https://github.com/koda7/point-in-polygon-detection

Developed an optimized solution to the point-polygon query program mentioned by the ACM SIGSPATIAL CUP 2013. Showed differences between naive solution and my solution. Achieved 100% accuracy for both 'INSIDE' and 'WITHIN n' queries.
https://github.com/koda7/point-in-polygon-detection

point-in-polygon sigspatial spatial-analysis within

Last synced: about 2 months ago
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Developed an optimized solution to the point-polygon query program mentioned by the ACM SIGSPATIAL CUP 2013. Showed differences between naive solution and my solution. Achieved 100% accuracy for both 'INSIDE' and 'WITHIN n' queries.

• Host: GitHub
• URL: https://github.com/koda7/point-in-polygon-detection
• Owner: Koda7
• Created: 2023-06-18T17:20:22.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-06-19T18:17:34.000Z (over 1 year ago)
• Last Synced: 2024-01-26T13:19:42.390Z (12 months ago)
• Topics: point-in-polygon, sigspatial, spatial-analysis, within
• Language: Jupyter Notebook
• Homepage:
• Size: 7.99 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Point-in-Polygon-Detection

## Description 

- The codes provided are an optimized solution to the point-polygon query program mentioned by the **ACM SIGSPATIAL CUP

2013**, guaranteeing an absolute accuracy rate of 100%

- The efficient algorithm that accelerates **’inside’** and **’within n’** relationship queries by at 5

seconds utilizing hierarchical indices

- The final report for the project is also attached for further details

## How to Run Code 

- Run `python3 inside.py` to get the results for INSIDE query on the testing data

- Run `python3 within.py` to get the results for 'within n' query on the testing data