dkazanc / HTTO

High Throughput TOmography pipeline for reconstruction

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 [e-mail]: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 [e-mail]: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