feat(seaborn): implement ternary-density

plots/ternary-density/implementations/python/seaborn.py

@@ -1,19 +1,31 @@
-""" pyplots.ai
+""" anyplot.ai
 ternary-density: Ternary Density Plot
-Library: seaborn 0.13.2 | Python 3.13.11
-Quality: 91/100 | Created: 2026-01-11
+Library: seaborn 0.13.2 | Python 3.13.13
+Quality: 91/100 | Updated: 2026-05-19
 """
 
+import os
+
+import matplotlib.cm as cm
 import matplotlib.pyplot as plt
 import numpy as np
 import seaborn as sns
+from matplotlib.colors import Normalize
 from matplotlib.patches import Polygon
 
 
+# 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"
+ACCENT = "#0072B2"  # Okabe-Ito blue — structural elements
+
+sns.set_theme(style="ticks", rc={"figure.facecolor": PAGE_BG, "axes.facecolor": PAGE_BG, "text.color": INK})
+
 # Data - Soil composition samples (sand/silt/clay percentages)
 np.random.seed(42)
 
-# Generate clustered compositional data
 # Cluster 1: Sandy soils (high sand content)
 n1 = 200
 sand1 = np.random.beta(5, 2, n1) * 70 + 25
@@ -32,96 +44,106 @@
 sand3 = np.random.beta(2, 3, n3) * (100 - clay3) * 0.4
 silt3 = 100 - clay3 - sand3
 
-# Combine all samples
 sand = np.concatenate([sand1, sand2, sand3])
 silt = np.concatenate([silt1, silt2, silt3])
 clay = np.concatenate([clay1, clay2, clay3])
 
-# Transform ternary to Cartesian coordinates
-# Convention: Sand at bottom-left, Silt at bottom-right, Clay at top
+# Transform ternary to Cartesian: Sand → bottom-left, Silt → bottom-right, Clay → top
 total = sand + silt + clay
 sand_norm = sand / total
 silt_norm = silt / total
 clay_norm = clay / total
 x = 0.5 * (2 * silt_norm + clay_norm)
 y = (np.sqrt(3) / 2) * clay_norm
 
-# Triangle vertices
 sqrt3_2 = np.sqrt(3) / 2
 vertices = np.array([[0, 0], [1, 0], [0.5, sqrt3_2]])
 
-# Create figure (square format for symmetric ternary plot)
-fig, ax = plt.subplots(figsize=(12, 12))
+# Plot
+fig, ax = plt.subplots(figsize=(12, 12), facecolor=PAGE_BG)
+ax.set_facecolor(PAGE_BG)
 
-# Create clipping polygon for the triangle
 triangle_clip = Polygon(vertices, transform=ax.transData)
 
-# Draw subtle grid lines FIRST (10% intervals)
+# Grid lines at 10% intervals (all three ternary families)
 for i in range(1, 10):
     frac = i / 10
-    # Lines parallel to bottom (constant clay proportion)
-    x1, y1 = frac, 0
-    x2, y2 = 0.5 + 0.5 * frac, sqrt3_2 * (1 - frac)
-    ax.plot([x1, x2], [y1, y2], color="gray", alpha=0.25, linewidth=0.8, zorder=1)
-
-    # Lines parallel to left side (constant silt proportion)
-    x1, y1 = 0.5 * frac, sqrt3_2 * frac
-    x2, y2 = 1 - 0.5 * frac, sqrt3_2 * frac
-    ax.plot([x1, x2], [y1, y2], color="gray", alpha=0.25, linewidth=0.8, zorder=1)
-
-    # Lines parallel to right side (constant sand proportion)
-    x1, y1 = 0, 0
-    x2, y2 = 0.5, sqrt3_2
-    # Shift along the base
-    x1, y1 = (1 - frac), 0
-    x2, y2 = 0.5 + 0.5 * (1 - frac), sqrt3_2 * frac
-    ax.plot([x1, x2], [y1, y2], color="gray", alpha=0.25, linewidth=0.8, zorder=1)
-
-# Seaborn KDE plot for density visualization
+    gkw = {"color": INK_SOFT, "alpha": 0.20, "linewidth": 0.8, "zorder": 1}
+    # Constant clay (horizontal, parallel to base)
+    ax.plot([0.5 * frac, 1 - 0.5 * frac], [sqrt3_2 * frac, sqrt3_2 * frac], **gkw)
+    # Constant silt (parallel to Sand-Clay left edge, slope +√3)
+    ax.plot([frac, 0.5 * (1 + frac)], [0, sqrt3_2 * (1 - frac)], **gkw)
+    # Constant sand (parallel to Silt-Clay right edge, slope -√3)
+    ax.plot([1 - frac, 0.5 * (1 - frac)], [0, sqrt3_2 * (1 - frac)], **gkw)
+
+# KDE density fill
 sns.kdeplot(x=x, y=y, fill=True, cmap="viridis", levels=20, alpha=0.85, ax=ax, thresh=0.02, zorder=5)
 
-# Apply clipping to the KDE contours
 for collection in ax.collections:
     collection.set_clip_path(triangle_clip)
 
