PathScripts.kdtree Namespace Reference

Classes

class  KDTree
 
class  Rectangle
 

Functions

def distance_matrix (x, y, p=2, threshold=1000000)
 
def minkowski_distance (x, y, p=2)
 
def minkowski_distance_p (x, y, p=2)
 

Function Documentation

def PathScripts.kdtree.distance_matrix (   x,
  y,
  p = 2,
  threshold = 1000000 
)
Compute the distance matrix.

Returns the matrix of all pair-wise distances.

Parameters
----------
x : (M, K) array_like
    TODO: description needed
y : (N, K) array_like
    TODO: description needed
p : float, 1 <= p <= infinity
    Which Minkowski p-norm to use.
threshold : positive int
    If ``M * N * K`` > `threshold`, algorithm uses a Python loop instead
    of large temporary arrays.

Returns
-------
result : (M, N) ndarray
    Distance matrix.

Examples
--------
>>> distance_matrix([[0,0],[0,1]], [[1,0],[1,1]])
array([[ 1.        ,  1.41421356],
       [ 1.41421356,  1.        ]])

References PathScripts.kdtree.minkowski_distance().

def PathScripts.kdtree.minkowski_distance (   x,
  y,
  p = 2 
)
Compute the L**p distance between two arrays.

Parameters
----------
x : (M, K) array_like
    Input array.
y : (N, K) array_like
    Input array.
p : float, 1 <= p <= infinity
    Which Minkowski p-norm to use.

Examples
--------
>>> minkowski_distance([[0,0],[0,0]], [[1,1],[0,1]])
array([ 1.41421356,  1.        ])

References PathScripts.kdtree.minkowski_distance_p().

Referenced by PathScripts.kdtree.KDTree.count_neighbors(), PathScripts.kdtree.distance_matrix(), PathScripts.kdtree.Rectangle.max_distance_point(), PathScripts.kdtree.Rectangle.max_distance_rectangle(), PathScripts.kdtree.Rectangle.min_distance_point(), PathScripts.kdtree.Rectangle.min_distance_rectangle(), PathScripts.kdtree.KDTree.query(), PathScripts.kdtree.KDTree.query_ball_tree(), and PathScripts.kdtree.KDTree.query_pairs().

def PathScripts.kdtree.minkowski_distance_p (   x,
  y,
  p = 2 
)
Compute the p-th power of the L**p distance between two arrays.

For efficiency, this function computes the L**p distance but does
not extract the pth root. If `p` is 1 or infinity, this is equal to
the actual L**p distance.

Parameters
----------
x : (M, K) array_like
    Input array.
y : (N, K) array_like
    Input array.
p : float, 1 <= p <= infinity
    Which Minkowski p-norm to use.

Examples
--------
>>> minkowski_distance_p([[0,0],[0,0]], [[1,1],[0,1]])
array([2, 1])

Referenced by PathScripts.kdtree.minkowski_distance().