JOSS review item: CI

[Matthew-Jennings]

1. FWIW, my investigations show ~75% test coverage. This isn't too bad, but it might be worth dedicating some spare time to lifting it a little, especially for the files with little-to-no coverage. See mirp_coverage.xlsx for per-file coverage details.

2. Improvements to temporary test directory handling are in Implement tmp_path #74. Not important for JOSS publication.

3. Comments related to implementation of GitHub CI can be found here and here. Not important for JOSS publication.

[alexzwanenburg]

I have increased test coverage to 89% by writing additional tests. Some tests remain.

[Matthew-Jennings]

I get 84%. See mirp_coverage_24-04-07.xlsx. Not quite 89%! But probably enough 😄

For fair comparison, I'm using pytest-cov with the following command run from the repo's root:

pytest -v --color=yes --cov=mirp --cov-report html --cov-report term --cov-report xml:cov.xml -n=14

Very pleased to find that I was able to run pytest-xdist (the -n=14) with no issue!

[alexzwanenburg]

Thanks again for the pull request that made pytest-xdist possible. One difference may be that my coverage results included the tests themselves.

[alexzwanenburg]

To expose (and test) SUV conversion we need to do the following:

• Add piping for passing arguments from StandardWorkflow.standard_image_processing to ImageDicomFilePT.load_data.
• Expose the following parameters by adding them to ImagePostProcessingClass:
  • suv_type with default body_weight.
  • decay_correction_event with default administration. There is no practical reason why decay correction should be configurable.
• Add documentation for new parameters.
• Add parameters to xml.
• Integrate SUVScalingObj into ImageDicomFilePT as private methods, since the required metadata for SUV conversion is not present in different file formats.
  • After consideration: split SUVScalingObj into parts related to decay correction, and parts related to SUV conversion.
  • Decay correction should take place as part of load_data.
  • SUV conversion (for now) takes place as part of load_data. In the future data conversion may move into the standard workflow to make it more explicit. This would require adding required data (weight, height, biological sex, voxel units) to PETImage objects.
• Add unit tests for parameters and parameter combinations.

[alexzwanenburg]

I made some progress in coverage with version 2.2.1. I am leaving this issue open as I need to create new test data to test remaining parts of the code.

[Matthew-Jennings]

No worries, @alexzwanenburg. At 86% coverage, I'm happy to consider this item "closed" from a JOSS review perspective.