spec: add voronoi-basic specification (#3420)

## New Specification: `voronoi-basic`

Related to #3415

---

### specification.md

# voronoi-basic: Voronoi Diagram for Spatial Partitioning

## Description

A Voronoi diagram partitions a plane into regions based on the distance
to a set of seed points, where each region contains all points closer to
its seed than to any other. This visualization is essential for
understanding spatial relationships, proximity analysis, and territorial
boundaries. It reveals natural clustering patterns and helps identify
areas of influence around data points.

## Applications

- Analyzing service area coverage for retail stores or emergency
facilities based on customer proximity
- Visualizing territorial boundaries in ecological studies to show
animal home ranges or plant distribution zones
- Mapping nearest-neighbor relationships in urban planning for
optimizing resource placement like cell towers or hospitals

## Data

- `x` (float) - X-coordinate of seed points
- `y` (float) - Y-coordinate of seed points
- `label` (string, optional) - Identifier for each seed point
- Size: 10-50 seed points recommended for clear visualization
- Example: Random or structured point distribution within a bounded
region

## Notes

- Cells should be clipped to a visible bounding box to prevent infinite
regions
- Each Voronoi cell should be visually distinguishable through colors or
edge styling
- Seed points should be clearly marked within their respective cells
- Consider using a color palette that allows easy differentiation of
adjacent regions

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plots/voronoi-basic/specification.md

@@ -0,0 +1,26 @@
+# voronoi-basic: Voronoi Diagram for Spatial Partitioning
+
+## Description
+
+A Voronoi diagram partitions a plane into regions based on the distance to a set of seed points, where each region contains all points closer to its seed than to any other. This visualization is essential for understanding spatial relationships, proximity analysis, and territorial boundaries. It reveals natural clustering patterns and helps identify areas of influence around data points.
+
+## Applications
+
+- Analyzing service area coverage for retail stores or emergency facilities based on customer proximity
+- Visualizing territorial boundaries in ecological studies to show animal home ranges or plant distribution zones
+- Mapping nearest-neighbor relationships in urban planning for optimizing resource placement like cell towers or hospitals
+
+## Data
+
+- `x` (float) - X-coordinate of seed points
+- `y` (float) - Y-coordinate of seed points
+- `label` (string, optional) - Identifier for each seed point
+- Size: 10-50 seed points recommended for clear visualization
+- Example: Random or structured point distribution within a bounded region
+
+## Notes
+
+- Cells should be clipped to a visible bounding box to prevent infinite regions
+- Each Voronoi cell should be visually distinguishable through colors or edge styling
+- Seed points should be clearly marked within their respective cells
+- Consider using a color palette that allows easy differentiation of adjacent regions

plots/voronoi-basic/specification.yaml

@@ -0,0 +1,29 @@
+# Specification-level metadata for voronoi-basic
+# Auto-synced to PostgreSQL on push to main
+
+spec_id: voronoi-basic
+title: Voronoi Diagram for Spatial Partitioning
+
+# Specification tracking
+created: 2026-01-09T07:51:19Z
+updated: null
+issue: 3415
+suggested: MarkusNeusinger
+
+# Classification tags (applies to all library implementations)
+# See docs/reference/tagging-system.md for detailed guidelines
+tags:
+  plot_type:
+    - voronoi
+    - tessellation
+  data_type:
+    - numeric
+    - spatial
+  domain:
+    - general
+    - science
+    - machine-learning
+  features:
+    - basic
+    - 2d
+    - partitioning