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feat(matplotlib): implement contour-filled#2508

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github-actions[bot] merged 4 commits intomainfrom
implementation/contour-filled/matplotlib
Dec 30, 2025
Merged

feat(matplotlib): implement contour-filled#2508
github-actions[bot] merged 4 commits intomainfrom
implementation/contour-filled/matplotlib

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Implementation: contour-filled - matplotlib

Implements the matplotlib version of contour-filled.

File: plots/contour-filled/implementations/matplotlib.py


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github-actions Bot and others added 2 commits December 30, 2025 00:02
🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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claude Bot commented Dec 30, 2025

AI Review - Attempt 1/3

Image Description

The plot displays a filled contour visualization of a 2D mathematical surface. The plot uses the viridis colormap, ranging from dark purple (approximately -0.6) through teal/blue, green, to bright yellow (approximately 1.5). The surface shows multiple features: two prominent yellow peaks (one around coordinates (1, 1) and another around (-1.5, -1)), a dark purple valley/depression around (-0.5, 1.5), and a smaller peak around (1.5, -1.5). White contour lines are overlaid on the filled regions for level identification. The X and Y axes range from -3 to 3, labeled as "X Position" and "Y Position" respectively. A colorbar on the right shows "Surface Height (z)" values. The title correctly displays "contour-filled · matplotlib · pyplots.ai". The plot uses equal aspect ratio, making the overall shape square within a 16:9 canvas.

Quality Score: 92/100

Criteria Checklist

Visual Quality (37/40 pts)

  • VQ-01: Text Legibility (10/10) - Title at 24pt, axis labels at 20pt, tick labels at 16pt, colorbar labels at appropriate sizes - all perfectly readable
  • VQ-02: No Overlap (8/8) - No overlapping text elements, clean layout
  • VQ-03: Element Visibility (8/8) - Contour levels clearly visible, 80x80 grid provides smooth color transitions
  • VQ-04: Color Accessibility (5/5) - Viridis is a perceptually uniform, colorblind-safe colormap
  • VQ-05: Layout Balance (4/5) - Good use of canvas, equal aspect ratio makes plot square leaving some empty space on sides but overall balanced
  • VQ-06: Axis Labels (1/2) - Descriptive labels ("X Position", "Y Position") but without units
  • VQ-07: Grid & Legend (1/2) - No explicit grid (appropriate for contour), colorbar well-placed; contour lines act as implicit grid

Spec Compliance (25/25 pts)

  • SC-01: Plot Type (8/8) - Correct filled contour plot using contourf
  • SC-02: Data Mapping (5/5) - X, Y, Z correctly assigned to meshgrid
  • SC-03: Required Features (5/5) - All spec features present: filled contours, colorbar, overlaid contour lines, appropriate level count (15)
  • SC-04: Data Range (3/3) - Full data range visible, colorbar shows complete value range
  • SC-05: Legend Accuracy (2/2) - Colorbar label correctly describes the z-values as "Surface Height (z)"
  • SC-06: Title Format (2/2) - Correct format: "contour-filled · matplotlib · pyplots.ai"

Data Quality (17/20 pts)

  • DQ-01: Feature Coverage (8/8) - Excellent feature coverage: multiple peaks, a valley, and smooth gradients demonstrating all aspects of filled contours
  • DQ-02: Realistic Context (5/7) - Mathematical surface (Gaussian peaks/valleys) is plausible for demonstrating contours but generic
  • DQ-03: Appropriate Scale (4/5) - Values in reasonable range (-0.8 to 1.5), coordinate range (-3 to 3) appropriate

Code Quality (10/10 pts)

  • CQ-01: KISS Structure (3/3) - Clean imports → data → plot → save structure, no functions/classes
  • CQ-02: Reproducibility (3/3) - np.random.seed(42) set (though not strictly needed as data is deterministic)
  • CQ-03: Clean Imports (2/2) - Only matplotlib.pyplot and numpy used
  • CQ-04: No Deprecated API (1/1) - Uses current matplotlib API
  • CQ-05: Output Correct (1/1) - Saves as 'plot.png'

Library Features (3/5 pts)

  • LF-01: Uses distinctive library features (3/5) - Uses contourf and contour appropriately, but could leverage additional matplotlib features like clabel for contour labels

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

Verdict: APPROVED

@github-actions github-actions Bot added the quality:92 Quality score 92/100 label Dec 30, 2025
@github-actions github-actions Bot added the ai-approved Quality OK, ready for merge label Dec 30, 2025
@github-actions github-actions Bot merged commit f6b34e4 into main Dec 30, 2025
@github-actions github-actions Bot deleted the implementation/contour-filled/matplotlib branch December 30, 2025 00:07
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