gemprf 0.1.1

A Python library for population receptive field (pRF) analysis

Welcome to GEM-pRF - a standalone, plug-and-play software for population receptive field (pRF) mapping, designed for large-scale data analysis with high accuracy.

To understand the theoretical foundations and details of how the software works, please refer to our paper: 👉Mittal et al (2025), GEM-pRF: GPU-Empowered Mapping of Population Receptive Fields for Large-Scale fMRI Analysis

Documentation

An official documentation is coming soon (GEM-pRF documentation link)! Meanwhile, to get the mathematical foundation of the software, you may refer to the GEM-pRF paper.

Installation

GEM-pRF requires the GPU access for the data processing. At the moment, GEM uses CUDA libraries to acess/process data on NVIDIA GPUs.

[!WARNING]

Please check your system has compatible NVIDIA GPU available.

Step-by-Step Guide

Step 1. Install dependencies

• Create or activate your preferred Python/Conda environment.
• Install all required dependencies listed in requirements.txt:

pip install -r requirements.txt

Step 2. Download GEM-pRF code

• Clone the repository:

git clone https://github.com/siddmittal/GEMpRF.git
cd GEMpRF

Running GEM-pRF

[!CAUTION] Before proceeding, make sure to install the required python dependencies as specified in the requirements.txt file

GEM-pRF is written as a standalone software. It comes with an XML configuration file. Once you configure your XML file (see sample config), you can directly run the software.

🔹 Option A: Run from terminal

1. Open a terminal (e.g. Anaconda Prompt).

2. Activate the environment with the dependencies installed.

3. Navigate to the GEM-pRF folder.

4. Run:

   python run_gem.py PATH_TO_YOUR_XML_CONFIG_FILE
   

🔹 Option B: Run from IDE (e.g. VS Code)

1. Open the downloaded GEM-pRF folder in VS Code.
2. Edit the run_gem.py script to specify the path to your XML config file.
3. Run the script directly from the IDE.