APOG_public/acsmnode
0
0
Fork 0
mirror of https://gitea.psi.ch/APOG/acsmnode.git synced 2025-06-24 21:21:08 +02:00
Code Issues Packages Projects Releases Wiki Activity

Save changes.

Browse Source
This commit is contained in:
florez_j
2025-02-15 18:20:58 +01:00
parent 25f3ee12a4
commit 0911260f26
5 changed files with 228 additions and 228 deletions
Download Patch File Download Diff File Expand all files Collapse all files

56
TODO.md
View File

@ -1,28 +1,28 @@
# 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~~
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).~~
* 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?
![Screenshot](figures/flagging_app_screenshot.JPG)
# 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~~
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).~~
* 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?
![Screenshot](figures/flagging_app_screenshot.JPG)