Calculates the mean maximum weight of the community through time. This can be calculated by numbers or biomass. The calculation is the sum of the w_inf * abundance of each species, divided by the total abundance community, where abundance is either in biomass or numbers. You can specify minimum and maximum weight or length range for the species. Lengths take precedence over weights (i.e. if both min_l and min_w are supplied, only min_l will be used). You can also specify the species to be used in the calculation.
getMeanMaxWeight(sim, species = NULL, measure = "both", ...)
sim  A MizerSim object 

species  The species to be selected. Optional. By default all target species are selected. A vector of species names, or a numeric vector with the species indices, or a logical vector indicating for each species whether it is to be selected (TRUE) or not. 
measure  The measure to return. Can be 'numbers', 'biomass' or 'both' 
...  Arguments passed on to

Depends on the measure
argument. If measure = “both”
then you get a matrix with two columns, one with values by numbers, the
other with values by biomass at each saved time step. If measure =
“numbers”
or “biomass”
you get a vector of the respective values at
each saved time step.
Other functions for calculating indicators:
getCommunitySlope()
,
getMeanWeight()
,
getProportionOfLargeFish()
mmw < getMeanMaxWeight(NS_sim) years < c("1967", "2010") mmw[years, ] #> mmw_numbers mmw_biomass #> 1967 2640.075 10980.365 #> 2010 2716.657 7940.787 getMeanMaxWeight(NS_sim, species=c("Herring","Sprat","N.pout"))[years, ] #> mmw_numbers mmw_biomass #> 1967 12.68424 20.07675 #> 2010 10.46315 22.66197 getMeanMaxWeight(NS_sim, min_w = 10, max_w = 5000)[years, ] #> mmw_numbers mmw_biomass #> 1967 1313.207 3444.342 #> 2010 2316.711 6742.697