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Value-Suppressing Uncertainty Palettes for Python

Project description

VSUP: Value-Suppressing Uncertainty Palettes

A Python package for visualizing data with uncertainty using Value-Suppressing Uncertainty Palettes (VSUPs). Inspired by https://github.com/uwdata/vsup.

Installation

Coming soon...

Development

The project is developed with uv.

To check for a local python environment, run:

uv run python

Also install the pre-commit hooks with:

uv tool install pre-commit
pre-commit install

Usage

from vsup import VSUP
import numpy as np
import matplotlib.pyplot as plt

# Create a grid of values and uncertainties for better visualization
n_points = 50
step = 1/n_points
values = np.linspace(step/2, 1-step/2, n_points)
uncertainties = np.linspace(step/2, 1-step/2, n_points)

# Create a 2D grid
values, uncertainties = np.meshgrid(values, uncertainties)

# Colorize the data
axs = plt.subplots(3, 3, figsize=(9, 9))[1]

for row, quantization in zip(axs, [None, 'linear','tree']):
    for ax, mode in zip(row, ["us", "ul", "usl"]):

        vsup = VSUP(palette='flare', mode=mode, quantization=quantization)

        colors = vsup(values, uncertainties)
        ax.pcolormesh(values, uncertainties, colors)
        # ax.set_title(f"{mode}")  #\n({description})")
        ax.set_xlabel("Value")
        ax.set_ylabel("Uncertainty")

flare example

Features

  • Three visualization modes:
    • USL: Uncertainty mapped to Saturation (chroma) and Lightness
    • US: Uncertainty mapped to Saturation
    • UL: Uncertainty mapped to Lightness
  • Two quantization mods:
    • Linear: independent binning of values and uncertainties
    • Tree: value bins depend on uncertainty bin: lower uncertainty, higher value resolution
  • Support for any matplotlib and seaborn colormaps

Citation

If you use this package in your research, please cite the original VSUP paper:

@inproceedings{2018-uncertainty-palettes,
 title = {Value-Suppressing Uncertainty Palettes},
 author = {Michael Correll AND Dominik Moritz AND Jeffrey Heer},
 booktitle = {ACM Human Factors in Computing Systems (CHI)},
 year = {2018},
 url = {http://idl.cs.washington.edu/papers/uncertainty-palettes},
}

License

MIT License

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