feat(pygal): implement sequence-logo-basic

[github-actions]

Implementation: sequence-logo-basic - pygal

Implements the pygal version of sequence-logo-basic.

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

Parent Issue: #4421

---

🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a stacked bar chart with 10 positions along the x-axis representing a DNA transcription factor binding site motif. Each position has stacked colored bars: green (A), blue (C), orange (G), and red (T). The y-axis shows "Information content (bits)" ranging from 0 to ~1.35. Position 4 has the highest stack (~1.35 bits, dominated by green/A), followed by positions 2-3 (dominated by orange/G) and positions 6-7 (dominated by red/T). Positions 8-10 have very low bars near zero, indicating low conservation. The title reads "sequence-logo-basic · pygal · pyplots.ai" at the top. A legend at the bottom shows A, C, G, T with colored squares. The background is white with subtle dotted horizontal grid lines. Bars have slightly rounded corners.

Score: 74/100

Category	Score	Max
Visual Quality	26	30
Design Excellence	9	20
Spec Compliance	11	15
Data Quality	14	15
Code Quality	9	10
Library Mastery	5	10
Total	74	100

Visual Quality (26/30)

• VQ-01: Text Legibility (7/8) — Font sizes explicitly set (title=28, labels=18, ticks=16). All text readable, though y-axis label is slightly small when rotated.
• VQ-02: No Overlap (6/6) — No overlapping text or elements anywhere.
• VQ-03: Element Visibility (5/6) — Bars at high-conservation positions are clearly visible. Bars at positions 8-10 are very thin but still discernible.
• VQ-04: Color Accessibility (3/4) — Standard DNA color scheme (green/blue/orange/red). Green and orange may be difficult for some colorblind viewers, but this is the conventional bioinformatics palette.
• VQ-05: Layout & Canvas (3/4) — Good overall proportions, but positions 8-10 have tiny bars creating visual imbalance with wasted vertical space on the right side.
• VQ-06: Axis Labels & Title (2/2) — "Position" and "Information content (bits)" both present with units.

Design Excellence (9/20)

• DE-01: Aesthetic Sophistication (4/8) — Custom DNA color palette applied, white background, legend at bottom. Looks like a well-configured default but not publication-ready.
• DE-02: Visual Refinement (3/6) — Subtle dotted grid lines, white background, rounded bar corners show some refinement beyond pure defaults.
• DE-03: Data Storytelling (2/6) — The data shows clear conserved vs. variable positions, but no visual emphasis or hierarchy guides the viewer to the key insight (the GGAATT core motif).

Spec Compliance (11/15)

• SC-01: Plot Type (3/5) — The spec requires a sequence logo with letter-shaped glyphs scaled to height. This is a stacked bar chart — correct data representation but missing the defining visual characteristic of a sequence logo. Pygal lacks native glyph rendering, but the stacked bar is the closest feasible approximation.
• SC-02: Required Features (2/4) — Has stacking by frequency, information content scaling, correct color scheme. Missing: letter glyphs rendered as scaled shapes (key spec requirement). Letters only appear in the legend, not within bars.
• SC-03: Data Mapping (3/3) — X-axis correctly maps to sequence position, Y-axis to information content in bits.
• SC-04: Title & Legend (3/3) — Title format "sequence-logo-basic · pygal · pyplots.ai" is correct. Legend labels match nucleotides A, C, G, T.

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6) — Shows both highly conserved positions (2-7) and variable positions (1, 8-10). Missing extreme cases like a position with maximum entropy (all equal frequencies).
• DQ-02: Realistic Context (5/5) — ETS transcription factor binding site motif is a real, well-characterized biological scenario commonly used in bioinformatics.
• DQ-03: Appropriate Scale (4/4) — Information content values 0-1.35 bits are realistic for DNA (theoretical max 2 bits). Frequencies sum to 1 per position.

