In john-harrold/ubiquity: PKPD, PBPK, and Systems Pharmacology Modeling Tools

library(knitr)
knitr::opts_chunk$set(echo = FALSE)

# Settign up the local variables
cfg = params$cfg
som = params$som

# Next we update the information in cfg to match that in the gui. Bascially if
# there is an overwrite specified in the cfg$gui$sysel_simulate data structure 
# we apply those here using the eval:
cfg = system_select_set(cfg, cfg$gui$sysel_simulate$pset)
cfg_option_names =  c('parameters', 
                      'options', 
                      'bolus', 
                      'covariates', 
                      'infusion_rates',
                      'iiv')

for(option_name in cfg_option_names){
  if(cfg$gui$sysel_simulate[[option_name]] != ""){
    eval(parse(text=cfg$gui$sysel_simulate[[option_name]])) }
}

# Pulling out the parameter set that was selected
pset_short = cfg$parameters$current_set
pset_long = cfg$parameters$sets[[pset_short]]$name

# Creating boolean variables to indicate the type
# of simulation that has been performed
som_individual = !(cfg$gui$check_variability)
som_population =   cfg$gui$check_variability

if(som_individual){
   # Put your individual code here
}


if(som_population){
   # Put your population code here
}

Implementing reporting

Disable the "Model Report" tab

Edit the file model_gui.r, search for the following line and comment it out:

cfg$gui$modelreport_files$R1$title = "Tab Title" cfg$gui$modelreport_files$R1$file = "my_report.Rmd"

Setting up a Customized Report

To create a customized report copy the template file:

r print(sprintf("library%stemplates%sr_system_report.Rmd", .Platform$file.sep, .Platform$file.sep))

Into the main directory and name it my_report.Rmd. Then edit the model_gui.r file and point it to the new report file:

cfg$gui$modelreport_files$R1$title = "Tab Title" cfg$gui$modelreport_files$R1$file = "my_report.Rmd"

Next you can customize that file using the information below.

Customizing the report

To customize this report, you have access the following variables:

• cfg - System configuration variable
• som - Mapped simulation output
• parameters - current system parameters

To understand the structure of som and access the components of cfg see the documentation in the simulation vignette or view the tutorial on simulations

presentation.ubiquity.grok.tv

Go to the R-Workflow part and look at the output of run_simulation_ubiquity for individual simulations and simulate_subjects for the population simulations.

r if(!som_individual){"\\begin{comment}"} Simulation Type: Individual

This text is shown when a individual simulation has been performed. To make sure that R-code is only executed for individual simulation output it is necessary to wrap that code in a conditional statement:

r if(!som_individual){"\\end{comment}"}

r if(!som_population){"\\begin{comment}"} Simulation Type: Population

This text is shown when a population simulation has been performed. To make sure that R-code is only executed for population simulation output it is necessary to wrap that code in a conditional statement:

r if(!som_population){"\\end{comment}"}

# uncomment the text below and replace OUTPUT with the model output
# and replace TS with the actual timescale
#p = ggplot() 
#p = p + geom_line(data=som$simout, aes(x=TS, y=OUTPUT  , color='OUTPUT'), linetype='solid', size=0.9)
#p = p + xlab('Time (TIME UNITS)')                     
#p = p + ylab('Output')                         
#p = prepare_figure('present', p)              
#p = p + scale_colour_manual(values=c("OUTPUT"="darkblue"))   
#p = p + theme(legend.title = element_blank()) 
#p = p + theme(legend.position = 'bottom')
#p

kable(t(parameters), col.names=c(''), caption="System Parameters")

john-harrold/ubiquity documentation built on March 13, 2024, 2:58 a.m.