geom_node_plot: Draw plots at nodes
In ggparty: 'ggplot' Visualizations for the 'partykit' Package

Description Usage Arguments See Also Examples

View source: R/geom_node_plot.R

Additional component for a ggparty() that allows to create in each node a ggplot with its data. #'

geom_node_plot(plot_call = "ggplot", gglist = NULL, width = 1,
  height = 1, size = 1, ids = "terminal", scales = "fixed",
  nudge_x = 0, nudge_y = 0, shared_axis_labels = FALSE,
  shared_legend = TRUE, predict = NULL, predict_gpar = NULL,
  legend_separator = FALSE)

`plot_call`	Any function that generates a `ggplot2` object.
`gglist`	List of additional `gg` components. Columns of `data` of nodes can be mapped. Additionally `fitted_values` and `residuals` can be mapped if present in `party` of `ggparty()`
`width`	Expansion factor for viewport's width.
`height`	Expansion factor for viewport's height.
`size`	Expansion factor for viewport's size.
`ids`	Id's to plot. Numeric, "terminal", "inner" or "all". Defaults to "terminal".
`scales`	See `facet_wrap()`
`nudge_x, nudge_y`	Nudges node plot.
`shared_axis_labels`	If TRUE only one pair of axes labels is plotted in the terminal space. Only recommended if `ids` "terminal" or "all".
`shared_legend`	If `TRUE` one shared legend is plotted at the bottom of the tree.
`predict`	Character string specifying variable for which predictions should be plotted.
`predict_gpar`	Named list containing arguments to be passed to the `geom_line()` call of predicted values.
`legend_separator`	If `TRUE` line between legend and tree is drawn.

ggparty()

library(ggparty)

airq <- subset(airquality, !is.na(Ozone))
airct <- ctree(Ozone ~ ., data = airq)

ggparty(airct, horizontal = TRUE, terminal_space = 0.6) +
  geom_edge() +
  geom_edge_label() +
  geom_node_splitvar() +
  geom_node_plot(gglist = list(
    geom_density(aes(x = Ozone))),
    shared_axis_labels = TRUE)

#############################################################

## Plot with ggparty


## Demand for economics journals data
data("Journals", package = "AER")
Journals <- transform(Journals,
                      age = 2000 - foundingyear,
                      chars = charpp * pages)

## linear regression tree (OLS)
j_tree <- lmtree(log(subs) ~ log(price/citations) | price + citations +
                   age + chars + society, data = Journals, minsize = 10, verbose = TRUE)

pred_df <- get_predictions(j_tree, ids = "terminal", newdata =  function(x) {
  data.frame(
    citations = 1,
    price = exp(seq(from = min(x$`log(price/citations)`),
                    to = max(x$`log(price/citations)`),
                    length.out = 100)))
})

ggparty(j_tree, terminal_space = 0.8) +
  geom_edge() +
  geom_edge_label() +
  geom_node_splitvar() +
  geom_node_plot(gglist =
                   list(aes(x = `log(price/citations)`, y = `log(subs)`),
                        geom_point(),
                        geom_line(data = pred_df,
                                  aes(x = log(price/citations),
                                      y = prediction),
                                  col = "red")))