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Aesthetic changes to plots #427

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2dbd354
Aesthetic changes to plots
julianwuth Feb 19, 2026
f9b9980
Transposed prior and posterior prob table
julianwuth Feb 19, 2026
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151 changes: 108 additions & 43 deletions R/bayesianProcessCapabilityStudies.R
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Original file line number Diff line number Diff line change
Expand Up @@ -327,6 +327,18 @@ bayesianProcessCapabilityStudies <- function(jaspResults, dataset, options) {
return(selectedMetrics)
}

.bpcsMetricToPlotmath <- function(metrics) {
lookup <- c(
"Cp" = "C[p]",
"CpU" = "C[pU]",
"CpL" = "C[pL]",
"Cpk" = "C[pk]",
"Cpc" = "C[pc]",
"Cpm" = "C[pm]"
)
unname(lookup[metrics])
}

.bpcsGetCustomAxisLimits <- function(options, base) {
keys <- c(paste0(base, "custom_x_", c("min", "max")), paste0(base, "custom_y_", c("min", "max")))
values <- lapply(keys, function(k) options[[k]])
Expand Down Expand Up @@ -384,7 +396,7 @@ bayesianProcessCapabilityStudies <- function(jaspResults, dataset, options) {
return()

table <- createJaspTable(title = gettext("Prior and Posterior Probabilities"), position = position)
table$dependOn(c("priorPosteriorTable", .bpcsDefaultDeps(), .bpcsProcessCriteriaDeps()))
table$dependOn(c("priorPosteriorTable", "transposePiorPosteriorTable", .bpcsDefaultDeps(), .bpcsProcessCriteriaDeps()))
jaspResults[["bpcsPriorPosteriorTable"]] <- table

if (!.bpcsIsReady(options) || is.null(fit))
Expand All @@ -411,49 +423,81 @@ bayesianProcessCapabilityStudies <- function(jaspResults, dataset, options) {
priorSum <- priorSum[match(selectedMetrics, priorSum$metric), , drop = FALSE]
}

table$addColumnInfo(name = "metric", title = gettext("Measure"), type = "string")
transposed <- isTRUE(options[["transposePiorPosteriorTable"]])

regionTitles <- .bpcsFormatIntervalBounds(intBounds, intNames)

for (i in seq_along(intNames)) {
regionTitle <- regionTitles[i]

if (hasProperPriors) {
table$addColumnInfo(name = paste0("prior_", i), title = gettext("Prior"), type = "number", overtitle = regionTitle)
}
table$addColumnInfo(name = paste0("post_", i), title = gettext("Posterior"), type = "number", overtitle = regionTitle)
if (hasProperPriors) {
table$addColumnInfo(name = paste0("bf_", i), title = gettext("BF"), type = "number", overtitle = regionTitle)
}
# Compute posterior (and optionally prior + BF) probabilities per metric and interval
postMatrix <- as.matrix(postSum[, -1, drop = FALSE]) # rows = metrics, cols = intervals
priorMatrix <- bfMatrix <- NULL
if (hasProperPriors) {
priorMatrix <- as.matrix(priorSum[, -1, drop = FALSE])

odds_prior <- priorMatrix / (1 - priorMatrix)
odds_post <- postMatrix / (1 - postMatrix)
odds_prior[priorMatrix >= 1] <- Inf
odds_post[postMatrix >= 1] <- Inf
odds_prior[priorMatrix <= 0] <- 0
odds_post[postMatrix <= 0] <- 0

bfMatrix <- odds_post / odds_prior
bfMatrix[odds_prior == 0 & odds_post == 0] <- 1
bfMatrix[odds_prior == 0 & odds_post > 0] <- Inf
}

df <- data.frame(metric = selectedMetrics)

for (i in seq_along(intNames)) {
p_post <- postSum[[i + 1]]
df[[paste0("post_", i)]] <- p_post

if (hasProperPriors) {
p_prior <- priorSum[[i + 1]]

odds_prior <- p_prior / (1 - p_prior)
odds_post <- p_post / (1 - p_post)
if (transposed) {
# Transposed layout: rows = metric x interval, columns = Prior, Posterior, BF
table$addColumnInfo(name = "metric", title = gettext("Measure"), type = "string")
table$addColumnInfo(name = "interval", title = gettext("Classification"), type = "string")
if (hasProperPriors)
table$addColumnInfo(name = "prior", title = gettext("Prior"), type = "number")
table$addColumnInfo(name = "post", title = gettext("Posterior"), type = "number")
if (hasProperPriors)
table$addColumnInfo(name = "bf", title = gettext("BF"), type = "number")

