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法学判断输入是否包含掩码值
要判断输入是否包含掩码值，可以使用Python Numpy中的ma.is_masked()方法。该方法接受任何对象作为输入，但除非输入是包含掩码值的MaskedArray，否则始终返回False。如果数组是包含掩码值的MaskedArray，则返回True；否则返回False。
掩码数组是标准numpy.ndarray和掩码的组合。掩码要么是nomask（表示关联数组的任何值均有效），要么是布尔数组，用于确定关联数组的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数元素的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) arr[0, 1] = ma.masked arr[1, 1] = ma.masked arr[2, 1] = ma.masked arr[2, 2] = ma.masked arr[3, 0] = ma.masked arr[3, 2] = ma.masked arr[3, 3] = ma.masked
沿特定轴计算掩码元素的个数：
print("
The number of masked elements...
",ma.count_masked(arr, axis = 1))
返回掩码数组的掩码：
print("
The mask of a masked array)...
",ma.getmask(arr))返回掩码数组的数据作为ndarray：
print("
Data of a masked array as an ndarray...
",ma.getdata(arr))
要判断输入是否包含掩码值，可以使用Python Numpy中的ma.is_masked()方法：
print("
Whether input has masked values?
",ma.is_masked(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)
arr[0, 1] = ma.masked
arr[1, 1] = ma.masked
arr[2, 1] = ma.masked
arr[2, 2] = ma.masked
arr[3, 0] = ma.masked
arr[3, 2] = ma.masked
arr[3, 3] = ma.masked
# Count the number of masked elements along specific axis
print("
The number of masked elements...
",ma.count_masked(arr, axis = 1))
# Return the mask of a masked array
print("
The mask of a masked array)...
",ma.getmask(arr))
# Return the data of a masked array as an ndarray
print("
Data of a masked array as an ndarray...
",ma.getdata(arr))
# To determine whether input has masked values, use the ma.is_masked() method in Python Numpy
print("
Whether input has masked values?
",ma.is_masked(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... [1 1 2 3] The mask of a masked array)... [[False True False False] [False True False False] [False True True False] [ True False True True]] Data of a masked array as an ndarray... [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11] [12 13 14 15]] Whether input has masked values? True
更新于：2022年2月18日
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