15.Numpy之点乘、算术运算、切片、遍历和下标取值

# Numpy之 点乘、算术运算、切片、遍历和下标取值 import numpy as np a = np.arange(4) b = np.arange(4, 11, 2) print(a) print(b) a_plus_b = a + b print(a_plus_b) a_multiplication_b = a * b print(a_multiplication_b) boolean_arr = b < 7 print(boolean_arr) # 对数组a中所有元素加一 a += 1 print(a) aa = np.array([[1, 2], [3, 4]]) bb = np.array([[1, 2], [3, 4]]) # 对应元素相乘 print(aa * bb) # 矩阵乘法 print(aa.dot(bb)) random_arr = np.random.random((2, 3)) print(random_arr) sum_random = random_arr.sum() print('sum of array: ', sum_random) print('minimum value of array: ', random_arr.min()) print('maximum value of array: ', random_arr.max()) print(random_arr.min(axis=0)) print(random_arr.min(axis=1)) # 一维数组的切片、根据下标取值和用迭代器遍历功能跟列表等序列相同 print(a) # [1 2 3 4] print(a[1:3]) # [2 3] print(a[-1]) # 4 for x in a: print(x) # output: # 1 # 2 # 3 # 4 # 多维数组的切片、根据下标取值和用迭代器遍历功能 b = np.array([[1, 2, 3, 4, 5], [11, 12, 13, 14, 15], [21, 22, 23, 24, 25], [31, 32, 33, 34, 35], [41, 42, 43, 44, 45]]) print('traversal array and treat it as one dimensional array:') for x in b: print(x, end=",") print() # output: # [1 2 3 4 5],[11 12 13 14 15],[21 22 23 24 25],[31 32 33 34 35],[41 42 43 44 45], print('traversal array for every element:') for x in b: for y in x: print(y, end=" ") print() # output: # 1 2 3 4 5 11 12 13 14 15 21 22 23 24 25 31 32 33 34 35 41 42 43 44 45 print('Slice the multidimensional array 1:') print(b[:, 1]) print('Slice the multidimensional array 2:') print(b[1:3, :]) # output: # Slice the multidimensional array 1: # [ 2 12 22 32 42] # Slice the multidimensional array 2: # [[11 12 13 14 15] # [21 22 23 24 25]] # ...的用法 c = np.array([[[1, 2, 3], [11, 12, 13]], [[4, 5, 6], [14, 15, 16]], [[7, 8, 9], [17, 18, 19]]]) print(c[1, ...]) # 相当于c[1,:,:] # output: # [[ 4 5 6] # [14 15 16]] print(c[..., 2]) # 等价于c[:,:,2] # output: # [[ 3 13] # [ 6 16] # [ 9 19]]

转载于:https://www.cnblogs.com/wjc920/p/9256149.html