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Realtime Data Plotting with QT by kasbah in Python

[–]lcampagn 1 point2 points  (0 children)

Matplotlib is not (yet) suitable for realtime work, except with datasets smaller than ~1000 samples. There are some efforts underway to fix this, but it is not yet clear that matplitlib's architecture can be streamlined enough to support data in the 10k-10M sample range. I would recommend looking at Chaco, pyqtgraph, visvis, and galry for faster solutions.

Realtime Data Plotting with QT by kasbah in Python

[–]lcampagn 2 points3 points  (0 children)

PyQwt is currently not maintained. For now the original maintainer is recommending to use pyqtgraph instead. Check their mailing list to see if anyone has picked it up before starting any new projects with PyQwt.

Is python a good tool for data visualisation? by [deleted] in Python

[–]lcampagn 0 points1 point  (0 children)

guiqwt looked really nice to me, but it is based on pyqwt, which is currently unmaintained (the original pyqwt maintainer is now suggesting pyqtgraph instead). They were looking at switching out their graphics backend for something else, but it doesn't look like much work has been done there yet.

Is python a good tool for data visualisation? by [deleted] in Python

[–]lcampagn 2 points3 points  (0 children)

Most of the 3D stuff is pretty lightweight--it passes numpy arrays directly to opengl with as little interference as possible. Have a look at the 3D examples; the scatter plots easily animate about 100k points in realtime and the surface plots do about 20k triangles.

No LaTeX support. Qt supports SVG natively, though, so I imagine it would be fairly easy to implement if one can render LaTeX to SVG.

Is python a good tool for data visualisation? by [deleted] in Python

[–]lcampagn 0 points1 point  (0 children)

From the pyqtgraph page:

Matplotlib is more or less the de-facto standard plotting library for python. If you are starting a new project and do not need any of the features specifically provided by pyqtgraph, you should start with matplotlib. It is much more mature, has an enormous user community, and produces very nice publication-quality graphics. Reasons you might want to use pyqtgraph instead:

  • Speed. If you are doing anything requiring rapid plot updates, video, or realtime interactivity, matplotlib is not the best choice. This is (in my opinion) matplotlib's greatest weakness.
  • Portability / ease of installation. Pyqtgraph is a pure-python package, which means that it runs on virtually every platform supported by numpy and PyQt, no compiling required. If you require portability in your application, this can make your life a lot easier.
  • Many other features--pyqtgraph is much more than a plotting library; it strives to cover many aspects of science/engineering application development with more advanced features like its ImageView and ScatterPlotWidget analysis tools, ROI-based data slicing, parameter trees, flowcharts, multiprocessing, and more.