feat(plotnine): implement streamgraph-basic

plots/streamgraph-basic/implementations/python/plotnine.py

@@ -1,7 +1,7 @@
-""" pyplots.ai
+""" anyplot.ai
 streamgraph-basic: Basic Stream Graph
-Library: plotnine 0.15.1 | Python 3.13.11
-Quality: 98/100 | Created: 2025-12-14
+Library: plotnine 0.15.3 | Python 3.13.13
+Quality: 79/100 | Created: 2026-05-05
 """
 
 import numpy as np

plots/streamgraph-basic/metadata/python/plotnine.yaml

@@ -1,26 +1,276 @@
 library: plotnine
+language: python
 specification_id: streamgraph-basic
 created: 2025-12-14 19:44:18+00:00
-updated: 2025-12-14 19:44:18+00:00
-generated_by: claude-opus-4-5-20251101
-workflow_run: 20213171391
+updated: '2026-05-05T03:37:22Z'
+generated_by: claude-sonnet
+workflow_run: 25356129081
 issue: 856
-python_version: 3.13.11
-library_version: 0.15.1
-preview_url: https://storage.googleapis.com/anyplot-images/plots/streamgraph-basic/plotnine/plot.png
-preview_html: null
-quality_score: 98
+python_version: 3.13.13
+library_version: 0.15.3
+preview_url_light: https://storage.googleapis.com/anyplot-images/plots/streamgraph-basic/python/plotnine/plot-light.png
+preview_url_dark: https://storage.googleapis.com/anyplot-images/plots/streamgraph-basic/python/plotnine/plot-dark.png
+preview_html_light: null
+preview_html_dark: null
+quality_score: 79
+review:
+  strengths:
+  - Correct streamgraph implementation using geom_ribbon with properly centered symmetric
+    baseline (-totals/2)
+  - Realistic music streaming data with 5 genres over 24 months using sinusoidal trends
+  - All font sizes explicitly set (title 24pt, axis labels 20pt, tick labels 16pt,
+    legend 16pt) and readable in both renders
+  - KISS code structure with clear Imports → Data → Plot → Save flow
+  - Reproducible with np.random.seed(42)
+  - Clean imports — all symbols used
+  - Good canvas utilization with legend correctly positioned to the right
+  weaknesses:
+  - 'VQ-07 FAIL: Uses non-Okabe-Ito palette (colors=["#306998", "#FFD43B", "#FF6B6B",
+    "#4ECDC4", "#9B59B6"]) — #306998 is legacy Python Blue explicitly flagged as non-compliant;
+    first series must be #009E73 brand green'
+  - 'Missing ANYPLOT_THEME support: no os.getenv("ANYPLOT_THEME", "light") reading
+    and no theme-adaptive tokens (PAGE_BG, ELEVATED_BG, INK, INK_SOFT) applied via
+    anyplot_theme; both renders likely rely on pipeline-level dark mode injection
+    rather than proper implementation'
+  - 'CQ-05: Saves to "plot.png" instead of f"plot-{THEME}.png" — must be plot-light.png
+    / plot-dark.png'
+  - 'SC-02: Spec explicitly requires smooth interpolation (spline/basis) for flowing
+    curves; implementation connects data points without any smoothing'
+  - 'Design Excellence low: no spine customization beyond theme_minimal defaults,
+    no visual hierarchy or focal emphasis on any genre trend, data displayed but not
+    interpreted'
+  - Code docstring header still says "pyplots.ai" (old branding) though rendered title
+    correctly shows anyplot.ai
+  image_description: |-
+    Light render (plot-light.png):
+      Background: Warm off-white (~#FAF8F1) for both page and panel backgrounds. PASS.
+      Chrome: Title "streamgraph-basic · plotnine · anyplot.ai" in dark text clearly readable. X-axis label "Month" and Y-axis label "Streaming Hours" readable in dark text at appropriate sizes. Tick labels (Jan '23, Jul '23, Jan '24, Jul '24; -400 to 400) all readable. Legend positioned right with Genre title and 5 swatches (Pop, Rock, Hip-Hop, Electronic, Jazz) — all readable.
+      Data: 5 centered ribbon bands filling the plot from ~-380 to ~+380. Colors: bottom (Pop) = teal (~#306998?), Rock = orange-brown, Hip-Hop = medium blue, Electronic = pink/lavender, Jazz = yellow/gold. Note: actual hex values (#306998, #FFD43B, #FF6B6B, #4ECDC4, #9B59B6) are non-Okabe-Ito — first series is NOT #009E73.
+      Legibility verdict: PASS — all text is readable against light background.
+
+    Dark render (plot-dark.png):
+      Background: Very dark near-black (appears close to pure #000000 rather than warm #1A1A17 — no theme tokens applied in code). FAIL on exact spec but functionally dark.
+      Chrome: Title, axis labels, and tick labels appear in white/light text — readable against dark background. No dark-on-dark failures observed for text. Legend box has dark background with light text — readable.
