feat(ggplot2): implement swarm-basic

[github-actions]

Implementation: swarm-basic - r/ggplot2

Implements the r/ggplot2 version of swarm-basic.

File: plots/swarm-basic/implementations/r/ggplot2.R

Parent Issue: #974

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

Light render (plot-light.png): Warm off-white background (#FAF8F1-matching), with the mandated title "swarm-basic · r · ggplot2 · anyplot.ai" and axis titles "Experimental Condition" / "Reaction Time (ms)" in dark ink, tick labels in a softer grey ink, only subtle horizontal grid lines and an L-shaped axis frame. Four swarm clusters (Baseline, Low Load, High Load, Time Pressure) are colored in canonical Imprint order (green, lavender, blue, ochre) with a black diamond mean marker per cluster; reaction times visibly increase left to right. All text is clearly readable against the light background.

Dark render (plot-dark.png): Warm near-black background (#1A1A17-matching); title, axis titles, and tick labels flip to light/near-white ink and remain fully legible — no dark-on-dark failures. Grid lines stay subtle but visible. The four cluster colors are identical to the light render (green, lavender, blue, ochre — only chrome changed), and the mean-marker diamond correctly flips from black to white to stay visible on the darker surface.

Both paragraphs confirmed — all text readable in both themes, no dark-on-dark or light-on-light issues found.

Score: 87/100

Category	Score	Max
Visual Quality	26	30
Design Excellence	13	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	10	10
Library Mastery	8	10
Total	87	100

Visual Quality (26/30)

• VQ-01: Text Legibility (7/8) — all text explicitly sized and readable in both themes
• VQ-02: No Overlap (4/6) — same-color markers lack an edge stroke and blend into solid bands in the densest value bins (e.g. High Load ~508–555ms)
• VQ-03: Element Visibility (5/6) — markers/mean diamonds clearly visible; size 2.6 is only the medium-density default for n=45/group, just under the sparse threshold
• VQ-04: Color Accessibility (2/2)
• VQ-05: Layout & Canvas (4/4) — correct 3200×1800 canvas, balanced margins, nothing clipped
• VQ-06: Axis Labels & Title (2/2) — descriptive, with units
• VQ-07: Palette Compliance (2/2) — canonical Imprint order, correct theme-adaptive backgrounds

Design Excellence (13/20)

• DE-01: Aesthetic Sophistication (6/8) - Custom beeswarm-approximation layout and mean markers show above-default craft
• DE-02: Visual Refinement (3/6) - Spines/grid subtle and minimal, but missing the style guide's recommended white/bg edge stroke on overlapping markers
• DE-03: Data Storytelling (4/6) - Clear increasing-difficulty trend and mean markers, but no explicit connector/annotation reinforcing it

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) — faithful swarm/beeswarm approximation
• SC-02: Required Features (4/4) — consistent point sizes, mean markers, color-coded categories, clear spacing
• SC-03: Data Mapping (3/3)
• SC-04: Title & Legend (3/3) — correct mandated title; legend correctly omitted as redundant with x-axis labels

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) — individual points, distribution shape, and mean markers all present
• DQ-02: Realistic Context (5/5) — plausible, neutral cognitive-load reaction-time experiment
• DQ-03: Appropriate Scale (4/4)

Code Quality (10/10)

• CQ-01: KISS Structure (3/3)
• CQ-02: Reproducibility (2/2) — set.seed(42)
• CQ-03: Clean Imports (2/2)
• CQ-04: Code Elegance (2/2)
• CQ-05: Output & API (1/1)

Library Mastery (8/10)

• LM-01: Idiomatic Usage (4/5) — standard dplyr/ggplot2 grammar
• LM-02: Distinctive Features (4/5) - Hand-built value-binning beeswarm approximation is a distinctive workaround for ggplot2's missing native geom

