Star cluster detection and membership estimation based on GAIA data.
Project description
SCLUDAM (Star CLUster Detection And Membership estimation)
scludam (Star CLUster Detection And Membership estimation) is a Python package for GAIA catalogues data fetching, star cluster detection and star cluster membership estimation.
Repository and issues
https://github.com/simonpedrogonzalez/scludam
Authors
- Simón Pedro González email: simon.pedro.g@gmail.com
Features
Currently scludam is a work in progress. Modules and features already included are:
-
fetcher: simple query builder to get data from the GAIA catalogue more easily, and some extra useful functions.
-
stat_tests: set of 3 clusterability tests that can be used to detect the presence of a cluster in a sample.
-
synthetic: classes that can be used to generate synthetic astrometric samples by specifying the distributions to use and parameter values.
-
detection: classes that can be used to detect the presence of a cluster in a sample.
-
shdbscan: soft clustering based on the HDBSCAN algorithm.
-
hkde: kernel density estimation with variable bandwidth.
-
membership: membership calculation based on hkde smoothing.
-
pipeline: pipeline for the detection and membership estimation, with default values and convenience functions.
Requirements
You need Python 3.7.6+ and R 3.6.3+ to run scludam. It is recommended to install scludam in a separate environment created with pyenv or conda, to avoid dependencies issues with other preinstalled packages you may have in the base environment. The following dependencies will be installed with SCLUDAM:
- numpy>=1.21.6
- matplotlib>=3.4.1
- scipy>=1.7.3
- astropy>=4.3.1
- astroquery>=0.4.6
- pandas>=1.3.5
- hdbscan==0.8.27
- scikit-learn>=1.0.2
- scikit-image>=0.18.1
- rpy2>=3.5.2
- seaborn>=0.11.0
- attrs>=21.4.0
- beartype>=0.10.0
- ordered_set>=4.0.2
- statsmodels>=0.12.2
- diptest>=0.4.2
- typing_extensions>=4.2.0
User install in a Conda environment
Create a conda environment named myscludamenv
with python3.8 and scludam
installed
conda create --name myscludamenv python=3.8 pip --yes
conda activate myscludamenv
python -m pip install scludam
User install
Install from PyPi:
python -m pip install scludam
Dev install
Clone the repo and run the following command in the cloned directory (with your environment activated):
python -m pip install -e .[dev]
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