# python中的numpy.sum()用法详细介绍

2021年3月15日09:00:44 发表评论 2,228 次浏览

numpy.sum(arr, axis, dtype, out):此函数返回指定轴上的数组元素的总和

``````# Python Program illustrating
# numpy.sum() method
import numpy as np

# 1D array
arr = [ 20 , 2 , . 2 , 10 , 4 ]

print ( "\nSum of arr : " , np. sum (arr))

print ( "Sum of arr(uint8) : " , np. sum (arr, dtype = np.uint8))
print ( "Sum of arr(float32) : " , np. sum (arr, dtype = np.float32))

print ( "\nIs np.sum(arr).dtype == np.uint : " , np. sum (arr).dtype = = np.uint)

print ( "Is np.sum(arr).dtype == np.float : " , np. sum (arr).dtype = = np. float )``````

``````Sum of arr :  36.2
Sum of arr(uint8) :  36
Sum of arr(float32) :  36.2

Is np.sum(arr).dtype == np.uint :  False
Is np.sum(arr).dtype == np.uint :  True``````

``````# Python Program illustrating
# numpy.sum() method
import numpy as np

# 2D array
arr = [[ 14 , 17 , 12 , 33 , 44 ], [ 15 , 6 , 27 , 8 , 19 ], [ 23 , 2 , 54 , 1 , 4 , ]]

print ( "\nSum of arr : " , np. sum (arr))

print ( "Sum of arr(uint8) : " , np. sum (arr, dtype = np.uint8))
print ( "Sum of arr(float32) : " , np. sum (arr, dtype = np.float32))

print ( "\nIs np.sum(arr).dtype == np.uint : " , np. sum (arr).dtype = = np.uint)

print ( "Is np.sum(arr).dtype == np.uint : " , np. sum (arr).dtype = = np. float )``````

``````Sum of arr :  279
Sum of arr(uint8) :  23
Sum of arr(float32) :  279.0

Is np.sum(arr).dtype == np.uint :  False
Is np.sum(arr).dtype == np.uint :  False``````

``````# Python Program illustrating
# numpy.sum() method

import numpy as np

# 2D array
arr = [[ 14 , 17 , 12 , 33 , 44 ], [ 15 , 6 , 27 , 8 , 19 ], [ 23 , 2 , 54 , 1 , 4 , ]]

print ( "\nSum of arr : " , np. sum (arr))
print ( "Sum of arr(axis = 0) : " , np. sum (arr, axis = 0 ))
print ( "Sum of arr(axis = 1) : " , np. sum (arr, axis = 1 ))

print ( "\nSum of arr (keepdimension is True): \n" , np. sum (arr, axis = 1 , keepdims = True ))``````

``````Sum of arr :  279
Sum of arr(axis = 0) :  [52 25 93 42 67]
Sum of arr(axis = 1) :  [120  75  84]

Sum of arr (keepdimension is True):
[[120]
[ 75]
[ 84]]``````