Skip to main content

High-performance tomographic reconstruction

Project description

Model-Based Iterative Reconstruction (MBIR) for tomographic reconstruction that is based on the JAX library. Full documentation is available at https://mbirjax.readthedocs.io .

Installing from PyPI

For CPU only:

pip install mbirjax

For CPU with a CUDA12-enabled GPU:

pip install --upgrade mbirjax[cuda12]

Installing from Source

  1. Clone the repository:

    git clone git@github.com:cabouman/mbirjax.git
  2. Install the conda environment and package

    1. Option 1: Clean install using dev_scripts - We provide bash scripts that will do a clean install of MBIRJAX in a new conda environment using the commands:

      cd dev_scripts
      source clean_install_all.sh
    2. Option 2: Manual install - You can also manually install MBIRJAX from the main directory of the repository with the following commands:

      conda create --name mbirjax python=3.10
      conda activate mbirjax
      pip install -r requirements.txt
      pip install .

Running Demo(s)

Run any of the available demo scripts with something like the following:

python demo/<demo_file>.py

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

mbirjax-0.6.5.tar.gz (371.5 kB view details)

Uploaded Source

Built Distribution

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

mbirjax-0.6.5-py3-none-any.whl (426.7 kB view details)

Uploaded Python 3

File details

Details for the file mbirjax-0.6.5.tar.gz.

File metadata

  • Download URL: mbirjax-0.6.5.tar.gz
  • Upload date:
  • Size: 371.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for mbirjax-0.6.5.tar.gz
Algorithm Hash digest
SHA256 7481bcabd6890937d20ec5b8390870f917f66eaaf75b17e3425d4ef5b94db6aa
MD5 fa0722b708359ac74a214602e0ea2de5
BLAKE2b-256 272698beb4f551aece1f20bac1fe611627e70b73cf5df0c82111066cd6416ecf

See more details on using hashes here.

File details

Details for the file mbirjax-0.6.5-py3-none-any.whl.

File metadata

  • Download URL: mbirjax-0.6.5-py3-none-any.whl
  • Upload date:
  • Size: 426.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for mbirjax-0.6.5-py3-none-any.whl
Algorithm Hash digest
SHA256 b1d738d1c1b12961b41a82f3df94dd3bc49fb1b265b5183ded906d35e63c6c46
MD5 b09669ab4fe993990d0113471e072f7e
BLAKE2b-256 61440d255064521cef40a01df02c775a614c75a03be36794d5b342cf2e1c2949

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