For these plots, data sets made long with respect to several
y-axis variables and then plotted and faceted with
ggplot2::facet_wrap(). wrap_cont_cont is a general function used by
the others to create faceted plots of two continuous variables.
wrap_cont_time plots several continuous variables versus time.
wrap_res_time plots several different residuals (or NPDE) versus time.
wrap_eta_cont plots etas versus a continuous covariate. wrap_hist
creates a faceted histogram plot. wrap_cont_cat plots continuous versus
categorical data as a boxplot.
wrap_cont_cont( df, x, y, ..., fun = pm_scatter, title = NULL, scales = "free_y", ncol = NULL, use_labels = FALSE, label_fun = label_parse_label ) wrap_cont_time(df, ..., x = pm_axis_time()) wrap_res_time(df, ..., x = pm_axis_time()) wrap_eta_cont(df, x, y, scales = "fixed", ...) wrap_hist( df, x, title = NULL, scales = "free_x", ncol = NULL, use_labels = FALSE, label_fun = label_parse_label, ... ) wrap_dv_preds( df, ..., title = "Predicted {yname}", xname = "", scales = "fixed" ) wrap_cont_cat( df, x, y, ..., title = NULL, scales = "free_y", ncol = NULL, use_labels = FALSE, label_fun = label_parse_label )
| df | data frame to plot |
|---|---|
| x | x-axis data in |
| y | y-axis data in |
| ... | passed to |
| fun | the plotting function |
| title | a title to use for the axis with faceting groups |
| scales | passed to |
| ncol | passed to |
| use_labels | if |
| label_fun | labeller function; passed to |
| xname | placeholder |
The following functions are called (as fun) to make each wrapped plot
wrap_cont_cont calls pm_scatter()
wrap_cont_time calls y_time()
wrap_res_time calls res_time()
wrap_eta_cont calls eta_cont()
wrap_hist calls cont_hist()
wrap_cont_cat calls pm_box();
For all plots, both x and y should name numeric data columns with the
exception of wrap_cont_cat which expects x to name a categorical
data column (the data are sent to pm_box()).
When pm_box() is called by wrap_cont_cat, the shown argument will be
forced to the value FALSE.
For all plots, either x or y may contain multiple columns, but an error
will be generated if both x and y list multiple columns.