feat(highcharts): implement stereonet-equal-area

[github-actions]

Implementation: stereonet-equal-area - highcharts

Implements the highcharts version of stereonet-equal-area.

File: plots/stereonet-equal-area/implementations/highcharts.py

Parent Issue: #4576

---

🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot shows a lower-hemisphere equal-area (Schmidt net) stereonet projection on a white background. A bold dark circle forms the primitive circle with tick marks every 10° around the perimeter. Cardinal directions (N, E, S, W) and degree labels (30°, 60°, 120°, 150°, 210°, 240°, 300°, 330°) are placed outside the circle. Inside, subtle dotted concentric circles and radial lines form the stereonet grid. Three types of structural data are plotted: blue great circle arcs and poles (Bedding), orange great circle arcs and poles (Joints), and red/pink great circle arcs and poles (Faults). Bedding poles cluster in the SE quadrant, Joints poles cluster in the NE quadrant, and Fault poles are scattered on the E side. Green density contours (Kamb-style) overlay the pole data highlighting preferred orientations. A horizontal legend at the bottom lists all 7 series: Bedding (planes), Joints (planes), Faults (planes), Bedding (poles), Joints (poles), Faults (poles), and Density contours. Title reads "stereonet-equal-area · highcharts · pyplots.ai" with subtitle "Lower Hemisphere Equal-Area (Schmidt) Projection".

Score: 81/100

Category	Score	Max
Visual Quality	25	30
Design Excellence	13	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	9	10
Library Mastery	4	10
Total	81	100

Visual Quality (25/30)

• VQ-01: Text Legibility (7/8) - Font sizes explicitly set (title 60px, subtitle 40px, labels 36px, legend 32px). All perimeter labels and title are clearly readable. Legend text is slightly small relative to the 3600px canvas.
• VQ-02: No Overlap (5/6) - Perimeter labels well-spaced. Legend has 7 items crammed into a single horizontal row, making it slightly cramped.
• VQ-03: Element Visibility (5/6) - Poles visible with marker radius 10 and white borders. Great circles at lineWidth 2.5 are visible. Some poles in dense clusters overlap slightly.
• VQ-04: Color Accessibility (3/4) - Blue (#306998), orange (#E5863D), red (#D64045) are distinguishable. Not pure red-green. Green contours add a 4th color that's distinct. Not fully optimized for colorblind users.
• VQ-05: Layout & Canvas (3/4) - Square 3600×3600 is appropriate for a circular stereonet. Good canvas utilization. Minor wasted space in corners (inherent to circular plot in square canvas).
• VQ-06: Axis Labels & Title (2/2) - N/E/S/W cardinal labels and degree marks are appropriate for a stereonet. No traditional axis labels needed.

Design Excellence (13/20)

• DE-01: Aesthetic Sophistication (5/8) - Custom color palette with intentional color assignments per feature type. Green density contours provide good contrast. Typography hierarchy (title > subtitle > labels) is clear. Above defaults but not publication-level polish.
• DE-02: Visual Refinement (4/6) - Grid lines are dotted with low opacity (0.3), avoiding visual clutter. Tick marks differentiate major/minor intervals. Default Highcharts axes are hidden. White marker borders improve visibility on overlaps.
• DE-03: Data Storytelling (4/6) - Three distinct structural domains create natural visual groupings. Density contours guide the viewer to preferred orientations. Great circles and poles together show the relationship between planes and their normals.

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) - Correct lower-hemisphere equal-area (Schmidt net) projection
• SC-02: Required Features (4/4) - All spec features present: great circles for planes, poles as points, color-coded by feature_type, legend, Kamb density contours, 10° tick marks, N label, subtle grid
• SC-03: Data Mapping (3/3) - Strike/dip correctly converted to equal-area projection coordinates. Poles placed at 90° to planes.
• SC-04: Title & Legend (3/3) - Title format "stereonet-equal-area · highcharts · pyplots.ai" correct. Legend labels match data series (planes and poles for each type, plus density contours).