+      Data: Colors appear identical to light render — same teal, orange, blue, pink, yellow/gold bands. Data colors are consistent between themes (only chrome flips). However, visible black gap below the bottom green ribbon to the -400 axis mark suggests pure-black panel background bleeding through rather than #1A1A17.
+      Legibility verdict: PASS for text readability. FAIL for correct background token (#1A1A17 not implemented — theme switching handled externally by pipeline, not by code).
+  criteria_checklist:
+    visual_quality:
+      score: 27
+      max: 30
+      items:
+      - id: VQ-01
+        name: Text Legibility
+        score: 8
+        max: 8
+        passed: true
+        comment: 'All font sizes explicitly set: title 24pt, axis_title 20pt, axis_text
+          16pt, legend_text 16pt, legend_title 18pt. Readable in both light and dark
+          renders.'
+      - id: VQ-02
+        name: No Overlap
+        score: 6
+        max: 6
+        passed: true
+        comment: No text overlap. X-axis has only 4 well-spaced labels. Legend does
+          not overlap data area.
+      - id: VQ-03
+        name: Element Visibility
+        score: 6
+        max: 6
+        passed: true
+        comment: All 5 ribbon bands clearly visible and well-sized. Alpha=0.85 provides
+          good opacity with slight transparency.
+      - id: VQ-04
+        name: Color Accessibility
+        score: 1
+        max: 2
+        passed: false
+        comment: 'Custom palette (#306998, #FFD43B, #FF6B6B, #4ECDC4, #9B59B6) not
+          designed for CVD safety. Reasonable luminance variation helps since layers
+          are spatially separated, but not Okabe-Ito guaranteed safe.'
+      - id: VQ-05
+        name: Layout & Canvas
+        score: 4
+        max: 4
+        passed: true
+        comment: Streamgraph fills the canvas well. Legend positioned outside plot
+          area to the right. No content cut off. Good canvas utilization (>60%).
+      - id: VQ-06
+        name: Axis Labels & Title
+        score: 2
+        max: 2
+        passed: true
+        comment: 'Y-axis: ''Streaming Hours'' (descriptive with implicit units). X-axis:
+          ''Month''. Title uses correct anyplot.ai format in rendered output.'
+      - id: VQ-07
+        name: Palette Compliance
+        score: 0
+        max: 2
+        passed: false
+        comment: 'FAIL: Uses custom non-Okabe-Ito colors. #306998 (Python Blue) explicitly
+          flagged as non-compliant. First series must be #009E73. Dark background
+          likely not #1A1A17 (no theme tokens in code). Score: 0.'
+    design_excellence:
+      score: 9
+      max: 20
+      items:
+      - id: DE-01
+        name: Aesthetic Sophistication
+        score: 4
+        max: 8
+        passed: false
+        comment: Well-configured theme_minimal() with explicit font sizes and custom
+          (non-Okabe-Ito) colors. Streamgraph form is sophisticated but design execution
+          is library-default level.
+      - id: DE-02
+        name: Visual Refinement
+        score: 3
+        max: 6
+        passed: false
+        comment: theme_minimal() provides clean look with subtle grid. Explicit font
+          sizing adds polish. No explicit spine removal, no grid direction restriction,
+          no whitespace tuning beyond defaults.
+      - id: DE-03
+        name: Data Storytelling
+        score: 2
+        max: 6
+        passed: false
+        comment: Data displayed without visual hierarchy. No genre highlighted, no
+          trend emphasized. Viewer must find their own story in the flowing shapes.
+    spec_compliance:
+      score: 14
+      max: 15
+      items:
+      - id: SC-01
+        name: Plot Type
+        score: 5
+        max: 5
+        passed: true
+        comment: Correct streamgraph with symmetric centered baseline (baseline =
+          -totals/2). Uses geom_ribbon to create the characteristic flowing band appearance.
+      - id: SC-02
+        name: Required Features
+        score: 3
+        max: 4
+        passed: false
+        comment: 'Centered baseline ✓, legend ✓, distinct colors ✓, multiple categories
+          ✓. Missing: explicit smooth interpolation (spline/basis). Spec explicitly
+          requires ''smooth interpolation for flowing curves''.'
+      - id: SC-03
+        name: Data Mapping
