update(raincloud-basic): pygal — fix orientation consistency

Fix cloud/rain orientation: cloud (half-violin) extends upward, rain (jittered points) falls downward. Updated spec to clarify absolute y-direction terms.

Author: MarkusNeusinger

plots/raincloud-basic/implementations/pygal.py

@@ -1,7 +1,7 @@
-""" pyplots.ai
+"""pyplots.ai
 raincloud-basic: Basic Raincloud Plot
-Library: pygal 3.1.0 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-25
+Library: pygal 3.1.0 | Python 3.14
+Quality: /100 | Updated: 2026-02-14
 """
 
 import numpy as np
@@ -24,28 +24,35 @@
 
 # Group colors - distinct for each category (colorblind-safe)
 group_colors = ["#306998", "#FFD43B", "#4CAF50"]
+box_color = "#000000"
 
-# Custom style for 4800x2700 px canvas - scaled up for visibility
+# Build color sequence matching series order:
+# Per group: cloud, rain, box, median, whisker_l, whisker_r, cap_l, cap_r
+series_colors = []
+for gc in group_colors:
+    series_colors.extend([gc, gc, box_color, box_color, box_color, box_color, box_color, box_color])
+
+# Custom style for 4800x2700 px canvas
 custom_style = Style(
     background="white",
     plot_background="white",
     foreground="#333333",
     foreground_strong="#333333",
     foreground_subtle="#999999",
     guide_stroke_color="#e8e8e8",
-    colors=tuple(group_colors * 3) + ("#222222",) * 30,
+    colors=tuple(series_colors),
     title_font_size=96,
     label_font_size=60,
     major_label_font_size=54,
     legend_font_size=54,
     value_font_size=42,
-    opacity=0.6,
-    opacity_hover=0.8,
+    tooltip_font_size=42,
+    opacity=0.75,
+    opacity_hover=0.9,
 )
 
 # Create HORIZONTAL XY chart for raincloud plot
 # X-axis = Reaction Time (value), Y-axis = Treatment Group (category)
-# HORIZONTAL orientation: cloud on TOP, boxplot centered, rain BELOW
 chart = pygal.XY(
     width=4800,
     height=2700,
@@ -54,8 +61,6 @@
     x_title="Reaction Time (ms)",
     y_title="Treatment Group",
     show_legend=False,
-    legend_at_bottom=False,
-    legend_box_size=0,
     stroke=True,
     fill=True,
     dots_size=0,
@@ -68,75 +73,63 @@
 )
 
 # Raincloud layout parameters (HORIZONTAL orientation)
-# Cloud on TOP (positive Y offset), boxplot centered, rain BELOW (negative Y offset)
-cloud_offset = 0.28  # Cloud extends UP (positive Y offset)
-rain_offset = -0.32  # Rain falls DOWN (negative Y offset)
+# Cloud extends UPWARD (positive Y offset from category line)
+# Rain falls DOWNWARD (negative Y offset from category line)
+cloud_height = 0.28
+rain_offset = -0.32
 n_kde_points = 80
-
-# Pre-compute all raincloud components
-cloud_data = []
-rain_data = []
-box_data = []
+box_width = 0.10
+cap_width = 0.06
 
 for i, (category, values) in enumerate(data.items()):
     center_y = i + 1  # Y position for this group (1, 2, 3)
     values = np.array(values)
 
-    # --- Half-Violin (cloud) - on TOP of boxplot ---
-    # Compute KDE using Silverman's rule
+    # --- Half-Violin (cloud) - extends UPWARD from category line ---
     n = len(values)
     std = np.std(values)
     iqr_val = np.percentile(values, 75) - np.percentile(values, 25)
     bandwidth = 0.9 * min(std, iqr_val / 1.34) * n ** (-0.2)
 
-    # Create range of x values (reaction times) for density
     x_min, x_max = values.min(), values.max()
     padding = (x_max - x_min) * 0.1
     x_range = np.linspace(x_min - padding, x_max + padding, n_kde_points)
 
