import numpy as np
vector = np.array([1])
vector2 = np.array([0])
(vector - vector2)^2
answer:
array([3])
Can someone explain what does [3] means?
Why the square of the difference of these two arrays is 3?
Viewed 35
2 Answers
When you create arrays with int objects, the dtype will be an integer type. That means that bit twiddling is supported.
^ is the bitwise XOR operator in python. ** is exponentiation. Numpy implements both operations elwment-wise, as expected.
1 ^ 2 -> 0001 XOR 0010 -> 0011 -> 3
That isn't a square. ^ is the xor (eXclusive OR) operator. Squaring a variable would be done with the ** operator (i.e., (vector-vector2)**2).
vector - vector2 returns array([1]). When you xor it is a scalar, each element (or here - the single element) is xored individually, and 1 xor 2 is 3.
Related