This repository contains the ELEPHANT pipeline described in the Pessi et al., 2024.
To use the pipeline, you can clone this repository with the command below
git clone https://github.com/COINtoolbox/extragalactic_hostless.git
After cloning install the necessary packages with the command below
pip install -r requirements.txt
The pipeline parameters can be configured in pipeline_config.json file.
A subset of sample data used in the paper is available in data
folder. The entire dataset used in the paper
can be downloaded from the Fink broker data server
{
"parquet_files_list": path to downloaded input parquet files (An example file available in data folder)
"save_directory": path to a folder to save results
"fwhm_bins": A list of FWHM bin values, default is [1.0, 2.0, 3.0]
"image_shape": Input stamps shape
"is_save_stacked_images": If true, stacked images are saved in results "save_directory" folder,
"sigma_clipping_kwargs": kwargs parameters for astropy sigma_clip function
"hostless_detection_with_clipping": sigma clipping hosteless detection threshold parameters defined in pixels
"number_of_processes": Number of workers used in pythong multiprocessing to process files in parallel
}
To run the pipeline use the command below
python run_pipeline.py
The pipeline generates a result parquet file with the following columns for each input parquet file
- b:cutoutScience_stampData_stacked: stacked science images
- b:cutoutTemplate_stampData_stacked: stacked template images
- b:cutoutDifference_stampData_stacked: stacked difference images
- science_clipped: stacked sigma clipped science image
- template_clipped: stacked sigma clipped template image
- number_of_stamps_in_stacking: number of images used for stacking after FWHM stamp preprocessing
- is_hostless_candidate_clipping: True, if the candidate flagged as hostless by sigma clipping approach
- distance_science: distance from transient to the nearest mask in pixels
- kstest_SCIENCE_N_statistic: Kolmogorov-Smirnov test statistic value for N x N cutout science image
- kstest_SCIENCE_N_pvalue: Kolmogorov-Smirnov test p-value for N x N cutout science image
- kstest_TEMPLATE_N_statistic: Kolmogorov-Smirnov test statistic value for N x N cutout template image
- kstest_TEMPLATE_N_pvalue: Kolmogorov-Smirnov test p-value for N x N cutout template image
The project is a result from COIN Residence Program #7, Portugal, 2023, held in Lisbon, Portugal, from 9 to 16 September 2023 and supported by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) through the Strategic Programme UIDP/FIS/00099/2020 and UIDB/FIS/00099/2020 for CENTRA. The Cosmostatistics Initiative (COIN) is an international network of researchers whose goal is to foster interdisciplinarity inspired by astronomy.