Metadata-Version: 2.4
Name: dsigma
Version: 1.2.0
Summary: A Galaxy-Galaxy Lensing Python Package
Author-email: "Johannes U. Lange" <jlange@american.edu>, Song Huang <shuang@tsinghua.edu.cn>
License-Expression: MIT
Project-URL: Homepage, https://github.com/johannesulf/dsigma
Project-URL: Documentation, https://dsigma.readthedocs.io
Project-URL: Repository, https://github.com/johannesulf/dsigma.git
Project-URL: Issues, https://github.com/johannesulf/dsigma/issues
Project-URL: Changelog, https://github.com/johannesulf/dsigma/blob/main/CHANGELOG.md
Keywords: astronomy,weak-lensing
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: astropy
Requires-Dist: astropy-healpix
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: tqdm
Provides-Extra: process
Requires-Dist: h5py>=3.0.0; extra == "process"
Dynamic: license-file

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``dsigma`` is an easy-to-use Python package for measuring gravitational galaxy-galaxy lensing. Using a lensing catalog, it estimates excess surface density around a population of lenses, such as galaxies in the Sloan Digital Sky Survey or the Baryon Oscillation Spectroscopic Survey. It has a flexible API and can utilize data from, DECADE, the Dark Energy Survey (DES), the Kilo-Degree Survey (KiDS), and the Hyper Suprime-Cam (HSC) lensing surveys, among others. With core computations written in C, ``dsigma`` is very fast. Additionally, ``dsigma`` provides out-of-the-box support for estimating covariances with jackknife resampling and calculating various summary statistics.

![plot](https://raw.githubusercontent.com/johannesulf/dsigma/main/docs/plot.png)

## Authors

* Johannes Lange
* Song Huang

## Installation

The easiest way to install ``dsigma`` is to use ``pip`` to install the latest stable version from the Python Package Index (PyPI).

    pip install dsigma

Alternatively, you can install the latest development version from GitHub.

    pip install git+https://github.com/johannesulf/dsigma

## Documentation

Documentation for ``dsigma`` with concept introductions, examples, and API documentation is available on [readthedocs](https://dsigma.readthedocs.io/).

## Attribution

``dsigma`` is listed in the [Astronomy Source Code Library](https://ascl.net/2204.006). If you find the code useful in your research, please cite [Lange & Huang (2022)](https://ui.adsabs.harvard.edu/abs/2022ascl.soft04006L/abstract).

## License

``dsigma`` is licensed under the MIT License.

## Generative AI

Generative AI was used to search for potential bugs in the code and to improve the documentation by finding typos and suggesting minor rewrites. No part of the ``dsigma`` code itself was written entirely or in parts by AI.
