Himena

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himena is an infinitely extensible and reusable applications framework for data science.

Motivation

There are many GUI applications for data science, and many of them use the "plugin system" to extend their functionality. Even though the plugin system is a good idea, there are plenty of duplicated works in the third-party plugins.

The reason is that plugins cannot extend other plugins. Imagine that you are a plugin developer and making a plugin that extract features from images as a table. To make your plugin more useful, you will need to implement not only the table widget, but filter/sort functions, plotting functions, and I/O functions as well. You will also be sad to find that these functions cannot readily be used in other plugins.

himena is designed so that plugins developers can cooperate with each other. The table widgets you implemented in your plugin can be used by other plugins that return a tabular data. The plotting functions you implemented in your plugin can be used from any table widgets implemented in other plugins.

To join this plugin community, please check out the developer's guide.

Documentation

Tutorial, developer's guide, and API reference are available at the documentation site.

Installation

himena is available on PyPI.

pip install himena -U

Alternatively, you can install the latest version from GitHub.

git clone git+https://github.com/hanjinliu/himena
cd himena
pip install -e .

Start application

himena

Existing Plugins

You can customize himena for your needs by installing plugins. Here's some example plugins:

• himena-image: image processing and analysis
• himena-stats: statistical testing and modeling.
• himena-seaborn: seaborn plotting.
• himena-lmfit: Curve fitting and parameter optimization using lmfit.
• himena-bio: widgets and commands for basic bioinformatics analysis using biopython.
• himena-relion: A modern RELION GUI built on himena.
• napari-himena: Sending data between napari and himena.