petscplot

PETScPlot is a simple tool for plotting convergence rates and scalability from output logs of PETSc programs.

Dependencies:

python-2.5 or later: http://python.org numpy: http://numpy.org matplotlib: http://matplotlib.sourceforge.net

Usage:

[Read the doc strings, they are more likely to be up-to-date. Also run with -help.]

Run your program with -{ksp,snes}_{monitor,converged_reason} and redirect the output into a file, perhaps for multiple problem sizes, or on different machines. If you want timing information, also use -log_summary.

Note: Currently the problem size parsing is specific to src/snes/examples/tutorials/ex48, it really needs to be made generic, but that requires the user to write a small code snippet to parse their header.

Then pass series of log files to petscplot, as in the following examples.

petscplot -t algorithmic foo{2,3,4,5,6}.log : bar{2,3,4,5,6}.log

Plots average number of Krylov iterations per nonlinear iteration versus number of nodes, on a log-log scale.

petscplot --type=algorithmic foo{2,3,4,5,6}.log : bar{2,3,4,5,6}.log --legend-labels='Foo Algorithm:Bar' --output=foobar.png

Uses the given legend (instead of first filename in each series) and directs output to the PNG file.

petscplot -t snes -m poster gridsequenced.log -o foobar.eps

Plots hybrid linear and nonlinear residuals for a grid-sequenced simulation, formatted for placement on a poster, in EPS format (short style options).

petscplot -t weak SERIES [ : SERIES ] ...

Not implemented yet, but necessary data has been parsed.

petscplot -t strong [--stage STAGE] [--event EVENT] SERIES [ : SERIES ] ...

Plots solve time versus number of procs on a log-log scale with the optimal slope=-1 line shown.