feat(seaborn): implement gauge-basic (#5392)

## Implementation: `gauge-basic` - python/seaborn

Implements the **python/seaborn** version of `gauge-basic`.

**File:** `plots/gauge-basic/implementations/python/seaborn.py`

**Parent Issue:** #857

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/24930951204)*

---------

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: github-actions[bot]

plots/gauge-basic/implementations/python/seaborn.py

@@ -1,172 +1,136 @@
-""" pyplots.ai
+""" anyplot.ai
 gauge-basic: Basic Gauge Chart
-Library: seaborn 0.13.2 | Python 3.13.11
-Quality: 90/100 | Created: 2025-12-23
+Library: seaborn 0.13.2 | Python 3.14.4
+Quality: 89/100 | Updated: 2026-04-25
 """
 
+import os
+
+import matplotlib.patheffects as pe
 import matplotlib.pyplot as plt
 import numpy as np
-import pandas as pd
 import seaborn as sns
+from matplotlib.patches import Circle, Wedge
+
+
+# Theme tokens
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
 
+# Okabe-Ito zone palette (semantic gauge mapping: vermillion / orange / brand green)
+ZONE_LOW, ZONE_MED, ZONE_HIGH = sns.color_palette(["#D55E00", "#E69F00", "#009E73"])
 
-# Data - Sales performance gauge
-value = 72  # Current sales performance
+# Data — sales performance gauge
+value = 72
 min_value = 0
 max_value = 100
-thresholds = [30, 70]  # Zone boundaries
+thresholds = [30, 70]
 
-# Create figure with larger gauge
-fig, ax = plt.subplots(figsize=(16, 9))
-sns.set_theme(style="white")
-
-# Gauge parameters - larger for better canvas utilization
-center = (0.5, 0.30)
-radius = 0.42
-width = 0.18
+# Gauge geometry
+center = (0.5, 0.45)
+radius = 0.40
+width = 0.16
 start_angle = 180
 end_angle = 0
 angle_range = start_angle - end_angle
 value_range = max_value - min_value
 
-# Colorblind-safe palette using seaborn's colorblind palette
-cb_palette = sns.color_palette("colorblind", 3)
-zone_colors = [cb_palette[2], cb_palette[1], cb_palette[0]]  # Blue-ish, Orange, Green-ish order for low-med-high
-
-# Draw gauge arc segments using seaborn scatterplot for the zone markers
-# Create data for zone indicator points along the arc
-n_points_per_zone = 50
 zone_boundaries = [min_value] + thresholds + [max_value]
-zone_data = []
+zone_names = ["Low", "Medium", "High"]
+zone_colors = [ZONE_LOW, ZONE_MED, ZONE_HIGH]
+
+# Plot
+sns.set_theme(
+    style="white",
+    rc={
+        "figure.facecolor": PAGE_BG,
+        "axes.facecolor": PAGE_BG,
+        "text.color": INK,
+        "axes.labelcolor": INK,
+        "xtick.color": INK_SOFT,
+        "ytick.color": INK_SOFT,
+    },
+)
+fig, ax = plt.subplots(figsize=(12, 12), facecolor=PAGE_BG)
+ax.set_facecolor(PAGE_BG)
 
