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

pip install mbirjax

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-0.5.2.tar.gz (283.1 kB view details)

Uploaded Source

Built Distribution

mbirjax-0.5.2-py3-none-any.whl (313.1 kB view details)

Uploaded Python 3

File details

Details for the file mbirjax-0.5.2.tar.gz.

File metadata

  • Download URL: mbirjax-0.5.2.tar.gz
  • Upload date:
  • Size: 283.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.5

File hashes

Hashes for mbirjax-0.5.2.tar.gz
Algorithm Hash digest
SHA256 a511294635c74f533724ef40557a5ec0df97be3819e2f2818ddcf0b7a095c483
MD5 e994809979079929a7029b665209358c
BLAKE2b-256 eb004adf48118bcc8253a2f330a8753414a08a6f8a69aa3f65b461d48d56ec44

See more details on using hashes here.

File details

Details for the file mbirjax-0.5.2-py3-none-any.whl.

File metadata

  • Download URL: mbirjax-0.5.2-py3-none-any.whl
  • Upload date:
  • Size: 313.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.5

File hashes

Hashes for mbirjax-0.5.2-py3-none-any.whl
Algorithm Hash digest
SHA256 061693908df106b9d6f8629f3a3c5d98308dc9bc895c1ef3773036f4cd9a7237
MD5 614aa6273619ca4fb0ce8cad7df79210
BLAKE2b-256 833d0f45ec8cbef5eb973aca2895a5db6f8b66b9864c6eb3e502b2e1063d4129

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