Code Quality (9/10)

• CQ-01: KISS Structure (3/3) — Clean flat structure: imports → data → calculation → style → chart → save.
• CQ-02: Reproducibility (2/2) — Data is fully deterministic (hardcoded frequency dict).
• CQ-03: Clean Imports (2/2) — numpy, pygal, and Style are all used.
• CQ-04: Code Elegance (1/2) — Dead code: sorted_nts (line 46) is computed but never used. np.random.seed(42) is called but no random generation occurs.
• CQ-05: Output & API (1/1) — Saves as plot.png and plot.html. Current API usage.

Library Mastery (5/10)

• LM-01: Idiomatic Usage (3/5) — Correct use of pygal.StackedBar, Style customization, x_labels, legend_at_bottom. Standard pygal patterns.
• LM-02: Distinctive Features (2/5) — Uses rounded_bars and dual output (render_to_png + render_to_file for HTML), which are somewhat pygal-specific. Could leverage more pygal features like custom tooltips or value formatting.

Score Caps Applied

• None applied

Strengths

• Correct information content calculation with proper entropy formula
• Realistic ETS transcription factor binding site data from bioinformatics
• Clean code structure with appropriate data representation
• Correct title format and axis labels with units

Weaknesses

• Not a true sequence logo: missing letter-shaped glyphs (the defining feature of the visualization type)
• Dead code: unused sorted_nts variable and unnecessary np.random.seed(42)
• Design is functional but not visually refined — no visual hierarchy or storytelling emphasis
• Limited use of pygal-specific features

Issues Found

1. SC-01/SC-02 LOW: Stacked bar chart instead of sequence logo with letter glyphs
   • Fix: Consider adding text annotations within each bar segment showing the nucleotide letter, or explore pygal's SVG capabilities to render letter shapes
2. DE-01 LOW: Generic styling with configured defaults
   • Fix: Enhance with bolder color saturation, improved typography, and remove unnecessary grid lines
3. DE-03 LOW: No visual hierarchy or storytelling
   • Fix: Use color intensity or bar border emphasis to highlight the conserved core motif (positions 2-7)
4. CQ-04: Dead code present
   • Fix: Remove unused sorted_nts variable and unnecessary np.random.seed(42) call

AI Feedback for Next Attempt

The main gap is the missing letter glyphs — a sequence logo's defining feature. Consider adding nucleotide letter labels within or above each bar segment to approximate the logo effect. Remove dead code (sorted_nts, seed). Improve design: suppress y-axis grid except at 0/1/2, add visual emphasis on the conserved GGAATT core positions (2-7), and consider a stronger color palette with better saturation.

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 stacked bar chart with 10 positions along the x-axis representing a DNA transcription factor binding site motif (ETS family). Each position has stacked colored bars: green (A), blue (C), orange (G), and red/crimson (T). The y-axis shows "Information content (bits)" ranging from 0 to 1.60. The chart uses a white background with a very light gray (#fafafa) plot background and dashed horizontal grid lines. Positions 4 and 3 have the tallest stacks (~1.37 and ~1.15 bits, dominated by green/A and orange/G respectively). Positions 6 and 7 show tall red/T-dominated bars (~1.15 bits each). Positions 8, 9, and 10 have very short stacks near zero, indicating low conservation. Some bars display printed numeric values (0.78, 0.98, 1.24, 0.98, 0.98, 0.98) centered within larger segments. The title "sequence-logo-basic · pygal · pyplots.ai" appears at top. A legend at the bottom displays A, C, G, T in a single row with colored squares. Bars have slightly rounded corners (radius=3). Font sizes appear larger than attempt 1.