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) - Three feature types (Bedding n=40, Joints n=35, Faults n=15) with different orientations and dip angles. Shows both planes and poles. Density contours highlight clustering.
• DQ-02: Realistic Context (5/5) - Geological field campaign data with realistic structural features: NE-striking bedding, NW-striking steep joints, N-S faults.
• DQ-03: Appropriate Scale (4/4) - Strike 0-360°, dip 5-89° with realistic distributions. Sample sizes typical for geological mapping.

Code Quality (9/10)

• CQ-01: KISS Structure (3/3) - Linear script: imports → data generation → projection math → series building → chart config → render
• CQ-02: Reproducibility (2/2) - np.random.seed(42) set
• CQ-03: Clean Imports (2/2) - All imports used (matplotlib for contour extraction, scipy for KDE, selenium for rendering)
• CQ-04: Code Elegance (1/2) - Python 2-style except syntax on lines 239 and 260 (except AttributeError, TypeError: should be except (AttributeError, TypeError):). Code is functional but this is a bug that would cause SyntaxError in strict Python 3 parsing.
• CQ-05: Output & API (1/1) - Saves as plot.png via Selenium screenshot

Library Mastery (4/10)

• LM-01: Idiomatic Usage (2/5) - Does not use the highcharts_core Python API at all. Builds raw JSON config dict and generates JavaScript directly via string formatting. While functional, this bypasses the library's Python OOP interface entirely.
• LM-02: Distinctive Features (2/5) - Leverages Highcharts interactive tooltips and HTML export. However, the heavy lifting (equal-area projection, KDE, contour extraction) is all done with numpy/scipy/matplotlib outside of Highcharts. Highcharts is essentially used as a rendering backend for pre-computed geometry.

Score Caps Applied

• None

Strengths

• Complete stereonet implementation with all spec features (great circles, poles, density contours, grid, tick marks, cardinal labels)
• Realistic geological data with three distinct structural domains showing clear clustering patterns
• Good visual hierarchy with subtle dotted grid, visible poles with white borders, and green density contours
• Interactive HTML export alongside static PNG is a nice Highcharts-specific addition

Weaknesses

• Does not use highcharts_core Python API; builds raw JSON config instead of using the library's Python classes
• Legend with 7 items in a single horizontal row is cramped and hard to read at the bottom
• Python 2-style except syntax (except AttributeError, TypeError:) on lines 239, 260 is a code bug
• Color palette is decent but could be more colorblind-optimized

Issues Found

1. LM-01 LOW: Raw JSON config instead of highcharts_core Python API
   • Fix: Use Chart(container="container"), HighchartsOptions(), and series classes from highcharts_core
2. LM-02 LOW: Highcharts used as a passive rendering backend
   • Fix: Leverage Highcharts-specific features like custom tooltips with strike/dip data, zoom controls, or series toggle
3. VQ-02 MINOR: Legend cramped with 7 items horizontally
   • Fix: Use vertical legend layout or split into two rows
4. CQ-04 MINOR: Python 2-style except syntax
   • Fix: Change except AttributeError, TypeError: to except (AttributeError, TypeError):

AI Feedback for Next Attempt

Improve library mastery by using the highcharts_core Python API (Chart, HighchartsOptions, ScatterSeries, LineSeries) instead of raw JSON dicts. Leverage Highcharts-distinctive features like rich tooltips showing strike/dip values on hover, series visibility toggling in the legend, or zoom. Fix the legend layout to use vertical alignment or multiple rows for better readability. Fix Python 2-style except syntax. Consider enhancing design excellence with more refined typography and a more intentional color scheme.

