dfm / george

Fast and flexible Gaussian Process regression in Python
http://george.readthedocs.io
MIT License
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Random seed / rng for sampling from GP #174

Open NoahAmsel opened 4 months ago

NoahAmsel commented 4 months ago

I want to get reproducible results from GP.sample. This function could take an optional parameter rng of type numpy.random.Generator. Rather than call np.random.multivariate_normal, we could then call rng.multivariate_normal.

The same holds for GP.sample_conditional. These seem to be the only two functions in George that rely on numpy.random.