+# Arc — three coloured zones drawn as smooth Wedge patches
 for i in range(len(zone_boundaries) - 1):
-    zone_start = zone_boundaries[i]
-    zone_end = zone_boundaries[i + 1]
-    zone_name = ["Low", "Medium", "High"][i]
-
-    for v in np.linspace(zone_start, zone_end, n_points_per_zone, endpoint=(i == len(zone_boundaries) - 2)):
-        angle = start_angle - (v - min_value) / value_range * angle_range
-        rad = np.radians(angle)
-        # Points along the middle of the arc width
-        for r_offset in np.linspace(-width / 2 + 0.01, width / 2 - 0.01, 8):
-            r = radius - width / 2 + r_offset + width / 2
-            x = center[0] + r * np.cos(rad)
-            y = center[1] + r * np.sin(rad)
-            zone_data.append({"x": x, "y": y, "zone": zone_name, "value": v})
-
-df_zones = pd.DataFrame(zone_data)
-
-# Use seaborn scatterplot to draw the gauge arc zones with denser points for smooth appearance
-sns.scatterplot(
-    data=df_zones,
-    x="x",
-    y="y",
-    hue="zone",
-    hue_order=["Low", "Medium", "High"],
-    palette=[zone_colors[0], zone_colors[1], zone_colors[2]],
-    s=180,
-    marker="o",
-    edgecolor="none",
-    alpha=1.0,
-    legend=False,
-    ax=ax,
-)
+    z_start_angle = start_angle - (zone_boundaries[i] - min_value) / value_range * angle_range
+    z_end_angle = start_angle - (zone_boundaries[i + 1] - min_value) / value_range * angle_range
+    ax.add_patch(
+        Wedge(
+            center=center,
+            r=radius + width / 2,
+            theta1=z_end_angle,
+            theta2=z_start_angle,
+            width=width,
+            facecolor=zone_colors[i],
+            edgecolor="none",
+            linewidth=0,
+            zorder=2,
+        )
+    )
 
-# Add thin white arc lines at zone boundaries using seaborn for visual separation
+# Boundary cuts between zones — short radial line, theme-visible color
 for threshold in thresholds:
     boundary_angle = start_angle - (threshold - min_value) / value_range * angle_range
     rad = np.radians(boundary_angle)
-    boundary_line_data = []
-    for r in np.linspace(radius - width, radius, 10):
-        boundary_line_data.append({"x": center[0] + r * np.cos(rad), "y": center[1] + r * np.sin(rad)})
-    boundary_df = pd.DataFrame(boundary_line_data)
-    sns.lineplot(data=boundary_df, x="x", y="y", color="white", linewidth=3, ax=ax, legend=False)
-
-# Create needle indicator data point using seaborn
+    rs = (radius - width / 2, radius + width / 2)
+    ax.plot(
+        [center[0] + r * np.cos(rad) for r in rs],
+        [center[1] + r * np.sin(rad) for r in rs],
+        color=INK_SOFT,
+        linewidth=3,
+        zorder=3,
+        solid_capstyle="butt",
+    )
+
+# Needle
 needle_angle = start_angle - (value - min_value) / value_range * angle_range
 needle_rad = np.radians(needle_angle)
-needle_length = radius - width / 2
-
-# Draw needle line
+needle_length = radius + width / 2 - 0.015
 needle_tip_x = center[0] + needle_length * np.cos(needle_rad)
 needle_tip_y = center[1] + needle_length * np.sin(needle_rad)
+ax.plot([center[0], needle_tip_x], [center[1], needle_tip_y], color=INK, linewidth=6, zorder=12, solid_capstyle="round")
 
-# Use seaborn lineplot for the needle
-needle_df = pd.DataFrame({"x": [center[0], needle_tip_x], "y": [center[1], needle_tip_y]})
-sns.lineplot(data=needle_df, x="x", y="y", color="#2C3E50", linewidth=6, ax=ax)
-
-# Draw needle tip marker using seaborn scatterplot - larger and more prominent
-tip_df = pd.DataFrame({"x": [needle_tip_x], "y": [needle_tip_y]})
-# White outline for contrast
-sns.scatterplot(data=tip_df, x="x", y="y", s=900, color="white", marker="v", ax=ax, zorder=9)
-# Main tip marker
-sns.scatterplot(data=tip_df, x="x", y="y", s=700, color="#E74C3C", marker="v", ax=ax, zorder=10)
-
-# Draw center hub using seaborn scatterplot
-hub_df = pd.DataFrame({"x": [center[0]], "y": [center[1]]})
-sns.scatterplot(data=hub_df, x="x", y="y", s=800, color="#2C3E50", marker="o", ax=ax, zorder=11)
+# Hub — outer ring (page bg) + inner disc (ink) for clean contrast in both themes
+ax.add_patch(Circle(center, radius=0.045, facecolor=PAGE_BG, edgecolor="none", zorder=13))
+ax.add_patch(Circle(center, radius=0.035, facecolor=INK, edgecolor="none", zorder=14))
 
