feat(plotly): implement sequence-logo-basic

[github-actions]

Implementation: sequence-logo-basic - plotly

Implements the plotly version of sequence-logo-basic.

File: plots/sequence-logo-basic/implementations/plotly.py

Parent Issue: #4421

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a stacked bar chart approximating a DNA sequence logo for a 10-position transcription factor binding site. Each position has colored bars representing nucleotides: A (green), C (blue), G (orange), T (red). White bold letter annotations are overlaid on each bar segment. The y-axis shows "Information content (bits)" ranging 0–2, and the x-axis shows "Position" 1–10. Position 4 is empty (zero information content due to equal frequencies). Highly conserved positions (1, 3, 7) have tall stacks (~1.0–1.2 bits), while others are shorter. A horizontal legend for A, C, G, T sits above the plot. The title reads "sequence-logo-basic · plotly · pyplots.ai". The background is white with very subtle horizontal gridlines.

Score: 75/100

Category	Score	Max
Visual Quality	23	30
Design Excellence	10	20
Spec Compliance	12	15
Data Quality	14	15
Code Quality	10	10
Library Mastery	6	10
Total	75	100

Visual Quality (23/30)

• VQ-01: Text Legibility (7/8) — Font sizes explicitly set for title (28), axis labels (22), ticks (18), legend (18). Letter annotations use dynamic sizing (14–36) and are readable on large bars but small on tiny segments.
• VQ-02: No Overlap (4/6) — At positions with many small segments (e.g., position 10), letter annotations are cramped and partially overlap each other. Bottom-of-stack letters at low-IC positions are crowded.
• VQ-03: Element Visibility (4/6) — Bar segments are visible, but very small segments (particularly at positions with low IC) are barely distinguishable. The thin slivers at the bottom of stacks are hard to interpret.
• VQ-04: Color Accessibility (3/4) — Uses green/blue/orange/red per the spec's DNA convention. Green and red are distinguishable here due to brightness differences, but the green-red pairing is not ideal for deuteranopia.
• VQ-05: Layout & Canvas (3/4) — Good proportions, margins explicitly set, plot fills reasonable canvas area. Slight wasted space in the upper portion since max IC is ~1.2 bits but y-axis goes to 2.1.
• VQ-06: Axis Labels & Title (2/2) — "Position" and "Information content (bits)" — descriptive with units.

Design Excellence (10/20)

• DE-01: Aesthetic Sophistication (4/8) — Uses plotly_white template, standard DNA nucleotide colors, white text on colored bars. Well-configured but not exceptional — looks like a competent default.
• DE-02: Visual Refinement (3/6) — Some refinement: plotly_white background, subtle grid (rgba 0.06 opacity), only bottom/left axes, explicit margins. Above default but not fully polished.
• DE-03: Data Storytelling (3/6) — The varying bar heights naturally highlight conserved vs. variable positions. Position 4 (no IC) provides good contrast. Visual hierarchy is present through bar height differences.

Spec Compliance (12/15)

• SC-01: Plot Type (3/5) — The spec requires "letters rendered as scaled glyphs (stretched to fill their allocated height), not as plain text." The implementation uses stacked bars with text overlays, which is a reasonable Plotly approximation but not actual scaled letter glyphs. Correct base concept, missing the key variant.
• SC-02: Required Features (3/4) — Most features present: stacking by frequency, height proportional to IC, standard colors, ordering by frequency. Missing: actual glyph stretching.
• SC-03: Data Mapping (3/3) — X = position (1–10), Y = information content in bits. Correctly mapped.
• SC-04: Title & Legend (3/3) — Title "sequence-logo-basic · plotly · pyplots.ai" ✓. Legend shows A, C, G, T with correct colors ✓.

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6) — Shows highly conserved positions (1, 3, 7), a completely variable position (4), and moderate conservation (others). Good variation but could show positions closer to maximum 2-bit IC.
• DQ-02: Realistic Context (5/5) — Transcription factor binding site motif — genuine bioinformatics use case, neutral scientific context.
• DQ-03: Appropriate Scale (4/4) — IC values range 0 to ~1.17 bits, realistic for a DNA motif. Frequencies sum to 1 per position.

