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I was playing around with the evaluation demo notebook and using BPZ in place of FlexZBoost, it threw an error because a handful of objects have weird colors and small errors, so the chi^2 fit is terrible, and the likelihood=e^-chi^2/2 ends up at 0.0 for all redshifts. This is obviously a problem when you try to normalize the PDF in qp, and the notebook threw an error. So, I should probably add a check to BPZ_lite to set these to a non-zero uniform value rather than 0.0.
The text was updated successfully, but these errors were encountered:
This seems like it should be moved to an issue in qp for dealing with flags in general, which probably just means agreeing on a convention for how to use qp ancillary data to flag bad distributions.
I was playing around with the evaluation demo notebook and using BPZ in place of FlexZBoost, it threw an error because a handful of objects have weird colors and small errors, so the chi^2 fit is terrible, and the likelihood=e^-chi^2/2 ends up at 0.0 for all redshifts. This is obviously a problem when you try to normalize the PDF in qp, and the notebook threw an error. So, I should probably add a check to BPZ_lite to set these to a non-zero uniform value rather than 0.0.
The text was updated successfully, but these errors were encountered: