ggvpc_standard: VPC plot using ggplot2 (standard)

In qPharmetra/qpToolkit: qPharmetra R Tools

VPC plot using ggplot2 (standard)

Description

Plot basic vpc with 95% PI and observed data. This call is to be extended with for stratification, and axes definition using the layering custom to ggplot2 objects. See the examples below to learn more.

Usage

ggvpc_standard(
  vpc,
  PI = c(0.025, 0.975),
  area.col = PI.ci.med.arcol,
  linecol.obs.central = PI.real.med.col,
  linetype.obs.central = "solid",
  linetype.obs.outer = "dashed",
  linecol.obs.outer = "darkslategrey",
  linesize.obs = 0.5,
  alpha = 0.33,
  point.shape = 1,
  point.size = 1.5,
  point.col = "darkslategrey",
  yrange.stretch = c(0.9, 1.1),
  quiet = TRUE
)

Arguments

vpc	output from nm.read.vpc
PI	prediction interval (c(0.025,0.975) for 95% CI)
area.col	color of prediction polygon
linecol.obs.central	color of observed central lines
linetype.obs.central	line type of observed central lines
linetype.obs.outer	line type of observed outer lines
linecol.obs.outer	line color of observed outer lines
linesize.obs	line width of observed data
alpha	transparancy scalar (between 0 and 1)
point.shape	numeric value for dot shape
point.size	numeric value for dot size
point.col	color of observed data dots
yrange.stretch	vector of c(min,max) which will proportionally rescale the lower and upper limits of the Y axis
quiet	whether to suppress process messages

Value

A ggplot object to be extended optionally

Note

Editing and stratification to be done by adding ggplot layer

See Also

nm.read.vpc, ggvpc_xpose

Examples

library(ggplot2)
vpc.all = nm.read.vpc(path = file.path(getOption("qpExampleDir"), "vpc_final_strt"))
ggvpc_standard(vpc.all)

ggvpc_standard(vpc.all) +
  labs(x = "Time (h)", y = "Concentration (ng/ml)")

## different Prediction Interval (PI), let's use 90% instead of 95%
ggvpc_standard(vpc.all, PI = c(0.05,0.95)) +
  labs(x = "Time (h)", y = "Concentration (ng/ml)")

## logging axes
ggvpc_standard(vpc.all) +
  labs(x = "Time (h)", y = "Concentration (ng/ml)") + scale_y_log10() + scale_x_log10()

#modify colors and transparency:
ggvpc_standard(vpc.all, area.col = indigo, alpha = 1, point.shape = 15) +
  labs(x = "Time (h)", y = "Concentration (ng/ml)") + scale_y_log10()

## dealing with stratification
myVPC = nm.read.vpc(path = file.path(getOption("qpExampleDir"), "vpc_base_strt"))

p = ggvpc_standard(vpc.all, yrange.stretch = c(1,1))
p = p +  labs(x = "Time (h)", y = "Concentration (ng/ml)")
p +  facet_wrap(~strata) + scale_y_log10()

qPharmetra/qpToolkit documentation built on May 24, 2023, 8:52 a.m.