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Python Library for Signal/Image Data Analysis with Transport Methods

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# rohdelab/PyTransKit

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# PyTransKit

Python Transport Based Signal Processing Toolkit

Introduction video

This python package provides signal/image representation software methods (i.e. mathematical transforms) based on the idea of matching signals & images to a reference by pixel displacement operations that are physically related to the concept of transport phenomena. You can think of and use the transforms described below just as one would with the Fourier or Wavelet Transforms. By solving signal/image analysis in transport transform (e.g. Wasserstein embedding) space, one can dramatically simplify and linearize statistical regression problems, enabling the straight forward (e.g. closed form) solution of signal/image detection, estimation, and classification problems with increased accuracy using few training samples, with mathematical understanding and interpretability, better generalization properties, and computationally efficiently.

## 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
``````

Introduction video

## Low Level Functions

### RSCDT

• RSCDT tutorial : Forward and Inverse Transform [10][notebook]
• RSCDT based nearest subspace method for image classification [10]. [notebook]

### CLOT

• Continuous Linear Optimal Transport Transform (CLOT) tutorial [notebook] [nbviewer]

## Classification Examples

• CDT Nearest Subspace (CDT-NS) classifier for 1D data [notebook] [nbviewer]
• SCDT Nearest Subspace (SCDT-NS) classifier for 1D data [8] [notebook] [nbviewer]
• SCDT Nearest Local Subspace (SCDT-NLS) classifier for 1D data [9] [notebook] [nbviewer]
• Radon-CDT Nearest Subspace (RCDT-NS) classifier for 2D data [4] [notebook] [nbviewer]
• 3D Radon-CDT Nearest Subspace (3D-RCDT-NS) classifier for 3D data [notebook] [nbviewer]
• Discrete Radon-CDT Nearest Subspace classifier for illumination-invariant Face Recognition [notebook]
• RSCDT based nearest subspace method for image classification [10]. [notebook]

## Transport-based Morphometry

• Transport-based Morphometry to detect and visualize cell phenotype differences [7] [notebook] [nbviewer]

## Resources

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

Video [tutorials]

## Authors

• Liam Cattell
• Xuwang Yin
• Shiying Li
• Yan Zhuang
• Gustavo K. Rohde
• Soheil Kolouri
• Serim Park

Python Library for Signal/Image Data Analysis with Transport Methods

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