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Rectangle

As explained in Advanced Algorithms and Data Structures

A rectangle is a planar quadrilateral with four right angles used here as the spatial region associated with an R-tree node.

A rectangle is the spatial region associated with an R-tree node. Its corners come from the minimum and maximum value of each coordinate among the points in that node’s subtree; in higher dimensions, it becomes a hyper-rectangle. section 10.2.2

R-tree rectangles serve two related purposes:

  • A leaf rectangle is the smallest axis-aligned rectangle containing every point stored in that leaf. section 10.2.2
  • An internal-node rectangle is the smallest axis-aligned rectangle containing the bounding rectangles of all its children. section 10.2.2

City-map regions

For points representing cities, an R-tree groups nearby points under bounding rectangles. A parent rectangle encloses the rectangles of its child groups, creating a hierarchy over the Cartesian plane.

How Advanced Algorithms and Data Structures covers it

How deep it goes
Defines rectangles through coordinate extrema and smallest containment, extending the idea to axis-aligned hyper-rectangles.
Examples
Illustrates rectangles with city-map points, nested bounding regions, and overlapping regions on a Cartesian plane.
What you can do after
Evaluate R-tree regions by identifying the minimum coordinate-aligned rectangle enclosing points or child rectangles.
How it connects
Connects rectangles with R-trees, B-trees, bounding boxes, Cartesian coordinates, and spatial hierarchy.

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This explainer was generated by Manning's knowledge graph from the text of Advanced Algorithms and Data Structures. The section links point to the parts of the book it draws on.