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matchmaker

MATCHMAKER is a set of python classes and functions to perform cross-matching of catalogs and parameter comparisons

https://github.com/macrocosme/matchmaker

Science Score: 26.0%

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Repository

MATCHMAKER is a set of python classes and functions to perform cross-matching of catalogs and parameter comparisons

Basic Info
  • Host: GitHub
  • Owner: macrocosme
  • License: bsd-3-clause
  • Language: Python
  • Default Branch: principale
  • Homepage:
  • Size: 180 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created almost 2 years ago · Last pushed almost 2 years ago
Metadata Files
Readme License Codemeta

README.md

MATCHMAKER

MATCHMAKER is a python package to perform cross-matching of catalogs and parameter comparisons.

USAGE

Firstly, create a Catalog instance within matchmaker.matchmaker.datasets for each of your datasets. Example instances are provided. The instance requires a load_data function that loads the dataset into a pandas Dataframe. Current APIs are provided for input files in csv and fits format. At least two datasets are required to perform cross-matching (or compare a unique dataset to itself). For each dataset, the Catalog class requires, at minimum, how to access the columns corresponding to right ascension (RA) and declination (DEC).

You can then perform cross-matching using matchmaker.matchmaker.crossmatch.crossmatch, specifying two Catalog inputs, spatial separation threshold for matching with corresponding physical unit, and wether or not to filter within an ellipse around the source centroid. Catalog masks can be provided to work on partial datasets.

One can evaluate chance allignment probabilities with one of matchmaker.matchmaker.stats.chance_association (circle) or matchmaker.matchmaker.stats.chance_association_ab (ellipse), specifying the source catalog Catalog, the name of the target Catalog, and internal indexes of matched sources, number of sources in target catalog and the area they cover (to get the target catalog source density). A monte carlo method is also made available.

Results are stored under Catalog(name='self').matches[Catalog(name='other').name] and include a variety of information about the cross-section (mask for source, matched indexes for target (idx), shortcuts (mask_idx=numpy.where(mask)[0], filtered_idx=idx[mask]), chance association). One can customize these masks.

Loaded data in a Catalog object can be accessed as a Pandas.Dataframe instance, letting use all of pandas functionalities (.loc, .iloc, .iterrows(), .isna()). Further access parameters can be found via Catalog().cols to retreive dataframe column names programmatically (e.g. Catalog().cols.<column_name>.label). Similarly, columns units can be found under Catalog().cols.<column_name>.unit.

Owner

  • Name: Dany Vohl
  • Login: macrocosme
  • Kind: user
  • Company: Anton Pannekoek Institute for Astronomy, University of Amsterdam; ASTRON, The Netherlands

CodeMeta (codemeta.json) 

{
  "@context": "https://doi.org/10.5063/schema/codemeta-2.0",
  "@type": "SoftwareSourceCode",
  "license": "https://spdx.org/licenses/BSD-3-Clause",
  "codeRepository": "git+https://gitlab.in2p3.fr/escape2020/virtual-environment/matchmaker.git",
  "datePublished": "2023-05-09",
  "dateModified": "2023-05-09",
  "name": "matchmaker",
  "version": "v1.0",
  "description": "matchmaker is a python package to perform cross-matching of (astronomical) catalogs and manipulate results.",
  "applicationCategory": "Astronomy",
  "readme": "https://gitlab.in2p3.fr/escape2020/virtual-environment/matchmaker",
  "softwareVersion": "v1.0",
  "keywords": [
    "Catalogs cross-matching"
  ],
  "programmingLanguage": [
    "Python"
  ],
  "author": [
    {
      "@type": "Person",
      "@id": "http://orcid.org/0000-0003-1779-4532",
      "givenName": "D.",
      "familyName": "Vohl",
      "email": "d.vohl@uva.nl",
      "affiliation": {
        "@type": "Organization",
        "name": "University of Amsterdam, ASTRON"
      }
    }
  ],
  "maintainer": [
    {
      "@type": "Person",
      "@id": "http://orcid.org/0000-0003-1779-4532",
      "givenName": "D.",
      "familyName": "Vohl",
      "email": "d.vohl@uva.nl",
      "affiliation": {
        "@type": "Organization",
        "name": "University of Amsterdam, ASTRON"
      }
    }
  ]
}

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Dependencies

requirements.txt pypi
  • aplpy *
  • astropy ==4.3.1
  • astroquery *
  • matplotlib ==3.5.1
  • pandas ==1.3.2
  • specutils *
  • tqdm *
  • wget *