Support multiple plots #232
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amete
requested changes
Jul 27, 2023
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Hi @Cossack42,
Thank you very much for your contribution. This is certainly a good functionality to have and the sample plots you attached look great. I have a few minor comments. Afterwards, this PR should be good to go.
Best,
Serhan
It was a random file I used to test the functionality of the terminal in creating files so it is not necessary.
graeme-a-stewart
requested changes
Jul 31, 2023
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Thanks so much for this @Cossack42, it's a nice feature to have. There's one small formatting bug to fix, then it's good to go from my side.
graeme-a-stewart
approved these changes
Aug 1, 2023
amete
approved these changes
Aug 1, 2023
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Thanks a lot @Cossack42, @graeme-a-stewart. All looks good now. |
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No thank you! I enjoyed working on this. |
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Let me add again my thanks @Cossack42. These are great contributions to receive. 🙏 |
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Anytime! |
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Multiple Plots
This allows the user to plot multiple prmon files on the same graph.
As part of this we have divided the main function into separate sub-functions.
Results
When graphing one set of data, the syntax of the input remains the same. The graphs on the original post are reproducible using the updated program.
Inputting multiple sets of data (by separating the filenames using commas) allows the plotting of multiple data sets on the same set of axes. For multiple data sets, dotted and dashed lines are used to distinguish each data set.
prmon_plot.py --input prmon.txt,prmon.txt.1 --xvar wtime --yvar vmem,pss,rss,swap --yunit GBInputting up to 7 data sets is supported, although the legend does increase significantly in size and the data sets are more difficult to distinguish on the graph: it may be preferable to graph two sets of data at a time.
-Memory as a function of wall-time using 3 data sets:
Issues
Plotting a stacked graph using multiple data sets is not supported (and will print an error) due to its lesser readability, although plotting a stacked graph using one set of data (stacking multiple variables) is still supported.
Committed by RAL Work Experience students Ismail Ryabchuk and Will Haywood under the supervision of Stewart Martin-Haugh (@StewMH).