ongoing efforts #3
Description
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Moved tasks to API “V2” => 3 types (0,1,N output images) to 2 types (0+N or 1).
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Unified handling of no-image-input and multi-image-input
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Basic examples for new_zarr+MIP and new_zarr+copy_data
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Important warning: N-dimensional parallelization (vs one-dimensional parallelization across images) is immediately risky re: huge number of parallelization items. [...]
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New example: custom init task (illumination correction parallelized over channels)
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New example: custom init task for registration, which pairs a reference cycle with all other cycles of each well. Note: well-handling is part of the task.
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Formalized a first version of the task-output API, via
TaskOutputmodel -
Deduplicate redundant new-images list coming from subset parallelization.
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Example of root_dir vs absolute path - ref Absolute paths #2
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Source-to-output mapping: Propagating image attributes in parallel tasks (without the task needing to handle it)
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Remove default values for filters, and only consider those that are set explicitly. EDIT This is currently covered, by defaulting to None. A further review is needed.
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TO CONSIDER: using both include&exclude filters, e.g. to enable selecting "images that do not have a certain attribute equal to something". EDIT: this is currently postponed, as the main intended use case (3D/2D/3D) is nicely covered by the dim=3,dim=2,dim=3 pattern (that is, using a string flag rather than a boolean attribute)
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Review and clean up the parallel-task-output merge strategies
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Add safety check: Total number of custom parallel items is limited (we can later enable a safe=False override)
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Add safety check: no unintended use case is reached when applying both filters and parallelization, if there was an init task. Let’s start with very explicit if/else and error messages, and then iterate.
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Fully enable 3D->2D->3D workflow example.
- TODO: take decision on root_dir vs absolute paths. At the moment none of the two options is blocking. The absolute-paths option requires a bit more string parsing, but that's OK (and part of it can be easily extracted into utils functions, like
def extract_base_parts_from_list_of_absolute_paths(absolute_image_paths: listr[str]) -> dict[str, Any]:
...
return dict(absolute_root_dir=absolute_root_dir, plate_names=plate_names)- Review strategy for backwards-compatibility