Score: 74/100

Category	Score	Max
Visual Quality	27	30
Design Excellence	10	20
Spec Compliance	11	15
Data Quality	14	15
Code Quality	10	10
Library Mastery	5	10
Total	77	100

Visual Quality (27/30)

• VQ-01: Text Legibility (8/8) — Font sizes explicitly set and increased: title=32, labels=20, major_labels=18, legend=20, value=16. All text clearly readable at full resolution.
• VQ-02: No Overlap (6/6) — No overlapping text or elements. Value labels only displayed when >= 0.15, avoiding clutter in small segments.
• VQ-03: Element Visibility (5/6) — High-conservation positions (2-7) have clearly visible, well-sized bars. Positions 8-10 have very thin segments that are hard to distinguish individually.
• VQ-04: Color Accessibility (3/4) — Standard DNA color scheme with improved saturation (#1b8a2e green, #2563eb blue, #e67e22 orange, #c0392b red). Conventional bioinformatics palette; green/orange distinction may still challenge deuteranopia viewers.
• VQ-05: Layout & Canvas (3/4) — Good proportions with explicit margins. The y-axis range goes to 1.6 while max data is ~1.37, creating some unused space at top. Positions 8-10 are nearly invisible creating right-side emptiness.
• VQ-06: Axis Labels & Title (2/2) — "Position" and "Information content (bits)" both present with proper units.

Design Excellence (10/20)

• DE-01: Aesthetic Sophistication (5/8) — Improved from attempt 1: deeper saturated DNA colors, custom opacity (0.92), monospace value font, light gray plot background. Shows design intent but still reads as a well-configured chart rather than publication-ready.
• DE-02: Visual Refinement (3/6) — Subtle improvements: #fafafa plot background, increased spacing (12), rounded bars, hidden x-guides. Grid lines are still prominent dashed lines. Foreground_subtle set but grid still visually dominant.
• DE-03: Data Storytelling (2/6) — The conserved core (positions 2-7) is visible through bar height differences, but no visual emphasis distinguishes this from the variable flanking positions. The printed values on some bars help slightly but don't create a narrative.

Spec Compliance (11/15)

• SC-01: Plot Type (3/5) — The spec requires a "sequence logo" with "letters rendered as scaled glyphs (stretched to fill their allocated height), not as plain text." This implementation uses a stacked bar chart — correct data encoding but missing the defining visual characteristic. Pygal lacks native glyph rendering capabilities, so a stacked bar is the best feasible approximation, but the printed numeric values don't substitute for letter glyphs.
• SC-02: Required Features (2/4) — Has: vertical stacking by frequency, information content scaling, standard DNA color scheme, x/y axis labels. Missing: letter glyphs as scaled shapes within bars (the spec's key requirement). The nucleotide letters only appear in the legend.
• SC-03: Data Mapping (3/3) — X-axis correctly maps to sequence position (1-10), Y-axis correctly shows information content in bits. Stacking order is consistent.
• SC-04: Title & Legend (3/3) — Title format "sequence-logo-basic · pygal · pyplots.ai" is correct. Legend labels match nucleotides A, C, G, T with appropriate colors.

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6) — Shows highly conserved positions (4: A-dominant, 6-7: T-dominant) and variable positions (1, 8-10). Good range of information content values. Could include a position with more equal distribution for completeness.
• DQ-02: Realistic Context (5/5) — ETS transcription factor binding site is a well-characterized, real-world biological motif commonly used in bioinformatics literature.
• DQ-03: Appropriate Scale (4/4) — Information content values (0-1.37 bits) are realistic for DNA (theoretical max 2 bits). All frequencies sum to 1.0 per position.

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — Clean flat structure: imports → data dict → entropy calculation → style → chart config → save. No functions or classes.
• CQ-02: Reproducibility (2/2) — Fully deterministic with hardcoded frequency dictionary. No random generation.
• CQ-03: Clean Imports (2/2) — numpy (for log2), pygal, and Style are all actively used.
• CQ-04: Code Elegance (2/2) — Dead code from attempt 1 removed. Clean value formatting with lambda. Appropriate complexity for the visualization.
• CQ-05: Output & API (1/1) — Saves as plot.png (render_to_png) and plot.html (render_to_file). Current pygal API.

Library Mastery (5/10)

• LM-01: Idiomatic Usage (3/5) — Good use of pygal.StackedBar with Style customization, x_labels, legend_at_bottom_columns, print_values with value_formatter. Standard pygal patterns.
• LM-02: Distinctive Features (2/5) — Uses pygal-specific features: rounded_bars, tooltip_fancy_mode, tooltip_border_radius, dual output (PNG + HTML with interactive tooltips). These are somewhat distinctive but don't push the library's boundaries.

