Eisch Lab - Touchscreen Data Analysis App

The EL Touchscreen Data Analysis App takes in complex raw ABET data and returns a csv file with usable data ready to be used for graphing mice performance over the span of the experiment.

This application can be used for the following test:

• Habituation 1 and 2
• Initial Touch
• Must Touch
• Must Initiate
• Punish Incorrect
• Location Discrimination Train
• Location Discrimination Probe
• Acquisition
• Extinction

Some Pictures of the Application

Modules

pandas
numpy
tkinter
os
glob
xlsxwriter
webbrowser
warnings

Installation

pip install pandas
pip install xlsxwriter
pip install webbrowser

Files

ts_main.py

The main file that gets ran. Calls on the other files and creates all of the GUI using tkinter.

setup.py

This file is used to determine which test should be ran and parses the raw ABET data accordingly. It also creates
the merged_files.csv and the dropped_duplicates.csv, both of which are useful for debugging.

setup_functions.py

This file contains extra functions that are used to help the setup.py parse the raw ABET data.

general_touchscreen.py

This file contains all the functions that are used to do all the General Touchscreen functions.

ld_train.py

This file contains all the functions that are used to do all the Location Discrimination Train functions.

ld_probe.py

This file contains all the functions that are used to do all the Location Discrimination Probe functions.

acquisition_extinction.py

This file contains all the functions that are used to do all the Acquisition and Extinction functions.

parameterized.py

This file contains all the functions that are used to do all the Parameterized functions.

Usage

python ts_main.py

Navigate to which test you want cleaned data for.
Click on the specific button to perform a specific type of cleaning.
Navigate to the directory where the raw data is stored and hit select folder.
Wait a few moments.
Navigate to the directory where you want to store the newly created csv file and name it.
Go to the directory where you saved the file and open it.
Use the file to start graphing mice performance over the course of the experiment.

License

Feel free to use it, but please credit me :)

Contact Me

If you have questions, you can email me at raymons@sas.upenn.edu