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### ============================================================================
### vode -- solves ordinary differential equation systems
### The user has to specify whether or not
### the problem is stiff and choose the appropriate method.
### It is very similar to lsode, except for some implementation details.
### More specifically,
### 1. there are more methods (mf) available in vode compared to lsode.
### 2. the memory management is more flexible in vode:
### when a method flag (mf) is positive, vode will save
### a copy of the Jacobian for reuse in the corrector iteration algorithm;
### for negative method flags a copy of the Jacobian is not saved.
### Thus negative flags need less memory, but positive flags
### may be (slightly) faster
### nb. this reduced memory strategy is the only option of lsode - a mf=21
### in lsode is then equivalent to a mf = -21 in vode.
### ============================================================================
vode <- function(y, times, func, parms, rtol=1e-6, atol=1e-6,
jacfunc=NULL, jactype = "fullint", mf = NULL, verbose=FALSE,
tcrit = NULL, hmin=0, hmax=NULL, hini=0, ynames=TRUE, maxord=NULL,
bandup=NULL, banddown=NULL, maxsteps=5000, dllname=NULL,
initfunc=dllname, initpar=parms, rpar=NULL, ipar=NULL,
nout=0, outnames=NULL, forcings=NULL, initforc = NULL,
fcontrol=NULL, events=NULL, lags = NULL, ...) {
### check input
if (is.list(func)) { # a list of compiled function specification
if (!is.null(jacfunc) & "jacfunc" %in% names(func))
stop("If 'func' is a list that contains jacfunc, argument 'jacfunc' should be NULL")
if (!is.null(initfunc) & "initfunc" %in% names(func))
stop("If 'func' is a list that contains initfunc, argument 'initfunc' should be NULL")
if (!is.null(dllname) & "dllname" %in% names(func))
stop("If 'func' is a list that contains dllname, argument 'dllname' should be NULL")
if (!is.null(initforc) & "initforc" %in% names(func))
stop("If 'func' is a list that contains initforc, argument 'initforc' should be NULL")
if (!is.null(events$func) & "eventfunc" %in% names(func))
stop("If 'func' is a list that contains eventfunc, argument 'events$func' should be NULL")
if ("eventfunc" %in% names(func)) {
if (! is.null(events))
events$func <- func$eventfunc
else
events <- list(func = func$eventfunc)
}
if (!is.null(func$jacfunc)) jacfunc <- func$jacfunc
if (!is.null(func$initfunc)) initfunc <- func$initfunc
if (!is.null(func$dllname)) dllname <- func$dllname
if (!is.null(func$initforc)) initforc <- func$initforc
func <- func$func
}
hmax <- checkInput (y, times, func, rtol, atol,
jacfunc, tcrit, hmin, hmax, hini, dllname)
n <- length(y)
if (!is.null(maxord))
if (maxord < 1)
stop("`maxord' must be >1")
### Jacobian, method flag
if (is.null(mf)) {
if (jactype == "fullint" )
imp <- 22 # full, calculated internally
else if (jactype == "fullusr" )
imp <- 21 # full, specified by user function
else if (jactype == "bandusr" )
imp <- 24 # banded, specified by user function
else if (jactype == "bandint" )
imp <- 25 # banded, calculated internally
else
stop("'jactype' must be one of 'fullint', 'fullusr', 'bandusr' or 'bandint' if 'mf' not specified")
} else imp <- mf
if (! imp %in% c(10:17, 20:27, -11,-12,-14,-15,-21, -22, -24: -27))
stop ("method flag 'mf' not allowed")
# check other specifications depending on Jacobian
miter <- abs(imp)%%10
if (miter %in% c(1,4) & is.null(jacfunc))
stop ("'jacfunc' NOT specified; either specify 'jacfunc' or change 'jactype' or 'mf'")
meth <- abs(imp)%/%10 # basic linear multistep method
jsv <- sign(imp)
if (is.null (maxord))
maxord <- ifelse(meth==1,12,5)
if (meth==1 && maxord > 12)
stop ("'maxord' too large: should be <= 12")
if (meth==2 && maxord > 5 )
stop ("'maxord' too large: should be <= 5")
if (miter %in% c(4,5) && is.null(bandup))
stop("'bandup' must be specified if banded Jacobian")
if (miter %in% c(4,5) && is.null(banddown))
stop("'banddown' must be specified if banded Jacobian")
