Class DescreteMetric

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Find neighboring points in descretized space

If input space is descretized and all points fill in N-dimensional cube, this finder returns list of neighboring points for a given distance.

As input points it operates on discretized values, not absolute coordinates (which are e.g. in mm)

Instance Methods

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__init__(self, elementsize=1, distance_function=cartesianDistance)
Initialize the class provided @elementsize and @distance_function

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_computeFilter(self, radius)
(Re)Computer filter_coord based on given radius

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getNeighbors(self, origin, radius=0)
Returns coordinates of the neighbors which are within distance from coord

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_setFilter(self, filter_coord)
Lets allow to specify some custom filter to use

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_getFilter(self)
Lets allow to specify some custom filter to use

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Inherited from Metric: getNeighbor

Inherited from object: __delattr__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __str__

Class Variables

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filter_coord = property(fget= _getFilter, fset= _setFilter)

elementsize = property(fget= lambda self: self.__elementsize)

Properties

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Inherited from object: __class__

Method Details

[hide private]

init(self, elementsize=1, distance_function=cartesianDistance)
(Constructor)

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Initialize the class provided @elementsize and @distance_function

Overrides: object.__init__

getNeighbors(self, origin, radius=0)

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Returns coordinates of the neighbors which are within distance from coord

XXX radius might need to be not a scalar but a vector of scalars to specify search distance in different dimensions differently... but then may be it has to be a tensor to specify orientation etc? :-) so it might not be necessary for now

Overrides: Metric.getNeighbors

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Class DescreteMetric

__init__(self, elementsize=1, distance_function=cartesianDistance) (Constructor)

getNeighbors(self, origin, radius=0)

init(self, elementsize=1, distance_function=cartesianDistance)
(Constructor)