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Forward bounds argument #405

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Forward bounds argument #405

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8c69b5d
Don't update SVGs
VisruthSK Dec 8, 2025
f583673
Merge pull request #404 from stan-dev/master
VisruthSK Dec 26, 2025
e443a01
Documented
VisruthSK Dec 26, 2025
1602181
Added bounds to another function
VisruthSK Dec 27, 2025
a59f841
add a few visual tests
jgabry Dec 29, 2025
bda7a93
suppress warnings about bounds in tests
jgabry Dec 29, 2025
f8c6777
Removed bounds from ppc_loo_pit_overlay()
VisruthSK Dec 30, 2025
c14f39f
Add tests for invalid bounds in density plotting functions (#406)
Copilot Dec 30, 2025
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15 changes: 15 additions & 0 deletions R/helpers-shared.R
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Expand Up @@ -44,3 +44,18 @@ check_ignored_arguments <- function(..., ok_args = character()) {
}
}
}

#' Validate bounds passed to stat_density/geom_density wrappers
#' @noRd
validate_density_bounds <- function(bounds) {
if (is.null(bounds)) {
return(NULL)
}
if (!is.numeric(bounds) || length(bounds) != 2 || anyNA(bounds)) {
abort("`bounds` must be a numeric vector of length 2.")
}
if (bounds[1] >= bounds[2]) {
abort("`bounds` must satisfy bounds[1] < bounds[2].")
}
bounds
}
Comment on lines +50 to +61
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Copilot AI Dec 29, 2025

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The new validate_density_bounds function lacks test coverage. While tests verify that the bounds argument can be passed to various plotting functions (e.g., in test-ppc-distributions.R, test-mcmc-distributions.R), there are no tests that validate the behavior of validate_density_bounds itself. Consider adding tests to test-helpers-shared.R to verify that the function correctly handles invalid inputs such as: non-numeric values, vectors with length != 2, vectors with NA values, and cases where bounds[1] >= bounds[2].

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@jgabry jgabry Dec 29, 2025

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You don't necessarily need to test the validate_density_bounds function itself, but it would be good to at least add a test where invalid bounds are passed to a plotting function.

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@VisruthSK VisruthSK Dec 30, 2025

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@copilot Implement Jonah's suggestion by writing a test in the same style as the existing tests where a plotting function receives invalid bounds. Test all branches of the validate_density_bounds function

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@VisruthSK VisruthSK Dec 30, 2025

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I'm not sure if that works, but I'll write/generate a test either way.

64 changes: 39 additions & 25 deletions R/mcmc-distributions.R
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Original file line number Diff line number Diff line change
Expand Up @@ -151,6 +151,7 @@ mcmc_dens <- function(
adjust = NULL,
kernel = NULL,
n_dens = NULL,
bounds = NULL,
alpha = 1
) {
check_ignored_arguments(...)
Expand All @@ -166,6 +167,7 @@ mcmc_dens <- function(
adjust = adjust,
kernel = kernel,
n_dens = n_dens,
bounds = bounds,
alpha = alpha,
...
)
Expand Down Expand Up @@ -216,7 +218,8 @@ mcmc_dens_overlay <- function(
bw = NULL,
adjust = NULL,
kernel = NULL,
n_dens = NULL
n_dens = NULL,
bounds = NULL
) {
check_ignored_arguments(...)
.mcmc_dens(
Expand All @@ -232,6 +235,7 @@ mcmc_dens_overlay <- function(
adjust = adjust,
kernel = kernel,
n_dens = n_dens,
bounds = bounds,
...
)
}
Expand All @@ -250,7 +254,8 @@ mcmc_dens_chains <- function(
bw = NULL,
adjust = NULL,
kernel = NULL,
n_dens = NULL
n_dens = NULL,
bounds = NULL
) {
check_ignored_arguments(...)
data <- mcmc_dens_chains_data(
Expand All @@ -261,7 +266,8 @@ mcmc_dens_chains <- function(
bw = bw,
adjust = adjust,
kernel = kernel,
n_dens = n_dens
n_dens = n_dens,
bounds = bounds
)

n_chains <- length(unique(data$chain))
Expand Down Expand Up @@ -314,9 +320,11 @@ mcmc_dens_chains_data <- function(
transformations = list(),
...,
bw = NULL, adjust = NULL, kernel = NULL,
n_dens = NULL
n_dens = NULL,
bounds = NULL
) {
check_ignored_arguments(...)
bounds <- validate_density_bounds(bounds)

