A kD-tree suitable for splitting parameter spaces and counting
hypervolumes. Is modified from the KDTree class so that bounding boxes
are stored. This means that there are no longer gaps in the hypervolume
once the samples have been split into groups.
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__init__(self,
objects,
boundingbox,
dims=0)
Construct a kD-tree from a sequence of objects. |
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_same_coords(self,
objects)
True if and only if all the given objects have the same coordinates. |
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objects(self)
Returns the objects in the tree. |
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__iter__(self)
Iterator over all the objects contained in the tree. |
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split_dim(self)
Returns the dimension along which this level of the kD-tree splits. |
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bounds(self)
Returns the coordinates of the lower-left and upper-right corners of
the bounding box for this tree: low_left, up_right |
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volume(self)
Returns the volume of the bounding box of the tree. |
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operate(self,
f,
g,
boxing=64)
Operates on tree nodes exceeding boxing parameter depth. |
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search(self,
coordinates,
boxing=64)
takes a set of coordinates and searches down through the tree untill
it gets to a box with less than 'boxing' objects in it and returns
the box bounds, number of objects in the box, and the weighting. |
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fillNewTree(self,
boxing=64,
isArea=False)
copies tree structure, but with KDSkeleton as the new nodes. |
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Inherited from object:
__delattr__,
__format__,
__getattribute__,
__hash__,
__new__,
__reduce__,
__reduce_ex__,
__repr__,
__setattr__,
__sizeof__,
__str__,
__subclasshook__
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