feat(letsplot): implement line-stress-strain

[github-actions]

Implementation: line-stress-strain - letsplot

Implements the letsplot version of line-stress-strain.

File: plots/line-stress-strain/implementations/letsplot.py

Parent Issue: #4413

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot shows a mild steel engineering stress-strain curve rendered as a blue line (#306998) on a light gray (#FAFAFA) background. The x-axis is labeled "Engineering Strain" (0 to 0.35) and the y-axis "Engineering Stress (MPa)" (0 to ~450). The title reads "Mild Steel Tensile Test · line-stress-strain · letsplot · pyplots.ai" in bold dark text. Three key points are marked with filled circles: Yield (orange, at ~0.003, 250 MPa), UTS (green, at ~0.22, 400 MPa), and Fracture (gray, at ~0.35, ~280 MPa). A dashed orange 0.2% offset line runs parallel to the elastic region. Region labels in gray italic — "Elastic", "Strain Hardening", "Necking" — span the top of the plot. Annotations include "Yield Point (250 MPa)" in orange, "UTS (400 MPa)" in green, "Fracture" in gray, "E = 210 GPa" in blue italic, and "0.2% offset" in orange italic. Only subtle horizontal grid lines are shown. The curve shows realistic mild steel behavior: steep elastic region, brief yield plateau, strain hardening curve up to UTS, and necking decline to fracture.

Score: 82/100

Category	Score	Max
Visual Quality	25	30
Design Excellence	14	20
Spec Compliance	14	15
Data Quality	15	15
Code Quality	9	10
Library Mastery	5	10
Total	82	100

Visual Quality (25/30)

• VQ-01: Text Legibility (7/8) — Font sizes explicitly set (title=22, axis_title=20, axis_text=16, annotations 9-12). All readable, but title slightly below 24pt recommendation.
• VQ-02: No Overlap (5/6) — Minor crowding near the yield point area where the "Yield Point (250 MPa)" label, offset line, and elastic region label converge. Not severe but noticeable.
• VQ-03: Element Visibility (5/6) — Main curve size=2.0 and key points size=7 are clearly visible. The 0.2% offset dashed line is visible but could be slightly more prominent.
• VQ-04: Color Accessibility (3/4) — Blue, orange, green, gray palette is mostly accessible. Orange (#D95319) and green (#2CA02C) used for Yield/UTS points could be problematic for deuteranopia, though spatial separation helps.
• VQ-05: Layout & Canvas (3/4) — Good overall proportions. The elastic region is very compressed on the left due to the small strain values, leaving some visual imbalance, but this is inherent to the data domain.
• VQ-06: Axis Labels & Title (2/2) — "Engineering Stress (MPa)" with units, "Engineering Strain" is dimensionless so no unit needed. Perfect.

Design Excellence (14/20)

• DE-01: Aesthetic Sophistication (5/8) — Custom color palette (Python blue main curve, distinct annotation colors), custom background (#FAFAFA), intentional typography hierarchy with different sizes and colors. Above configured defaults but not publication-level polish.
• DE-02: Visual Refinement (4/6) — theme_minimal with customized grid (horizontal only, subtle #E0E0E0), minor grid removed, ticks removed, custom background. Good refinement beyond defaults.
• DE-03: Data Storytelling (5/6) — Excellent storytelling: labeled regions guide the viewer through the material's behavior phases. Key points are highlighted with distinct colors and annotated with values. The 0.2% offset method is illustrated. Clear visual hierarchy from curve → points → annotations → regions.

Spec Compliance (14/15)

• SC-01: Plot Type (5/5) — Correct line plot showing stress-strain curve.
• SC-02: Required Features (4/4) — All spec requirements met: labeled regions (elastic, strain hardening, necking), critical points marked (yield, UTS, fracture), elastic modulus annotated, 0.2% offset line drawn.
• SC-03: Data Mapping (3/3) — X=strain, Y=stress correctly mapped. Axes show full data range.
• SC-04: Title & Legend (2/3) — Title contains spec-id, library, and pyplots.ai but has extra prefix "Mild Steel Tensile Test". Legend is suppressed (guides fill="none") with direct annotation, which is appropriate, but the title format deviates slightly from the standard {spec-id} · {library} · pyplots.ai.

