distr reexports Bernouilli, it may as well have a distribution test for it.