Metadata-Version: 2.4
Name: anacal
Version: 0.6.3
Home-page: https://github.com/mr-superonion/AnaCal/
Author: Xiangchong Li
Author-email: mr.superonion@hotmail.com
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pybind11>=2.2
Requires-Dist: numpy
Requires-Dist: galsim
Requires-Dist: fitsio
Requires-Dist: pydantic
Dynamic: author
Dynamic: author-email
Dynamic: description
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# AnaCal
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Analytic Calibration for Perturbation Estimation from Galaxy Images.

This framework is devised to measure the responses for shape estimators that
have been developed or are anticipated to be created in the future. We intend
to develop a suite of analytical shear estimators capable of inferring shear
with subpercent accuracy, all while maintaining minimal computational time. To
derive the shear response of shapes, we introudce [ pixel shear
response](https://ui.adsabs.harvard.edu/abs/2023MNRAS.521.4904L/abstract), the
derivatives of pixel values with respect to shear distortions, then we
propogate pixel shear response using [quintuple
numbers](https://ui.adsabs.harvard.edu/abs/2025arXiv250616607L/abstract). A
[renoising
approach](https://ui.adsabs.harvard.edu/abs/2025MNRAS.536.3663L/abstract) is
addopt to analytically derive noise bias correction. The currently supported
analytic shear estimators are:
+ [FPFS](https://github.com/mr-superonion/FPFS): A fixed moments method based
  on shapelets including analytic correction for selection, detection and noise
  bias. (see [ref1](https://ui.adsabs.harvard.edu/abs/2018MNRAS.481.4445L/abstract),
  [ref2](https://ui.adsabs.harvard.edu/abs/2022MNRAS.511.4850L/abstract),
  [ref3](https://ui.adsabs.harvard.edu/abs/2024MNRAS.52710388L/abstract),
  and [ref4](https://ui.adsabs.harvard.edu/abs/2025MNRAS.537..507P/abstract).)
+ [NGMIX](https://github.com/esheldon/ngmix): Gassian model fitting.
  (see [ref5](https://ui.adsabs.harvard.edu/abs/2025arXiv250616607L/abstract))

## Installation
Users can clone this repository and install the latest package by
```shell
git clone https://github.com/mr-superonion/AnaCal.git
cd AnaCal
# install required softwares
conda install -c conda-forge --file requirements.txt
# install required softwares for unit tests (if necessary)
conda install -c conda-forge --file requirements_test.txt
pip install . --user
```
or install stable verion
```
pip install anacal
```
or
```
conda install -c conda-forge anacal
```

## Examples
Examples can be found [here](https://github.com/mr-superonion/AnaCal/blob/main/examples/).

## Development

Before sending pull request, please make sure that the modified code passed the
pytest and flake8 tests. Run the following commands under the root directory
for the tests:

```shell
flake8
pytest -vv
```
----
