Developer function for plotting results from Evaluator. — plot_eval

A helper function for developing new Visualizer plotting functions that plot the summarized evaluation results as a boxplot, scatter plot, line plot, or bar plot with or without 1 SD error bars/ribbons. This function accepts either (1) the name(s) of the Evaluator(s) to plot (eval_names) or (2) a tibble containing the summarized evaluation results to plot (plot_data).

Usage

plot_eval_constructor(
  eval_results = NULL,
  eval_names = NULL,
  plot_data = NULL,
  eval_id = NULL,
  vary_params = NULL,
  show = c("boxplot", "point", "line", "bar", "errorbar", "ribbon", "violin"),
  x_str = "auto",
  y_str = "auto",
  y_boxplot_str = "auto",
  err_sd_str = "auto",
  color_str = "auto",
  linetype_str = "auto",
  facet_formula = NULL,
  facet_type = c("grid", "wrap"),
  plot_by = "auto",
  add_ggplot_layers = NULL,
  boxplot_args = NULL,
  point_args = NULL,
  line_args = NULL,
  bar_args = NULL,
  errorbar_args = NULL,
  ribbon_args = NULL,
  violin_args = NULL,
  facet_args = NULL,
  interactive = FALSE,
  ...
)

Arguments

eval_results: A list of result tibbles, as returned by evaluate_experiment().
eval_names: (Optional) A character vector or string, specifying the name(s) of Evaluator(s) to plot. If multiple Evaluators are specified, these result tibbles are concatenated along the rows. Must provide either eval_names or plot_data.
plot_data: (Optional) Tibble (typically from the output of eval_summary_constructor) containing the summarized evaluation results to plot. Must provide either eval_names or plot_data. If eval_names is provided, this argument is ignored.
eval_id: (Optional) Character string. ID used as the suffix for naming columns in evaluation results tibble. If eval_summary_constructor() was used to construct the Evaluator, this should be the same as the eval_id argument in eval_summary_constructor(). Only used to assign default (i.e., "auto") aesthetics in ggplot.
vary_params: A vector of DGP or Method parameter names that are varied across in the Experiment.
show: Character vector with elements being one of "boxplot", "point", "line", "bar", "errorbar", "ribbon", "violin", indicating what plot layer(s) to construct.
x_str: (Optional) Name of column in data frame to plot on the x-axis. Default "auto" chooses what to plot on the x-axis automatically.
y_str: (Optional) Name of column in data frame to plot on the y-axis if show is anything but "boxplot". Default "auto" chooses what to plot on the y-axis automatically.
y_boxplot_str: (Optional) Name of column in data frame to plot on the y-axis if show is "boxplot". Default "auto" chooses what to plot on the y-axis automatically.
err_sd_str: (Optional) Name of column in data frame containing the standard deviations of y_str. Used for plotting the errorbar and ribbon ggplot layers. Default "auto" chooses what column to use for the standard deviations automatically.
color_str: (Optional) Name of column in data frame to use for the color and fill aesthetics when plotting. Default "auto" chooses what to use for the color and fill aesthetics automatically. Use NULL to avoid adding any color and fill aesthetic.
linetype_str: (Optional) Name of column in data frame to use for the linetype aesthetic when plotting. Used only when show = "line". Default "auto" chooses what to use for the linetype aesthetic automatically. Use NULL to avoid adding any linetype aesthetic.
facet_formula: (Optional) Formula for ggplot2::facet_wrap() or ggplot2::facet_grid() if need be.
facet_type: One of "grid" or "wrap" specifying whether to use ggplot2::facet_wrap() or ggplot2::facet_grid() if need be.
plot_by: (Optional) Name of column in eval_tib to use for subsetting data and creating different plots for each unique value. Default "auto" chooses what column to use for the subsetting automatically. Use NULL to avoid creating multiple plots.
add_ggplot_layers: List of additional layers to add to a ggplot object via +.
boxplot_args: (Optional) Additional arguments to pass into ggplot2::geom_boxplot().
point_args: (Optional) Additional arguments to pass into ggplot2::geom_point().
line_args: (Optional) Additional arguments to pass into ggplot2::geom_line().
bar_args: (Optional) Additional arguments to pass into ggplot2::geom_bar().
errorbar_args: (Optional) Additional arguments to pass into ggplot2::geom_errorbar().
ribbon_args: (Optional) Additional arguments to pass into ggplot2::geom_ribbon().
violin_args: (Optional) Additional arguments to pass into ggplot2::geom_violin().
facet_args: (Optional) Additional arguments to pass into ggplot2::facet_grid() or ggplot2::facet_wrap().
interactive: Logical. If TRUE, returns interactive plotly plots. If FALSE, returns static ggplot plots.
...: Not used.

Value

If interactive = TRUE, returns a plotly object if plot_by is NULL and a list of plotly objects if plot_by is not NULL. If interactive = FALSE, returns a ggplot object if plot_by is NULL and a list of ggplot objects if plot_by is not NULL.

Examples

# generate example fit results data
fit_results <- tibble::tibble(
  .rep = rep(1:2, times = 2),
  .dgp_name = c("DGP1", "DGP1", "DGP2", "DGP2"),
  .method_name = c("Method"),
  # true response
  y = lapply(1:4, FUN = function(x) rnorm(100)),
  # predicted response
  predictions = lapply(1:4, FUN = function(x) rnorm(100))
)

# generate example evaluation results data
eval_results <- list(
  `Prediction Errors` = summarize_pred_err(
    fit_results = fit_results,
    truth_col = "y",
    estimate_col = "predictions",
    eval_id = "pred_err"
  )
)

# create plot using name of Evaluator
plt <- plot_eval_constructor(eval_results = eval_results,
                             eval_name = "Prediction Errors",
                             eval_id = "pred_err",
                             show = c("point", "errorbar"),
                             facet_formula = ~ .metric)
# create plot using pre-computed evaluation results
plt <- plot_eval_constructor(plot_data = eval_results[["Prediction Errors"]],
                             eval_id = "pred_err",
                             show = c("point", "errorbar"),
                             facet_formula = ~ .metric)
# can customize plots using additional arguments or ggplot2::`+`
plt <- plot_eval_constructor(eval_results = eval_results,
                             eval_name = "Prediction Errors",
                             eval_id = "pred_err",
                             show = c("point", "errorbar"),
                             facet_formula = ~ .metric,
                             facet_type = "wrap",
                             errorbar_args = list(width = 0.5),
                             facet_args = list(scales = "free")) +
  ggplot2::labs(y = "Mean Prediction Error")
# can return interactive plotly plot
plt <- plot_eval_constructor(eval_results = eval_results,
                             eval_name = "Prediction Errors",
                             eval_id = "pred_err",
                             show = c("point", "errorbar"),
                             facet_formula = ~ .metric,
                             interactive = TRUE)