feat(ggplot2): implement ohlc-bar

[github-actions]

Implementation: ohlc-bar - r/ggplot2

Implements the r/ggplot2 version of ohlc-bar.

File: plots/ohlc-bar/implementations/r/ggplot2.R

Parent Issue: #3293

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

Light render (`plot-light.png): Identical data visualization with colors preserved—green and orange bars remain #009E73 and #D55E00 respectively. Chrome has flipped to light text on warm near-black background (#1A1A17), with grid lines now subtle light gray. All text remains clearly readable with no dark-on-dark failures. Background, title, axis labels, and grid all properly theme-adapted while data colors stay constant.

Both renders are readable and theme-compliant. ✓

Score: 88/100

Category	Score	Max
Visual Quality	30	30
Design Excellence	10	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	10	10
Library Mastery	8	10
Total	88	100

Visual Quality (30/30)

• VQ-01: Text Legibility (8/8) - All sizes explicit (24/20/16pt), perfect readability both themes
• VQ-02: No Overlap (6/6) - X-labels rotated 45°, no collisions
• VQ-03: Element Visibility (6/6) - Bars and ticks optimally sized for 45-point data density
• VQ-04: Color Accessibility (2/2) - Okabe-Ito palette, excellent contrast
• VQ-05: Layout & Canvas (4/4) - Good utilization (60-70%), balanced margins
• VQ-06: Axis Labels & Title (2/2) - "Date", "Price ($)" — descriptive with units
• VQ-07: Palette Compliance (2/2) - Perfect: #009E73 up bars, #D55E00 down bars, backgrounds #FAF8F1/#1A1A17, theme-correct text in both renders

Design Excellence (10/20)

• DE-01: Aesthetic Sophistication (4/8) - Well-configured library default (theme_minimal), no custom design sophistication
• DE-02: Visual Refinement (4/6) - Clean minimal grid (Y-axis only), good whitespace, basic customization
• DE-03: Data Storytelling (2/6) - Color distinction shows up/down, but no visual hierarchy or advanced emphasis

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) - Correct OHLC: vertical bars for high-low, left/right ticks for open/close
• SC-02: Required Features (4/4) - Thin lines, ticks, up/down colors, date axis, price grid
• SC-03: Data Mapping (3/3) - X=dates, Y=prices, all data visible
• SC-04: Title & Legend (3/3) - Format correct; legend removed (appropriate for binary categorical)

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) - Mix of up (green) and down (orange) bars, realistic trend, volatility
• DQ-02: Realistic Context (5/5) - Stock prices ($150–175), realistic daily moves (0.1–2%), plausible scenario
• DQ-03: Appropriate Scale (4/4) - Factually sound stock price magnitudes and volatility

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) - Theme setup → Data → Segments → Plot → Save, no functions
• CQ-02: Reproducibility (2/2) - set.seed(42)
• CQ-03: Clean Imports (2/2) - ggplot2, dplyr, ragg all used
• CQ-04: Code Elegance (2/2) - Clean ggplot2 idioms, proper theme composition, no fake UI
• CQ-05: Output & API (1/1) - Saves plot-{THEME}.png, ragg device, current API

Library Mastery (8/10)

• LM-01: Idiomatic Usage (5/5) - Expert ggplot2: grammar of graphics, theme composition, segment-based rendering, dplyr piping
• LM-02: Distinctive Features (3/5) - Uses segment layers appropriately for OHLC, but similar approaches available in other libraries

Score Caps Applied

• None — all pass threshold checks

Strengths

• Perfect visual quality and readability in both light and dark themes
• Excellent data quality with realistic stock-price patterns and proper trend generation
• All spec requirements met with correct OHLC bar implementation
• Clean, idiomatic ggplot2 code with proper theme-token handling and environment-based rendering
• Perfect palette compliance (Okabe-Ito with correct up/down distinction)

Weaknesses

• Design Excellence is generic — relies on library defaults with minimal custom sophistication
• Visual refinement could be improved beyond minimal theming
• No advanced visual hierarchy or emphasis techniques beyond the required up/down color distinction

Issues Found

1. DE-01 LOW (4/8): Generic styling with default aesthetic
   • Fix: Add more sophisticated design touches — consider alpha-blending effects, refined typography weight variation, or custom color enhancements beyond Okabe-Ito
2. DE-02 MODERATE (4/6): Basic visual refinement
   • Fix: Experiment with spine removal for cleaner look, grid opacity fine-tuning, or whitespace enhancement
3. DE-03 LOW (2/6): No advanced data storytelling
   • Fix: Consider visual techniques to emphasize market direction — e.g., subtle color intensity variation, size modulation, or strategic data highlighting

AI Feedback for Next Attempt

The implementation is technically excellent with perfect visual quality and spec compliance. To reach 90+, focus on Design Excellence: move beyond library defaults with more sophisticated styling choices, refine visual hierarchy (grid, spines, typography weights), and add subtle emphasis techniques that help viewers see the overall market direction or price trend more immediately. Consider theme enhancements like custom spine styling, gradient backgrounds (subtle), or refined typography hierarchy that elevates this from "default ggplot2" to "publication-ready design."

Verdict: REJECTED

Review 1 threshold is ≥90; score of 88 does not meet this requirement. Plot will APPROVED at Review 2 (≥80 threshold). Recommend design refinements above for the repair attempt.

[github-actions]

🔧 Repair Attempt 1/4

Applied fixes based on AI review feedback.

Status: Repair completed, re-triggering review...

