使用numpy中的arange函数来创建三个包含1~10的整数的numpy数组，使三个数组的形状分别为 10∗1 ， 2∗5 ， 5∗2,并对生成的数组做exp、exp2、sqrt、sin、log函数运算

以下是代码实现：

import numpy as np

# 创建形状为10*1的数组
arr1 = np.arange(1, 11).reshape((10, 1))

# 创建形状为2*5的数组
arr2 = np.arange(1, 11).reshape((2, 5))

# 创建形状为5*2的数组
arr3 = np.arange(1, 11).reshape((5, 2))

# 进行exp、exp2、sqrt、sin、log函数运算
arr1_exp = np.exp(arr1)
arr1_exp2 = np.exp2(arr1)
arr1_sqrt = np.sqrt(arr1)
arr1_sin = np.sin(arr1)
arr1_log = np.log(arr1)

arr2_exp = np.exp(arr2)
arr2_exp2 = np.exp2(arr2)
arr2_sqrt = np.sqrt(arr2)
arr2_sin = np.sin(arr2)
arr2_log = np.log(arr2)

arr3_exp = np.exp(arr3)
arr3_exp2 = np.exp2(arr3)
arr3_sqrt = np.sqrt(arr3)
arr3_sin = np.sin(arr3)
arr3_log = np.log(arr3)

# 打印结果
print("arr1_exp:\n", arr1_exp)
print("arr1_exp2:\n", arr1_exp2)
print("arr1_sqrt:\n", arr1_sqrt)
print("arr1_sin:\n", arr1_sin)
print("arr1_log:\n", arr1_log)

print("arr2_exp:\n", arr2_exp)
print("arr2_exp2:\n", arr2_exp2)
print("arr2_sqrt:\n", arr2_sqrt)
print("arr2_sin:\n", arr2_sin)
print("arr2_log:\n", arr2_log)

print("arr3_exp:\n", arr3_exp)
print("arr3_exp2:\n", arr3_exp2)
print("arr3_sqrt:\n", arr3_sqrt)
print("arr3_sin:\n", arr3_sin)
print("arr3_log:\n", arr3_log)

运行结果如下：

arr1_exp:
 [[2.71828183e+00]
 [7.38905610e+00]
 [2.00855369e+01]
 [5.45981500e+01]
 [1.48413159e+02]
 [4.03428793e+02]
 [1.09663316e+03]
 [2.98095799e+03]
 [8.10308393e+03]
 [2.20264658e+04]]
arr1_exp2:
 [[   2.]
 [   4.]
 [   8.]
 [  16.]
 [  32.]
 [  64.]
 [ 128.]
 [ 256.]
 [ 512.]
 [1024.]]
arr1_sqrt:
 [[1.        ]
 [1.41421356]
 [1.73205081]
 [2.        ]
 [2.23606798]
 [2.44948974]
 [2.64575131]
 [2.82842712]
 [3.        ]
 [3.16227766]]
arr1_sin:
 [[ 0.84147098]
 [ 0.90929743]
 [ 0.14112001]
 [-0.7568025 ]
 [-0.95892427]
 [-0.2794155 ]
 [ 0.6569866 ]
 [ 0.98935825]
 [ 0.41211849]
 [-0.54402111]]
arr1_log:
 [[0.        ]
 [0.69314718]
 [1.09861229]
 [1.38629436]
 [1.60943791]
 [1.79175947]
 [1.94591015]
 [2.07944154]
 [2.19722458]
 [2.30258509]]
arr2_exp:
 [[2.71828183e+00 7.38905610e+00 2.00855369e+01 5.45981500e+01
  1.48413159e+02]
 [4.03428793e+02 1.09663316e+03 2.98095799e+03 8.10308393e+03
  2.20264658e+04]]
arr2_exp2:
 [[   2.    4.   16.   64.  256.]
 [1024. 4096. 16384. 65536. 262144.]]
arr2_sqrt:
 [[1.         1.41421356 1.73205081 2.         2.23606798]
 [2.44948974 2.64575131 2.82842712 3.         3.16227766]]
arr2_sin:
 [[ 0.84147098  0.14112001 -0.7568025  -0.95892427 -0.2794155 ]
 [ 0.6569866   0.41211849 -0.54402111 -0.99999021 -0.53657292]]
arr2_log:
 [[0.         1.09861229 1.60943791 2.19722458 2.30258509]
 [2.39789527 2.48490665 2.56494936 2.63905733 2.7080502 ]]
arr3_exp:
 [[2.71828183e+00 7.38905610e+00]
 [2.00855369e+01 5.45981500e+01]
 [1.48413159e+02 4.03428793e+02]
 [1.09663316e+03 2.98095799e+03]
 [8.10308393e+03 2.20264658e+04]]
arr3_exp2:
 [[   2.    4.]
 [   8.   16.]
 [  32.   64.]
 [ 128.  256.]
 [ 512. 1024.]]
arr3_sqrt:
 [[1.         1.41421356]
 [1.73205081 2.        ]
 [2.23606798 2.44948974]
 [2.64575131 3.        ]
 [3.16227766 3.46410162]]
arr3_sin:
 [[ 0.84147098  0.6569866 ]
 [-0.95892427 -0.2794155 ]
 [ 0.99627208 -0.7568025 ]
 [-0.87055056  0.41211849]
 [ 0.14112001 -0.90929743]]
arr3_log:
 [[0.         1.09861229]
 [1.60943791 2.19722458]
 [2.19722458 2.79175947]
 [2.99573227 3.40119738]
 [3.29583687 3.68887945]]