+        score: 3
+        max: 3
+        passed: true
+        comment: X=month (time), Y=streaming hours centered around 0. All 5 genres
+          visible. Y-axis correctly shows both positive and negative range (-400 to
+          400).
+      - id: SC-04
+        name: Title & Legend
+        score: 3
+        max: 3
+        passed: true
+        comment: 'Rendered title: ''streamgraph-basic · plotnine · anyplot.ai'' —
+          correct format. Legend shows all 5 genres with correct labels. (Note: code
+          file still has ''pyplots.ai'' branding in labs() call and docstring.)'
+    data_quality:
+      score: 14
+      max: 15
+      items:
+      - id: DQ-01
+        name: Feature Coverage
+        score: 5
+        max: 6
+        passed: true
+        comment: Shows 5 genres (3-8 range ✓), 24 time points (10-100 range ✓), centered
+          baseline, varying magnitudes per genre, time trends visible. Could show
+          more dramatic crossover/convergence to better demonstrate the format's storytelling
+          power.
+      - id: DQ-02
+        name: Realistic Context
+        score: 5
+        max: 5
+        passed: true
+        comment: Music streaming hours by genre (Pop, Rock, Hip-Hop, Electronic, Jazz)
+          over two years — realistic, neutral, comprehensible scenario.
+      - id: DQ-03
+        name: Appropriate Scale
+        score: 4
+        max: 4
+        passed: true
+        comment: Base values 100-200 hours/month per genre are plausible streaming
+          magnitudes. Total ~600-800 hours/month across genres is reasonable. Y-axis
+          range (-400 to 400) correctly reflects the centered baseline.
+    code_quality:
+      score: 9
+      max: 10
+      items:
+      - id: CQ-01
+        name: KISS Structure
+        score: 3
+        max: 3
+        passed: true
+        comment: 'Linear flow: Imports → Data generation → Streamgraph position calculation
+          → Long-form DataFrame → Plot → Save. No functions or classes.'
+      - id: CQ-02
+        name: Reproducibility
+        score: 2
+        max: 2
+        passed: true
+        comment: np.random.seed(42) set before data generation.
+      - id: CQ-03
+        name: Clean Imports
+        score: 2
+        max: 2
+        passed: true
+        comment: All plotnine imports are used (aes, element_text, geom_ribbon, ggplot,
+          labs, scale_fill_manual, scale_x_continuous, theme, theme_minimal). numpy
+          and pandas used.
+      - id: CQ-04
+        name: Code Elegance
+        score: 2
+        max: 2
+        passed: true
+        comment: Clean Pythonic code. Matrix-based streamgraph position calculation
+          is appropriate. No over-engineering or fake functionality.
+      - id: CQ-05
+        name: Output & API
+        score: 0
+        max: 1
+        passed: false
+        comment: 'FAIL: Saves to ''plot.png'' instead of f''plot-{THEME}.png''. No
+          ANYPLOT_THEME env var reading. Should read os.getenv(''ANYPLOT_THEME'',
+          ''light'') and save as plot-{THEME}.png.'
+    library_mastery:
+      score: 6
+      max: 10
+      items:
+      - id: LM-01
+        name: Idiomatic Usage
+        score: 4
+        max: 5
+        passed: true
+        comment: 'Good use of plotnine''s grammar of graphics: ggplot() + geom_ribbon()
+          + scale_fill_manual() + labs() + theme_minimal() + theme(). pd.Categorical
+          for ordered factor control is idiomatic. Minor: could use ggsave() instead
+          of plot.save().'
+      - id: LM-02
+        name: Distinctive Features
+        score: 2
+        max: 5
+        passed: false
+        comment: geom_ribbon with fill aesthetic and the grammar-of-graphics layering
+          via + operator are distinctive to plotnine/ggplot2. However, the streamgraph
+          computation itself is library-agnostic, and geom_ribbon appears in letsplot/R
+          ggplot2 as well. No uniquely plotnine features leveraged.
+  verdict: REJECTED
 impl_tags:
   dependencies: []
-  techniques: []
+  techniques:
+  - layer-composition
   patterns:
-    - data-generation
-    - matrix-construction
+  - data-generation
+  - matrix-construction
+  - iteration-over-groups
   dataprep: []
   styling:
-    - alpha-blending
-review:
-  strengths: []
-  weaknesses: []
-  improvements: []
-  verdict: APPROVED
+  - alpha-blending