Metadata-Version: 2.1
Name: powerxrd
Version: 0.0.8
Summary: Simple tools to handle powder XRD (and XRD) data with Python
Home-page: https://github.com/andrewrgarcia/powerxrd
Author: Andrew Garcia, PhD
License: MIT
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: numpy

# powerxrd
Simple tools to handle powder XRD (and XRD) data



## Installation

```ruby
pip install powerxrd
```
## Usage Example

```ruby
import powerxrd as xrd
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt


df = pd.read_csv('/your-path-to-powerxrd/sample1.xy', sep='\t', header=None)  
x,y = np.array(df).T
x,y = xrd.backsub(x,y)

plt.plot(x,y)
plt.xlabel('2 $\\theta$')
```
![alt text](https://github.com/andrewrgarcia/powerxrd/blob/main/img/readme.png?raw=true)

## Contributors

- [Andrew Garcia](https://github.com/andrewrgarcia) - creator and maintainer

## Contributing

1. Fork it (<https://github.com/your-github-user/tensorscout/fork>)
2. Create your feature branch (`git checkout -b my-new-feature`)
3. Commit your changes (`git commit -am 'Add some feature'`)
4. Push to the branch (`git push origin my-new-feature`)
5. Create a new Pull Request



