Materials and resources for an internal talk at Rockefeller University. This repo includes installation instructions and the demo notebooks covered in our talk.
Recording: https://www.youtube.com/watch?v=nmi-X6eU7Wo
For more info on fastplotlib see the repo:
https://github.com/fastplotlib/fastplotlib/
The demos cover the following topics:
- Simple introduction to
fastplotlib-Images,Lines, and events- plotting simple images, feature changes, image updates, fancy indexing of features
- included exercises
- Neuroscience using
fastplotlib- building a complex plot to explore behavioral and calcium imaging data
- integration of
fastplotlibwithpynapple
See the fastplotlib repo for installation.
In order to run the notebooks you will need to have imageio, pynapple, and scikit-image. These are not dependencies of fastplotlib, but are being used in these demos.
# you will need to install imageio
pip install imageio
# you will need to install scikit-image
pip install scikit-image
# optional, you'll need C compilers
pip install simplejpeg
# fastplotlib with notebook dependencies
pip install "fastplotlib[notebook,imgui]"
# pynapple
pip install pynapple
-
Image,Line,Scatter -
Collections -
LineCollection,LineStack(ex: neural timeseries data)- Common:
Name,Offset,Rotation,Visible,Deleted - Graphic Specific:
ImageVmin,ImageVmax,VertexColors, etc.
LinearSelector- horizontal or vertical line sliderLinearRegionSelector- horizontal or vertical resizable region selection
- Common:
Figure- a single plot or a grid of subplots
ImageWidget- widget forImageGraphicdata with dims:xy,txy,tzxy- Sliders, support window functions, etc.
For a more in-depth look at our API, please visit our docs.
fastplotlib is a relatively new library, and we are always looking for feedback or help! Please see the contributing guide.
You can also look at our Roadmap for 2025 and Issues for more ideas on how to contribute.