feat(pygal): implement line-confidence (#2251)

## Implementation: `line-confidence` - pygal

Implements the **pygal** version of `line-confidence`.

**File:** `plots/line-confidence/implementations/pygal.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20525435948)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/line-confidence/implementations/pygal.py

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+""" pyplots.ai
+line-confidence: Line Plot with Confidence Interval
+Library: pygal 3.1.0 | Python 3.13.11
+Quality: 58/100 | Created: 2025-12-26
+"""
+
+import numpy as np
+import pygal
+from pygal.style import Style
+
+
+# Data - Model predictions with 95% confidence interval
+np.random.seed(42)
+
+# Time points (e.g., weeks)
+x = np.linspace(0, 12, 50)
+
+# Central prediction: exponential growth pattern (e.g., user growth model)
+y_center = 1000 + 500 * (1 - np.exp(-0.3 * x)) + np.random.randn(50) * 20
+# Smooth the center line
+y_center = np.convolve(y_center, np.ones(5) / 5, mode="same")
+y_center[0:2] = y_center[2]  # Fix edge effects from convolution
+y_center[-2:] = y_center[-3]
+
+# Confidence interval widens over time (increasing uncertainty in predictions)
+uncertainty = 30 + 15 * x
+y_lower = y_center - uncertainty
+y_upper = y_center + uncertainty
+
+# Custom style for 4800x2700 canvas
+custom_style = Style(
+    background="white",
+    plot_background="white",
+    foreground="#333333",
+    foreground_strong="#333333",
+    foreground_subtle="#666666",
+    guide_stroke_color="#cccccc",
+    colors=(
+        "rgba(48, 105, 152, 0.25)",  # Semi-transparent blue for confidence band
+        "#306998",  # Solid dark blue for predicted mean line
+    ),
+    opacity="1",
+    opacity_hover="1",
+    title_font_size=60,
+    label_font_size=42,
+    major_label_font_size=42,
+    legend_font_size=42,
+    value_font_size=36,
+)
+
+# Create XY chart
+chart = pygal.XY(
+    style=custom_style,
+    width=4800,
+    height=2700,
+    title="line-confidence · pygal · pyplots.ai",
+    x_title="Time (weeks)",
+    y_title="Predicted Users",
+    show_dots=False,
+    show_x_guides=True,
+    show_y_guides=True,
+    fill=True,
+    legend_at_bottom=True,
+    truncate_legend=-1,
+    range=(float(y_lower.min() - 50), float(y_upper.max() + 50)),
+)
+
+# Create confidence band as a closed polygon:
+# Trace upper bound left-to-right, then lower bound right-to-left
+# This forms a closed shape that pygal can fill
+confidence_band = []
+
+# Forward pass: upper bound (left to right)
+for xi, yi in zip(x, y_upper, strict=True):
+    confidence_band.append((float(xi), float(yi)))
+
+# Backward pass: lower bound (right to left) - closes the polygon
+for xi, yi in zip(reversed(x), reversed(y_lower), strict=True):
+    confidence_band.append((float(xi), float(yi)))
+
+# Center line data
+center_data = [(float(xi), float(yi)) for xi, yi in zip(x, y_center, strict=True)]
+
+# Add confidence band (filled polygon)
+chart.add("95% Confidence Interval", confidence_band, show_dots=False, stroke=False)
+
+# Add center line (solid stroke, no fill)
+chart.add("Predicted Mean", center_data, fill=False, stroke=True, show_dots=False, stroke_style={"width": 6})
+
+# Save outputs
+chart.render_to_png("plot.png")
+chart.render_to_file("plot.html")

plots/line-confidence/metadata/pygal.yaml

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+library: pygal
+specification_id: line-confidence
+created: '2025-12-26T16:13:44Z'
+updated: '2025-12-26T16:36:56Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20525435948
+issue: 0
+python_version: 3.13.11
+library_version: 3.1.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/line-confidence/pygal/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/line-confidence/pygal/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/line-confidence/pygal/plot.html
+quality_score: 58
+review:
+  strengths:
+  - Clean KISS code structure with proper random seed for reproducibility
+  - Correct title format following pyplots.ai convention
+  - Realistic user growth prediction scenario with appropriate data scale
+  - Good use of pygal XY chart and custom Style configuration
+  - Proper axis labels and grid configuration
+  weaknesses:
+  - Confidence interval band is nearly invisible - the filled polygon approach with
+    rgba opacity renders as an almost imperceptible thin region rather than a clearly
+    visible shaded band
+  - Legend claims 95% Confidence Interval but users cannot actually see the band,
+    making the visualization misleading
+  - Pygal fill mechanism for polygons may not be suitable for confidence bands - library
+    limitation for this visualization type