From e1f46c2c80d51708e2fe0a0f26bcfd35b90ecfb1 Mon Sep 17 00:00:00 2001 From: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com> Date: Wed, 11 Feb 2026 23:23:10 +0100 Subject: [PATCH 1/2] =?UTF-8?q?update(area-basic):=20matplotlib=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 Added viral blog post spike with annotation, improved data range, enhanced title --- .../area-basic/implementations/matplotlib.py | 33 ++++++++++++++----- plots/area-basic/metadata/matplotlib.yaml | 4 +-- 2 files changed, 26 insertions(+), 11 deletions(-) diff --git a/plots/area-basic/implementations/matplotlib.py b/plots/area-basic/implementations/matplotlib.py index 7b6f305b0d..19c58c3aab 100644 --- a/plots/area-basic/implementations/matplotlib.py +++ b/plots/area-basic/implementations/matplotlib.py @@ -1,7 +1,7 @@ -""" pyplots.ai +"""pyplots.ai area-basic: Basic Area Chart Library: matplotlib 3.10.8 | Python 3.14.2 -Quality: 95/100 | Created: 2025-12-23 +Quality: /100 | Updated: 2026-02-11 """ import matplotlib.colors as mcolors @@ -11,26 +11,29 @@ from matplotlib.path import Path -# Data - daily website visitors over a month with weekend dips +# Data - daily website visitors over a month with weekend dips and a viral spike np.random.seed(42) days = np.arange(1, 31) -base_visitors = 5000 + np.linspace(0, 2500, 30) # Upward trend +base_visitors = 3000 + np.linspace(0, 2000, 30) # Upward trend from 3k to 5k weekend_effect = np.array([-1200 if d % 7 in (0, 6) else 0 for d in days]) # Weekend dips -noise = np.random.randn(30) * 400 +noise = np.random.randn(30) * 300 visitors = base_visitors + weekend_effect + noise -visitors = np.clip(visitors, 2000, 10000) +# Viral blog post spike on day 18 +visitors[17] = 8200 +visitors[18] = 6800 +visitors = np.clip(visitors, 1000, 10000) # Create plot (4800x2700 px) fig, ax = plt.subplots(figsize=(16, 9)) -y_max = visitors.max() * 1.15 +y_max = visitors.max() * 1.12 # Gradient fill using imshow clipped to the area shape cmap = mcolors.LinearSegmentedColormap.from_list("area_grad", ["#d6e6f5", "#306998"]) gradient = np.linspace(0, 1, 256).reshape(-1, 1) gradient = np.hstack([gradient, gradient]) -# Build clip path manually from fill_between polygon +# Build clip path from area polygon verts = [(days[0], 0)] for d, v in zip(days, visitors, strict=True): verts.append((d, v)) @@ -49,10 +52,22 @@ # Solid line on top ax.plot(days, visitors, color="#306998", linewidth=3, zorder=3) +# Annotate the viral spike +ax.annotate( + "Viral post", + xy=(18, visitors[17]), + xytext=(22, visitors[17] + 400), + fontsize=16, + color="#306998", + fontweight="bold", + arrowprops={"arrowstyle": "->", "color": "#306998", "lw": 2}, + zorder=4, +) + # Labels and styling ax.set_xlabel("Day of Month", fontsize=20) ax.set_ylabel("Daily Visitors (count)", fontsize=20) -ax.set_title("area-basic · matplotlib · pyplots.ai", fontsize=24) +ax.set_title("Website Traffic · area-basic · matplotlib · pyplots.ai", fontsize=24) ax.tick_params(axis="both", labelsize=16) ax.grid(True, alpha=0.3, linestyle="--") diff --git a/plots/area-basic/metadata/matplotlib.yaml b/plots/area-basic/metadata/matplotlib.yaml index 1a2f233e0a..b916eae708 100644 --- a/plots/area-basic/metadata/matplotlib.yaml +++ b/plots/area-basic/metadata/matplotlib.yaml @@ -1,7 +1,7 @@ library: matplotlib specification_id: area-basic created: '2025-12-23T00:46:12Z' -updated: '2026-02-11T20:57:35Z' +updated: '2026-02-11T22:20:05+00:00' generated_by: claude-opus-4-6 workflow_run: 20447957143 issue: 0 @@ -10,7 +10,7 @@ library_version: 3.10.8 preview_url: https://storage.googleapis.com/pyplots-images/plots/area-basic/matplotlib/plot.png preview_thumb: https://storage.googleapis.com/pyplots-images/plots/area-basic/matplotlib/plot_thumb.png preview_html: null -quality_score: 95 +quality_score: null impl_tags: dependencies: [] techniques: From 3a24e249ad9356929b83207ec120077668a946f5 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Wed, 11 Feb 2026 22:26:10 +0000 Subject: [PATCH 2/2] chore(matplotlib): update quality score 100 and review feedback for area-basic --- .../area-basic/implementations/matplotlib.py | 4 +- plots/area-basic/metadata/matplotlib.yaml | 119 +++++++++--------- 2 files changed, 60 insertions(+), 63 deletions(-) diff --git a/plots/area-basic/implementations/matplotlib.py b/plots/area-basic/implementations/matplotlib.py index 19c58c3aab..f5ab57e7ae 100644 --- a/plots/area-basic/implementations/matplotlib.py +++ b/plots/area-basic/implementations/matplotlib.py @@ -1,7 +1,7 @@ -"""pyplots.ai +""" pyplots.ai area-basic: Basic Area Chart Library: matplotlib 3.10.8 | Python 3.14.2 -Quality: /100 | Updated: 2026-02-11 +Quality: 100/100 | Created: 2025-12-23 """ import matplotlib.colors as mcolors diff --git a/plots/area-basic/metadata/matplotlib.yaml b/plots/area-basic/metadata/matplotlib.yaml index b916eae708..f754145d15 100644 --- a/plots/area-basic/metadata/matplotlib.yaml +++ b/plots/area-basic/metadata/matplotlib.yaml @@ -1,7 +1,7 @@ library: matplotlib specification_id: area-basic created: '2025-12-23T00:46:12Z' -updated: '2026-02-11T22:20:05+00:00' +updated: '2026-02-11T22:26:09Z' generated_by: claude-opus-4-6 workflow_run: 20447957143 issue: 0 @@ -10,11 +10,11 @@ library_version: 3.10.8 preview_url: https://storage.googleapis.com/pyplots-images/plots/area-basic/matplotlib/plot.png preview_thumb: https://storage.googleapis.com/pyplots-images/plots/area-basic/matplotlib/plot_thumb.png preview_html: null -quality_score: null +quality_score: 100 impl_tags: dependencies: [] techniques: - - patches + - annotations patterns: - data-generation - explicit-figure @@ -26,32 +26,31 @@ impl_tags: - grid-styling review: strengths: - - Excellent gradient fill implementation using imshow clipped to the area polygon - — visually appealing and demonstrates advanced matplotlib techniques - - Data is well-crafted with realistic upward trend and periodic weekend dips that - showcase the area chart purpose - - Perfect text sizing following library guidelines (24pt title, 20pt labels, 16pt - ticks) - - Colorblind-safe blue palette (#306998) consistent with pyplots recommended colors - - Clean readable code with proper seed for reproducibility - weaknesses: - - Y-axis starting at 0 with data in 4000-7500 range leaves significant empty space - at bottom, slightly reducing visual impact - - Data could include one more interesting feature such as a notable spike or event - for maximum feature coverage - image_description: The plot displays a basic area chart showing daily website visitors - over a 30-day month. The x-axis shows "Day of Month" (1–30), and the y-axis shows - "Daily Visitors (count)" (0–~8500). The area beneath the line is filled with a - vertical gradient transitioning from light blue (#d6e6f5) at the bottom to a deeper - blue (#306998) at the top, with alpha transparency of 0.6. The line itself is - a solid dark blue (#306998) at linewidth 3. The data shows a clear upward trend - from ~5000 visitors to ~7500 visitors, with periodic dips approximately every - 7 days corresponding to weekends. Gridlines are subtle dashed lines at alpha 0.3. - The title reads "area-basic · matplotlib · pyplots.ai" in the correct format. - Layout is clean with balanced margins and good canvas utilization via tight_layout. + - Gradient fill via imshow + PathPatch clipping is a sophisticated, visually striking + technique that goes well beyond basic fill_between + - Data generation is rich and realistic with upward trend, weekend dips, noise, + and a viral spike — all telling a coherent story + - The Viral post annotation with arrow adds narrative value and demonstrates matplotlib + annotation capabilities + - All text sizes follow the library guidelines exactly (24/20/16pt) ensuring perfect + legibility at full resolution + - Code is clean and well-structured with clear comments explaining each section + weaknesses: [] + image_description: The plot displays a basic area chart titled "Website Traffic + · area-basic · matplotlib · pyplots.ai". The X-axis is labeled "Day of Month" + (1–30) and the Y-axis is labeled "Daily Visitors (count)" (0–~9000). The area + beneath the line is filled with a vertical gradient transitioning from a light + sky blue (#d6e6f5) at the bottom to a deep Python blue (#306998) at the top, achieved + via an imshow layer clipped to the area polygon. A solid blue line (linewidth + 3) traces the upper boundary. The data shows an overall upward trend from ~3000 + to ~5000 visitors with periodic weekend dips and random noise. A dramatic spike + on day 18 reaches ~8200 visitors, annotated with a bold "Viral post" label and + an arrow pointing to the peak. The grid uses subtle dashed lines at alpha 0.3. + The layout is well-balanced with tight_layout applied, and the plot fills the + canvas effectively. criteria_checklist: visual_quality: - score: 37 + score: 40 max: 40 items: - id: VQ-01 @@ -59,48 +58,45 @@ review: score: 10 max: 10 passed: true - comment: Title at 24pt, axis labels at 20pt, ticks at 16pt — all perfectly - readable at full size + comment: Title 24pt, labels 20pt, ticks 16pt — all perfectly readable at 4800x2700 - id: VQ-02 name: No Overlap score: 8 max: 8 passed: true - comment: No overlapping text elements anywhere + comment: No overlapping text; annotation well-positioned away from other elements - id: VQ-03 name: Element Visibility score: 8 max: 8 passed: true - comment: Line at linewidth=3 is clearly visible, gradient fill with alpha=0.6 - provides good visual weight + comment: Linewidth 3 is optimal for 30 data points; gradient fill is clearly + visible - id: VQ-04 name: Color Accessibility score: 5 max: 5 passed: true - comment: Uses colorblind-safe blue palette (#306998), no problematic color - combinations + comment: Single-series using pyplots blue (#306998); no colorblind concerns - id: VQ-05 name: Layout Balance - score: 4 + score: 5 max: 5 passed: true - comment: Good canvas utilization with tight_layout; y-axis starting at 0 leaves - empty space below data range but appropriate for area charts + comment: Plot fills canvas well with tight_layout; balanced margins - id: VQ-06 name: Axis Labels score: 2 max: 2 passed: true - comment: 'Both axes have descriptive labels with units: Day of Month, Daily - Visitors (count)' + comment: Day of Month and Daily Visitors (count) — descriptive with units - id: VQ-07 name: Grid & Legend score: 2 max: 2 passed: true - comment: Grid is subtle (alpha=0.3, dashed), no legend needed for single series + comment: Grid at alpha 0.3 dashed — subtle and helpful; no legend needed for + single series spec_compliance: score: 25 max: 25 @@ -116,56 +112,57 @@ review: score: 5 max: 5 passed: true - comment: X is continuous (days), Y is numeric (visitors) + comment: X = continuous days, Y = numeric visitor magnitude - id: SC-03 name: Required Features score: 5 max: 5 passed: true comment: Semi-transparent fill, gridlines, clear axis labels with units, gradient - fill — all spec features present + fill from bottom to line - id: SC-04 name: Data Range score: 3 max: 3 passed: true - comment: All data visible within axis limits + comment: Y-axis starts at 0, x-axis spans full 1-30 range - id: SC-05 name: Legend Accuracy score: 2 max: 2 passed: true - comment: Single series, no legend needed — appropriate + comment: No legend needed for single-series area chart - id: SC-06 name: Title Format score: 2 max: 2 passed: true - comment: Exactly matches area-basic · matplotlib · pyplots.ai + comment: Website Traffic · area-basic · matplotlib · pyplots.ai matches required + format data_quality: - score: 19 + score: 20 max: 20 items: - id: DQ-01 name: Feature Coverage - score: 7 + score: 8 max: 8 passed: true - comment: Shows upward trend and periodic weekend dips; could benefit from - one more feature like a sudden spike + comment: Shows upward trend, weekend dips, noise, and viral spike — demonstrates + area chart strengths - id: DQ-02 name: Realistic Context score: 7 max: 7 passed: true - comment: Website daily visitors — realistic neutral scenario matching spec - example + comment: Website traffic is a perfect neutral real-world scenario matching + the spec example - id: DQ-03 name: Appropriate Scale score: 5 max: 5 passed: true - comment: Values of 4000-7500 daily visitors are entirely realistic for a website + comment: 2000-8200 daily visitors with weekend dips is highly realistic code_quality: score: 10 max: 10 @@ -175,40 +172,40 @@ review: score: 3 max: 3 passed: true - comment: 'Clean linear flow: imports → data → plot → save' + comment: Clean imports, data, plot, save flow with no functions/classes - id: CQ-02 name: Reproducibility score: 3 max: 3 passed: true - comment: Uses np.random.seed(42) + comment: np.random.seed(42) set at the start - id: CQ-03 name: Clean Imports score: 2 max: 2 passed: true - comment: All imports are used (mcolors, PathPatch, Path) + comment: All imports used (mcolors, plt, np, PathPatch, Path) - id: CQ-04 name: No Deprecated API score: 1 max: 1 passed: true - comment: No deprecated functions used + comment: No deprecated functions - id: CQ-05 name: Output Correct score: 1 max: 1 passed: true - comment: Saves as plot.png + comment: Saves as plot.png with dpi=300 library_features: - score: 4 + score: 5 max: 5 items: - id: LF-01 name: Distinctive Features - score: 4 + score: 5 max: 5 passed: true - comment: Uses imshow with custom clipping path for gradient fill, LinearSegmentedColormap, - and PathPatch — advanced matplotlib capabilities + comment: Excellent use of imshow with PathPatch clipping for gradient fill, + LinearSegmentedColormap, and Path construction verdict: APPROVED