geokdtree.kdtree 

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

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): 
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]

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.