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Curve and image plotting tools for Python/Qt applications

Project description

PlotPy: Curve and image plotting tools for Python/Qt applications

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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:

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

Copyrights and licensing:


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)

Dependencies and installation

See Installation section in the documentation for more details.

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