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-rw-r--r--R/mkinpredict.R152
1 files changed, 61 insertions, 91 deletions
diff --git a/R/mkinpredict.R b/R/mkinpredict.R
index 16ee7903..0f8e83bb 100644
--- a/R/mkinpredict.R
+++ b/R/mkinpredict.R
@@ -41,57 +41,63 @@
#' @author Johannes Ranke
#' @examples
#'
-#' SFO <- mkinmod(degradinol = mkinsub("SFO"))
-#' # Compare solution types
-#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-#' solution_type = "analytical")
-#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-#' solution_type = "deSolve")
-#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-#' solution_type = "deSolve", use_compiled = FALSE)
-#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-#' solution_type = "eigen")
+#' SFO <- mkinmod(degradinol = mkinsub("SFO"))
+#' # Compare solution types
+#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+#' solution_type = "analytical")
+#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+#' solution_type = "deSolve")
+#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+#' solution_type = "deSolve", use_compiled = FALSE)
+#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+#' solution_type = "eigen")
#'
+#' # Compare integration methods to analytical solution
+#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+#' solution_type = "analytical")[21,]
+#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+#' method = "lsoda")[21,]
+#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+#' method = "ode45")[21,]
+#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+#' method = "rk4")[21,]
+#' # rk4 is not as precise here
#'
-#' # Compare integration methods to analytical solution
-#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-#' solution_type = "analytical")[21,]
-#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-#' method = "lsoda")[21,]
-#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-#' method = "ode45")[21,]
-#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
-#' method = "rk4")[21,]
-#' # rk4 is not as precise here
+#' # The number of output times used to make a lot of difference until the
+#' # default for atol was adjusted
+#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
+#' seq(0, 20, by = 0.1))[201,]
+#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
+#' seq(0, 20, by = 0.01))[2001,]
#'
-#' # The number of output times used to make a lot of difference until the
-#' # default for atol was adjusted
-#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
-#' seq(0, 20, by = 0.1))[201,]
-#' mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
-#' seq(0, 20, by = 0.01))[2001,]
+#' # Check compiled model versions - they are faster than the eigenvalue based solutions!
+#' SFO_SFO = mkinmod(parent = list(type = "SFO", to = "m1"),
+#' m1 = list(type = "SFO"))
+#' if(require(rbenchmark)) {
+#' benchmark(
+#' eigen = mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
+#' c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
+#' solution_type = "eigen")[201,],
+#' deSolve_compiled = mkinpredict(SFO_SFO,
+#' c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
+#' c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
+#' solution_type = "deSolve")[201,],
+#' deSolve = mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
+#' c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
+#' solution_type = "deSolve", use_compiled = FALSE)[201,],
+#' replications = 10)
+#' }
#'
-#' # Check compiled model versions - they are faster than the eigenvalue based solutions!
-#' SFO_SFO = mkinmod(parent = list(type = "SFO", to = "m1"),
-#' m1 = list(type = "SFO"))
-#' system.time(
-#' print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
-#' c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
-#' solution_type = "eigen")[201,]))
-#' system.time(
-#' print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
-#' c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
-#' solution_type = "deSolve")[201,]))
-#' system.time(
-#' print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
-#' c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
-#' solution_type = "deSolve", use_compiled = FALSE)[201,]))
+#' # Since mkin 0.9.49.11 we also have analytical solutions for some models, including SFO-SFO
+#' # deSolve = mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
+#' # c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
+#' # solution_type = "analytical", use_compiled = FALSE)[201,],
#'
-#' \dontrun{
-#' # Predict from a fitted model
-#' f <- mkinfit(SFO_SFO, FOCUS_2006_C)
-#' head(mkinpredict(f))
-#' }
+#' \dontrun{
+#' # Predict from a fitted model
+#' f <- mkinfit(SFO_SFO, FOCUS_2006_C, quiet = TRUE)
+#' head(mkinpredict(f))
+#' }
#'
#' @export
mkinpredict <- function(x, odeparms, odeini,
@@ -124,54 +130,17 @@ mkinpredict.mkinmod <- function(x,
odeini <- odeini[mod_vars]
}
- # Create function for evaluation of expressions with ode parameters and initial values
- evalparse <- function(string)
- {
- eval(parse(text=string), as.list(c(odeparms, odeini)))
- }
-
- # Create a function calculating the differentials specified by the model
- # if necessary
if (solution_type == "analytical") {
- parent.type = names(x$map[[1]])[1]
- parent.name = names(x$diffs)[[1]]
- o <- switch(parent.type,
- SFO = SFO.solution(outtimes,
- evalparse(parent.name),
- ifelse(x$use_of_ff == "min",
- evalparse(paste("k", parent.name, "sink", sep="_")),
- evalparse(paste("k", parent.name, sep="_")))),
- FOMC = FOMC.solution(outtimes,
- evalparse(parent.name),
- evalparse("alpha"), evalparse("beta")),
- IORE = IORE.solution(outtimes,
- evalparse(parent.name),
- ifelse(x$use_of_ff == "min",
- evalparse(paste("k__iore", parent.name, "sink", sep="_")),
- evalparse(paste("k__iore", parent.name, sep="_"))),
- evalparse("N_parent")),
- DFOP = DFOP.solution(outtimes,
- evalparse(parent.name),
- evalparse("k1"), evalparse("k2"),
- evalparse("g")),
- HS = HS.solution(outtimes,
- evalparse(parent.name),
- evalparse("k1"), evalparse("k2"),
- evalparse("tb")),
- SFORB = SFORB.solution(outtimes,
- evalparse(parent.name),
- evalparse(paste("k", parent.name, "bound", sep="_")),
- evalparse(paste("k", sub("free", "bound", parent.name), "free", sep="_")),
- evalparse(paste("k", parent.name, "sink", sep="_"))),
- logistic = logistic.solution(outtimes,
- evalparse(parent.name),
- evalparse("kmax"), evalparse("k0"),
- evalparse("r"))
- )
- out <- data.frame(outtimes, o)
- names(out) <- c("time", sub("_free", "", parent.name))
+ out <- x$deg_func(odeini = odeini,
+ odeparms = odeparms, outtimes = outtimes)
}
+
if (solution_type == "eigen") {
+
+ evalparse <- function(string) {
+ eval(parse(text=string), as.list(c(odeparms, odeini)))
+ }
+
coefmat.num <- matrix(sapply(as.vector(x$coefmat), evalparse),
nrow = length(mod_vars))
e <- eigen(coefmat.num)
@@ -184,6 +153,7 @@ mkinpredict.mkinmod <- function(x,
out <- data.frame(outtimes, t(o))
names(out) <- c("time", mod_vars)
}
+
if (solution_type == "deSolve") {
if (!is.null(x$cf) & use_compiled[1] != FALSE) {
out <- ode(

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