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — Clean Imports → Data → Plot → Save flow. No functions/classes.
• CQ-02: Reproducibility (2/2) — Deterministic hardcoded PWM data.
• CQ-03: Clean Imports (2/2) — Only numpy and plotly.graph_objects, both used.
• CQ-04: Code Elegance (2/2) — Clean, appropriate complexity. Loop structure is clear and readable.
• CQ-05: Output & API (1/1) — Saves as plot.png (1600×900, scale=3) and plot.html. Current API.

Library Mastery (6/10)

• LM-01: Idiomatic Usage (3/5) — Uses go.Bar with base parameter for stacking, add_annotation, update_layout. Correct but standard graph_objects patterns.
• LM-02: Distinctive Features (3/5) — Leverages Plotly-specific hover tooltips (hovertemplate) with position/frequency/height info, plus HTML export. These are distinctively Plotly features.

Score Caps Applied

• None applied

Strengths

• Clean, well-structured code with deterministic data and proper KISS layout
• Realistic bioinformatics data with good variation in conservation levels
• Correct information content calculation with proper entropy formula
• Good use of Plotly interactivity (hover tooltips showing frequency and height)
• Properly formatted title and legend following spec conventions

Weaknesses

• Uses stacked bars with text overlays instead of actual scaled letter glyphs — the defining visual feature of a sequence logo
• Small bar segments have cramped, overlapping letter annotations
• Y-axis range extends to 2.1 but max data is ~1.2, wasting upper canvas space
• Color palette follows spec convention but green-red pairing is not colorblind-optimal

Issues Found

1. SC-01 MEDIUM: Stacked bars instead of scaled letter glyphs — the spec explicitly says "Letters should be rendered as scaled glyphs (stretched to fill their allocated height), not as plain text"
   • Fix: Use Plotly shapes or SVG paths to render stretched letters, or use add_layout_image with dynamically generated letter images
2. VQ-02 MEDIUM: Letter annotations overlap in small segments at positions with low IC
   • Fix: Only show letter annotations when segment height exceeds a minimum threshold, or use hover-only labels for small segments
3. VQ-05 LOW: Y-axis range [0, 2.1] wastes space when max IC is ~1.2
   • Fix: Set y-axis range dynamically based on actual max IC with some padding

AI Feedback for Next Attempt

The main issue is that this renders as a stacked bar chart with text overlays, not as a true sequence logo with scaled letter glyphs. Consider using Plotly shapes or layout images to create stretched letters that fill their bar segments. Also address the overlapping text in small segments — either increase the minimum height threshold for showing annotations or use a smarter label placement strategy. Reduce the y-axis range to better utilize canvas space. For design, consider removing the top gridlines or making them even more subtle, and explore whether letter outlines (instead of white fill text) could improve readability.

Verdict: REJECTED

[github-actions]

🔧 Repair Attempt 1/3

Applied fixes based on AI review feedback.

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

---

🤖 impl-repair

[claude]

AI Review - Attempt 2/3

Image Description

The plot displays a 10-position DNA transcription factor binding site motif as a stacked bar chart approximation of a sequence logo. At each position, colored bars represent four nucleotides stacked vertically, with total stack height proportional to information content in bits. The colors are: A = teal/green (#009E73), C = blue (#0072B2), G = amber/orange (#E69F00), T = pink/mauve (#CC79A7). Bold white letter labels are overlaid on bars that are tall enough to be legible. Positions 3 and 7 have the highest conservation (~1.15 bits), while position 4 is nearly flat (uniform distribution, ~0 bits). A subtle gray "most conserved" annotation with a downward triangle marks position 3. The title reads "sequence-logo-basic · plotly · pyplots.ai" centered at the top, with a horizontal legend showing all four nucleotides. The background is white with a subtle dotted y-axis grid. X-axis labeled "Position" (1-10), y-axis labeled "Information content (bits)" (0-1.2).

Score: 80/100

Category	Score	Max
Visual Quality	27	30
Design Excellence	12	20
Spec Compliance	11	15
Data Quality	14	15
Code Quality	10	10
Library Mastery	6	10
Total	80	100

Visual Quality (27/30)

• VQ-01: Text Legibility (7/8) — All font sizes explicitly set (title 28, labels 22, ticks 18, letter annotations 16-42). Readable at full resolution. Minor deduction: some smaller letter annotations are on the small side.
• VQ-02: No Overlap (5/6) — Generally clean, but some smaller bar segments with letter annotations at positions 2, 9, 10 have letters that are slightly cramped relative to their bar height.
• VQ-03: Element Visibility (5/6) — Bars are clearly visible and well-sized. Bar width of 0.75 is appropriate. White letter annotations provide good contrast against colored bars.
• VQ-04: Color Accessibility (4/4) — Excellent colorblind-safe palette (Wong colors: teal, blue, amber, pink). Avoids red-green confusion entirely.
• VQ-05: Layout & Canvas (4/4) — Good proportions, plot fills canvas well. Margins are generous but not wasteful. Nothing cut off.
• VQ-06: Axis Labels & Title (2/2) — "Position" and "Information content (bits)" are descriptive with units.

Design Excellence (12/20)

• DE-01: Aesthetic Sophistication (5/8) — Thoughtful colorblind-safe palette (not defaults), clean typography with Arial Black for letter glyphs, white background. Above default configuration but not publication-exceptional.
• DE-02: Visual Refinement (4/6) — Plotly_white template, subtle dotted grid, only bottom/left axes with lines, generous whitespace. Good refinement visible.
• DE-03: Data Storytelling (3/6) — The "most conserved" annotation adds a focal point. Varying bar heights naturally tell the conservation story. Position 4 (uniform) provides contrast. Above default data display.

Spec Compliance (11/15)

• SC-01: Plot Type (3/5) — Uses stacked bars as a sequence logo approximation. The spec explicitly states "Letters should be rendered as scaled glyphs (stretched to fill their allocated height), not as plain text." Current implementation uses bars with text annotations overlaid, which is a reasonable Plotly workaround but not the specified glyph approach.
• SC-02: Required Features (2/4) — Has: vertical stacking ordered by frequency, IC calculation, colorblind-safe colors roughly mapping to spec. Missing: true stretched letter glyphs (spec requirement), T color is pink instead of red as specified.
• SC-03: Data Mapping (3/3) — X-axis shows positions 1-10, Y-axis shows IC in bits. All data correctly mapped. IC calculation is correct (2 + sum(f*log2(f))).
• SC-04: Title & Legend (3/3) — Title "sequence-logo-basic · plotly · pyplots.ai" is correct format. Legend shows all four nucleotides with matching colors.

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6) — Shows high conservation (pos 3, 7), low conservation (pos 4), medium conservation, and mixed positions. Good variety. Could show a position with ~2 bits (perfect conservation) for full range demonstration.
• DQ-02: Realistic Context (5/5) — Transcription factor binding site motif is a real-world bioinformatics application. Neutral scientific context.
• DQ-03: Appropriate Scale (4/4) — IC values range 0 to ~1.15 bits, well within the 0-2 bit range for DNA. Frequencies sum to 1 per position. Realistic PWM values.

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — Clean linear flow: imports → data → IC calculation → plot → style → save. No functions or classes.
• CQ-02: Reproducibility (2/2) — Fully deterministic with hardcoded position weight matrix.
• CQ-03: Clean Imports (2/2) — Only numpy and plotly.graph_objects, both used.
• CQ-04: Code Elegance (2/2) — Appropriate complexity. Loop over positions and sorted indices is clean. Font scaling logic is reasonable.
• CQ-05: Output & API (1/1) — Saves as plot.png (1600x900 scale=3 = 4800x2700) and plot.html. Current API.

