PyQtGraph is a graphics and user interface library for Python that provides functionality commonly required in engineering and science applications. Its primary goals are 1) to provide fast, interactive graphics for displaying data (plots, video, etc.) and 2) to provide tools to aid in rapid application development (for example, property trees such as used in Qt Designer).
PyQtGraph makes heavy use of the Qt GUI platform (via PyQt or PySide) for its high-performance graphics and numpy for heavy number crunching. In particular, pyqtgraph uses Qt's GraphicsView framework which is a highly capable graphics system on its own; we bring optimized and simplified primitives to this framework to allow data visualization with minimal effort.
This will start a launcher with a list of available examples. Select an item from the list to view its source code and double-click an item to run the example.
* matplotlib: For plotting, pyqtgraph is not nearly as complete/mature as matplotlib, but runs much faster. Matplotlib is more aimed toward making publication-quality graphics, whereas pyqtgraph is intended for use in data acquisition and analysis applications. Matplotlib is more intuitive for matlab programmers; pyqtgraph is more intuitive for python/qt programmers. Matplotlib (to my knowledge) does not include many of pyqtgraph's features such as image interaction, volumetric rendering, parameter trees, flowcharts, etc.
* pyqwt5: About as fast as pyqwt5, but not quite as complete for plotting functionality. Image handling in pyqtgraph is much more complete (again, no ROI widgets in qwt). Also, pyqtgraph is written in pure python, so it is more portable than pyqwt, which often lags behind pyqt in development (I originally used pyqwt, but decided it was too much trouble to rely on it as a dependency in my projects). Like matplotlib, pyqwt (to my knowledge) does not include many of pyqtgraph's features such as image interaction, volumetric rendering, parameter trees, flowcharts, etc.
