Adjacent-Correlation-Analysis documentation¶
Welcome to the Adjacent-Correlation-Analysis documentation!
Contents:
- Features & Design
- Concept & Methods
- Installation & Usage
- Adjacent Correlation Analysis: Spatially-aware 2D histograms for data visualization
- Adjacent Correlation Map: Visualizing Correlations between Quantities
- Time Series Example
- Interactive Exploration
- Manifold Interpretation
- Contribute and Support
- Credit
Features & Design¶
A Python package for performing adjacent correlation analysis on image data.
The input are images 1 and image 2, in the form of Numpy arrays of the same size. The method is designed to reveal regularities by comparing these images through correlations.
The adjacent correlation analysis is performed by calculating and visualizing the adjacency-induced correlation in the phase space. The adjacent correlation map is a spatially-resolved representation of the correlation between the two images.
The methods are designed to represent the data using correlations, which can be used to perform visualization and interactive data explorations.