Metadata-Version: 2.1
Name: adadjust
Version: 0.1.30
Summary: A package to fit functions on data
Home-page: https://github.com/Advestis/adadjust
Author: Philippe COTTE
Author-email: pcotte@advestis.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 5 - Production/Stable
Requires-Python: >=3.7
Description-Content-Type: text/markdown

---
permalink: /docs/index.html
---

**The official documentation is available at https://advestis.github.io/adadjust/**

# AdAdjust

Package allowing to fit any mathematical function to (for now 1-D only) data.


## Installation

```bash
pip install adadjust
```

## Usage

```python
from adadjust import Function
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams.update({"text.usetex": True})  # Needs texlive installed

nsamples = 1000
a = 0.3
b = -10
xstart = 0
xend = 1
noise = 0.01
x = np.linspace(xstart, xend, nsamples)
y = a * x ** 2 + b + np.random.normal(0, noise, nsamples)


def linfunc(xx, p):
    return xx * p[0] + p[1]


def square(xx, p):
    return xx ** 2 * p[0] + p[1]


func = Function(linfunc, "$a \\times p[0] + p[1]$")
func2 = Function(square, "$a^2 \\times p[0] + p[1]$")

params = func.fit(x, y, np.array([0, 0]))[0]
rr = func.compute_rsquared(x, y, params)

params2 = func2.fit(x, y, np.array([0, 0]))[0]
rr2 = func2.compute_rsquared(x, y, params2)

table = Function.make_table(
    [func, func2], [params, params2], [rr, rr2], caption="Linear and Square fit", path_output="table.pdf"
)
table.compile()
Function.plot(x, [func, func2], [params, params2], y=y, rsquared=[rr, rr2])
plt.gcf().savefig("plot.pdf")
```

**NOTE** : to have pretty gaphs, put the line `plt.rcParams.update({"text.usetex": True})` just after you imported adadjust.
This requiers that you have TexLive full installed on your computer.

The result will be :

![Alt text](tests/data/plot.png)


