Return the multiple vector cross product of two vectors and change the orientation of the result in Python

To compute the cross product of two vectors, use the numpy.cross() method in Python Numpy. The method returns c, the Vector cross product(s). The 1st parameter is a, the components of the first vector(s). The 2nd parameter is b, the components of the second vector(s). The 3rd parameter is axisa, the axis of a that defines the vector(s). By default, the last axis. The 4th parameter is axisb, the axis of b that defines the vector(s). By default, the last axis.

The 5th parameter is axisc, the axis of c containing the cross product vector(s). Ignored if both input vectors have dimension 2, as the return is scalar. By default, the last axis. The 6th parameter is the axis, if defined, the axis of a, b and c that defines the vector(s) and cross product(s). Overrides axisa, axisb and axisc.

Steps

At first, import the required libraries −

import numpy as np

Creating two vectors. We have inserted elements of int type −

arr1 = np.array([[5,10,15], [30,35,40]])
arr2 = np.array([[30,35,40], [5,10,15]])

Display the vectors −

print("Vector 1...\n", arr1)
print("\nVector 2...\n", arr2)

To compute the cross product of two vectors, use the numpy.cross() method in Python Numpy. The method returns c, the Vector cross product(s) −

print("\nResult...\n",np.cross(arr1, arr2, axisc=0))

Example

import numpy as np

# Creating two vectors
# We have inserted elements of int type
arr1 = np.array([[5,10,15], [30,35,40]])
arr2 = np.array([[30,35,40], [5,10,15]])

# Display the vectors
print("Vector 1...\n", arr1)
print("\nVector 2...\n", arr2)

# To compute the cross product of two vectors, use the numpy.cross() method in Python Numpy
print("\nResult...\n",np.cross(arr1, arr2, axisc=0))

Output

Vector 1...
[[ 5 10 15]
[30 35 40]]

Vector 2...
[[30 35 40]
[ 5 10 15]]

Result...
[[-125 125]
[ 250 -250]
[-125 125]]