Creates either coordinated heatmaps of yield and economic losses or a regression-style visualization from an object returned by `simulate_losses()`.
Usage
plot_losses(
data,
x,
type = c("heatmap", "regression"),
y = "att_yield",
yield_loss = "yield_loss",
economic_loss = "econ_loss",
reg_y = "ap_yield",
att_yield = NULL,
facet = NULL,
plots = c("yield", "economic"),
ncol = NULL,
nrow = NULL,
facet_ncol = 4L,
facet_nrow = NULL,
yield_fill_scale = NULL,
economic_fill_scale = NULL,
yield_fill_label = expression(bold(kg ~ ha^{
-1
})),
economic_fill_label = expression(bold(USD ~ ha^{
-1
})),
x_breaks = NULL,
y_breaks = NULL,
x_expand = c(0.02, 0.02),
y_expand = c(0.02, 0.02),
x_limits = NULL,
y_limits = NULL,
x_label = NULL,
y_label = "Attainable yield (kg/ha)",
reg_y_label = NULL,
yield_title = NULL,
economic_title = NULL,
show_yield_x_text = FALSE,
show_yield_x_label = FALSE,
show_economic_strips = FALSE,
raster_interpolate = FALSE,
raster_args = list(),
yield_raster_args = list(),
economic_raster_args = list(),
theme = NULL,
base_size = 10,
text_face = "bold",
axis_title_size = 12,
strip_background = ggplot2::element_rect(fill = "white", colour = "black"),
legend_position = "right",
tag_levels = "a",
tag_prefix = "(",
tag_suffix = ")",
tag_size = 12,
tag_face = "bold",
tag_position = c(0.01, 1.02),
collect_guides = FALSE,
yield_add = NULL,
economic_add = NULL,
combined_add = NULL,
...
)Arguments
- data
A non-empty data frame returned by `simulate_losses()`.
- x
Character scalar naming the variable displayed on the x-axis.
- type
Character scalar selecting `"heatmap"` or `"regression"`. Default is `"heatmap"`.
- y
Character scalar naming the y-axis variable for heatmaps. Default is `"att_yield"`, the shortened output name returned by the current `simulate_losses()`.
- yield_loss
Character scalar naming the yield-loss column used by the heatmap. Default is `"yield_loss"`.
- economic_loss
Character scalar naming the economic-loss column used by the heatmap. Default is `"econ_loss"`.
- reg_y
Character scalar naming the y-axis variable when `type = "regression"`. Default is `"ap_yield"`.
- att_yield
Optional finite numeric scalar used only with `type = "regression"`. When supplied, rows are filtered to the selected `att_yield` value before plotting.
- facet
Optional character vector naming scenario variables used as facets. For heatmaps, `facet_wrap()` is used as in the original function. For regression plots, the first facet variable is placed in rows and any remaining facet variables are placed in columns together with the automatically generated `yield_model` facet. Thus `facet = c("tmean", "wetness")` reproduces `facet_grid(rows = vars(tmean), cols = vars(wetness, yield_model))`.
- plots
Character vector selecting `"yield"`, `"economic"`, or both. Used only when `type = "heatmap"` and ignored for regression plots.
- ncol, nrow
Optional positive integers controlling the arrangement of the main heatmap plots. When both are `NULL` and both plots are requested, `nrow = 2` is used.
- facet_ncol, facet_nrow
Optional positive integers controlling the arrangement of heatmap facets.
- yield_fill_scale, economic_fill_scale
Optional continuous ggplot2 fill scales for heatmaps. When `NULL`, `ggplot2::scale_fill_viridis_b()` is used.
- yield_fill_label, economic_fill_label
Legend titles used by the default heatmap fill scales.
- x_breaks, y_breaks
Optional numeric axis breaks.
- x_expand, y_expand
Numeric expansion vectors passed to the axes.
- x_limits, y_limits
Optional numeric vectors of length two.
- x_label
Axis label. If `NULL`, a title-case label is generated from `x`.
- y_label
Y-axis label used for heatmaps.
- reg_y_label
Optional y-axis label used for regression plots. If `NULL`, a label is generated from `reg_y`, with informative defaults for standard `simulate_losses()` output columns.
- yield_title, economic_title
Optional heatmap panel titles.
- show_yield_x_text
Logical. Show x-axis text and ticks in the yield heatmap panel. Default is `FALSE`.
- show_yield_x_label
Logical. Show the x-axis title in the yield heatmap panel. Default is `FALSE`.
- show_economic_strips
Logical. Show facet strips in the economic heatmap panel. Default is `FALSE`.
- raster_interpolate
Logical passed to `ggplot2::geom_raster()`.
- raster_args
Named list of arguments passed to both raster layers.
- yield_raster_args, economic_raster_args
Named lists of panel-specific raster arguments. Panel-specific arguments override `raster_args` and `...`.