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 stereonet (equal-area Schmidt projection) on a square canvas with a light gray (#FAFAFA) background. A dark circular primitive circle encloses the projection area. Cardinal directions (N at top, E at right, S at bottom, W at left) are labeled in bold, with degree labels (30°, 60°, 120°, 150°, 210°, 240°, 300°, 330°) placed around the perimeter. Tick marks appear every 10° around the circle edge. Inside, dotted concentric circles and radial lines form a subtle grid. Three types of geological features are plotted: dark teal/blue Bedding poles (clustered in the lower-center), orange Joints poles (clustered in the upper-right quadrant), and purple Faults poles (scattered on the right side). Great circles in matching colors represent planar features. Green semi-transparent density contours (Kamb-style) surround the pole clusters, highlighting preferred orientations. A horizontal legend at the bottom lists all 7 series: Bedding/Joints/Faults (planes), Bedding/Joints/Faults (poles), and Density contours. Title reads "stereonet-equal-area · highcharts · pyplots.ai" with subtitle "Lower Hemisphere Equal-Area (Schmidt) Projection".

Score: 84/100

Category	Score	Max
Visual Quality	26	30
Design Excellence	13	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	8	10
Library Mastery	7	10
Total	84	100

Visual Quality (26/30)

• VQ-01: Text Legibility (7/8) - Font sizes explicitly set (56px title, 38px subtitle, 30-38px perimeter labels, 30px legend). All text readable, though legend items are relatively small for 7 entries.
• VQ-02: No Overlap (5/6) - No significant overlap. Legend with 7 items in a single horizontal row is slightly cramped; some label proximity around the perimeter.
• VQ-03: Element Visibility (5/6) - Poles clearly visible with radius 10 and white edge highlighting. Great circles visible. Density contours subtle but discernible.
• VQ-04: Color Accessibility (4/4) - Colorblind-safe palette: blue (#306998), orange (#E5863D), purple (#8B5CF6) — all distinguishable.
• VQ-05: Layout & Canvas (3/4) - Square 3600×3600 format is ideal for stereonets. Good margins, but the plot area could fill slightly more of the canvas; legend is somewhat detached at the very bottom.
• VQ-06: Axis Labels & Title (2/2) - Appropriate for a stereonet: cardinal directions and degree labels replace traditional axes. Descriptive subtitle explains the projection type.

Design Excellence (13/20)

• DE-01: Aesthetic Sophistication (5/8) - Custom colorblind-safe palette, intentional typography hierarchy (bold title, lighter subtitle), clean #FAFAFA background. Above library defaults but not yet publication-quality — great circles could have more differentiated line styles per type.
• DE-02: Visual Refinement (4/6) - Dotted grid lines with low opacity (0.25), axes completely hidden, white marker edges for pole visibility, clean whitespace. Good refinement visible.
• DE-03: Data Storytelling (4/6) - Three distinct geological feature types with clear spatial clustering. Density contours effectively highlight preferred orientations. Visual hierarchy through color coding and great circle + pole pairing guides the viewer.

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) - Correct Schmidt equal-area lower-hemisphere stereographic projection.
• SC-02: Required Features (4/4) - All spec features present: great circles for planes, poles to planes as points, Kamb-style density contours, 10° tick marks, N label at top, color-coding by feature_type, legend, subtle grid lines.
• SC-03: Data Mapping (3/3) - Strike/dip correctly converted to equal-area projection coordinates. Pole trends and plunges correctly computed (trend = strike + 90°, plunge = 90° - dip).
• SC-04: Title & Legend (3/3) - Title follows exact format "stereonet-equal-area · highcharts · pyplots.ai". Legend comprehensively labels all 7 series.

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) - Three feature types (bedding, joints, faults) with distinct orientations and dip angles. Shows both clustered (bedding, joints) and dispersed (faults) data patterns.
• DQ-02: Realistic Context (5/5) - Geological field measurements from a mapping campaign: NE-striking bedding at moderate dip, NW-striking steep joints, N-S steep faults — all geologically plausible.
• DQ-03: Appropriate Scale (4/4) - Strike values 0-360°, dip values 5-89°, 90 total measurements — all within realistic ranges for structural geology data.

Code Quality (8/10)

• CQ-01: KISS Structure (3/3) - Linear flow: imports → data generation → projection math → chart construction → rendering.
• CQ-02: Reproducibility (2/2) - np.random.seed(42) set.
• CQ-03: Clean Imports (1/2) - LineSeries imported from highcharts_core.options.series.area instead of highcharts_core.options.series.line. Works but is misleading.
• CQ-04: Code Elegance (1/2) - except AttributeError, TypeError: on lines 304 and 323 uses Python 2 syntax. In Python 3 this should be except (AttributeError, TypeError):. The current syntax catches AttributeError and binds it to name TypeError, silently shadowing the builtin.
• CQ-05: Output & API (1/1) - Saves plot.png via Selenium screenshot and plot.html for interactive use.

