Metadata-Version: 2.1
Name: MARCIA
Version: 0.1.3
Summary: Manual hyperspectral data classifier
Home-page: https://github.com/hameye/marcia
Author: Hadrien Meyer
Author-email: meyerhadrien96@gmail.com
License: GPL v3
Project-URL: Example, https://github.com/hameye/MARCIA/blob/master/examples/Tutorial.ipynb
Project-URL: Source, https://github.com/hameye/MARCIA
Project-URL: Report a bug, https://github.com/hameye/MARCIA/issues
Platform: UNKNOWN
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Typing :: Typed
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: hyperspy (==1.5.2)
Requires-Dist: matplotlib (==3.2.2)
Requires-Dist: numpy (==1.18.5)
Requires-Dist: pandas (==1.0.5)
Requires-Dist: Pillow (==8.1.1)
Requires-Dist: scikit-image (==0.16.2)
Requires-Dist: seaborn (==0.10.1)
Requires-Dist: xlrd (==1.2.0)


# MARCIA - MAsking spectRosCopIc dAtacube
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3929745.svg)](https://doi.org/10.5281/zenodo.3929745)
[![PyPI](https://img.shields.io/badge/MARCIA-v0.1.3-blue.svg?maxAge=2592000)](https://pypi.org/project/MARCIA/)

## Manual classifier for µXRF and EDS/SEM hypercubes
 - Classification is achieved by defining masks that are linear combination of elemental intensities in spectra.
 - Classes can then be extracted and read with hyperspy or PyMca or Esprit


## Install
Just do
```bash
pip install marcia
```

## Use in python
```python
from marcia.mask import Mask
```

## Gallery
![Example](https://github.com/hameye/MARCIA/blob/master/gallery.png)


