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:caption: Contents: | ||
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overview | ||
motivation | ||
installation | ||
examples | ||
licenses |
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.. _motivation: | ||
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Motivation | ||
========== | ||
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What are PlotPy V2 advantages over PlotPy V1? | ||
--------------------------------------------- | ||
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From a developer point of view, PlotPy V2 is a major overhaul of PlotPy V1: | ||
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* Architecture has been redesigned to be more modular and extensible, and more simple. | ||
* Code quality has been improved introducing `black`, `isort` and typing annotations | ||
all over the codebase | ||
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.. note:: | ||
PlotPy V2 is fully typed using Python 3.8+ type annotations. | ||
This means that you can use your IDE to get autocompletion and type checking | ||
(e.g. with VSCode, Visual Studio, etc.). | ||
This is a major improvement when you write code using PlotPy V2: | ||
you can rely on the type annotations to understand what a function does | ||
and what it returns, and your IDE can help you a lot with autocompletion | ||
and type checking. | ||
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To sum up, PlotPy V2 is a more modern and more maintainable codebase that will | ||
allow developers to create plotting applications even more easily than before. | ||
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From an end-user point of view, PlotPy V2 is also a significant improvement over | ||
PlotPy V1: | ||
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* PlotPy V2 is more stable and more robust thanks to the new `pytest`-based | ||
automated test suite, with a 70% code coverage. | ||
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* PlotPy V2 benefits from the backport of many bug fixes and improvements | ||
that were made in the guiqwt codebase since PlotPy V1 was released (i.e. from | ||
2016 to 2023). | ||
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* PlotPy V2 provides tons of new features (e.g. alpha function for better transparency | ||
control, refined contour plots, synchronized multiple plots, selection dialog boxes, | ||
SVG-based shapes, JSON de/serialization of plot items, new simple way to create | ||
plotting widgets with `PlotBuilder`, etc.) | ||
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* PlotPy V2 will be maintained and improved in the future, while PlotPy V1 is not | ||
maintained anymore. Some significant improvements are already planned for the | ||
next releases (e.g. enhanced color maps, new plot items, etc.) | ||
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What are PlotPy V2 advantages over guiqwt? | ||
------------------------------------------ | ||
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Except from the backporting of bug fixes and improvements that were made in the | ||
guiqwt codebase since PlotPy V1 was released (i.e. from 2016 to 2023), PlotPy V2 | ||
provides the same advantages over guiqwt as PlotPy V1: see previous section. |
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# Announcement: Release of PlotPy V2 📊 | ||
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PlotPy V2 distinguishes itself in the realm of plotting libraries. Designed for Python/Qt applications, this library offers a blend of superior performance and enhanced interactive features. Its image display features, driven by a C++ transform engine, include real-time high-quality interpolation, LUT, and geometric transformations, elevating data interaction. | ||
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PlotPy is part of the PlotPyStack project (<https://github.com/PlotPyStack>), dedicated to delivering a comprehensive toolkit for crafting scientific and technical data visualization applications. | ||
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The development efforts for PlotPy V2 were financed by the CEA (<https://www.cea.fr/>). | ||
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What's New in PlotPy V2 🌟: | ||
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🔍 Major Updates: | ||
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Refined and unified API for curve and image plotting features (widget, dialog, window). Introduction of a new window for synchronized multi-plot displays 🔄. | ||
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🎨 Enhancements: | ||
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Expanded Image Lookup Table functionalities. | ||
Integration of SVG-based shapes. | ||
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📖 Documentation: | ||
Comprehensive Sphinx-based documentation enriched with API links, examples, and tutorials. | ||
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⚙️ Development Features: | ||
Black code formatting, robust `pytest`-based automated test suite, and a 70% test coverage milestone ✅. | ||
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We invite the community to explore PlotPy V2's capabilities. | ||
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Explore PlotPy V2 on PyPI: <https://pypi.org/project/PlotPy/>. | ||
View the project on GitHub: <https://github.com/PlotPyStack/plotpy/>. | ||
Review the documentation: <https://plotpy.readthedocs.io/en/latest/>. |
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PlotPy V2 is now live! 🎉Introducing an optimized 2D curve/image plotting library📊. | ||
It's the successor to guiqwt. <https://pypi.org/project/PlotPy/> | ||
PlotPy is part of PlotPyStack, representing 15 years of expertise | ||
in Python-Qt scientific software development. | ||
#Python #Plotting |
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