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feat(matplotlib): implement subplot-mosaic#3028

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implementation/subplot-mosaic/matplotlib
Dec 31, 2025
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feat(matplotlib): implement subplot-mosaic#3028
github-actions[bot] merged 4 commits intomainfrom
implementation/subplot-mosaic/matplotlib

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Implementation: subplot-mosaic - matplotlib

Implements the matplotlib version of subplot-mosaic.

File: plots/subplot-mosaic/implementations/matplotlib.py

Parent Issue: #3002


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claude Bot commented Dec 31, 2025

AI Review - Attempt 1/3

Image Description

The plot displays a mosaic subplot layout with 5 panels arranged in the pattern "AAB;AAB;CDE". The main panel (A) shows a cumulative sales time series with a blue line and light blue fill area, spanning the left 2/3 of the upper portion. Panel B on the right shows a horizontal bar chart with yellow bars (outlined in blue) for 4 products with value labels. The bottom row has three smaller panels: C shows a scatter plot with blue points, D displays a histogram with blue bars, and E contains a "Key Metrics" panel with text values. The main title "subplot-mosaic · matplotlib · pyplots.ai" appears at the top. Colors are primarily blue (#306998) and yellow (#FFD43B) with white backgrounds and subtle gray grids.

Quality Score: 92/100

Criteria Checklist

Visual Quality (36/40 pts)

  • VQ-01: Text Legibility (9/10) - All text is readable; main titles and labels are appropriately sized, though some bottom panel labels are slightly smaller
  • VQ-02: No Overlap (8/8) - No overlapping text elements
  • VQ-03: Element Visibility (7/8) - Most elements well-sized; scatter points could be slightly larger for the 80-point dataset
  • VQ-04: Color Accessibility (5/5) - Blue and yellow palette is colorblind-safe
  • VQ-05: Layout Balance (4/5) - Good layout following mosaic pattern; slight imbalance with metrics panel having more whitespace
  • VQ-06: Axis Labels (2/2) - Descriptive labels with units ("Cumulative Sales ($)", "Units Sold")
  • VQ-07: Grid & Legend (1/2) - Grids are subtle (alpha 0.3), but no legends needed for this visualization

Spec Compliance (23/25 pts)

  • SC-01: Plot Type (8/8) - Correctly implements mosaic subplot layout
  • SC-02: Data Mapping (5/5) - Data appropriately mapped in each subplot
  • SC-03: Required Features (4/5) - Shows varying sizes, multiple plot types, but doesn't demonstrate empty cells with "." placeholder
  • SC-04: Data Range (3/3) - All axes show complete data ranges
  • SC-05: Legend Accuracy (1/2) - No legends present (not strictly required but would help)
  • SC-06: Title Format (2/2) - Uses correct format: "subplot-mosaic · matplotlib · pyplots.ai"

Data Quality (20/20 pts)

  • DQ-01: Feature Coverage (8/8) - Demonstrates time series, bar chart, scatter, histogram, and metrics panel - excellent variety
  • DQ-02: Realistic Context (7/7) - Sales dashboard scenario is realistic and neutral
  • DQ-03: Appropriate Scale (5/5) - All values are realistic (sales ~500-650, units 85-120, percentages for metrics)

Code Quality (10/10 pts)

  • CQ-01: KISS Structure (3/3) - Clean imports → data → plot → save structure
  • CQ-02: Reproducibility (3/3) - Uses np.random.seed(42)
  • CQ-03: Clean Imports (2/2) - Only matplotlib and numpy imported
  • CQ-04: No Deprecated API (1/1) - No deprecated functions used
  • CQ-05: Output Correct (1/1) - Saves as plot.png

Library Features (3/5 pts)

  • LF-01: Uses distinctive library features (3/5) - Excellent use of plt.subplot_mosaic() which is matplotlib's signature feature for this task, but could also use additional matplotlib-specific features like annotations or color normalization

Strengths

  • Excellent demonstration of plt.subplot_mosaic() with the "AAB;AAB;CDE" pattern - this is exactly what the spec asked for
  • Great variety of plot types (line with fill_between, horizontal bar, scatter, histogram, text metrics)
  • Clean, professional color scheme with accessible blue/yellow palette
  • Well-structured dashboard layout with clear visual hierarchy (large overview, medium bar chart, small detail panels)
  • Realistic sales dashboard scenario with appropriate data scales

Weaknesses

  • Scatter plot markers could be larger (s=100 is adequate but s=150 would be more visible for 80 points)
  • Missing demonstration of empty cells with "." placeholder mentioned in spec notes
  • Metrics panel (E) layout could be tighter - the box has significant internal whitespace

Verdict: APPROVED

@github-actions github-actions Bot added the quality:92 Quality score 92/100 label Dec 31, 2025
@github-actions github-actions Bot added the ai-approved Quality OK, ready for merge label Dec 31, 2025
@github-actions github-actions Bot merged commit 54f9beb into main Dec 31, 2025
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@github-actions github-actions Bot deleted the implementation/subplot-mosaic/matplotlib branch December 31, 2025 11:10
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