Numpy MaskedArray.all()函数| Python

在许多情况下，数据集可能不完整或因存在无效数据而受到污染。例如，传感器可能无法记录数据，或记录无效值。 numpy.ma模块通过引入掩码数组提供了一种解决此问题的便捷方法。掩码数组是可能缺少或无效条目的数组。

如果所有元素的计算结果为 True， numpy.MaskedArray.all()函数将返回 True。

Syntax : MaskedArray.all(axis=None, out=None, keepdims)

Parameters:
axis : [int or None] Axis or axes along which a logical AND reduction is performed.
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 : [ndarray, bool] A new boolean or array is returned unless out is specified, in which case a reference to out is returned.

代码#1：

# Python program explaining
# numpy.MaskedArray.all() 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])
print ("Input array : ", in_arr)
  
  
# applying MaskedArray.all methods to input array
out_arr = in_arr.all()
print ("Output array : ", out_arr)
  
  
# Now we are creating a masked array by 
# making third entry as invalid. 
mask_arr = ma.masked_array(in_arr, mask =[0, 0, 1, 0, 0])
print ("Masked array : ", mask_arr)
  
# applying MaskedArray.all methods to mask array
out_arr = mask_arr.all()
print ("Output array : ", out_arr)

输出：

Input array :  [ 1  2  3 -1  5]
Output array :  True
Masked array :  [1 2 -- -1 5]
Output array :  True

代码#2：

# Python program explaining
# numpy.MaskedArray.all() 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])
print ("Input array : ", in_arr)
  
# Now we are creating a masked array by 
# making all entry as invalid. 
mask_arr = ma.masked_array(in_arr, mask =[1, 1, 1, 1, 1])
print ("Masked array : ", mask_arr)
  
# applying MaskedArray.all methods to mask array
out_arr = mask_arr.all()
print ("Output array : ", out_arr)

输出：

Input array :  [ 1  2  3 -1  5]
Masked array :  [-- -- -- -- --]
Output array :  --