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The Shapely User Manual — Shapely 2.0.6 documentation

shapely.readthedocs.io · 15,364 words · saved by 1 readers

Deterministic spatial analysis is an important component of computational approaches to problems in agriculture, ecology, epidemiology, sociology, and many other fields. What is the surveyed perimeter/area ratio of these patches of animal habitat? Which properties in this town intersect with the 50-year flood contour from this new flooding model? What are the extents of findspots for ancient ceramic wares with maker’s marks “A” and “B”, and where do the extents overlap? What’s the path from home to office that best skirts identified zones of location based spam? These are just a few of the possible questions addressable using non-statistical spatial analysis, and more specifically, computational geometry. Shapely is a Python package for set-theoretic analysis and manipulation of planar features using functions from the well known and widely deployed GEOS library. GEOS, a port of the Java Topology Suite (JTS), is the geometry engine of the PostGIS spatial extension for the PostgreSQL RD

The Shapely User Manual # Author : Sean Gillies, < sean &#46; gillies &#64; gmail &#46; com > Version : 2.1.2 Date : Sep 24, 2025 Copyright : This work is licensed under a Creative Commons Attribution 3.0 United States License . Abstract : This document explains how to use the Shapely Python package for computational geometry. Introduction # Deterministic spatial analysis is an important component of computational approaches to problems in agriculture, ecology, epidemiology, sociology, and many other fields. What is the surveyed perimeter/area ratio of these patches of animal habitat? Which pr

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