update(band-basic): pygal — comprehensive quality review (#4355)

## Summary

Updated **pygal** implementation for **band-basic**.

**Changes:** Comprehensive quality review — improved data context, axis
labels, visual design.

## Test Plan

- [x] Preview images uploaded to GCS staging
- [x] Implementation file passes ruff format/check
- [x] Metadata YAML updated with current versions
- [ ] Automated review triggered

---
Generated with [Claude Code](https://claude.com/claude-code) `/update`
command

---------

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

Author: MarkusNeusinger

plots/band-basic/implementations/pygal.py

@@ -1,78 +1,140 @@
 """ pyplots.ai
 band-basic: Basic Band Plot
-Library: pygal 3.1.0 | Python 3.13.11
-Quality: 88/100 | Created: 2025-12-23
+Library: pygal 3.1.0 | Python 3.14
+Quality: 89/100 | Updated: 2026-02-23
 """
 
 import numpy as np
 import pygal
 from pygal.style import Style
 
 
-# Data - Time series with 95% confidence interval
+# Data - Soil moisture sensor readings with 95% confidence interval
 np.random.seed(42)
-x = np.linspace(0, 10, 50)
-# Central trend line (quadratic curve)
-y_center = 2 + 0.5 * x + 0.1 * x**2 + np.random.randn(50) * 0.3
-# Smooth the center line
-y_center = np.convolve(y_center, np.ones(3) / 3, mode="same")
-# Confidence interval widens with x (increasing uncertainty)
-uncertainty = 0.5 + 0.15 * x
+n_points = 80
+hours = np.linspace(0, 48, n_points)
+
+# Realistic soil moisture pattern: starts high after rain, drops during day,
+# recovers slightly at night, then dips to a low before a second rain event
+base_trend = 38 - 0.3 * hours + 4.0 * np.sin(2 * np.pi * hours / 24) + 8.0 * np.exp(-((hours - 40) ** 2) / 8)
+noise = np.random.randn(n_points) * 0.6
+y_raw = base_trend + noise
+
+# Smooth with convolution, padding edges to preserve length
+kernel = np.ones(7) / 7
+y_smooth = np.convolve(y_raw, kernel, mode="valid")
+pad_left = (n_points - len(y_smooth)) // 2
+pad_right = n_points - len(y_smooth) - pad_left
+y_center = np.concatenate([np.full(pad_left, y_smooth[0]), y_smooth, np.full(pad_right, y_smooth[-1])])
+
+# Confidence interval: wider during dry spell, narrower after rain
+uncertainty = 1.2 + 0.8 * np.sin(2 * np.pi * hours / 24) ** 2 + 0.04 * hours
 y_lower = y_center - uncertainty
 y_upper = y_center + uncertainty
 
-# Custom style for 4800x2700 canvas
+# Explicit y-axis labels at clean intervals for precise grid control
+y_lo = 4 * (int(min(y_lower)) // 4)
+y_hi = 4 * (int(max(y_upper)) // 4 + 1)
+y_label_values = list(range(y_lo, y_hi + 1, 4))
+
+# Custom style — sans-serif typography, polished palette, refined visual hierarchy
 custom_style = Style(
     background="white",
     plot_background="white",
-    foreground="#333333",
-    foreground_strong="#333333",
-    foreground_subtle="#666666",
-    guide_stroke_color="#888888",  # Darker grid lines for better visibility
-    colors=("#306998", "#FFD43B"),  # Blue for band, Yellow for center line
-    opacity=".65",  # Higher opacity for clearly visible band
-    opacity_hover=".75",
-    stroke_width=5,  # Thicker lines for better visibility
+    foreground="#2C3E50",
+    foreground_strong="#1A252F",
+    foreground_subtle="#BDC3C7",
+    guide_stroke_color="#F0F0F0",
+    guide_stroke_dasharray="2,8",
+    major_guide_stroke_color="#E8E8E8",
+    major_guide_stroke_dasharray="4,6",
+    colors=("#306998", "#B8860B", "#7F8C8D"),
+    opacity=".20",
+    opacity_hover=".35",
+    stroke_opacity="1",
+    stroke_opacity_hover="1",
+    stroke_width=4,
     title_font_size=60,
     label_font_size=42,
     major_label_font_size=42,
-    legend_font_size=42,
+    legend_font_size=40,
     value_font_size=36,
+    value_colors=("transparent",),
+    tooltip_font_size=32,
+    font_family='Helvetica, Arial, "DejaVu Sans", sans-serif',
 )
 
