Numpy에서 일반적으로 사용되는 기능에 대한 빠른 소개

import numpy as np

array1 = np.array([1, 2, 3, 4, 5])  # 将列表转换为数组
print(array1)

array2 = np.arange(1, 10, 2)  # 生成等差数列，起始值为1，结束值为10，步长为2
print(array2)

array3 = np.random.random((2, 3))  # 生成2行3列的随机数数组
print(array3)

import numpy as np

array1 = np.array([1, 2, 3, 4, 5])
array2 = np.array([6, 7, 8, 9, 10])

array_sum = np.add(array1, array2)  # 数组相加
print(array_sum)

array_diff = np.subtract(array1, array2)  # 数组相减
print(array_diff)

array_mult = np.multiply(array1, array2)  # 数组相乘
print(array_mult)

array_div = np.divide(array1, array2)  # 数组相除
print(array_div)

array_exp = np.exp(array1)  # 数组指数
print(array_exp)

array_log = np.log(array1)  # 数组对数
print(array_log)

array_sin = np.sin(array1)  # 数组正弦值
print(array_sin)

import numpy as np

array1 = np.array([[1, 2, 3], [4, 5, 6]])
array2 = np.array([[7, 8, 9], [10, 11, 12]])

array_transpose = np.transpose(array1)  # 数组转置
print(array_transpose)

array_concatenate = np.concatenate((array1, array2), axis=0)  # 数组垂直拼接
print(array_concatenate)

array_slice = array1[0:2, 1:3]  # 数组切片
print(array_slice)

import numpy as np

array1 = np.array([1, 2, 3, 4, 5])

array_sum = np.sum(array1)  # 数组元素求和
print(array_sum)

array_mean = np.mean(array1)  # 数组元素求平均值
print(array_mean)

array_std = np.std(array1)  # 数组元素求标准差
print(array_std)

import numpy as np

matrix1 = np.array([[1, 2], [3, 4]])
matrix2 = np.array([[5, 6], [7, 8]])

matrix_dot = np.dot(matrix1, matrix2)  # 矩阵相乘
print(matrix_dot)

matrix_inv = np.linalg.inv(matrix1)  # 求矩阵的逆
print(matrix_inv)

matrix_eigen = np.linalg.eig(matrix1)  # 求矩阵的特征值
print(matrix_eigen)