Skip to main content

An adaptive optics alignment tool for ALS beamlines utilizing gpCAM.

Project description

Tsuchinoko

PyPI License Build Status Documentation Status Test Coverage Slack Status

Tsuchinoko is a Qt application for adaptive experiment execution and tuning. Live visualizations show details of measurements, and provide feedback on the adaptive engine's decision-making process. The parameters of the adaptive engine can also be tuned live to explore and optimize the search procedure.

While Tsuchinoko is designed to allow custom adaptive engines to drive experiments, the gpCAM engine is a featured inclusion. This tool is based on a flexible and powerful Gaussian process regression at the core.

A Tsuchinoko system includes 4 distinct components: the GUI client, an adaptive engine, and execution engine, and a core service. These components are separable to allow flexibility with a variety of distributed designs.

Tsuchinoko running simulated measurements

Installation

The latest stable Tsuchinoko version is available on PyPI, and is installable with pip.

pip install tsuchinoko

For more information, see the installation documentation.

Resources

About the name

Japanese folklore describes the Tsuchinoko as a wide and short snake-like creature living in the mountains of western Japan. This creature has a cultural following similar to the Bigfoot of North America. Much like the global optimum of a non-convex function, its elusive nature is infamous.

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

tsuchinoko-1.0.10.tar.gz (80.8 kB view details)

Uploaded Source

Built Distribution

tsuchinoko-1.0.10-py3-none-any.whl (76.2 kB view details)

Uploaded Python 3

File details

Details for the file tsuchinoko-1.0.10.tar.gz.

File metadata

  • Download URL: tsuchinoko-1.0.10.tar.gz
  • Upload date:
  • Size: 80.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.2

File hashes

Hashes for tsuchinoko-1.0.10.tar.gz
Algorithm Hash digest
SHA256 47f46cf8aa5762e828c525838f6526958dd1afa60993629861d923fc63f4c0b3
MD5 2e400dda0b22ddbc5cb89654e5f35f96
BLAKE2b-256 8cb333ffa1c1e97fb2174de758781122619109d854dd56f76ed4d44b34d100a1

See more details on using hashes here.

File details

Details for the file tsuchinoko-1.0.10-py3-none-any.whl.

File metadata

  • Download URL: tsuchinoko-1.0.10-py3-none-any.whl
  • Upload date:
  • Size: 76.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.2

File hashes

Hashes for tsuchinoko-1.0.10-py3-none-any.whl
Algorithm Hash digest
SHA256 fa1d830cb24db301ae0d8131fdd148a91bf548205a4276d5374a23b253579c3b
MD5 e8b5bd83732cf09d0725a9daf43763a7
BLAKE2b-256 18abbb9f5f5815a02b3562f04d747bd7802050ca868e33395fc9018c865928b0

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