scripts

Static hosting:

• Source: https://github.com/TomographicImaging/scripts
• Rendered: https://tomographicimaging.github.io/scripts

Environment files for installing software

CIL-Demos

cil_demos.yml - for installing the latest release of CIL-Demos on a system with a GPU.

cil_demos_cpu.yml - for installing the latest release of CIL-Demos on a system without a GPU.

CILViewer

cilviewer_ui - for installing the latest release of CILViewer, with packages needed to run the GUI.

Script for Testing CIL demos

test_notebooks_sequential.py is a script for testing the CIL-Demos

To use it:

1. Clone CIL-Demos, if you haven't already, and move to the branch of CIL-Demos you would like to test.

2. Clone scripts

3. Download all datasets used by the CIL-Demos notebooks you would like to test.

4. Create an environment using:

   conda env create -f https://tomographicimaging.github.io/scripts/env/cil_test_demos.yml

5. Clone CIL, if you haven't already, and move to the branch of CIL you would like to test the demos with.

6. Activate the environment you created:

   conda activate cil_test_demos

7. Navigate into the CIL directory and install CIL into this environment:

   pip install -e .

8. The script uses nbmake and needs to point to the kernel to run the notebooks with. We need to make sure our conda environment is registered with the correct jupyter kernel name. Run:

   jupyter kernelspec list

   If there is a kernel with name cil_test_demos then move to step 9. If not, run:

   python -m ipykernel install --user --name cil_test_demos --display-name "cil_test_demos"

9. At the top of the test_notebooks_sequential.py file, update these variables: CIL_DEMOS_DIR - should point to your clone of CIL-Demos DATA_PATH and DATA_PATH_ALT should point to directories where the CIL-Demos data is saved.

10. Run test_notebooks_sequential.py. This is likely to take quite a long time. It will create the following inside the current directory:

    test_notebooks_*.log log file (with name including date and time of run): This shows which notebooks have run and whether they have passed or failed.

    tmp_notebooks directory: This contains the run and rendered .ipynb notebook files.