diff options
Diffstat (limited to 'man')
| -rw-r--r-- | man/mkinfit.Rd | 30 | ||||
| -rw-r--r-- | man/mkinpredict.Rd | 24 |
2 files changed, 49 insertions, 5 deletions
diff --git a/man/mkinfit.Rd b/man/mkinfit.Rd index 9c82f5ff..801f540c 100644 --- a/man/mkinfit.Rd +++ b/man/mkinfit.Rd @@ -21,8 +21,9 @@ mkinfit(mkinmod, observed, parms.ini = "auto", state.ini = "auto", fixed_parms = NULL, fixed_initials = names(mkinmod$diffs)[-1], - solution_type = "auto", + solution_type = c("auto", "analytical", "eigen", "deSolve"), method.ode = "lsoda", + use_compiled = "auto", method.modFit = c("Port", "Marq", "SANN", "Nelder-Mead", "BFGS", "CG", "L-BFGS-B"), maxit.modFit = "auto", control.modFit = list(), @@ -102,6 +103,11 @@ mkinfit(mkinmod, observed, \code{\link{ode}} in case the solution type is "deSolve". The default "lsoda" is performant, but sometimes fails to converge. } + \item{use_compiled}{ + If set to \code{FALSE}, no compiled version of the \code{\link{mkinmod}} + model is used, in the calls to \code{\link{mkinpredict}} even if + a compiled verion is present. + } \item{method.modFit}{ The optimisation method passed to \code{\link{modFit}}. @@ -235,8 +241,22 @@ SFO_SFO <- mkinmod( parent = list(type = "SFO", to = "m1", sink = TRUE), m1 = list(type = "SFO")) # Fit the model to the FOCUS example dataset D using defaults -fit <- mkinfit(SFO_SFO, FOCUS_2006_D) -summary(fit) +system.time(fit <- mkinfit(SFO_SFO, FOCUS_2006_D, + solution_type = "eigen")) +system.time(fit.deSolve <- mkinfit(SFO_SFO, FOCUS_2006_D, + solution_type = "deSolve", use_compiled = FALSE)) +system.time(fit.deSolve.compiled <- mkinfit(SFO_SFO, FOCUS_2006_D, + solution_type = "deSolve", use_compiled = TRUE)) +# The performance benefit of using the compiled version is immense compared +# with deSolve without compilation, and about a factor of two compared with the +# eigenvalue based solution +coef(fit) +coef(fit.deSolve) +coef(fit.deSolve.compiled) +endpoints(fit) +endpoints(fit.deSolve) +# Check compiled model versions against other solutions + # Use stepwise fitting, using optimised parameters from parent only fit, FOMC \dontrun{ @@ -258,10 +278,10 @@ SFORB_SFO <- mkinmod( m1 = list(type = "SFO")) # Fit the model to the FOCUS example dataset D using defaults fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D) +fit.SFORB_SFO.deSolve <- mkinfit(SFORB_SFO, FOCUS_2006_D, solution_type = "deSolve") # Use starting parameters from parent only SFORB fit (not really needed in this case) fit.SFORB = mkinfit(SFORB, FOCUS_2006_D) fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D, parms.ini = fit.SFORB$bparms.ode) -} # Weighted fits, including IRLS SFO_SFO.ff <- mkinmod(parent = list(type = "SFO", to = "m1"), @@ -275,6 +295,7 @@ summary(f.w.mean) f.w.mean.irls <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, weight = "mean", reweight.method = "obs") summary(f.w.mean.irls) +} \dontrun{ # Manual weighting @@ -287,6 +308,7 @@ f.w.man.irls <- mkinfit(SFO_SFO.ff, dw, err = "err.man", reweight.method = "obs") summary(f.w.man.irls) } + } \keyword{ models } \keyword{ optimize } diff --git a/man/mkinpredict.Rd b/man/mkinpredict.Rd index 7d8979e4..c6aee75f 100644 --- a/man/mkinpredict.Rd +++ b/man/mkinpredict.Rd @@ -10,7 +10,8 @@ } \usage{ mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = "deSolve", - method.ode = "lsoda", atol = 1e-08, rtol = 1e-10, map_output = TRUE, ...) + use_compiled = "auto", method.ode = "lsoda", atol = 1e-08, rtol = 1e-10, + map_output = TRUE, ...) } \arguments{ \item{mkinmod}{ @@ -41,6 +42,10 @@ \code{\link{ode}} in case the solution type is "deSolve". The default "lsoda" is performant, but sometimes fails to converge. } + \item{use_compiled}{ + If set to \code{FALSE}, no compiled version of the \code{\link{mkinmod}} + model is used, even if is present. + } \item{atol}{ Absolute error tolerance, passed to \code{\link{ode}}. Default is 1e-8, lower than in \code{\link{lsoda}}. @@ -71,6 +76,8 @@ 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") @@ -92,5 +99,20 @@ 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")) + 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,])) } \keyword{ manip } |