AllenInstitute / AllenInstitute/ccf_streamlines
project_coordinates with thickness_type="normalized_layers" does not respect layer_thicknesses
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- Python
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Description
The main issue is described in #9
Repeating here for dicussion, in case it's a feature that I didn't understand
If thickness_type is normalized_layers, a list of layer thicknesses (layer_thicknesses kwarg) must be provided to the projector and each layer is normalised to have this thickness across the whole cortex. However, depth is rescaled later to have the size of the deepest cortical layer in the volume. This seems confusing as one must know this size to the downscale again to the thicknesses that were provided.
The implementation of the micron seems also buggy as the normalisation happens twice (but I don't use it so I haven't tested).
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading issue #9 and tracing the projector path for project_coordinates with thickness_type="normalized_layers". Check how layer_thicknesses is applied and where depth is rescaled, including the reported micron normalization; done means the supplied layer thicknesses remain respected without requiring an additional downscaling step.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- backend
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 45/100