Metadata-Version: 2.1
Name: pytranskit
Version: 0.2.1
Summary: Python transport based signal processing toolkit.
Home-page: https://github.com/rohdelab/PyTransKit
Author: Abu Hasnat Mohammad Rubaiyat, Xuwang Yin, Liam Cattell, Soheil Kolouri, Mohammad Shifat-E-Rabbi, Yan Zhuang, Gustavo Rohde
Author-email: ar3fx@virginia.edu, xuwangyin@gmail.com, gustavo.rohde@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

# PyTransKit
Python Transport Based Signal Processing Toolkit

Website and documentation: https://pytranskit.readthedocs.io/


## Installation
The library could be installed through pip
```
pip install pytranskit
```
Alternately, you could clone/download the repository and add the `pytranskit` directory to your Python path
```
import sys
sys.path.append('path/to/pytranskit')

from pytranskit.optrans.continuous.cdt import CDT
```

## Low Level Functions
### CDT
- Cumulative Distribution Transform (CDT) tutorial [[notebook](https://github.com/rohdelab/PyTransKit/blob/master/tutorials/01_tutorial_cdt.ipynb)] [[nbviwer](https://nbviewer.jupyter.org/github/rohdelab/PyTransKit/blob/master/tutorials/01_tutorial_cdt.ipynb)]
### R-CDT
- Radon-CDT tutorial [[notebook](https://github.com/rohdelab/PyTransKit/blob/master/tutorials/02_tutorial_rcdt.ipynb)] [[nbviewer](https://nbviewer.jupyter.org/github/rohdelab/PyTransKit/blob/master/tutorials/02_tutorial_rcdt.ipynb)]
- 3D Radon-CDT tutorial [[notebook](https://github.com/rohdelab/PyTransKit/blob/master/tutorials/05_tutorial_rcdt3D.ipynb)][[nbviewer](https://nbviewer.jupyter.org/github/rohdelab/PyTransKit/blob/master/tutorials/05_tutorial_rcdt3D.ipynb)]
### CLOT
- Continuous Linear Optimal Transport Transform (CLOT) tutorial [[notebook](https://github.com/rohdelab/PyTransKit/blob/master/tutorials/07_tutorial_clot.ipynb)] [[nbviewer](https://nbviewer.jupyter.org/github/rohdelab/PyTransKit/blob/master/tutorials/07_tutorial_clot.ipynb)]

## Classification Examples
- CDT Nearest Subspace (CDT-NS) classifier for 1D data [[notebook](https://github.com/rohdelab/PyTransKit/blob/master/tutorials/04_tutorial_CDT-NS_classifier.ipynb)] [[nbviewer](https://nbviewer.jupyter.org/github/rohdelab/PyTransKit/blob/master/tutorials/04_tutorial_CDT-NS_classifier.ipynb)]
- Radon-CDT Nearest Subspace (RCDT-NS) classifier for 2D data [4] [[notebook](https://github.com/rohdelab/PyTransKit/blob/master/tutorials/03_tutorial_RCDT-NS_classifier.ipynb)] [[nbviewer](https://nbviewer.jupyter.org/github/rohdelab/PyTransKit/blob/master/tutorials/03_tutorial_RCDT-NS_classifier.ipynb)]
- 3D Radon-CDT Nearest Subspace (3D-RCDT-NS) classifier for 3D data [[notebook](https://github.com/rohdelab/PyTransKit/blob/master/tutorials/06_tutorial_3DRCDT-NS_classifier.ipynb)] [[nbviewer](https://nbviewer.jupyter.org/github/rohdelab/PyTransKit/blob/master/tutorials/06_tutorial_3DRCDT-NS_classifier.ipynb)]

## Estimation Examples
- Time delay estimation using CDT [5] [[notebook](https://github.com/rohdelab/PyTransKit/blob/master/Examples/Example01_estimation_delay.ipynb)] [[nbviewer](https://nbviewer.jupyter.org/github/rohdelab/PyTransKit/blob/master/Examples/Example01_estimation_delay.ipynb)]
- Time delay and linear dispersion estimation using CDT [5] [[notebook](https://github.com/rohdelab/PyTransKit/blob/master/Examples/Example02_estimation_delay_linear_dispersion.ipynb)] [[nbviewer](https://nbviewer.jupyter.org/github/rohdelab/PyTransKit/blob/master/Examples/Example02_estimation_delay_linear_dispersion.ipynb)]

## References
1. [The cumulative distribution transform and linear pattern classification, Applied and Computational Harmonic Analysis, November 2018](http://www.sciencedirect.com/science/article/pii/S1063520317300076)
2. [The Radon Cumulative Distribution Transform and Its Application to Image Classification, IEEE Transactions on Image Processing, December 2015](https://ieeexplore.ieee.org/document/7358128)
3. [A continuous linear optimal transport approach for pattern analysis in image datasets, Pattern Recognition, March 2016](https://www.sciencedirect.com/science/article/abs/pii/S0031320315003507)
4. [Radon cumulative distribution transform subspace modeling for image classification, arXiv preprint, 2020](https://arxiv.org/abs/2004.03669)
5. [Parametric Signal Estimation Using the Cumulative Distribution Transform, IEEE Transactions on Signal Processing, May 2020](https://ieeexplore.ieee.org/abstract/document/9099391)

## Resources
External website http://imagedatascience.com/transport/


