This is a wrapper function for first making a map with table data then,
running optimizations to make the map otherwise done with acmap()
followed by optimizeMap().
make.acmap(
titer_table = NULL,
ag_names = NULL,
sr_names = NULL,
number_of_dimensions = 2,
number_of_optimizations = 100,
minimum_column_basis = "none",
fixed_column_bases = NULL,
sort_optimizations = TRUE,
check_convergence = TRUE,
verbose = TRUE,
options = list(),
...
)Returns an acmap object that has optimization run results.
A table of titer data
A vector of antigen names
A vector of sera names
The number of dimensions in the map
The number of optimization runs to perform
The minimum column basis for the map
A vector of fixed values to use as column bases directly, rather than calculating them from the titer table.
Should optimizations be sorted by stress afterwards?
Should a basic check for convergence of lowest stress optimization runs onto a similar solution be performed.
Should progress messages be reported, see also
RacOptimizer.options()
List of named optimizer options, see RacOptimizer.options()
Further arguments to pass to acmap()
Other map optimization functions:
RacOptimizer.options(),
moveTrappedPoints(),
optimizeMap(),
randomizeCoords(),
relaxMapOneStep(),
relaxMap()