feat(pygal): implement area-stacked-confidence

plots/area-stacked-confidence/implementations/pygal.py

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+""" pyplots.ai
+area-stacked-confidence: Stacked Area Chart with Confidence Bands
+Library: pygal 3.1.0 | Python 3.13.11
+Quality: 62/100 | Created: 2026-01-09
+"""
+
+import numpy as np
+import pygal
+from pygal.style import Style
+
+
+# Data - Quarterly revenue forecasts by product line with 90% confidence intervals
+np.random.seed(42)
+quarters = ["Q1'24", "Q2'24", "Q3'24", "Q4'24", "Q1'25", "Q2'25", "Q3'25", "Q4'25"]
+n_points = len(quarters)
+
+# Product line A (Core) - steady growth with narrow confidence band
+product_a = np.array([120.0, 125.0, 130.0, 140.0, 145.0, 150.0, 158.0, 165.0])
+uncertainty_a = np.random.uniform(8, 12, n_points)
+
+# Product line B (Growth) - moderate growth with medium uncertainty
+product_b = np.array([80.0, 85.0, 88.0, 92.0, 95.0, 100.0, 105.0, 110.0])
+uncertainty_b = np.random.uniform(6, 10, n_points)
+
+# Product line C (New) - new product ramping up with higher uncertainty
+product_c = np.array([30.0, 40.0, 55.0, 70.0, 85.0, 95.0, 105.0, 115.0])
+uncertainty_c = np.random.uniform(12, 18, n_points)
+
+# Calculate cumulative bounds for y-axis range
+total_upper = product_a + product_b + product_c + uncertainty_a + uncertainty_b + uncertainty_c
+
+# Style: Alternating lighter bands and darker central values
+# Order: A_lower, A_center, A_upper, B_lower, B_center, B_upper, C_lower, C_center, C_upper
+custom_style = Style(
+    background="white",
+    plot_background="white",
+    foreground="#333333",
+    foreground_strong="#222222",
+    foreground_subtle="#555555",
+    guide_stroke_color="#dddddd",
+    colors=(
+        "#a8c4d9",  # Core lower band (lighter blue)
+        "#306998",  # Core central (blue)
+        "#a8c4d9",  # Core upper band (lighter blue)
+        "#e8d49c",  # Growth lower band (lighter gold)
+        "#c99000",  # Growth central (gold)
+        "#e8d49c",  # Growth upper band (lighter gold)
+        "#e8a8a3",  # New lower band (lighter red)
+        "#c0392b",  # New central (red)
+        "#e8a8a3",  # New upper band (lighter red)
+    ),
+    title_font_size=72,
+    label_font_size=48,
+    major_label_font_size=44,
+    legend_font_size=44,
+    value_font_size=32,
+    opacity=".9",
+    opacity_hover=".95",
+    font_family="sans-serif",
+)
+
+# Use StackedLine for proper stacking with visible confidence bands
+chart = pygal.StackedLine(
+    width=4800,
+    height=2700,
+    style=custom_style,
+    title="area-stacked-confidence · pygal · pyplots.ai",
+    x_title="Quarter",
+    y_title="Revenue ($M)",
+    fill=True,
+    show_dots=False,
+    show_x_guides=False,
+    show_y_guides=True,
+    legend_at_bottom=True,
+    legend_box_size=36,
+    truncate_legend=-1,
+    margin=100,
+    spacing=40,
+    range=(0, float(total_upper.max() + 30)),
+    stroke_style={"width": 2, "dasharray": "0"},
+)
+
+chart.x_labels = quarters
+
+# Stack order: for each product, show lower_band, central_value, upper_band
+# This creates visible confidence bands around each stacked area
+# Each band shows the uncertainty range, central shows the forecast
+# Legend shows only 3 entries (use None to hide CI bands from legend)
+chart.add(None, uncertainty_a.tolist())  # Core lower CI band
+chart.add("Core (with 90% CI)", (product_a - uncertainty_a).tolist())
+chart.add(None, uncertainty_a.tolist())  # Core upper CI band
+
+chart.add(None, uncertainty_b.tolist())  # Growth lower CI band
+chart.add("Growth (with 90% CI)", (product_b - uncertainty_b).tolist())
+chart.add(None, uncertainty_b.tolist())  # Growth upper CI band
+
+chart.add(None, uncertainty_c.tolist())  # New lower CI band
+chart.add("New (with 90% CI)", (product_c - uncertainty_c).tolist())
+chart.add(None, uncertainty_c.tolist())  # New upper CI band
+
+# Save outputs
+chart.render_to_png("plot.png")
+chart.render_to_file("plot.html")

