feat(altair): implement scatter-matrix

plots/scatter-matrix/implementations/altair.py

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+""" pyplots.ai
+scatter-matrix: Scatter Plot Matrix
+Library: altair 6.0.0 | Python 3.13.11
+Quality: 85/100 | Created: 2025-12-26
+"""
+
+import altair as alt
+import numpy as np
+import pandas as pd
+
+
+# Data - Iris dataset (classic multivariate data)
+np.random.seed(42)
+
+# Generate realistic iris-like data with 4 variables and 3 species
+n_per_species = 50
+
+data = []
+# Setosa - smaller flowers
+for _ in range(n_per_species):
+    data.append(
+        {
+            "Sepal Length (cm)": np.random.normal(5.0, 0.35),
+            "Sepal Width (cm)": np.random.normal(3.4, 0.38),
+            "Petal Length (cm)": np.random.normal(1.5, 0.17),
+            "Petal Width (cm)": np.random.normal(0.25, 0.1),
+            "Species": "Setosa",
+        }
+    )
+
+# Versicolor - medium flowers
+for _ in range(n_per_species):
+    data.append(
+        {
+            "Sepal Length (cm)": np.random.normal(5.9, 0.52),
+            "Sepal Width (cm)": np.random.normal(2.8, 0.31),
+            "Petal Length (cm)": np.random.normal(4.3, 0.47),
+            "Petal Width (cm)": np.random.normal(1.3, 0.2),
+            "Species": "Versicolor",
+        }
+    )
+
+# Virginica - larger flowers
+for _ in range(n_per_species):
+    data.append(
+        {
+            "Sepal Length (cm)": np.random.normal(6.6, 0.64),
+            "Sepal Width (cm)": np.random.normal(3.0, 0.32),
+            "Petal Length (cm)": np.random.normal(5.5, 0.55),
+            "Petal Width (cm)": np.random.normal(2.0, 0.27),
+            "Species": "Virginica",
+        }
+    )
+
+df = pd.DataFrame(data)
+
+# Variables for the scatter matrix
+variables = ["Sepal Length (cm)", "Sepal Width (cm)", "Petal Length (cm)", "Petal Width (cm)"]
+
+# Color scheme - Distinct colorblind-safe palette (blue, orange, green)
+color_scale = alt.Scale(domain=["Setosa", "Versicolor", "Virginica"], range=["#306998", "#E69F00", "#009E73"])
+
+# Use Altair's native repeat() for declarative scatter matrix construction
+# This is the idiomatic Altair approach for creating SPLOM (scatter plot matrix)
+scatter_matrix = (
+    alt.Chart(df)
+    .mark_circle(size=100, opacity=0.7)
+    .encode(
+        alt.X(alt.repeat("column"), type="quantitative", axis=alt.Axis(labelFontSize=18, titleFontSize=22)),
+        alt.Y(alt.repeat("row"), type="quantitative", axis=alt.Axis(labelFontSize=18, titleFontSize=22)),
+        alt.Color(
+            "Species:N",
+            scale=color_scale,
+            legend=alt.Legend(
+                title="Species",
+                titleFontSize=28,
+                labelFontSize=24,
+                symbolSize=400,
+                orient="right",
+                titlePadding=15,
+                labelPadding=10,
+            ),
+        ),
+        tooltip=[
+            "Species:N",
+            alt.Tooltip(alt.repeat("column"), type="quantitative"),
+            alt.Tooltip(alt.repeat("row"), type="quantitative"),
+        ],
+    )
+    .properties(width=320, height=320)
+    .repeat(row=variables, column=variables)
+)
+
+# Apply configuration and title
+chart = (
+    scatter_matrix.properties(
+        title=alt.Title(text="scatter-matrix · altair · pyplots.ai", fontSize=36, anchor="middle", offset=25)
+    )
+    .configure_axis(gridOpacity=0.3)
+    .configure_view(strokeWidth=0)
+)
+
+# Save as PNG (scale_factor=3 gives us ~3840x3840 for square output close to 3600x3600 target)
+chart.save("plot.png", scale_factor=3.0)
+
+# Save interactive HTML version
+chart.save("plot.html")

plots/scatter-matrix/metadata/altair.yaml

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+library: altair
+specification_id: scatter-matrix
+created: '2025-12-26T16:13:43Z'
+updated: '2025-12-26T16:37:44Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20525446227
+issue: 0
+python_version: 3.13.11
+library_version: 6.0.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-matrix/altair/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/scatter-matrix/altair/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/scatter-matrix/altair/plot.html
+quality_score: 85
+review:
+  strengths:
+  - Excellent use of Altair's declarative repeat() pattern for idiomatic SPLOM construction
+  - Colorblind-safe palette (blue/orange/green) provides clear species distinction
+  - Clean data generation with realistic Iris-like measurements and proper random
+    seed
+  - All axis labels include units (cm) for clarity
+  - Interactive tooltips enhance usability in HTML version
+  weaknesses:
+  - Diagonal cells show scatter (x=y lines) instead of required histograms/KDE for
+    univariate distributions as specified
+  - Legend could be larger or more prominently positioned for better visual balance