Supplementary Materials for "2D AMIS Normalization for Spatial Data"

This dataset accompanies the article "2D ADAPTIVE MULTI-INTERVAL SCALE (AMIS): METHOD FOR NORMALIZATION AND VISUALIZATION OF SPATIAL DATA" (https://doi.org/10.5281/zenodo.20577673). The dataset contains: 1. Example data: - Reference dataset (32 teams, Russian Championship 2012-13, 25×40 grid, 32,000 observations) - Match data (France vs Croatia, 2018 World Cup final; England vs Germany, 1966 World Cup final) 2. Software: - Executable tool (2D AMIS normalizer for Windows, packaged as 2D_AMIS_Tool_eng.zip) - Python source code (2D_AMIS_Tool_eng.py) 3. Results (figures from the article): - AMIS-normalized heatmaps (cellwise, 25×40 grid) - AMIS transformation curve for central cell (row 13, column 20) - Spatial profile (row 13, Croatia) Method summary: The 2D AMIS method normalizes each spatial cell individually using adaptive multi-interval scaling, transforming raw data into a unified [0, 100] scale where 50 represents the reference norm. Unlike min-max or z-score normalization, AMIS accounts for the local density of data distribution. Software notes: - The executable file is provided as .zip due to archiving policies. Unzip before use. - First launch may take 10-30 seconds due to Python initialization. License: - Source code: MIT - Data: CC BY 4.0 Related links: - GitHub: https://github.com/Famimot/2D_AMIS_Tool - Related preprint (SSRN): https://ssrn.com/abstract=6792479