This is an efficient implementation of Friedman’s SuperSmoother based in Python. It makes use of numpy for fast numerical computation.

For more information, see the github project page: http://github.com/jakevdp/supersmoother

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for Jake.Vanderplas from gravatar.com Jake.Vanderplas

Credits

Author: Jake VanderPlas

License

BSD License (BSD 3-clause)

Classifiers

Report project as malware

Download files

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

Source Distribution

supersmoother-0.4.tar.gz (233.8 kB view details)

Uploaded Source

File details

Details for the file supersmoother-0.4.tar.gz.

File metadata

  • Download URL: supersmoother-0.4.tar.gz
  • Upload date:
  • Size: 233.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for supersmoother-0.4.tar.gz
Algorithm Hash digest
SHA256 aeef4e1b00c32316d624ea7e3ac87c244bf2e59abbb6c042e7791f69ae0669cb
MD5 0d4953293776ed4932b8e14d0adb9f3d
BLAKE2b-256 73d744f69557f2685e80ef7d558b605b080cbb9ae9500c154e4105dbdddb017e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page