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🤖 impl-repair

[claude]

AI Review - Attempt 2/3

Image Description

Light render (plot-light.png): Warm off-white background (#FAF8F1) with title "ohlc-bar · ggplot2 · anyplot.ai" in bold dark text (24pt, clearly readable). Axis labels "Date" (x) and "Price ($)" (y) in bold dark (20pt). Tick labels in soft dark gray (16pt, #4A4A44) with date rotation at 45° for clarity. OHLC bars rendered correctly with green (#009E73) for up-bars and orange (#D55E00) for down-bars. Vertical lines show high-low range, horizontal ticks on left (open) and right (close). Opacity variation indicates volatility. Y-axis grid subtle and appropriate. Dotted trend line shows 7-day moving average in INK_SOFT. All text readable, excellent contrast, no overlaps.

Dark render (plot-dark.png): Warm near-black background (#1A1A17) with identical layout. Title in light text (24pt, #F0EFE8), clearly visible. Axis labels in light text (20pt), tick labels in light gray (#B8B7B0, 16pt) - all readable with excellent contrast on dark surface. Data colors identical to light render (green #009E73 and orange #D55E00 preserved perfectly). Vertical and horizontal segments properly colored and visible. Opacity variation maintained for volatility. Dotted trend line visible. Y-axis grid properly themed. No dark-on-dark failures detected.

Score: 87/100

Category	Score	Max
Visual Quality	30	30
Design Excellence	10	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	10	10
Library Mastery	7	10
Total	87	100

Visual Quality (30/30)

• VQ-01: Text Legibility (8/8) - Title (24pt), axis labels (20pt), tick labels (16pt) all explicitly sized and readable in both themes with proper theme-adaptive colors
• VQ-02: No Overlap (6/6) - Date labels rotated 45° for clarity, no text collisions, bars properly spaced
• VQ-03: Element Visibility (6/6) - All OHLC elements clearly visible (vertical lines, ticks, opacity variation shows volatility adaptation)
• VQ-04: Color Accessibility (2/2) - Okabe-Ito palette (up=#009E73, down=#D55E00) CVD-safe with high contrast
• VQ-05: Layout & Canvas (4/4) - 16:9 landscape with good proportions, nothing cut off, generous whitespace
• VQ-06: Axis Labels & Title (2/2) - Descriptive labels with units (Price $), title format correct
• VQ-07: Palette Compliance (2/2) - First series #009E73, second #D55E00, backgrounds #FAF8F1 light/#1A1A17 dark, theme-correct chrome

Design Excellence (10/20)

• DE-01: Aesthetic Sophistication (5/8) - Theme tokens properly applied, opacity variation thoughtful, but relies on theme_minimal defaults (raised from 4 for volatility feature)
• DE-02: Visual Refinement (3/6) - Grid subtle and Y-axis only (good), but no spine removal or extra refinements
• DE-03: Data Storytelling (2/6) - Moving average provides trend context, color coding is clear, but no strong visual hierarchy or focal point

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) - Correct OHLC bar chart implementation
• SC-02: Required Features (4/4) - Vertical high-low range, left open tick, right close tick, up/down color differentiation
• SC-03: Data Mapping (3/3) - X=date, Y=price with correct axis ranges
• SC-04: Title & Legend (3/3) - Title format correct, legend appropriately omitted

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) - All OHLC aspects (open, high, low, close) shown across 45 trading days
• DQ-02: Realistic Context (5/5) - Stock price data realistic (starting ~$150, realistic volatility and intraday variation)
• DQ-03: Appropriate Scale (4/4) - Price range $150-$173 sensible for daily stock data

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) - No unnecessary functions/classes, straightforward data generation
• CQ-02: Reproducibility (2/2) - Uses set.seed(42) for reproducible synthetic data
• CQ-03: Clean Imports (2/2) - Only necessary imports: ggplot2, dplyr, ragg
• CQ-04: Code Elegance (2/2) - Appropriate complexity, uses geom_segment idiomatically for OHLC, no fake UI
• CQ-05: Output & API (1/1) - Saves as plot-{THEME}.png with ragg::agg_png device

Library Mastery (7/10)

• LM-01: Idiomatic Usage (5/5) - Proper ggplot2 patterns: geom_segment for custom lines, theme_minimal + layered theme, aes() mappings, scale_color_manual, scale_alpha_identity()
• LM-02: Distinctive Features (2/5) - Uses geom_segment creatively for OHLC and demonstrates theme-adaptive design (raised from 1)

Score Caps Applied

• None - all criteria well above caps

Strengths

• Proper theme-adaptive design with correct color token usage (INK, INK_SOFT, BORDER_COL, GRID_COL)
• OHLC bars correctly implemented with vertical high-low lines and open-close ticks matching specification
• Excellent legibility in both light and dark themes with no theme-readability failures
• Data colors consistent across themes (Okabe-Ito compliant #009E73 and #D55E00 identical)
• Smart opacity variation by volatility adds visual sophistication and data insight
• Clean, idiomatic ggplot2 code with proper geom_segment usage for custom line segments
• Reproducible data generation with set.seed(42) for consistent output
• 7-day moving average provides useful context line for trend visualization

Weaknesses

• Design is functional but lacks distinctive polish - relies heavily on theme_minimal defaults
• No visual hierarchy or emphasis technique to create a focal point
• Panel border present but spines not explicitly addressed (no removal/customization decision)
• Moving average styling is subtle but could benefit from more design intentionality

Issues Found

None - no blocking issues. All implementation requirements met. Design is competent and functional.

AI Feedback for Next Attempt

This implementation is solid and ready for production. All technical requirements met, legibility excellent in both themes, code clean and idiomatic. If future regenerations are needed, consider: adding subtle spine removal (top/right) for cleaner aesthetic, emphasizing the moving average with a more distinctive color or style, or adding subtle annotations to key price points.

Verdict: APPROVED