# SCLUDAM (**S**tar **CLU**ster **D**etection **A**nd **M**embership estimation)
[](https://travis-ci.com/simonpedrogonzalez/scludam)
[](https://simonpedrogonzalez.github.io/scludam-docs/index.html)
[](https://pypi.org/project/scludam/)
[](https://github.com/simonpedrogonzalez/scludam)
[](https://github.com/simonpedrogonzalez/scludam)
[](https://tldrlegal.com/license/gnu-lesser-general-public-license-v3-(lgpl-3))
**SCLUDAM** (**S**tar **CLU**ster **D**etection **A**nd **M**embership 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](https://github.com/simonpedrogonzalez/scludam)
### Authors
- Simón Pedro González.
Email: [simon.pedro.g@gmail.com](simon.pedro.g@gmail.com)
### 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.
--------------------------------------------------------------------------------
### 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]```
Raw data
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"description": "# SCLUDAM (**S**tar **CLU**ster **D**etection **A**nd **M**embership estimation)\n\n[](https://travis-ci.com/simonpedrogonzalez/scludam)\n[](https://simonpedrogonzalez.github.io/scludam-docs/index.html)\n[](https://pypi.org/project/scludam/)\n[](https://github.com/simonpedrogonzalez/scludam)\n[](https://github.com/simonpedrogonzalez/scludam)\n[](https://tldrlegal.com/license/gnu-lesser-general-public-license-v3-(lgpl-3))\n\n\n**SCLUDAM** (**S**tar **CLU**ster **D**etection **A**nd **M**embership estimation) is a Python package for GAIA catalogues **data fetching**, **star cluster detection** and **star cluster membership estimation**.\n\n### Repository and issues\n[https://github.com/simonpedrogonzalez/scludam](https://github.com/simonpedrogonzalez/scludam)\n\n### Authors\n- Sim\u00f3n Pedro Gonz\u00e1lez. \nEmail: [simon.pedro.g@gmail.com](simon.pedro.g@gmail.com)\n\n### Features\nIncluded modules and features are:\n\n- **fetcher**: Query builder for easy access to GAIA catalogues data, functions to get catalogues and SIMBAD objects information.\n\n- **stat_tests**: Set of three clusterability tests that can be used to detect the presence of a cluster in a sample.\n\n- **synthetic**: Classes that can be used to generate synthetic astrometric samples by specifying the distributions and parameter values.\n\n- **detection**: Detection of star clusters in a sample using an improved version of the Star Counts algorithm.\n\n- **shdbscan**: Soft clustering based on the **HDBSCAN** algorithm.\n\n- **hkde**: Kernel density estimation with per-observation or per-dimension variable bandwidth.\n\n- **membership**: Membership probability estimation based on **hkde** smoothing.\n\n- **pipeline**: Pipeline for the detection and membership estimation, with default values and convenience functions.\n\n- **plots**: Plot detection and membership estimation results alongside SIMBAD objects for better result interpretation.\n\n--------------------------------------------------------------------------------\n\n### Requirements\n**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:\n\n- numpy>=1.21.6\n- matplotlib>=3.4.1\n- scipy>=1.7.3\n- astropy>=4.3.1\n- astroquery>=0.4.6\n- pandas>=1.3.5\n- hdbscan==0.8.27\n- scikit-learn>=1.0.2\n- scikit-image>=0.18.1\n- seaborn>=0.11.0\n- attrs>=21.4.0\n- beartype>=0.10.0\n- ordered_set>=4.0.2\n- statsmodels>=0.12.2\n- diptest>=0.4.2\n- typing_extensions>=4.2.0\n\n### User install in a Conda environment (recommended)\nCreate a conda environment named ``myscludamenv`` with python3.8 and ``scludam`` installed\n```\nconda create --name myscludamenv python=3.8 pip --yes\nconda activate myscludamenv\npython -m pip install scludam\n```\n\n### Update scludam in a Conda environment\n```\nconda activate myscludamenv\npython -m pip install -U scludam\npython -m pip show scludam\n```\n\n### Simple user install\nInstall from PyPi:\n```python -m pip install scludam```\n\n### Simple user update\nUpdate from PyPi:\n```python -m pip install -U scludam```\n\n### Dev install\nClone the repo and run the following command in the cloned directory (with your environment activated):\n```python -m pip install -e .[dev]```\n",
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