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Prost is a library for rapidly associating transients with their host galaxies.

The code calculates the posterior probability that each galaxy in a search region is the true host galaxy, by considering the transient's fractional offset, redshift (or the prior for the survey), and brightness. The code can query from the following catalogs:

The code also estimates the posterior probability that the true host lies outside of the search cone or is missing from the search catalog. The priors and likelihoods for each property can be customized according to the transient survey. Using the code is straightforward:

import pandas as pd
from astro_prost import associate_sample
from scipy.stats import gamma, halfnorm, uniform

# define a transient catalog 
transient_catalog = pd.DataFrame({
    'name': ['MyTransient'],
    'ra': [237.1981094],
    'dec': [9.2000414]
})

# define a catalog to search -- options are glade, decals, and panstarrs
catalogs = ["decals"]

# define priors and likelihoods
priorfunc_offset = uniform(loc=0, scale=10)
likefunc_offset = gamma(a=0.75)

priors = {"offset": priorfunc_offset}
likes = {"offset": likefunc_offset}

# associate
hosts = \
    associate_sample(
        transient_catalog,
        priors=priors,
        likes=likes,
        catalogs=catalogs,
        name_col='name',
        coord_cols=('ra', 'dec'),
        save=False
)

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PyPI GitHub Workflow Status Read The Docs

Questions? Functionality you'd like to see? Report an issue or reach out at gaglian2[at]mit.edu.

This project was automatically generated using the LINCC-Frameworks python-project-template.

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