From 102b128e7722f942a7ceb5f9d59a7d4dff37ea66 Mon Sep 17 00:00:00 2001 From: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com> Date: Sat, 21 Feb 2026 23:28:21 +0100 Subject: [PATCH 1/8] =?UTF-8?q?update(violin-basic):=20highcharts=20?= =?UTF-8?q?=E2=80=94=20comprehensive=20quality=20review?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Comprehensive quality review improving code quality, data choice, visual design, spec compliance, and library feature usage. --- .../implementations/highcharts.py | 125 ++++++++---------- plots/violin-basic/metadata/highcharts.yaml | 10 +- 2 files changed, 60 insertions(+), 75 deletions(-) diff --git a/plots/violin-basic/implementations/highcharts.py b/plots/violin-basic/implementations/highcharts.py index 23874223ce..7eea0ae953 100644 --- a/plots/violin-basic/implementations/highcharts.py +++ b/plots/violin-basic/implementations/highcharts.py @@ -1,7 +1,7 @@ """ pyplots.ai violin-basic: Basic Violin Plot -Library: highcharts unknown | Python 3.13.11 -Quality: 91/100 | Created: 2025-12-23 +Library: highcharts 1.10.3 | Python 3.14.3 +Quality: /100 | Updated: 2026-02-21 """ import tempfile @@ -19,12 +19,11 @@ from selenium.webdriver.chrome.options import Options -# Data - generate sample distributions for 4 categories +# Data - test scores across 4 study groups with distinct distributions np.random.seed(42) categories = ["Group A", "Group B", "Group C", "Group D"] colors = ["#306998", "#FFD43B", "#9467BD", "#17BECF"] -# Generate data with different distributions raw_data = { "Group A": np.random.normal(50, 12, 200), "Group B": np.concatenate([np.random.normal(40, 8, 100), np.random.normal(65, 8, 100)]), # Bimodal @@ -33,125 +32,115 @@ } # Calculate KDE and statistics for each category -violin_width = 0.35 # Half-width of violin in category units +violin_width = 0.35 violin_data = [] for i, cat in enumerate(categories): data = raw_data[cat] - - # Compute KDE using scipy y_min, y_max = data.min() - 5, data.max() + 5 y_grid = np.linspace(y_min, y_max, 100) kde_func = gaussian_kde(data) density = kde_func(y_grid) - - # Normalize density to fit within violin width density_norm = density / density.max() * violin_width - # Statistics for markers - q1 = np.percentile(data, 25) - median = np.percentile(data, 50) - q3 = np.percentile(data, 75) - violin_data.append( { "category": cat, "index": i, "y_grid": y_grid, "density": density_norm, - "q1": q1, - "median": median, - "q3": q3, + "q1": float(np.percentile(data, 25)), + "median": float(np.percentile(data, 50)), + "q3": float(np.percentile(data, 75)), "color": colors[i], } ) -# Create chart +# Chart chart = Chart(container="container") chart.options = HighchartsOptions() -# Chart configuration chart.options.chart = { "type": "scatter", "width": 4800, "height": 2700, "backgroundColor": "#ffffff", - "marginBottom": 200, - "marginLeft": 250, - "marginRight": 100, + "marginBottom": 180, + "marginLeft": 240, + "marginRight": 80, + "marginTop": 160, } -# Title chart.options.title = { - "text": "violin-basic · highcharts · pyplots.ai", - "style": {"fontSize": "84px", "fontWeight": "bold"}, + "text": "violin-basic \u00b7 highcharts \u00b7 pyplots.ai", + "style": {"fontSize": "72px", "fontWeight": "bold", "color": "#333333"}, } -# X-axis (categories) chart.options.x_axis = { - "title": {"text": "Study Group", "style": {"fontSize": "56px"}}, - "labels": {"style": {"fontSize": "44px"}, "format": "{value}"}, + "title": {"text": "Study Group", "style": {"fontSize": "52px", "color": "#555555"}}, + "labels": {"style": {"fontSize": "44px", "color": "#555555"}}, "min": -0.5, "max": 3.5, "tickPositions": [0, 1, 2, 3], "categories": categories, "lineWidth": 2, + "lineColor": "#cccccc", + "tickLength": 0, } -# Y-axis (values) chart.options.y_axis = { - "title": {"text": "Test Score (points)", "style": {"fontSize": "56px"}}, - "labels": {"style": {"fontSize": "44px"}}, + "title": {"text": "Test Score (points)", "style": {"fontSize": "52px", "color": "#555555"}}, + "labels": {"style": {"fontSize": "44px", "color": "#555555"}}, "gridLineWidth": 1, - "gridLineColor": "rgba(0, 0, 0, 0.15)", + "gridLineColor": "rgba(0, 0, 0, 0.08)", + "lineWidth": 2, + "lineColor": "#cccccc", } -# Legend -chart.options.legend = {"enabled": True, "itemStyle": {"fontSize": "44px"}} +chart.options.legend = { + "enabled": True, + "itemStyle": {"fontSize": "40px", "color": "#555555"}, + "verticalAlign": "top", + "align": "right", + "layout": "vertical", + "x": -20, + "y": 80, + "floating": True, +} -# Plot options chart.options.plot_options = { - "polygon": {"lineWidth": 3, "fillOpacity": 0.6, "enableMouseTracking": True}, - "scatter": {"marker": {"radius": 20, "symbol": "circle"}, "zIndex": 10}, + "polygon": {"lineWidth": 2, "fillOpacity": 0.55, "enableMouseTracking": True}, + "scatter": {"marker": {"radius": 18, "symbol": "circle"}, "zIndex": 10}, } -# Add violin shapes as polygon series +# Violin shapes as polygon series for v in violin_data: - # Create polygon points for the violin shape - # Go up the right side, then down the left side to form a closed shape polygon_points = [] - - # Right side (positive x offset from center) for y_val, dens in zip(v["y_grid"], v["density"], strict=True): polygon_points.append([float(v["index"] + dens), float(y_val)]) - - # Left side (negative x offset from center) - reversed to close the polygon for j in range(len(v["y_grid"]) - 1, -1, -1): - y_val = v["y_grid"][j] - dens = v["density"][j] - polygon_points.append([float(v["index"] - dens), float(y_val)]) + polygon_points.append([float(v["index"] - v["density"][j]), float(v["y_grid"][j])]) series = PolygonSeries() series.data = polygon_points series.name = v["category"] series.color = v["color"] series.fill_color = v["color"] - series.fill_opacity = 0.6 + series.fill_opacity = 0.55 chart.add_series(series) -# Add median markers as scatter points +# Median markers med_series = ScatterSeries() med_series.data = [[float(v["index"]), float(v["median"])] for v in violin_data] med_series.name = "Median" -med_series.color = "#FF0000" -med_series.marker = {"fillColor": "#FF0000", "lineColor": "#000000", "lineWidth": 5, "radius": 22, "symbol": "diamond"} +med_series.color = "#333333" +med_series.marker = {"fillColor": "#ffffff", "lineColor": "#333333", "lineWidth": 6, "radius": 18, "symbol": "diamond"} med_series.z_index = 20 chart.add_series(med_series) -# Add quartile box indicators (thin rectangles for IQR) +# IQR boxes (thin rectangles for interquartile range) for v in violin_data: - # Create a thin box for IQR - box_width = 0.05 + box_width = 0.06 box_points = [ [float(v["index"] - box_width), float(v["q1"])], [float(v["index"] + box_width), float(v["q1"])], @@ -163,22 +152,20 @@ box_series.data = box_points box_series.name = f"{v['category']} IQR" box_series.show_in_legend = False - box_series.color = "#000000" - box_series.fill_color = "#000000" - box_series.fill_opacity = 0.8 + box_series.color = "#333333" + box_series.fill_color = "#333333" + box_series.fill_opacity = 0.85 chart.add_series(box_series) -# Download Highcharts JS files -highcharts_url = "https://code.highcharts.com/highcharts.js" +# Export +highcharts_url = "https://cdn.jsdelivr.net/npm/highcharts@11/highcharts.js" with urllib.request.urlopen(highcharts_url, timeout=30) as response: highcharts_js = response.read().decode("utf-8") -# Polygon requires highcharts-more.js -highcharts_more_url = "https://code.highcharts.com/highcharts-more.js" +highcharts_more_url = "https://cdn.jsdelivr.net/npm/highcharts@11/highcharts-more.js" with urllib.request.urlopen(highcharts_more_url, timeout=30) as response: highcharts_more_js = response.read().decode("utf-8") -# Generate HTML with inline scripts html_str = chart.to_js_literal() html_content = f""" @@ -193,19 +180,17 @@ """ -# Write temp HTML file with tempfile.NamedTemporaryFile(mode="w", suffix=".html", delete=False, encoding="utf-8") as f: f.write(html_content) temp_path = f.name -# Save HTML for interactive viewing with open("plot.html", "w", encoding="utf-8") as f: standalone_html = f""" - - + +
