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    Clustar

    Release: 1.2.1

    Date: June 27, 2021

    Overview

    A python package for processing and analyzing protostars/protoplanetary disks in astronomical data in Flexible Image Transport System (FITS) images.

    These files contain grayscale images represented as two-dimensional arrays, with each pixel containing the intensity values, and headers containing the telescope observational parameters.

    Clustar simplifies and expediates the identification pipeline of FITS files by automating the preprocessing, grouping, and fitting for a large amount of FITS files.

    Requirements

    Clustar 1.2.1 requires

    • GEOS >= 3.3
    • Shapely >= 1.7.1

    Both of these dependencies are available on https://anaconda.org/conda-forge.

    conda install -c conda-forge geos
    conda install -c conda-forge shapely 
    

    Installation

    Clustar is available on PyPI and can be installed using pip:

    pip install clustar
    

    Singular Usage

    Detect celestial objects in a singular FITS image by creating a ClustarData object.

    from clustar.core import ClustarData
    
    # Create the 'ClustarData' object by specifying the path to FITS file.
    cd = ClustarData(path='~/data/example.fits', threshold=0.025)
    
    # Visualize the detected groups.
    cd.identify()
    
    # Access individual 'Group' objects.
    cd.groups
    

    Multiple Usage

    Detect celestial objects in a directory containing multiple FITS images by creating a Clustar object.

    from clustar.search import Clustar
    
    # Setup 'Clustar' object.
    cs = Clustar(radius_factor=0.95, threshold=0.025)
    
    # Execute pipeline on directory containing FITS files.
    cs.run(directory='~/data/')
    
    # Access individual 'ClustarData' objects.
    cs.data
    
    # Check which FITS files raised an error.
    cs.errors
    
    # Inspect 'ClustarData' variables for all groups in each FITS file.
    cs.display(category='all')
    

    Modules

    1. base.py

      Internal module for testing clustar modules.

    2. core.py

      Contains the ClustarData class, which is responsible for executing the entire project pipeline for detecting groups in a single FITS image.

    3. denoise.py

      Clustar module for denoising-related methods.

    4. fit.py

      Clustar module for fitting-related methods.

    5. graph.py

      General module for graphing-related methods.

    6. group.py

      Clustar module for grouping-related methods.

    7. search.py

      Contains the Clustar hierarchical class, which is responsible for transforming all available FITS images in a specified directory into their respective ClustarData objects.

    Notes

    Visit https://clustar.github.io/ for additional information.

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