Numpy MaskedArray.prod()函数| Python

numpy.MaskedArray.prod()函数用于计算数组元素在给定轴上的乘积。这里掩码元素在内部设置为 1 以进行计算。

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

Parameters:

arr : [ ndarray ] Input masked array.
axis :[ int, optional] Axis along which the product is computed. The default (None) is to compute the product over the flattened array.
dtype : [dtype, optional] Type of the returned array, as well as of the accumulator in which the elements are multiplied.
out : [ndarray, optional] A location into which the result is stored.
  -> If provided, it must have a shape that the inputs broadcast to.
  -> If not provided or None, a freshly-allocated array is returned.
keepdims :[ bool, optional] If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.

Return : [product_along_axis, ndarray] A new array holding the result is returned unless out is specified, in which case a reference to out is returned.

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]