chore(matplotlib): update quality score 84 and review feedback for scatter-lag

Author: github-actions[bot]

plots/scatter-lag/implementations/matplotlib.py

@@ -1,7 +1,7 @@
-"""pyplots.ai
+""" pyplots.ai
 scatter-lag: Lag Plot for Time Series Autocorrelation Diagnosis
-Library: matplotlib | Python 3.13
-Quality: pending | Created: 2026-04-12
+Library: matplotlib 3.10.8 | Python 3.14.3
+Quality: 84/100 | Created: 2026-04-12
 """
 
 import matplotlib.pyplot as plt

plots/scatter-lag/metadata/matplotlib.yaml

@@ -1,18 +1,232 @@
-# Per-library metadata for matplotlib implementation of scatter-lag
-# Auto-generated by impl-generate.yml
-
 library: matplotlib
 specification_id: scatter-lag
 created: '2026-04-12T18:10:35Z'
-updated: '2026-04-12T18:10:35Z'
+updated: '2026-04-12T18:15:15Z'
 generated_by: claude-opus-4-5-20251101
 workflow_run: 24313009889
 issue: 5251
 python_version: 3.14.3
 library_version: 3.10.8
 preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-lag/matplotlib/plot.png
 preview_html: null
-quality_score: null
+quality_score: 84
 review:
-  strengths: []
-  weaknesses: []
+  strengths:
+  - 'Perfect spec compliance: diagonal reference line, temporal color encoding, correlation
+    annotation, and configurable lag all implemented'
+  - 'Excellent code quality: clean KISS structure, reproducible with seed(42), idiomatic
+    matplotlib patterns throughout'
+  - 'Good data storytelling: viridis time-index coloring meaningfully encodes temporal
+    evolution of the AR(1) series'
+  weaknesses:
+  - Marker size too large for 500 points (s=120 vs recommended s=20-50); significant
+    overplotting in the dense central diagonal band
+  - Design follows the library guide but lacks aesthetic differentiation — viridis
+    + spine removal is well-configured but not elevated
+  - Full x+y grid should be y-only per library conventions; colorbar tick labels at
+    14pt should be raised to 16pt
+  image_description: The plot shows a lag-1 scatter plot of a synthetic AR(1) time
+    series (500 observations, phi=0.85). The x-axis shows y(t) ranging from approximately
+    -4.5 to 5.5, and the y-axis shows y(t+1) over the same range. Points are colored
+    by time index using the viridis colormap (purple=early, yellow=late), with a vertical
+    colorbar on the right labeled "Time Index" (range 0-500). A dashed gray diagonal
+    reference line (y=x) runs from bottom-left to top-right. In the upper-left corner,
+    an annotation reads "r = 0.834". The scatter cloud forms a clear elongated ellipse
+    along the diagonal, demonstrating strong positive autocorrelation. The top and
+    right spines are removed; a subtle full-grid is visible. The title reads "AR(1)
+    Autocorrelation · scatter-lag · matplotlib · pyplots.ai". Overall layout is clean
+    and balanced on a 16:9 canvas.
+  criteria_checklist:
+    visual_quality:
+      score: 26
+      max: 30
+      items:
+      - id: VQ-01
+        name: Text Legibility
+        score: 7
+        max: 8
+        passed: true
+        comment: All key fonts explicitly set (title 24pt, labels 20pt, ticks 16pt,
+          r-annotation 20pt); colorbar tick labels at 14pt are slightly below the
+          16pt minimum
+      - id: VQ-02
+        name: No Overlap
+        score: 6
+        max: 6
+        passed: true
+        comment: No text collisions; r annotation, colorbar, and axis labels are well
+          separated
+      - id: VQ-03
+        name: Element Visibility
+        score: 3
+        max: 6
+        passed: false
+        comment: 500 points with s=120, alpha=0.65 produces significant overplotting
+          in the dense center; guidelines recommend s=20-50, alpha=0.3-0.5 for 300+
+          points
+      - id: VQ-04
+        name: Color Accessibility
+        score: 4
+        max: 4
+        passed: true
+        comment: Viridis is perceptually uniform and colorblind-safe
+      - id: VQ-05
+        name: Layout & Canvas
+        score: 4
+        max: 4
+        passed: true
+        comment: 16:9 canvas, balanced margins, colorbar well-placed
+      - id: VQ-06
+        name: Axis Labels & Title
+        score: 2
+        max: 2
+        passed: true
+        comment: y(t) and y(t+1) are standard mathematical notation for a lag plot
+    design_excellence:
+      score: 12
+      max: 20