Score Caps Applied

• None applied

Strengths

• Dead code removed from attempt 1 — clean, elegant implementation
• Font sizes explicitly set and well-calibrated for 4800x2700 canvas
• Improved color saturation and style refinement over attempt 1
• Realistic ETS transcription factor motif data with correct entropy calculation
• Smart use of value_formatter to only display values on larger segments

Weaknesses

• Still a stacked bar chart rather than a sequence logo with letter glyphs (pygal limitation)
• No visual emphasis or storytelling to highlight the conserved GGAATT core motif
• Grid lines remain visually prominent despite refinement attempts
• Low-conservation positions (8-10) are nearly invisible, creating visual imbalance

Issues Found

1. DE-03 LOW: No visual hierarchy or storytelling emphasis
   • Fix: The printed values could show nucleotide letters instead of numbers (e.g., "A" instead of "1.24") to better approximate the sequence logo concept. Use the label field in data dicts to embed nucleotide identity.
2. DE-02 MEDIUM: Grid lines still visually dominant
   • Fix: Use a lighter foreground_subtle color (e.g., #e8e8e8 or #f0f0f0) to push grid further into background
3. SC-01/SC-02 LOW: Missing letter glyphs — fundamental spec feature
   • Fix: Modify value_formatter or print_values to display the dominant nucleotide letter within each bar segment, approximating the glyph effect within pygal's capabilities
4. LM-02 LOW: Not fully leveraging pygal's distinctive capabilities
   • Fix: Consider using custom tooltip formatting, secondary_series, or x_label_rotation for more library-specific features

AI Feedback for Next Attempt

Key improvement needed: use the value_formatter or custom label logic to print nucleotide letters (A, C, G, T) inside bar segments instead of numeric values — this would better approximate the sequence logo concept within pygal's constraints. Soften grid lines further (foreground_subtle=#eeeeee). Add visual storytelling: consider using different opacity or style emphasis on the conserved core positions (2-7) vs. variable flanks. The code quality and data are strong — focus remaining effort on design excellence and approximating the spec's letter-glyph requirement.

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 stacked bar chart with 10 positions along the x-axis representing a DNA transcription factor binding site motif (ETS family). Each position has stacked colored bars: green (A), blue (C), orange (G), and red/crimson (T). The y-axis shows "Information content (bits)" ranging from 0 to 1.5. Positions 4 and 5 have the tallest stacks (~1.35 bits, dominated by green/A), positions 2 and 3 are orange/G-dominated (~0.85 and ~1.15 bits), positions 6 and 7 are red/T-dominated (~1.15 bits each). Positions 1, 8, 9, and 10 have very short bars indicating low conservation. Some bars display nucleotide letters (G, A, T) centered inside larger segments. The title "sequence-logo-basic · pygal · pyplots.ai" appears at top. A legend at the bottom displays A, C, G, T in a single row with colored squares. Bars have slightly rounded corners. Background is white with light gray (#fafafa) plot area and subtle horizontal grid lines.

Score: 82/100

Category	Score	Max
Visual Quality	27	30
Design Excellence	12	20
Spec Compliance	12	15
Data Quality	14	15
Code Quality	10	10
Library Mastery	7	10
Total	82	100

Visual Quality (27/30)

• VQ-01: Text Legibility (8/8) — Font sizes explicitly set: title=34, labels=22, major_labels=20, legend=22, value=22. All text clearly readable at full resolution.
• VQ-02: No Overlap (6/6) — No overlapping text or elements. Nucleotide letters only displayed when bar height >= 0.12, avoiding clutter in small segments.
• VQ-03: Element Visibility (5/6) — High-conservation positions (2–7) have clearly visible, well-sized bars. Positions 8–10 have very thin segments that are hard to distinguish individually, though this accurately represents low information content.
• VQ-04: Color Accessibility (3/4) — Standard DNA color scheme (green=A, blue=C, orange=G, red=T). Green and red are distinguishable by saturation and position context, but green-red pairing is not ideal for deuteranopia.
• VQ-05: Layout & Canvas (3/4) — Plot fills canvas reasonably well. Right side (positions 8–10) appears visually empty due to tiny bars, creating slight imbalance. Legend placement at bottom is clean.
• VQ-06: Axis Labels & Title (2/2) — "Position" for x-axis, "Information content (bits)" for y-axis — descriptive with units.

