Containers
==========

Spatial data structures for efficient nearest neighbor queries.

.. automodule:: pytcl.containers
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K-D Tree
--------

K-dimensional tree for spatial queries.

.. automodule:: pytcl.containers.kd_tree
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   :exclude-members: NeighborResult


R-Tree
------

R-tree for spatial indexing.

.. automodule:: pytcl.containers.rtree
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   :exclude-members: NeighborResult

VP-Tree
-------

Vantage-point tree for metric spaces.

.. automodule:: pytcl.containers.vptree
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   :exclude-members: NeighborResult

Cover Tree
----------

Cover tree for approximate nearest neighbors.

.. automodule:: pytcl.containers.covertree
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   :exclude-members: NeighborResult

Base
----

.. automodule:: pytcl.containers.base
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Cluster Set
-----------

.. automodule:: pytcl.containers.cluster_set
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Measurement Set
---------------

.. automodule:: pytcl.containers.measurement_set
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Track List
----------

.. automodule:: pytcl.containers.track_list
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