Library Mastery (6/10)

• LM-01: Idiomatic Usage (3/5) — Uses go.Bar with base parameter for manual stacking, go.Figure, add_annotation, update_layout. Correct Plotly GO patterns but could leverage more advanced features.
• LM-02: Distinctive Features (3/5) — Interactive hover templates with position/nucleotide/frequency/height info are Plotly-distinctive. HTML export alongside PNG. Hoverlabel customization.

Score Caps Applied

• None

Strengths

• Excellent colorblind-safe palette (Wong colors) that avoids red-green confusion
• Clean data storytelling with "most conserved" annotation and position 4 contrast
• Perfect code quality: deterministic, clean structure, appropriate complexity
• Good interactive hover templates showing position, nucleotide, frequency, and IC
• Correct information content calculation with proper entropy formula

Weaknesses

• Letters are rendered as text annotations on bars, not as stretched glyphs filling their allocated height (spec explicitly requires scaled glyphs)
• T color is pink (#CC79A7) instead of red as specified in the standard color scheme
• No position reaches maximum conservation (~2 bits) in the example data, limiting range demonstration
• Library mastery could be stronger — consider using Plotly shapes or SVG paths for letter rendering

Issues Found

1. SC-01 MODERATE: Stacked bars with text overlay instead of true sequence logo with stretched letter glyphs
   • Fix: Use Plotly shapes (SVG paths) or scaled rectangle+text combinations to render letters that fill their allocated bar height, creating a more authentic sequence logo appearance
2. SC-02 LOW: T colored pink instead of red per standard sequence logo convention
   • Fix: Use a red shade for T (e.g., #D55E00 or #E74C3C) while maintaining colorblind safety
3. LM-01 MODERATE: Could leverage more Plotly-specific patterns
   • Fix: Consider using go.Shape for letter rendering or other advanced Plotly GO features

AI Feedback for Next Attempt

The main gap is that the spec explicitly requires letters rendered as scaled glyphs stretched to fill their height, not plain text on bars. For the next attempt, try rendering each letter as a Plotly shape or use SVG-based approaches to create stretched letters that fill each bar segment. Also change T from pink to a red shade (e.g., #D55E00) to match the standard DNA color scheme while staying colorblind-safe. These changes would significantly improve spec compliance and visual authenticity.

Verdict: REJECTED

[github-actions]

🔧 Repair Attempt 2/3

Applied fixes based on AI review feedback.

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

---

🤖 impl-repair

[claude]

AI Review - Attempt 3/3

Image Description

The plot displays a 10-position DNA transcription factor binding site as a true sequence logo with SVG-rendered letter glyphs. Each position shows stacked nucleotide letters (A, C, G, T) with height proportional to information content in bits. The letters are rendered as stretched SVG path shapes — not text overlays — creating an authentic sequence logo appearance. Colors follow the standard DNA scheme: A = teal-green (#009E73), C = blue (#0072B2), G = amber-orange (#E69F00), T = burnt-orange/red (#D55E00), all from the colorblind-safe Wong palette. Position 3 shows a tall blue C (~1.7 bits) and position 7 shows a tall red-orange T (~1.8 bits), both annotated with "▼ X.X bits" labels. Position 4 is empty (uniform distribution = 0 bits). The title "sequence-logo-basic · plotly · pyplots.ai" is centered at top. A horizontal legend (A, C, G, T) sits below the title. X-axis labeled "Position" (1–10), Y-axis labeled "Information content (bits)" (0–2.0). Background is white with subtle dotted y-grid lines. Only bottom and left axes are drawn.

Score: 87/100

Category	Score	Max
Visual Quality	28	30
Design Excellence	13	20
Spec Compliance	15	15
Data Quality	14	15
Code Quality	9	10
Library Mastery	8	10
Total	87	100

Visual Quality (28/30)

