You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
It would be useful to implement some tests to check the rigor of our Gaussian and floating point random number streams, since the underlying PCG implementation we are based on only generates integral types (and thus our 1:1 comparisons to them are only for the integral types, not our derived representations). We could potentially compare ourselves to another jvm implementation of PCG or call into a test suite.
The text was updated successfully, but these errors were encountered:
testFloatDistribution() and testGaussianDistribution() do check whether the distributions are correct. They aren't super robust, but if there were a bug in the implementation of Box-Muller it would be very unlikely to pass.
Right... this is referring to the potential need for more rigorous testing. We already have that for integers via the direct comparison to the reference implementation which was itself tested against TestU01. But we don't have that for other (derived from integral) types because the reference implementation doesn't generate them.
It would be useful to implement some tests to check the rigor of our Gaussian and floating point random number streams, since the underlying PCG implementation we are based on only generates integral types (and thus our 1:1 comparisons to them are only for the integral types, not our derived representations). We could potentially compare ourselves to another jvm implementation of PCG or call into a test suite.
The text was updated successfully, but these errors were encountered: