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 (via PySide or PyQt)
• 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)

See Installation section in the documentation for more details.