Plot for each run one black curve 'error vs. iterations' and aggregate the mean curve (red) and
the median curve (green) of all runs. 'error' is the distance between the ever-best feasible
value and optim
.
multiRunPlot(
dfAll,
optim = NULL,
fName = "multiRun",
main = "",
xlim = NULL,
ylim = c(1e-05, 10000),
ylog = TRUE,
xlog = FALSE,
target = 0.05,
plotPDF = FALSE,
subPDF = NULL,
legendWhere = "topright",
absErr = FALSE
)
the data frame of all runs, obtained with multiCOBRA
or loaded
from .Rdata file
[NULL] the true optimum (or best known value) of the problem (only for diagnostics).
If optim==NULL
, we plot instead of errors the ever-best feasible values.
["multiRun"] the name of the .Rdata file, printed as subtitle
[""] the name of the problem (e.g. "G01 problem"), printed as title
the x limits
the y limits
[TRUE] logarithmic y-axis
[FALSE] logarithmic x-axis
[0.05] a single run meets the target, if the final error is smaller than target
[FALSE] if TRUE, plot to 'fName'.pdf
[NULL] optional subdirectory where .pdf should go
["topright"]
[FALSE] if TRUE, plot abs(error) instead of error.
z3
, a vector containing for each run the ever-best feasible objective value
Print some diagnostic information: final median & mean error, percentage of runs which meet the
target (only if optim
is available)).