在K-D Tree中对于“the nearest neighbor query”的定义出现问题

Question

在对K-D Tree 类的编写的时候定义the nearest neighbor query时发生错误

问题显示“缩进”出现问题

尝试调整缩进但似乎出现了更多的问题

def nearest_neighbor(self, point: Point) -> Point:
        closest = None
        depth = 0
        return self._nearest_neighbor(point, self._root, closest, depth)

    def _nearest_neighbor(self, point, node, closest, depth):
       if node is None:
            return closest
       if closest is None or self.distance(point, node.location) < self.distance(point, closest):
           closest = node.location
        axis = depth % 2
        if point[axis] < node.location[axis]:
           closest = self._nearest_neighbor(point, node.left, closest, depth+1)
        else:
            closest = self._nearest_neighbor(point, node.right, closest, depth+1)
        return closest

    def distance(self, p1, p2):
        return ((p1.x - p2.x) ** 2 + (p1.y - p2.y) ** 2) ** 0.5

def range_test():
    points = [Point(7, 2), Point(5, 4), Point(9, 6), Point(4, 7), Point(8, 1), Point(2, 3)]
    kd = KDTree()
    kd.insert(points)
    result = kd.range(Rectangle(Point(0, 0), Point(6, 6)))
    assert sorted(result) == sorted([Point(2, 3), Point(5, 4)])

Answer 1

你的代码是有从网页复制的吗？可能是tab和空格混用导致缩进出现了问题
试试这个

def nearest_neighbor(self, point: Point) -> Point:
    closest = None
    depth = 0
    return self._nearest_neighbor(point, self._root, closest, depth)
 
def _nearest_neighbor(self, point, node, closest, depth):
    if node is None:
        return closest
    if closest is None or self.distance(point, node.location) < self.distance(point, closest):
        closest = node.location
    axis = depth % 2
    if point[axis] < node.location[axis]:
        closest = self._nearest_neighbor(point, node.left, closest, depth+1)
    else:
        closest = self._nearest_neighbor(point, node.right, closest, depth+1)
    return closest

def distance(self, p1, p2):
    return ((p1.x - p2.x) ** 2 + (p1.y - p2.y) ** 2) ** 0.5
 
def range_test():
    points = [Point(7, 2), Point(5, 4), Point(9, 6), Point(4, 7), Point(8, 1), Point(2, 3)]
    kd = KDTree()
    kd.insert(points)
    result = kd.range(Rectangle(Point(0, 0), Point(6, 6)))
    assert sorted(result) == sorted([Point(2, 3), Point(5, 4)])