Common functions and infrastructure built during my PhD projects (custom-made automatic-tracking based on computer vision, caiman-based 2p-Ca analysis pipeline, neuron-based simulations)
The main script is run_analysis_pipeline.sh, as an example of a slurm-based pipeline.
In addition, utils folder contains my opencv-based common functions (tbd add more)
(For my phd I used parameter files passed to the main script for more flexibility. Not added here due to privacy)
Scripts used by run_analysis_pipeline.sh:
- python_scripts - contains help scripts:
- create_tiff_from_raw_data.py: prepare data (.raw format to tiffs) for caiman's code.
- extract_raw_and_motion_corr_traces.py: creates data traces from caiman's output (hdf5 and mat files) as a mat file.
- matlab_functions folder contains functions triggered by the pipeline:
- visualize_raw_data_and_stimulus.m: movie visualization of raw data (from tiff files), annotated with stimulus
- Matlab: sbatch $scripts_dir/run_general_matlab_script.sh $dataset_path $data_folder "<additional args if needed, sep by comma>"
- Python: sbatch $scripts_dir/run_general_python_script.sh $dataset_path/$data_folder
- Can add later support for additional parameters (currently not needed)
- Both can get the following additional slurm parameters, s.a --mem, --job-name, --depend (see run_analysis_pipeline.sh for example)