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Jet Killer

Jet Killer converts images using the "jet" colormap to a better one (by default "viridis") by using directly the pixel values, without any knowledge about the underlying data.

It can be used as a tool to enhance data visualizations for which the original dataset is unavailable. Use cases include:

  • enhancing figures from sources who made an unfortunate colormap choice,
  • enhancing graphs for which the original data may be lost,
  • enhancing visualizations without having to regenerate it from the original dataset.

Principle

Installation

To install and use Jet Killer, Python 3 is required.

The following command installs the jetkiller command and the jetkiller package:

pip3 install jetkiller

For details and alternative installation methods, read the user guide.

Basic Usage

With the GUI

To launch the GUI, use the following command:

jetkiller --gui

Screenshot of the GUI

From the Command Line

Use the following command to convert input_file to output_file:

jetkiller input_file output_file

For more details, read the user guide.

From Python

To convert images, import the jetkiller package and use the jetkiller.convert_file function:

import jetkiller
jetkiller.convert_file("input_image.png", "output_image.png")

For more details, read the user guide.

Documentation

The reference documentation is the user guide.

Release History

All releases of this project are listed on the tag page of this repository.

See CHANGES.md for more details on the content of each release.

Development Roadmap

The standalone version of Jet Killer is considered as complete and will not have any major new features.

Here are a few ideas on how to further improve the user experience:

  • develop an extension for GIMP (probably with Python-Fu)
  • develop an extension for Inkscape (probably using Python)

Versioning

Jet Killer attempts to follow the Semantic Versioning Specification for its version numbers.

License

Jet Killer is distributed under the MIT License. See LICENSE-MIT for more details.

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Enhance data visualizations using the "jet" colormap.

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