@@ -214,20 +199,20 @@ """ f.write(standalone_html) -# Take screenshot with Selenium +# Screenshot chrome_options = Options() chrome_options.add_argument("--headless") chrome_options.add_argument("--no-sandbox") chrome_options.add_argument("--disable-dev-shm-usage") chrome_options.add_argument("--disable-gpu") -chrome_options.add_argument("--window-size=5000,3000") +chrome_options.add_argument("--window-size=4900,2800") driver = webdriver.Chrome(options=chrome_options) driver.get(f"file://{temp_path}") -time.sleep(5) # Wait for chart to render +time.sleep(5) container = driver.find_element("id", "container") container.screenshot("plot.png") driver.quit() -Path(temp_path).unlink() # Clean up temp file +Path(temp_path).unlink() diff --git a/plots/violin-basic/metadata/highcharts.yaml b/plots/violin-basic/metadata/highcharts.yaml index 33fba10d6f..57eb4ae2e8 100644 --- a/plots/violin-basic/metadata/highcharts.yaml +++ b/plots/violin-basic/metadata/highcharts.yaml @@ -1,16 +1,16 @@ library: highcharts specification_id: violin-basic created: '2025-12-23T00:36:59Z' -updated: '2025-12-23T07:20:01Z' -generated_by: claude-opus-4-5-20251101 +updated: '2026-02-21T22:25:00+00:00' +generated_by: claude-opus-4-6 workflow_run: 20447783582 issue: 0 -python_version: 3.13.11 -library_version: unknown +python_version: '3.14.3' +library_version: '1.10.3' preview_url: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot.png preview_thumb: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot_thumb.png preview_html: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot.html -quality_score: 91 +quality_score: null impl_tags: dependencies: - scipy From c65bdd88736c42a7dafbd565ff8a6e47b253f450 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sat, 21 Feb 2026 22:33:47 +0000 Subject: [PATCH 2/8] chore(highcharts): update quality score 79 and review feedback for violin-basic --- .../implementations/highcharts.py | 2 +- plots/violin-basic/metadata/highcharts.yaml | 289 +++++++++--------- 2 files changed, 152 insertions(+), 139 deletions(-) diff --git a/plots/violin-basic/implementations/highcharts.py b/plots/violin-basic/implementations/highcharts.py index 7eea0ae953..b31052eeaa 100644 --- a/plots/violin-basic/implementations/highcharts.py +++ b/plots/violin-basic/implementations/highcharts.py @@ -1,7 +1,7 @@ """ pyplots.ai violin-basic: Basic Violin Plot Library: highcharts 1.10.3 | Python 3.14.3 -Quality: /100 | Updated: 2026-02-21 +Quality: 79/100 | Updated: 2026-02-21 """ import tempfile diff --git a/plots/violin-basic/metadata/highcharts.yaml b/plots/violin-basic/metadata/highcharts.yaml index 57eb4ae2e8..0ae52533b8 100644 --- a/plots/violin-basic/metadata/highcharts.yaml +++ b/plots/violin-basic/metadata/highcharts.yaml @@ -1,224 +1,237 @@ library: highcharts specification_id: violin-basic created: '2025-12-23T00:36:59Z' -updated: '2026-02-21T22:25:00+00:00' +updated: '2026-02-21T22:33:47Z' generated_by: claude-opus-4-6 workflow_run: 20447783582 issue: 0 -python_version: '3.14.3' -library_version: '1.10.3' +python_version: 3.14.3 +library_version: 1.10.3 preview_url: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot.png preview_thumb: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot_thumb.png preview_html: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot.html -quality_score: null +quality_score: 79 impl_tags: dependencies: - - scipy - - selenium + - scipy + - selenium techniques: - - html-export + - html-export + - custom-legend patterns: - - data-generation - dataprep: [] - styling: [] + - data-generation + - iteration-over-groups + dataprep: + - kde + styling: + - alpha-blending + - grid-styling review: strengths: - - Excellent distribution variety demonstrating violin plot capabilities (normal, - bimodal, skewed) - - Clear colorblind-safe color palette with good contrast - - Proper use of Highcharts PolygonSeries to create violin shapes with KDE - - Includes median markers and IQR boxes as spec requires - - Realistic test score scenario with appropriate data ranges - - Both PNG and interactive HTML outputs provided - - Clean separation of violin shapes with no overlap + - Excellent distribution variety showing normal, bimodal, and skewed shapes that + showcase violin plot capabilities + - Clean visual refinement with subtle grid (0.08 opacity), removed ticks, and semi-transparent + fills + - All font sizes explicitly set for high-resolution output (title 72px, axis titles + 52px, labels 44px) + - Correct title format and complete legend with all groups plus median marker weaknesses: - - Legend positioning at bottom overlaps slightly with x-axis title - could be better - placed - - The IQR boxes are very thin (box_width=0.05) and could be slightly wider for better - visibility - - Grid lines could be even more subtle (currently alpha=0.15, could use 0.1) - image_description: 'The plot displays four violin shapes representing Study Groups - A, B, C, and D on a white background. Each violin uses a distinct colorblind-safe - color: blue (#306998) for Group A, yellow (#FFD43B) for Group B, purple (#9467BD) - for Group C, and cyan (#17BECF) for Group D. Each violin features a centered black - IQR (interquartile range) box and a red diamond marker indicating the median. - The title "violin-basic · highcharts · pyplots.ai" appears at the top in bold. - The Y-axis labeled "Test Score (points)" ranges from 0-130, and the X-axis labeled - "Study Group" shows the four category labels. A legend at the bottom identifies - each group color and the median marker. The violins effectively demonstrate different - distribution shapes: Group A shows a symmetric normal distribution, Group B displays - clear bimodality with two bulges, Group C is normally distributed, and Group D - exhibits right-skewed exponential distribution with a long upper tail reaching - ~120.' + - Generic group labels (Group A-D) instead of realistic context-specific names reduce + data quality + - Median shown as diamond marker rather than a line as spec requests + - Group D exponential tail extends to ~122 which is unrealistic for test scores + and wastes vertical space + - Does not leverage Highcharts interactive features like custom tooltips showing + distribution statistics + - Redundant plot.html file generation alongside the temp file used for screenshot + image_description: The plot displays four violin shapes arranged horizontally, each + representing a study group (Group A through Group D). Group A is steel blue (#306998), + Group B is yellow (#FFD43B), Group C is purple (#9467BD), and Group D is cyan + (#17BECF). Each violin shows a mirrored KDE density curve with a dark rectangular + IQR box inside and a white diamond-shaped median marker. Group A shows a roughly + normal distribution centered around 50. Group B displays a clear bimodal shape + with humps near 40 and 65. Group C is a normal distribution centered around 60. + Group D is right-skewed with a very thin tail extending up to approximately 122. + The y-axis reads "Test Score (points)" ranging from 0 to 130, and the x-axis reads + "Study Group" with category labels. The title reads "violin-basic · highcharts + · pyplots.ai" centered at the top. A floating legend in the top-right corner lists + all four groups with colored circle markers plus a "Median" entry with a diamond. + The background is clean white with very subtle horizontal grid lines. The overall + layout is well-proportioned though the extended y-axis range (to 130) due to Group + D's tail creates some wasted vertical space. criteria_checklist: visual_quality: - score: 36 - max: 40 + score: 27 + max: 30 items: - id: VQ-01 name: Text Legibility - score: 9 - max: 10 + score: 8 + max: 8 passed: true - comment: Title, axis labels, and tick marks are all clearly readable at full - size. Font sizes are appropriately scaled for 4800x2700 resolution. + comment: 'All font sizes explicitly set: title 72px, axis titles 52px, tick + labels 44px, legend 40px' - id: VQ-02 name: No Overlap - score: 8 - max: 8 + score: 6 + max: 6 passed: true - comment: No overlapping text elements. Category labels, axis titles, and legend - are all clearly separated. + comment: No overlapping text elements; legend floats cleanly in top-right - id: VQ-03 name: Element Visibility - score: 7 - max: 8 + score: 5 + max: 6 passed: true - comment: Violin shapes are clearly visible with good fill opacity. IQR boxes - and median markers are well-sized and prominent. + comment: Violin shapes well-formed; Group D thin tail spike barely visible + at top - id: VQ-04 name: Color Accessibility - score: 5 - max: 5 + score: 3 + max: 4 passed: true - comment: Uses colorblind-safe palette (blue, yellow, purple, cyan) - no red-green - conflicts. + comment: Blue/yellow/purple/cyan avoids red-green; yellow slightly low contrast + on white - id: VQ-05 - name: Layout Balance - score: 4 - max: 5 + name: Layout & Canvas + score: 3 + max: 4 passed: true - comment: Good overall layout with appropriate margins. Slight excess whitespace - at top of chart above Group D's extended distribution. + comment: Good proportions but Group D tail forces y-axis to 130, wasting vertical + space - id: VQ-06 - name: Axis Labels + name: Axis Labels & Title score: 2 max: 2 passed: true - comment: 'Descriptive labels with units: "Test Score (points)" and "Study - Group".' - - id: VQ-07 - name: Grid & Legend - score: 1 - max: 2 + comment: Test Score (points) includes units; Study Group is descriptive + design_excellence: + score: 12 + max: 20 + items: + - id: DE-01 + name: Aesthetic Sophistication + score: 5 + max: 8 + passed: true + comment: Custom palette, semi-transparent fills, dark IQR boxes with diamond + medians; above defaults but not publication-level + - id: DE-02 + name: Visual Refinement + score: 4 + max: 6 passed: true - comment: Grid is subtle. Legend is positioned at bottom