Python Scripts for NCT-Lab

This repository is for developing python scripts to generate a number of statistics from CSV files that contain experimental results for the following three different tasks:

• Task 1: N-back
• Task 2: Face-matching
• Task 3: BELT

Requirements

In order to run the scripts, it is necessary to install the following library on your system:

• Pandas (>=0.24.2)

Usages

First, download the Prod folder to your local machine. Then run one of the following commands depending on your interest.

📌 Task 1: N-back Analyzer

To run the N-back analyzer, open your terminal and execute the following command:

user@local:~$ python <PATH/TO/analyze_Nback.py> -csv_main_path=<PATH/TO/XXX_Nback_XXX.csv> -csv_ref_path=<PATH/TO/nback_AB.csv>

For instance, if you downloaded the Prod folder to your local machine, say, under ~/Downloads, and your main CSV (e.g., AA06LC00_Nback_2021_Jun_09_1034.csv) and nback_AB.csv is located at ~/Desktop/data, the command should look like the following:

user@local:~$ python ~/Downloads/Prod/Task1_N-Back/analyze_Nback.py -csv_main_path=~/Desktop/data/AA06LC00_Nback_2021_Jun_09_1034.csv -csv_ref_path=~/Desktop/data/nback_AB.csv

Note 1. The path of csv_ref_path should be the same for running the other main CSV files.
Note 2. The script will generate two CSV files:

Filename	Contents
<SUBJECTID>_avg_rxntime_per_loadsize.csv	Average response time per loadsize
<SUBJECTID>_avg_rxntime_per_stimulus.csv	Average response time per stimulus

📌 Task 2: Face-matching Analyzer

Similar as above, open your terminal and execute the following command:

user@local:~$ python <PATH/TO/analyze_FaceMatching.py> -csv_main_path=<PATH/TO/XXX_FaceMatching_XXX.csv> -csv_ref_path=<PATH/TO/facematching_AB.csv>

Note 1. The path of csv_ref_path should be the same for running the other main CSV files.
Note 2. The script will generate two CSV files:

Filename	Contents
<SUBJECTID>_avg_rxntime_per_condition.csv	Average response time per condition
<SUBJECTID>_avg_accuracy_per_condition.csv	Average accuracy per condition

📌 Task 3: BELT Analyzer

Unlike the above two tasks, in order to run the script for the BELT task, a .log file corresponding to the main CSV file is required as following:

user@local:~$ python <PATH/TO/analyze_BELT.py> -csv_path=<PATH/TO/XXX_BELT_XXX.csv> -log_path=<PATH/TO/XXX_BELT_XXX.log>

For instance, if you downloaded the Prod folder to your local machine, say, under ~/Downloads, and your main CSV (e.g., AA06LC00_BELT_TEST_2021_Jun_09_1320.csv) and the corresponding log file (e.g., AA06LC00_BELT_TEST_2021_Jun_09_1320.log are located at ~/Desktop/data, the command should look like the following:

user@local:~$ python ~/Downloads/Prod/Task3_BELT/analyze_BELT.py -csv_path=~/Desktop/data/AA06LC00_BELT_TEST_2021_Jun_09_1320.csv -log_path=~/Desktop/data/AA06LC00_BELT_TEST_2021_Jun_09_1320.log

Note 1. The path of log_path MUST be changed accordingly for running the each main CSV file.
Note 2. The script will generate the following CSV files:

Filename	Contents
<SUBJECTID>_rxntime_from_onset_from_previous.csv	- Response time per presentation from onset stimulus - Response time from previous stimulus
<SUBJECTID>_aggregated_stats.csv	Aggregated stats, including balloonscore per color, total balloonscores, average reaction time after popped, etc.
<SUBJECTID>_post_explosion_behavior.csv	Filtered results from _rxntime_from_onset_from_previous.csv to show every popped case and the right after of the same condition

Author

• Chulwoo (Mike) Pack