chore(altair): add metadata for facet-grid

Author: github-actions[bot]

plots/facet-grid/implementations/python/altair.py

@@ -1,14 +1,25 @@
-""" pyplots.ai
+"""anyplot.ai
 facet-grid: Faceted Grid Plot
-Library: altair 6.0.0 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-30
+Library: altair | Python 3.13
+Quality: pending | Created: 2026-05-13
 """
 
+import os
+
 import altair as alt
 import numpy as np
 import pandas as pd
 
 
+# Theme tokens
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+
+OKABE_ITO = ["#009E73", "#D55E00", "#0072B2", "#CC79A7", "#E69F00", "#56B4E9", "#F0E442"]
+
 # Data - Crop yield across different soil types and seasons
 np.random.seed(42)
 
@@ -21,11 +32,8 @@
 for soil in soil_types:
     for season in seasons:
         for crop in crop_types:
-            # Base yield varies by soil type
             base_yield = {"Sandy": 3.5, "Clay": 4.0, "Loam": 5.0}[soil]
-            # Season affects yield
             season_mult = {"Spring": 0.9, "Summer": 1.1, "Fall": 1.0}[season]
-            # Crop type affects yield and water needs
             crop_base = {"Wheat": 3.8, "Corn": 4.5, "Soybean": 3.2}[crop]
 
             yield_val = np.random.normal(base_yield * season_mult + crop_base, 0.8, n_per_group)
@@ -44,31 +52,49 @@
 
 df = pd.DataFrame(data)
 
-# Create faceted chart with scatter plots - facet by soil and season, color by crop
+# Create faceted chart with scatter plots
 chart = (
     alt.Chart(df)
-    .mark_circle(size=100, opacity=0.7)
+    .mark_circle(size=150, opacity=0.7)
     .encode(
         x=alt.X("Water Usage (mm):Q", scale=alt.Scale(zero=False)),
         y=alt.Y("Yield (tons/ha):Q", scale=alt.Scale(zero=False)),
-        color=alt.Color("Crop:N", scale=alt.Scale(domain=crop_types, range=["#306998", "#FFD43B", "#4CAF50"])),
+        color=alt.Color("Crop:N", scale=alt.Scale(domain=crop_types, range=OKABE_ITO[:3])),
         tooltip=["Yield (tons/ha)", "Water Usage (mm)", "Soil Type", "Season", "Crop"],
     )
     .properties(width=320, height=260)
     .facet(
         column=alt.Column(
-            "Season:N", header=alt.Header(titleFontSize=20, labelFontSize=16), sort=["Spring", "Summer", "Fall"]
+            "Season:N", header=alt.Header(titleFontSize=22, labelFontSize=18), sort=["Spring", "Summer", "Fall"]
         ),
         row=alt.Row(
-            "Soil Type:N", header=alt.Header(titleFontSize=20, labelFontSize=16), sort=["Sandy", "Clay", "Loam"]
+            "Soil Type:N", header=alt.Header(titleFontSize=22, labelFontSize=18), sort=["Sandy", "Clay", "Loam"]
         ),
     )
-    .configure_axis(labelFontSize=14, titleFontSize=16)
-    .configure_legend(titleFontSize=18, labelFontSize=16, symbolSize=180)
-    .configure_title(fontSize=24)
-    .properties(title="facet-grid · altair · pyplots.ai")
+    .configure_axis(
+        labelFontSize=16,
+        titleFontSize=20,
+        domainColor=INK_SOFT,
+        tickColor=INK_SOFT,
+        gridColor=INK,
+        gridOpacity=0.10,
+        labelColor=INK_SOFT,
+        titleColor=INK,
+    )
+    .configure_legend(
+        titleFontSize=18,
+        labelFontSize=16,
+        symbolSize=180,
+        fillColor=ELEVATED_BG,
+        strokeColor=INK_SOFT,
+        labelColor=INK_SOFT,
+        titleColor=INK,
+    )
+    .configure_title(fontSize=28, color=INK)
+    .configure_view(fill=PAGE_BG, stroke=INK_SOFT)
+    .properties(title="facet-grid · altair · anyplot.ai", background=PAGE_BG)
 )
 
