/HTTO

High Throughput TOmography pipeline for reconstruction

Primary LanguagePythonBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

HTTO (High Throughput TOmography pipeline)

  • A Python tool for parallel read of h5 tomographic data using MPI protocols
  • The data can be re-chunked, saved and re-loaded (e.g. projection or sinogram-wise)
  • The data is then can be processed by any tomographic packages, e.g. TomoPy, ASTRA

Setup a Development Environment:

Using VScode Dev Containers

  • Clone the repository from GitHub using git clone git@github.com:dkazanc/HTTO.git
  • Open the directory in VSCode and follow the prompts in the bottom right

Using Conda

  • Clone the repository from GitHub using git clone git@github.com:dkazanc/HTTO.git
  • Install dependencies from the environment file conda env create htto --file conda/environment.yml
  • Activate the environment with conda activate htto
  • Install the enviroment in development mode with python setup.py develop

Install as a Python module

  • Ensure all nessacary dependencies are present in the environment (you may wish to refer to the Using Conda directions above)
  • Install the module with python setup.py install

Building the Container

  • Execute docker build . --tag htto

Running the code:

Using the python module

  • Install the module as described in
  • Simply execute the python module with python -m htto <args>
  • For help with the command line interface simply execute python -m htto --help

In a Container

  • Build the container as described in Building the Container
  • Run the container with docker run htto <args>
  • For help with the command line interface simply execute docker run htto python -m htto --help