dosing_regimen_plot: Plot the dosing regimens used in simulations

In shirewoman2/Consultancy: Standardized tools for using R within the Simcyp Consultancy Team

Plot the dosing regimens used in simulations

Description

dosing_regimen_plot creates a graph of the dosing regimens used. This requires you to have created an object with simulation information by running codeextractExpDetails or codeextractExpDetails_mult; that object will be a list, and the list item named "Dosing" will be used for creating these graphs.

Usage

dosing_regimen_plot(
  existing_exp_details,
  sims_to_include = NA,
  colorBy_column,
  color_set = NA,
  facet1_column,
  facet2_column,
  bar_width = NA
)

Arguments

existing_exp_details	output from extractExpDetails or extractExpDetails_mult.
sims_to_include	optionally specify which simulation files you'd like to include in the annotated output. Acceptable input: NA (default) get all the simulations included in existing_exp_details a character vector of the file names you want The items in the character vector must exactly match file names in the column "File" of the "MainDetails" item in existing_exp_details, including the ".xlsx" or ".db" file extension
colorBy_column	(optional) the column in existing_exp_details$Dosing that should be used for determining which color lines will be. This should be unquoted, e.g., colorBy_column = Compound.
color_set	the set of colors to use. Options: "default" a set of colors from Cynthia Brewer et al. from Penn State that are friendly to those with red-green colorblindness. The first three colors are green, orange, and purple. This can also be referred to as "Brewer set 2". If there are only two unique values in the colorBy_column, then Brewer set 1 will be used since red and blue are still easily distinguishable but also more aesthetically pleasing than green and orange. "Brewer set 1" colors selected from the Brewer palette "set 1". The first three colors are red, blue, and green. "ggplot2 default" the default set of colors used in ggplot2 graphs (ggplot2 is an R package for graphing.) "rainbow" colors selected from a rainbow palette. The default palette is limited to something like 6 colors, so if you have more than that, that's when this palette is most useful. It's not very useful when you only need a couple of colors. "blue-green" a set of blues fading into greens. This palette can be especially useful if you are comparing a systematic change in some continuous variable – for example, increasing dose or predicting how a change in intrinsic solubility will affect concentration-time profiles – because the direction of the trend will be clear. "blues" a set of blues fading from sky to navy. Like "blue-green", this palette can be especially useful if you are comparing a systematic change in some continuous variable. "greens" a set of greens fading from chartreuse to forest. Great for showing systematic changes in a continuous variable. "purples" a set of purples fading from lavender to aubergine. Great for showing systematic changes in a continuous variable. "reds" a set of reds from pink to brick. Great for showing systematic changes in a continuous variable. "Tableau" uses the standard Tableau palette; requires the "ggthemes" package "viridis" from the eponymous package by Simon Garnier and ranges colors from purple to blue to green to yellow in a manner that is "printer-friendly, perceptually uniform and easy to read by those with colorblindness", according to the package author a character vector of colors If you'd prefer to set all the colors yourself to exactly the colors you want, you can specify those colors here. An example of how the syntax should look: color_set = c("dodgerblue3", "purple", "#D8212D") or, if you want to specify exactly which item in colorBy_column gets which color, you can supply a named vector. For example, if you're coloring the lines by the compound ID, you could do this: color_set = c("substrate" = "dodgerblue3", "inhibitor 1" = "purple", "primary metabolite 1" = "#D8212D"). If you'd like help creating a specific gradation of colors, please talk to a member of the R Working Group about how to do that using colorRampPalette.
facet1_column	optionally break up the graph into small multiples in the vertical direction. The designated column name should be unquoted, e.g., facet1_column = CompoundID. NB: If the object with simulation information that you provided with the argument existing_exp_details doesn't have the column you want in the item named "Dosing", which is where this function gets the information it graphs, but it does have that column in the item named "MainDetails", that's fine; we'll get the information we need from there. If you want to add some other column of information for breaking up the graph, please add that column to the item in existing_exp_details titled "Dosing".
facet2_column	optionally break up the graph into small multiples in the horizontal direction. The designated column name should be unquoted, e.g., facet2_column = File. NB: If the object with simulation information that you provided with the argument existing_exp_details doesn't have the column you want in the item named "Dosing", which is where this function gets the information it graphs, but it does have that column in the item named "MainDetails", that's fine; we'll get the information we need from there. If you want to add some other column of information for breaking up the graph, please add that column to the item in existing_exp_details titled "Dosing".
bar_width	width of the bars in hours; we'll go for a smallish bar as the default, but please do try making it larger to visualize more easily if your time range allows for that.

Value

a ggplot2 graph

Examples

dosing_regimen_plot(existing_exp_details = MDZdetails)

dosing_regimen_plot(existing_exp_details = MDZdetails,
                    bar_width = 20)

dosing_regimen_plot(existing_exp_details = MDZdetails,
                    colorBy_column = CompoundID)

shirewoman2/Consultancy documentation built on June 1, 2025, 6:05 p.m.