 # Save as PNG and HTML
-chart.save("plot.png", scale_factor=3.0)
-chart.save("plot.html")
+chart.save(f"plot-{THEME}.png", scale_factor=3.0)
+chart.save(f"plot-{THEME}.html")

plots/facet-grid/metadata/python/altair.yaml

@@ -1,212 +1,21 @@
+# Per-library metadata for altair implementation of facet-grid
+# Auto-generated by impl-generate.yml
+
 library: altair
+language: python
 specification_id: facet-grid
 created: '2025-12-30T16:30:41Z'
-updated: '2025-12-30T16:38:55Z'
-generated_by: claude-opus-4-5-20251101
-workflow_run: 20601059244
-issue: 0
-python_version: 3.13.11
-library_version: 6.0.0
-preview_url: https://storage.googleapis.com/anyplot-images/plots/facet-grid/altair/plot.png
-preview_html: https://storage.googleapis.com/anyplot-images/plots/facet-grid/altair/plot.html
-quality_score: 91
-impl_tags:
-  dependencies: []
-  techniques:
-  - faceting
-  - html-export
-  patterns:
-  - data-generation
-  - iteration-over-groups
-  dataprep: []
-  styling: []
+updated: '2026-05-13T03:34:01Z'
+generated_by: claude-haiku
+workflow_run: 25776543142
+issue: 2696
+python_version: 3.13.13
+library_version: 6.1.0
+preview_url_light: https://storage.googleapis.com/anyplot-images/plots/facet-grid/python/altair/plot-light.png
+preview_url_dark: https://storage.googleapis.com/anyplot-images/plots/facet-grid/python/altair/plot-dark.png
+preview_html_light: https://storage.googleapis.com/anyplot-images/plots/facet-grid/python/altair/plot-light.html
+preview_html_dark: https://storage.googleapis.com/anyplot-images/plots/facet-grid/python/altair/plot-dark.html
+quality_score: null
 review:
-  strengths:
-  - Excellent use of Altair's declarative faceting syntax with .facet() for clean
-    2D grid creation
-  - Well-structured agricultural scenario that naturally demonstrates multi-dimensional
-    data exploration
-  - Clean color palette (blue, yellow, green) that is both aesthetically pleasing
-    and colorblind-safe
-  - Proper use of Altair encoding types (:Q for quantitative, :N for nominal)
-  - Good axis labels with units and appropriate scale configuration
-  weaknesses:
-  - Legend is positioned at the edge of the canvas rather than integrated closer to
-    the plot area
-  - Could benefit from interactive selections (Altair's distinctive feature) to highlight
-    crop types across all facets
-  image_description: 'The plot displays a 3×3 faceted grid of scatter plots showing
-    crop yield vs water usage. The grid is organized with Season (Spring, Summer,
-    Fall) as columns and Soil Type (Sandy, Clay, Loam) as rows. Each subplot contains
-    scatter points colored by crop type: blue for Wheat, yellow for Corn, and green
-    for Soybean. The title "facet-grid · altair · pyplots.ai" appears at the top left.
-    Axis labels show "Water Usage (mm)" on x-axis (range ~40-95) and "Yield (tons/ha)"
-    on y-axis (range ~5-13). A color legend for Crop appears on the right side. The
-    grid lines are subtle gray, and the overall layout is clean with good spacing
-    between panels.'
-  criteria_checklist:
-    visual_quality:
-      score: 36
-      max: 40
-      items:
-      - id: VQ-01
-        name: Text Legibility
-        score: 9
-        max: 10
-        passed: true
-        comment: All text is readable; title, axis labels, and tick marks are appropriately
-          sized, though axis title font could be slightly larger
-      - id: VQ-02
-        name: No Overlap
-        score: 8
-        max: 8
-        passed: true
-        comment: No overlapping text anywhere in the visualization
-      - id: VQ-03
-        name: Element Visibility
-        score: 7
-        max: 8
-        passed: true
-        comment: Markers are well-sized with good opacity (0.7); slightly crowded
-          in some cells but still distinguishable
-      - id: VQ-04
-        name: Color Accessibility
-        score: 5
-        max: 5
-        passed: true
-        comment: Blue, yellow, and green palette is colorblind-safe
-      - id: VQ-05
-        name: Layout Balance
-        score: 4
-        max: 5
-        passed: true
