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The code is available in Matlab, Python and Thunder(Spark) -- Matlab -- Files: * Demo.m - Run with option 1, and then option 2 to see how code works * RunFISTA.m - runs the "group lasso" code to detect neuronal centers and activity * RunNMFmethod.m - run coordinate descent gready NMF to find neuronal activity and (non-negtive) shapes, based on group lasso initialization * GetDefaultInput.m - fetch default parameters for each dataset (params,flags,specs) Folders: * Misc - Auxilary Functions * Plotting - Auxilary Functions for plotting only * Datasets - some datasets for demonstrations -- Python -- Files: * Demo.py - Run with option 1, 2 or 3 to see how code works * BlockGroupLasso.py - a pythonized version of RunFISTA.m * BlockLocalNMF.py - a pythonized version of RunNMFmethod.m -- Thunder (https://github.com/j-friedrich/thunder/tree/LocalNMF) -- File: * DemoThunder.ipynb - Change option to 1, 2 or 3 in ipython notebook to see how code works
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Automatic ROI Detection
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- Jupyter Notebook 86.3%
- MATLAB 10.2%
- Python 3.5%