Library Mastery (7/10)

• LM-01: Idiomatic Usage (4/5) - Good use of highcharts_core Python API: Chart, HighchartsOptions, series types (LineSeries, ScatterSeries), annotations, to_js_literal(). Proper container setup and Selenium export.
• LM-02: Distinctive Features (3/5) - Leverages Highcharts annotations module for perimeter labels (a Highcharts-specific feature). Interactive tooltips and HTML export provide added value beyond static output.

Score Caps Applied

• None

Strengths

• Excellent spec compliance: all required features (great circles, poles, density contours, grid, tick marks, cardinal labels) are implemented correctly
• Geologically accurate equal-area projection mathematics with proper pole/plane transformations
• Clean colorblind-safe palette with three well-differentiated feature types
• Density contours effectively highlight preferred orientations using Kamb-style KDE approach
• Good use of Highcharts annotations for perimeter degree/cardinal labels

Weaknesses

• except AttributeError, TypeError: syntax is Python 2-style and incorrect in Python 3 — should be except (AttributeError, TypeError):
• LineSeries imported from wrong module path (area instead of line)
• Legend with 7 items in a single horizontal row could be better organized (e.g., two rows or vertical layout)
• Great circles for different feature types could benefit from differentiated line styles (dashed, dotted) in addition to color

Issues Found

1. CQ-04 BUG: except AttributeError, TypeError: on lines 304 and 323 is Python 2 syntax
   • Fix: Change to except (AttributeError, TypeError):
2. CQ-03 IMPORT: LineSeries imported from highcharts_core.options.series.area instead of .line
   • Fix: from highcharts_core.options.series.line import LineSeries
3. DE-01 MODERATE: Great circles all use the same line style, reducing distinguishability
   • Fix: Use different dash styles (solid, dashed, dotted) per feature type for great circles
4. VQ-02 MINOR: Legend layout cramped with 7 items in one row
   • Fix: Use vertical layout or split into two rows for better readability

AI Feedback for Next Attempt

Fix the Python 2 except syntax (except (AttributeError, TypeError):) and the LineSeries import path. Improve design: differentiate great circle line styles per feature type (solid/dashed/dotted), reorganize the legend into a vertical or two-row layout for better readability. Consider slightly increasing pole marker sizes for better visibility at density clusters.

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 Schmidt equal-area (lower-hemisphere) stereonet projection on a square canvas with a light gray (#FAFAFA) background. A solid dark circle forms the primitive boundary, with dotted concentric circles at 15° dip intervals and dotted radial lines every 30° forming a subtle grid. Cardinal directions (N, S, E, W) are labeled in bold around the perimeter, with intermediate degree markings (30°, 60°, 120°, 150°, 210°, 240°, 300°, 330°) and tick marks every 10°. Three feature types are plotted: Bedding (blue #306998) with poles clustered in the central-south area and great circles arcing across the SW quadrant; Joints (orange #E5863D) with poles tightly clustered in the NE quadrant and great circles crossing the S-SW area; and Faults (purple #8B5CF6) with poles more scattered in the E and SE areas. Green semi-transparent density contours (Kamb-style) overlay the pole data highlighting the two main concentration zones. A horizontal legend at the bottom lists all seven series: Bedding/Joints/Faults planes and poles, plus density contours. The title reads "stereonet-equal-area · highcharts · pyplots.ai" with subtitle "Lower Hemisphere Equal-Area (Schmidt) Projection".

