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chore(plotly): update quality score 88 and review feedback for heatmap-geographic
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‎plots/heatmap-geographic/implementations/python/plotly.py‎

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"""anyplot.ai
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""" anyplot.ai
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heatmap-geographic: Geographic Heatmap for Spatial Density
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Library: plotly | Python 3.13
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Quality: 92/100 | Created: 2026-01-10
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Library: plotly 6.7.0 | Python 3.13.13
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Quality: 88/100 | Updated: 2026-05-18
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"""
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import os

‎plots/heatmap-geographic/metadata/python/plotly.yaml‎

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# Per-library metadata for plotly implementation of heatmap-geographic
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# Auto-generated by impl-generate.yml
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library: plotly
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language: python
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specification_id: heatmap-geographic
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created: '2026-01-10T08:16:18Z'
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updated: '2026-05-18T23:33:57Z'
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updated: '2026-05-18T23:40:45Z'
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generated_by: claude-sonnet
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workflow_run: 26066433362
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issue: 3638
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preview_url_dark: https://storage.googleapis.com/anyplot-images/plots/heatmap-geographic/python/plotly/plot-dark.png
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preview_html_light: https://storage.googleapis.com/anyplot-images/plots/heatmap-geographic/python/plotly/plot-light.html
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preview_html_dark: https://storage.googleapis.com/anyplot-images/plots/heatmap-geographic/python/plotly/plot-dark.html
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quality_score: null
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quality_score: 88
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review:
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strengths: []
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weaknesses: []
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strengths:
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- Theme-adaptive basemap style switching (carto-positron vs carto-darkmatter) integrates
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seamlessly with the light/dark theme system
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- 'Perfect spec compliance: density heatmap, basemap, colorbar, transparency, interactivity
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all present and working'
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- Real SF Bay Area data with four geographically accurate hotspots creates an immediately
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interpretable visualization
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- Clean flat code with all theme tokens properly applied to colorbar elements
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- HTML export provides interactive output alongside PNG renders
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weaknesses:
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- YlOrRd colorscale is valid per spec but not the style guide default (viridis preferred);
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yellow-end has lower CVD safety compared to viridis — switch to colorscale=Viridis
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- 'Design sophistication (DE-01=5/8): no focal-point annotation on highest-density
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hotspot, no colorbar frame styling using ELEVATED_BG token'
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- Map tile text cannot be resized by implementation, slightly limiting VQ-01
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image_description: |-
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Light render (plot-light.png):
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Background: Warm off-white carto-positron basemap with paper_bgcolor ~#FAF8F1 border area; basemap itself is light grey/white tile style
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Chrome: Title "Activity Density · heatmap-geographic · python · plotly · anyplot.ai" at 28px in dark INK color — clearly readable; colorbar title "Intensity" at 20px, tick labels at 16px in INK_SOFT — all readable
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Data: YlOrRd colorscale with opacity=0.7; four hotspots visible (Downtown SF largest/most intense in red, Oakland, Berkeley, South SF); background scatter in yellow; color gradient clearly shows density variation
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Legibility verdict: PASS
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Dark render (plot-dark.png):
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Background: Near-black carto-darkmatter basemap with paper_bgcolor ~#1A1A17 border area; basemap itself is dark tile style
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Chrome: Title text in light INK color (#F0EFE8) — clearly readable against dark background; colorbar title and ticks in INK_SOFT (#B8B7B0) — readable; map tile city labels appear in light/white text; NO dark-on-dark failures
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Data: YlOrRd colorscale colors are identical to light render (same yellow→red gradient hotspots); data colors unchanged, only chrome flipped; hotspots pop vividly against the near-black basemap
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Legibility verdict: PASS
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criteria_checklist:
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visual_quality:
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score: 27
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max: 30
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items:
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- id: VQ-01
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name: Text Legibility
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score: 7
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max: 8
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passed: true
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comment: Title 28px, colorbar title 20px, colorbar ticks 16px all explicitly
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set and readable; map tile labels from external service can't be controlled
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- id: VQ-02
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name: No Overlap
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score: 6
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max: 6
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passed: true
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comment: No text or element collisions in either render
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- id: VQ-03
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name: Element Visibility
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score: 6
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max: 6
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passed: true
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comment: Density hotspots distinct and well-contrasted; radius=15 appropriate
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for data density
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- id: VQ-04
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name: Color Accessibility
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score: 1
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max: 2
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passed: false
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comment: YlOrRd yellow-end has lower luminance contrast and some CVD concerns
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compared to viridis
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- id: VQ-05
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name: Layout & Canvas
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score: 4
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max: 4
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passed: true
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comment: Map fills canvas efficiently; explicit margins; colorbar well-positioned
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outside map
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- id: VQ-06
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name: Axis Labels & Title
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score: 2
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max: 2
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passed: true
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comment: Descriptive title in correct format; colorbar labeled Intensity
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- id: VQ-07
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name: Palette Compliance
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score: 1
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max: 2
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passed: false
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comment: Correct theme chrome (#FAF8F1/#1A1A17 backgrounds, INK tokens); YlOrRd
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is valid sequential but not default recommendation (viridis preferred)
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design_excellence:
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score: 13
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max: 20
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items:
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- id: DE-01
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name: Aesthetic Sophistication