-# Add contour lines for better interpretation
-sns.kdeplot(x=x, y=y, levels=10, color="#306998", linewidths=1.2, ax=ax, zorder=6)
+# KDE contour lines — thicker for visibility at full resolution
+sns.kdeplot(x=x, y=y, levels=10, color=ACCENT, linewidths=3.0, ax=ax, zorder=6)
 
-# Clip contour lines too
 for collection in ax.collections:
     collection.set_clip_path(triangle_clip)
 
-# Draw triangle boundary LAST (on top)
-triangle_border = Polygon(vertices, fill=False, edgecolor="#306998", linewidth=4, zorder=15)
-ax.add_patch(triangle_border)
-
-# Vertex labels
-ax.text(0, -0.08, "Sand (%)", ha="center", va="top", fontsize=22, fontweight="bold", color="#306998")
-ax.text(1, -0.08, "Silt (%)", ha="center", va="top", fontsize=22, fontweight="bold", color="#306998")
-ax.text(0.5, sqrt3_2 + 0.08, "Clay (%)", ha="center", va="bottom", fontsize=22, fontweight="bold", color="#306998")
-
-# Percentage labels along edges
+# Triangle boundary
+ax.add_patch(Polygon(vertices, fill=False, edgecolor=ACCENT, linewidth=4, zorder=15))
+
+# Colorbar showing relative density scale
+sm = cm.ScalarMappable(cmap="viridis", norm=Normalize(vmin=0, vmax=1))
+sm.set_array([])
+cbar = plt.colorbar(sm, ax=ax, fraction=0.025, pad=0.04, aspect=20, shrink=0.55)
+cbar.set_label("Relative Density", fontsize=18, labelpad=12)
+cbar.ax.yaxis.label.set_color(INK)
+cbar.set_ticks([0, 0.5, 1.0])
+cbar.ax.set_yticklabels(["Low", "Medium", "High"])
+for lbl in cbar.ax.get_yticklabels():
+    lbl.set_color(INK_SOFT)
+    lbl.set_fontsize(16)
+cbar.ax.tick_params(colors=INK_SOFT)
+cbar.outline.set_edgecolor(INK_SOFT)
+
+# Vertex labels (component names + unit)
+ax.text(0, -0.08, "Sand (%)", ha="center", va="top", fontsize=22, fontweight="bold", color=INK)
+ax.text(1, -0.08, "Silt (%)", ha="center", va="top", fontsize=22, fontweight="bold", color=INK)
+ax.text(0.5, sqrt3_2 + 0.08, "Clay (%)", ha="center", va="bottom", fontsize=22, fontweight="bold", color=INK)
+
+# Percentage tick labels along each edge
 for i in [2, 4, 6, 8]:
     frac = i / 10
-    # Bottom edge
-    ax.text(frac, -0.04, f"{int(frac * 100)}", ha="center", va="top", fontsize=14, color="gray")
-    # Left edge (clay axis)
-    lx = 0.5 * frac
-    ly = sqrt3_2 * frac
-    ax.text(lx - 0.04, ly, f"{int(frac * 100)}", ha="right", va="center", fontsize=14, color="gray")
-    # Right edge
-    rx = 1 - 0.5 * frac
-    ry = sqrt3_2 * frac
-    ax.text(rx + 0.04, ry, f"{int(frac * 100)}", ha="left", va="center", fontsize=14, color="gray")
-
-# Title
-ax.set_title("Soil Composition · ternary-density · seaborn · pyplots.ai", fontsize=26, fontweight="bold", pad=25)
-
-# Clean up axes
+    ax.text(frac, -0.04, f"{int(frac * 100)}", ha="center", va="top", fontsize=16, color=INK_SOFT)
+    ax.text(
+        0.5 * frac - 0.04, sqrt3_2 * frac, f"{int(frac * 100)}", ha="right", va="center", fontsize=16, color=INK_SOFT
+    )
+    ax.text(
+        1 - 0.5 * frac + 0.04, sqrt3_2 * frac, f"{int(frac * 100)}", ha="left", va="center", fontsize=16, color=INK_SOFT
+    )
+
+# Cluster annotations — label each density peak for data storytelling
+ann_kw = {
+    "fontsize": 15,
+    "fontweight": "bold",
+    "color": INK,
+    "bbox": {"boxstyle": "round,pad=0.3", "facecolor": PAGE_BG, "edgecolor": INK_SOFT, "alpha": 0.75},
+}
+ax.text(0.13, 0.04, "Sandy\nsoils", ha="center", va="center", **ann_kw)
+ax.text(0.80, 0.11, "Silty\nsoils", ha="center", va="center", **ann_kw)
+ax.text(0.53, 0.50, "Clay-rich\nsoils", ha="center", va="center", **ann_kw)
+
+# Style
+ax.set_title(
+    "Soil Composition · ternary-density · python · seaborn · anyplot.ai",
+    fontsize=24,
+    fontweight="medium",
+    color=INK,
+    pad=25,
+)
 ax.set_xlim(-0.15, 1.15)
 ax.set_ylim(-0.15, 1.05)
 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)