scludam 1.0.8

Star cluster detection and membership estimation based on GAIA data.

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: [e-mail]

Features

Included modules and features are:

• fetcher: Query builder for easy access to GAIA catalogues data, functions to get catalogues and SIMBAD objects information.

• stat_tests: Set of three 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 and parameter values.

• detection: Detection of star clusters in a sample using an improved version of the Star Counts algorithm.

• shdbscan: Soft clustering based on the HDBSCAN algorithm.

• hkde: Kernel density estimation with per-observation or per-dimension variable bandwidth.

• membership: Membership probability estimation based on hkde smoothing.

• pipeline: Pipeline for the detection and membership estimation, with default values and convenience functions.

• plots: Plot detection and membership estimation results alongside SIMBAD objects for better result interpretation.

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Requirements

Python 3.7.6+ are needed 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 in the base environment. The following dependencies will be installed along 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
• 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 (recommended)

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

Update scludam in a Conda environment

conda activate myscludamenv
python -m pip install -U scludam
python -m pip show scludam

Simple user install

Install from PyPi: python -m pip install scludam

Simple user update

Update from PyPi: python -m pip install -U 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]