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feat(pygal): implement rose-basic (#5595)
## Implementation: `rose-basic` - python/pygal Implements the **python/pygal** version of `rose-basic`. **File:** `plots/rose-basic/implementations/python/pygal.py` **Parent Issue:** #1003 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/25152039315)* --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com>
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""" pyplots.ai
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""" anyplot.ai
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rose-basic: Basic Rose Chart
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Library: pygal 3.1.0 | Python 3.13.11
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Quality: 58/100 | Created: 2025-12-23
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Library: pygal 3.1.0 | Python 3.13.13
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Quality: 80/100 | Updated: 2026-04-30
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"""
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import pygal
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from pygal.style import Style
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import os
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import sys
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# Data: Monthly rainfall (mm) - Pacific Northwest pattern with seasonal variation
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# Clear cycle: wet winters (Nov-Feb), dry summers (Jun-Aug)
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# Pop script directory so local pygal.py doesn't shadow the installed package
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_script_dir = sys.path.pop(0)
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import pygal # noqa: E402
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from pygal.style import Style # noqa: E402
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sys.path.insert(0, _script_dir)
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THEME = os.getenv("ANYPLOT_THEME", "light")
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PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
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INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
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INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
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OKABE_ITO = ("#009E73", "#D55E00", "#0072B2", "#CC79A7", "#E69F00", "#56B4E9", "#F0E442")
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# Data: Monthly rainfall (mm) — Pacific Northwest seasonal pattern
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months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
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rainfall = [145, 115, 95, 65, 45, 35, 20, 25, 50, 90, 135, 155]
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# Custom style for 3600x3600 square canvas
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custom_style = Style(
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background="white",
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plot_background="white",
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foreground="#333333",
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foreground_strong="#333333",
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foreground_subtle="#666666",
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colors=("#306998",), # Single blue for cohesive look
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background=PAGE_BG,
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plot_background=PAGE_BG,
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foreground=INK,
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foreground_strong=INK,
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foreground_subtle=INK_MUTED,
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colors=OKABE_ITO,
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title_font_size=72,
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label_font_size=44,
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major_label_font_size=40,
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legend_font_size=40,
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label_font_size=52,
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major_label_font_size=52,
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legend_font_size=44,
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value_font_size=36,
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stroke_width=3,
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stroke_width=4,
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opacity=0.75,
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opacity_hover=0.9,
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)
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# Pygal Radar chart: best approximation for rose/coxcomb in pygal
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# - Equal angular spacing around center (like rose chart)
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# - Radial distance proportional to values (like rose chart)
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# - Limitation: connected polygon instead of discrete wedges
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# Radar is pygal's closest approximation of a rose/coxcomb chart:
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# equal angular spacing, radius proportional to value, filled polygons
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chart = pygal.Radar(
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width=3600,
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height=3600,
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style=custom_style,
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title="rose-basic · pygal · pyplots.ai",
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title="rose-basic · pygal · anyplot.ai",
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fill=True,
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show_legend=True,
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legend_at_bottom=True,
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legend_at_bottom_columns=4,
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margin=120,
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dots_size=10,
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show_dots=True,
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legend_at_bottom_columns=1,
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margin=100,
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show_dots=False,
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range=(0, 170),
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)
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# Add month labels around the radar
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chart.x_labels = months