Design Excellence (12/20)

• DE-01: Aesthetic Sophistication (5/8) — Custom DNA-themed palette with intentional color choices (#0d7a22, #1d4ed8, #d97706, #b91c1c). Monospace font for value labels with sans-serif elsewhere shows typography thought. Rounded bars and subtle off-white background. Clearly above library defaults.
• DE-02: Visual Refinement (4/6) — X-guides disabled, y-guides present with subtle foreground_subtle (#eeeeee). Plot background slightly off-white (#fafafa). Bar spacing=8 creates clean separation. Legend at bottom in 4-column layout. Margins adjusted.
• DE-03: Data Storytelling (3/6) — The ETS motif data creates a natural story: conserved GGAATT core (positions 2–7) stands out through bar height, while flanking regions (1, 8–10) show low conservation. Nucleotide letters inside dominant bars aid identification. However, no additional emphasis (e.g., highlighting the conserved core) to actively guide the viewer.

Spec Compliance (12/15)

• SC-01: Plot Type (3/5) — Spec requests a sequence logo with letters scaled as glyphs. This is a stacked bar chart approximation — pygal cannot render stretched letter glyphs. Best approximation possible with this library, but not a true sequence logo.
• SC-02: Required Features (3/4) — Has stacking by frequency × IC, standard DNA colors, position numbers, correct axes. Letters appear as text labels inside bars rather than as scaled glyphs filling their allocated height.
• SC-03: Data Mapping (3/3) — X=position (1–10), Y=information content in bits. Letters ordered by stacking. Correct mapping.
• SC-04: Title & Legend (3/3) — Title "sequence-logo-basic · pygal · pyplots.ai" matches required format. Legend shows A, C, G, T with correct color mapping.

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6) — Shows highly conserved positions (4, 5, 6, 7 at ~1.15–1.35 bits), moderately conserved (2, 3), and low conservation (1, 8, 9, 10). Good range. Could benefit from one position with moderate mixed conservation.
• DQ-02: Realistic Context (5/5) — ETS transcription factor binding site with GGAATT core motif — real biological scenario, scientifically accurate and neutral.
• DQ-03: Appropriate Scale (4/4) — Information content 0–~1.35 bits for DNA (max possible 2 bits). Frequencies sum to 1.0 per position. Realistic values.

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — Linear flow: imports → data → IC calculation → style → chart → save. No functions or classes.
• CQ-02: Reproducibility (2/2) — Fully deterministic data, no randomness involved.
• CQ-03: Clean Imports (2/2) — All three imports (numpy, pygal, Style) are used.
• CQ-04: Code Elegance (2/2) — Clean implementation. Lambda for formatter is appropriate for conditional in-bar labels. No over-engineering.
• CQ-05: Output & API (1/1) — Saves as plot.png via render_to_png(). Also renders HTML. Current pygal API.

Library Mastery (7/10)

• LM-01: Idiomatic Usage (4/5) — Good use of pygal StackedBar with custom Style object, dict-based data points with label and formatter keys, legend configuration, print_values. Idiomatic pygal patterns.
• LM-02: Distinctive Features (3/5) — Uses pygal-specific features: formatter lambda for conditional in-bar text, tooltip configuration (border_radius, fancy_mode), rounded_bars, dual output (PNG + HTML), dict-based data points with custom tooltip labels.

Score Caps Applied

• None — no score cap conditions triggered.

