Pipeline steps:

PreProcessing - Manually:

• create a copy of examples/demo.json and change the variable to match the new experiment, save it as mouse_name.json
• copy the relevant files (HCR/2P) to the relevant folder (look at examples/file_structure.txt)
• run the pipeline with the new json file. Running everything on colab00 - in terminal run python -- manifest master_pipeline.py examples/CIM132.hjson

A - Automatic M - Manual SA - Semi-Automatic

Steps of the pipeline, will be instructed to the manual stesps

1. parse manifest. I.e: python master_pipeline.py --manifest examples/CIM130.hjson
2. validate manifest
3. generate mean images from low res functional video -extract meanE, meanOverTime, and meanImg from suite2p files.
4. process high res tile sbx files (A):
   • transform sbx to tiff
   • output files:
     • currently outputs all planes (Warped),
5. unwarp tiff files (A):
   • take each plane and use remap & unwarp_config to fix the x axis stretch from the resonant
   • output files:
     • currently outputs all planes (Unwarped)
6. stitch tiff files (M):
   • take each plane and stitch them together manually using bigsticher
7. register HCR rounds - ezfish_pipeline scripts (SA)
   • run 1_scan_lowres_parameters.ipynb with the correct hjson file
   • find the correct paramters that are good for lowres
   • run_2_scan_highres_parameters.ipynb with the correct hjson file
   • find the correct paramters that are good for highres
   • set the correct parameters in the OUTPUT/params.hjson file
   • apply registration to all channels in rounds