rows <- list()
for (m in seq_along(selectedMetrics)) {
for (i in seq_along(intNames)) {
row <- list(
metric = if (i == 1L) selectedMetrics[m] else "",
interval = regionTitles[i],
post = postMatrix[m, i]
)
if (hasProperPriors) {
row$prior <- priorMatrix[m, i]
row$bf <- bfMatrix[m, i]
}
rows[[length(rows) + 1L]] <- row
}
}

odds_prior[p_prior >= 1] <- Inf
odds_post[p_post >= 1] <- Inf
odds_prior[p_prior <= 0] <- 0
odds_post[p_post <= 0] <- 0
df <- do.call(rbind.data.frame, c(rows, stringsAsFactors = FALSE))
table$setData(df)

bf <- odds_post / odds_prior
bf[odds_prior == 0 & odds_post == 0] <- 1
bf[odds_prior == 0 & odds_post > 0] <- Inf
} else {
# Default layout: rows = metrics, columns grouped by interval
table$addColumnInfo(name = "metric", title = gettext("Measure"), type = "string")

for (i in seq_along(intNames)) {
regionTitle <- regionTitles[i]
if (hasProperPriors)
table$addColumnInfo(name = paste0("prior_", i), title = gettext("Prior"), type = "number", overtitle = regionTitle)
table$addColumnInfo(name = paste0("post_", i), title = gettext("Posterior"), type = "number", overtitle = regionTitle)
if (hasProperPriors)
table$addColumnInfo(name = paste0("bf_", i), title = gettext("BF"), type = "number", overtitle = regionTitle)
}

df[[paste0("prior_", i)]] <- p_prior
df[[paste0("bf_", i)]] <- bf
df <- data.frame(metric = selectedMetrics)
for (i in seq_along(intNames)) {
df[[paste0("post_", i)]] <- postMatrix[, i]
if (hasProperPriors) {
df[[paste0("prior_", i)]] <- priorMatrix[, i]
df[[paste0("bf_", i)]] <- bfMatrix[, i]
}
}
}

table$setData(df)
table$setData(df)
}

if (!hasProperPriors) {
table$addFootnote(gettext("Prior probabilities and Bayes factors are not available for improper priors. Specify proper priors in the Prior Settings to enable these columns."))
Expand All @@ -480,7 +524,7 @@ bayesianProcessCapabilityStudies <- function(jaspResults, dataset, options) {

jaspPlt <- createJaspPlot(
title = if (isPost) gettext("Posterior Distribution") else gettext("Prior Distribution"),
width = 400 * (if (singlePanel) 1 else 3),
width = 400 * (if (singlePanel) 1.5 else 3),
height = 400 * (if (singlePanel) 1 else 2),
position = position,
dependencies = jaspDeps(
Expand Down Expand Up @@ -523,7 +567,7 @@ bayesianProcessCapabilityStudies <- function(jaspResults, dataset, options) {
showRegions <- isTRUE(options[[paste0(base, "ShowRegions")]])
regionCutoffs <- unlist(options[paste0("interval", 1:4)], use.names = FALSE)

jaspPlt$plotObject <- qc::plot_density(
plt <- qc::plot_density(
summaryObject,
what = selectedMetrics,
point_estimate = if (options[[paste0(base, "IndividualPointEstimate")]]) options[[paste0(base, "IndividualPointEstimateType")]] else "none",
Expand All @@ -545,6 +589,18 @@ bayesianProcessCapabilityStudies <- function(jaspResults, dataset, options) {
jaspGraphs::geom_rangeframe() +
jaspGraphs::themeJaspRaw()

if (length(selectedMetrics) == 1L) {
plt <- plt + ggplot2::labs(x = parse(text = .bpcsMetricToPlotmath(selectedMetrics)))
} else if (!singlePanel) {
metricLabeller <- ggplot2::as_labeller(
setNames(.bpcsMetricToPlotmath(selectedMetrics), selectedMetrics),
default = ggplot2::label_parsed
)
plt <- plt + ggplot2::facet_wrap(~metric, labeller = metricLabeller)
}

jaspPlt$plotObject <- plt


}
}, error = function(e) {
Expand Down Expand Up @@ -612,7 +668,7 @@ bayesianProcessCapabilityStudies <- function(jaspResults, dataset, options) {
plts <- lapply(seq_len(nrow(intervalSummary)), function(i) {
jaspGraphs::plotPieChart(
unlist(intervalSummary[i, -1]), groups, legendName = NULL, legendColors = legendColors
) + ggplot2::ggtitle(intervalSummary$metric[i])
) + ggplot2::ggtitle(parse(text = .bpcsMetricToPlotmath(intervalSummary$metric[i])))
})
return(patchwork::wrap_plots(plts) + patchwork::plot_layout(nrow = 2, guides = "collect"))
}
Expand All @@ -625,7 +681,9 @@ bayesianProcessCapabilityStudies <- function(jaspResults, dataset, options) {
return()

