Paper Code Reproduction

"(2025) Decoding the Valence of Developmental Social Behavior: Dopamine Governs Social Motivation Deficits in Autism. In preparation"

Author: Chen Xinfeng, 2025-08-09. Modified: Tao Xianming, 2025-08-15

Run the code in this repository to reproduce the figures in the paper. Fig1_S1 Fig2_S2 Fig3_S3 Fig4_S4 Fig5_S5 Fig6_S6 Fig7_S7

Code and Data Download

The data and code have been open-sourced, with the link: Figshare_DATA_20250818.zip🔗 (1.0 GB). After downloading, unzip it into a folder named Figshare.

Installation

Supports Windows, Linux, and MacOS systems.

First, install the dependency environment using uv.

Warning

Do not use uv and conda simultaneously, as this will cause package installation conflicts. Before running the following codes, please run conda deactivate first.

# Before running the following code, please download the FIGSHARE code and data.
unzip Figshare_DATA_2025*.zip -d Figshare
cd Figshare

python3 -m pip install uv          # UV is a lightweight Python package manager, similar to conda.

uv sync  # Download the required packages and dependencies.
uv run python --version  # Verify the Python version (should be 3.12)

Install Custom Packages 

uv pip install git+https://github.com/chenxinfeng4/multiview_calib.git

git clone https://github.com/chenxinfeng4/LILAB-py.git ../LILAB-py
uv pip install -e ../LILAB-py

uv run python -m lilab.multiview_scripts_dev.p1_checkboard_global -h   # Verify the installation

Generate a Single Figure: Fig1C.pdf

You can run the code in Fig*/Fig*.py one by one to generate figures. 

uv run python Fig1_S1/Fig1C.py   # The result is saved to Fig1_S1/result/Fig1C.pdf

Note: If any error occurs, please ensure that all data files have been downloaded correctly.

Generate All Figures with One Command

uv run python main.py test
Figures such as Fig1.pdf, FigS1.pdf, Fig2.pdf, ... will be generated and saved in the corresponding folders: Fig/result/*.pdf, e.g., Fig1_S1/result/Fig1E.pdf.

Clean All Results, Reset

#1. Delete all result data
uv run python main.py clean

#2. Or manually delete all result data
rm Fig*/result/*pdf Fig*/result/*pkl Fig*/result/*png