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prfmodel

A modern Python implementation for population receptive field modelling.

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Description

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How to use prfmodel

A modern Python implementation for population receptive field model fitting.

Getting started

See our online documentation on how to get started with prfmodel.

Installation

Requirements: prfmodel requires Python version >= 3.10 and <= 3.13.

To install the development version of prfmodel from GitHub, run:

git clone git@github.com:popylar-org/prfmodel.git
cd prfmodel
python -m pip install .

The package relies on Keras for multi-backend model fitting. At least one backend must be installed to use prfmodel.

To install prfmodel with the Tensorflow backend, run:

python -m pip install .[tensorflow]

To install the PyTorch backend, run:

python -m pip install .[torch]

To install the JAX backend, run:

python -m pip install .[jax]

The default backend in Keras is Tensorflow, but this can be changed by setting the KERAS_BACKEND environment variable, for example, at the beginning of a Python script or Jupyter notebook:

import os

os.environ["KERAS_BACKEND"] = "jax"

import prfmodel

Important: The backend must be set before importing prfmodel or keras. See the Keras documentation for details.

Documentation

The online documentation is available at: https://popylar-org.github.io/prfmodel/.

The local documentation can be build as HTML files with:

# In prfmodel directory
cd docs/
make html

The documentation can then be opened in the browser from _build/html/index.html.

Development

The project setup for developers is documented in project_setup.md. To make an editable install with development dependencies, run:

python -m pip install -e .[dev]

The test suite can be run with:

python -m pytest

Credits

This package was created with Copier and the NLeSC/python-template.

The model fitting workflow in prfmodel was inspired by braincoder.

Generative AI usage

Claude Code (Opus version 4.5 - 5.0) was used to partially generate and improve code in prfmodel. All improvements were manually evaluated and approved by the authors.

Copyright

2026, Netherlands eScience Center, Vrije Universiteit Amsterdam, Netherlands Institute for Neuroscience

Keywords
Programming language
  • Python 100%
License
</>Source code

Participating organisations

Netherlands eScience Center
Royal Netherlands Academy of Arts and Sciences
Vrije Universiteit Amsterdam

Contributors

Contact person

Malte Lüken

Malte Lüken

Lead Engineer
Netherlands eScience Center
0000-0001-7095-203XMail Malte
Malte Lüken
Malte Lüken
Lead Engineer
Netherlands eScience Center
0000-0001-7095-203X
Flavio Hafner
Flavio Hafner
Research Software Engineer
Netherlands eScience Center
0009-0000-5893-9000
Angel Daza
Angel Daza
Research Software Engineer
Netherlands eScience Center
0000-0003-1711-3151

Related projects

Popylar

Popularizing Population Receptive Field Modeling in Neuroimaging

Updated 18 months ago
In progress