如何使用python从3d中的两个点计算向量

Question

我正在尝试在原点（0,0,0）到特定点之间生成向量。如何将数学转换为代码？

编辑：

抱歉，不清楚。

假设我有一个位于3d坐标系中的点o（0,0,0）和点p（3,6,8）。

如何计算从点o到点p的方向的向量？

Answer 1

您的问题尚不清楚，但这是一个如何绘制一些3D向量的示例

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

vectors=np.array( [ [0,0,1,1,-2,0], [0,0,2,1,1,0],[0,0,3,2,1,0],[0,0,4,0.5,0.7,0]]) 
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
for vector in vectors:
    v = np.array([vector[3],vector[4],vector[5]])
    vlength=np.linalg.norm(v)
    ax.quiver(vector[0],vector[1],vector[2],vector[3],vector[4],vector[5],
              pivot='tail',length=vlength,arrow_length_ratio=0.3/vlength)
ax.set_xlim([-4,4])
ax.set_ylim([-4,4])
ax.set_zlim([0,4])
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_zlabel('z')
plt.show()

Answer 2

我和其他人一样不清楚。据我了解，您想要的只是一个向量，它将把您从一个点带到另一个点。这只是基本的向量加法，非常简单。我做到了，因此它适用于任何尺寸，而不仅仅是第三个尺寸。

def multiDimenDist(point1,point2):
   #find the difference between the two points, its really the same as below
   deltaVals = [point2[dimension]-point1[dimension] for dimension in range(len(point1))]
   runningSquared = 0
   #because the pythagarom theorm works for any dimension we can just use that
   for coOrd in deltaVals:
       runningSquared += coOrd**2
   return runningSquared**(1/2)
def findVec(point1,point2,unitSphere = False):
  #setting unitSphere to True will make the vector scaled down to a sphere with a radius one, instead of it's orginal length
  finalVector = [0 for coOrd in point1]
  for dimension, coOrd in enumerate(point1):
      #finding total differnce for that co-ordinate(x,y,z...)
      deltaCoOrd = point2[dimension]-coOrd
      #adding total difference
      finalVector[dimension] = deltaCoOrd
  if unitSphere:
      totalDist = multiDimenDist(point1,point2)
      unitVector =[]
      for dimen in finalVector:
          unitVector.append( dimen/totalDist)
      return unitVector
  else:
      return finalVector

编辑，忘记了用法：

 vector = findVec([0,0,0],[3,6,8])# you can also set unitCircle to True
 >>[3,6,8]