acsmnode/TODO.md

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.
  4. Define data manager obj with apply flags behavior.
  5. Define metadata answering who did the flagging and quality assurance tests?
  6. Update intruments/dictionaries/ACSM_TOFWARE_flags.yaml and instruments/readers/flag_reader.py to describe metadata elements based on dictionary.
  7. Update DIMA data integration pipeline to allowed user-defined file naming template
  8. Design and implement flag visualization feature: click flag on table and display on figure shaded region when feature is enabled
  9. Implement schema validator on yaml/json representation of hdf5 metadata
  10. 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).

• Record collected flag information initially in a YAML or JSON file. Is this faster than writing directly to the HDF5 file?

• Should we actively transfer collected flags by clicking a button? after commit button is pressed, each flag is now stored in an independent json file

• Enable some form of chunk storage and visualization from the HDF5 file. Iterate over chunks for faster display versus access time.

  1. Do I need to modify DIMA?
  2. What is a good chunk size?
  3. What Dash component can we use to iterate over the chunks?