Strengths

• Scientifically accurate ETS transcription factor binding site data with realistic information content values
• Clean, well-structured code with linear flow and deterministic data
• Good use of pygal-specific features (formatters, tooltips, dual output)
• Custom DNA color palette with intentional typography choices
• Effective use of conditional value printing to avoid clutter in small segments

Weaknesses

• Not a true sequence logo — letters are text labels inside stacked bars rather than scaled glyphs (pygal limitation)
• Green-red color pairing could be improved for colorblind accessibility
• Low-conservation positions (8–10) create visual emptiness on the right side
• No active emphasis on the conserved core region to guide viewer attention

Issues Found

1. SC-01 MODERATE: Stacked bar approximation instead of true sequence logo — inherent pygal limitation, best possible approach
2. DE-03 MODERATE: Conserved core (positions 2–7) is visually apparent through height but no additional emphasis guides the viewer
3. VQ-04 MINOR: Green (A) and red (T) could be problematic for deuteranopia — consider teal/amber alternatives

AI Feedback for Next Attempt

This is attempt 3/3. The implementation is a solid pygal approximation of a sequence logo with good data quality and code structure. The main limitation (no scaled letter glyphs) is inherent to pygal. Score of 82 reflects good technical quality with room for design improvement.

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 is a stacked bar chart with 10 positions along the x-axis and "Information content (bits)" on the y-axis (ranging from 0 to ~1.5). Four nucleotide series are displayed: A (teal/green), C (blue), G (amber/orange), T (red/purple). Positions 2–7 feature tall stacked bars representing a conserved GGAATT core—position 4 is the tallest (~1.35 bits, dominated by green A). Positions 1, 8, 9, 10 have very short bars indicating low information content. Letters (G, A, T) are printed as text labels inside the larger bar segments. The title reads "sequence-logo-basic · pygal · pyplots.ai" at the top. A legend at the bottom shows all four nucleotides in a 4-column layout. The plot background is light gray (#f8f9fa) on a white canvas, with rounded bar corners and subtle styling.

Score: 81/100

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	7	10
Total	81	100

Visual Quality (27/30)

• VQ-01: Text Legibility (7/8) — Font sizes explicitly set (title=36, labels=22, major_labels=20, value=24, legend=22). All text readable at full resolution. Minor deduction: title appears somewhat compact relative to the large canvas.
• VQ-02: No Overlap (6/6) — No overlapping text or elements. X-labels well-spaced, legend at bottom with 4 columns is clean, bar spacing of 6 prevents collision.
• VQ-03: Element Visibility (5/6) — Conserved positions (2-7) have prominent bars with clear dominant nucleotide colors. Positions 8-10 have very short bars where individual segments are hard to distinguish, though this accurately reflects low information content.
• VQ-04: Color Accessibility (4/4) — Teal/blue/amber/purple palette deliberately avoids red-green confusion. Good contrast between all four colors.
• VQ-05: Layout & Canvas (3/4) — Plot fills approximately 50-60% of canvas. Some wasted vertical space above the tallest bar (y-range set to 1.6 but max bar is ~1.35). Right side positions (8-10) have near-invisible bars creating visual imbalance.
• VQ-06: Axis Labels & Title (2/2) — Y-axis: "Information content (bits)" with units. X-axis: "Position (* = conserved core, IC > 0.5 bits)" is descriptive with context.

Design Excellence (12/20)

• DE-01: Aesthetic Sophistication (5/8) — Custom teal/blue/amber/purple palette, light gray plot background, rounded bar corners (rounded_bars=3), custom opacity (0.92), monospace font for value labels. Clearly above defaults but not publication-ready.
• DE-02: Visual Refinement (4/6) — No x-guides, y-guides only, subtle foreground colors, custom margins and spacing, legend at bottom in organized columns. Some refinement visible.
• DE-03: Data Storytelling (3/6) — The conserved core (positions 2-7) visually stands out through tall bars vs. short flanking positions. X-labels mark core positions with asterisks. Letters inside bars identify dominant nucleotides. Creates a clear visual narrative of the binding motif.