but could be placed - more optimally. + comment: Subtle grid (0.08 opacity), light axis lines, removed ticks; good + refinement visible + - id: DE-03 + name: Data Storytelling + score: 3 + max: 6 + passed: true + comment: Four distinct distribution shapes create comparison but no particular + emphasis or focal point spec_compliance: - score: 24 - max: 25 + score: 14 + max: 15 items: - id: SC-01 name: Plot Type - score: 8 - max: 8 - passed: true - comment: Correct violin plot type with kernel density estimation shown via - polygon shapes. - - id: SC-02 - name: Data Mapping score: 5 max: 5 passed: true - comment: Categories on X-axis, values on Y-axis correctly assigned. - - id: SC-03 + comment: Correct violin plot with mirrored KDE density shapes + - id: SC-02 name: Required Features - score: 4 - max: 5 + score: 3 + max: 4 passed: true - comment: Shows quartile markers (IQR box), median line (diamond marker), mirrored - density on both sides. Split violin comparison not shown but spec says "consider" - not required. - - id: SC-04 - name: Data Range + comment: Mirrored density and IQR boxes present; median shown as diamond marker + instead of line + - id: SC-03 + name: Data Mapping score: 3 max: 3 passed: true - comment: All data visible within the axis ranges (0-130 appropriately covers - all distributions). - - id: SC-05 - name: Legend Accuracy - score: 2 - max: 2 - passed: true - comment: Legend correctly identifies all groups and median marker. - - id: SC-06 - name: Title Format - score: 2 - max: 2 + comment: Categories on x-axis, values on y-axis, all data correctly mapped + - id: SC-04 + name: Title & Legend + score: 3 + max: 3 passed: true - comment: 'Correct format: "violin-basic · highcharts · pyplots.ai"' + comment: Title format correct; legend labels match data groups plus Median data_quality: - score: 19 - max: 20 + score: 12 + max: 15 items: - id: DQ-01 name: Feature Coverage - score: 7 - max: 8 + score: 6 + max: 6 passed: true - comment: Excellent variety showing normal (A, C), bimodal (B), and skewed - (D) distributions. Demonstrates the plot type's ability to reveal distribution - shapes. + comment: Normal, bimodal, shifted-normal, and right-skewed distributions showcase + violin capabilities - id: DQ-02 name: Realistic Context - score: 7 - max: 7 + score: 3 + max: 5 passed: true - comment: Test scores by study group is a plausible, real-world scenario that - makes sense for comparing distributions. + comment: Test scores plausible but group labels are generic (Group A-D) - id: DQ-03 name: Appropriate Scale - score: 5 - max: 5 + score: 3 + max: 4 passed: true - comment: Test scores in 0-130 range with most values in 20-100 range are realistic - and sensible. + comment: Mostly realistic; Group D exponential tail reaching ~122 slightly + unrealistic for test scores code_quality: - score: 8 + score: 9 max: 10 items: - id: CQ-01 name: KISS Structure - score: 2 + score: 3 max: 3 passed: true - comment: Follows imports → data → plot → save structure, but code is more - complex than strictly necessary due to manual polygon construction for violins. + comment: 'Flat structure: imports, data, KDE, chart config, series, export' - id: CQ-02 name: Reproducibility - score: 3 - max: 3 + score: 2 + max: 2 passed: true - comment: Uses np.random.seed(42) for reproducibility. + comment: np.random.seed(42) set - id: CQ-03 name: Clean Imports score: 2 max: 2 passed: true - comment: All imports are used. + comment: All imports used - id: CQ-04 - name: No Deprecated API + name: Code Elegance score: 1 - max: 1 + max: 2 passed: true - comment: Uses current API. + comment: Polygon construction appropriate but redundant plot.html generation - id: CQ-05 - name: Output Correct - score: 0 + name: Output & API + score: 1 max: 1 passed: true - comment: Saves both plot.png and plot.html correctly. - library_features: - score: 4 - max: 5 + comment: Saves plot.png via Selenium, uses current highcharts_core API + library_mastery: + score: 5 + max: 10 items: - - id: LF-01 - name: Uses distinctive library features - score: 4 + - id: LM-01 + name: Idiomatic Usage + score: 3 max: 5 passed: true - comment: Good use of PolygonSeries and ScatterSeries to construct custom violin - shapes. Uses highcharts-more.js for polygon support. Interactive HTML output - included. - verdict: APPROVED + comment: Correct use of HighchartsOptions, PolygonSeries, ScatterSeries; building + from raw polygons is necessary but basic + - id: LM-02 + name: Distinctive Features + score: 2 + max: 5 + passed: false + comment: Uses enableMouseTracking and floating legend but doesn't leverage + tooltips, animation, or interactive strengths + verdict: REJECTED From 5e5fba5aa99d4076a853a0eb62a3007cdbc5c763 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sat, 21 Feb 2026 22:40:07 +0000 Subject: [PATCH 3/8] fix(highcharts): address review feedback for violin-basic Attempt 1/3 - fixes based on AI review --- .../implementations/highcharts.py | 114 ++++++++++++------ 1 file changed, 80 insertions(+), 34 deletions(-) diff --git a/plots/violin-basic/implementations/highcharts.py b/plots/violin-basic/implementations/highcharts.py index b31052eeaa..d515b426bb 100644 --- a/plots/violin-basic/implementations/highcharts.py +++ b/plots/violin-basic/implementations/highcharts.py @@ -1,7 +1,6 @@ -""" pyplots.ai +"""pyplots.ai violin-basic: Basic Violin Plot Library: highcharts 1.10.3 | Python 3.14.3 -Quality: 79/100 | Updated: 2026-02-21 """ import tempfile @@ -13,7 +12,6 @@ from highcharts_core.chart import Chart from highcharts_core.options import HighchartsOptions from highcharts_core.options.series.polygon import PolygonSeries -from highcharts_core.options.series.scatter import ScatterSeries from scipy.stats import gaussian_kde from selenium import webdriver from selenium.webdriver.chrome.options import Options @@ -21,14 +19,14 @@ # Data - test scores across 4 study groups with distinct distributions np.random.seed(42) -categories = ["Group A", "Group B", "Group C", "Group D"] +categories = ["Control", "Tutorial", "Self-Study", "Intensive"] colors = ["#306998", "#FFD43B", "#9467BD", "#17BECF"] raw_data = { - "Group A": np.random.normal(50, 12, 200), - "Group B": np.concatenate([np.random.normal(40, 8, 100), np.random.normal(65, 8, 100)]), # Bimodal - "Group C": np.random.normal(60, 10, 200), - "Group D": np.random.exponential(15, 200) + 30, # Skewed + "Control": np.random.normal(50, 12, 200), + "Tutorial": np.concatenate([np.random.normal(40, 8, 100), np.random.normal(65, 8, 100)]), + "Self-Study": np.random.normal(60, 10, 200), + "Intensive": np.clip(np.random.exponential(15, 200) + 30, 0, 100), } # Calculate KDE and statistics for each category @@ -37,7 +35,7 @@ for i, cat in enumerate(categories): data = raw_data[cat] - y_min, y_max = data.min() - 5, data.max() + 5 + y_min, y_max = data.min() - 3, data.max() + 3 y_grid = np.linspace(y_min, y_max, 100) kde_func = gaussian_kde(data) density = kde_func(y_grid) @@ -52,6 +50,9 @@ "q1": float(np.percentile(data, 25)), "median": float(np.percentile(data, 50)), "q3": float(np.percentile(data, 75)), + "mean": float(np.mean(data)), + "std": float(np.std(data)), + "n": len(data), "color": colors[i], } ) @@ -69,6 +70,7 @@ "marginLeft": 240, "marginRight": 80, "marginTop": 160, + "animation": {"duration": 1000}, } chart.options.title = { @@ -95,6 +97,8 @@ "gridLineColor": "rgba(0, 0, 0, 0.08)", "lineWidth": 2, "lineColor": "#cccccc", + "min": 0, + "max": 105, } chart.options.legend = { @@ -108,12 +112,25 @@ "floating": True, } +chart.options.tooltip = { + "enabled": True, + "shared": False, + "useHTML": True, + "style": {"fontSize": "28px"}, + "headerFormat": "", + "backgroundColor": "rgba(255, 255, 255, 0.95)", + "borderColor": "#cccccc", + "borderRadius": 8, + "shadow": {"color": "rgba(0,0,0,0.15)", "offsetX": 2, "offsetY": 2, "width": 4}, +} + chart.options.plot_options = { - "polygon": {"lineWidth": 2, "fillOpacity": 0.55, "enableMouseTracking": True}, - "scatter": {"marker": {"radius": 18, "symbol": "circle"}, "zIndex": 10}, + "polygon": {"lineWidth": 2, "fillOpacity": 0.55, "enableMouseTracking": True, "animation": True}, + "scatter": {"marker": {"radius": 18, "symbol": "circle"}, "zIndex": 10, "enableMouseTracking": True}, + "series": {"animation": {"duration": 1200, "easing": "easeOutBounce"}}, } -# Violin shapes as polygon series +# Violin shapes as polygon series with tooltip showing statistics for v in violin_data: polygon_points = [] for y_val, dens in zip(v["y_grid"], v["density"], strict=True): @@ -127,16 +144,41 @@ series.color = v["color"] series.fill_color = v["color"] series.fill_opacity = 0.55 + series.tooltip = { + "pointFormat": ( + f'' + f"{v['category']}
" + f"n = {v['n']}
" + f"Mean: {v['mean']:.1f}
" + f"Median: {v['median']:.1f}
" + f"Q1: {v['q1']:.1f} | Q3: {v['q3']:.1f}
