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-0.6.7.tar.gz (380.7 kB view details)

Uploaded Source

Built Distribution

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

mbirjax-0.6.7-py3-none-any.whl (439.5 kB view details)

Uploaded Python 3

File details

Details for the file mbirjax-0.6.7.tar.gz.

File metadata

  • Download URL: mbirjax-0.6.7.tar.gz
  • Upload date:
  • Size: 380.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for mbirjax-0.6.7.tar.gz
Algorithm Hash digest
SHA256 ea78dfc3113fcb4917c9b273074bad522dfd8a8ace4a0c8aa0c487c90a7f511d
MD5 f5732e272b14e386b6c934c1c9d0d1a3
BLAKE2b-256 02a3528c23c3bd462e8b06457dd6066a9dd24e39bb9db80035bba12a5402896b

See more details on using hashes here.

File details

Details for the file mbirjax-0.6.7-py3-none-any.whl.

File metadata

  • Download URL: mbirjax-0.6.7-py3-none-any.whl
  • Upload date:
  • Size: 439.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for mbirjax-0.6.7-py3-none-any.whl
Algorithm Hash digest
SHA256 166f5a5bfa31fa7cbb6ccd943c85717712e7316ef5d9c144a4684f0363968be1
MD5 45053ccdbe1e974080e8da1b0d800627
BLAKE2b-256 46c6a3d9c2bb6afdc3be28cad4a39de7519420d1ca1530350388edcbddc7df35

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