HTTomo (High Throughput Tomography pipeline)

A user interface (UI) written in Python for fast big data processing using MPI protocols
HTTomo efficiently deals with I/O data operations while enabling processing on a CPU or a GPU
The GPU processing can be performed purely on a device by grouping the methods together
HTTomo can use other libraries as a backend. Currently we support TomoPy and HTTomolib
The methods from the libraries are exposed through YAML templates enabling fast task programming

Install HTTomo as a pre-built conda Python package

Create a fresh conda environment with conda env create --name httomo
This will install all the dependencies required into conda install -c conda-forge -c https://conda.anaconda.org/httomo/ httomo

Install as a Python module

Clone the repository from GitHub using git clone git@github.com:DiamondLightSource/HTTomo.git
Install dependencies from the environment file conda env create --name httomo --file conda/environment.yml. We suggest on using mamba in order to accelerate the resolving time, i.e., conda install -c conda-forge mamba and then mamba env create --name httomo --file conda/environment.yml.
Alternatively you can install from the existing explicit file conda create --name httomo --file conda/explicit/latest.txt
Activate the environment with conda activate httomo
You should choose which backend(s) you'd like to use - either tomopy or httomolib, or both
Install the module + backend(s) with pip install .[httomolib,tomopy]

Setup a Development Environment:

working with the package in the development mode with pip install -e .[dev]

Build HTTomo as a conda Python package

conda build conda/recipe/ -c conda-forge -c https://conda.anaconda.org/httomo/

Running the code:

Install the module as described in "Install as a Python module"
Execute the python module with python -m httomo <args>
For help with the command line interface, execute python -m httomo --help

An example of running the code with test data:

Create an output directory mkdir output_dir/
Go to the home directory and run: python -m httomo run tests/test_data/tomo_standard.nxs samples/pipeline_template_examples/02_basic_cpu_pipeline_tomo_standard.yaml output_dir/

An example of running validation on a YAML pipeline file

python -m httomo check samples/pipeline_template_examples/02_basic_cpu_pipeline_tomo_standard.yaml

Release Tagging Scheme

We use the setuptools-git-versioning package for automatically determining the version from the latest git tag. For this to work, release tags should start with a v followed by the actual version, e.g. v1.1.0a. We have setup a tag_filter in pyproject.toml to filter tags following this pattern.

namannimmo10/httomo