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Remove unnecessary ccpi conda dependency
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.github/workflows/httomolibgpu_tests_run_iris.yml

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@@ -30,7 +30,6 @@ jobs:
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environment-name: httomo
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create-args: >-
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cupy==12.3.0
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ccpi::ccpi-regulariser
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post-cleanup: 'all'
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init-shell: bash
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.github/workflows/httomolibgpu_zenodotests_iris.yml

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@@ -27,7 +27,6 @@ jobs:
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environment-name: httomo
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create-args: >-
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cupy==12.3.0
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ccpi::ccpi-regulariser
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post-cleanup: 'all'
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init-shell: bash
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README.rst

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@@ -17,14 +17,24 @@ MPI protocols or as well serially.
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Installation
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============
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HTTomolibGPU is available on PyPI, but currently can only be installed into a conda environment
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(due to a dependency being available only through conda).
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HTTomolibGPU is available on PyPI, so it can be installed into either a virtual environment or
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a conda environment.
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Virtual environment
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~~~~~~~~~~~~~~~~~~~
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.. code-block:: console
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$ python -m venv httomolibgpu
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$ source httomolibgpu/bin/activate
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$ pip install httomolibgpu
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Conda environment
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~~~~~~~~~~~~~~~~~
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.. code-block:: console
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$ conda create --name httomolibgpu # create a fresh conda environment
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$ conda activate httomolibgpu # activate the environment
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$ conda install -c ccpi -c conda-forge ccpi-regulariser cupy==12.3.0 # for linux users
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$ conda install -c conda-forge cupy==12.3.0 # for linux users
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$ pip install httomolibgpu
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Setup the development environment:
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.. code-block:: console
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$ git clone [email protected]:DiamondLightSource/httomolibgpu.git # clone the repo
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$ conda env create --name httomolibgpu -c ccpi -c conda-forge ccpi-regulariser cupy==12.3.0 # install dependencies
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$ conda env create --name httomolibgpu -c conda-forge cupy==12.3.0 # install dependencies
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$ conda activate httomolibgpu # activate the environment
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$ pip install -e ./httomolibgpu[dev] # editable/development mode

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