Random number generator fix

Bilby change (bilby!1273 (merged))

For a detailed discussion see the linked merge request. To summarize, using the global numpy RNG with multiprocessing means that each thread uses the same random sequence. The only place in Bilby analyses of real data that this is relevant is in the reconstruction of the marginalized parameters in post-processing and leads to non-independent samples for any marginalized parameters.

The most obvious display of this is in the network optimal SNR where we see clustering of the values in trace plots, e.g.,

after implementing this fix the same analysis gives the following trace

The number of points is slightly different because a different random downsampling from nested samples to posterior samples was used.

bilby_pipe update (!565 (merged))

This will require an update to bilby_pipe after the release of Bilby is made to make sure the random seed is set properly.

bilby_mcmc

There may be unknown issues remaining with parallelization in bilby_mcmc. Resolving these will be deferred to a future release.