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Fixes a bug where lclip and/or rclip on mixture distribution were not working correctly.
Fixes a bug where dist_fn did not work with np.vectorize functions.
Fixes a bug where in-memory caching was invoked for bayesnet when not desired.
Caching and Multicore
[Breaking change]bayesnet caching is now based on binary files instead of pickle files (uses msgspec as the underlying library).
[Breaking change]sample caching is now based on numpy files instead of pickle files.
A cache can now be loaded via sample(load_cache=cachefile) or bayesnet(load_cache=cachefile), without needing to pass the distribution / function.
bayesnet and sample now take an argument cores (default 1). If greater than 1, will run the calculations on multiple cores using the pathos package.
Other
Functions that take weights now can instead take a parameter relative_weights where waits are automatically normalized to sum to 1 (instead of erroring, which is still the behavior if using weights).
Verbose output for bayesnet and sample is now clearer (and slightly more verbose).