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) — Shows all regions: elastic, yield plateau (mild steel characteristic), strain hardening, necking. All critical points demonstrated.
• DQ-02: Realistic Context (5/5) — Mild steel tensile test with accurate material properties: E=210 GPa, yield=250 MPa, UTS=400 MPa, fracture strain=0.35. Neutral engineering domain.
• DQ-03: Appropriate Scale (4/4) — All values are realistic for mild steel. Random noise adds realistic experimental scatter.

Code Quality (9/10)

• CQ-01: KISS Structure (3/3) — Linear flow: imports → data generation → plot → save. No functions or classes.
• CQ-02: Reproducibility (2/2) — np.random.seed(42) set.
• CQ-03: Clean Imports (2/2) — numpy, pandas, lets_plot all used.
• CQ-04: Code Elegance (1/2) — Many single-row DataFrames for annotations (df_yield_label, df_uts_label, etc.) is verbose. Necessary for lets-plot's grammar but could be consolidated.
• CQ-05: Output & API (1/1) — Saves as plot.png with scale=3 for correct resolution.

Library Mastery (5/10)

• LM-01: Idiomatic Usage (4/5) — Properly uses ggplot grammar: layered geoms, aes mappings, scale_fill_manual, theme customization, ggsize. Good idiomatic usage.
• LM-02: Distinctive Features (1/5) — Generic grammar-of-graphics usage that could be replicated in plotnine with minor syntax changes. No lets-plot distinctive features used (e.g., interactive tooltips, livemap, corr_plot, geom_livemap).

Score Caps Applied

• None

Strengths

• Excellent data storytelling with labeled regions, annotated critical points, and 0.2% offset method illustration
• Realistic mild steel material properties with appropriate noise for experimental scatter
• Good visual refinement with customized grid, background, and typography hierarchy
• Complete spec compliance — all required features present

Weaknesses

• Title format deviates from standard {spec-id} · {library} · pyplots.ai pattern
• Orange/green color combination for Yield/UTS points could be improved for colorblind accessibility
• No distinctive lets-plot features leveraged (tooltips, interactive elements via HTML export)
• Verbose annotation code with many single-row DataFrames

Issues Found

1. SC-04 MINOR: Title prepends "Mild Steel Tensile Test" before the standard format
   • Fix: Use line-stress-strain · letsplot · pyplots.ai as the title, optionally with subtitle for description
2. LM-02 LOW: Generic grammar-of-graphics usage with no lets-plot distinctive features
   • Fix: Consider leveraging lets-plot specific features like geom_segment for the offset line or tooltip layers for the HTML export
3. VQ-04 MINOR: Orange and green markers could be problematic for colorblind users
   • Fix: Replace green with a blue-shifted teal or use shape differentiation alongside color

AI Feedback for Next Attempt

Improve library mastery by using lets-plot distinctive features (e.g., tooltips for the HTML version, geom_segment for annotation lines). Fix the title to follow the standard {spec-id} · {library} · pyplots.ai format — use a subtitle for the descriptive text. Consider replacing the green UTS marker with a more colorblind-safe alternative like teal (#17BECF). Consolidate annotation DataFrames where possible to reduce code verbosity.

Verdict: REJECTED

[github-actions]

🔧 Repair Attempt 1/3

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

The plot displays a mild steel engineering stress-strain curve rendered as a thick blue (#306998) line on a light off-white (#FAFAFA) background. The x-axis is labeled "Engineering Strain" (0 to 0.35) and the y-axis "Engineering Stress (MPa)" (0 to 450). The title reads "line-stress-strain · letsplot · pyplots.ai" in bold dark text at the top left. Three colored background bands span the plot height: light blue for the Elastic region, light yellow/cream for Strain Hardening, and light pink/salmon for the Necking region, with large italic labels at the top of each. Three key points are marked with filled outlined circles: Yield (purple/orange fill at ~0.003, 250 MPa), UTS (red/green fill at ~0.22, 400 MPa), and Fracture (gray fill at ~0.35, ~280 MPa). A dashed offset line runs near the origin parallel to the elastic slope. Annotations include "Yield Point (250 MPa)" in orange with a bordered box, "UTS (400 MPa)" in green with a bordered box, "Fracture" in gray, "E = 210 GPa" in blue italic, and "0.2% offset" in orange italic. Only subtle horizontal grid lines are shown. The curve demonstrates realistic mild steel behavior: steep elastic region, brief yield plateau, smooth strain hardening up to UTS, and necking decline to fracture.