- theme
A ggplot2 theme. The default is `ggplot2::theme_bw(base_size = base_size)`.
- base_size
Base font size used by the default theme.
- text_face
Font face used for common heatmap text.
- axis_title_size
Axis-title size.
- strip_background
Facet-strip background in heatmaps and regression plots.
- legend_position
Legend position used in heatmaps. Regression plots intentionally suppress the legend, matching the requested display.
- tag_levels
Tag sequence passed to `patchwork::plot_annotation()`.
- tag_prefix, tag_suffix
Prefix and suffix for plot tags.
- tag_size, tag_face, tag_position
Appearance and position of plot tags.
- collect_guides
Logical. Collect compatible guides with patchwork.
- yield_add, economic_add
Optional ggplot2 component or list of components added to the corresponding heatmap panel.
- combined_add
Optional patchwork-compatible component added to the combined heatmap.
- ...
Additional named arguments passed to both heatmap raster layers.
Value
With `type = "regression"`, a `ggplot` object. With `type = "heatmap"`, a `patchwork` object when both heatmaps are requested or a `ggplot` object when only one is requested. Heatmap panels are retained as `"yield_plot"` and `"economic_plot"` attributes.
Details
With `type = "heatmap"` (default), the function preserves the original raster-plot workflow. Yield loss and economic loss can be displayed alone or together, and scenario variables can be shown as facets.
With `type = "regression"`, `plots` is not used and a single regression plot is returned. The response plotted on the y-axis is selected with `reg_y`. Optionally, `att_yield` filters the data to one attainable-yield scenario before plotting. A `yield_model` facet is generated automatically from `intercept_sim` and `slope_sim`.
Regression input is recognized as draw-level when a `sample` column is present. In that case, one `geom_smooth(se = FALSE)` curve is drawn for each sample using `group = sample` and `color = sample`. Otherwise, the data are treated as summary output. The central response is drawn as a solid black smooth and, when `<reg_y>_lower` and `<reg_y>_upper` are present, the lower and upper curves are drawn as dashed black smooths.
## Regression mode
For summary-style data, the function plots the central column selected by `reg_y`. If columns named `<reg_y>_lower` and `<reg_y>_upper` are available, they are plotted using dashed black `geom_smooth(se = FALSE)` curves. These bounds are used exactly as returned by `simulate_losses()`; no interval is recalculated by `plot_losses()`.
For draw-level data containing `sample`, the function plots one smooth curve per sample and maps both `group` and `color` to `sample`. No summary interval is calculated.
Examples
# Small simulated loss surface
losses <- expand.grid(
rain = seq(0, 12, by = 3),
att_yield = seq(4000, 8000, by = 1000)
)
losses$yield_loss <- with(
losses,
0.04 * rain * att_yield
)
losses$econ_loss <- losses$yield_loss * 0.25
# Heatmap of yield loss
loss_heatmap <- plot_losses(
losses,
x = "rain",
type = "heatmap",
plots = "yield",
x_breaks = seq(0, 12, by = 3),
y_breaks = seq(4000, 8000, by = 1000),
x_label = "Daily precipitation (mm)",
show_yield_x_text = TRUE,
show_yield_x_label = TRUE
)
# Summary-style regression data
regression_losses <- data.frame(
rain = rep(seq(0, 12, length.out = 20), 2),
att_yield = 6000,
intercept_sim = rep(c(0.95, 0.90), each = 20),
slope_sim = rep(c(-0.015, -0.025), each = 20)
)
regression_losses$ap_yield <- with(
regression_losses,
att_yield * (intercept_sim + slope_sim * rain)
)
regression_losses$ap_yield_lower <-
regression_losses$ap_yield - 150
regression_losses$ap_yield_upper <-
regression_losses$ap_yield + 150
summary_regression_plot <- plot_losses(
regression_losses,
x = "rain",
type = "regression",
reg_y = "ap_yield",
att_yield = 6000,
x_label = "Daily precipitation (mm)"
)
# Draw-level regression data
losses_samples <- expand.grid(
rain = seq(0, 12, length.out = 20),
sample = 1:3
)
losses_samples$att_yield <- 6000
losses_samples$intercept_sim <- 0.95
losses_samples$slope_sim <- -0.02
losses_samples$ap_yield <- with(
losses_samples,
att_yield *
(intercept_sim + slope_sim * rain) +
sample * 25
)
sample_regression_plot <- plot_losses(
losses_samples,
x = "rain",
type = "regression",
reg_y = "ap_yield",
att_yield = 6000,
x_label = "Daily precipitation (mm)"
)
stopifnot(
inherits(loss_heatmap, "ggplot"),
inherits(summary_regression_plot, "ggplot"),
inherits(sample_regression_plot, "ggplot")
)