ℹ️ Created in 2016 by Pierre Raybaut and maintained by the PlotPyStack organization.

ℹ️ PlotPy V2 is the new major release of guiqwt: same team 🏋️, same goal 🎯, same long-term support ⏳.

plotpy is is a Python library providing efficient 2D data-plotting features for interactive computing and signal/image processing application development. It is part of the PlotPyStack project, aiming at providing a unified framework for creating scientific GUIs with Python and Qt.

plotpy is based on:

• Python language and Qt GUI toolkit
• guidata automatic GUI generation library
• PythonQwt plotting widgets library
• NumPy and SciPy scientific computing libraries

See documentation for more details on the library and changelog for recent history of changes.

Copyrights and licensing:

• Copyright © 2023 CEA, Codra, Pierre Raybaut.
• Licensed under the terms of the BSD 3-Clause (see LICENSE).

The plotpy library also provides the following features.

General plotting features:

• Ready-to-use plot widgets and dialog boxes
• pyplot: interactive plotting widgets, equivalent to matplotlib.pyplot, at least for the implemented functions
• Supported plot items: curves, images, contours, histograms, labels, shapes, annotations, ...

Interactive features (i.e. not only programmatic plotting but also with mouse/keyboard):

• Multiple object selection for moving objects or editing their properties through automatically generated dialog boxes
• Item list panel: move objects from foreground to background, show/hide objects, remove objects, ...
• Customizable aspect ratio for images
• Tons of ready-to-use tools: plot canvas export to image file, image snapshot, interval selection, image rectangular filter, etc.
• Curve fitting tool with automatic fit, manual fit with sliders, ...
• Contrast adjustment panel for images: select the LUT by moving a range selection object on the image levels histogram, eliminate outliers, ...
• X-axis and Y-axis cross-sections: support for multiple images, average cross-section tool on a rectangular area, ...
• Apply any affine transform to displayed images in real-time (rotation, magnification, translation, horizontal/vertical flip, ...)

Application development helpers:

• Ready-to-use plot widgets and dialog boxes
• Load/save graphical objects (curves, images, shapes) into HDF5, JSON or INI files
• A lot of test scripts which demonstrate plotpy features (see examples)

The whole PlotPyStack set of libraries relies on the Qt GUI toolkit, thanks to QtPy, an abstraction layer which allows to use the same API to interact with different Python-to-Qt bindings (PyQt5, PyQt6, PySide2, PySide6).

Compatibility table:

See Installation section in the documentation for more details.