use jaspgraphs in custom frequency plots

R/descriptives.R

@@ -2416,52 +2416,36 @@ DescriptivesInternal <- function(jaspResults, dataset, options) {
 }
 
 .descriptivesDensityPlotsFill <- function(container, data, plotName, axeName, position, options) {
-  data$split <- NULL
-
-  if (options[["densityPlotSeparate"]] != "") {
-
-    trans <- 1 - (options[["densityPlotTransparency"]] / 100)
-    p <- ggplot2::ggplot(data, ggplot2::aes(x = variable, fill = separator))
-    scale_fill <- jaspGraphs::scale_JASPfill_discrete(
-      palette = options[["colorPalette"]],
-      name = options[["densityPlotSeparate"]])
-    if (options[["densityPlotType"]] == "histogram" && (options[["customHistogramPosition"]] != "identity")) {
-      trans <- 1
-    }
-
-  } else {
-    p <- ggplot2::ggplot(data, ggplot2::aes(x = variable, fill = factor(1)))
-    scale_fill <- jaspGraphs::scale_JASPfill_discrete(palette = options[["colorPalette"]])
-    trans <- 1
-  }
-
+  jaspGraphs::graphOptions(palette = options[["colorPalette"]])
+
   densPlot <- createJaspPlot(title = plotName, width = 480, height = 320, position = position)
   if (options[["densityPlotSeparate"]] != "" && any(table(data$separator) == 1)) {
     densPlot$setError(gettext("Levels within variable require at least two or more data points!"))
-  } else {
-    # p <- p + ggplot2::geom_histogram(position = "identity", alpha = trans)
-    if (options[["densityPlotType"]] == "density") {
-      p <- p + ggplot2::geom_density(alpha = trans)
-      thisYlab = "Density"
-    } else if (options[["densityPlotType"]] == "histogram") {
-      p <- p + ggplot2::geom_histogram(position = options[["customHistogramPosition"]], alpha = trans)
-      thisYlab = "Frequency"
-    }
-
-    # Determine range of axes to generate pretty breaks
-    yRange <- ggplot2::ggplot_build(p)$layout$panel_scales_y[[1]]$range$range
-    xRange <- ggplot2::ggplot_build(p)$layout$panel_scales_x[[1]]$range$range
-    yBreaks <- jaspGraphs::getPrettyAxisBreaks(yRange)
-    xBreaks <- jaspGraphs::getPrettyAxisBreaks(xRange)
+  } else if (options[["densityPlotType"]] == "density") {
 
-    p <- p + ggplot2::scale_y_continuous(name = thisYlab, breaks = yBreaks, limits = range(yBreaks)) +
-      ggplot2::scale_x_continuous(name = axeName, breaks = xBreaks, limits = range(xBreaks)) +
-      scale_fill +
-      jaspGraphs::geom_rangeframe() +
-      jaspGraphs::themeJaspRaw(legend.position = if (options[["densityPlotSeparate"]] != "") "right" else "none")
+    densPlot$plotObject <- jaspGraphs::jaspHistogram(x = data[["variable"]],
+                                                     histogram = FALSE,  
+                                                     density = TRUE,
+                                                     densityColor = TRUE,
+                                                     densityShade = TRUE,
+                                                     densityShadeAlpha = 1 - (options[["densityPlotTransparency"]]/100),
+                                                     xName = axeName,
+                                                     groupingVariableName = options[["densityPlotSeparate"]],
+                                                     groupingVariable = data[["separator"]],
+                                                     histogramPosition = options[["customHistogramPosition"]])
 
-    densPlot$plotObject <- p
+
+  } else if (options[["densityPlotType"]] == "histogram") {
+
+    densPlot$plotObject <- jaspGraphs::jaspHistogram(x = data[["variable"]], 
+                                                     xName = axeName,
+                                                     groupingVariableName = options[["densityPlotSeparate"]],
+                                                     groupingVariable = data[["separator"]],
+                                                     histogramPosition = options[["customHistogramPosition"]])
+    if (options[["customHistogramPosition"]] == "identity")
+      densPlot$plotObject$layers[[1]]$aes_params$alpha <- 1 - (options[["densityPlotTransparency"]]/100)
   }
 
+
   container[[plotName]] <- densPlot
 }

inst/help/Descriptives.md

@@ -111,14 +111,17 @@ Descriptives allows the user to obtain basic descriptive statistics, histograms
 #### Likert plots
 - Displays a horizontally stacked bar chart showing the contribution of levels within a variable in percent. Order of levels depends on defined order in the JASP data table. A legend below the graph provides an overview of levels and their respective colors in the graph.
   - The y-axis represents the variables used, the x-axis represents the percentages. Percentage contribution of all lower-order (below the middle level) and higher-order (above the middle level) levels are displayed on their respective side of the graph.
-  - The graph displays percentages on the x-axis as positive in both directions. Reason for the chosen display (in two directions) is the graphs usefulness in survey research where levels often follow a likert based order (e.g., high - low, likely - unlikely, agreement - disagreement). Therefore, the graph contains a split between levels at their median.
+  - The graph displays percentages on the x-axis as positive in both directions. Reason for the chosen display (in two directions) is the graphs usefulness in survey research where levels often follow a Likert based order (e.g., high - low, likely - unlikely, agreement - disagreement). Therefore, the graph contains a split between levels at their median.
   - The number of variable levels determines the number of layers displayed. Layers represent the percentage distribution of the levels of the variable under investigation.
   - If the variables contain an uneven amount of levels, the middle level is displayed as a grey block in the middle of the stacked bar with its percentage contribution on top.
 - Available font sizes: normal, small, medium, large.
 
-#### Density plots
-- Diplays the distribution of a numeric variable. If other nominal or ordinal variables are included, different distributions representing different values of the other variable are displayed in the same plot.
-- The y-axis represents the probability density for the kernel density estimation (probability per unit on the x-axis), the x-axis represents the variables used.
+#### Frequency plots
+- Displays the distribution of a numeric variable by either a density or histogram plot. 
+	- Density: The y-axis represents the probability density for the kernel density estimation (probability per unit on the x-axis).
+	- Histogram: The y-axis represents the frequency
+		- When separate frequencies are specified, the bars can be combined in various ways: Stack (stacked), Identify (behind each other), Dodge (next to each other). 
+- The x-axis represents the variables used.
 - Appearance can be manipulated by adjusting color palette and transparency.
 
 #### Frequency Tables (nominal and ordinal variables)