x %>%
prepare_mcmc_array(
Expand All @@ -329,7 +337,8 @@ mcmc_dens_chains_data <- function(
group_vars = c("Parameter", "Chain"),
value_var = "Value",
interval_width = 1,
bw = bw, adjust = adjust, kernel = kernel, n_dens = n_dens
bw = bw, adjust = adjust, kernel = kernel,
bounds = bounds, n_dens = n_dens
) %>%
mutate(Chain = factor(.data$Chain)) %>%
rlang::set_names(tolower) %>%
Expand Down Expand Up @@ -441,21 +450,23 @@ mcmc_violin <- function(
color_chains = FALSE,
geom = c("density", "violin"),
probs = c(0.1, 0.5, 0.9),
trim = FALSE,
alpha = 1,
bw = NULL,
adjust = NULL,
kernel = NULL,
n_dens = NULL,
...
) {
trim = FALSE,
alpha = 1,
bw = NULL,
adjust = NULL,
kernel = NULL,
n_dens = NULL,
bounds = NULL,
...
) {

bw <- bw %||% "nrd0"
adjust <- adjust %||% 1
kernel <- kernel %||% "gaussian"
n_dens <- n_dens %||% 1024
bw <- bw %||% "nrd0"
adjust <- adjust %||% 1
kernel <- kernel %||% "gaussian"
n_dens <- n_dens %||% 1024
bounds <- validate_density_bounds(bounds)

x <- prepare_mcmc_array(x, pars, regex_pars, transformations)
x <- prepare_mcmc_array(x, pars, regex_pars, transformations)
data <- melt_mcmc.mcmc_array(x)
data$Chain <- factor(data$Chain)
n_param <- num_params(data)
Expand All @@ -475,13 +486,16 @@ mcmc_violin <- function(
geom_args <- list(linewidth = 0.5, na.rm = TRUE, alpha = alpha)
if (violin) {
geom_args[["draw_quantiles"]] <- probs
} else {
geom_args[["trim"]] <- trim
geom_args[["bw"]] <- bw
geom_args[["adjust"]] <- adjust
geom_args[["kernel"]] <- kernel
geom_args[["n"]] <- n_dens
}
} else {
geom_args[["trim"]] <- trim
geom_args[["bw"]] <- bw
geom_args[["adjust"]] <- adjust
geom_args[["kernel"]] <- kernel
geom_args[["n"]] <- n_dens
if (!is.null(bounds)) {
geom_args[["bounds"]] <- bounds
}
}
if (by_chain) {
# aes_mapping[["color"]] <- ~ Chain
# aes_mapping[["group"]] <- ~ Chain
Expand Down
36 changes: 27 additions & 9 deletions R/mcmc-intervals.R
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Original file line number Diff line number Diff line change
Expand Up @@ -301,15 +301,17 @@ mcmc_areas <- function(x,
bw = NULL,
adjust = NULL,
kernel = NULL,
n_dens = NULL) {
n_dens = NULL,
bounds = NULL) {
check_ignored_arguments(...)
area_method <- match.arg(area_method)

data <- mcmc_areas_data(
x, pars, regex_pars, transformations,
prob = prob, prob_outer = prob_outer,
point_est = point_est, rhat = rhat,
bw = bw, adjust = adjust, kernel = kernel, n_dens = n_dens
bw = bw, adjust = adjust, kernel = kernel,
n_dens = n_dens, bounds = bounds
)
datas <- split(data, data$interval)

Expand Down Expand Up @@ -474,13 +476,14 @@ mcmc_areas_ridges <- function(x,
prob = 1,
border_size = NULL,
bw = NULL, adjust = NULL, kernel = NULL,
n_dens = NULL) {
n_dens = NULL,
bounds = NULL) {
check_ignored_arguments(...)
data <- mcmc_areas_ridges_data(x, pars = pars, regex_pars = regex_pars,
transformations = transformations,
prob = prob, prob_outer = prob_outer,
bw = bw, adjust = adjust, kernel = kernel,
n_dens = n_dens)
n_dens = n_dens, bounds = bounds)

datas <- data %>%
split(data$interval)
Expand Down Expand Up @@ -668,8 +671,10 @@ mcmc_areas_data <- function(x,
bw = NULL,
adjust = NULL,
kernel = NULL,
n_dens = NULL) {
n_dens = NULL,
bounds = NULL) {
probs <- check_interval_widths(prob, prob_outer)
bounds <- validate_density_bounds(bounds)

# First compute normal intervals so we know the width of the data, point
# estimates, and have prepared rhat values.
Expand Down Expand Up @@ -699,6 +704,7 @@ mcmc_areas_data <- function(x,
bw = bw,
adjust = adjust,
kernel = kernel,
bounds = bounds,
n_dens = n_dens) %>%
mutate(interval = "inner")