Score: 84/100

Category	Score	Max
Visual Quality	26	30
Design Excellence	14	20
Spec Compliance	15	15
Data Quality	14	15
Code Quality	8	10
Library Mastery	7	10
Total	84	100

Visual Quality (26/30)

• VQ-01: Text Legibility (7/8) - Font sizes explicitly set (56px title, 38px subtitle, 30-38px labels). All text readable. Legend text at bottom is slightly small relative to the large canvas.
• VQ-02: No Overlap (5/6) - Generally clean layout. Minor crowding near some degree labels in the NE quadrant where data is dense.
• VQ-03: Element Visibility (5/6) - Poles well-sized (radius 10 with white border). Great circles are somewhat thin at 2.5px width with 0.7 opacity, making them harder to trace across the stereonet.
• VQ-04: Color Accessibility (4/4) - Excellent colorblind-safe palette: blue, orange, and purple are easily distinguishable under all color vision types.
• VQ-05: Layout & Canvas (3/4) - Square format is ideal for a stereonet. The stereonet fills the canvas well, though the legend floats somewhat isolated at the bottom with a gap.
• VQ-06: Axis Labels & Title (2/2) - Descriptive title with correct format, informative subtitle, compass directions and degree markings around perimeter.

Design Excellence (14/20)

• DE-01: Aesthetic Sophistication (6/8) - Strong design: custom colorblind-safe palette, professional typography with Segoe UI font family, intentional color hierarchy with muted green contours vs. vibrant feature colors. Clearly above configured defaults.
• DE-02: Visual Refinement (4/6) - Subtle dotted grid with low opacity (0.25), axes completely hidden, clean background. Good whitespace management with generous margins. Tick marks differentiate major/minor intervals.
• DE-03: Data Storytelling (4/6) - Visual hierarchy guides the viewer: density contours immediately draw attention to preferred orientations, color coding distinguishes three geological feature types, and the combination of great circles + poles + contours tells the structural geology story. Viewer can identify the two main clusters.

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) - Correct Schmidt equal-area lower-hemisphere projection with proper mathematical transformation.
• SC-02: Required Features (4/4) - All spec features present: great circles for planes, poles to planes as points, density contours (Kamb-style via KDE), color-coded by feature_type, degree tick marks every 10°, N label, legend.
• SC-03: Data Mapping (3/3) - Strike/dip correctly mapped to both great circles and pole positions using proper equal-area projection formulas.
• SC-04: Title & Legend (3/3) - Title "stereonet-equal-area · highcharts · pyplots.ai" matches required format. Legend labels clearly distinguish planes vs. poles for each feature type.

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6) - Three distinct feature types (bedding, joints, faults) with different orientations and clustering patterns. Shows both tight clusters (bedding, joints) and scattered data (faults). Could benefit from showing a wider range of dip angles.
• DQ-02: Realistic Context (5/5) - Geological field measurement campaign with bedding planes (NE-striking, moderate dip), joint sets (NW-striking, steep), and faults (N-S, steep). Highly realistic structural geology scenario.
• DQ-03: Appropriate Scale (4/4) - 90 total measurements (40+35+15) within the spec's 30-200 range. Strike values 0-360°, dips 5-89° — all geologically plausible.

Code Quality (8/10)

• CQ-01: KISS Structure (3/3) - Linear flow: imports → data generation → chart config → grid/ticks → contours → great circles → poles → render. No functions or classes.
• CQ-02: Reproducibility (2/2) - np.random.seed(42) set at the start.
• CQ-03: Clean Imports (1/2) - LineSeries imported from highcharts_core.options.series.area rather than highcharts_core.options.series.line, which is misleading. All other imports used.
• CQ-04: Code Elegance (1/2) - The except AttributeError, TypeError: syntax on lines 305 and 324 uses Python 2 tuple-catch syntax instead of except (AttributeError, TypeError):. This is a latent bug. The contour extraction fallback logic is also somewhat verbose.
• CQ-05: Output & API (1/1) - Saves as plot.png via Selenium screenshot and plot.html for interactive use.

Library Mastery (7/10)

• LM-01: Idiomatic Usage (4/5) - Good use of highcharts_core API: Chart with container, HighchartsOptions, typed series (ScatterSeries, LineSeries), annotations API for labels, to_js_literal() for rendering. Could use more dictionary-based configuration for efficiency.
• LM-02: Distinctive Features (3/5) - Uses Highcharts annotations API for compass labels (positioning labels at data coordinates), interactive tooltips on poles, and HTML export alongside PNG. The annotations feature is somewhat distinctive to Highcharts.

