Plot the thermal tolerance landscape as a surface to rotate

Draws the thermal tolerance landscape from derive_tdt_ttl() in three dimensions: elapsed exposure time and constant temperature across the floor, and the posterior median survival as the height. The figure is interactive, so it can be rotated, zoomed and read by hovering, in a viewer, a browser or an HTML document.

Usage

plot_ttl_3d(x, row = NULL, interval = FALSE, grid = FALSE, time_unit = NULL)

Arguments

x

A list, the output of derive_tdt_ttl().

row

An optional single whole number, the setting of newdata to draw, as its row number among the settings. NULL (the default) draws the first, with a message when there are several.

interval

A single logical value, whether to add the lower and upper bounds of the credible interval as two faint surfaces around the median.

grid

A single logical value, or one or two whole numbers. TRUE draws a grid on the median surface, ten lines at constant temperature and ten at constant elapsed time. A number sets how many lines each way, and two numbers the lines at constant temperature and at constant time, e.g. c(5, 15). FALSE (the default) draws none.

time_unit

An optional character string giving the time unit for the axis label, e.g. "min".

Value

A plotly object.

Details

It needs the plotly package, and returns a plotly object rather than a ggplot, so it is refined with plotly's own functions (for example plotly::layout()), not with ggplot2 layers. A three-dimensional surface hides part of itself in a static figure; for print, plot_ttl() shows the same landscape as a map.

One setting of newdata is drawn at a time. Elapsed time is on a log scale, unless the times include zero.

Examples

if (FALSE) { # \dontrun{
# a model fitted to a small ramping trial: 20 individuals warmed from 20 to 35
# degrees over 60 minutes and checked every 10, in two trials (see fit_hazard())
path   <- data.frame(path_id = "A", time = c(0, 60), temp = c(20, 35))
checks <- data.frame(path_id = "A", time = seq(0, 60, by = 10))
ind    <- data.frame(id = 1:20, path_id = "A", event = 1, mass = runif(20, 8, 12),
                     trial = rep(c("a", "b"), each = 10),
                     t_upper = sample(seq(10, 60, 10), 20, replace = TRUE))
long   <- build_hazard_data(ind, path, "interval", covariates = c("mass", "trial"),
                            checks = checks)
fit    <- fit_hazard(long, "exp", dpar_formulas = list(loga = ~ 1 + mass))

tol <- derive_tdt_ttl(fit, newdata = data.frame(mass = c(8, 12)), t_ref = 60)
plot_ttl_3d(tol, row = 2, time_unit = "min")
} # }