rt_runGrid: spatial tsetse population simulation with mortality varying...
In AndySouth/rtsetse: simulating tsetse fly populations

Description Usage Arguments Details Value Examples

rt_runGrid is the main function of the rtsetse package to run a spatial simulation

rt_runGrid(mVegCats = array(c("D", "T", "O", "S", "N", "N"), dim = c(2, 3)),
  dfMortByVeg = data.frame(code = c("D", "T", "O", "S", "B", "G", "N"),
  mortality = c(200, 150, 110, 100, 110, 210, 999), pupmortality = c(120, 110,
  105, 100, 120, 170, 999), stringsAsFactors = FALSE),
  dfMoveByVeg = data.frame(code = c("D", "T", "O", "S", "B", "G", "N"), move =
  c(0.85, 0.9, 0.95, 1, 1.05, 1.1, 0)), iBestVeg = 4, pMoveF = 0.6,
  pMoveM = 0.3, iDays = 4, iMaxAge = 120, iCarryCapF = 200,
  fMperF = 0.5, fStartPopPropCC = 1, pMortF = 0.05, pMortM = 0.05,
  iMortMinAgeStart = 10, iMortMinAgeStop = 50, fMortMinProp = 0.2,
  fMortOldProp = 0.3, propMortAdultDD = 0.25, pMortPupa = 0.25,
  propMortPupaDD = 0.25, iPupDurF = 26, iPupDurM = 28, iFirstLarva = 16,
  iInterLarva = 10, pMortLarva = 0.05, propMortLarvaDD = 0.25,
  pControl = 0, iControlBorder = 8, verbose = FALSE, report = NULL)

`mVegCats`	a matrix or filepath for a map of vegetation codes
`dfMortByVeg`	a dataframe or filepath to a lookup table specifying mortality multiplier (percent) for each vegetation type
`dfMoveByVeg`	dataframe specifying a movement multiplier for each vegetation category
`iBestVeg`	the index of the preferred vegetation for this species, used in influencing movement
`pMoveF`	probability of F moving between cells
`pMoveM`	probability of M moving between cells
`iDays`	days to run simulation
`iMaxAge`	max age of fly allowed in model (will warn if flies age past this)
`iCarryCapF`	carrying capacity of adult females
`fMperF`	numbers of males per female, default 0.5 for half as many M as F
`fStartPopPropCC`	starting population as a proportion of carrying capacity, default = 1 option "sameAsAdults" to set tot pupae same as tot adults.
`pMortF`	adult female mortality on day1, rates on later days are determined by following parameters.
`pMortM`	adult male mortality on day1, rates on later days are determined by following parameters.
`iMortMinAgeStart`	Age at which min death rates start.
`iMortMinAgeStop`	Age at which min death rates stop.
`fMortMinProp`	What proportion of the maximum death rate on day 0 is the minimum death rate.
`fMortOldProp`	What proportion of the maximum death rate on day 0 is the death rate after iDeathMinAgeStop.
`propMortAdultDD`	proportion of adult mortality that is density dependent
`pMortPupa`	pupal mortality per period
`propMortPupaDD`	proportion of pupal mortality that is density dependent
`iPupDurF`	days it takes pupa(F) to develop
`iPupDurM`	days it takes pupa(M) to develop
`iFirstLarva`	Age that female produces first larva
`iInterLarva`	Inter-larval period
`pMortLarva`	larval mortality per period
`propMortLarvaDD`	proportion of larval mortality that is density dependent
`pControl`	extra mortality probability due to control, first go at implementing control. TODO improve this
`iControlBorder`	width (in cells) of border area not to control
`verbose`	print what it's doing T/F
`report`	filename for a report for this run, if not specified no report is produced

This accepts a grid of vegetation and how mortality varies by vegetation.

a multi-dimensional array [day,y,x,sex,ages]

## Not run: 
tst <- rt_runGrid()
rtPlotMapPop(tst)
#now try an unequal matrix
mCarryCapF <- matrix( 10*(1:16), 4, 4)
tst <- rt_runGrid(mCarryCapF)
rtPlotMapPop(tst) 
#an unequal matrix starting at a fraction of CC
tst <- rt_runGrid(mCarryCapF, fStartPopPropCC = 0.5)
rtPlotMapPop(tst) 

## End(Not run)