Shady 1.13.3
Welcome to Shady. Shady is for programmers who work in neuroscience, especially vision science. It is a two-dimensional graphics engine and Python framework, for generating and presenting psychophysically-accurate visual stimuli, and for manipulating them in real time with minimal CPU usage and minimal “boilerplate” coding. For an outline of Shady’s structure and features, see the “Overview” topic documentation.
To download and install the Python package:
The short answer:
python -m pip install shady
The long answer: see the “Installing the Shady Package” topic documentation.
To get started:
To run an interactive tour of the main features:
python -m Shady demo showcase
To get more information about that demo (such as the command-line options it supports):
python -m Shady help showcase
To see a list of other similar demos:
python -m Shady list
To learn more:
Class and method docstrings—e.g.
help(Shady.World)
orhelp(Shady.Screens)
from within Python (or better, if you are using IPython:Shady.World?
etc.)For topic documentation: docstrings of objects inside the
Shady.Documentation
submodule—e.g.help(Shady.Documentation.PreciseControlOfLuminance)
It’s also all on https://shady.readthedocs.io
To ask questions:
You can ask programming questions on stackoverflow, using the
[shady]
tag (https://stackoverflow.com/questions/tagged/shady )If an issue is confirmed to be a technical problem or bug, you can submit details at https://bitbucket.org/snapproject/shady-gitrepo/issues
To cite Shady:
When reporting any study in which you used Shady, please cite:
Hill NJ, Mooney SWJ, Ryklin EB & Prusky GT (2019). Shady: a Software Engine for Real-Time Visual Stimulus Manipulation. Journal of Neuroscience Methods 320: 79-86. https://doi.org/10.1016/j.jneumeth.2019.03.020
@article{shady2019, author = {Hill, N. Jeremy and Mooney, Scott W. J. and Ryklin, Edward B. and Prusky, Glen T.}, title = {{Shady}: a Software Engine for Real-Time Visual Stimulus Manipulation}, journal = {Journal of Neuroscience Methods}, volume = {320}, number = {C}, pages = {79--86}, month = {May}, year = {2019}, date = {2019-05-15}, doi = {10.1016/j.jneumeth.2019.03.020}, url = {https://doi.org/10.1016/j.jneumeth.2019.03.020}, }
A pre-print is also available
on https://shady.readthedocs.io