• VQ-01: Text Legibility (7/8) — Font sizes explicitly set: title 28pt, axis labels 22pt, ticks 18pt, legend 20pt. All clearly readable at 4800×2700. Minor deduction: conservation annotations at 13pt are on the small side.
• VQ-02: No Overlap (6/6) — No overlapping elements. Letters are well-spaced within their positions. Annotations above stacks clear of other content.
• VQ-03: Element Visibility (5/6) — Letter glyphs are clearly visible at most positions. SVG paths render well. Very small letters at low-IC positions (e.g., bottom of stacks at positions 8–10) are tiny but still discernible. Code properly filters out heights < 0.005.
• VQ-04: Color Accessibility (4/4) — Excellent colorblind-safe Wong palette. Green, blue, orange, burnt-orange — avoids red-green confusion entirely. High contrast against white background.
• VQ-05: Layout & Canvas (4/4) — Good proportions, plot fills canvas well. Y-axis to 2.1 is appropriate for DNA max of 2 bits. Margins generous but not wasteful. Nothing cut off.
• VQ-06: Axis Labels & Title (2/2) — "Position" and "Information content (bits)" — descriptive with units.

Design Excellence (13/20)

• DE-01: Aesthetic Sophistication (5/8) — Custom colorblind-safe Wong palette, clean Arial typography, plotly_white template. Clearly above configured defaults with intentional design choices. Not yet publication-exceptional.
• DE-02: Visual Refinement (4/6) — Good refinement: subtle dotted grid (rgba 0.05 opacity), only bottom/left axes with explicit linewidth, removed mirror, generous margins. Above default but could further polish (e.g., lighter tick marks, more whitespace).
• DE-03: Data Storytelling (4/6) — Conservation annotations with "▼ 1.7 bits" and "▼ 1.8 bits" create clear focal points. Empty position 4 provides contrast. Varying letter heights naturally guide the viewer through the conservation pattern.

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) — True sequence logo with SVG path letter glyphs stretched to fill their allocated height. This directly addresses the spec requirement: "Letters should be rendered as scaled glyphs (stretched to fill their allocated height), not as plain text."
• SC-02: Required Features (4/4) — All features present: vertical stacking ordered by frequency, IC-scaled heights, standard DNA colors (A=green, C=blue, G=orange, T=red), stretched letter glyphs.
• SC-03: Data Mapping (3/3) — X = position (1–10), Y = information content in bits. IC correctly calculated as 2 + Σ(f·log₂(f)).
• SC-04: Title & Legend (3/3) — Title "sequence-logo-basic · plotly · pyplots.ai" in correct format. Legend shows A, C, G, T with matching colors.

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6) — Shows high conservation (pos 3 ~1.7 bits, pos 7 ~1.8 bits), zero information (pos 4), and moderate conservation (other positions). Good variety. Could show a position at ~2 bits (near-perfect conservation) for full range.
• DQ-02: Realistic Context (5/5) — Transcription factor binding site motif — genuine bioinformatics context. Neutral scientific data.
• DQ-03: Appropriate Scale (4/4) — IC values range 0 to ~1.85 bits, realistic for a DNA motif. Frequencies sum to 1 per position. PWM values are biologically plausible.

Code Quality (9/10)

• CQ-01: KISS Structure (2/3) — Clean flow: imports → data → IC calculation → plotting → styling → save. However, includes a helper function svg_path_to_plotly() which breaks the no-functions KISS rule. The function is justified by the complexity of SVG path coordinate transformation but is still a deviation.
• CQ-02: Reproducibility (2/2) — Fully deterministic with hardcoded position weight matrix.
• CQ-03: Clean Imports (2/2) — Only numpy and plotly.graph_objects, both used.
• CQ-04: Code Elegance (2/2) — SVG path approach is complex but necessary. Invisible bars for hover interaction is a legitimate technique. Code is well-commented and readable.
• CQ-05: Output & API (1/1) — Saves plot.png (1600×900 scale=3 = 4800×2700) and plot.html. Current API.

Library Mastery (8/10)

• LM-01: Idiomatic Usage (4/5) — Advanced Plotly usage: go.Figure with add_shape for SVG paths in data coordinates, invisible go.Bar traces for hover, go.Scatter for custom legend, add_annotation. Demonstrates strong understanding of Plotly's shape and coordinate systems.
• LM-02: Distinctive Features (4/5) — SVG path shapes rendered in data coordinates is a distinctive Plotly capability. Interactive hover templates with nucleotide/frequency/height info. HTML export. Hoverlabel customization. These are features unique to Plotly.