Score Caps Applied

• None

Strengths

• Custom-built swarm/beeswarm approximation (value-binning + rank-based symmetric x-offset) — a genuine technical achievement given ggplot2 has no native beeswarm geom, with clear code comments explaining the approach.
• Correct Imprint palette usage in canonical order across the 4 categories, with theme-adaptive chrome correctly threaded through both renders.
• Per-category mean markers (diamond) directly answer the spec's suggestion to add a mean/median indicator, correctly recolored per theme.
• Clean, KISS-structured code, reproducible via set.seed(42), correct ragg::agg_png device and plot-{THEME}.png naming.
• Realistic, neutral psychology reaction-time dataset with a clear increasing-difficulty narrative across the four conditions.

Weaknesses

• Overlapping same-color points in dense clusters blend into solid bands because markers have no edge/stroke — add a subtle stroke (e.g. shape=21, fill=condition color, color=PAGE_BG, stroke~0.3) so individual points stay separated in dense regions.
• At n=45 points per condition (just under the "sparse <50" threshold), marker size (2.6) only matches the medium-density default — bump to ~3.0–3.2 alongside the edge stroke above for more prominence.
• No visual connector or annotation makes the increasing-reaction-time trend explicit beyond the diamond mean markers — a subtle mean-to-mean guide line or brief callout would sharpen the data storytelling.

Issues Found

1. VQ-02 / DE-02 MEDIUM: Overlapping same-color markers with no edge stroke blend into solid bands in the densest value bins
   • Fix: Use geom_point(shape = 21, fill = condition_color, color = PAGE_BG, stroke = 0.3, ...) (or a low-alpha theme-ink edge) so individual points remain distinguishable where the swarm is densest.
2. DE-03 LOW: Trend across conditions relies solely on point position/mean markers
   • Fix: Consider a subtle line connecting the four mean diamonds, or a light annotation, to make the increasing-reaction-time narrative more explicit.

AI Feedback for Next Attempt

Add a subtle edge stroke (white or PAGE_BG) to the swarm markers so overlapping same-color points stay individually distinguishable in the densest bins, and consider slightly larger markers (~3.0-3.2) given n=45/condition. Optionally connect or annotate the per-condition mean markers to make the increasing-reaction-time trend explicit.

Verdict: APPROVED

[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), not pure white. Title "swarm-basic · r · ggplot2 · anyplot.ai" top-left in dark ink, axis titles "Experimental Condition" / "Reaction Time (ms)" in dark ink, tick labels in soft grey-ink, subtle horizontal gridlines only. Four category swarms (Baseline, Low Load, High Load, Time Pressure) rendered as filled circles in canonical Imprint order — #009E73, #C475FD, #4467A3, #BD8233 — first series correctly green. A dark diamond mean-marker sits at the center of each swarm. All text is clearly readable against the light background.

Dark render (plot-dark.png): Warm near-black background (~#1A1A17), not pure black. Same chrome now flipped to light ink (#F0EFE8 titles, #B8B7B0 ticks) — no dark-on-dark anywhere, all text legible. Data colors are pixel-identical to the light render (confirmed the four category hues did not shift), and the mean diamonds correctly flip to a light marker color against the dark surface.

Both renders pass the theme-readability check. One issue found in both renders (see Weaknesses): the dashed mean-trend connector line between the four diamond markers does not actually render — pixel-level inspection confirms zero line pixels anywhere along its path in either theme, only the diamonds themselves are visible.

