httomolibgpu 2.2

Commonly used tomography data processing methods at DLS.

HTTomolibGPU is a collection of image processing methods in Python for computed tomography. The methods are GPU-accelerated with the open-source Python library CuPy. Most of the methods migrated from TomoPy and Savu software packages. Some of the methods also have been optimised to ensure higher computational efficiency, before ported to CuPy.

The purpose of HTTomolibGPU

HTTomolibGPU can be used as a stand-alone library, see Examples section in Documentation. However, it has been specifically developed to work together with the HTTomo package as its backend for data processing. HTTomo is a user interface (UI) written in Python for fast big tomographic data processing using MPI protocols.

Install HTTomolibGPU as a PyPi package

$ pip install httomolibgpu

Install HTTomolibGPU as a pre-built conda Python package

$ conda create --name httomolibgpu # create a fresh conda environment
$ conda activate httomolibgpu # activate the environment
$ conda install -c httomo httomolibgpu -c conda-forge # for linux users

Setup the development environment:

$ git clone [e-mail]:DiamondLightSource/httomolibgpu.git # clone the repo
$ conda env create --name httomolibgpu --file conda/environment.yml # install dependencies
$ conda activate httomolibgpu # activate the environment
$ pip install -e .[dev] # editable/development mode

Build HTTomolibGPU as a conda Python package

$ conda build conda/recipe/ -c conda-forge -c httomo