Score Caps Applied

• None — no cap conditions triggered

Strengths

• True SVG path letter glyphs that stretch to fill their allocated height — authentic sequence logo rendering
• Excellent colorblind-safe Wong palette (green, blue, orange, burnt-orange)
• Conservation annotations at positions 3 and 7 create clear focal points
• Interactive hover templates showing position, nucleotide, frequency, and IC height
• Correct information content calculation with well-varied PWM data

Weaknesses

• Helper function svg_path_to_plotly() breaks KISS structure (though justified by complexity)
• Conservation annotation font size (13pt) could be larger for better readability
• No position reaches maximum 2-bit conservation, slightly limiting range demonstration

Issues Found

1. CQ-01 LOW: Helper function breaks no-functions KISS rule
   • Fix: Could inline the path transformation logic, though this would reduce readability
2. VQ-01 LOW: Conservation annotation text at 13pt is small relative to other text
   • Fix: Increase annotation font size to 15-16pt
3. DQ-01 LOW: No position demonstrates near-maximum (2-bit) conservation
   • Fix: Adjust one position (e.g., pos 7) to have ~0.99 frequency for the dominant nucleotide

AI Feedback for Next Attempt

Strong implementation that successfully renders true sequence logo letter glyphs using SVG paths. The main areas for improvement are design excellence — consider further polishing the grid styling, increasing annotation font size, and exploring whether subtle spine removal or background accents could elevate the aesthetic. The data could include a position with near-perfect conservation (~2 bits) to demonstrate the full range.

Verdict: REJECTED

[github-actions]

🔧 Repair Attempt 3/3

Applied fixes based on AI review feedback.

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

---

🤖 impl-repair

[claude]

AI Review - Attempt 3/3

Image Description

The plot shows a DNA sequence logo for a 10-position transcription factor binding site motif. Letters (A, C, G, T) are rendered as custom SVG-path glyphs stacked vertically at each position, with heights proportional to information content in bits. Position 3 has a tall blue C (~1.70 bits) and position 7 has a near-maximum-height orange/red T (~1.97 bits), both annotated with downward triangles and bit values. Position 4 is empty (zero information) with a "no signal" label below. The remaining positions show varying conservation levels with stacked letters of different sizes. Colors follow standard DNA conventions using Wong palette variants: A=green, C=blue, G=orange, T=red-orange. The title reads "sequence-logo-basic · plotly · pyplots.ai" centered at top with a horizontal legend (A, C, G, T squares) below it. X-axis labeled "Position" (1-10), Y-axis labeled "Information content (bits)" (0-2.0). Clean white background with subtle dotted y-grid lines.

Score: 86/100

Category	Score	Max
Visual Quality	27	30
Design Excellence	16	20
Spec Compliance	14	15
Data Quality	15	15
Code Quality	8	10
Library Mastery	6	10
Total	86	100

Visual Quality (27/30)

• VQ-01: Text Legibility (8/8) - All font sizes explicitly set: title 28, axis labels 22, ticks 18, annotations 16/13. All clearly readable.
• VQ-02: No Overlap (5/6) - Minor crowding at low-IC positions (9, 10) where small glyphs overlap slightly
• VQ-03: Element Visibility (5/6) - High-IC letters are excellent; low-IC positions have very small letters that are hard to distinguish
• VQ-04: Color Accessibility (4/4) - Wong palette variants are colorblind-safe with good contrast
• VQ-05: Layout & Canvas (3/4) - Good proportions overall; some vertical wasted space in the middle area
• VQ-06: Axis Labels & Title (2/2) - "Information content (bits)" and "Position" are descriptive with units

Design Excellence (16/20)

• DE-01: Aesthetic Sophistication (6/8) - Strong design with custom SVG letter glyphs, Wong palette, intentional color scheme (#1a1a2e dark accents), plotly_white template. Goes clearly beyond defaults.
• DE-02: Visual Refinement (5/6) - Spines only on bottom/left, subtle dotted y-grid, x-grid removed, generous whitespace, clean zeroline styling. Well-polished.
• DE-03: Data Storytelling (5/6) - Annotations highlight conserved positions (3 and 7), "no signal" label at position 4 creates contrast. Visual hierarchy through letter heights and annotations guides the viewer effectively.

