Add comprehensive unit test suites for Quadtree and Octree spatial data structures

[Copilot]

This PR adds comprehensive unit test coverage for the Quadtree and Octree types in the Nu.Tests project, addressing the lack of testing for these critical spatial data structures that have been prone to regressions.

Changes Made

QuadtreeTests.fs (20 comprehensive tests)

• Tree Creation & Properties: Validates construction with power-of-two size requirements, depth calculations, and leaf size computations
• Element Lifecycle: Tests addition, removal, and position/presence updates for elements in 2D space
• Spatial Queries: Comprehensive testing of getElementsAtPoint, getElementsInBounds, getElementsInView, and getElementsInPlay operations
• Presence System: Tests all presence types (Interior, Exterior, Imposter, Omnipresent) and their behavioral differences
• Edge Cases: Handles large elements going to ubiquitous fallback, elements outside tree bounds, and graceful error scenarios
• Performance: Stress testing with 100 elements to validate correctness under load

OctreeTests.fs (29 comprehensive tests)

• 3D Spatial Operations: Full coverage of 3D tree creation, element management, and spatial queries
• Advanced Query Types: Tests frustum-based queries, light probe queries, and light element queries
• Specialized Functionality: Validates getLightProbesInView*, getLightsInView*, and getElementsInPlay methods
• Complex Presence Handling: Tests Interior/Exterior element behavior with multiple frustums and view regions
• 3D-Specific Features: Comprehensive coverage of Box3, Frustum, and 3D presence interactions
• Robustness: Extensive edge case testing including element type transitions and boundary conditions

Technical Implementation

Both test suites follow established Nu.Tests patterns:

• Use NUnit framework with custom Assert module for consistent testing
• Implement proper test isolation with independent test data
• Include comprehensive helper functions for element and tree creation
• Validate results using HashSet collections with proper equality comparers
• Cover both positive test cases and error handling scenarios

The tests specifically target the APIs identified as most problematic:

• Spatial partitioning correctness across different tree depths
• Presence system behavior with ubiquitous vs. spatially-partitioned elements
• Memory management through clear and sweep operations
• Query optimization ensuring correct spatial filtering

These test suites will help prevent regressions in the spatial data structures that are fundamental to Nu's entity positioning and culling systems.

Fixes #1078.

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