plenoptic is a python library for model-based synthesis of perceptual stimuli, intended for researchers in neuroscience, psychology, and machine learning. The stimuli generated by plenoptic enable interpretation of model properties through features that are enhanced, suppressed, or discarded.
Check out our documentation to learn how to use plenoptic and see examples.
You can install plenoptic using pip or conda. See our documentation for more details.
We are currently under review at pyOpenSci!
Feel free to ask any questions on our discussions page. See our readme for what to do if you find an issue or want to contribute.
Browse the materials from workshops we've run to see more examples of how to use plenoptic.
View the slides from presentations explaining the science that plenoptic can facilitate.
If you use plenoptic in a published academic article or presentation, please cite us! View our citation guide for more details.
The package was intially developed by members of the Lab for Computational Vision at New York University and is now maintained by Billy Broderick.
Development and maintenance is supported by the Simons Foundation Flatiron Institute's Center for Computational Neuroscience.