Spec Compliance (14/15)

• SC-01: Plot Type (5/5) - Correct sequence logo with stacked letters proportional to information content
• SC-02: Required Features (3/4) - All major features present: vertical stacking by frequency, IC scaling, standard colors, axis labels. Position 7's T glyph appears somewhat rectangular at large scale rather than clearly T-shaped.
• SC-03: Data Mapping (3/3) - X-axis positions 1-10, Y-axis IC in bits 0-2.15. Correct mapping.
• SC-04: Title & Legend (3/3) - Title format correct "sequence-logo-basic · plotly · pyplots.ai". Legend shows A, C, G, T with matching colors.

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) - Excellent variety: highly conserved (pos 3, 7), moderate (pos 1, 5, 6), low conservation (pos 2, 8-10), and zero information (pos 4).
• DQ-02: Realistic Context (5/5) - Transcription factor binding site motif with biologically plausible PWM values
• DQ-03: Appropriate Scale (4/4) - IC values correct for DNA (max ~2 bits), frequencies sum to 1.0 per position

Code Quality (8/10)

• CQ-01: KISS Structure (2/3) - Follows imports → data → plot → save structure but the SVG path transformation loop adds significant inline complexity
• CQ-02: Reproducibility (2/2) - Fully deterministic hardcoded PWM data
• CQ-03: Clean Imports (2/2) - Only numpy and plotly.graph_objects, both used
• CQ-04: Code Elegance (1/2) - The SVG path parsing/transformation is clever but verbose and hard to follow
• CQ-05: Output & API (1/1) - Saves as plot.png at 4800x2700, also HTML. Current API.

Library Mastery (6/10)

• LM-01: Idiomatic Usage (3/5) - Uses go.Figure, go.Bar, go.Scatter, add_shape correctly. However, the heavy SVG path manipulation for letter glyphs is a workaround rather than idiomatic Plotly.
• LM-02: Distinctive Features (3/5) - Leverages Plotly's SVG shape system (add_shape with path data), interactive hover via invisible bars, and HTML export — features distinctive to Plotly.

Score Caps Applied

• None

Strengths

• Creative use of SVG path shapes to render stretched letter glyphs — achieves the spec requirement of "scaled glyphs, not plain text"
• Excellent data quality with biologically plausible PWM covering full range of conservation levels
• Strong design with thoughtful color scheme, annotations on conserved positions, and clean visual refinement
• Interactive hover tooltips provide nucleotide frequency details (distinctive Plotly feature)

Weaknesses

• SVG path transformation code is complex and verbose, reducing code readability
• Small letters at low-IC positions are hard to distinguish from each other
• Position 7's T glyph appears somewhat rectangular/block-like rather than clearly T-shaped at tall heights

Issues Found

1. CQ-01/CQ-04 MODERATE: SVG path inline transformation is complex — the while-loop token parser is hard to follow
   • Fix: Could pre-compute path transformations or use a helper approach to reduce inline complexity
2. VQ-02/VQ-03 MINOR: Small letter glyphs at positions 9-10 are crowded and hard to read
   • Fix: Consider a minimum height threshold or wider bar_width for better visibility
3. LM-01 MODERATE: Heavy manual SVG path manipulation is not idiomatic Plotly usage
   • Fix: Consider leveraging Plotly's text/annotation features or a more native approach

AI Feedback for Next Attempt

This is attempt 3/3. The implementation is solid at 86/100 — strong data quality, good design, and creative SVG glyph rendering. The main gaps are in code complexity (SVG path parsing) and library mastery (workaround-heavy approach). Since this is the final attempt, the score of 86 qualifies for merge.

Verdict: REJECTED