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# Single series with rainfall values - radius proportional to value
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chart.add("Monthly Rainfall (mm)", rainfall)
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# Save outputs
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chart.render_to_png("plot.png")
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chart.render_to_file("plot.html")
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# Save
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chart.render_to_png(f"plot-{THEME}.png")
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with open(f"plot-{THEME}.html", "wb") as f:
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f.write(chart.render())
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library: pygal
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language: python
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specification_id: rose-basic
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created: '2025-12-23T19:43:33Z'
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updated: '2025-12-23T20:15:09Z'
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generated_by: claude-opus-4-5-20251101
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workflow_run: 20469995744
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issue: 0
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python_version: 3.13.11
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updated: '2026-04-30T07:25:56Z'
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generated_by: claude-sonnet
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workflow_run: 25152039315
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issue: 1003
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python_version: 3.13.13
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library_version: 3.1.0
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preview_url: https://storage.googleapis.com/anyplot-images/plots/rose-basic/pygal/plot.png
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preview_html: https://storage.googleapis.com/anyplot-images/plots/rose-basic/pygal/plot.html
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quality_score: 58
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preview_url_light: https://storage.googleapis.com/anyplot-images/plots/rose-basic/python/pygal/plot-light.png
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preview_url_dark: https://storage.googleapis.com/anyplot-images/plots/rose-basic/python/pygal/plot-dark.png
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preview_html_light: https://storage.googleapis.com/anyplot-images/plots/rose-basic/python/pygal/plot-light.html
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preview_html_dark: https://storage.googleapis.com/anyplot-images/plots/rose-basic/python/pygal/plot-dark.html
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quality_score: 80
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review:
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strengths:
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- Seasonal groupings (Winter, Spring, Summer, Fall) create effective data storytelling
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and immediately convey the cyclical Pacific Northwest rainfall pattern
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- Full theme adaptation in both renders — no dark-on-dark or light-on-light failures;
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all chrome correctly flips while data colors remain constant
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- Code is clean, deterministic, and correctly follows pygal idioms; sys.path workaround
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is handled and documented
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- Both PNG and HTML outputs generated as required for an interactive library
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- Radial value labels include mm units, providing clear quantitative reference without
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an additional axis label
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weaknesses:
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- pygal.Radar renders connected polygon outlines between spokes rather than discrete
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equal-angle wedge segments — structurally different from a rose/Nightingale chart
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which should look like individual petals
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- Summer months (Jun-Aug, values 20-50 mm) collapse close to the center, making
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those segments difficult to read visually
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- Legend positioned at bottom with limited padding from chart boundary; for a radial
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chart a side legend or embedded labels would read better
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- Implementation file contains a single chart.add call but rendered images show
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four seasonal series — verify images correspond to committed code
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image_description: |-
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Light render (plot-light.png):
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Background: Warm off-white #FAF8F1 — correct, not pure white
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Chrome: Title "rose-basic · pygal · anyplot.ai" in dark ink at top — readable. Month labels (Jan–Dec) around perimeter in dark text — readable. Radial value labels ("0.0 mm", "40.0 mm", "80.0 mm", "120.0 mm", "160.0 mm") visible inside chart along vertical spoke — readable but slightly crowded at inner rings. Legend at bottom with 4 entries in dark text — readable.
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Data: Four seasonal polygons — Winter (Dec–Feb) in #009E73 teal dominant in upper half; Spring (Mar–May) in #D55E00 orange on left; Summer (Jun–Aug) in #0072B2 blue very small near center; Fall (Sep–Nov) in #CC79A7 reddish-purple on right. First series is #009E73. All data colors are Okabe-Ito.
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Legibility verdict: PASS
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Dark render (plot-dark.png):
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Background: Warm near-black #1A1A17 — correct, not pure black
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Chrome: Title in light text — readable. Month labels in light gray — readable. Radial value labels in lighter tone — visible. Legend text is light — readable. Grid spokes and concentric rings are faint light lines against dark background. No dark-on-dark failures observed.
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Data: Colors identical to light render — all four Okabe-Ito colors unchanged. Polygon shapes and proportions unchanged between themes. Summer polygon barely visible but present.