 # Value display
-ax.text(
-    center[0], center[1] - 0.22, f"{value}%", ha="center", va="center", fontsize=52, fontweight="bold", color="#2C3E50"
-)
-
-# Min and max labels
-ax.text(
-    center[0] - radius + width / 2,
-    center[1] - 0.10,
-    f"{min_value}",
-    ha="center",
-    va="top",
-    fontsize=22,
-    color="#555555",
-)
-ax.text(
-    center[0] + radius - width / 2,
-    center[1] - 0.10,
-    f"{max_value}",
-    ha="center",
-    va="top",
-    fontsize=22,
-    color="#555555",
-)
-
-# Zone labels on the arc
-zone_label_angles = [
-    start_angle - (15 / value_range) * angle_range,
-    start_angle - (50 / value_range) * angle_range,
-    start_angle - (85 / value_range) * angle_range,
+ax.text(center[0], center[1] - 0.20, f"{value}%", ha="center", va="center", fontsize=56, fontweight="bold", color=INK)
+
+# Min / max endpoint labels
+for vlabel, x_off in [(min_value, -1), (max_value, 1)]:
+    ax.text(
+        center[0] + x_off * radius, center[1] - 0.06, f"{vlabel}", ha="center", va="top", fontsize=20, color=INK_SOFT
+    )
+
+# Zone labels on the arc — white text with dark stroke for legibility on every zone in both themes
+zone_label_centers = [
+    (thresholds[0] - min_value) / 2 + min_value,
+    (thresholds[0] + thresholds[1]) / 2,
+    (thresholds[1] + max_value) / 2,
 ]
-zone_label_names = ["Low", "Medium", "High"]
-label_radius = radius - width / 2
-
-for angle, label in zip(zone_label_angles, zone_label_names, strict=True):
+for v_center, label in zip(zone_label_centers, zone_names, strict=True):
+    angle = start_angle - (v_center - min_value) / value_range * angle_range
     rad = np.radians(angle)
-    x = center[0] + label_radius * np.cos(rad)
-    y = center[1] + label_radius * np.sin(rad)
-    # Text shadow/outline for better contrast on colored backgrounds
-    for dx, dy in [(-1, -1), (-1, 1), (1, -1), (1, 1), (-1, 0), (1, 0), (0, -1), (0, 1)]:
-        ax.text(
-            x + dx * 0.003,
-            y + dy * 0.003,
-            label,
-            ha="center",
-            va="center",
-            fontsize=18,
-            color="#1a1a1a",
-            fontweight="bold",
-        )
-    ax.text(x, y, label, ha="center", va="center", fontsize=18, color="white", fontweight="bold")
+    lx = center[0] + radius * np.cos(rad)
+    ly = center[1] + radius * np.sin(rad)
+    txt = ax.text(lx, ly, label, ha="center", va="center", fontsize=22, color="white", fontweight="bold", zorder=5)
+    txt.set_path_effects([pe.withStroke(linewidth=3, foreground="#1A1A17")])
 
-# Title and subtitle
-ax.set_title("gauge-basic · seaborn · pyplots.ai", fontsize=28, fontweight="bold", pad=20, color="#333333")
-ax.text(center[0], 0.95, "Sales Performance", ha="center", va="top", fontsize=24, color="#555555")
+# Title
+ax.set_title("gauge-basic · seaborn · anyplot.ai", fontsize=24, fontweight="medium", pad=20, color=INK)
 
-# Axis settings
+# Axis settings — purely a canvas
 ax.set_xlim(0, 1)
 ax.set_ylim(0, 1)
 ax.set_aspect("equal")
 ax.axis("off")
 
 plt.tight_layout()
-plt.savefig("plot.png", dpi=300, bbox_inches="tight", facecolor="white")
+plt.savefig(f"plot-{THEME}.png", dpi=300, bbox_inches="tight", facecolor=PAGE_BG)