Score Caps Applied

• None

Strengths

• Mathematically correct equal-area (Schmidt) projection with proper pole and great circle calculations
• Excellent spec compliance — all required features implemented including density contours, great circles, poles, tick marks, and compass labels
• Strong colorblind-safe palette with good visual hierarchy between data layers
• Professional design with subtle grid, clean background, and thoughtful typography
• Realistic geological data with three distinct feature types showing different clustering patterns
• Interactive HTML output alongside static PNG leverages Highcharts' web capabilities

Weaknesses

• LineSeries imported from wrong submodule (area instead of line)
• Python 2 exception syntax except AttributeError, TypeError: on lines 305 and 324 should be except (AttributeError, TypeError):
• Great circle lines are somewhat thin and hard to trace across the full stereonet
• Legend is slightly disconnected from the main plot area

Issues Found

1. CQ-03 MINOR: LineSeries imported from highcharts_core.options.series.area instead of highcharts_core.options.series.line
   • Fix: Change import to from highcharts_core.options.series.line import LineSeries
2. CQ-04 MINOR: Invalid Python 3 exception syntax on lines 305 and 324
   • Fix: Change except AttributeError, TypeError: to except (AttributeError, TypeError):

AI Feedback for Next Attempt

Solid implementation with full spec compliance and professional design. The main code quality issues are the incorrect LineSeries import path and the Python 2 exception syntax. Great circle visibility could be improved with slightly thicker lines. Overall a good implementation that demonstrates competent use of Highcharts for a specialized geological visualization.

Verdict: APPROVED

[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 displays a lower-hemisphere equal-area (Schmidt) stereographic projection on a square canvas with a light gray background. A bold dark primitive circle encloses the projection area, with tick marks every 10° around the perimeter (longer ticks at 30° intervals). Cardinal directions (N, E, S, W) are labeled in bold around the outside, with intermediate degree labels (30°, 60°, 120°, etc.) in regular weight. Subtle dotted concentric circles and radial lines form the stereonet grid. Three geological feature types are plotted: Bedding (blue #306998) with great circle arcs and scatter poles clustered in the south-central area, Joints (orange #E5863D) with great circles and poles concentrated in the NE quadrant, and Faults (purple #8B5CF6) with great circles and poles scattered in the eastern portion. Green semi-transparent density contours overlay the pole data, highlighting preferred orientations especially in the NE and south-central clusters. The title reads "stereonet-equal-area · highcharts · pyplots.ai" with a subtitle "Lower Hemisphere Equal-Area (Schmidt) Projection". A horizontal legend at the bottom lists all seven series: Bedding/Joints/Faults (planes), Bedding/Joints/Faults (poles), and Density contours.

Score: 85/100

Category	Score	Max
Visual Quality	26	30
Design Excellence	14	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	8	10
Library Mastery	7	10
Total	85	100

Visual Quality (26/30)

• VQ-01: Text Legibility (7/8) — Font sizes explicitly set (56px title, 38px subtitle, 30–38px degree labels). All text readable at full resolution; degree labels slightly small but legible.
• VQ-02: No Overlap (5/6) — Legend has 7 items slightly cramped. Minor crowding in NE quadrant where joint poles cluster densely.
• VQ-03: Element Visibility (5/6) — Poles and great circles clearly visible. Some pole markers overlap in dense clusters, slightly reducing individual distinguishability.
• VQ-04: Color Accessibility (4/4) — Blue/orange/purple palette is colorblind-safe with strong contrast against the light background and green contours.
• VQ-05: Layout & Canvas (3/4) — Square canvas is appropriate for the circular projection. Legend is positioned far from the plot with noticeable gap.
• VQ-06: Axis Labels & Title (2/2) — Cardinal directions serve as axis labels; subtitle describes the projection type. Appropriate for a stereonet.

