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fink-science

User-defined science module for the Fink broker.

  • 3.13.3
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  • PyPI
  • Socket score

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pypi Sentinel PEP8 codecov

Fink Science

This repository contains science modules used to generate added values to alert collected by the Fink broker.

ZTF alert stream

It currently contains:

SourceField in Fink alertsTypeContents
fink_science/xmatchcdsxmatch++stringCounterpart (cross-match) from any CDS catalog or database using the CDS xmatch service. Contains also crossmatch to the General Catalog of Variable Stars and the International Variable Star Index, 3HSP, 4LAC DR3, Mangrove
fink_science/random_forest_sniarf_snia_vs_noniafloatProbability to be a rising SNe Ia based on Random Forest classifier (1 is SN Ia). Based on https://arxiv.org/abs/2111.11438
fink_science/snnsnn_snia_vs_noniafloatProbability to be a SNe Ia based on SuperNNova classifier (1 is SN Ia). Based on https://arxiv.org/abs/1901.06384
fink_science/snnsnn_sn_vs_allfloatProbability to be a SNe based on SuperNNova classifier (1 is SNe). Based on https://arxiv.org/abs/1901.06384
fink_science/microlensingmulensfloatProbability score to be a microlensing event by LIA
fink_science/asteroidsroidintDetermine if the alert is a Solar System object
fink_science/kilonovarf_kn_vs_nonknfloatprobability of an alert to be a kilonova using a Random Forest Classifier (binary classification).
fink_science/nalerthistnalerthistintNumber of detections contained in each alert (current+history). Upper limits are not taken into account.
fink_science/ad_featureslc_*dict[int, array]Numerous light curve features used in astrophysics.
fink_science/agnrf_agn_vs_nonagnfloatProbability to be an AGN based on Random Forest classifier (1 is AGN).
fink_science/anomaly_detectionanomaly_scorefloatAnomaly score (lower values mean more anomalous observations)
fink_science/t2t2dic[str, float]Classifier based on Transformers. Based on https://arxiv.org/abs/2105.06178

You will find README in each subfolder describing the module.

ELASTiCC stream (Rubin-like simulated data)

These modules are being tested for Rubin era on the LSST-DESC ELASTiCC data challenge:

SourceField in Fink alertsTypeContents
fink_science/agn_elasticcrf_agn_vs_nonagnfloatProbability to be an AGN based on Random Forest classifier (1 is AGN).
fink_science/random_forest_sniarf_snia_vs_noniafloatProbability to be a rising SNe Ia based on Random Forest classifier (1 is SN Ia). Based on https://arxiv.org/abs/2111.11438
fink_science/snnsnn_snia_vs_noniafloatProbability to be a SNe Ia based on SuperNNova classifier (1 is SN Ia). Based on https://arxiv.org/abs/1901.06384
fink_science/snnbroadarray[float]Broad classifier based on SNN. Returns [class, max(prob)].
fink_science/catsfinearray[float]Fine classifier based on the CBPF Algorithm for Transient Search. Returns [class, max(prob)].

How to contribute

Learn how to design your science module, and integrate it inside the Fink broker.

Installation

If you want to install the package (broker deployment), you can just pip it:

pip install fink_science

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