In astronomy jargon, the code performs forced photometry with PSF matching if needed using an optimal weight function given by the signal-to-noise weighted morphology across bands. The minimization itself uses the proximal gradient method PGM. In short, we iteratively compute gradients of the likelihood or of the posterior if priors are included , perform a downhill step, and project the outcome on a sub-manifold that satisfies one or multiple non-differentiable constraints for any of the sources.
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This package provides a stand-alone implementation that contains the core components of the source separation algorithm. The API is reasonably stable, but feel free to contact the authors fred3m and pmelchior for guidance. For bug reports and feature request, open an issue. If you make use of scarlet, please acknowledge Melchior et al.
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Sign up. Source separation in multi-band images by Constrained Matrix Factorization. Branch: master New pull request. Find File. Download ZIP.
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Sign in Sign up. Launching GitHub Desktop Go back. Launching Xcode Launching Visual Studio Latest commit b Jul 5, Scarlet This package performs source separation aka "deblending" on multi-band images. In addition, you'll need numpy pybind11 autograd proxmin. You signed in with another tab or window. All rights reserved. This site is a part of Fandom, Inc. Support Contact PRO. Immortals Academy.
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