The DataPointLocator class is a simple utility class that allows
data-points that are 'close' to a given position in space to be located
easily. This class uses spatial partitioning (k-d tree) to ensure that
the search for data-points is carried out in a computationally efficient
manner.
1) Instantiate a new DataPointLocator object. This sets up the
instance ready to carry out the search. At this point the results list is
empty. 2) Execute the various SearchForDataPointsWithinX methods to fill
the internal results list with array-coordinates that are within the
specified world-distance of the various search origins. 3) Optionally
'uniquify' the results list. 4) Examine the results list to find those
points that were within the specified distances of the search
origins.
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__init__(self,
volumeData)
This function creates a new DataPointLocator instance. |
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SearchForDataPointsWithin(self,
world,
distance)
This function searches for valid array-coordinates whose
corresponding world-coordinate lies within distance of the specified
world-coordinate. |
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SearchForDataPointsWithinL(self,
worldCoordinates,
distances)
This function is similar to SearchForDataPointsWith, however this
function accepts a list of world-coordinate search origins and a
corresponding list of distances. |
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UniquifyResults(self)
This function uniquifies the result list so that each
array-coordinate appears only once. |
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ClearResults(self)
This function clears the current result list. |
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iterable< iterable< int, 3 > >
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_getResults(self)
This function and the synonymous property Results allows access to
the result list. |
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Inherited from object:
__delattr__,
__format__,
__getattribute__,
__hash__,
__new__,
__reduce__,
__reduce_ex__,
__repr__,
__setattr__,
__sizeof__,
__str__,
__subclasshook__
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