# CEREsFit
[](https://pypi.org/project/ceresfit/)
[](https://github.com/galactic-forensics/CEREsFit/actions/workflows/package_testing.yml)
[](https://codecov.io/gh/galactic-forensics/CEREsFit)
[](https://results.pre-commit.ci/latest/github/galactic-forensics/CEREsFit/main)
[](https://opensource.org/licenses/MIT)
[](https://github.com/psf/black)
The goal of CEREsFit (Correlated Errors Regression Estimate Fit)
is to provide a python package
that allows to calculate linear regressions on data sets with correlated uncertainties.
The calculations follow the methodology published by
[Mahon (1996)](https://doi.org/10.1080/00206819709465336).
Typos and errors that were made in that work have been corrected.
A method to allow calculating a linear regression through a fixed point,
avoiding previously made errors,
is also provided.
## Installation
The package can be installed from `pypi` via:
```
pip install ceresfit
```
## Usage
Below is an example on how to use the package.
```python
>>> import numpy as np
>>> from ceresfit import LinReg
>>> # some data
>>> xdata = np.array([1, 2, 3.1, 4.9])
>>> ydata = np.array([1.1, 1.9, 3, 5.5])
>>> # some uncertainty and correlation
>>> xunc = 0.05 * xdata
>>> yunc = 0.073 * ydata
>>> rho = np.zeros_like(xdata) + 0.5
>>> # do regression
>>> my_reg = LinReg(xdata, xunc, ydata, yunc, rho)
>>> # print out the parameters and their uncertainties
>>> my_reg.slope
(0.9983613298400896, 0.06844666435449052)
>>> my_reg.intercept
(0.05545398718611372, 0.11812746374874884)
>>> my_reg.mswd
2.5105964767071143
```
Detailed example on how to use the class for fitting and plotting the results
can be found
[in these Jupyter notebooks](https://github.com/galactic-forensics/CEREsFit/tree/main/examples).
## Development & Contributing
If you would like to contribute,
clone the GitHub repo and then install the package locally from within the folder via:
```
pip install -e .[dev]
```
If you also want to install the full test environment,
run:
```
pip install -e .[dev,test]
```
Code auto formatting is implemented using
[`pre-commit`](https://pre-commit.com/) hooks.
Full testing of the package can be done with
[`nox`](https://nox.thea.codes/en/stable/index.html).
Please feel free to raise issues on GitHub
and open pull requests if you have a feature to be added.
Tests and adequate docstrings should be provided along with your new code.
