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Updated TODO list

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florez_j
2024-11-18 11:57:25 +01:00
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# TODO
* Implement flagging-app specific data operations such as:
1. [New item] When verify flags from checklist is active, enable delete-flag button to delete flag associated with active cell on table.
2. [New item] When verify and ready to trasnfer items on checklist are active, enable record-flags button to record verified flags into the HDF5 file.
3. [New item] When all checklist items active, enable apply button to apply flags to the time series data and save it to the HDF5 file.
1. ~~Define data manager obj with apply flags behavior.~~
2. Define metadata answering who did the flagging and quality assurance tests?
3. Update intruments/dictionaries/ACSM_TOFWARE_flags.yaml and instruments/readers/flag_reader.py to describe metadata elements based on dictionary.
4. ~~Update DIMA data integration pipeline to allowed user-defined file naming template~~
5. Design and implement flag visualization feature: click flag on table and display on figure shaded region when feature is enabled
5. ~~Design and implement flag visualization feature: click flag on table and display on figure shaded region when feature is enabled~~
6. Implement schema validator on yaml/json representation of hdf5 metadata
7. Implement updates to 'actris level' and 'processing_script' after operation applied to data/file?
* ~~When `Create Flag` is clicked, modify the title to indicate that we are in flagging mode and ROIs can be drawn by dragging.~~
* Update `Commit Flag` logic:
3. Update recorded flags directory, and add provenance information to each flag (which instrument and channel belongs to).
* ~~Update `Commit Flag` logic:~~
~~3. Update recorded flags directory, and add provenance information to each flag (which instrument and channel belongs to).~~
* Record collected flag information initially in a YAML or JSON file. Is this faster than writing directly to the HDF5 file?