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Update based on Mike's changes to enable a subject-wise folder structure for the data authored by Mike Cichonski's avatar Mike Cichonski
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directories.md
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![folders](/uploads/0ff4703fe808462d68c7d4f5749b004e/folders.png)
# Data
This is where you can store all the data files for all stages of the pipeline. The current default for this is a step-wise folder structure, which stores all subject files together in each step's folder. This is described below:
* **0_raw:** Your raw data files and individual location files will be placed here, they will have a extension such as .bdf. These files are loaded into the *init* script. If you are loading a level 0 ESS capsule then place the main project folder in this folder.
* **1_init:** Your data files will go here after they have been initialized and are have the .set/.fdt extension. If the files only have a .set part make sure your eeglab options are correct, and that you loaded the matlab.minit file in your configs.These files are loaded into the rest of the pipeline.
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* **4_study:** The pipeline does not automatically save any files into this folder, but it is useful to store files that are included in your study.
NOTE: If desired, a subject-wise folder structure is also possible to set up with a few minor changes:
1. Remove all the default folders from the Data directory.
2. Copy your subject folders into this directory (assumes that each subject's files for all steps will be stored within its own subject folder).
3. When running a job through the File->Batch->Run History Template Batch menu, replace the values for [in_path] (and [out_path], if exists),
located in the "replace_string" field of each batch config file, with analysis/data (or [batch_dfp]) if this is what you enter into the "path:" field).
Example: [in_path],analysis/data/1_init ----- change to -----> [in_path],analysis/data
[out_path],analysis/data/2_preproc ----- change to -----> [out_path],analysis/data
4. For now, the path to the folder containing the subject folders must be manually typed/pasted into the "path:" field. This will usually be analysis/data if that's
the folder you'd like to use. Likewise, the _init.set file name(s) must be manually typed/pasted into the "file:" field. In this case they must include the name
of the subject folder in the name.
Example: subj001/subj001_init.set (this should work regardless of how many folders deep the init file is stored)
5. If you are running your jobs remotely, remember to also change the folder structure on the remote end in the same way as in steps 1-4 above.
# Log
Log is automatically populated with scripts when you execute the pipeline. You will see a folder generated for every script identified by the script that was run followed by the date and time of the scripts execution. These folders contain:
* A specific **.m** file for each subject data file.
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