numpy中的向量操作

import numpy as np

if __name__ == ‘__main__‘:
    print(np.__version__)

    vec = np.array([1, 2, 3])
    print(vec)
    vec[0] = ‘111‘
    print(vec)  # [111   2   3]
    # vec[0] = ‘a‘
    # print(vec)  # ValueError: invalid literal for int() with base 10: ‘a‘

    print(np.zeros(3))  # [0. 0. 0.]
    print(np.ones(3))  # [1. 1. 1.]
    print(np.full(2, 3))  # [3 3]

    print(vec.size)
    print(len(vec))
    print(vec[0])
    print(vec[-1])
    print(vec[0:])
    print(type(vec))  # <class ‘numpy.ndarray‘>

    vec2 = np.array([1, 2, 3])

    print(vec + vec2)
    print(vec - vec2)
    print(vec * vec2)  # [111   4   9]
    print(2 * vec2)  # [2 4 6]
    print(vec * 2)
    print(np.linalg.norm(vec))  # 模 111.05854312028409
    print(vec / np.linalg.norm(vec))  # 归一化 #[0.99947286 0.01800852 0.02701278]
    print(np.linalg.norm(vec / np.linalg.norm(vec)))  # 1.0
    print(np.zeros(3) / np.linalg.norm(vec))  # [0. 0. 0.]

numpy中的向量操作

原文：https://www.cnblogs.com/fly-book/p/13390657.html