w <- 400
plt <- createJaspPlot(title = gettext("Sequential Analysis Point Estimate"), width = 3*w, height = 2*w,
nSelectedMetrics <- length(.bpcsGetSelectedMetrics(options))
singleMetric <- nSelectedMetrics <= 1L
plt <- createJaspPlot(title = gettext("Sequential Analysis Point Estimate"), width = if (singleMetric) 1.5*w else 3*w, height = if (singleMetric) w else 2*w,
position = position,
dependencies = jaspDeps(c(
.bpcsDefaultDeps(),
Expand Down Expand Up @@ -664,7 +722,9 @@ bayesianProcessCapabilityStudies <- function(jaspResults, dataset, options) {
return()

w <- 400
plt <- createJaspPlot(title = gettext("Sequential Analysis Interval Estimate"), width = 3*w, height = 2*w,
nSelectedMetrics <- length(.bpcsGetSelectedMetrics(options))
singleMetric <- nSelectedMetrics <= 1L
plt <- createJaspPlot(title = gettext("Sequential Analysis Interval Estimate"), width = if (singleMetric) 1.5*w else 3*w, height = if (singleMetric) w else 2*w,
position = position,
dependencies = jaspDeps(c(
.bpcsDefaultDeps(),
Expand Down Expand Up @@ -865,6 +925,11 @@ bayesianProcessCapabilityStudies <- function(jaspResults, dataset, options) {
upper = as.vector(estimates[, "upper", ]),
)
tb <- tb[tb$metric %in% selectedMetrics, , drop = FALSE]
metricExpressions <- parse(text = .bpcsMetricToPlotmath(as.character(unique(tb$metric))))
metricLabeller <- ggplot2::as_labeller(
setNames(.bpcsMetricToPlotmath(selectedMetrics), selectedMetrics),
default = ggplot2::label_parsed
)
if (length(selectedMetrics) == 1L)
single_panel <- TRUE

Expand Down Expand Up @@ -1050,19 +1115,19 @@ bayesianProcessCapabilityStudies <- function(jaspResults, dataset, options) {
} else if (axes == "automatic" || axes == "free") {
scale_facet <- ggh4x::facetted_pos_scales(y = y_breaks_per_scale)
}
facet <- ggplot2::facet_wrap(~metric, scales = scales)
facet <- ggplot2::facet_wrap(~metric, scales = scales, labeller = metricLabeller)
}

ggplot2::ggplot(tb, ggplot2::aes(x = .data$n, y = .data$mean, group = .data$metric,
color = .data$metric, fill = .data$metric)) +
ggplot2::scale_color_manual(values = .bpcsPalette(values = unique(tb$metric), colorScheme = colorScheme, single_panel = single_panel)) +
ggplot2::scale_fill_manual(values = .bpcsPalette(values = unique(tb$metric), colorScheme = colorScheme, single_panel = single_panel)) +
ggplot2::scale_color_manual(values = .bpcsPalette(values = unique(tb$metric), colorScheme = colorScheme, single_panel = single_panel), labels = metricExpressions) +
ggplot2::scale_fill_manual(values = .bpcsPalette(values = unique(tb$metric), colorScheme = colorScheme, single_panel = single_panel), labels = metricExpressions) +
gridLinesLayer +
ribbon +
ggplot2::geom_line(linewidth = 1) +
facet + scale_facet + scale_x +
ggplot2::labs(
x = gettext("Number of observations"),
x = gettext("Observation"),
y = y_title,
color = gettext("Metric"),
fill = gettext("Metric")
Expand Down
9 changes: 9 additions & 0 deletions inst/qml/bayesianProcessCapabilityStudies.qml
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Original file line number Diff line number Diff line change
Expand Up @@ -274,8 +274,17 @@ Form
CheckBox
{
name: "priorPosteriorTable"
id: priorPosteriorTable
label: qsTr("Prior and posterior probabilities table")
info: qsTr("Show the prior and posterior probabilities, along with the Bayes factor, for the intervals. This table is only available when proper priors are specified.")

CheckBox
{
enabled: priorPosteriorTable.checked
name: "transposePiorPosteriorTable"
label: qsTr("Transpose table")
info: qsTr("Show the prior and posterior probabilities table with intervals in the rows and probabilities and Bayes factors in the columns.")
}
}

Common.PlotLayout
Expand Down
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