Metadata-Version: 2.1
Name: msicpe
Version: 1.0.3
Summary: Toolbox for Maths,Signal,Image Teaching @ CPE
Author-email: Marion Foare <marion.foare@cpe.fr>, Eric Van Reeth <eric.vanreeth@cpe.fr>, Arthur Gautheron <arthur.gautheron@cpe.fr>
License: MIT License
Project-URL: Homepage, https://www.cpe.fr
Project-URL: Documentation, https://cpe.pages.in2p3.fr/msi/toolbox/
Project-URL: Moodle, https://e-campus.cpe.fr/course/view.php?id=539
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: plotly
Requires-Dist: sounddevice>=0.5
Requires-Dist: soundfile


A toolbox used for practical sessions at [CPE Lyon](https://www.cpe.fr/).
Developped and maintained for teaching usage only!

# Installation

## In a Jupyter Notebook

```!pip install -U msicpe```

## In a local environment

```pip install -U msicpe```

# Usage example

The example below uses the kurtosis method available in the `tsa` subpackage of `msicpe`.
It requires `numpy.randn` to generate a gaussian distribution of N points.

```python
import numpy as np
from msicpe.tsa import kurtosis
N=10000

x=np.randn(1,N)
kurt=kurtosis(x)

print(kurt)
```
