A pure Python Quadtree implementation.
Project description
quads
A pure Python Quadtree implementation.
Quadtrees are a useful data structure for sparse datasets where the position of the data is important. They're especially for spatial indexing & image processing.
Usage
>>> import quads
>>> tree = quads.QuadTree(
... (0, 0), # The center point
... 10, # The width
... 10, # The height
... )
# You can choose to simply represent points that exist.
>>> tree.insert((1, 2))
True
# ...or include extra data at those points.
>>> tree.insert(quads.Point(4, -3, data="Samus"))
True
# You can search for a given point. It returns the point if found...
>>> tree.find((1, 2))
Point(1, 2)
# Or `None` if there's no match.
>>> tree.find((4, -4))
None
# You can also find all the points within a given region.
>>> bb = quads.BoundingBox(min_x=-1, min_y=-2, max_x=2, max_y=2)
>>> tree.within_bb(bb)
[Point(1, 2)]
Setup
$ pip install quads
Requirements
- Python 3.7+ (untested on older versions but may work)
Running Tests
$ git clone https://github.com/toastdriven/quads.git
$ cd quads
$ poetry install
$ pytest .
License
New BSD
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quads-1.0.0b0.tar.gz
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