Metadata-Version: 2.2
Name: httomolibgpu
Version: 2.3.1
Summary: Commonly used tomography data processing methods at DLS.
Author-email: Daniil Kazantsev <daniil.kazantsev@diamond.ac.uk>, Yousef Moazzam <yousef.moazzam@diamond.ac.uk>, Naman Gera <naman.gera@diamond.ac.uk>
License: BSD-3-Clause
Project-URL: Repository, https://github.com/DiamondLightSource/httomolibgpu
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.10
Classifier: Environment :: GPU :: NVIDIA CUDA
Requires-Python: >=3.10
Description-Content-Type: text/x-rst
License-File: LICENSE
Requires-Dist: cupy==12.3.0
Requires-Dist: nvtx
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: pillow
Requires-Dist: scikit-image
Requires-Dist: tomobar
Requires-Dist: ccpi-regularisation-cupy
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Requires-Dist: pytest-xdist; extra == "dev"
Requires-Dist: pytest-benchmark; extra == "dev"
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Requires-Dist: pre-commit; extra == "dev"
Requires-Dist: pyfftw; extra == "dev"

HTTomolibGPU is a library of GPU accelerated methods for tomography
--------------------------------------------------------------------

**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 <https://cupy.dev/>`_. Most of the
methods migrated from `TomoPy <https://tomopy.readthedocs.io/en/stable/>`_ and `Savu <https://savu.readthedocs.io/en/latest/>`_ software packages.
Some of the methods also have been optimised to ensure higher computational efficiency, before ported to CuPy.

The purpose of HTTomolibGPU
===========================

Although **HTTomolibGPU** can be used as a stand-alone library, it has been specifically developed to work together with the 
`HTTomo <https://diamondlightsource.github.io/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 or as well serially.

Install HTTomolibGPU as a PyPi package
=========================================================
.. code-block:: console

   $ pip install httomolibgpu

Install HTTomolibGPU as a pre-built conda Python package
=========================================================
.. code-block:: console

   $ 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:
==================================

.. code-block:: console

   $ git clone git@github.com: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
============================================

.. code-block:: console

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

