Metadata-Version: 2.4
Name: dsigma
Version: 1.1.0
Author: Song Huang
Author-email: "Johannes U. Lange" <jlange@american.edu>
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
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: astropy
Requires-Dist: scipy
Requires-Dist: scikit-learn
Requires-Dist: astropy-healpix
Requires-Dist: tqdm
Dynamic: license-file

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

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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 broadly applicable API and can utilize data from 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. Below is a plot showing the excess surface density around galaxies in the CMASS sample calculated with `dsigma`.

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

## Authors

* Johannes Lange
* Song Huang

## 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.