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score: 5
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max: 8
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passed: true
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comment: Theme-adaptive basemap styles (carto-positron/carto-darkmatter) is
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above-default thinking; good but not strong design territory
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- id: DE-02
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name: Visual Refinement
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score: 4
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max: 6
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passed: true
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comment: Clean layout with explicit margins; good refinement for geographic
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map context; no traditional spines/grids to remove
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- id: DE-03
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name: Data Storytelling
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score: 4
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max: 6
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passed: true
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comment: SF Bay Area activity story immediately clear; color gradient focuses
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on hotspots; no focal-point annotations to highlight specific insights
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spec_compliance:
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score: 15
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max: 15
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items:
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- id: SC-01
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name: Plot Type
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score: 5
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max: 5
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passed: true
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comment: go.Densitymap is the correct geographic density heatmap type
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- id: SC-02
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name: Required Features
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score: 4
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max: 4
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passed: true
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comment: KDE density, sequential colormap, transparency, basemap, colorbar,
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interactivity, hover template all present
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- id: SC-03
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name: Data Mapping
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score: 3
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max: 3
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passed: true
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comment: Latitude, longitude, intensity (z) correctly mapped; all clusters
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visible
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- id: SC-04
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name: Title & Legend
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score: 3
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max: 3
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passed: true
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comment: Title Activity Density · heatmap-geographic · python · plotly · anyplot.ai
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matches required format
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data_quality:
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score: 15
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max: 15
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items:
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- id: DQ-01
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name: Feature Coverage
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score: 6
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max: 6
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passed: true
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comment: Multiple distinct hotspots at varying intensities, background scatter,
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clear density gradients — all aspects demonstrated
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- id: DQ-02
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name: Realistic Context
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score: 5
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max: 5
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passed: true
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comment: Real SF Bay Area geography with plausible urban activity density;
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neutral, non-controversial
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- id: DQ-03
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name: Appropriate Scale
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score: 4
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max: 4
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passed: true
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comment: Geographically accurate coordinates; 1500 points appropriate; intensity
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0.1-1.0 realistic for relative activity
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code_quality:
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score: 10
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max: 10
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items:
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- id: CQ-01
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name: KISS Structure
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score: 3
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max: 3
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passed: true
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comment: 'Flat structure: imports → theme tokens → data → plot → save; no
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functions or classes'
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- id: CQ-02
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name: Reproducibility
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score: 2
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max: 2
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passed: true
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comment: np.random.seed(42) set before all random calls
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- id: CQ-03
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name: Clean Imports
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score: 2
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max: 2
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passed: true
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comment: Only os, numpy, plotly.graph_objects — all used
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- id: CQ-04
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name: Code Elegance
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score: 2
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max: 2
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passed: true
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comment: Clean, idiomatic Python; appropriate complexity; no over-engineering
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- id: CQ-05
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name: Output & API
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score: 1
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max: 1
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passed: true
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comment: Saves plot-{THEME}.png and plot-{THEME}.html; uses current go.Densitymap
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API
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library_mastery:
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score: 8
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max: 10
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items:
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- id: LM-01
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name: Idiomatic Usage
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score: 4
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max: 5
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passed: true
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comment: Correct use of go.Densitymap; proper layout/map configuration with
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center/zoom; colorbar configured via trace dict
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- id: LM-02
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name: Distinctive Features
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score: 4
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max: 5
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passed: true
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comment: go.Densitymap is distinctly Plotly; CARTO tile integration with theme-adaptive
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styles; interactive HTML export with hover templates
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verdict: REJECTED
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impl_tags:
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dependencies: []
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techniques:
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- colorbar
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- hover-tooltips
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- html-export
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patterns:
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- data-generation
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dataprep: []
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styling:
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- custom-colormap
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- alpha-blending

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