Skip to main content

Poisson disc sampling in arbitrary dimensions using Bridson's algorithm, implemented in python using numpy and scipy. Generates so-called "blue noise" that prevents clustering by ensuring each two points are at least "radius" apart.

Project description

Poisson disc sampling

Poisson disc sampling in arbitrary dimensions using Bridson's algorithm, implemented in python using numpy and scipy.

Generates so-called "blue noise" that prevents clustering by ensuring each two points are at least radius apart.

https://www.cs.ubc.ca/~rbridson/docs/bridson-siggraph07-poissondisk.pdf

Implementation is located in poisson_disc.py, while poisson_disc_sampling.ipynb contains some examples.

Available through PyPI as poisson_disc, https://pypi.org/project/poisson-disc/

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

poisson_disc-0.2.1.tar.gz (3.7 kB view details)

Uploaded Source

Built Distribution

poisson_disc-0.2.1-py3-none-any.whl (4.6 kB view details)

Uploaded Python 3

File details

Details for the file poisson_disc-0.2.1.tar.gz.

File metadata

  • Download URL: poisson_disc-0.2.1.tar.gz
  • Upload date:
  • Size: 3.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.4 CPython/3.7.9 Linux/5.4.0-65-generic

File hashes

Hashes for poisson_disc-0.2.1.tar.gz
Algorithm Hash digest
SHA256 ce27112eabf1bbf3ad1b28a15005d31bfff8f45390bcdfd20f8ae0aceae2b0b4
MD5 f8384cabb297637f4d6ff132ef30b028
BLAKE2b-256 bda15cf94da9eb526be07d5544b9ca3f15e3961c527facf78556db9d5ff6b64a

See more details on using hashes here.

File details

Details for the file poisson_disc-0.2.1-py3-none-any.whl.

File metadata

  • Download URL: poisson_disc-0.2.1-py3-none-any.whl
  • Upload date:
  • Size: 4.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.4 CPython/3.7.9 Linux/5.4.0-65-generic

File hashes

Hashes for poisson_disc-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 158ee3f471018cf0d4c1cbd4bd6432fd66c7d56785a91e6234eefbf71e55a599
MD5 4ece4f335d905755524d4e2a41f1acce
BLAKE2b-256 cf6d61237b115905fbb7ad525d04acf5f621c7bff1dd7550041d4b399ce64790

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page