Spec Compliance (11/15)

• SC-01: Plot Type (3/5) — Spec requires a sequence logo with scaled letter glyphs. This is a stacked bar chart approximation—reasonable for pygal's capabilities, but not a true sequence logo. Letters are plain text labels inside bars rather than stretched glyphs.
• SC-02: Required Features (2/4) — Missing: frequency-based stacking order (most frequent on top)—stacking is fixed A/C/G/T order. Missing: scaled letter glyphs. Present: IC-scaled heights, standard-ish DNA colors (T=purple instead of red for accessibility), position numbers on x-axis, bits on y-axis, axis labels.
• SC-03: Data Mapping (3/3) — X-axis correctly shows positions 1-10, Y-axis shows information content in bits. Total stack heights correctly reflect IC at each position.
• SC-04: Title & Legend (3/3) — Title follows exact format "sequence-logo-basic · pygal · pyplots.ai". Legend correctly labels all four nucleotides A, C, G, T.

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6) — Shows 10-position DNA motif with good variation: highly conserved positions (2-7 with dominant nucleotides), mixed positions (1, 9), and near-uniform positions (8, 10). Demonstrates both high and low information content.
• DQ-02: Realistic Context (5/5) — ETS transcription factor binding site with GGAATT core is a real, well-known biological motif. Scientifically accurate and neutral.
• DQ-03: Appropriate Scale (4/4) — Frequencies sum to 1.0 per position. Information content ranges from ~0.02 to ~1.35 bits, well within the 0-2 bits range for DNA. Biologically realistic values.

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — Linear flow: imports → data → IC calculation → style → chart config → save. No functions or classes.
• CQ-02: Reproducibility (2/2) — Fully deterministic data, no random generation.
• CQ-03: Clean Imports (2/2) — numpy, pygal, pygal.style.Style — all used.
• CQ-04: Code Elegance (2/2) — Clean, well-organized. Lambda with default arguments for formatters is appropriate. Core position detection adds value without over-engineering.
• CQ-05: Output & API (1/1) — Saves as plot.png via render_to_png, also generates plot.html. Current API.

Library Mastery (7/10)

• LM-01: Idiomatic Usage (4/5) — Uses StackedBar chart type, Style class for theming, structured data dictionaries with value/label/formatter keys, legend configuration options, chart rendering pipeline. Idiomatic pygal patterns throughout.
• LM-02: Distinctive Features (3/5) — Uses pygal-specific features: print_values with custom formatter functions, tooltip_fancy_mode, tooltip_border_radius, rounded_bars, legend_at_bottom_columns, dual render (PNG + HTML/SVG). These leverage pygal's interactive SVG capabilities.

Score Caps Applied

• None — no cap conditions triggered (DE-01=5 > 2, DE-02=4 > 2)

Strengths

• Excellent data quality: real ETS transcription factor binding site with biologically accurate frequencies
• Colorblind-safe palette (teal/blue/amber/purple) with deliberate avoidance of red-green confusion
• Clean, well-structured code with appropriate complexity
• Good use of pygal-specific features (formatters, tooltips, rounded bars, dual output)
• Core position marking on x-axis adds context to the visualization

Weaknesses

• Not a true sequence logo: letters are small text labels inside bars rather than scaled glyphs filling the bar height
• Fixed stacking order (A, C, G, T) rather than frequency-sorted per position as spec requires
• Y-axis range (0-1.6) creates wasted vertical space above the tallest bar (~1.35)

Issues Found

1. SC-01 MODERATE: Stacked bar chart instead of true sequence logo with scaled letter glyphs
   • Pygal has limited glyph-rendering capabilities, so this is a reasonable library constraint
2. SC-02 LOW: Stacking order not sorted by frequency per position
   • Fix: Would require per-position series reordering, which pygal StackedBar doesn't natively support

AI Feedback for Next Attempt

This is attempt 3/3. The implementation is a solid pygal approximation of a sequence logo using stacked bars. The main limitations (no scaled glyphs, fixed stacking order) are inherent to pygal's capabilities rather than implementation choices. Design excellence is good with custom palette, refined styling, and data storytelling through core position emphasis. Code quality is excellent.

Verdict: REJECTED