Design Excellence (14/20)

• DE-01: Aesthetic Sophistication (6/8) — Custom colorblind-safe palette, custom font family, intentional visual hierarchy with title/subtitle sizing. Clearly above defaults, approaching publication quality.
• DE-02: Visual Refinement (4/6) — Subtle dotted grid with low opacity, axes hidden, clean background (#FAFAFA). Good refinement but legend styling could be more polished.
• DE-03: Data Storytelling (4/6) — Three distinct geological feature types with characteristically different orientations create a clear structural narrative. Density contours effectively highlight preferred orientations.

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) — Correct equal-area (Schmidt) lower-hemisphere projection with all required geometric elements.
• SC-02: Required Features (4/4) — Great circles for planes, poles to planes as points, density contours (Kamb-style via KDE), color-coding by feature_type, tick marks every 10°, N label, subtle grid.
• SC-03: Data Mapping (3/3) — Strike/dip correctly converted to great circles; poles computed at 90° to planes with proper equal-area projection formula.
• SC-04: Title & Legend (3/3) — Title follows {spec-id} · {library} · pyplots.ai format. Legend labels distinguish planes and poles per feature type.

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) — Three distinct feature types (Bedding: moderate NE dip, Joints: steep NW dip, Faults: steep N-S) with varying cluster tightness and populations (40/35/15).
• DQ-02: Realistic Context (5/5) — Geological field measurements from a mapping campaign with realistic strike/dip distributions for each structural feature type.
• DQ-03: Appropriate Scale (4/4) — Strike values span full azimuth range, dip values are geologically sensible (bedding 35° ± 8°, joints 75° ± 10°, faults 65° ± 12°).

Code Quality (8/10)

• CQ-01: KISS Structure (3/3) — Linear flow: imports → data generation → chart setup → series → render → screenshot.
• CQ-02: Reproducibility (2/2) — np.random.seed(42) ensures deterministic data.
• CQ-03: Clean Imports (1/2) — LineSeries imported from highcharts_core.options.series.area instead of the canonical highcharts_core.options.series.line module.
• CQ-04: Code Elegance (1/2) — except AttributeError, TypeError: on lines 305 and 324 uses Python 2 syntax; should be except (AttributeError, TypeError):.
• CQ-05: Output & API (1/1) — Saves as plot.png via Selenium screenshot. Also generates plot.html for interactivity.

Library Mastery (7/10)

• LM-01: Idiomatic Usage (4/5) — Good use of highcharts_core Python API: Chart with container, HighchartsOptions, typed series classes, annotations API, to_js_literal() for rendering.
• LM-02: Distinctive Features (3/5) — Leverages Highcharts annotations for degree labels, interactive tooltips on pole data, and standalone HTML export for interactivity.

Score Caps Applied

• None

Strengths

• Excellent spec compliance — all required stereonet features (great circles, poles, density contours, grid, tick marks, cardinal labels) are present and correctly computed
• Strong geological data quality with three distinct, realistic feature types showing different structural characteristics
• Professional visual design with custom colorblind-safe palette, subtle dotted grid, and clean typography hierarchy
• Dual output (PNG + interactive HTML) leverages Highcharts' strengths well

Weaknesses

• except AttributeError, TypeError: uses Python 2 except syntax (lines 305, 324) — should be except (AttributeError, TypeError):
• LineSeries imported from area submodule instead of line submodule
• Legend is slightly cramped with 7 items in a single horizontal row

Issues Found

1. CQ-04 LOW: Python 2 except syntax except AttributeError, TypeError: on lines 305 and 324
   • Fix: Change to except (AttributeError, TypeError):
2. CQ-03 LOW: LineSeries imported from wrong submodule
   • Fix: Import from highcharts_core.options.series.line instead of highcharts_core.options.series.area

AI Feedback for Next Attempt

The implementation is strong with excellent spec compliance and data quality. Minor code quality issues remain: fix the Python 2 except syntax and correct the LineSeries import path. The visual design is good but could reach publication quality with tighter legend integration and slightly larger pole markers in dense clusters.

Verdict: REJECTED