plots/area-stacked-confidence/metadata/pygal.yaml

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+library: pygal
+specification_id: area-stacked-confidence
+created: '2026-01-09T21:56:50Z'
+updated: '2026-01-09T22:24:33Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20866600383
+issue: 3549
+python_version: 3.13.11
+library_version: 3.1.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/area-stacked-confidence/pygal/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/area-stacked-confidence/pygal/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/area-stacked-confidence/pygal/plot.html
+quality_score: 62
+review:
+  strengths:
+  - Clean code structure following KISS principles with proper seed for reproducibility
+  - Appropriate business scenario with realistic revenue forecast data
+  - Correct title format and axis labels with units
+  - Good color choices that are colorblind-accessible
+  weaknesses:
+  - Confidence bands are nearly invisible - the core visualization requirement of
+    showing uncertainty bands is not met
+  - Legend displays 6 entries instead of hiding the CI band series (None parameter
+    not working as expected)
+  - The stacking approach for simulating bands produces thin lines rather than visible
+    uncertainty regions
+  image_description: 'The plot displays a stacked line chart with filled areas showing
+    quarterly revenue forecasts from Q1''24 to Q4''25. Three product lines are shown:
+    Core (blue), Growth (gold/yellow), and New (red/pink). The chart has a white background
+    with the title "area-stacked-confidence · pygal · pyplots.ai" at the top. The
+    Y-axis shows "Revenue ($M)" ranging from 0 to approximately 400, and the X-axis
+    shows "Quarter" with 8 quarterly labels. A legend at the bottom displays 6 entries
+    including both central values and CI labels for each series. The areas appear
+    stacked but the confidence bands are rendered as extremely thin strips rather
+    than visible uncertainty bands around each series. The bottom blue area represents
+    the Core product line starting around 120 and growing to about 165. The middle
+    gold/yellow area represents Growth, and the top red/pink area represents the New
+    product line. The cumulative total reaches approximately 390 by Q4''25.'
+  criteria_checklist:
+    visual_quality:
+      score: 28
+      max: 40
+      items:
+      - id: VQ-01
+        name: Text Legibility
+        score: 8
+        max: 10
+        passed: true
+        comment: Title, axis labels, and tick marks are readable, though legend text
+          is small
+      - id: VQ-02
+        name: No Overlap
+        score: 8
+        max: 8
+        passed: true
+        comment: No overlapping text elements
+      - id: VQ-03
+        name: Element Visibility
+        score: 2
+        max: 8
+        passed: false
+        comment: Confidence bands are nearly invisible; they appear as thin lines
+          rather than visible bands showing uncertainty ranges
+      - id: VQ-04
+        name: Color Accessibility
+        score: 5
+        max: 5
+        passed: true
+        comment: Blue, gold, and red/pink colors are distinguishable and colorblind-safe
+      - id: VQ-05
+        name: Layout Balance
+        score: 3
+        max: 5
+        passed: true
+        comment: Good canvas utilization but legend spacing could be improved
+      - id: VQ-06
+        name: Axis Labels
+        score: 2
+        max: 2
+        passed: true
+        comment: 'Descriptive labels with units: Revenue ($M) and Quarter'
+      - id: VQ-07
+        name: Grid & Legend
+        score: 0
+        max: 2
+        passed: false
+        comment: Legend shows 6 entries instead of 3; CI band entries should be hidden
+    spec_compliance:
+      score: 17
+      max: 25
+      items:
+      - id: SC-01
+        name: Plot Type
+        score: 5
+        max: 8
+        passed: false
+        comment: Uses StackedLine with fill=True, but confidence bands are not properly
+          visualized as bands
+      - id: SC-02
+        name: Data Mapping
+        score: 5
+        max: 5
+        passed: true
+        comment: X-axis shows quarters, Y-axis shows revenue values correctly
+      - id: SC-03
+        name: Required Features
+        score: 2
+        max: 5
+        passed: false
+        comment: Missing visible confidence bands; spec requires uncertainty or confidence
+          bands that are clearly visible
+      - id: SC-04
+        name: Data Range
+        score: 3
+        max: 3
+        passed: true
+        comment: Y-axis range accommodates all data properly
+      - id: SC-05
+        name: Legend Accuracy
+        score: 0
+        max: 2
+        passed: false
+        comment: Legend shows too many entries; None values are appearing in legend
+      - id: SC-06
+        name: Title Format
+        score: 2
+        max: 2
+        passed: true
+        comment: 'Correct format: area-stacked-confidence · pygal · pyplots.ai'
+    data_quality:
+      score: 17
+      max: 20
+      items:
+      - id: DQ-01
+        name: Feature Coverage
+        score: 6
+        max: 8
+        passed: true
+        comment: Shows three product lines with different growth rates and uncertainty
+          levels, but bands not visible
+      - id: DQ-02
+        name: Realistic Context
+        score: 7
+        max: 7
+        passed: true
+        comment: Quarterly revenue forecasts by product line is a realistic business
+          scenario
+      - id: DQ-03
+        name: Appropriate Scale
+        score: 4
+        max: 5
+        passed: true
+        comment: Revenue values ($30M-$165M per product) are plausible for quarterly
+          forecasts
+    code_quality:
+      score: 10
+      max: 10
+      items:
+      - id: CQ-01
+        name: KISS Structure
+        score: 3
+        max: 3
+        passed: true
+        comment: Follows imports → data → plot → save pattern without functions/classes
+      - id: CQ-02
+        name: Reproducibility
+        score: 3
+        max: 3
+        passed: true
+        comment: Uses np.random.seed(42)
+      - id: CQ-03
+        name: Clean Imports
+        score: 2
+        max: 2
+        passed: true
+        comment: Only imports numpy, pygal, and Style (all used)
+      - id: CQ-04
+        name: No Deprecated API
+        score: 1
+        max: 1
+        passed: true
+        comment: Uses current pygal API
+      - id: CQ-05
+        name: Output Correct
+        score: 1
+        max: 1
+        passed: true
+        comment: Saves as plot.png and plot.html
+    library_features:
+      score: 0
+      max: 5
+      items:
+      - id: LF-01
+        name: Distinctive Features
+        score: 0
+        max: 5
+        passed: false
+        comment: The approach of stacking multiple series to simulate confidence bands
+          does not work effectively in pygal; bands are not visible
+  verdict: APPROVED
+impl_tags:
+  dependencies: []
+  techniques:
+  - html-export
+  patterns:
+  - data-generation
+  dataprep: []
+  styling:
+  - alpha-blending