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Copy file name to clipboardexpand all lines: README.md
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# visual_behavior_glm
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Fits a kernel regression model to df/f traces during visual behavior.
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Fits a kernel regression model to neural traces during visual behavior.
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# Installing and setting up the package
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>>> from visual_behavior_glm.glm import GLM
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Please report issues at https://github.com/AllenInstitute/visual_behavior_glm/issues
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# Use
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## Defining new kernels/regressors
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- Adding a new kernel requires changes in two places.
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- Add the kernel parameters to `make_run_json()` as a dictionary with keys `length` and `offset`
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- Define the event times in `add_kernel_by_label()`
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## Fit the model
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- Make the run json using `delete_rebuild_run_json.py` in `scripts` with `python delete_rebuild_run_json.py --version <version> --label <a descriptive label> --src-path <path_to_source_code>`
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- Start the run for a single session with `python scripts/fit_glm.py --oied <ophys_experiment_id> --version <version>`
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- Start the run for all sessions at the command line on hpc-login with `python scripts/deploy_fits.py --glm-version <version> --env <name_of_conda_environment>`
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- Collect the results across sessions using `retrieve_results(glm_version=<version>)` from `src/GLM_analysis_tools.py`
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## Model Iteration System
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-`delete_rebuild_run_json.py` saves a copy of current files, as well as a JSON file with run parameters to `../nc-ophys/visual_behavior/ophys_glm/v_<version>/`
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