if (is.null(banddown)) banddown <-1
if (is.null(bandup )) bandup <-1
### model and Jacobian function
Func <- NULL
JacFunc <- NULL
## if (miter == 4) Jacobian should have banddown empty rows!
if (miter == 4 && banddown>0)
erow<-matrix(data=0, ncol=n, nrow=banddown) else erow<-NULL
Ynames <- attr(y,"names")
flist<-list(fmat=0,tmat=0,imat=0,ModelForc=NULL)
ModelInit <- NULL
Eventfunc <- NULL
events <- checkevents(events, times, Ynames, dllname)
if (! is.null(events$newTimes)) times <- events$newTimes
if (is.character(func) | inherits(func, "CFunc")) { # function specified in a DLL or inline compiled
DLL <- checkDLL(func,jacfunc,dllname,
initfunc,verbose,nout, outnames)
ModelInit <- DLL$ModelInit
Func <- DLL$Func
JacFunc <- DLL$JacFunc
Nglobal <- DLL$Nglobal
Nmtot <- DLL$Nmtot
if (! is.null(forcings))
flist <- checkforcings(forcings,times,dllname,initforc,verbose,fcontrol)
if (is.null(ipar)) ipar<-0
if (is.null(rpar)) rpar<-0
Eventfunc <- events$func
if (is.function(Eventfunc))
rho <- environment(Eventfunc)
else
rho <- NULL
} else {
if(is.null(initfunc))
initpar <- NULL # parameter initialisation not needed if function is not a DLL
rho <- environment(func)
# func and jac are overruled, either including ynames, or not
# This allows to pass the "..." arguments and the parameters
if(ynames) {
Func <- function(time,state) {
attr(state,"names") <- Ynames
unlist(func (time,state,parms,...))
}
Func2 <- function(time,state){
attr(state,"names") <- Ynames
func (time,state,parms,...)
}
JacFunc <- function(time,state){
attr(state,"names") <- Ynames
rbind(jacfunc(time,state,parms,...),erow)
}
if (! is.null(events$Type))
if (events$Type == 2)
Eventfunc <- function(time,state) {
attr(state,"names") <- Ynames
events$func(time,state,parms,...)
}
} else { # no ynames...
Func <- function(time,state)
unlist(func (time,state,parms,...))
Func2 <- function(time,state)
func (time,state,parms,...)
JacFunc <- function(time,state)
rbind(jacfunc(time,state,parms,...),erow)
if (! is.null(events$Type))
if (events$Type == 2)
Eventfunc <- function(time,state)
events$func(time,state,parms,...)
}
## Check function and return the number of output variables +name
FF <- checkFunc(Func2,times,y,rho)
Nglobal<-FF$Nglobal
Nmtot <- FF$Nmtot
if (! is.null(events$Type))
if (events$Type == 2)
checkEventFunc(Eventfunc,times,y,rho)
if (miter %in% c(1,4)) {
tmp <- eval(JacFunc(times[1], y), rho)
if (!is.matrix(tmp))
stop("Jacobian function must return a matrix\n")
dd <- dim(tmp)
if((miter ==4 && any(dd != c(bandup+banddown+banddown+1,n))) ||
(miter ==1 && any(dd != c(n,n))))
stop("Jacobian dimension not ok")
}
}
### work arrays iwork, rwork
# length of rwork and iwork
lrw <- 20+n*(maxord+1)+3*n
if(miter %in% c(1,2) && imp>0)
lrw <- lrw + 2*n*n+2
if(miter %in% c(1,2) && imp<0)
lrw <- lrw + n*n+2
if(miter ==3)
lrw <- lrw + n+2
if(miter %in% c(4,5) && imp>0)
lrw <- lrw + (3*banddown+2*bandup+2)*n+2
if(miter %in% c(4,5) && imp<0)
lrw <- lrw + (2*banddown+bandup+1)*n+2
liw <- ifelse(miter %in% c(0,3),30,30+n)
# only first 20 or 30 elements passed; other will be allocated in C-code
iwork <- vector("integer",30)
rwork <- vector("double",20)
rwork[] <- 0.
