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.