Skip to main content

No project description provided

Project description

pyrao

pyrao is a few things:

  • a Python wrapper for rao package - a set of Adaptive Optics (AO) tools written in Rust,
  • a standalone AO simulator with Python APIs, fast enough to run 8m class simulations at real time on a modest laptop,
  • a data stream generator for developing tools based on ImageStreamIO,
  • (todo) a Gymnasium formatted environment for developping and testing reinforcement learning.
  • an experiment in linear algebra + statistics, optimal control/estimation, python-wrapped-rust (using PyO3).
  • (todo) a performance evaluation tool - provided you can simulate your system in rao.

There are many things that pyrao is not, but most importantly:

  • pyrao is not an "end-to-end numerical simulation tool for AO" (see [#assumptions])
  • pyrao is not an RTC in its own right, though it emulates some functionalities of one.

Assumptions

We assume that everything in the AO loop is linear, and all sources of noise are additive Gaussian iid processes. For example, we assume that the measurements are a linear combination of atmospheric phase (according to some sampling of von Karman layers), actuator commands (according to some influence functions), and a noise vector with a specified covariance matrix.

Disclaimer

This is presently a hobby-project, so development may be slow and/or unpredictable. However, if you have a change you would like to see, or a feature you would like added, I encourage you to file an issue - since it's likely something I haven't considered and it could prove useful to others. If you make a change yourself and you think others might also find it useful, please consider making a pull request so that I can include your edits in this repo. If you have any other feedback, feel free to share it with me directly via email: jesse.cranney@anu.edu.au.

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

rao-0.1.3.tar.gz (14.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

rao-0.1.3-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (416.6 kB view details)

Uploaded CPython 3.8+manylinux: glibc 2.17+ x86-64

File details

Details for the file rao-0.1.3.tar.gz.

File metadata

  • Download URL: rao-0.1.3.tar.gz
  • Upload date:
  • Size: 14.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: maturin/1.7.7

File hashes

Hashes for rao-0.1.3.tar.gz
Algorithm Hash digest
SHA256 a95533ee7c0819b10456d772bdd8aa3925be61c312be8ba6f9354c1461ffa318
MD5 b008607f96462f82dc1cba8d279f55f0
BLAKE2b-256 38b8123c57f5ded010892492f657905d50aeb332b2cd46c78fa693c6655ac4f3

See more details on using hashes here.

File details

Details for the file rao-0.1.3-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rao-0.1.3-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b4b2406eb8605b60ac78eec0948c43d28fe4fc7217ab5c483136ba540205bee2
MD5 9cb5694f8df118b7a66fd5f8f331f7ba
BLAKE2b-256 3926964ec4fe506294abe6f4a2f081bfbffbf3a077970cd68ab5a6dd424e8a78

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 Pingdom Monitoring Sentry Error logging StatusPage Status page