View source: R/visualizer-lib-utils.R
| plot_fit_constructor | R Documentation |
Experiment fit.A helper function for developing new Visualizer plotting
functions that plot results from particular replicate(s) in the
Experiment fit. This function will construct one plot for each
row in the Experiment's fit_results from the specified
replicates.
plot_fit_constructor(
fit_results,
vary_params = NULL,
reps = 1,
plot_fun,
interactive = FALSE,
...
)
fit_results |
A tibble, as returned by |
vary_params |
A vector of |
reps |
Vector of replicates from which to plot results. |
plot_fun |
The plotting function, which takes in the arguments
|
interactive |
Logical. If |
... |
Additional arguments to pass to |
If interactive = TRUE, returns a plotly object or
list of plotly objects if there are multiple replicates, DGPs, or
Methods to plot. If interactive = FALSE, returns a ggplot
object or list of ggplot objects if there are multiple replicates,
DGPs, or Methods to plot.
# 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))
)
# function to plot scatter plot of y vs predictions
plot_fun <- function(fit_results, vary_params = NULL) {
plt <- fit_results |>
tidyr::unnest(c("y", "predictions")) |>
ggplot2::ggplot() +
ggplot2::aes(x = y, y = predictions) +
ggplot2::geom_point() +
ggplot2::labs(title = sprintf("DGP: %s | Method: %s | Rep: %s",
fit_results$.dgp_name,
fit_results$.method_name,
fit_results$.rep))
return(plt)
}
# returns the scatter plot for each (DGP, Method) combination from rep 1
plt <- plot_fit_constructor(fit_results, reps = 1, plot_fun = plot_fun)
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