Blind detection of faint emission line galaxies in MUSE datacubes
Project description
ORIGIN is a software to perform blind detection of faint emitters in MUSE datacubes.
The algorithm is tuned to efficiently detects faint spatial-spectral emission signatures, while allowing for a stable false detection rate over the data cube and providing in the same time an automated and reliable estimation of the purity.
The algorithm implements :
1. A nuisance removal part based on a continuum subtraction combining a Discrete Cosine Transform and an iterative Principal Component Analysis,
2. A detection part based on the local maxima of Generalized Likelihood Ratio test statistics obtained for a set of spatial-spectral profiles of emission line emitters,
3. A purity estimation part, where the proportion of true emission lines is estimated from the data itself: the distribution of the local maxima in the noise only configuration is estimated from that of the local minima.
Citation
ORIGIN is presented in the following paper: Mary et al., A&A, 2020, in press
Links
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Filename, size | File type | Python version | Upload date | Hashes |
---|---|---|---|---|
Filename, size muse_origin-3.2-py3-none-any.whl (86.2 kB) | File type Wheel | Python version py3 | Upload date | Hashes View |
Filename, size muse-origin-3.2.tar.gz (1.1 MB) | File type Source | Python version None | Upload date | Hashes View |
Hashes for muse_origin-3.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | e673a239bcde265e4dea697d94609d16bf7f28a0513b5c57a0625bc6e5aaf681 |
|
MD5 | 6c5ab265c4315a80bda7987e46f81169 |
|
BLAKE2-256 | 50df41cec39739c6520b131b18b468b59210b5b84986b0de86292f2796202da0 |