-        comment: Good use of canvas space; the faceted grid fills the area well, though
-          legend is positioned slightly away from the main plot
-      - id: VQ-06
-        name: Axis Labels
-        score: 2
-        max: 2
-        passed: true
-        comment: 'Labels include units: "Yield (tons/ha)", "Water Usage (mm)"'
-      - id: VQ-07
-        name: Grid & Legend
-        score: 1
-        max: 2
-        passed: true
-        comment: Grid is subtle; legend is clear but positioned at the edge
-    spec_compliance:
-      score: 25
-      max: 25
-      items:
-      - id: SC-01
-        name: Plot Type
-        score: 8
-        max: 8
-        passed: true
-        comment: Correct faceted grid with scatter plots in each cell
-      - id: SC-02
-        name: Data Mapping
-        score: 5
-        max: 5
-        passed: true
-        comment: X (Water Usage) and Y (Yield) correctly assigned with two categorical
-          faceting variables
-      - id: SC-03
-        name: Required Features
-        score: 5
-        max: 5
-        passed: true
-        comment: 'All spec features present: faceting by row (Soil Type) and column
-          (Season), shared axes, scatter as base plot'
-      - id: SC-04
-        name: Data Range
-        score: 3
-        max: 3
-        passed: true
-        comment: All data visible within axes ranges
-      - id: SC-05
-        name: Legend Accuracy
-        score: 2
-        max: 2
-        passed: true
-        comment: Crop legend correctly shows all three categories
-      - id: SC-06
-        name: Title Format
-        score: 2
-        max: 2
-        passed: true
-        comment: Correct format "facet-grid · altair · pyplots.ai"
-    data_quality:
-      score: 18
-      max: 20
-      items:
-      - id: DQ-01
-        name: Feature Coverage
-        score: 7
-        max: 8
-        passed: true
-        comment: Shows variation across soil types (Loam yields higher), seasons (Summer
-          slightly higher), and crops; demonstrates the multi-dimensional exploration
-          purpose well
-      - id: DQ-02
-        name: Realistic Context
-        score: 7
-        max: 7
-        passed: true
-        comment: Crop yield vs water usage across soil types and seasons is a realistic
-          agricultural scenario
-      - id: DQ-03
-        name: Appropriate Scale
-        score: 4
-        max: 5
-        passed: true
-        comment: Yield values (5-13 tons/ha) and water usage (40-95 mm) are plausible,
-          though water usage range is on the lower end for seasonal measurements
-    code_quality:
-      score: 9
-      max: 10
-      items:
-      - id: CQ-01
-        name: KISS Structure
-        score: 3
-        max: 3
-        passed: true
-        comment: Clean imports → data → plot → save structure, no functions/classes
-      - id: CQ-02
-        name: Reproducibility
-        score: 3
-        max: 3
-        passed: true
-        comment: Uses np.random.seed(42)
-      - id: CQ-03
-        name: Clean Imports
-        score: 2
-        max: 2
-        passed: true
-        comment: All imports are used (altair, numpy, pandas)
-      - id: CQ-04
-        name: No Deprecated API
-        score: 1
-        max: 1
-        passed: true
-        comment: Current Altair API used
-      - id: CQ-05
-        name: Output Correct
-        score: 0
-        max: 1
-        passed: false
-        comment: Saves as both plot.png and plot.html, which is fine, but minor deduction
-          for not following the exact single-output convention
-    library_features:
-      score: 3
-      max: 5
-      items:
-      - id: LF-01
-        name: Uses distinctive library features
-        score: 3
-        max: 5
-        passed: true
-        comment: Good use of Altair's declarative faceting with .facet(), Column/Row
-          headers, encoding types (:Q, :N), and tooltips. Could leverage more Altair-specific
-          features like interactive selections or conditional encoding
-  verdict: APPROVED
+  strengths: []
+  weaknesses: []