Python Vector3 3D向量类

# -*- coding: UTF-8 -*-
'''
Vector3 3D向量类
关于操作符重载 http://docs.python.org/reference/datamodel.html
'''

import math

class Vector3():

    def __init__(self,x,y,z):
        self.x = x
        self.y = y
        self.z = z

    #置为零向量
    def zero():
        self.x = 0
        self.y = 0
        self.z = 0

    #"=" 赋值不支持重载

    #重载 "==" 操作符
    def __eq__(self, other):
        return self.x == other.x and self.y == other.y and self.z == other.z

    #重载 "!=" 操作符     
    def __ne__(self, other):
        return self.x != other.x or self.y != other.y or self.z != other.z

    #重载一元 "-" 操作符
    def __neg__(self):
        return Vector3(-self.x, -self.y, -self.z)

    #重载 "+" 操作符
    def __add__(self, other):
        return Vector3(self.x + other.x, self.y + other.y, self.z + other.z)

    #重载 "-" 操作符
    def __sub__(self, other):
        return Vector3(self.x - other.x, self.y - other.y, self.z - other.z)

    #重载 "*" 操作符
    def __mul__(self, a):
        return Vector3(self.x * a, self.y * a, self.z * a)
    
    #重载 "/" 操作符
    def __div__(self, a):
        if(a != 0):
            return Vector3(self.x / a, self.y / a, self.z / a)
        else:
            return None

    #重载 "+=" 操作符
    def __iadd__(self, other):
        self.x += other.x
        self.y += other.y
        self.z += other.z
        return self

    #重载 "-=" 操作符
    def __isub__(self, other):
        self.x -= other.x
        self.y -= other.y
        self.z -= other.z
        return self

    #重载 "*=" 操作符
    def __imul__(self, a):
        self.x *= a
        self.y *= a
        self.z *= a
        return self
    
    #重载 "/=" 操作符
    def __idiv__(self, a):
        if(a != 0):
            self.x /= a
            self.y /= a
            self.z /= a
        return self

    #向量标准化
    def normalize(self):
        magSq = self.x * self.x + self.y * self.y + self.z * self.z
        if(magSq >0):
            oneOverMag = 1.0/ math.sqrt(magSq)
            self.x *= oneOverMag
            self.y *= oneOverMag
            self.z *= oneOverMag
    
    #向量求模
    def vectorMag(self):
        return math.sqrt(self.x * self.x + self.y * self.y + self.z * self.z)

    #向量显示
    def toString(self):       
        print "{x:" + str(self.x)+ ",y:" + str(self.y) + ",z:" + str(self.z)+"}"
    

#向量点乘
def dotProduct(va, vb):
    return va.x * vb.x + va.y * vb.y + va.z * vb.z


#向量叉乘
def crossProduct(va, vb):
    x = va.y * vb.z - va.z * vb.y
    y = va.z * vb.x - va.x * vb.z
    z = va.x * vb.y - va.y * vb.x
    return Vector3(x,y,z)
    

#计算两点间的距离
def distance(va, vb):
    dx = va.x - vb.x
    dy = va.y - vb.y
    dz = va.z - vb.z
    return math.sqrt(dx * dx + dy * dy + dz * dz)

 

 

测试代码

v1 = Vector3(1,2,3)
v2 = Vector3(2,3,4)
v3 = v1 / 2.0
v3.toString()
v4 = -v3
v4.toString()
v4.normalize()
v4.toString()
print v4.vectorMag()

v5 = Vector3(0,0,0)
v6 = Vector3(2,2,2)
print distance(v5,v6)