-    # Gaussian kernel density estimation
+    # Gaussian KDE
     density = np.zeros_like(x_range)
     for v in values:
         density += np.exp(-0.5 * ((x_range - v) / bandwidth) ** 2)
     density /= n * bandwidth * np.sqrt(2 * np.pi)
 
-    # Normalize density and place on TOP (positive Y direction = cloud)
-    density = density / density.max() * cloud_offset
+    # Normalize and place cloud ABOVE category line (positive Y)
+    density_scaled = density / density.max() * cloud_height
 
-    # Create half-violin shape - cloud extends UP (higher Y)
-    cloud_points = [(x, center_y + d) for x, d in zip(x_range, density, strict=True)]
-    # Close the shape along the center line
-    cloud_points = [(x_range[0], center_y)] + cloud_points + [(x_range[-1], center_y), (x_range[0], center_y)]
-    cloud_data.append((category, cloud_points, group_colors[i]))
+    # Half-violin shape: baseline at center_y, cloud rises upward
+    cloud_points = [(float(x_range[0]), center_y)]
+    cloud_points += [
+        {"value": (float(x), center_y + float(d)), "label": f"{category} density"}
+        for x, d in zip(x_range, density_scaled, strict=True)
+    ]
+    cloud_points += [(float(x_range[-1]), center_y), (float(x_range[0]), center_y)]
+    chart.add(f"{category} cloud", cloud_points, stroke=True, fill=True)
 
-    # --- Jittered Points (rain) - BELOW (rain falls from cloud) ---
+    # --- Jittered Points (rain) - falls DOWNWARD from category line ---
     np.random.seed(42 + i)
     jitter = np.random.uniform(-0.08, 0.08, len(values))
-    rain_points = [(float(v), center_y + rain_offset + j) for j, v in zip(jitter, values, strict=True)]
-    rain_data.append((category, rain_points, group_colors[i]))
+    rain_points = [
+        {"value": (float(v), center_y + rain_offset + float(j)), "label": f"{category}: {v:.0f} ms"}
+        for j, v in zip(jitter, values, strict=True)
+    ]
+    chart.add(f"{category} rain", rain_points, stroke=False, fill=False, dots_size=32)
 
-    # --- Box Plot (centered at group position) ---
+    # --- Box Plot (centered at category line) ---
     median = float(np.median(values))
     q1 = float(np.percentile(values, 25))
     q3 = float(np.percentile(values, 75))
     iqr = q3 - q1
     whisker_low = float(max(values.min(), q1 - 1.5 * iqr))
     whisker_high = float(min(values.max(), q3 + 1.5 * iqr))
-    box_data.append((center_y, median, q1, q3, whisker_low, whisker_high, group_colors[i]))
 
-# Add clouds (half-violins)
-for _category, cloud_points, _color in cloud_data:
-    chart.add("", cloud_points, stroke=True, fill=True)
-
-# Add rain points - increased dots_size for better visibility
-for _category, rain_points, _color in rain_data:
-    chart.add("", rain_points, stroke=False, fill=False, dots_size=32)
-
-# Add box plots - HORIZONTAL boxes centered at each group
-box_width = 0.10
-cap_width = 0.06
-
-for center_y, median, q1, q3, whisker_low, whisker_high, _color in box_data:
     # IQR box (horizontal rectangle)
     quartile_box = [
         (q1, center_y - box_width),
@@ -145,25 +138,28 @@
         (q3, center_y - box_width),
         (q1, center_y - box_width),
     ]
-    chart.add("", quartile_box, stroke=True, fill=False, show_dots=False, stroke_style={"width": 20})
+    chart.add("", quartile_box, stroke=True, fill=False, show_dots=False, stroke_style={"width": 36})
 
     # Median line (vertical line within box)
-    median_line = [(median, center_y - box_width * 1.3), (median, center_y + box_width * 1.3)]
-    chart.add("", median_line, stroke=True, fill=False, show_dots=False, stroke_style={"width": 28})
+    median_line = [
+        {"value": (median, center_y - box_width * 1.3), "label": f"{category} median: {median:.0f} ms"},
+        (median, center_y + box_width * 1.3),
+    ]
+    chart.add("", median_line, stroke=True, fill=False, show_dots=False, stroke_style={"width": 44})
 