iwork[] <- 0
iwork[1] <- banddown
iwork[2] <- bandup
iwork[5] <- maxord
iwork[6] <- maxsteps
if(! is.null(tcrit)) rwork[1] <- tcrit
rwork[5] <- hini
rwork[6] <- hmax
rwork[7] <- hmin
### the task to be performed.
if (! is.null(times))
itask <- ifelse (is.null (tcrit), 1,4) else # times specified
itask <- ifelse (is.null (tcrit), 2,5) # only one step
if(is.null(times)) times<-c(0,1e8)
### print to screen...
if (verbose) {
printtask(itask,func,jacfunc)
printM("\n--------------------")
printM("Integration method")
printM("--------------------")
df <- c("method flag, =",
"jsv =",
"meth =",
"miter =")
vals <- c(imp, jsv, meth, miter)
txt <- "; (note: mf = jsv * (10 * meth + miter))"
if (jsv==1) txt<-c(txt,
"; a copy of the Jacobian is saved for reuse in the corrector iteration algorithm" ) else
if (jsv==-1)txt<-c(txt,
"; a copy of the Jacobian is not saved")
if (meth==1)txt<-c(txt,
"; the basic linear multistep method: the implicit Adams method") else
if (meth==2)txt<-c(txt,"; the basic linear multistep method:
based on backward differentiation formulas")
if (miter==0)txt<-c(txt,
"; functional iteration (no Jacobian matrix is involved") else
if (miter==1)txt<-c(txt,
"; chord iteration with a user-supplied full (NEQ by NEQ) Jacobian") else
if (miter==2)txt<-c(txt,
"; chord iteration with an internally generated full Jacobian,
(NEQ extra calls to F per df/dy value)") else
if (miter==3)txt<-c(txt,
"; chord iteration with an internally generated diagonal Jacobian
(1 extra call to F per df/dy evaluation)") else
if (miter==4)txt<-c(txt,
"; chord iteration with a user-supplied banded Jacobian") else
if (miter==5)txt<-c(txt,
"; chord iteration with an internally generated banded Jacobian
(using ML+MU+1 extra calls to F per df/dy evaluation)")
printmessage(df, vals, txt)
}
### calling solver
storage.mode(y) <- storage.mode(times) <- "double"
IN <- 5 # vode is livermore solver type 5
lags <- checklags(lags,dllname)
on.exit(.C("unlock_solver"))
out <- .Call("call_lsoda", y, times, Func, initpar, rtol, atol,
rho, tcrit, JacFunc, ModelInit, Eventfunc,
as.integer(verbose),as.integer(itask),
as.double(rwork),as.integer(iwork), as.integer(imp),as.integer(Nglobal),
as.integer(lrw),as.integer(liw),as.integer(IN),NULL,
0L, as.double (rpar), as.integer(ipar),
0L, flist, events, lags, PACKAGE = "deSolve")
### saving results
out [1,1] <- times[1] # t=0 may be altered by dvode!
out <- saveOut(out, y, n, Nglobal, Nmtot, func, Func2,
iin=c(1,12:23), iout=1:13)
attr(out, "type") <- "vode"
if (verbose) diagnostics(out)
out
}
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