-# Create XY chart for precise coordinate control
+# Create XY chart with fine-tuned layout and pygal-specific configuration
 chart = pygal.XY(
     style=custom_style,
     width=4800,
     height=2700,
-    title="95% Confidence Interval · band-basic · pygal · pyplots.ai",
-    x_title="Time (s)",
-    y_title="Measurement Value",
+    explicit_size=True,
+    title="band-basic \u00b7 pygal \u00b7 pyplots.ai",
+    x_title="Time (hours)",
+    y_title="Soil Moisture (%)",
     show_dots=False,
-    show_x_guides=True,
+    show_x_guides=False,
     show_y_guides=True,
     fill=True,
     stroke=True,
     legend_at_bottom=True,
+    legend_at_bottom_columns=3,
+    legend_box_size=28,
     truncate_legend=-1,
+    x_label_rotation=0,
+    range=(y_lo - 1, y_hi + 1),
+    y_labels=y_label_values,
+    x_labels=[0, 6, 12, 18, 24, 30, 36, 42, 48],
+    x_labels_major=[0, 12, 24, 36, 48],
+    show_minor_x_labels=True,
+    show_minor_y_labels=False,
+    print_values=False,
+    x_value_formatter=lambda x: f"{x:.0f}h",
+    value_formatter=lambda x: f"{x:.1f}%",
+    tooltip_border_radius=8,
+    margin_top=30,
+    margin_bottom=50,
+    margin_left=30,
+    margin_right=50,
+    spacing=18,
+    js=[],
 )
 
-# Create band as a closed polygon: upper boundary forward, then lower backward
-# Using fill only (no stroke) to avoid visual artifacts at polygon edges
-band_polygon = []
-# Upper boundary (forward)
-for xi, yi in zip(x, y_upper, strict=True):
-    band_polygon.append((float(xi), float(yi)))
-# Lower boundary (backward to close the polygon smoothly)
-for xi, yi in zip(reversed(x), reversed(y_lower), strict=True):
-    band_polygon.append((float(xi), float(yi)))
+# Band as closed polygon: upper boundary forward, then lower boundary reversed
+band_polygon = [(float(h), float(y)) for h, y in zip(hours, y_upper, strict=True)]
+for h, y in zip(reversed(hours), reversed(y_lower), strict=True):
+    band_polygon.append((float(h), float(y)))
 
-chart.add("Confidence Band", band_polygon, stroke=False)
+chart.add(
+    "95% Confidence Band",
+    band_polygon,
+    stroke_style={"width": 0.5, "color": "#306998", "opacity": 0.15},
+    show_dots=False,
+)
 
-# Add center line (no fill, just stroke) - using a contrasting color
-center_data = [(float(xi), float(yi)) for xi, yi in zip(x, y_center, strict=True)]
-chart.add("Central Trend", center_data, fill=False, stroke=True, dots_size=0, stroke_style={"width": 6})
+# Central trend line — bold stroke with rounded SVG caps for smooth rendering
+center_data = [(float(h), float(y)) for h, y in zip(hours, y_center, strict=True)]
+chart.add(
+    "Sensor Mean",
+    center_data,
+    fill=False,
+    stroke=True,
+    dots_size=0,
+    stroke_style={"width": 48, "linecap": "round", "linejoin": "round"},
+)
+
+# Wilting point reference — threshold below which plants cannot extract moisture
+chart.add(
+    "Wilting Point (25%)",
+    [(0.0, 25.0), (48.0, 25.0)],
+    fill=False,
+    stroke=True,
+    dots_size=0,
+    formatter=lambda x: f"{x:.0f}%",
+    stroke_style={"width": 5, "dasharray": "16,10", "linecap": "round"},
+)
 
-# Save outputs
+# Save
 chart.render_to_png("plot.png")
 chart.render_to_file("plot.html")