feat(letsplot): implement contour-density (#2594)

## Implementation: `contour-density` - letsplot

Implements the **letsplot** version of `contour-density`.

**File:** `plots/contour-density/implementations/letsplot.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20593405154)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/contour-density/implementations/letsplot.py

@@ -0,0 +1,59 @@
+""" pyplots.ai
+contour-density: Density Contour Plot
+Library: letsplot 4.8.2 | Python 3.13.11
+Quality: 92/100 | Created: 2025-12-30
+"""
+
+import numpy as np
+import pandas as pd
+from lets_plot import *
+
+
+LetsPlot.setup_html()
+
+# Data - two clusters with different spreads for bivariate distribution
+np.random.seed(42)
+
+# Cluster 1: Dense core cluster (temperature measurements)
+n1 = 400
+x1 = np.random.normal(loc=22, scale=3, size=n1)
+y1 = np.random.normal(loc=55, scale=8, size=n1)
+
+# Cluster 2: More diffuse cluster
+n2 = 300
+x2 = np.random.normal(loc=32, scale=5, size=n2)
+y2 = np.random.normal(loc=75, scale=10, size=n2)
+
+# Cluster 3: Small dense cluster
+n3 = 150
+x3 = np.random.normal(loc=15, scale=2, size=n3)
+y3 = np.random.normal(loc=80, scale=5, size=n3)
+
+# Combine clusters
+x = np.concatenate([x1, x2, x3])
+y = np.concatenate([y1, y2, y3])
+
+df = pd.DataFrame({"temperature": x, "humidity": y})
+
+# Plot - density contour with scatter overlay for context
+plot = (
+    ggplot(df, aes(x="temperature", y="humidity"))
+    + geom_density2d(color="#306998", size=1.2, bins=10)
+    + geom_point(color="#FFD43B", alpha=0.3, size=2)
+    + labs(x="Temperature (°C)", y="Relative Humidity (%)", title="contour-density · letsplot · pyplots.ai")
+    + theme_minimal()
+    + theme(
+        axis_title=element_text(size=20),
+        axis_text=element_text(size=16),
+        plot_title=element_text(size=24),
+        panel_grid=element_line(color="#888888", size=0.3),
+        panel_grid_minor=element_blank(),
+    )
+    + ggsize(1600, 900)
+)
+
+# Save as PNG (scale 3x for 4800 × 2700 px)
+ggsave(plot, "plot.png", path=".", scale=3)
+
+# Save as HTML for interactive version
+ggsave(plot, "plot.html", path=".")

plots/contour-density/metadata/letsplot.yaml

@@ -0,0 +1,26 @@
+library: letsplot
+specification_id: contour-density
+created: '2025-12-30T09:37:09Z'
+updated: '2025-12-30T09:47:24Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20593405154
+issue: 0
+python_version: 3.13.11
+library_version: 4.8.2
+preview_url: https://storage.googleapis.com/pyplots-images/plots/contour-density/letsplot/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/contour-density/letsplot/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/contour-density/letsplot/plot.html
+quality_score: 92
+review:
+  strengths:
+  - Excellent visualization of three distinct density clusters with clear concentric
+    contour lines
+  - Good use of scatter overlay with low alpha providing context without overwhelming
+    the contours
+  - Proper ggplot2-style grammar with geom_density2d following lets-plot conventions
+  - Axis labels include appropriate units (°C, %) and are descriptive
+  - 'Title follows the exact required format: spec-id · library · pyplots.ai'
+  - Realistic temperature/humidity scenario with sensible data ranges
+  weaknesses:
+  - Scatter point alpha could be slightly lower (0.2) for better contour visibility
+    in dense areas