Create partial dependence plots for deweather models — plot_dw_partial

Generates partial dependence plots to visualize the relationship between predictor variables and model predictions. These plots show how the predicted pollutant concentration changes as a function of one variable while averaging over the effects of all other variables.

Usage

plot_dw_partial_1d(
  dw,
  vars = NULL,
  intervals = 40L,
  group = NULL,
  group_intervals = 3L,
  show_conf_int = TRUE,
  show_rug = TRUE,
  n = NULL,
  prop = 0.01,
  cols = "tol",
  ylim = NULL,
  radial_wd = TRUE,
  ncol = NULL,
  nrow = NULL,
  ...,
  .plot = TRUE,
  .plot_engine = NULL,
  .progress = rlang::is_interactive()
)

Arguments

dw: A deweather model created with build_dw_model().
vars: Character. The name of the variable(s) to plot. Must be one of the variables used in the model. If NULL, all variables will be plotted in order of importance.
intervals: The number of points for the partial dependence profile.
group: Optional grouping variable to show separate profiles for different levels of another predictor. Must be one of the variables used in the model. Default is NULL (no grouping).
group_intervals: The number of bins when the group variable is numeric.
show_conf_int: Should the bootstrapped 95% confidence interval be shown? In plot_dw_partial_1d() these are shown using transparent ribbons (for numeric variables) and rectangles (for categorical variables).
show_rug: Should a 'rug' (ticks along the x-axis) be shown which identifies the exact intervals for each parameter?
n: The number of observations to use for calculating the partial dependence profile. If NULL (default), uses prop to determine the sample size.
prop: The proportion of input data to use for calculating the partial dependence profile, between 0 and 1. Default is 0.01 (1% of input data). Ignored if n is specified.
cols: Colours to use for plotting. See openair::openColours().
ylim: The limits of the y-axis. The default, NULL, allows each partial dependence panel to have its own y-axis scale.
radial_wd: Should the "wd" (wind direction) variable be plotted on a radial axis? This can enhance interpretability, but makes it inconsistent with other variables which are plotted on cartesian coordinates. Defaults to TRUE.
ncol, nrow: When more than one vars is defined, ncol and nrow define the dimensions of the grid to create. Setting both to be NULL creates a roughly square grid.
...: Not currently used.
.plot: When FALSE, return a data.frame of plot data instead of a plot.
.plot_engine: The plotting engine to use. One of "ggplot2", which returns a static plot, or "plotly", which returns a dynamic HTML plot.
.progress: Show a progress bar? Defaults to TRUE in interactive sessions.

Value

A ggplot2 object showing the partial dependence plot. If multiple vars are specified, a patchwork assembly of plots will be returned. If plot = FALSE, a named list of plot data will be returned instead.

Parallel Processing

This function supports parallel processing using the {mirai} package. You will likely find that the performance of this function increases if "daemons" are set. The greatest benefits will be seen if you spawn as many daemons as you have cores on your machine, although one fewer than the available cores is often a good rule of thumb.

# set workers - once per session
mirai::daemons(4)

# run your function as normal
tune_dw_model(aqroadside, "no2", tree_depth = c(5, 10))

Plotting Engines

deweather offers different plotting engines for different purposes. At the moment, two plotting engines are supported:

"ggplot2", for static plotting. This engine produces plots which can be easily saved to a .png, .svg, or other 'static' file format. To save a ggplot2 plot, it is recommended to use the ggplot2::ggsave() function.
"plotly", for dynamic plotting. This engine produces HTML plots which are suitable for embedding into quarto or rmarkdown documents, or for use in shiny applications. These can be saved using functions like htmlwidgets::saveWidget().

The plotting engine is defined using the .plot_engine argument in any plot_* function in deweather.

# use default
plot_dw_importance(dw)

# set to ggplot2 (static)
plot_dw_importance(dw, .plot_engine = "ggplot2")

# set to plotly (HTML)
plot_dw_importance(dw, .plot_engine = "plotly")

When .plot_engine is not set, the engine defaults to "ggplot2". However, this option can be overridden by using the deweather.plot_engine global option.

# set once per session
options("deweather.plot_engine" = "plotly")

# now defaults to "plotly" over "ggplot2"
plot_dw_importance(dw)

Note that not all arguments in a function may apply to all plotting engines. For example, hexagonal binning in plot_tdw_testing_scatter() is supported in ggplot2 but not in plotly at time of writing.

Author

Jack Davison

Examples

if (FALSE) { # \dontrun{
dw <- build_dw_model(aqroadside, "no2")
plot_dw_partial_1d(dw)
} # }