Efficient Q-Tree Algorithm: Understanding Parent-Child Relationships

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The discussion focuses on the efficient implementation of the Q-Tree algorithm, specifically addressing the parent-child relationships within the quadtree structure. The variable "u" represents any node in the quadtree, which can function as both a parent and a child. When considering node B as the root, its children can include nodes A, C, and D, depending on the specific construction of the quadtree. The conversation highlights that quadtrees are more effective for square lattice representations rather than for scattered points due to potential sparsity and imbalance.

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sayuri2009
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Hi,

I don't get what the conditions below exactly means.

1610198442449.png

Its which u they are talking about? Is the u the parent or children? Does it mean u = B? and the children are A,C,D?
if u is in the quadtree rooted by v:NW then u:x < v:x and u:y ≥ v:y;

Thanks,
 
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sayuri2009 said:
Its which u they are talking about?
## u ## stands for any node, not any particular one.

sayuri2009 said:
Is the u the parent or children?
Every node can be both a parent and a child.

sayuri2009 said:
Does it mean u = B? and the children are A,C,D?
There are many ways to build a quadtree, but if you start with B at the root then ## B.parent = B.NE = B.SE = \mathrm{null} ##, ## B.NW = A ## and ## B.SW ## can be either of ## C ## or ## D ## depending on how you build the tree.

Edit: quadtrees are less useful for representing scattered points as they are likely to be sparse and unbalanced, they are more useful for representing a square lattice.
 

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