[jaspQualityControl] Fix legend text cutoff and expand abbreviated x-axis labels in...

.claude/CLAUDE.md

@@ -231,3 +231,36 @@ After `runAnalysis()`, check:
 - Use `createJaspTable()`, `createJaspPlot()`, `createJaspHtml()` for output elements
 - Always set `$dependOn()` for proper caching and state management
 - Use containers for grouping related elements, state objects for reusing computed results
+
+## Container Environment (overrides Session Setup section above)
+
+This is a **headless Docker container**. There is no interactive user.
+
+### MANDATORY FIRST ACTION — R Session Connection
+
+Before doing ANYTHING else (before reading code, before exploring the repo),
+you MUST connect to the pre-started R session:
+
+1. Call `list_r_sessions` to discover available sessions.
+2. Call `select_r_session` to connect to the listed session.
+3. Only then proceed with the workflow.
+
+If `list_r_sessions` returns empty, the background R session failed to start.
+Fall back to Bash for R execution. Do NOT spend more than 2 turns debugging.
+
+This step is NOT optional. Without it, `btw_tool_run_r` will fail.
+
+### Other container rules
+
+- `session_startup.R` is NOT relevant here — ignore references to it.
+- Do NOT run any git commands (the outer orchestrator handles git).
+
+## Compact Instructions
+
+When context is compacted, preserve:
+- Current workflow stage (from /workspace/.openclaw-run/current_stage)
+- Implementation plan (from /workspace/.openclaw-run/PLAN.md)
+- The module name and original task description
+- What git changes have been made so far
+
+After compaction, re-read /workspace/.openclaw-run/RECOVERY.md to re-orient.

R/msaGaugeRR.R

@@ -687,14 +687,14 @@ msaGaugeRR <- function(jaspResults, dataset, options, ...) {
       return(list(study = c(round(studyVar/max(studyVar) * 100,2))[1], tol = c(round(studyVar / options[["toleranceValue"]] * 100,2))[1]))
 
     if (options[["varianceComponentsGraph"]]) {
-      plot <- createJaspPlot(title = gettext("Components of variation"), width = 850, height = 500)
+      plot <- createJaspPlot(title = gettext("Components of variation"), width = 950, height = 500)
       plot$dependOn(c("varianceComponentsGraph", "report"))
       plot$plotObject <- p
       anovaTables[['VarCompGraph']] <- plot
     }
   } else {
 
-    plot <- createJaspPlot(title = gettext("Components of variation"), width = 850, height = 500)
+    plot <- createJaspPlot(title = gettext("Components of variation"), width = 950, height = 500)
     plot$dependOn(c("gaugeVarCompGraph", "report"))
 
     anovaTables[['anovaTable1']] <- anovaTable1
@@ -904,7 +904,7 @@ msaGaugeRR <- function(jaspResults, dataset, options, ...) {
 }
 
 .gaugeVarCompGraph <- function(percentContributionValues, studyVariationValues, percentToleranceValues, Type3 = FALSE) {
-  sources <- gettext(c('Gauge r&R', 'Repeat', 'Reprod', 'Part-to-part'))
+  sources <- gettext(c('Total Gauge R&R', 'Repeatability', 'Reproducibility', 'Part-to-Part'))
   if (!all(is.na(percentToleranceValues))) {
     references <- gettextf(c('%% Contribution', '%% Study variation', '%% Tolerance'))
     values <- c(percentContributionValues, studyVariationValues, percentToleranceValues)