Commonly used tomography data processing methods at DLS.
Project description
HTTomolib is a collection of CPU-only image processing methods in Python for computed tomography.
HTTomolib can be used as a stand-alone library, however, it has been specifically developed to work together with the HTTomo package. HTTomo is a user interface (UI) written in Python for fast big data processing using MPI protocols. HTTomolib methods for processing using GPU are accessible in the dedicated HTTomolibGPU repository.
Purpose of HTTomolib
HTTomolib can be used as a stand-alone library, but it has been specifically developed to work together with the HTTomo package. HTTomo is a user interface (UI) written in Python for fast big data processing using MPI protocols.
Install HTTomolib as a pre-built conda Python package
$ conda create --name httomolib # create a fresh conda environment
$ conda activate httomolib # activate the environment
$ conda install -c httomo httomolib -c conda-forge
Setup the development environment:
$ git clone git@github.com:DiamondLightSource/httomolib.git # clone the repo
$ conda env create --name httomolib --file conda/environment.yml # install dependencies
$ conda activate httomolib # activate the environment
$ pip install .[dev] # development mode
Build HTTomolib as a conda Python package
$ conda build conda/recipe/ -c conda-forge -c httomo
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