Closed jeff-regier closed 4 months ago
roger that
If we need to improve BLISS's image normalization, the arcsinh transform (torch.arcsinh
) may give us better results than log, which is what we use here:
https://github.com/prob-ml/bliss/blob/3b79b7e057777bcc504331b1fa84fd33ac3c6d31/bliss/encoder/image_normalizer.py#L93
Fiddling with some of the thresholds may help too. Currently the thresholds we use for log transforms are set here: https://github.com/prob-ml/bliss/blob/3b79b7e057777bcc504331b1fa84fd33ac3c6d31/bliss/conf/base_config.yaml#L86
we can now outperform lsst
Wonderful!
Figures 2 & 3 in the DC2 manuscript show BLISS being outperformed by the LSST pipeline for the dimmest light sources. We should confirm that these numbers are correct by rerunning everything. If they are correct, we should improve BLISS's image normalization for these dim light sources.