+      items:
+      - id: DE-01
+        name: Aesthetic Sophistication
+        score: 4
+        max: 8
+        passed: false
+        comment: 'Well-configured library defaults: viridis + spine removal follows
+          the guide but does not reach strong design territory'
+      - id: DE-02
+        name: Visual Refinement
+        score: 4
+        max: 6
+        passed: true
+        comment: 'Spines removed, grid alpha=0.2 is subtle; minor issue: full x+y
+          grid rather than y-only as recommended'
+      - id: DE-03
+        name: Data Storytelling
+        score: 4
+        max: 6
+        passed: true
+        comment: Temporal color encoding reveals autocorrelation evolution; diagonal
+          reference + r annotation create a clear narrative
+    spec_compliance:
+      score: 15
+      max: 15
+      items:
+      - id: SC-01
+        name: Plot Type
+        score: 5
+        max: 5
+        passed: true
+        comment: Correct lag scatter plot (y(t) vs y(t+k))
+      - id: SC-02
+        name: Required Features
+        score: 4
+        max: 4
+        passed: true
+        comment: Diagonal reference line, time-index color coding, correlation annotation,
+          and configurable lag variable all present
+      - id: SC-03
+        name: Data Mapping
+        score: 3
+        max: 3
+        passed: true
+        comment: x=y(t), y=y(t+1) correctly assigned; axes cover full data range
+      - id: SC-04
+        name: Title & Legend
+        score: 3
+        max: 3
+        passed: true
+        comment: Title contains spec-id · library · pyplots.ai; colorbar labeled Time
+          Index is appropriate
+    data_quality:
+      score: 13
+      max: 15
+      items:
+      - id: DQ-01
+        name: Feature Coverage
+        score: 5
+        max: 6
+        passed: true
+        comment: Demonstrates strong positive autocorrelation clearly; could show
+          contrast with uncorrelated or differently-lagged data
+      - id: DQ-02
+        name: Realistic Context
+        score: 4
+        max: 5
+        passed: true
+        comment: Synthetic AR(1) is explicitly listed in the spec as valid; neutral
+          and appropriate, though abstract without real-world labeling
+      - id: DQ-03
+        name: Appropriate Scale
+        score: 4
+        max: 4
+        passed: true
+        comment: AR(1) with phi=0.85 and unit noise produces values in [-5, 5] — correct
+          and realistic
+    code_quality:
+      score: 10
+      max: 10
+      items:
+      - id: CQ-01
+        name: KISS Structure
+        score: 3
+        max: 3
+        passed: true
+        comment: 'Linear: imports → data generation → correlation → plot → save; no
+          functions or classes'
+      - id: CQ-02
+        name: Reproducibility
+        score: 2
+        max: 2
+        passed: true
+        comment: np.random.seed(42) set
+      - id: CQ-03
+        name: Clean Imports
+        score: 2
+        max: 2
+        passed: true
+        comment: Only matplotlib.pyplot and numpy imported, both used
+      - id: CQ-04
+        name: Code Elegance
+        score: 2
+        max: 2
+        passed: true
+        comment: Clean, idiomatic Python; appropriate complexity
+      - id: CQ-05
+        name: Output & API
+        score: 1
+        max: 1
+        passed: true
+        comment: Saves as plot.png with dpi=300; uses ax methods throughout
+    library_mastery:
+      score: 8
+      max: 10
+      items:
+      - id: LM-01
+        name: Idiomatic Usage
+        score: 5
+        max: 5
+        passed: true
+        comment: ax.scatter with c= + cmap, fig.colorbar(scatter, ax=ax), ax.transAxes
+          for annotation, tight_layout — all idiomatic matplotlib patterns
+      - id: LM-02
+        name: Distinctive Features
+        score: 3
+        max: 5
+        passed: true
+        comment: Continuous color mapping via scatter c= + colorbar is a recognizable
+          matplotlib pattern; white edgecolors on markers is a nice touch, but not
+          uniquely distinctive
+  verdict: REJECTED
+impl_tags:
+  dependencies: []
+  techniques:
+  - annotations
+  - colorbar
+  patterns:
+  - data-generation
+  - explicit-figure
+  dataprep: []
+  styling:
+  - custom-colormap
+  - alpha-blending
+  - edge-highlighting