Optimize antigen reactivity adjustments — optimizeAgReactivity • Racmacs

optimizeAgReactivity(
  map,
  optimization_number = 1,
  reactivity_stress_weighting = 1,
  fixed_ag_reactivities = rep(NA, numAntigens(map)),
  start_pars = rep(0, numAntigens(map)),
  reoptimize = FALSE,
  number_of_optimizations = 100,
  options = list()
)

Arguments

map: The acmap object
optimization_number: The optimization number for which to optimize antigen reactivity adjustments
reactivity_stress_weighting: The weighting to apply when calculating how much antigen reactivity changes should additionally contribute to stress in the optimization regime (see details).
fixed_ag_reactivities: A vector of fixed antigen reactivities, use NA values to distinguish the positions you would still like to be optimized.
start_pars: A vector of starting parameters to use for the optimizer, you can still supply starting parameters for antigens listed in fixed_ag_reactivities but they will be ignored.
reoptimize: Should the map be reoptimized from scratch (slower but more likely to explore other optima) when testing each reactivity adjustment or simply relaxed from it's current coordinates (default)
number_of_optimizations: If reoptimizing from scratch, how many optimization runs should be performed each time.
options: A named list of additional options to pass to RacOptimizer.options()

Value

The acmap object is returned with antigen reactivity adjustments set to the value calculated in the optimizer. This can be queried with agReactivityAdjustments().