" + f"Std Dev: {v['std']:.1f}" + ) + } chart.add_series(series) -# Median markers -med_series = ScatterSeries() -med_series.data = [[float(v["index"]), float(v["median"])] for v in violin_data] -med_series.name = "Median" -med_series.color = "#333333" -med_series.marker = {"fillColor": "#ffffff", "lineColor": "#333333", "lineWidth": 6, "radius": 18, "symbol": "diamond"} -med_series.z_index = 20 -chart.add_series(med_series) +# Median lines (horizontal lines across each violin at the median position) +for v in violin_data: + # Find density at median to determine line width + kde_func = gaussian_kde(raw_data[v["category"]]) + med_density = kde_func(v["median"])[0] + max_density = max(kde_func(v["y_grid"])) + line_half_width = (med_density / max_density) * violin_width * 0.85 + + med_line = PolygonSeries() + med_line.data = [ + [float(v["index"] - line_half_width), float(v["median"])], + [float(v["index"] + line_half_width), float(v["median"])], + ] + med_line.name = "Median" if v["index"] == 0 else f"Median {v['category']}" + med_line.show_in_legend = v["index"] == 0 + med_line.color = "#ffffff" + med_line.line_width = 8 + med_line.fill_opacity = 0 + med_line.z_index = 15 + med_line.enable_mouse_tracking = False + med_line.marker = {"enabled": False} + chart.add_series(med_line) # IQR boxes (thin rectangles for interquartile range) for v in violin_data: @@ -155,6 +197,7 @@ box_series.color = "#333333" box_series.fill_color = "#333333" box_series.fill_opacity = 0.85 + box_series.enable_mouse_tracking = False chart.add_series(box_series) # Export @@ -167,37 +210,40 @@ highcharts_more_js = response.read().decode("utf-8") html_str = chart.to_js_literal() -html_content = f""" + +# plot.html for interactive viewing (CDN links for browser) +with open("plot.html", "w", encoding="utf-8") as f: + standalone_html = f""" - - + + -
+
""" + f.write(standalone_html) -with tempfile.NamedTemporaryFile(mode="w", suffix=".html", delete=False, encoding="utf-8") as f: - f.write(html_content) - temp_path = f.name - -with open("plot.html", "w", encoding="utf-8") as f: - standalone_html = f""" +# Temp HTML for screenshot (inline JS for headless Chrome) +html_content = f""" - - + + -
+
""" - f.write(standalone_html) + +with tempfile.NamedTemporaryFile(mode="w", suffix=".html", delete=False, encoding="utf-8") as f: + f.write(html_content) + temp_path = f.name # Screenshot chrome_options = Options() From 0f2907af1ebc428b57bd92067e95935ea1abb6ab Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sat, 21 Feb 2026 22:46:43 +0000 Subject: [PATCH 4/8] chore(highcharts): update quality score 86 and review feedback for violin-basic --- .../implementations/highcharts.py | 3 +- plots/violin-basic/metadata/highcharts.yaml | 160 +++++++++--------- 2 files changed, 82 insertions(+), 81 deletions(-) diff --git a/plots/violin-basic/implementations/highcharts.py b/plots/violin-basic/implementations/highcharts.py index d515b426bb..b35401ce02 100644 --- a/plots/violin-basic/implementations/highcharts.py +++ b/plots/violin-basic/implementations/highcharts.py @@ -1,6 +1,7 @@ -"""pyplots.ai +""" pyplots.ai violin-basic: Basic Violin Plot Library: highcharts 1.10.3 | Python 3.14.3 +Quality: 86/100 | Updated: 2026-02-21 """ import tempfile diff --git a/plots/violin-basic/metadata/highcharts.yaml b/plots/violin-basic/metadata/highcharts.yaml index 0ae52533b8..5f67ad6309 100644 --- a/plots/violin-basic/metadata/highcharts.yaml +++ b/plots/violin-basic/metadata/highcharts.yaml @@ -1,7 +1,7 @@ library: highcharts specification_id: violin-basic created: '2025-12-23T00:36:59Z' -updated: '2026-02-21T22:33:47Z' +updated: '2026-02-21T22:46:42Z' generated_by: claude-opus-4-6 workflow_run: 20447783582 issue: 0 @@ -10,12 +10,13 @@ library_version: 1.10.3 preview_url: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot.png preview_thumb: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot_thumb.png preview_html: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot.html -quality_score: 79 +quality_score: 86 impl_tags: dependencies: - scipy - selenium techniques: + - hover-tooltips - html-export - custom-legend patterns: @@ -28,40 +29,37 @@ impl_tags: - grid-styling review: strengths: - - Excellent distribution variety showing normal, bimodal, and skewed shapes that - showcase violin plot capabilities - - Clean visual refinement with subtle grid (0.08 opacity), removed ticks, and semi-transparent - fills - - All font sizes explicitly set for high-resolution output (title 72px, axis titles - 52px, labels 44px) - - Correct title format and complete legend with all groups plus median marker + - Excellent data choices with four distinct distribution shapes (normal, bimodal, + shifted normal, right-skewed) that showcase the violin plot ability to reveal + distribution differences + - 'All spec features implemented correctly: mirrored KDE, IQR quartile boxes, median + lines' + - Interactive HTML tooltips showing full statistics (n, mean, median, Q1, Q3, std + dev) — meaningful use of Highcharts interactivity + - Clean code structure with appropriate complexity for manual violin construction + - Custom color palette with good contrast and cohesion weaknesses: - - Generic group labels (Group A-D) instead of realistic context-specific names reduce - data quality - - Median shown as diamond marker rather than a line as spec requests - - Group D exponential tail extends to ~122 which is unrealistic for test scores - and wastes vertical space - - Does not leverage Highcharts interactive features like custom tooltips showing - distribution statistics - - Redundant plot.html file generation alongside the temp file used for screenshot - image_description: The plot displays four violin shapes arranged horizontally, each - representing a study group (Group A through Group D). Group A is steel blue (#306998), - Group B is yellow (#FFD43B), Group C is purple (#9467BD), and Group D is cyan - (#17BECF). Each violin shows a mirrored KDE density curve with a dark rectangular - IQR box inside and a white diamond-shaped median marker. Group A shows a roughly - normal distribution centered around 50. Group B displays a clear bimodal shape - with humps near 40 and 65. Group C is a normal distribution centered around 60. - Group D is right-skewed with a very thin tail extending up to approximately 122. - The y-axis reads "Test Score (points)" ranging from 0 to 130, and the x-axis reads - "Study Group" with category labels. The title reads "violin-basic · highcharts - · pyplots.ai" centered at the top. A floating legend in the top-right corner lists - all four groups with colored circle markers plus a "Median" entry with a diamond. - The background is clean white with very subtle horizontal grid lines. The overall - layout is well-proportioned though the extended y-axis range (to 130) due to Group - D's tail creates some wasted vertical space. + - Y-axis tick density is excessive (every 2 units from 0-106 = ~53 tick labels), + creating visual clutter on the left side + - Overall design polish is good but not publication-quality — needs more refined + y-axis tick interval and visual refinement + - Library mastery is adequate but could leverage more Highcharts-specific features + image_description: 'The plot displays four violin shapes representing test score + distributions across four study groups: Control (dark blue, #306998), Tutorial + (yellow/gold, #FFD43B), Self-Study (purple, #9467BD), and Intensive (cyan/teal, + #17BECF). Each violin shows a mirrored KDE density shape with a dark IQR box in + the center and a white horizontal median line. The Control group shows a symmetric + normal distribution centered around 50. The Tutorial group displays a wider, bimodal + distribution spanning roughly 10-85. Self-Study shows a tighter normal distribution + centered around 60. Intensive shows a right-skewed distribution centered lower + (~38) with a long upper tail reaching above 100. The title reads "violin-basic + · highcharts · pyplots.ai" at the top center. Y-axis labeled "Test Score (points)" + with ticks every 2 units from 0 to 106. X-axis labeled "Study Group". Legend in + top-right shows all four categories plus "Median" entry. Background is white with + subtle grid lines.' criteria_checklist: visual_quality: - score: 27 + score: 28 max: 30 items: - id: VQ-01 @@ -70,40 +68,40 @@ review: max: 8 passed: true comment: 'All font sizes explicitly set: title 72px, axis titles 52px, tick - labels 44px, legend 40px' + labels 44px, legend 40px. Perfectly readable.' - id: VQ-02 name: No Overlap score: 6 max: 6 passed: true - comment: No overlapping text elements; legend floats cleanly in top-right + comment: No overlapping text anywhere. Category labels well-spaced. - id: VQ-03 name: Element Visibility - score: 5 + score: 6 max: 6 passed: true - comment: Violin shapes well-formed; Group D thin tail spike barely visible - at top + comment: Violins clearly visible with fill opacity 0.55. IQR boxes and white + median lines are distinct. - id: VQ-04 name: Color Accessibility score: 3 max: 4 passed: true - comment: Blue/yellow/purple/cyan avoids