ode.band(y, times, func, parms, nspec = NULL,
bandup = nspec, banddown = nspec, method = "lsode", ...)
y
has a name attribute, the names will be used to label the
output matrix.times
must be the initial time.t
, or a character string giving the name of a compiled
function in a dynamically loaded shared library.If
func
."vode"
,
"lsode"
, "lsoda"
, "lsodar"
.times
and as
many columns as elements in y
plus the number of "global"
values returned in the second element of the return from func
,
plus an additional column (the first) for the time value. There will
be one row for each element in times
unless the integrator
returns with an unrecoverable error. If y
has a names
attribute, it will be used to label the columns of the output value.
The output will have the attributes istate
and rstate
,
two vectors with several elements. See the help for the selected
integrator for details. the first element of istate returns the
conditions under which the last call to vode returned. Normal is
istate = 2
. If verbose = TRUE
, the settings of
istate
and rstate
will be written to the screen.ode.1D
.
See the selected integrator for the additional options.ode.1D
, for integrating, when the jacobian matrix is
banded, and where the state variables need to be rearranged.## =================================================
## The Aphid model from Soetaert and Herman, 2008.
## A practical guide to ecological modelling.
## Using R as a simulation platform. Springer.
## =================================================
## 1-D diffusion model
## ================
## Model equations
## ================
Aphid <- function(t, APHIDS, parameters)
{
deltax <- c (0.5, rep(1, numboxes-1), 0.5)
Flux <- -D*diff(c(0, APHIDS, 0))/deltax
dAPHIDS <- -diff(Flux)/delx + APHIDS*r
list(dAPHIDS) # the output
}
## ==================
## Model application
## ==================
## the model parameters:
D <- 0.3 # m2/day diffusion rate
r <- 0.01 # /day net growth rate
delx <- 1 # m thickness of boxes
numboxes <- 60
## distance of boxes on plant, m, 1 m intervals
Distance <- seq(from = 0.5, by = delx, length.out = numboxes)
## Initial conditions, ind/m2
## aphids present only on two central boxes
APHIDS <- rep(0, times = numboxes)
APHIDS[30:31] <- 1
state <- c(APHIDS = APHIDS) # initialise state variables
## RUNNING the model:
times <- seq(0, 200, by = 1) # output wanted at these time intervals
out <- ode.band(state, times, Aphid, parms = 0, nspec = 1)
## ================
## Plotting output
## ================
## the data in 'out' consist of: 1st col times, 2-41: the density
## select the density data
DENSITY <- out[,2:(numboxes + 1)]
filled.contour(x = times, y = Distance, DENSITY, color = topo.colors,
xlab = "time, days", ylab = "Distance on plant, m",
main = "Aphid density on a row of plants")
Run the code above in your browser using DataLab