Skip to main content

Phase Retrieval algorithms in Python

Project description

PRiPy

Phase Retrieval in Python.

This package intends to implement common phase retrieval algorithms for Adaptive Optics (AO), for use in Python-based AO simulators such as COMPASS and CEO. Ideally, these algorithms should have a common and minimal API, in order to accelerate the testing of various algorithms on a given optical system.

TODO

  • Sandbox examples (numpy AND cupy compatible),
  • CEO examples.
  • COMPASS examples,

Early implementation goals:

  • FF: Fast and Furious Wavefront Sensing,
  • LIFT: LInearised Focal-plane Technique,
  • GS: classical Gerchberg Saxton algorithm for phase estimation,
  • TAME: Taylor-based Moving horizon Estimation,

Medium-term goals:

  • COMPASS API,
  • CEO API.
  • PyPI for pip install

Installation

git clone git@github.com/jcranney/pripy.git
cd pripy
pip install .

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

pripy-0.1.2.tar.gz (11.7 kB view details)

Uploaded Source

Built Distribution

pripy-0.1.2-py3-none-any.whl (11.9 kB view details)

Uploaded Python 3

File details

Details for the file pripy-0.1.2.tar.gz.

File metadata

  • Download URL: pripy-0.1.2.tar.gz
  • Upload date:
  • Size: 11.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.5

File hashes

Hashes for pripy-0.1.2.tar.gz
Algorithm Hash digest
SHA256 064a6d1ea546d5f1e477e9bc98c16b855cb90b9d0285e5d245a50bdf6b22251e
MD5 5b43e4ddfe02ab23959219ce58484380
BLAKE2b-256 17e6eca03a046b8a9f8f48136202c45bf7cb4f9269b40ddfdb66d5a2e2518d1c

See more details on using hashes here.

File details

Details for the file pripy-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: pripy-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 11.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.5

File hashes

Hashes for pripy-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 f4d55f23f0973870409472c4383baa5eef45e12878fd0e6d4813d724bd72f5c1
MD5 4274be978cb68af5582c073de91c0f72
BLAKE2b-256 28198c531691a6c8017336ff21dd102c5b4bb463bc98774aa264b6c6f4ff5777

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