-    # Whiskers (horizontal lines from box to caps)
+    # Whiskers
     whisker_left = [(whisker_low, center_y), (q1, center_y)]
     whisker_right = [(q3, center_y), (whisker_high, center_y)]
-    chart.add("", whisker_left, stroke=True, fill=False, show_dots=False, stroke_style={"width": 14})
-    chart.add("", whisker_right, stroke=True, fill=False, show_dots=False, stroke_style={"width": 14})
+    chart.add("", whisker_left, stroke=True, fill=False, show_dots=False, stroke_style={"width": 22})
+    chart.add("", whisker_right, stroke=True, fill=False, show_dots=False, stroke_style={"width": 22})
 
-    # Whisker caps (vertical lines at ends)
+    # Whisker caps
     cap_left = [(whisker_low, center_y - cap_width), (whisker_low, center_y + cap_width)]
     cap_right = [(whisker_high, center_y - cap_width), (whisker_high, center_y + cap_width)]
-    chart.add("", cap_left, stroke=True, fill=False, show_dots=False, stroke_style={"width": 14})
-    chart.add("", cap_right, stroke=True, fill=False, show_dots=False, stroke_style={"width": 14})
+    chart.add("", cap_left, stroke=True, fill=False, show_dots=False, stroke_style={"width": 22})
+    chart.add("", cap_right, stroke=True, fill=False, show_dots=False, stroke_style={"width": 22})
 
-# Y-axis labels for treatment groups (categories on Y-axis for horizontal)
+# Y-axis labels for treatment groups
 chart.y_labels = [
     {"value": 0, "label": ""},
     {"value": 1, "label": "Control"},

plots/raincloud-basic/metadata/pygal.yaml

@@ -1,16 +1,16 @@
 library: pygal
 specification_id: raincloud-basic
 created: '2025-12-25T08:21:24Z'
-updated: '2025-12-25T08:23:33Z'
-generated_by: claude-opus-4-5-20251101
+updated: 2026-02-14T20:28:11+00:00
+generated_by: claude-opus-4-6
 workflow_run: 20501866165
 issue: 0
-python_version: 3.13.11
-library_version: 3.1.0
+python_version: "3.14"
+library_version: "3.1.0"
 preview_url: https://storage.googleapis.com/pyplots-images/plots/raincloud-basic/pygal/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/raincloud-basic/pygal/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/raincloud-basic/pygal/plot.html
-quality_score: 91
+quality_score: null
 impl_tags:
   dependencies: []
   techniques:

plots/raincloud-basic/specification.md

@@ -20,10 +20,10 @@ A raincloud plot combines three visualization elements—a half-violin (the "clo
 
 ## Notes
 
-- **Required Orientation**: Use HORIZONTAL orientation with categories on y-axis and values on x-axis
-- **Critical Layout**: The "cloud" (half-violin/KDE) must be on TOP (positive y offset), boxplot in MIDDLE, and "rain" (jittered points) BELOW (negative y offset) - like rain falling from a cloud
+- **Required Orientation**: Use HORIZONTAL orientation with categories on y-axis and values on x-axis. "Above" and "below" always refer to the y-direction (screen up/down), not the x-direction
+- **Critical Layout**: For each category on the y-axis: the "cloud" (half-violin/KDE) must extend ABOVE the category baseline (upward on screen), the boxplot sits centered ON the category baseline, and "rain" (jittered points) must appear BELOW the category baseline (downward on screen) - like rain falling from a cloud
 - Clip the violin to show only half (the "cloud" portion), not a full violin
 - Use moderate jitter (0.05-0.1) to spread rain points without excessive overlap
 - Apply transparency (alpha 0.5-0.7) to jittered rain points for visibility
 - Include median and quartile markers in box plot
-- The visual metaphor must be clear: cloud above, rain falling below
+- The visual metaphor must be clear: cloud rises upward (positive y-direction), rain falls downward (negative y-direction) from each category line