Dtrace: Trace optimization routines

In andrewhooker/PopED: Population (and Individual) Optimal Experimental Design

Trace optimization routines

Description

A helper function for writing output to the screen and files when optimizing.

Usage

Dtrace(
  fn,
  it,
  ni,
  xtopt,
  xopt,
  aopt,
  gxt,
  ga,
  dmf,
  diff,
  ixt,
  ia,
  itvector,
  dmfvector,
  poped.db,
  opt_xt = poped.db$settings$optsw[2],
  opt_a = poped.db$settings$optsw[4],
  opt_x = poped.db$settings$optsw[3],
  opt_samps = poped.db$settings$optsw[1],
  opt_inds = poped.db$settings$optsw[5],
  rsit = poped.db$settings$rsit,
  convergence_eps = poped.db$settings$convergence_eps
)

Arguments

fn	A file to output information to. Can also be the screen if ''.
it	the iteration number.
ni	A vector of the number of samples in each group.
xtopt	The matrix defining current best sampling schedule.
xopt	The cell structure defining the current best discrete design variables.
aopt	The matrix defining the current best continuous design variables.
gxt	The matrix defining the current gradient of the xt vector.
ga	The matrix defining the current gradient for the continuous design variables.
dmf	The current OFV.
diff	The difference from the previous iteration.
ixt	If xt Gradient Inversion occurred or not.
ia	If a Gradient Inversion occurred or not.
itvector	The iteration vector. Not currently used.
dmfvector	The dmf vector. Not currently used.
poped.db	A PopED database.
opt_xt	Should the sample times be optimized?
opt_a	Should the continuous design variables be optimized?
opt_x	Should the discrete design variables be optimized?
opt_samps	Are the number of sample times per group being optimized?
opt_inds	Are the number of individuals per group being optimized?
rsit	Number of Random search iterations
convergence_eps	Stochastic Gradient convergence value, (difference in OFV for D-optimal, difference in gradient for ED-optimal)

Examples

library(PopED)

############# START #################
## Create PopED database
## (warfarin model for optimization)
#####################################

## Warfarin example from software comparison in:
## Nyberg et al., "Methods and software tools for design evaluation 
##   for population pharmacokinetics-pharmacodynamics studies", 
##   Br. J. Clin. Pharm., 2014. 

## Optimization using an additive + proportional reidual error  
## to avoid sample times at very low concentrations (time 0 or very late samples).

## find the parameters that are needed to define from the structural model
ff.PK.1.comp.oral.sd.CL

## -- parameter definition function 
## -- names match parameters in function ff
sfg <- function(x,a,bpop,b,bocc){
  parameters=c(CL=bpop[1]*exp(b[1]),
               V=bpop[2]*exp(b[2]),
               KA=bpop[3]*exp(b[3]),
               Favail=bpop[4],
               DOSE=a[1])
  return(parameters) 
}

## -- Define initial design  and design space
poped.db <- create.poped.database(ff_fun=ff.PK.1.comp.oral.sd.CL,
                                  fg_fun=sfg,
                                  fError_fun=feps.add.prop,
                                  bpop=c(CL=0.15, V=8, KA=1.0, Favail=1), 
                                  notfixed_bpop=c(1,1,1,0),
                                  d=c(CL=0.07, V=0.02, KA=0.6), 
                                  sigma=c(prop=0.01,add=0.25),
                                  groupsize=32,
                                  xt=c( 0.5,1,2,6,24,36,72,120),
                                  minxt=0.01,
                                  maxxt=120,
                                  a=c(DOSE=70),
                                  mina=c(DOSE=0.01),
                                  maxa=c(DOSE=100))

############# END ###################
## Create PopED database
## (warfarin model for optimization)
#####################################


FIM <- evaluate.fim(poped.db) 
dmf <- det(FIM)

Dtrace(fn="",
       it=1,
       ni=poped.db$design$ni,
       xtopt=poped.db$design$xt,
       xopt=poped.db$design$x,
       aopt=poped.db$design$a,
       gxt=0,ga=0,
       dmf=dmf,diff=3,
       ixt=FALSE,
       ia=FALSE, 
       itvector=NULL,
       dmfvector=NULL,
       poped.db,
       opt_xt=poped.db$settings$optsw[2],
       opt_a=poped.db$settings$optsw[4],opt_x=poped.db$settings$optsw[3],
       opt_samps=poped.db$settings$optsw[1],opt_inds=poped.db$settings$optsw[5],
       rsit=200)

Dtrace(fn="",
       it=1,
       ni=poped.db$design$ni,
       xtopt=poped.db$design$xt,
       xopt=poped.db$design$x,
       aopt=poped.db$design$a,
       gxt=0,ga=0,
       dmf=dmf,diff=3,
       ixt=FALSE,
       ia=FALSE, 
       itvector=NULL,
       dmfvector=NULL,
       poped.db,
       opt_xt=poped.db$settings$optsw[2],
       opt_a=poped.db$settings$optsw[4],opt_x=poped.db$settings$optsw[3],
       opt_samps=poped.db$settings$optsw[1],opt_inds=poped.db$settings$optsw[5],
       rsit=0)

Dtrace(fn="",
       it=1,
       ni=poped.db$design$ni,
       xtopt=poped.db$design$xt,
       xopt=poped.db$design$x,
       aopt=poped.db$design$a,
       gxt=0,ga=0,
       dmf=dmf,diff=3,
       ixt=FALSE,
       ia=FALSE, 
       itvector=NULL,
       dmfvector=NULL,
       poped.db,
       opt_xt=poped.db$settings$optsw[2],
       opt_a=poped.db$settings$optsw[4],opt_x=poped.db$settings$optsw[3],
       opt_samps=poped.db$settings$optsw[1],opt_inds=poped.db$settings$optsw[5],
       rsit=1)

Dtrace(fn="",
       it=1,
       ni=poped.db$design$ni,
       xtopt=poped.db$design$xt,
       xopt=poped.db$design$x,
       aopt=poped.db$design$a,
       gxt=0,ga=0,
       dmf=dmf,
       diff=0,
       ixt=FALSE,
       ia=FALSE, 
       itvector=NULL,
       dmfvector=NULL,
       poped.db,
       opt_xt=poped.db$settings$optsw[2],
       opt_a=poped.db$settings$optsw[4],opt_x=poped.db$settings$optsw[3],
       opt_samps=poped.db$settings$optsw[1],opt_inds=poped.db$settings$optsw[5],
       rsit=1)

Dtrace(fn="",
       it=5,
       ni=poped.db$design$ni,
       xtopt=poped.db$design$xt,
       xopt=poped.db$design$x,
       aopt=poped.db$design$a,
       gxt=0,ga=0,
       dmf=dmf,
       diff=0,
       ixt=FALSE,
       ia=FALSE, 
       itvector=NULL,
       dmfvector=NULL,
       poped.db,
       opt_xt=poped.db$settings$optsw[2],
       opt_a=poped.db$settings$optsw[4],opt_x=poped.db$settings$optsw[3],
       opt_samps=poped.db$settings$optsw[1],opt_inds=poped.db$settings$optsw[5],
       rsit=1)

andrewhooker/PopED documentation built on Nov. 23, 2023, 1:37 a.m.