GitLab

    - add a function to calculate a Gaussian Mixture Model fit to an ND
      set of samples (using function from scikit-learn)
    - allow previous posterior samples files to be read in and used to
      create a Gaussian Mixture Model from amplitude and cos(iota) samples
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 - remove the previous 1D Gaussian Mixture Model prior
 - add functions to create multi-variate Gaussian mixture model priors
 - edit DrawNameFromPrior function to draw points from a GMM prior
 - add function to calculate PDF value of GMM prior
 - closes #5008
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brought in through glue dependencies, this was done for the debian
packaging in a99092c2fff3c8e724f3e047a81d389fea34a0cb, this ports that
change to the SL packaging
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- type is being removed
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Gstlal an PyCBC send us more data than we need. Trim the SNR time
series before passing to BAYESTAR in order to speed up time
marginalization.
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This reverts commit 277dfbb4a53eada9605dbdff034ffa63d00b6bc1.
This change actually made it slightly slower.
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It cuts down on the integer-to-floating-point conversions.
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- Move it to its own compilation unit.
- Restore dynamic allocation init function.
- Precompute bounds checking.
- Precompute invalid value checking.
- Apply the same speedups to the 1D cubic interpolator.
- Expand unit tests.
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these are brought in through python-glue dependency
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This speeds up BAYESTAR by about 50%.
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