feat(plotly): implement contour-decision-boundary

plots/contour-decision-boundary/implementations/python/plotly.py

@@ -1,16 +1,27 @@
-""" pyplots.ai
+""" anyplot.ai
 contour-decision-boundary: Decision Boundary Classifier Visualization
-Library: plotly 6.5.0 | Python 3.13.11
-Quality: 92/100 | Created: 2025-12-31
+Library: plotly 6.7.0 | Python 3.13.13
+Quality: 95/100 | Updated: 2026-05-16
 """
 
+import os
+
 import numpy as np
 import plotly.graph_objects as go
 from sklearn.datasets import make_moons
 from sklearn.neighbors import KNeighborsClassifier
 from sklearn.preprocessing import StandardScaler
 
 
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+GRID = "rgba(26,26,23,0.10)" if THEME == "light" else "rgba(240,239,232,0.10)"
+
+OKABE_ITO = ["#009E73", "#D55E00", "#0072B2", "#CC79A7"]
+
 # Data - Generate moon-shaped classification data
 np.random.seed(42)
 X, y = make_moons(n_samples=200, noise=0.25, random_state=42)
@@ -28,11 +39,7 @@
 y_min, y_max = X[:, 1].min() - 0.5, X[:, 1].max() + 0.5
 xx, yy = np.meshgrid(np.linspace(x_min, x_max, 150), np.linspace(y_min, y_max, 150))
 
-# Get predictions for mesh grid
-Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])
-Z = Z.reshape(xx.shape)
-
-# Get prediction probabilities for smoother contours
+# Get prediction probabilities for smooth contours
 Z_prob = clf.predict_proba(np.c_[xx.ravel(), yy.ravel()])[:, 1]
 Z_prob = Z_prob.reshape(xx.shape)
 
@@ -45,14 +52,18 @@
         x=np.linspace(x_min, x_max, 150),
         y=np.linspace(y_min, y_max, 150),
         z=Z_prob,
-        colorscale=[[0, "#306998"], [1, "#FFD43B"]],
-        opacity=0.6,
+        colorscale=[[0, OKABE_ITO[0]], [1, OKABE_ITO[1]]],
+        opacity=0.4,
         showscale=True,
         colorbar=dict(
-            title=dict(text="Class Probability", font=dict(size=18)), tickfont=dict(size=16), len=0.7, thickness=25
+            title=dict(text="Class Probability", font=dict(size=18)),
+            tickfont=dict(size=16),
+            len=0.7,
+            thickness=25,
+            bordercolor=INK_SOFT,
         ),
         contours=dict(showlines=False),
-        hoverinfo="skip",
+        hovertemplate="Feature 1: %{x:.2f}<br>Feature 2: %{y:.2f}<br>Probability: %{z:.2f}<extra></extra>",
     )
 )
 
@@ -64,7 +75,7 @@
         z=Z_prob,
         showscale=False,
         contours=dict(start=0.5, end=0.5, size=0.1, coloring="lines", showlabels=False),
-        line=dict(color="white", width=3, dash="dash"),
+        line=dict(color=INK_SOFT, width=3, dash="dash"),
         hoverinfo="skip",
     )
 )
@@ -79,9 +90,9 @@
         x=X_class0[:, 0],
         y=X_class0[:, 1],
         mode="markers",
-        marker=dict(size=14, color="#306998", line=dict(color="white", width=2), symbol="circle"),
+        marker=dict(size=14, color=OKABE_ITO[0], line=dict(color=PAGE_BG, width=2), symbol="circle"),
         name="Class 0",
-        hovertemplate="Feature 1: %{x:.2f}<br>Feature 2: %{y:.2f}<extra>Class 0</extra>",
+        hovertemplate="Feature 1: %{x:.2f}<br>Feature 2: %{y:.2f}<br>Class: 0<extra></extra>",
     )
 )
 
@@ -91,47 +102,56 @@
         x=X_class1[:, 0],
         y=X_class1[:, 1],
         mode="markers",
-        marker=dict(size=14, color="#FFD43B", line=dict(color="black", width=2), symbol="diamond"),
+        marker=dict(size=14, color=OKABE_ITO[1], line=dict(color=PAGE_BG, width=2), symbol="diamond"),
         name="Class 1",
-        hovertemplate="Feature 1: %{x:.2f}<br>Feature 2: %{y:.2f}<extra>Class 1</extra>",
+        hovertemplate="Feature 1: %{x:.2f}<br>Feature 2: %{y:.2f}<br>Class: 1<extra></extra>",
     )
 )
 
-# Update layout
+# Update layout with theme-adaptive colors
 fig.update_layout(
-    title=dict(text="contour-decision-boundary · plotly · pyplots.ai", font=dict(size=28), x=0.5, xanchor="center"),
+    title=dict(
+        text="contour-decision-boundary · plotly · anyplot.ai", font=dict(size=28, color=INK), x=0.5, xanchor="center"
+    ),
     xaxis=dict(
-        title=dict(text="Feature 1 (Standardized)", font=dict(size=22)),
-        tickfont=dict(size=18),
+        title=dict(text="Feature 1 (Standardized)", font=dict(size=22, color=INK)),
+        tickfont=dict(size=18, color=INK_SOFT),
         showgrid=True,
         gridwidth=1,
-        gridcolor="rgba(128, 128, 128, 0.3)",
+        gridcolor=GRID,
         zeroline=False,
+        linecolor=INK_SOFT,
+        linewidth=2,
     ),
     yaxis=dict(
-        title=dict(text="Feature 2 (Standardized)", font=dict(size=22)),
-        tickfont=dict(size=18),
+        title=dict(text="Feature 2 (Standardized)", font=dict(size=22, color=INK)),
+        tickfont=dict(size=18, color=INK_SOFT),
         showgrid=True,
         gridwidth=1,
-        gridcolor="rgba(128, 128, 128, 0.3)",
+        gridcolor=GRID,
         zeroline=False,
+        linecolor=INK_SOFT,
+        linewidth=2,
         scaleanchor="x",
         scaleratio=1,
     ),
-    template="plotly_white",
+    paper_bgcolor=PAGE_BG,
+    plot_bgcolor=PAGE_BG,
+    font=dict(color=INK),
     legend=dict(
-        font=dict(size=18),
-        x=0.02,
-        y=0.98,
-        xanchor="left",
-        yanchor="top",
-        bgcolor="rgba(255, 255, 255, 0.8)",
-        bordercolor="rgba(0, 0, 0, 0.3)",
+        font=dict(size=18, color=INK_SOFT),
+        x=0.98,
+        y=0.02,
+        xanchor="right",
+        yanchor="bottom",
+        bgcolor=ELEVATED_BG,
+        bordercolor=INK_SOFT,
         borderwidth=1,
     ),
     margin=dict(l=80, r=100, t=100, b=80),
+    hovermode="closest",
 )
 
 # Save as PNG and HTML
-fig.write_image("plot.png", width=1600, height=900, scale=3)
-fig.write_html("plot.html", include_plotlyjs="cdn")
+fig.write_image(f"plot-{THEME}.png", width=1600, height=900, scale=3)
+fig.write_html(f"plot-{THEME}.html", include_plotlyjs="cdn")