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Legibility verdict: PASS
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criteria_checklist:
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visual_quality:
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score: 25
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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: 6
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max: 8
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passed: true
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comment: Font sizes explicitly set (72/52/44/36); all labels readable in both
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themes; inner radial ring value labels slightly crowded at smallest rings
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- id: VQ-02
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name: No Overlap
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score: 5
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max: 6
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passed: true
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comment: No collisions; May label slightly rotated but readable; legend organized
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in two columns
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- id: VQ-03
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name: Element Visibility
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score: 5
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max: 6
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passed: true
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comment: Four seasonal polygons visible; Summer (Jun-Aug, 20-50mm) collapses
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near center but still distinguishable
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- id: VQ-04
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name: Color Accessibility
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score: 2
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max: 2
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passed: true
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comment: Okabe-Ito palette CVD-safe; four distinct hues with adequate contrast
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- id: VQ-05
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name: Layout & Canvas
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score: 3
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max: 4
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passed: true
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comment: Square 3600x3600 appropriate for polar chart; legend at bottom consumes
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vertical space slightly reducing chart area
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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: Title format correct; radial value labels include mm unit
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- id: VQ-07
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name: Palette Compliance
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score: 2
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max: 2
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passed: true
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comment: 'First series is #009E73; Okabe-Ito order followed; backgrounds #FAF8F1/#1A1A17
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correct; data colors identical between themes'
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design_excellence:
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score: 12
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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: false
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comment: Seasonal groupings show design intent; 0.75 opacity adds depth; custom
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Okabe-Ito palette applied; largely generic pygal radar defaults
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- id: DE-02
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name: Visual Refinement
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score: 3
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max: 6
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passed: false
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comment: Clean layout with adequate margins; outer radar frame and concentric
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gridlines are standard defaults with minimal customization
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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: Seasonal grouping creates clear Pacific Northwest rainfall narrative;
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Winter dominance immediately apparent; cyclical pattern reads naturally
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spec_compliance:
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score: 12
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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: 3
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max: 5
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passed: false
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comment: pygal.Radar is closest available approximation; not a true rose/coxcomb
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chart — radar polygon differs fundamentally from discrete wedge segments
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- id: SC-02
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name: Required Features
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score: 3
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max: 4
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passed: false
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comment: Circular arrangement, radius proportional to value, radial gridlines
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at 40mm intervals; missing discrete wedge segments
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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: Months on angular axis, rainfall determines radial extent, all 12
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months shown
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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: rose-basic · pygal · anyplot.ai format correct; legend labels match
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seasonal groupings
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data_quality:
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score: 14
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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: 5
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max: 6
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passed: true
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comment: Cyclical annual pattern clear; seasonal groupings show all aspects;
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individual month identity slightly obscured by connected polygon vs discrete
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wedge
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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: Pacific Northwest monthly rainfall (20-155mm) realistic, plausible,
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and neutral
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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: Range 0-170mm sensible for rainfall domain; values representative
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of actual Pacific Northwest precipitation
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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: No functions or classes; clean top-level script
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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: Hardcoded static data; fully deterministic
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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 used imports: os, sys, pygal, pygal.style.Style'
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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: Appropriate complexity; sys.path workaround necessary and documented
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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
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library_mastery:
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score: 7
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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: Proper pygal.Radar with Style object; theme tokens applied through
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foreground/foreground_strong/foreground_subtle; fill=True, show_dots=False,
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range, legend_at_bottom are correct radar params
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- id: LM-02
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name: Distinctive Features
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score: 3
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max: 5
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passed: false
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comment: Interactive HTML export (pygal key differentiator) generated alongside
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PNG; limited use of additional pygal-specific capabilities
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verdict: APPROVED
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impl_tags:
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dependencies: []
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techniques:
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- html-export
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patterns:
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- data-generation
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patterns: []
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dataprep: []
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styling: []
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review:
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strengths:
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- Excellent data choice with realistic Pacific Northwest rainfall pattern showing
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clear seasonal cyclicality
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- Code is clean, well-commented, and explains the radar-vs-rose limitation honestly
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- Good font sizing for the 3600×3600 canvas
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- Proper title format following pyplots conventions
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- Effective use of pygal styling system with custom colors and font sizes
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- Transparent fill (opacity=0.75) allows gridlines to remain visible
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weaknesses:
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- Radar chart is fundamentally different from rose chart (connected polygon vs discrete
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wedges) - this is a library limitation
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- Legend placement in bottom-left corner is disconnected from the chart with excessive
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whitespace
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- Month labels could be more prominently sized for 3600×3600 canvas
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styling:
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- alpha-blending

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