Score: 86/100

Category	Score	Max
Visual Quality	27	30
Design Excellence	15	20
Spec Compliance	14	15
Data Quality	15	15
Code Quality	9	10
Library Mastery	6	10
Total	86	100

Visual Quality (27/30)

• VQ-01: Text Legibility (7/8) — Font sizes explicitly set (title=22, axis_title=20, axis_text=16, annotations 9-12). All readable. Title 22pt is slightly below the 24pt recommendation.
• VQ-02: No Overlap (5/6) — Minor crowding in the elastic region where "Yield Point (250 MPa)", "E = 210 GPa", "0.2% offset", and the offset line converge in a small area. Rest of the plot is clean.
• VQ-03: Element Visibility (6/6) — Main curve at size=2.0 is clearly visible. Key points at size=7 with white stroke stand out well. Offset dashed line at size=1.2 is appropriately visible.
• VQ-04: Color Accessibility (3/4) — Orange (#D95319) for yield and green (#2CA02C) for UTS can be difficult to distinguish under deuteranopia. Spatial separation helps but the color pair is not ideal.
• VQ-05: Layout & Canvas (4/4) — Excellent canvas utilization with 1600×900 base, margins [30,40,20,20]. Plot fills the space well with balanced whitespace.
• VQ-06: Axis Labels & Title (2/2) — "Engineering Stress (MPa)" with units. "Engineering Strain" is dimensionless, correctly without units.

Design Excellence (15/20)

• DE-01: Aesthetic Sophistication (6/8) — Colored region backgrounds, custom color palette, intentional typography hierarchy with different sizes and colors. Clearly above configured defaults. The region shading adds visual sophistication not seen in generic plots.
• DE-02: Visual Refinement (4/6) — theme_minimal with customized grid (horizontal only, subtle #E0E0E0 at size=0.3), minor grid removed, ticks removed, custom #FAFAFA background. Good refinement beyond defaults.
• DE-03: Data Storytelling (5/6) — Excellent narrative flow: colored regions guide the viewer through elastic → strain hardening → necking. Key points annotated with values. The 0.2% offset method is illustrated with both the line and label. Clear visual hierarchy from regions → curve → points → annotations.

Spec Compliance (14/15)

• SC-01: Plot Type (5/5) — Correct line plot showing engineering stress-strain curve.
• SC-02: Required Features (4/4) — All spec requirements met: regions labeled (elastic, strain hardening, necking), critical points marked (yield, UTS, fracture), elastic modulus annotated (E = 210 GPa), 0.2% offset line drawn.
• SC-03: Data Mapping (3/3) — X=strain, Y=stress correctly mapped. Axes show full data range with appropriate breaks.
• SC-04: Title & Legend (2/3) — Code sets title as "Mild Steel Tensile Test · line-stress-strain · letsplot · pyplots.ai" which prepends extra text before the standard format. Should be line-stress-strain · letsplot · pyplots.ai. Legend suppressed with direct annotations is appropriate.

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) — Shows all regions: elastic, yield plateau (characteristic of mild steel), strain hardening, necking. All critical points (yield, UTS, fracture) demonstrated with realistic transitions.
• DQ-02: Realistic Context (5/5) — Mild steel tensile test with accurate material properties: E=210 GPa, yield=250 MPa, UTS=400 MPa, fracture strain=0.35. Neutral engineering domain with realistic experimental noise.
• DQ-03: Appropriate Scale (4/4) — All values are realistic for mild steel. Random noise adds realistic experimental scatter without distorting the curve shape.

Code Quality (9/10)

• CQ-01: KISS Structure (3/3) — Linear flow: imports → data generation → plot construction → save. No functions or classes.
• CQ-02: Reproducibility (2/2) — np.random.seed(42) set at the beginning.
• CQ-03: Clean Imports (2/2) — numpy, pandas, lets_plot, export_ggsave all used.
• CQ-04: Code Elegance (1/2) — Many single-row DataFrames for individual annotations (df_yield_label, df_uts_label, df_fracture_label, df_modulus_label, df_offset_label, plus 3 region DataFrames). While necessary for ggplot grammar, some could be consolidated into fewer DataFrames.
• CQ-05: Output & API (1/1) — Saves as plot.png with export_ggsave at scale=3 for correct 4800×2700 resolution. Also exports HTML.

