dreye

Dreye: Receptor Space Manipulation

https://github.com/neuralsignal/dreye

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 1 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (16.3%) to scientific vocabulary

Keywords

color color-theory color-vision drosophila insect-eye neuroscience python stimulus-design stimulus-presentation
Last synced: 6 months ago · JSON representation

Repository

Dreye: Receptor Space Manipulation

Basic Info
Statistics
  • Stars: 6
  • Watchers: 1
  • Forks: 2
  • Open Issues: 0
  • Releases: 5
Topics
color color-theory color-vision drosophila insect-eye neuroscience python stimulus-design stimulus-presentation
Created almost 6 years ago · Last pushed over 2 years ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

DrEye: Exploiting Receptor Space Geometry for Stimulus Design across Animals

DOI

drEye is a package that implements various approaches to design stimuli for sensory receptors. The main focus of the package is geared towards designing color stimuli for any animal under investigation, where the photoreceptor spectral sensitivities are known. The hardware-agnostic approach incorporates photoreceptor models within the framework of the principle of univariance. This enables experimenters to identify the most effective way to combine multiple light sources to create desired distributions of light, and thus easily construct relevant stimuli for mapping the color space of an organism. The methods support broad applications in color vision science and provide a framework for uniform stimulus designs across experimental systems. Many of the methods described can be used more generally to design stimuli for other sensory organs or used more broadly where a set of linear filters define the input to a system.

Documentationa and tutorials

Documentation and tutorials can be found here https://dreye.readthedocs.io/en/latest/.

Web application

To test stimulus creation, check out the corresponding web applitcation: https://share.streamlit.io/gucky92/dreyeapp/main/app.py.

Paper

Our paper that explains the purpose of the package drEye and goes through key concepts:

"Exploiting colour space geometry for visual stimulus design across animals"; Matthias P. Christenson, S. Navid Mousavi, Elie Oriol, Sarah L. Heath and Rudy Behnia; Philosophical Transactions of the Royal Society B: Biological Sciences; https://royalsocietypublishing.org/doi/10.1098/rstb.2021.0280.

Please reference this paper when using drEye.

Installation

bash pip install dreye

In order to use the non-linear fitting procedures, JAX should be installed separately:

bash pip install jax[cpu]

This code has been tested on Python 3.8, 3.9, and 3.10.

Common Issues

  • Running jax on the new Macbook Pro chips can run into problems. Make sure to install the versions that work with the M1 chip. For my purposes jaxlib==0.1.60 and jax==0.2.10 currently work (14/01/21).

Old code

The nonlinear fitting procedures for the variance minimization, underdetermined, and decomposition algorithms and the silent substitution algorithm described in the paper have yet to be refactored into the new API. The old API can be found at https://github.com/gucky92/dreye_ext. The linear versions (faster and convex) are already available in the new API.

Development

If you are interested in contributing to the project, please email at gucky@gucky.eu. We would also love any type of general feedback or contributions to the code and methods implemented.

Owner

  • Name: Matthias Christenson
  • Login: neuralsignal
  • Kind: user

PhD, Columbia University | Computational Neuroscientist | ML and Data Scientist

GitHub Events

Total
Last Year

Dependencies

.github/workflows/pythonpackage.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v1 composite
docs/environment.yml pypi
environment.yml pypi
requirements.txt pypi
  • cvxpy >=1.1.10
  • matplotlib *
  • numpy *
  • pandas >=1.0
  • pint >=0.16.1
  • pyarrow >=3.0.0
  • quadprog *
  • scikit-learn >=1.0
  • scipy >=1.9.0
  • seaborn >=0.10
  • tqdm *
setup.py pypi