geokdtree.kdtree 

 1from .core import kdtree, closest_point
 2
 3
 4class KDTree:
 5    def __init__(self, points):
 6        """
 7        Function:
 8
 9        - Build a KDTree from a list of n dimensional cartesian points.
10
11        Required Arguments:
12
13        - `points`
14            - Type: list of tuples
15            - What: A list of n dimensional cartesian points to build the KDTree from
16
17        Returns:
18
19        - A KDTree object that can be used to find the closest point to a given point.
20        """
21        self.tree = kdtree(points, depth=0, axis_count=len(points[0]))
22
23    def closest_point(self, point):
24        """
25        Function:
26
27        - Find the closest point in the KDTree to a given point.
28
29        Required Arguments:
30
31        - `point`
32            - Type: tuple
33            - What: The point to find the closest point to
34
35        Returns:
36
37        - The closest point found in the KDTree to the given point.
38        """
39        return closest_point(self.tree, point)[0]
class KDTree: 
 5class KDTree:
 6    def __init__(self, points):
 7        """
 8        Function:
 9
10        - Build a KDTree from a list of n dimensional cartesian points.
11
12        Required Arguments:
13
14        - `points`
15            - Type: list of tuples
16            - What: A list of n dimensional cartesian points to build the KDTree from
17
18        Returns:
19
20        - A KDTree object that can be used to find the closest point to a given point.
21        """
22        self.tree = kdtree(points, depth=0, axis_count=len(points[0]))
23
24    def closest_point(self, point):
25        """
26        Function:
27
28        - Find the closest point in the KDTree to a given point.
29
30        Required Arguments:
31
32        - `point`
33            - Type: tuple
34            - What: The point to find the closest point to
35
36        Returns:
37
38        - The closest point found in the KDTree to the given point.
39        """
40        return closest_point(self.tree, point)[0]
KDTree(points) 
 6    def __init__(self, points):
 7        """
 8        Function:
 9
10        - Build a KDTree from a list of n dimensional cartesian points.
11
12        Required Arguments:
13
14        - `points`
15            - Type: list of tuples
16            - What: A list of n dimensional cartesian points to build the KDTree from
17
18        Returns:
19
20        - A KDTree object that can be used to find the closest point to a given point.
21        """
22        self.tree = kdtree(points, depth=0, axis_count=len(points[0]))

Function:

  • Build a KDTree from a list of n dimensional cartesian points.

Required Arguments:

  • points
    • Type: list of tuples
    • What: A list of n dimensional cartesian points to build the KDTree from

Returns:

  • A KDTree object that can be used to find the closest point to a given point.
tree
def closest_point(self, point): 
24    def closest_point(self, point):
25        """
26        Function:
27
28        - Find the closest point in the KDTree to a given point.
29
30        Required Arguments:
31
32        - `point`
33            - Type: tuple
34            - What: The point to find the closest point to
35
36        Returns:
37
38        - The closest point found in the KDTree to the given point.
39        """
40        return closest_point(self.tree, point)[0]

Function:

  • Find the closest point in the KDTree to a given point.

Required Arguments:

  • point
    • Type: tuple
    • What: The point to find the closest point to

Returns:

  • The closest point found in the KDTree to the given point.