feat(matplotlib): implement contour-filled

plots/contour-filled/implementations/matplotlib.py

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+""" pyplots.ai
+contour-filled: Filled Contour Plot
+Library: matplotlib 3.10.8 | Python 3.13.11
+Quality: 92/100 | Created: 2025-12-30
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+# Data - create a meshgrid with an interesting mathematical surface
+np.random.seed(42)
+x = np.linspace(-3, 3, 80)
+y = np.linspace(-3, 3, 80)
+X, Y = np.meshgrid(x, y)
+
+# Create a surface with multiple Gaussian peaks and a saddle point
+# This demonstrates various features: peaks, valleys, and gradients
+Z = (
+    1.5 * np.exp(-((X - 1) ** 2 + (Y - 1) ** 2))  # Peak at (1, 1)
+    + 1.2 * np.exp(-((X + 1.5) ** 2 + (Y + 1) ** 2) / 1.5)  # Peak at (-1.5, -1)
+    - 0.8 * np.exp(-((X + 0.5) ** 2 + (Y - 1.5) ** 2) / 0.8)  # Valley at (-0.5, 1.5)
+    + 0.5 * np.exp(-((X - 1.5) ** 2 + (Y + 1.5) ** 2))  # Small peak at (1.5, -1.5)
+)
+
+# Create figure
+fig, ax = plt.subplots(figsize=(16, 9))
+
+# Define number of contour levels for smooth transitions
+levels = 15
+
+# Create filled contour plot with a sequential colormap
+contourf = ax.contourf(X, Y, Z, levels=levels, cmap="viridis")
+
+# Overlay contour lines for precise level identification
+ax.contour(X, Y, Z, levels=levels, colors="white", linewidths=0.8, alpha=0.5)
+
+# Add colorbar to indicate value mapping
+cbar = plt.colorbar(contourf, ax=ax, shrink=0.9, pad=0.02)
+cbar.set_label("Surface Height (z)", fontsize=20)
+cbar.ax.tick_params(labelsize=16)
+
+# Styling
+ax.set_xlabel("X Position", fontsize=20)
+ax.set_ylabel("Y Position", fontsize=20)
+ax.set_title("contour-filled · matplotlib · pyplots.ai", fontsize=24)
+ax.tick_params(axis="both", labelsize=16)
+
+# Make the plot aspect ratio equal for proper visualization
+ax.set_aspect("equal", adjustable="box")
+
+plt.tight_layout()
+plt.savefig("plot.png", dpi=300, bbox_inches="tight")

plots/contour-filled/metadata/matplotlib.yaml

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+library: matplotlib
+specification_id: contour-filled
+created: '2025-12-30T00:02:41Z'
+updated: '2025-12-30T00:05:49Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20585400377
+issue: 0
+python_version: 3.13.11
+library_version: 3.10.8
+preview_url: https://storage.googleapis.com/pyplots-images/plots/contour-filled/matplotlib/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/contour-filled/matplotlib/plot_thumb.png
+preview_html: null
+quality_score: 92
+review:
+  strengths:
+  - Excellent mathematical surface with multiple features (peaks, valley, gradients)
+    that clearly demonstrates filled contour capabilities
+  - Proper use of viridis colormap which is colorblind-safe and perceptually uniform
+  - Overlaid white contour lines with appropriate alpha for level identification as
+    recommended in spec
+  - Clean KISS code structure following matplotlib best practices
+  - Correct title format and appropriate font sizes throughout
+  weaknesses:
+  - Axis labels could include units (e.g., "X Position (units)" or use a more realistic
+    application context)
+  - Mathematical demonstration is generic rather than a compelling real-world scenario
+    (e.g., topographic elevation, temperature field)
+  - Could add contour labels (clabel) to show numerical values on contour lines