red-green; yellow slightly low contrast - on white + comment: Blue, yellow, purple, cyan palette is mostly colorblind-safe. Yellow + has slightly reduced contrast against white background. - id: VQ-05 name: Layout & Canvas score: 3 max: 4 passed: true - comment: Good proportions but Group D tail forces y-axis to 130, wasting vertical - space + comment: Good margins and proportions. Y-axis has excessive tick density (every + 2 units from 0-106) creating visual clutter. - id: VQ-06 name: Axis Labels & Title score: 2 max: 2 passed: true - comment: Test Score (points) includes units; Study Group is descriptive + comment: Test Score (points) with units, Study Group descriptive. design_excellence: score: 12 max: 20 @@ -113,24 +111,24 @@ review: score: 5 max: 8 passed: true - comment: Custom palette, semi-transparent fills, dark IQR boxes with diamond - medians; above defaults but not publication-level + comment: Custom color palette, cohesive harmony, translucent fill effect. + Above defaults but not publication-quality. - id: DE-02 name: Visual Refinement - score: 4 + score: 3 max: 6 passed: true - comment: Subtle grid (0.08 opacity), light axis lines, removed ticks; good - refinement visible + comment: Subtle grid, clean background, but y-axis has too many tick marks + (every 2 units). - id: DE-03 name: Data Storytelling - score: 3 + score: 4 max: 6 passed: true - comment: Four distinct distribution shapes create comparison but no particular - emphasis or focal point + comment: Four distinct distributions create natural visual comparison. Bimodal + Tutorial and skewed Intensive draw attention. spec_compliance: - score: 14 + score: 15 max: 15 items: - id: SC-01 @@ -138,28 +136,28 @@ review: score: 5 max: 5 passed: true - comment: Correct violin plot with mirrored KDE density shapes + comment: Correct violin plot with mirrored KDE density shapes. - id: SC-02 name: Required Features - score: 3 + score: 4 max: 4 passed: true - comment: Mirrored density and IQR boxes present; median shown as diamond marker - instead of line + comment: 'All features present: quartile boxes, mirrored density, median lines.' - id: SC-03 name: Data Mapping score: 3 max: 3 passed: true - comment: Categories on x-axis, values on y-axis, all data correctly mapped + comment: Categories on X, values on Y. 4 categories with 200 points each. - id: SC-04 name: Title & Legend score: 3 max: 3 passed: true - comment: Title format correct; legend labels match data groups plus Median + comment: Title format correct. Legend labels match categories. Median entry + included. data_quality: - score: 12 + score: 15 max: 15 items: - id: DQ-01 @@ -167,23 +165,23 @@ review: score: 6 max: 6 passed: true - comment: Normal, bimodal, shifted-normal, and right-skewed distributions showcase - violin capabilities + comment: 'Shows all aspects: different centers, spreads, shapes, skewness, + multimodality.' - id: DQ-02 name: Realistic Context - score: 3 + score: 5 max: 5 passed: true - comment: Test scores plausible but group labels are generic (Group A-D) + comment: Test scores across study groups — realistic, neutral educational + scenario. - id: DQ-03 name: Appropriate Scale - score: 3 + score: 4 max: 4 passed: true - comment: Mostly realistic; Group D exponential tail reaching ~122 slightly - unrealistic for test scores + comment: Test scores in 0-100 range, realistic for educational context. code_quality: - score: 9 + score: 10 max: 10 items: - id: CQ-01 @@ -191,33 +189,35 @@ review: score: 3 max: 3 passed: true - comment: 'Flat structure: imports, data, KDE, chart config, series, export' + comment: 'Clean linear flow: imports, data, chart config, series, export. + No functions/classes.' - id: CQ-02 name: Reproducibility score: 2 max: 2 passed: true - comment: np.random.seed(42) set + comment: np.random.seed(42) set. - id: CQ-03 name: Clean Imports score: 2 max: 2 passed: true - comment: All imports used + comment: All imports used. - id: CQ-04 name: Code Elegance - score: 1 + score: 2 max: 2 passed: true - comment: Polygon construction appropriate but redundant plot.html generation + comment: Appropriate complexity. Manual KDE with PolygonSeries is the right + approach. - id: CQ-05 name: Output & API score: 1 max: 1 passed: true - comment: Saves plot.png via Selenium, uses current highcharts_core API + comment: Saves as plot.png via container screenshot. Also creates plot.html. library_mastery: - score: 5 + score: 6 max: 10 items: - id: LM-01 @@ -225,13 +225,13 @@ review: score: 3 max: 5 passed: true - comment: Correct use of HighchartsOptions, PolygonSeries, ScatterSeries; building - from raw polygons is necessary but basic + comment: Correct usage of Chart, HighchartsOptions, PolygonSeries. Manual + polygon construction is necessary but lower-level. - id: LM-02 name: Distinctive Features - score: 2 + score: 3 max: 5 - passed: false - comment: Uses enableMouseTracking and floating legend but doesn't leverage - tooltips, animation, or interactive strengths + passed: true + comment: HTML tooltips with detailed statistics, floating legend, animation + options. Meaningful Highcharts interactivity. verdict: REJECTED From 1baef7b7066fd31175d8481a87b5fe22865c02c4 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sat, 21 Feb 2026 22:52:21 +0000 Subject: [PATCH 5/8] fix(highcharts): address review feedback for violin-basic Attempt 2/3 - fixes based on AI review --- .../implementations/highcharts.py | 26 +++++++++++++++---- 1 file changed, 21 insertions(+), 5 deletions(-) diff --git a/plots/violin-basic/implementations/highcharts.py b/plots/violin-basic/implementations/highcharts.py index b35401ce02..b47727a63c 100644 --- a/plots/violin-basic/implementations/highcharts.py +++ b/plots/violin-basic/implementations/highcharts.py @@ -1,7 +1,7 @@ -""" pyplots.ai +"""pyplots.ai violin-basic: Basic Violin Plot Library: highcharts 1.10.3 | Python 3.14.3 -Quality: 86/100 | Updated: 2026-02-21 +Quality: repair-2 | Updated: 2026-02-21 """ import tempfile @@ -21,7 +21,7 @@ # Data - test scores across 4 study groups with distinct distributions np.random.seed(42) categories = ["Control", "Tutorial", "Self-Study", "Intensive"] -colors = ["#306998", "#FFD43B", "#9467BD", "#17BECF"] +colors = ["#306998", "#E5AB00", "#9467BD", "#17BECF"] raw_data = { "Control": np.random.normal(50, 12, 200), @@ -70,7 +70,7 @@ "marginBottom": 180, "marginLeft": 240, "marginRight": 80, - "marginTop": 160, + "marginTop": 200, "animation": {"duration": 1000}, } @@ -79,6 +79,11 @@ "style": {"fontSize": "72px", "fontWeight": "bold", "color": "#333333"}, } +chart.options.subtitle = { + "text": "Distribution of scores across 200 students per group", + "style": {"fontSize": "44px", "fontWeight": "normal", "color": "#777777"}, +} + chart.options.x_axis = { "title": {"text": "Study Group", "style": {"fontSize": "52px", "color": "#555555"}}, "labels": {"style": {"fontSize": "44px", "color": "#555555"}}, @@ -89,6 +94,7 @@ "lineWidth": 2, "lineColor": "#cccccc", "tickLength": 0, + "crosshair": {"width": 2, "color": "rgba(0, 0, 0, 0.15)", "dashStyle": "Dash"}, } chart.options.y_axis = { @@ -100,6 +106,8 @@ "lineColor": "#cccccc", "min": 0, "max": 105, + "tickInterval": 10, + "crosshair": {"width": 1, "color": "rgba(0, 0, 0, 0.12)", "dashStyle": "Dot"}, } chart.options.legend = { @@ -113,6 +121,8 @@ "floating": True, } +chart.options.credits = {"enabled": False} + chart.options.tooltip = { "enabled": True, "shared": False, @@ -126,7 +136,13 @@ } chart.options.plot_options = { - "polygon": {"lineWidth": 2, "fillOpacity": 0.55, "enableMouseTracking": True, "animation": True}, + "polygon": { + "lineWidth": 2, + "fillOpacity": 0.55, + "enableMouseTracking": True, + "animation": True, + "states": {"hover": {"lineWidth": 3, "brightness": 0.1}, "inactive": {"opacity": 0.4}}, + }, "scatter": {"marker": {"radius": 18, "symbol": "circle"}, "zIndex": 10, "enableMouseTracking": True}, "series": {"animation": {"duration": 1200, "easing": "easeOutBounce"}}, } From bb6ba1185cfda68de9f6882dd7bf16dc0b097cc0 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sat, 21 Feb 2026 22:59:06 +0000 Subject: [PATCH 6/8] chore(highcharts): update quality score 87 and review feedback for violin-basic --- .../implementations/highcharts.py | 4 +- plots/violin-basic/metadata/highcharts.yaml | 151 +++++++++--------- 2 files changed, 79 insertions(+), 76 deletions(-) diff --git a/plots/violin-basic/implementations/highcharts.py b/plots/violin-basic/implementations/highcharts.py index b47727a63c..caa3defb91 100644 --- a/plots/violin-basic/implementations/highcharts.py +++ b/plots/violin-basic/implementations/highcharts.py @@ -1,7 +1,7 @@ -"""pyplots.ai +""" pyplots.ai violin-basic: Basic Violin Plot Library: highcharts 1.10.3 | Python 3.14.3 -Quality: repair-2 | Updated: 2026-02-21 +Quality: 87/100 | Updated: 2026-02-21 """ import tempfile diff --git a/plots/violin-basic/metadata/highcharts.yaml b/plots/violin-basic/metadata/highcharts.yaml index 5f67ad6309..ff252fd10c 100644 --- a/plots/violin-basic/metadata/highcharts.yaml +++ b/plots/violin-basic/metadata/highcharts.yaml @@ -1,7 +1,7 @@ library: highcharts specification_id: violin-basic created: '2025-12-23T00:36:59Z' -updated: '2026-02-21T22:46:42Z' +updated: '2026-02-21T22:59:06Z' generated_by: claude-opus-4-6 workflow_run: 20447783582 issue: 0 @@ -10,7 +10,7 @@ library_version: 1.10.3 preview_url: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot.png preview_thumb: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot_thumb.png preview_html: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot.html -quality_score: 86 +quality_score: 87 impl_tags: dependencies: - scipy @@ -18,7 +18,6 @@ impl_tags: techniques: - hover-tooltips - html-export - - custom-legend patterns: - data-generation - iteration-over-groups @@ -29,37 +28,37 @@ impl_tags: - grid-styling review: strengths: - - Excellent data choices with four distinct distribution shapes (normal, bimodal, - shifted normal, right-skewed) that showcase the violin plot ability to reveal - distribution differences - - 'All spec features implemented correctly: mirrored KDE, IQR quartile boxes, median - lines' - - Interactive HTML tooltips showing full statistics (n, mean, median, Q1, Q3, std - dev) — meaningful use of Highcharts interactivity - - Clean code structure with appropriate complexity for manual violin construction - - Custom color palette with good contrast and cohesion + - Excellent data variety with 4 distinct distribution shapes showcasing violin plot + strengths + - Rich interactive tooltips showing complete statistical summary per group + - 'All spec features implemented cleanly: mirrored density, IQR boxes, median lines' + - Perfect text legibility with explicitly set font sizes throughout + - Colorblind-safe palette with good visual harmony weaknesses: - - Y-axis tick density is excessive (every 2 units from 0-106 = ~53 tick labels), - creating visual clutter on the left side - - Overall design polish is good but not publication-quality — needs more refined - y-axis tick interval and visual refinement - - Library mastery is adequate but could leverage more Highcharts-specific features - image_description: 'The plot displays four violin shapes representing test score - distributions across four study groups: Control (dark blue, #306998), Tutorial - (yellow/gold, #FFD43B), Self-Study (purple, #9467BD), and Intensive (cyan/teal, - #17BECF). Each violin shows a mirrored KDE density shape with a dark IQR box in - the center and a white horizontal median line. The Control group shows a symmetric - normal distribution centered around 50. The Tutorial group displays a wider, bimodal - distribution spanning roughly 10-85. Self-Study shows a tighter normal distribution - centered around 60. Intensive shows a right-skewed distribution centered lower - (~38) with a long upper tail reaching above 100. The title reads "violin-basic - · highcharts · pyplots.ai" at the top center. Y-axis labeled "Test Score (points)" - with ticks every 2 units from 0 to 106. X-axis labeled "Study Group". Legend in - top-right shows all four categories plus "Median" entry. Background is white with - subtle grid lines.' + - 'Design Excellence remains the main gap: good but not yet publication-quality + polish' + - IQR boxes are quite narrow (box_width=0.06), reducing their visual impact as quartile + markers + - No visual emphasis or focal point to guide the viewer toward a specific insight + - Manual polygon construction limits idiomatic Highcharts usage (inherent to the + approach) + image_description: 'The plot displays 4 violin shapes representing test score distributions + across study groups: Control (steel blue, #306998), Tutorial (gold, #E5AB00), + Self-Study (purple, #9467BD), and Intensive (cyan, #17BECF). Each violin has mirrored + KDE density contours with a semi-transparent fill (opacity ~0.55). Inside each + violin, a narrow dark rectangle shows the interquartile range (Q1-Q3) and a white + horizontal line marks the median. The Control violin is centered around 50 with + a roughly normal bell shape. The Tutorial violin is wider and shows a bimodal + bulge around 40 and 65. The Self-Study violin is centered higher around 60 with + a normal shape. The Intensive violin is right-skewed with a lower center (~38) + and a long thin tail extending up to ~103. The title reads "violin-basic · highcharts + · pyplots.ai" with a subtitle "Distribution of scores across 200 students per + group". Y-axis labeled "Test Score (points)" from 0-110, X-axis labeled "Study + Group". Legend in top-right shows all 4 groups plus "Median". Background is white + with subtle gray gridlines.' criteria_checklist: visual_quality: - score: 28 + score: 29 max: 30 items: - id: VQ-01 @@ -67,41 +66,43 @@ review: score: 8 max: 8 passed: true - comment: 'All font sizes explicitly set: title 72px, axis titles 52px, tick - labels 44px, legend 40px. Perfectly readable.' + comment: 'All font sizes explicitly set: title 72px, subtitle 44px, axis titles + 52px, axis labels 44px, legend 40px. All perfectly readable.' - id: VQ-02 name: No Overlap score: 6 max: 6 passed: true - comment: No overlapping text anywhere. Category labels well-spaced. + comment: No overlapping text or data elements. Legend floats in top-right + without overlapping violins. - id: VQ-03 name: Element Visibility - score: 6 + score: 5 max: 6 passed: true - comment: Violins clearly visible with fill opacity 0.55. IQR boxes and white - median lines are distinct. + comment: Violin shapes clearly visible with good opacity. IQR boxes (box_width=0.06) + are functional but quite narrow. - id: VQ-04 name: Color Accessibility - score: 3 + score: 4 max: 4 passed: true - comment: Blue, yellow, purple, cyan palette is mostly colorblind-safe. Yellow - has slightly reduced contrast against white background. + comment: Blue/gold/purple/cyan palette is colorblind-safe with no red-green + pairing. Good contrast. - id: VQ-05 name: Layout & Canvas - score: 3 + score: 4 max: 4 passed: true - comment: Good margins and proportions. Y-axis has excessive tick density (every - 2 units from 0-106) creating visual clutter. + comment: Well-proportioned layout with explicit margins. Violins well-distributed. + Canvas well-utilized. - id: VQ-06 name: Axis Labels & Title score: 2 max: 2 passed: true - comment: Test Score (points) with units, Study Group descriptive. + comment: Test Score (points) and Study Group are descriptive with units where + applicable. design_excellence: score: 12 max: 20 @@ -111,22 +112,22 @@ review: score: 5 max: 8 passed: true - comment: Custom color palette, cohesive harmony, translucent fill effect. - Above defaults but not publication-quality. + comment: Custom harmonious palette, clean design, good typography. Above defaults + but not publication-ready. - id: DE-02 name: Visual Refinement - score: 3 + score: 4 max: 6 passed: true - comment: Subtle grid, clean background, but y-axis has too many tick marks - (every 2 units). + comment: Subtle grid (opacity 0.08), clean axis lines, no tick marks, credits + disabled, generous margins. - id: DE-03 name: Data Storytelling - score: 4 + score: 3 max: 6 - passed: true - comment: Four distinct distributions create natural visual comparison. Bimodal - Tutorial and skewed Intensive draw attention. + passed: false + comment: Four distinct distribution shapes create visual interest but no clear + focal point or guided emphasis. spec_compliance: score: 15 max: 15 @@ -136,26 +137,26 @@ review: score: 5 max: 5 passed: true - comment: Correct violin plot with mirrored KDE density shapes. + comment: Correct violin plot with KDE density shapes. - id: SC-02 name: Required Features score: 4 max: 4 passed: true - comment: 'All features present: quartile boxes, mirrored density, median lines.' + comment: Mirrored density, quartile markers (IQR boxes), median lines all + present. - id: SC-03 name: Data Mapping score: 3 max: 3 passed: true - comment: Categories on X, values on Y. 4 categories with 200 points each. + comment: Categories on X-axis, numerical values on Y-axis, all data visible. - id: SC-04 name: Title & Legend score: 3 max: 3 passed: true - comment: Title format correct. Legend labels match categories. Median entry - included. + comment: Correct title format. Legend labels match group names. data_quality: score: 15 max: 15 @@ -165,21 +166,22 @@ review: score: 6 max: 6 passed: true - comment: 'Shows all aspects: different centers, spreads, shapes, skewness, - multimodality.' + comment: 'Excellent variety: normal, bimodal, shifted normal, right-skewed + distributions.' - id: DQ-02 name: Realistic Context score: 5 max: 5 passed: true - comment: Test scores across study groups — realistic, neutral educational - scenario. + comment: Educational study comparing test scores across study methods. Neutral, + real-world plausible. - id: DQ-03 name: Appropriate Scale score: 4 max: 4 passed: true - comment: Test scores in 0-100 range, realistic for educational context. + comment: Test scores 0-100, 200 students per group, sensible distribution + parameters. code_quality: score: 10 max: 10 @@ -189,33 +191,34 @@ review: score: 3 max: 3 passed: true - comment: 'Clean linear flow: imports, data, chart config, series, export. - No functions/classes.' + comment: 'Linear flow: imports, data generation, KDE calculation, chart config, + series creation, export.' - id: CQ-02 name: Reproducibility score: 2 max: 2 passed: true - comment: np.random.seed(42) set. + comment: np.random.seed(42) set at top. - id: CQ-03 name: Clean Imports score: 2 max: 2 passed: true - comment: All imports used. + comment: All imports are used. - id: CQ-04 name: Code Elegance score: 2 max: 2 passed: true - comment: Appropriate complexity. Manual KDE with PolygonSeries is the right - approach. + comment: Clean loop-based construction. Appropriate complexity for manual + polygon violin construction. - id: CQ-05 name: Output & API score: 1 max: 1 passed: true - comment: Saves as plot.png via container screenshot. Also creates plot.html. + comment: Saves as plot.png via selenium screenshot. Also generates plot.html. + Current API. library_mastery: score: 6 max: 10 @@ -225,13 +228,13 @@ review: score: 3 max: 5 passed: true - comment: Correct usage of Chart, HighchartsOptions, PolygonSeries. Manual - polygon construction is necessary but lower-level. + comment: Uses Chart, HighchartsOptions, PolygonSeries correctly. Manual polygon + construction necessary since Highcharts lacks native violin series. - id: LM-02 name: Distinctive Features score: 3 max: 5 passed: true - comment: HTML tooltips with detailed statistics, floating legend, animation - options. Meaningful Highcharts interactivity. + comment: Interactive tooltips with rich HTML, hover states, inactive states, + crosshair, animation with custom easing. verdict: REJECTED From 35fd3a38efe2182f4758d33bb4fe801e78b77cd6 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sat, 21 Feb 2026 23:07:37 +0000 Subject: [PATCH 7/8] fix(highcharts): address review feedback for violin-basic Attempt 3/3 - fixes based on AI review --- .../implementations/highcharts.py | 53 +++++++++++++++---- 1 file changed, 44 insertions(+), 9 deletions(-) diff --git a/plots/violin-basic/implementations/highcharts.py b/plots/violin-basic/implementations/highcharts.py index caa3defb91..9f62c42f2b 100644 --- a/plots/violin-basic/implementations/highcharts.py +++ b/plots/violin-basic/implementations/highcharts.py @@ -1,4 +1,4 @@ -""" pyplots.ai +"""pyplots.ai violin-basic: Basic Violin Plot Library: highcharts 1.10.3 | Python 3.14.3 Quality: 87/100 | Updated: 2026-02-21 @@ -30,6 +30,13 @@ "Intensive": np.clip(np.random.exponential(15, 200) + 30, 0, 100), } +# RGB values for gradient fills +colors_rgb = ["48,105,152", "229,171,0", "148,103,189", "23,190,207"] + +# Overall mean for reference line +all_scores = np.concatenate(list(raw_data.values())) +overall_mean = float(np.mean(all_scores)) + # Calculate KDE and statistics for each category violin_width = 0.35 violin_data = [] @@ -55,6 +62,7 @@ "std": float(np.std(data)), "n": len(data), "color": colors[i], + "rgb": colors_rgb[i], } ) @@ -67,6 +75,7 @@ "width": 4800, "height": 2700, "backgroundColor": "#ffffff", + "plotBorderWidth": 0, "marginBottom": 180, "marginLeft": 240, "marginRight": 80, @@ -91,8 +100,7 @@ "max": 3.5, "tickPositions": [0, 1, 2, 3], "categories": categories, - "lineWidth": 2, - "lineColor": "#cccccc", + "lineWidth": 0, "tickLength": 0, "crosshair": {"width": 2, "color": "rgba(0, 0, 0, 0.15)", "dashStyle": "Dash"}, } @@ -102,12 +110,27 @@ "labels": {"style": {"fontSize": "44px", "color": "#555555"}}, "gridLineWidth": 1, "gridLineColor": "rgba(0, 0, 0, 0.08)", - "lineWidth": 2, - "lineColor": "#cccccc", + "lineWidth": 0, "min": 0, "max": 105, "tickInterval": 10, "crosshair": {"width": 1, "color": "rgba(0, 0, 0, 0.12)", "dashStyle": "Dot"}, + "plotLines": [ + { + "value": overall_mean, + "color": "rgba(0, 0, 0, 0.22)", + "dashStyle": "LongDash", + "width": 3, + "zIndex": 3, + "label": { + "text": f"Overall Mean ({overall_mean:.0f})", + "style": {"fontSize": "32px", "color": "rgba(0, 0, 0, 0.40)", "fontStyle": "italic"}, + "align": "right", + "x": -15, + "y": -10, + }, + } + ], } chart.options.legend = { @@ -138,7 +161,7 @@ chart.options.plot_options = { "polygon": { "lineWidth": 2, - "fillOpacity": 0.55, + "fillOpacity": 1.0, "enableMouseTracking": True, "animation": True, "states": {"hover": {"lineWidth": 3, "brightness": 0.1}, "inactive": {"opacity": 0.4}}, @@ -155,12 +178,24 @@ for j in range(len(v["y_grid"]) - 1, -1, -1): polygon_points.append([float(v["index"] - v["density"][j]), float(v["y_grid"][j])]) + is_featured = v["category"] == "Tutorial" + center_alpha = "0.70" if is_featured else "0.55" + edge_alpha = "0.20" if is_featured else "0.12" + series = PolygonSeries() series.data = polygon_points series.name = v["category"] series.color = v["color"] - series.fill_color = v["color"] - series.fill_opacity = 0.55 + series.fill_color = { + "linearGradient": {"x1": 0, "y1": 0, "x2": 1, "y2": 0}, + "stops": [ + [0, f"rgba({v['rgb']},{edge_alpha})"], + [0.5, f"rgba({v['rgb']},{center_alpha})"], + [1, f"rgba({v['rgb']},{edge_alpha})"], + ], + } + series.fill_opacity = 1.0 + series.line_width = 3 if is_featured else 2 series.tooltip = { "pointFormat": ( f'' @@ -199,7 +234,7 @@ # IQR boxes (thin rectangles for interquartile range) for v in violin_data: - box_width = 0.06 + box_width = 0.10 box_points = [ [float(v["index"] - box_width), float(v["q1"])], [float(v["index"] + box_width), float(v["q1"])], From f5049103604220fe4fbb0fc4f84efd396a678383 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sat, 21 Feb 2026 23:13:37 +0000 Subject: [PATCH 8/8] chore(highcharts): update quality score 92 and review feedback for violin-basic --- .../implementations/highcharts.py | 4 +- plots/violin-basic/metadata/highcharts.yaml | 164 +++++++++--------- 2 files changed, 85 insertions(+), 83 deletions(-) diff --git a/plots/violin-basic/implementations/highcharts.py b/plots/violin-basic/implementations/highcharts.py index 9f62c42f2b..9a2a99f63b 100644 --- a/plots/violin-basic/implementations/highcharts.py +++ b/plots/violin-basic/implementations/highcharts.py @@ -1,7 +1,7 @@ -"""pyplots.ai +""" pyplots.ai violin-basic: Basic Violin Plot Library: highcharts 1.10.3 | Python 3.14.3 -Quality: 87/100 | Updated: 2026-02-21 +Quality: 92/100 | Updated: 2026-02-21 """ import tempfile diff --git a/plots/violin-basic/metadata/highcharts.yaml b/plots/violin-basic/metadata/highcharts.yaml index ff252fd10c..2ec103063d 100644 --- a/plots/violin-basic/metadata/highcharts.yaml +++ b/plots/violin-basic/metadata/highcharts.yaml @@ -1,7 +1,7 @@ library: highcharts specification_id: violin-basic created: '2025-12-23T00:36:59Z' -updated: '2026-02-21T22:59:06Z' +updated: '2026-02-21T23:13:37Z' generated_by: claude-opus-4-6 workflow_run: 20447783582 issue: 0 @@ -10,7 +10,7 @@ library_version: 1.10.3 preview_url: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot.png preview_thumb: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot_thumb.png preview_html: https://storage.googleapis.com/pyplots-images/plots/violin-basic/highcharts/plot.html -quality_score: 87 +quality_score: 92 impl_tags: dependencies: - scipy @@ -18,44 +18,46 @@ impl_tags: techniques: - hover-tooltips - html-export + - custom-legend patterns: - data-generation - iteration-over-groups dataprep: - kde styling: + - gradient-fill - alpha-blending - grid-styling review: strengths: - - Excellent data variety with 4 distinct distribution shapes showcasing violin plot - strengths - - Rich interactive tooltips showing complete statistical summary per group - - 'All spec features implemented cleanly: mirrored density, IQR boxes, median lines' - - Perfect text legibility with explicitly set font sizes throughout - - Colorblind-safe palette with good visual harmony + - Excellent data choices with four distinct distribution shapes (normal, bimodal, + shifted normal, skewed) showcasing violin plot capabilities + - Gradient fills with center-to-edge transparency create a polished professional + look + - All font sizes explicitly set and perfectly readable at 4800x2700 + - 'Clean visual refinement: removed axis lines, removed ticks, subtle grid, generous + margins' + - Rich HTML tooltips with formatted statistics (n, mean, median, Q1/Q3, std dev) + - Overall mean reference line provides useful context for cross-group comparison weaknesses: - - 'Design Excellence remains the main gap: good but not yet publication-quality - polish' - - IQR boxes are quite narrow (box_width=0.06), reducing their visual impact as quartile - markers - - No visual emphasis or focal point to guide the viewer toward a specific insight - - Manual polygon construction limits idiomatic Highcharts usage (inherent to the - approach) - image_description: 'The plot displays 4 violin shapes representing test score distributions - across study groups: Control (steel blue, #306998), Tutorial (gold, #E5AB00), - Self-Study (purple, #9467BD), and Intensive (cyan, #17BECF). Each violin has mirrored - KDE density contours with a semi-transparent fill (opacity ~0.55). Inside each - violin, a narrow dark rectangle shows the interquartile range (Q1-Q3) and a white - horizontal line marks the median. The Control violin is centered around 50 with - a roughly normal bell shape. The Tutorial violin is wider and shows a bimodal - bulge around 40 and 65. The Self-Study violin is centered higher around 60 with - a normal shape. The Intensive violin is right-skewed with a lower center (~38) - and a long thin tail extending up to ~103. The title reads "violin-basic · highcharts - · pyplots.ai" with a subtitle "Distribution of scores across 200 students per - group". Y-axis labeled "Test Score (points)" from 0-110, X-axis labeled "Study - Group". Legend in top-right shows all 4 groups plus "Median". Background is white - with subtle gray gridlines.' + - Blue and cyan colors could be slightly similar for some forms of color vision + deficiency + - IQR boxes are plain dark rectangles — more refined styling could improve polish + image_description: The plot displays four violin shapes representing test score + distributions across study groups (Control, Tutorial, Self-Study, Intensive). + Each violin is rendered as a PolygonSeries with horizontal gradient fills — center + opaque fading to transparent edges. Colors are steel blue (#306998), golden yellow + (#E5AB00), medium purple (#9467BD), and cyan (#17BECF). Dark IQR boxes sit inside + each violin spanning Q1–Q3, with white horizontal median lines crossing each at + the median position. A dashed "Overall Mean (51)" reference line spans the full + width. The y-axis reads "Test Score (points)" from 0–110 with subtle gridlines + every 10 points. The x-axis reads "Study Group" with category labels. A floating + legend in the upper right shows all four categories plus "Median". The title "violin-basic + · highcharts · pyplots.ai" appears at the top with subtitle "Distribution of scores + across 200 students per group." The Control violin is bell-shaped centered ~50, + Tutorial is distinctly bimodal (wide body spanning ~25–85), Self-Study is a tighter + bell centered ~60, and Intensive is right-skewed with a long thin tail reaching + ~103. The layout is clean with no axis lines, no tick marks, and generous margins. criteria_checklist: visual_quality: score: 29 @@ -66,68 +68,68 @@ review: score: 8 max: 8 passed: true - comment: 'All font sizes explicitly set: title 72px, subtitle 44px, axis titles - 52px, axis labels 44px, legend 40px. All perfectly readable.' + comment: All font sizes explicitly set (title 72px, subtitle 44px, axis titles + 52px, axis labels 44px, legend 40px). All text perfectly readable. - id: VQ-02 name: No Overlap score: 6 max: 6 passed: true - comment: No overlapping text or data elements. Legend floats in top-right - without overlapping violins. + comment: No overlapping text elements. Category labels well-spaced, legend + floats cleanly. - id: VQ-03 name: Element Visibility - score: 5 + score: 6 max: 6 passed: true - comment: Violin shapes clearly visible with good opacity. IQR boxes (box_width=0.06) - are functional but quite narrow. + comment: Violin shapes clearly visible with appropriate sizing. IQR boxes + and median lines have strong contrast. - id: VQ-04 name: Color Accessibility - score: 4 + score: 3 max: 4 passed: true - comment: Blue/gold/purple/cyan palette is colorblind-safe with no red-green - pairing. Good contrast. + comment: Four distinct hue families work for most CVD types. Blue and cyan + could be slightly similar for tritanopia. - id: VQ-05 name: Layout & Canvas score: 4 max: 4 passed: true - comment: Well-proportioned layout with explicit margins. Violins well-distributed. - Canvas well-utilized. + comment: Plot fills ~60% of canvas. Explicit margins create balanced layout. + Nothing cut off. - id: VQ-06 name: Axis Labels & Title score: 2 max: 2 passed: true - comment: Test Score (points) and Study Group are descriptive with units where - applicable. + comment: Y-axis 'Test Score (points)' with units. X-axis 'Study Group' descriptive + for categorical data. design_excellence: - score: 12 + score: 15 max: 20 items: - id: DE-01 name: Aesthetic Sophistication - score: 5 + score: 6 max: 8 passed: true - comment: Custom harmonious palette, clean design, good typography. Above defaults - but not publication-ready. + comment: Custom palette, gradient fills, featured violin, overall mean reference + line. Professional and polished, clearly above defaults. - id: DE-02 name: Visual Refinement - score: 4 + score: 5 max: 6 passed: true - comment: Subtle grid (opacity 0.08), clean axis lines, no tick marks, credits - disabled, generous margins. + comment: Axis lines removed, tick marks removed, subtle grid (alpha 0.08), + styled crosshairs, generous whitespace. - id: DE-03 name: Data Storytelling - score: 3 + score: 4 max: 6 - passed: false - comment: Four distinct distribution shapes create visual interest but no clear - focal point or guided emphasis. + passed: true + comment: Featured Tutorial violin with higher opacity, overall mean reference + line, distinct distribution shapes create natural comparison. spec_compliance: score: 15 max: 15 @@ -137,26 +139,27 @@ review: score: 5 max: 5 passed: true - comment: Correct violin plot with KDE density shapes. + comment: Correct violin plot combining KDE density shapes with box-plot-style + statistics. - id: SC-02 name: Required Features score: 4 max: 4 passed: true - comment: Mirrored density, quartile markers (IQR boxes), median lines all - present. + comment: Quartile markers (IQR boxes), mirrored density, median line all present. - id: SC-03 name: Data Mapping score: 3 max: 3 passed: true - comment: Categories on X-axis, numerical values on Y-axis, all data visible. + comment: Categories on X-axis, numerical values on Y-axis. 4 categories with + 200 points each. - id: SC-04 name: Title & Legend score: 3 max: 3 passed: true - comment: Correct title format. Legend labels match group names. + comment: Title follows exact format. Legend labels match category names. data_quality: score: 15 max: 15 @@ -166,22 +169,22 @@ review: score: 6 max: 6 passed: true - comment: 'Excellent variety: normal, bimodal, shifted normal, right-skewed - distributions.' + comment: 'Four distinct distributions: normal, bimodal, shifted normal, right-skewed + exponential.' - id: DQ-02 name: Realistic Context score: 5 max: 5 passed: true - comment: Educational study comparing test scores across study methods. Neutral, - real-world plausible. + comment: Test scores across study groups — plausible educational research + scenario, neutral topic. - id: DQ-03 name: Appropriate Scale score: 4 max: 4 passed: true - comment: Test scores 0-100, 200 students per group, sensible distribution - parameters. + comment: Scores 0-100, 200 students per group — realistic for educational + assessment. code_quality: score: 10 max: 10 @@ -191,50 +194,49 @@ review: score: 3 max: 3 passed: true - comment: 'Linear flow: imports, data generation, KDE calculation, chart config, - series creation, export.' + comment: 'Linear script: imports, data, chart setup, series, export. No functions + or classes.' - id: CQ-02 name: Reproducibility score: 2 max: 2 passed: true - comment: np.random.seed(42) set at top. + comment: np.random.seed(42) set at start. - id: CQ-03 name: Clean Imports score: 2 max: 2 passed: true - comment: All imports are used. + comment: All imports used. - id: CQ-04 name: Code Elegance score: 2 max: 2 passed: true - comment: Clean loop-based construction. Appropriate complexity for manual - polygon violin construction. + comment: Clean dictionary-based data structure. Loop-based series construction + is appropriate. - id: CQ-05 name: Output & API score: 1 max: 1 passed: true - comment: Saves as plot.png via selenium screenshot. Also generates plot.html. - Current API. + comment: Saves as plot.png via Selenium. Uses current highcharts_core API. library_mastery: - score: 6 + score: 8 max: 10 items: - id: LM-01 name: Idiomatic Usage - score: 3 + score: 4 max: 5 passed: true - comment: Uses Chart, HighchartsOptions, PolygonSeries correctly. Manual polygon - construction necessary since Highcharts lacks native violin series. + comment: Correct use of PolygonSeries for custom shapes. Chart options, tooltip, + crosshair, and series config follow highcharts_core patterns. - id: LM-02 name: Distinctive Features - score: 3 + score: 4 max: 5 passed: true - comment: Interactive tooltips with rich HTML, hover states, inactive states, - crosshair, animation with custom easing. - verdict: REJECTED + comment: Linear gradient fills, HTML tooltips, hover states, crosshairs, animation + easing — distinctive Highcharts features. + verdict: APPROVED