runMICE: Run simulations
In jcpayne/mice-models: Model of Intermediate Complexity for Ecosystem Assessment

Description Usage Arguments Value Examples

This function drives the model. It creates and initializes objects by reading two files (input_params.csv and diet_prefs.csv) into data frames, replaces the "params" data frame if an alternative is passed in by the user, and then steps through years and intra-year timesteps, calculating population numbers-at-age, recruits, catch, etc. for each species. Species interactions are possible because the calculations for each species are done at least once per year. It returns a list of data and plots for each species. Note: the order of some operations matters. This function must initialize the simulationParams object before Species objects; do prey calculations before predators; calculate sardine numbers before anchovy (because anchovy reproduction depends on sardine numbers); update population numbers before recruitment and catch (because catch and recruitment may depend on population size).

1	runMICE(Params, inputdir, scenario = "base", nYears = 100, nSteps = 4)

`inputdir`	A directory where the input_params.csv and diet_prefs.csv files are.
`scenario`	Character. A scenario name (must match a column name in the input file.)
`nYears`	Integer. Number of years for the simulation.
`nSteps`	Integer. Number of timesteps within a year (ignored by some species).
`params`	A data frame of parameters

A list with several components: $input_params: the simulationParams object that was used to make the run. $Anchovy: anchovy results. This has two components: $data: a data frame of some of the most commonly-used results $plots: a set of plots, which may be accessed as a group or individually $Sardine (same as Anchovy), etc. $species. The species objects that contain all values used. $Anchovy: the anchovy object $Sardine: the sardine object, etc.

## Not run: 
 result<-simulate() #uses default input files

 #Instead of using the default, modify some values in the parameter object
 my_params<-new("simulationParams") #create a new simulationParams object
 my_params<-set_simParam(my_params) #initialize the object with data from stored files
 p<-my_params@params #Get the input parameter data frame
 p[p$species=="Sardine",1:7] #Look at the parameters for one species.
 p$base[p$species=="Sardine" & p$parameter=="fished"]<-TRUE #Set fished to TRUE in the base scenario
 my_params@params<-p #put the changed value back into the simulationParams object.

 #Re-run the model with the changed values (Alternatively, one could re-make the .csv input files).
 result<-runMICE(my_params) #uses a modified simulationParams object

 #Look at the results
 result$Pelican$plots #Show Pelican plots
 anchovy.df<-result$Anchovy$data #save the Anchovy data to a data frame for further analysis

 #Look at a slot in one of the Species objects
 res$species$Anchovy@wv #weight at age

## End(Not run)