eprimedata2feat

EPRIME CODE DOCUMENTATION

Generate .csv files from eprime .txt files

Run these Python codes in the given order –

1. batch_ce.py – Generates the .csv file from the .txt eprime file (saved in the main directory containing the log and originals directories-accepts data from originals/ePrimeData) input in a new data directory named eprime_csvfiles, which is created in the input folder directory. a) --path: Takes the full path directory to the .txt eprime files.[The main directory containing all the subjectIDs with subdirectories – log, originals.] b) --subjectID: Takes the subject ID name and generates the .txt file for the particular subject. [accepts sub- ID number/ID number, you can either be in the main directory and enter only the ID number or enter the full path to the subjectID] Example: batch_ce.py --subjectID=”80026b” batch_ce.py --subjectID=”sub-80026b” batch_ce.py –subjectID=”/projects……/MB6/sub-80026b or 80026b” [MB6 contains all the subject folders] batch_ce.py --path=”/projects…/MB6”

Generate .tsv files from .csv files

2) csv2tsv.py – Generate the .tsv files form the .csv input file (the .csv directory is taken in as eprime_csvfiles – generated form batch_ce.py arrangement). The inputs to this code are:
a) --input_dir: The pathway to the input directory containing the .csv files. [It takes the main directory as input, which contains all the subject directories]
b)--output_dir: The pathway to the output directory where you would like to save the .tsv files [This is accordance to the BIDS directory arrangement, and takes the main directory containing all the BIDS converted subject directories as input here]
c)--subID: Takes the subjectID as input. 

Example:

csv2tsv.py –-input_dir=”/projects/……/MB6” --output_dir = “/projects/…../rawData” [MB6 consiss of all the subject folders, rawData consists of the BIDS converted datasets, where the code searches for the func directory to store the .tsv files] csv2tsv.py –-input_dir="/projects/…../MB6" --output_dir = "/projects/..../rawData" --subID=”sub-80026b” csv2tsv.py –-subID=”/projects/……/MB6/sub-80026b” --output_dir=”/projects/…/rawData” csv2tsv.py --subID=”sub-80026b” --output_dir=”/projects/…./rawData” [Make sure your current directory contains the subID folder]

Generate the feat onset vectors (3 column format) and subject accuracy summary file list in the directory containing the rawData folder.

3) feat_excel.py – Generate feat onset vectors in .txt file.
	a)--input_dir: Contains the .csv file input directory. [The main 		directory containing the subject lists which have log and 			originals folders.]
	b)--output_dir: Contains the output directory in accordance with 		the 	BIDS structure.[The main rawData folder]
	c)--subjectID: Enter the subjectID

examples:

feat_excel.py –-input_dir=”/projects/……./MB6” --output_dir=”/projects/…./rawData” feat_excel.py –-input_dir=”/projects/…./MB6” --subjectID=”sub-80026b” --output_dir=”/projects/…../rawData” feat_excel.py –-subjectID=”/projects/…../MB6/sub-80026b” --output_dir=”/projects/…...rawData” feat_excel.py –-subjectID=”sub-80026b” --output_dir=”/projects/….rawData” [Make sure your current diretory contains the subjectID folder which contains the log and originals folders.]