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Improve time to plot data about pyphs HOT 2 OPEN

pyphs avatar pyphs commented on May 30, 2024
Improve time to plot data

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Comments (2)

afalaize avatar afalaize commented on May 30, 2024

Additionally, there is an error in the computation of the power balance for decimated data

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FabricioS avatar FabricioS commented on May 30, 2024

Hi Antoine,
the data.ntplot attribute is defined only for H5Data. Maybe you are using the fallback asciidata for some reason...

Moreover, you can look at the amount of data attached to the results plot in order to check whether it respects the given upper bound:

ax = plt.gca()
print([line.get_xdata().shape for line in ax.get_lines()])

As a last note, even if not competing in the realtime plotting category, matplotlib is pretty efficient to handle a reasonable number of axes with a large number of curves, each one with a large amount of points. Despite that, performance can still be improved using path_simplification, see
https://matplotlib.org/3.1.1/tutorials/introductory/usage.html#performance

Which backend are you using?

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