Python Numpy MaskedArray.prod()函数

numpy.MaskedArray.prod()函数用于计算数组元素在给定轴上的乘积。这里的掩码元素在内部被设置为1，用于计算。

语法: numpy.ma.prod(self, axis=None, dtype=None, out=None, keepdims=False)

参数:

arr : [ ndarray ] 输入屏蔽的数组。
axis : [ int, optional] 计算积的轴。默认情况下（无）是在扁平化的数组上计算乘积。
dtype : [dtype, optional] 返回数组的类型，以及与元素相乘的累积器的类型。
out : [ndarray, optional] 一个储存结果的位置。
-> 如果提供，它必须有一个输入广播到的形状。
-> 如果没有提供或没有，将返回一个新分配的数组。
keepdims : [ bool, optional] 如果设置为True，被缩小的轴将作为尺寸为1的尺寸留在结果中。有了这个选项，结果将正确地针对输入阵列进行广播。

返回 : [product_along_axis, ndarray] 返回一个保存结果的新数组，除非指定out，在这种情况下，返回对out的引用。

代码#1：

# Python program explaining
# numpy.MaskedArray.prod() method 
    
# importing numpy as geek  
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma 
    
# creating input array  
in_arr = geek.array([[1, 2], [ 3, -1], [ 5, -3]])
print ("Input array : ", in_arr) 
    
# Now we are creating a masked array. 
# by making  entry as invalid.  
mask_arr = ma.masked_array(in_arr, mask =[[1, 0], [ 1, 0], [ 0, 0]]) 
print ("Masked array : ", mask_arr) 
    
# applying MaskedArray.prod    
# methods to masked array
out_arr = ma.prod(mask_arr) 
print ("product of masked array along default axis : ", out_arr)

输出:

Input array :  [[ 1  2]
 [ 3 -1]
 [ 5 -3]]
Masked array :  [[-- 2]
 [-- -1]
 [5 -3]]
product of masked array along default axis :  30

代码#2：

# Python program explaining
# numpy.MaskedArray.prod() method 
     
# importing numpy as geek  
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma 
     
# creating input array 
in_arr = geek.array([[1, 0, 3], [ 4, 1, 6]]) 
print ("Input array : ", in_arr)
      
# Now we are creating a masked array. 
# by making one entry as invalid.  
mask_arr = ma.masked_array(in_arr, mask =[[ 0, 0, 0], [ 0, 0, 1]]) 
print ("Masked array : ", mask_arr) 
     
# applying MaskedArray.prod methods 
# to masked array
out_arr1 = ma.prod(mask_arr, axis = 0) 
print ("product of masked array along 0 axis : ", out_arr1)
  
out_arr2 = ma.prod(mask_arr, axis = 1) 
print ("product of masked array along 1 axis : ", out_arr2)

输出:

Input array :  [[1 0 3]  

 [4 1 6]]  

Masked array :  [[1 0 3]  

 [4 1 --]]  

product of masked array along 0 axis :  [4 0 3]  

product of masked array along 1 axis :  [0 4]