八叉树体素网格可视化python代码

以下是一个简单的八叉树体素网格可视化的 Python 代码示例：

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d.art3d import Poly3DCollection

class Octree:
    def __init__(self, min_point, max_point, depth=0, max_depth=5):
        self.min_point = min_point
        self.max_point = max_point
        self.depth = depth
        self.max_depth = max_depth
        self.children = [None]*8
        self.is_leaf = True
        self.points = []

    def insert(self, point):
        if self.depth == self.max_depth:
            self.points.append(point)
            return

        idx = self.get_octant_idx(point)

        if self.children[idx] is None:
            self.children[idx] = self.create_octant(idx)

        self.is_leaf = False
        self.children[idx].insert(point)

    def create_octant(self, idx):
        x, y, z = self.get_octant_center(idx)
        min_point = np.array([x, y, z])
        max_point = np.array([self.max_point[0] if idx & 4 else x,
                              self.max_point[1] if idx & 2 else y,
                              self.max_point[2] if idx & 1 else z])
        return Octree(min_point, max_point, self.depth+1, self.max_depth)

    def get_octant_center(self, idx):
        x = (self.min_point[0] + self.max_point[0])/2.0
        y = (self.min_point[1] + self.max_point[1])/2.0
        z = (self.min_point[2] + self.max_point[2])/2.0

        if idx & 4:
            x = (x + self.max_point[0])/2.0
        else:
            x = (x + self.min_point[0])/2.0

        if idx & 2:
            y = (y + self.max_point[1])/2.0
        else:
            y = (y + self.min_point[1])/2.0

        if idx & 1:
            z = (z + self.max_point[2])/2.0
        else:
            z = (z + self.min_point[2])/2.0

        return x, y, z

    def get_octant_idx(self, point):
        idx = 0
        if point[0] > (self.min_point[0] + self.max_point[0])/2.0:
            idx |= 4
        if point[1] > (self.min_point[1] + self.max_point[1])/2.0:
            idx |= 2
        if point[2] > (self.min_point[2] + self.max_point[2])/2.0:
            idx |= 1
        return idx

    def get_leaf_nodes(self):
        if self.is_leaf:
            return [self]

        leaf_nodes = []
        for child in self.children:
            if child is not None:
                leaf_nodes.extend(child.get_leaf_nodes())
        return leaf_nodes

def plot_cube(cube_definition, ax):
    x = [cube_definition[0][0], cube_definition[1][0], cube_definition[2][0], cube_definition[3][0],
         cube_definition[0][0], cube_definition[4][0], cube_definition[5][0], cube_definition[1][0]]
    y = [cube_definition[0][1], cube_definition[1][1], cube_definition[2][1], cube_definition[3][1],
         cube_definition[0][1], cube_definition[4][1], cube_definition[5][1], cube_definition[1][1]]
    z = [cube_definition[0][2], cube_definition[1][2], cube_definition[2][2], cube_definition[3][2],
         cube_definition[0][2], cube_definition[4][2], cube_definition[5][2], cube_definition[1][2]]
    verts = [list(zip(x, y, z))]
    ax.add_collection3d(Poly3DCollection(verts, facecolors='blue', linewidths=1, edgecolors='r', alpha=.25))

def plot_octree(node, ax):
    if node.is_leaf:
        return

    for child in node.children:
        if child is not None:
            plot_cube([(child.min_point[0], child.min_point[1], child.min_point[2]),
                       (child.max_point[0], child.min_point[1], child.min_point[2]),
                       (child.max_point[0], child.max_point[1], child.min_point[2]),
                       (child.min_point[0], child.max_point[1], child.min_point[2]),
                       (child.min_point[0], child.min_point[1], child.max_point[2]),
                       (child.max_point[0], child.min_point[1], child.max_point[2]),
                       (child.max_point[0], child.max_point[1], child.max_point[2]),
                       (child.min_point[0], child.max_point[1], child.max_point[2])], ax)

        plot_octree(child, ax)

def main():
    points = np.random.rand(100, 3)

    min_point = np.min(points, axis=0)
    max_point = np.max(points, axis=0)
    octree = Octree(min_point, max_point, max_depth=5)

    for point in points:
        octree.insert(point)

    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
    plot_octree(octree, ax)
    ax.scatter(points[:,0], points[:,1], points[:,2], c='r', marker='o')
    ax.set_xlabel('X Label')
    ax.set_ylabel('Y Label')
    ax.set_zlabel('Z Label')
    plt.show()

if __name__ == '__main__':
    main()

这个代码使用 matplotlib 库绘制了八叉树体素网格，并在其中添加了随机生成的点。您可以根据需要调整点的数量和八叉树的深度。