Materials for the fastplotlib talk at Society for Neuroscience (SFN) 2023. This repo includes installation instructions and the demo notebooks covered in our talk.

For more info on fastplotlib see the repo: https://github.com/fastplotlib/fastplotlib/

The demos cover the following topics:

1. Simple introduction to fastplotlib - Images, ImageWidget, and Lines
   • plotting simple images, feature changes, image updates, fancy indexing of features
2. Neuroscience using fastplotlib
   • building a complex plot to explore behavioral and calcium imaging data
   • integration of fastplotlib with other Python neuroscience tools (i.e. mesmerize_core, CaImAn, pynapple)

See the fastplotlib repo for installation.

In order to run the notebooks you will need to have imageio. This is not a dependency of fastplotlib, but is being used in these demos.

Additionally, for the intro_demo.ipynb, you can find the 10GB zebrafish dataset being used here:

# you will need to install imageio
pip install imageio

# optional, you'll need C compilers
pip install simplejpeg

# fastplotlib with notebook dependencies
pip install "fastplotlib[notebook]"

• Image, Line, Scatter, Heatmap
• Collections - LineCollection, LineStack (ex: neural timeseries data)
• Interactions

• Plot - a single plot area
• GridPlot - a grid of Subplots

• ImageWidget- n-dimensional widget for Image data
• Sliders, support window functions, GridPlot, 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 2023 and Issues for more ideas on how to contribute.