在NumPy中返回掩码数组的掩码或全为False的布尔数组


要返回掩码数组的掩码或全为False的布尔数组,请在Python NumPy中使用**ma.getmaskarray()**方法。如果arr是MaskedArray且掩码不是nomask,则返回arr的掩码作为ndarray;否则,返回与arr形状相同的全为False的布尔数组。

掩码数组是标准numpy.ndarray和掩码的组合。掩码可以是nomask(表示关联数组中没有无效值),也可以是布尔数组,用于确定关联数组中每个元素的值是否有效。

步骤

首先,导入所需的库:

import numpy as np
import numpy.ma as ma

使用numpy.arange()方法创建一个包含整型元素的4x4数组:

arr = np.arange(16).reshape((4,4))
print("Array...
", arr) print("
Array type...
", arr.dtype)

获取数组的维度:

print("
Array Dimensions...
",arr.ndim)

获取数组的形状:

print("
Our Masked Array Shape...
",arr.shape)

获取数组的元素个数:

print("
Elements in the Masked Array...
",arr.size)

创建一个掩码数组:

arr = ma.array(arr)

统计沿特定轴的掩码元素个数:

print("
The number of masked elements...
",ma.count_masked(arr))

要返回掩码数组的掩码或全为False的布尔数组,请在Python NumPy中使用ma.getmaskarray()方法:

print("
Result (mask of a masked array)...
",ma.getmaskarray(arr))

示例

import numpy as np
import numpy.ma as ma

# Creating a 4x4 array with int elements using the numpy.arange() method
arr = np.arange(16).reshape((4,4))
print("Array...
", arr) print("
Array type...
", arr.dtype) # Get the dimensions of the Array print("
Array Dimensions...
",arr.ndim) print("
Our Array type...
", arr.dtype) # Get the shape of the Array print("
Our Masked Array Shape...
",arr.shape) # Get the number of elements of the Array print("
Elements in the Masked Array...
",arr.size) # Create a masked array arr = ma.array(arr) # Count the number of masked elements along specific axis print("
The number of masked elements...
",ma.count_masked(arr)) # To return the mask of a masked array, or full boolean array of False, use the ma.getmaskarray() method in Python Numpy print("
Result (mask of a masked array)...
",ma.getmaskarray(arr))

输出

Array...
[[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]
[12 13 14 15]]

Array type...
int64

Array Dimensions...
2

Our Array type...
int64

Our Masked Array Shape...
(4, 4)

Elements in the Masked Array...
16

The number of masked elements...
0

Result (mask of a masked array)...
[[False False False False]
[False False False False]
[False False False False]
[False False False False]]

更新于:2022年2月21日

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