Python 中 NumPy.dot()和' * '运算的区别
原文:https://www . geesforgeks . org/numpy-dot-and-operation-in-python/
在 Python 中，如果我们有两个通常被称为向量的 numpy 数组。“*”运算符和 numpy.dot()对它们的作用不同。了解这一点很重要，尤其是当你处理数据科学或竞争性编程问题时。
“*”运算符的工作原理
”操作在数组元素上执行逐元素乘法。a[i][j]处的元素乘以 b[i][j]。这发生在数组的所有元素上。 例:*
Let the two 2D array are v1 and v2:-
v1 = [[1, 2], [3, 4]]
v2 = [[1, 2], [3, 4]]
Output:
[[1, 4]
[9, 16]]
From below picture it would be clear.
numpy.dot()的工作原理
它带有正规矩阵乘法。如果第一个数组的列数应等于第二个数组的行数，则只检查 numpy.dot()函数，否则会显示错误。 例:
Let the two 2D array are v1 and v2:-
v1=[[1, 2], [3, 4]]
v2=[[1, 2], [3, 4]]
Than numpy.dot(v1, v2) gives output of :-
[[ 7 10]
[15 22]]
例 1:
蟒蛇 3
import numpy as np
# vector v1 of dimension (2, 2)
v1 = np.array([[1, 2], [1, 2]])
# vector v2 of dimension (2, 2)
v2 = np.array([[1, 2], [1, 2]])
print("vector multiplication")
print(np.dot(v1, v2))
print("\nElementwise multiplication of two vector")
print(v1 * v2)
Output :
vector multiplication
[[3 6]
[3 6]]
Elementwise multiplication of two vector
[[1 4]
[1 4]]
例 2:
蟒蛇 3
import numpy as np
v1 = np.array([[1, 2, 3], [1, 2, 3], [1, 2, 3]])
v2 = np.array([[[1, 2, 3], [1, 2, 3], [1, 2, 3]]])
print("vector multiplication")
print(np.dot(v1, v2))
print("\nElementwise multiplication of two vector")
print(v1 * v2)
Output :
vector multiplication
[[ 6 12 18]
[ 6 12 18]
[ 6 12 18]]
Elementwise multiplication of two vector
[[1 4 9]
[1 4 9]
[1 4 9]]