Expand All @@ -710,6 +716,7 @@ mcmc_areas_data <- function(x,
bw = bw,
adjust = adjust,
kernel = kernel,
bounds = bounds,
n_dens = n_dens) %>%
mutate(interval = "outer")

Expand Down Expand Up @@ -777,12 +784,14 @@ mcmc_areas_ridges_data <- function(x,
prob = 1,
bw = NULL,
adjust = NULL, kernel = NULL,
n_dens = NULL) {
n_dens = NULL,
bounds = NULL) {
check_ignored_arguments(...)
mcmc_areas_data(x, pars = pars, regex_pars = regex_pars,
transformations = transformations,
prob = prob, prob_outer = prob_outer, point_est = "none",
bw = bw, adjust = adjust, kernel = kernel, n_dens = n_dens)
bw = bw, adjust = adjust, kernel = kernel,
n_dens = n_dens, bounds = bounds)
}


Expand Down Expand Up @@ -841,15 +850,24 @@ compute_column_density <- function(df, group_vars, value_var, ...) {

# Given a vector of values, compute a density dataframe.
compute_interval_density <- function(x, interval_width = 1, n_dens = 1024,
bw = NULL, adjust = NULL, kernel = NULL) {
bw = NULL, adjust = NULL, kernel = NULL,
bounds = NULL) {
n_dens <- n_dens %||% 1024

tail_width <- (1 - interval_width) / 2
qs <- quantile(x, probs = c(tail_width, 1 - tail_width))
support <- range(qs)
if (!is.null(bounds)) {
support[1] <- max(bounds[1], support[1])
support[2] <- min(bounds[2], support[2])
if (!(support[1] < support[2])) {
support <- range(qs)
}
}

args <- c(
# can't be null
list(x = x, from = min(qs), to = max(qs), n = n_dens),
list(x = x, from = support[1], to = support[2], n = n_dens),
# might be null
bw = bw, adjust = adjust, kernel = kernel)

Expand Down
13 changes: 11 additions & 2 deletions R/ppc-distributions.R
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Original file line number Diff line number Diff line change
Expand Up @@ -165,8 +165,10 @@ ppc_dens_overlay <-
bw = "nrd0",
adjust = 1,
kernel = "gaussian",
bounds = NULL,
n_dens = 1024) {
check_ignored_arguments(...)
bounds <- validate_density_bounds(bounds)

data <- ppc_data(y, yrep)
ggplot(data, mapping = aes(x = .data$value)) +
Expand All @@ -179,6 +181,7 @@ ppc_dens_overlay <-
bw = bw,
adjust = adjust,
kernel = kernel,
bounds = bounds,
n = n_dens
) +
overlay_ppd_densities(
Expand All @@ -190,6 +193,7 @@ ppc_dens_overlay <-
bw = bw,
adjust = adjust,
kernel = kernel,
bounds = bounds,
n = n_dens
) +
scale_color_ppc() +
Expand All @@ -215,6 +219,7 @@ ppc_dens_overlay_grouped <- function(y,
bw = "nrd0",
adjust = 1,
kernel = "gaussian",
bounds = NULL,
n_dens = 1024) {
check_ignored_arguments(...)

Expand All @@ -228,6 +233,7 @@ ppc_dens_overlay_grouped <- function(y,
bw = bw,
adjust = adjust,
kernel = kernel,
bounds = bounds,
n_dens = n_dens
)
# Use + list(data) trick to replace the data in the plot. The layer-specific
Expand Down Expand Up @@ -335,8 +341,10 @@ ppc_dens <-
...,
trim = FALSE,
size = 0.5,
alpha = 1) {
alpha = 1,
bounds = NULL) {
check_ignored_arguments(...)
bounds <- validate_density_bounds(bounds)
data <- ppc_data(y, yrep)
ggplot(data, mapping = aes(
x = .data$value,
Expand All @@ -346,7 +354,8 @@ ppc_dens <-
geom_density(
linewidth = size,
alpha = alpha,
trim = trim
trim = trim,
bounds = bounds
) +
scale_fill_ppc() +
scale_color_ppc() +
Expand Down
3 changes: 2 additions & 1 deletion R/ppc-loo.R
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Original file line number Diff line number Diff line change
Expand Up @@ -141,7 +141,8 @@ NULL
#' calculated from the PIT values to the theoretical standard normal
#' quantiles.
#' @param trim Passed to [ggplot2::stat_density()].
#' @template args-density-controls
#' @param bw,adjust,kernel,n_dens Optional arguments passed to
#' [stats::density()] to override the defaults.
#' @param boundary_correction For `ppc_loo_pit_overlay()`, when set to `TRUE`
#' (the default) the function will compute boundary corrected density values
#' via convolution and a Gaussian filter, also known as the reflection method
Expand Down
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