feat(plotly): implement andrews-curves (#6820)

## Implementation: `andrews-curves` - python/plotly

Implements the **python/plotly** version of `andrews-curves`.

**File:** `plots/andrews-curves/implementations/python/plotly.py`

**Parent Issue:** #2859

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/25918836175)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com>

Author: github-actions[bot]

plots/andrews-curves/implementations/python/plotly.py

@@ -1,108 +1,113 @@
-""" pyplots.ai
+""" anyplot.ai
 andrews-curves: Andrews Curves for Multivariate Data
-Library: plotly 6.5.0 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-31
+Library: plotly 6.7.0 | Python 3.13.13
+Quality: 85/100 | Updated: 2026-05-15
 """
 
+import os
+
 import numpy as np
 import plotly.graph_objects as go
 from sklearn.datasets import load_iris
 
 
-# Data - Load Iris dataset
+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"]
+BRAND = OKABE_ITO[0]
+
+# Data
 iris = load_iris()
-X = iris.data  # 150 samples, 4 features
+X = iris.data
 y = iris.target
-species_names = ["Setosa", "Versicolor", "Virginica"]
-colors = ["#306998", "#FFD43B", "#E74C3C"]  # Python Blue, Python Yellow, Red
+species_names = iris.target_names
 
-# Normalize data to prevent dominant variables
+# Normalize
 X_normalized = (X - X.mean(axis=0)) / X.std(axis=0)
 
-# Andrews curve transformation
-# f(t) = x1/sqrt(2) + x2*sin(t) + x3*cos(t) + x4*sin(2t) + x5*cos(2t) + ...
+# Andrews curve transformation parameter
 t = np.linspace(-np.pi, np.pi, 200)
 
-
-def andrews_curve(x, t_vals):
-    """Transform a single observation to Andrews curve values."""
-    n_features = len(x)
-    curve = np.ones_like(t_vals) * x[0] / np.sqrt(2)
-    for i in range(1, n_features):
-        freq = (i + 1) // 2
-        if i % 2 == 1:
-            curve += x[i] * np.sin(freq * t_vals)
-        else:
-            curve += x[i] * np.cos(freq * t_vals)
-    return curve
-
-
-# Create figure
+# Plot
 fig = go.Figure()
 
-# Plot Andrews curves for each sample, colored by species
+# Plot curves for each sample, colored by species
 for species_idx in range(3):
     species_mask = y == species_idx
     X_species = X_normalized[species_mask]
 
     for i, x in enumerate(X_species):
-        curve_y = andrews_curve(x, t)
+        # Inline Andrews curve transformation
+        n_features = len(x)
+        curve = np.ones_like(t) * x[0] / np.sqrt(2)
+        for j in range(1, n_features):
+            freq = (j + 1) // 2
+            if j % 2 == 1:
+                curve += x[j] * np.sin(freq * t)
+            else:
+                curve += x[j] * np.cos(freq * t)
+
         fig.add_trace(
             go.Scatter(
                 x=t,
-                y=curve_y,
+                y=curve,
                 mode="lines",
-                line=dict(color=colors[species_idx], width=2),
+                line=dict(color=OKABE_ITO[species_idx], width=2),
                 opacity=0.4,
                 name=species_names[species_idx],
                 legendgroup=species_names[species_idx],
-                showlegend=(i == 0),  # Only show legend for first curve of each species
+                showlegend=(i == 0),
                 hovertemplate=f"{species_names[species_idx]}<br>t: %{{x:.2f}}<br>f(t): %{{y:.2f}}<extra></extra>",
             )
         )
 
-# Update layout for 4800x2700 canvas
+# Layout
 fig.update_layout(
-    title=dict(text="Iris Dataset · andrews-curves · plotly · pyplots.ai", font=dict(size=32), x=0.5, xanchor="center"),
+    title=dict(text="andrews-curves · plotly · anyplot.ai", font=dict(size=28, color=INK), x=0.5, xanchor="center"),
     xaxis=dict(
-        title=dict(text="Parameter t (radians)", font=dict(size=24)),
-        tickfont=dict(size=18),
-        gridcolor="rgba(128, 128, 128, 0.3)",
-        gridwidth=1,
+        title=dict(text="Parameter t (radians)", font=dict(size=22, color=INK)),
+        tickfont=dict(size=18, color=INK_SOFT),
+        gridcolor=GRID,
+        gridwidth=0.5,
         zeroline=True,
-        zerolinecolor="rgba(128, 128, 128, 0.5)",
+        zerolinecolor=GRID,
         zerolinewidth=1,
+        linecolor=INK_SOFT,
         range=[-np.pi, np.pi],
         tickvals=[-np.pi, -np.pi / 2, 0, np.pi / 2, np.pi],
         ticktext=["-π", "-π/2", "0", "π/2", "π"],
     ),
     yaxis=dict(
-        title=dict(text="f(t) (normalized units)", font=dict(size=24)),
-        tickfont=dict(size=18),
-        gridcolor="rgba(128, 128, 128, 0.3)",
-        gridwidth=1,
+        title=dict(text="f(t) (normalized units)", font=dict(size=22, color=INK)),
+        tickfont=dict(size=18, color=INK_SOFT),
+        gridcolor=GRID,
+        gridwidth=0.5,
         zeroline=True,
-        zerolinecolor="rgba(128, 128, 128, 0.5)",
+        zerolinecolor=GRID,
         zerolinewidth=1,
+        linecolor=INK_SOFT,
     ),
-    template="plotly_white",
     legend=dict(
-        font=dict(size=20),
+        font=dict(size=16, color=INK_SOFT),
         x=0.98,
         y=0.98,
         xanchor="right",
         yanchor="top",
-        bgcolor="rgba(255, 255, 255, 0.8)",
-        bordercolor="rgba(128, 128, 128, 0.3)",
+        bgcolor=ELEVATED_BG,
+        bordercolor=INK_SOFT,
         borderwidth=1,
     ),
-    margin=dict(l=100, r=80, t=100, b=80),
-    plot_bgcolor="white",
-    paper_bgcolor="white",
+    margin=dict(l=120, r=80, t=100, b=100),
+    plot_bgcolor=PAGE_BG,
+    paper_bgcolor=PAGE_BG,
+    font=dict(color=INK),
 )
 
-# Save as PNG (4800 x 2700 px)
-fig.write_image("plot.png", width=1600, height=900, scale=3)
-
-# Save interactive HTML version
-fig.write_html("plot.html", include_plotlyjs=True, full_html=True)
+# Save
+fig.write_image(f"plot-{THEME}.png", width=1600, height=900, scale=3)
+fig.write_html(f"plot-{THEME}.html", include_plotlyjs="cdn")