Library Mastery (6/10)

• LM-01: Idiomatic Usage (4/5) — Properly uses ggplot grammar: layered geoms, aes mappings, scale_fill_manual, guides, theme_minimal with extensive customization, ggsize. Good idiomatic usage of the grammar-of-graphics paradigm.
• LM-02: Distinctive Features (2/5) — HTML export via export_ggsave is a lets-plot feature. Using shape=21 with fill mapping for outlined points. But no truly distinctive lets-plot features (e.g., tooltips for HTML version, geom_segment, coord_flip, or interactive capabilities).

Score Caps Applied

• None

Strengths

• Outstanding data storytelling with colored region backgrounds, annotated critical points, and 0.2% offset method illustration
• Realistic mild steel material properties with appropriate experimental noise
• Excellent spec compliance — all required features present and well-executed
• Good visual refinement with y-only grid, removed ticks, and custom background

Weaknesses

• Title format still deviates from standard {spec-id} · {library} · pyplots.ai pattern (extra "Mild Steel Tensile Test" prefix)
• Orange/green color pair for Yield/UTS markers not ideal for colorblind accessibility
• No distinctive lets-plot features leveraged (tooltips in HTML export, geom_segment)
• Verbose annotation code with 8 separate single-row DataFrames

Issues Found

1. SC-04 MINOR: Title includes "Mild Steel Tensile Test ·" before the standard format
   • Fix: Change title to line-stress-strain · letsplot · pyplots.ai
2. LM-02 LOW: No distinctive lets-plot features used
   • Fix: Add tooltip layer to geom_line/geom_point for the HTML export; use geom_segment for the offset line or annotation connectors
3. VQ-04 MINOR: Orange (#D95319) and green (#2CA02C) are problematic for deuteranopia
   • Fix: Replace green with teal (#17BECF) or dark blue (#1F77B4) for the UTS point
4. VQ-01 MINOR: Title font size 22pt, slightly below 24pt recommendation
   • Fix: Increase plot_title size to 24

AI Feedback for Next Attempt

This is the final attempt. To reach 90+: (1) Fix title to exactly line-stress-strain · letsplot · pyplots.ai — no prefix. (2) Add tooltips to geom_line and geom_point for the HTML export to leverage lets-plot's interactive capabilities. (3) Replace green UTS color with teal (#17BECF) for better colorblind accessibility. (4) Increase title font size to 24pt. These four targeted fixes should push the score from 86 to 90+.

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 an engineering stress-strain curve for mild steel on a light gray background. The x-axis shows "Engineering Strain" (0 to 0.35) and the y-axis shows "Engineering Stress (MPa)" (0 to 450). The main curve is drawn as a thick blue line starting from the origin, rising steeply through the elastic region, showing a brief yield plateau around 250 MPa, then curving through strain hardening up to ~400 MPa (UTS), and finally declining through the necking region to fracture at ~280 MPa. Three colored background bands distinguish the regions: light blue for Elastic, light yellow for Strain Hardening, and light pink for Necking, each labeled in gray italic text. Key points are marked with filled circles: purple for Yield Point (250 MPa), red for UTS (400 MPa), and gray for Fracture. A dashed pink line shows the 0.2% offset construction, and "E = 210 GPa" is annotated in blue italic. Dotted gray connector lines link points to their labels. The title reads "line-stress-strain · letsplot · pyplots.ai" in bold at the top. Only horizontal grid lines are shown, subtle and light.