Score: 84/100

Category	Score	Max
Visual Quality	24	30
Design Excellence	14	20
Spec Compliance	15	15
Data Quality	14	15
Code Quality	9	10
Library Mastery	8	10
Total	84	100

Visual Quality (24/30)

• VQ-01: Text Legibility (7/8)
• VQ-02: No Overlap (4/6) - points overlap noticeably in the denser High Load / Time Pressure clusters
• VQ-03: Element Visibility (3/6) - mean-trend connector line does not render in either theme
• VQ-04: Color Accessibility (2/2)
• VQ-05: Layout & Canvas (4/4)
• VQ-06: Axis Labels & Title (2/2)
• VQ-07: Palette Compliance (2/2)

Design Excellence (14/20)

• DE-01: Aesthetic Sophistication (6/8) - custom beeswarm binning algorithm, polished diamond mean markers
• DE-02: Visual Refinement (5/6) - spines removed, subtle grid, generous whitespace
• DE-03: Data Storytelling (3/6) - escalating trend is visible from swarm position/color, but the invisible connector line weakens the intended storytelling guide

Spec Compliance (15/15)

• SC-01: Plot Type (5/5)
• SC-02: Required Features (4/4)
• SC-03: Data Mapping (3/3)
• SC-04: Title & Legend (3/3)

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6)
• DQ-02: Realistic Context (5/5)
• DQ-03: Appropriate Scale (4/4)

Code Quality (9/10)

• CQ-01: KISS Structure (3/3)
• CQ-02: Reproducibility (2/2)
• CQ-03: Clean Imports (2/2)
• CQ-04: Code Elegance (1/2) - the geom_line mean-connector layer is dead code (renders nothing)
• CQ-05: Output & API (1/1)

Library Mastery (8/10)

• LM-01: Idiomatic Usage (4/5)
• LM-02: Distinctive Features (4/5) - manual bin-and-rank beeswarm approximation is a genuinely distinctive technique given ggplot2 has no native beeswarm geom

Score Caps Applied

• None

Strengths

• Clever custom beeswarm layout built entirely from geom_point (bin the value axis, then rank and symmetrically offset points within each bin) since ggplot2 has no native beeswarm geom — a genuine library-mastery technique.
• Imprint palette applied correctly in canonical order with first series #009E73; theme-adaptive chrome (background, ink, grid) flips correctly between light and dark while data colors stay identical.
• Strong spec compliance: correct title format, descriptive axis labels with units, per-category mean markers, clear spacing between category groups, realistic psychology reaction-time dataset with plausible escalating means across cognitive-load conditions.
• Correct 3200×1800 canvas, theme_minimal with spines/heavy grid stripped, generous whitespace, explicit font sizes throughout.

Weaknesses

• The dashed mean-trend connector (geom_line over condition_means, color = scales::alpha(INK, 0.4)) does not render at all in either theme — pixel-level inspection of both PNGs found zero line pixels anywhere between the four mean-diamond markers, only the diamonds themselves are visible. This is dead/non-functional code; either fix the rendering (verify the 8-digit alpha hex string is honoured by the ragg device, check the layer isn't being clipped or dropped) or remove the geom_line layer entirely since the diamond markers alone already satisfy the spec's "subtle mean marker" note.
• Points overlap fairly densely in the Low Load / High Load / Time Pressure clusters at fill alpha = 0.85, making some individual observations hard to distinguish at the busiest bins — slightly smaller point_spacing or a touch more alpha reduction would improve separation.
• No legend for the categorical fill (guide = "none") — acceptable since x-axis tick labels already identify each category, but worth confirming this is the intended encoding.

Issues Found

1. VQ-03 / CQ-04 MODERATE: geom_line mean-trend connector renders nothing in either theme (confirmed via pixel inspection — zero non-background pixels along its expected path)
   • Fix: Debug why the dashed line isn't appearing (color-alpha string parsing, z-order/clipping) or remove the layer.
2. VQ-02 LOW: Points overlap noticeably in the denser clusters (High Load, Time Pressure)
   • Fix: Slightly reduce point_spacing/increase max_offset, or reduce fill alpha a touch further to improve individual-point separation.

AI Feedback for Next Attempt

Investigate and fix (or remove) the non-rendering geom_line mean-connector — it is present in the code but produces zero visible pixels in both themes. Otherwise this is a strong, spec-compliant implementation with a genuinely distinctive custom beeswarm technique; tightening point spacing in the busiest clusters would further help readability.

Verdict: APPROVED