compute-geometry 0.1.0

Computational Geometry Library

Welcome to the compute-geometry library, a comprehensive computational geometry library for Python. This library is designed to provide a set of tools and algorithms for solving geometric problems, making it a valuable resource for developers and researchers working in areas such as computer graphics, robotics, and geographic information systems.

Features

• Geometry Primitives: Efficient implementations of fundamental geometric primitives, including points, lines, and polygons.

• Algorithms: A variety of computational geometry algorithms, such as convex hull computation, line segment intersection, and Voronoi diagram generation.

• Geometry Operations: Functions for performing common geometric operations, such as distance calculations, area computations, and geometric transformations.

• Visualization: Functions for visualizing geometric objects and algorithms using Matplotlib.

• Documentation: Comprehensive documentation with usage examples to help you quickly integrate the library into your projects.

Installation

You can install the compute-geometry library using pip:

pip install compute-geometry

Getting Started

To get started with the compute-geometry library, import it into your Python script or project:

import compute-geometry as cgeom

Explore the library's documentation to understand the available functionality and how to use it effectively.

Examples

Here are some examples to demonstrate how to use the Geometry library:

# Example 1: Compute the convex hull of a set of points

from cgeom.algorithms import ConvexHull

# create a list of points
points = [(326, 237),(373, 209), (378, 265), (443, 241), (396, 231), (416, 270), (361, 335), (324, 297)]

# create a convex hull object with the list of points
convex_hull = ConvexHull(points)

# plot the convex hull
convex_hull.plot()

# print the indexes of the points that form the convex hull
print('Convex Hull: ', convex_hull.get_indexes())


# Example 2: Compute Voronoi diagram of a set of points

from cgeom.voronoi import VoronoiDiagram

# load a set of points
points = np.loadtxt("./points1.txt")

# create a voronoi diagram object
voronoi = VoronoiDiagram(points)

# build the voronoi diagram
cells = voronoi.build_voronoi_diagram()

# plot the voronoi diagram
voronoi.plot_voronoi(cells)

Contributing

Contributions to the compute-geometry library are welcome! If you have additional algorithms, improvements, or bug fixes, please submit a pull request. Be sure to follow the contribution guidelines outlined in the repository.

License

This library is licensed under the MIT License, allowing you to use, modify, and distribute it for both commercial and non-commercial purposes.

Start exploring the world of computational geometry with the compute-geometry library in Python!