Metadata-Version: 2.4
Name: dsigma
Version: 1.2.1
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`` for 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. The core developers did not use AI to write any part of the ``dsigma`` code itself. Code contributions from other developers may use AI, as described in the respective pull requests, and are carefully vetted by the core developers.
