The pmplots Gallery - 14 Customize plots

14.1 Layers

“Layers” refer to different reference lines or smoothers that are added to plots by default.

Layers include

smoothing line through the data: smooth
horizontal reference lines: hline
identity lines: abline

For example, dv_pred() adds an identity line (y = x) for reference as well as a smoother through the data

dv_pred(df)

These layers can all be customized or dropped from the plot altogether. This section shows you how to do that. We’ll work on this basic plot as well as plots that come right out of pmplots.

p <- ggplot(df, aes(PRED, DV))  + geom_point() + pm_theme()
p

14.1.1 Layer smooth

p + pm_smooth()

layer_s(p)

14.1.2 Layer abline

p + pm_abline()

layer_a(p)

14.1.3 Layer hline

p + pm_hline(2000)

layer_h(p, hline = 2000)

14.1.4 Drop specific layers

Set the layer to NULL to drop one or more of these layers from the plot.

dv_pred(df, smooth = NULL)

dv_pred(df, abline = NULL)

cwres_time(df, hline = NULL)

dv_pred(df, abline = NULL, smooth = NULL)

14.1.5 Drop all layers

You can also decline to add any layers through add_layers

dv_pred(df, add_layers = FALSE)

14.1.6 Modify layer specs

For any layer type, you can pass a list of arguments that will get passed on to the appropriate geom.

For example, change the values of argument for ggplot2::geom_smooth()

cwres_time(
  df, 
  smooth = list(method = "gam", se = TRUE)
)

The items in the list getting passed as smooth should be arguments in ggplot2::geom_smooth().

Similarly, you can set abline with a list of arguments to get passed to geom_abline() or hline with a list of arguments to get passed to geom_hline().

14.1.7 Extra reference lines to [C]WRES plots

wres_time(df) + geom_3s()

14.2 Axes

You can pass lists of arguments as xs or ys to modify the x- or y-axis, respectively. These arguments get passed to ggplot2::scale_x_continuous() or ggplot2::scale_y_continuous().

14.2.1 Modify x-axis

To modify the x-axis of a plot, pass a list of items as the xs argument; these items will get passed to ggplot2::scale_x_continuous().

For example, to make the x-axis log transformed and modify the breaks, write

a <- list(trans = "log", breaks = logbr3())

dv_time(df, xs = a)

Note: that you can modify the x-axis label of a plot without modifying the scale using ggplot2::xlab()

dv_time(df) + xlab("Time (years)")

14.2.2 Modify y-axis

To modify the y-axis of a plot, pass a list of items as the ys argument; these items will get passed to ggplot2::scale_y_continuous().

For example, to make the y-axis log transformed and modify the breaks, write

dv_time(df, ys = a, yname = "Y-axis name")

There may also be a yname argument for a given plot that will let you directly change the y-axis label as in the example above.

Note: that you can modify the y-axis label of a plot without modifying the scale using ggplot2::ylab()

dv_time(df) + ylab("Concentration (centrigrams/gallon)")

14.2.3 Rotate x and y axis labels

Specify the angle

dv_pred(df) + rot_x(angle = 90) + rot_y()

Rotate to vertical

We are typically rotating the tick labels on the x-axis and frequently it is convenient to ask for a totally vertical rendering

cwres_cat(df, x = "STUDYc") + 
  facet_wrap(~CPc) + rot_x(vertical = TRUE)

14.2.4 Flip coordinates when labels get cramped

If this is too cramped

cont_cat(
  id, 
  y = c("WT", "BMI", "ALB", "CRCL"), 
  x = "STUDYc"
) %>% pm_grid()

Try this

cont_cat(
  id, 
  y = c("WT", "BMI", "ALB", "CRCL"), 
  x = "STUDYc"
) %>% map(~.x+coord_flip()) %>% pm_grid()

14.2.5 Standard axis titles

pm_axis_time()

[1] "TIME//Time {xunit}"

pm_axis_tad()

[1] "TAD//Time after dose {xunit}"

pm_axis_tafd()

[1] "TAFD//Time after first dose {xunit}"

pm_axis_res()

[1] "RES//Residual"

pm_axis_wres()

[1] "WRES//Weighted residual"

pm_axis_cwres()

[1] "CWRES//Conditional weighted residual"

pm_axis_cwresi()

[1] "CWRESI//CWRES with interaction"

pm_axis_npde()

[1] "NPDE//NPDE"

pm_axis_dv()

[1] "DV//Observed {yname}"

pm_axis_pred()

[1] "PRED//Population predicted {xname}"

pm_axis_ipred()

[1] "IPRED//Individual predicted {xname}"

You can glue() in information with these functions

pm_axis_time("hr")

[1] "TIME//Time (hr)"

Similar with

pm_axis_tafd("hr")
pm_axis_tad("hr")

And

pm_axis_dv("ASA concentration (ng/mL)")

[1] "DV//Observed ASA concentration (ng/mL)"

Similar with

pm_axis_pred("ASA concentration (ng/mL)")
pm_axis_ipred("ASA concentration (ng/mL)")

14.2.6 Log breaks

logbr3()

 [1] 1e-10 3e-10 1e-09 3e-09 1e-08 3e-08 1e-07 3e-07 1e-06 3e-06 1e-05 3e-05
[13] 1e-04 3e-04 1e-03 3e-03 1e-02 3e-02 1e-01 3e-01 1e+00 3e+00 1e+01 3e+01
[25] 1e+02 3e+02 1e+03 3e+03 1e+04 3e+04 1e+05 3e+05 1e+06 3e+06 1e+07 3e+07
[37] 1e+08 3e+08 1e+09 3e+09 1e+10 3e+10

logbr()

 [1] 1e-10 1e-09 1e-08 1e-07 1e-06 1e-05 1e-04 1e-03 1e-02 1e-01 1e+00 1e+01
[13] 1e+02 1e+03 1e+04 1e+05 1e+06 1e+07 1e+08 1e+09 1e+10

14.2.7 Custom breaks

Default breaks

dv_time(df)

Break every 3 days

dv_time(df, xby = 72)

Custom breaks and limits

a <- list(breaks = seq(0,240,48), limits = c(0,240))
dv_time(df, xs = a)

14.3 Replicate look and feel

p <- ggplot(df, aes(IPRED,DV)) + geom_point()

p

14.3.1 Theme

p + pm_theme()

14.3.2 Plain

p + theme_plain()

14.3.3 Smooth

p + pm_smooth()

14.3.4 Abline

p + pm_abline()

14.3.5 Horizontal reference line

ggplot(df, aes(TIME,CWRES)) + geom_point() + pm_hline()

14.4 Latex

14.4.1 Latex in axis title

dv_pred(df, x = "PRED//Concentration ($\\mu$g)")

14.4.2 Latex in pairs plot

data <- data.frame(
  m = rnorm(100), 
  s = rnorm(100), 
  n = rnorm(100)
)

x <- c("m//$\\mu$", "s//$\\sigma$", "n//$\\nu$")

pairs_plot(data,x)

14.4.3 Latex in wrapped plots

y <- c("WT//Weight (kg)", "BMI//BMI (kg/m$^2$)", "SCR//SCR (g/dL)")

wrap_cont_time(df, y = y, use_labels=TRUE)