Hotfix v0.10.2

Fixed regression introduced by last revision

PySide6 compatible release

v0.10.0

Added support for QtPy 2, PyQt6, PySide6

Maintenance release

Added internal scripts for automated test in virtual environments with both PyQt5 and PySide2

PySide2 support

This release adds PySide2 support.

However, please note that PySide2 still lacks features regarding NumPy arrays interface, hence a huge performance difference with respect to PyQt5 (see here).

PythonQwt 0.7.0

This release introduces the following features:

• a brand new test launcher,
• a new flat-style design,
• new convenience make functions to create rapidly plots, curves, markers, and so on (examples were updated to use those functions).

An overview of the new flat-style design:

It may not be visible, but a major code cleaning and code formatting effort was also achieved for this release, hence leading to:

• a more readable and easy to maintain source code base,
• a couple of bug fixes and optimizations.

To try the new test launcher, you may type python-qwt-tests from the command line or run it directly from Python:

from qwt import tests
tests.run()

This will show the test launcher main window:

Maintenance release

v0.6.2

Updated changelog

v0.6.1 - Maintenance release

Fixed another couple of annoying bugs left alone for around four years...

v0.6.0 - Maintenance release

This is just a maintenance release, almost four years after v0.5.0.

PythonQwt is still alive... and it's still running!

After being widely used through guiqwt which extends PythonQwt features (adding higher-level features like efficient image visualization, advanced interaction with graphic objects, ready-to-use GUI components to build your scientific application with a few lines of code, etc.), PythonQwt may also be used through plotpy.

v0.5.5

This release demonstrates that some essential features of PyQwt can be reimplemented in pure Python, with some limitations (see README) but without too much performance loss (depending on your application, of course).

Note that you might be interested by guiqwt which is an extension to PythonQwt, adding higher-level features like efficient image visualization, advanced interaction with graphic objects, ready-to-use GUI components to build your scientific application with a few lines of code, etc.

The most important additions of recent versions are:

• documentation,
• huge performance improvements (between v0.4.0 and v0.5.0).

To test this release, you may run the GUI-based test launcher from Python:

from qwt import tests
tests.run()

or from command line: python-qwt-tests.

GUI-based test launcher (requires guidata):

Example showing curve styles:

Example benchmarking the plotting feature ("lines" and "dots" plots are the most optimized thanks to a direct memory mapping between NumPy array data and Qt polygon data):

Other examples: