update(area-basic): matplotlib — comprehensive quality review

plots/area-basic/implementations/matplotlib.py

@@ -1,7 +1,7 @@
 """ pyplots.ai
 area-basic: Basic Area Chart
 Library: matplotlib 3.10.8 | Python 3.14.2
-Quality: 95/100 | Created: 2025-12-23
+Quality: 100/100 | Created: 2025-12-23
 """
 
 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="--")
 

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: '2026-02-11T22:26:09Z'
 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: 95
+quality_score: 100
 impl_tags:
   dependencies: []
   techniques:
-  - patches
+  - annotations
   patterns:
   - data-generation
   - explicit-figure
@@ -26,81 +26,77 @@ 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
         name: Text Legibility
         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