Fast interactive visualization remains a considerable barrier in analysis pipelines for large neuronal datasets. Here, we present fastplotlib, a scientific plotting library featuring an expressive API for very fast visualization of scientific data. Fastplotlib is built upon pygfx, which utilizes the GPU via WGPU, allowing it to interface with modern graphics APIs such as Vulkan for fast rendering of objects. Fastplotlib is non-blocking, allowing for interactivity with data after plot generation. Ultimately, fastplotlib is a general-purpose scientific plotting library that is useful for fast and live visualization and analysis of complex datasets.

The default color space for computers includes over 16 million colors—an embarrassment of riches that is also a potential quagmire to anyone considering how to best choose colors for visualizations. In this workshop, we will provide a practical framework for working with color. We will start by developing an understanding of color models and color theory, building from these to provide simple but powerful heuristics for color selection that will enable creators of data visualization to enhance the clarity, power, and storytelling of their visualizations. We will conclude with the introduction of tools for working with and selecting color, followed by hands-on activities using these tools. No prior knowledge is needed or assumed, and the only tools you will need is a computer with a web browser and an internet connection.