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Time-values profile plot for population simulations

Source: R/plot-population-time-profile.R
plotPopulationTimeProfile.Rd

Time-values profile plot for population simulations

Usage

plotPopulationTimeProfile(
  dataCombined,
  defaultPlotConfiguration = NULL,
  aggregation = "quantiles",
  quantiles = c(0.05, 0.5, 0.95),
  showLegendPerDataset = FALSE,
  ...
)

Arguments

dataCombined

A single instance of DataCombined class containing both observed and simulated datasets to be compared.

defaultPlotConfiguration

A DefaultPlotConfiguration object, which is an R6 class object that defines plot properties.

aggregation

The type of the aggregation of individual data. One of quantiles (Default), arithmetic or geometric (full list in ospsuite::DataAggregationMethods). Will replace yValues by the median, arithmetic or geometric average and add a set of upper and lower bounds (yValuesLower and yValuesHigher).

quantiles

A numerical vector with quantile values (Default: c(0.05, 0.50, 0.95)) to be plotted. Ignored if aggregation is not quantiles.

showLegendPerDataset

Logical flag to display separate legend entries for observed and simulated datasets, if available. This is experimental and may not work reliably when both observed and simulated datasets > 1. Defaults to FALSE.

...

additionnal arguments to pass to .extractAggregatedSimulatedData()

Details

The simulated values will be aggregated across individuals for each time point.

For aggregation = quantiles (default), the quantile values defined in the argument quantiles will be used. In the profile plot, the middle value will be used to draw a line, while the lower and upper values will be used as the lower und upper ranges. For aggregation = arithmetic, arithmetic mean with arithmetic standard deviation (SD) will be plotted. Use the optional parameter nsd to change the number of SD to plot above and below the mean. For aggregation = geometric, geometric mean with geometric standard deviation (SD) will be plotted. Use the optional parameter nsd to change the number of SD to plot above and below the mean.

See also

Other plotting: DefaultPlotConfiguration, plotIndividualTimeProfile(), plotObservedVsSimulated(), plotResidualsVsSimulated(), plotResidualsVsTime()

Examples

simFilePath <- system.file("extdata", "Aciclovir.pkml", package = "ospsuite")
sim <- loadSimulation(simFilePath)

populationResults <- importResultsFromCSV(
  simulation = sim,
  filePaths = system.file("extdata", "SimResults_pop.csv", package = "ospsuite")
)

# Create a new instance of `DataCombined` class
myDataComb <- DataCombined$new()
myDataComb$addSimulationResults(populationResults)


# plot
plotPopulationTimeProfile(myDataComb)


# plot with other quantiles
plotPopulationTimeProfile(myDataComb, quantiles = c(0.1, 0.5, 0.9))


# plot with arithmetic mean
plotPopulationTimeProfile(myDataComb,
  aggregation = "arithmetic"
)