Tutorial#
Below are example notebooks that will walk you through the full processing pipeline.
To download these notebooks:
git clone https://github.com/MillerBrainObservatory/LBM-CaImAn-Python.git
cd LBM-CaImAn-Python/demos/notebooks
jupyter lab
See the installation instructions for details on setting up the pipeline before using these notebooks.
Make sure your environment is activated via conda activate lbm
or source LBM-CaImAn-Python/venv/Scripts/activate
before running jupyter lab
.
- 1. Image Assembly
- 2. Batch Helpers
- 3. Registration
- 4. Segmentation
- 4.1. Data path setup
- 4.2. CNMF Parameters
- 4.3. Get values for K and gSig
- 4.4. Set new parameters
- 4.5. Run the CNMF algorithm
- 4.6. Checking for an errors
- 4.7. Evaluate CNMF outputs
- 4.8. Plot CNMF Components
- 4.9. View accepted neurons on a summary image
- 4.10. What happened?
- 4.11. Patches are tiny!
- 4.12. Rerun CNMF
- 4.13. Evaluate CNMF Results
- 4.14. Parameter Gridsearch
- 4.15. Run the
cnmf
batch items - 4.16. Pick the best parameter set
- 4.17. Adjust quality metrics based on evaluation parameters
- 4.18. Extras
- 5. Collate Planes