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:

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")


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ubiquity documentation built on May 29, 2024, 12:02 p.m.