Score: 92/100

Category	Score	Max
Visual Quality	27	30
Design Excellence	16	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	10	10
Library Mastery	9	10
Total	92	100

Visual Quality (27/30)

• VQ-01: Text Legibility (7/8) - All major text sizes explicitly set (title 24, axis title 20, axis text 16). Annotation text sizes (9-11) are slightly small but still readable at full resolution.
• VQ-02: No Overlap (5/6) - Minor crowding in the elastic region where "Elastic" label, yield point annotation, E=210 GPa, and 0.2% offset text are close together, but all remain readable.
• VQ-03: Element Visibility (6/6) - Main curve line is thick and clearly visible. Key points use large filled circles with white stroke. The 0.2% offset dashed line is distinct.
• VQ-04: Color Accessibility (3/4) - Uses blue, purple, red, gray, pink — avoids pure red-green pairs. Red (UTS) and purple (Yield) could be slightly challenging for some protanopia cases but are distinguishable by position and labeling.
• VQ-05: Layout & Canvas (4/4) - Plot fills the canvas well with balanced margins. Good proportions at 1600×900 (scaled 3x).
• VQ-06: Axis Labels & Title (2/2) - "Engineering Strain" and "Engineering Stress (MPa)" — descriptive with units.

Design Excellence (16/20)

• DE-01: Aesthetic Sophistication (6/8) - Custom color palette with intentional color assignments per point type. Colored region bands add visual structure. Italic region labels and connector lines show design thought beyond defaults.
• DE-02: Visual Refinement (5/6) - Minimal theme with removed x-grid, subtle y-grid (0.3 width, light gray), removed ticks, custom background (#FAFAFA), transparent panel. Well-polished.
• DE-03: Data Storytelling (5/6) - Excellent story: colored region bands immediately communicate the three deformation phases. Annotated key points (Yield, UTS, Fracture) with values guide the viewer through material behavior. The 0.2% offset line demonstrates the engineering method for yield determination.

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) - Correct line plot showing stress-strain curve.
• SC-02: Required Features (4/4) - All required: region labels (Elastic, Strain Hardening, Necking) ✓, critical points (Yield, UTS, Fracture) ✓, elastic modulus annotation ✓, 0.2% offset line ✓.
• SC-03: Data Mapping (3/3) - X=strain, Y=stress correctly mapped. Axes cover full data range.
• SC-04: Title & Legend (3/3) - Title format "line-stress-strain · letsplot · pyplots.ai" correct. Legend suppressed in favor of direct annotations — appropriate for this plot.

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) - Shows all regions: elastic (linear), yield plateau (mild steel characteristic), strain hardening (exponential approach), and necking (decline to fracture). Noise added for realism.
• DQ-02: Realistic Context (5/5) - Mild steel tensile test with accurate properties: E=210 GPa, σ_y=250 MPa, UTS=400 MPa, fracture strain=0.35.
• DQ-03: Appropriate Scale (4/4) - All values are textbook-accurate for mild steel.

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) - Linear flow: imports → data generation → plot → save. No functions or classes.
• CQ-02: Reproducibility (2/2) - np.random.seed(42) set.
• CQ-03: Clean Imports (2/2) - All imports used (numpy, pandas, lets_plot, export_ggsave).
• CQ-04: Code Elegance (2/2) - Well-organized with clear variable names. Consolidated annotations DataFrame reduces repetition. Appropriate complexity.
• CQ-05: Output & API (1/1) - Saves as plot.png via export_ggsave with scale=3.

Library Mastery (9/10)

• LM-01: Idiomatic Usage (5/5) - Expert ggplot grammar: layered geoms, aes mappings, scale_fill_manual, theme customization. Properly uses lets-plot's export_ggsave.
• LM-02: Distinctive Features (4/5) - Uses layer_tooltips() for interactive hover info (lets-plot distinctive feature), geom_rect for region bands, geom_segment for connector lines. HTML export also generated. Missing only more advanced lets-plot features like coord transforms or custom stat layers.

Score Caps Applied

• None — no caps triggered.

Strengths

• Excellent data storytelling with colored region bands that immediately communicate the three deformation phases
• All spec requirements fully implemented including 0.2% offset line and elastic modulus annotation
• Textbook-accurate mild steel properties with realistic noise
• Strong lets-plot idiomatic usage with distinctive tooltip features
• Clean, well-organized code with consolidated annotation DataFrames

Weaknesses

• Minor crowding of annotations in the elastic region (small area with multiple labels)
• Red/purple color pair could be slightly improved for colorblind accessibility

Issues Found

None significant — implementation meets quality threshold.

AI Feedback for Next Attempt

N/A — implementation approved.

Verdict: APPROVED