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法学返回NumPy中掩码数组的视图形式的底层数据
要返回底层数据，作为掩码数组的视图，请在Python NumPy中使用**ma.MaskedArray.data**。
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数量：
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))
确定输入是否为掩码数组的实例：
print("Whether input is an instance of masked array?",ma.isMaskedArray(arr))
要返回底层数据，作为掩码数组的视图，请使用ma.MaskedArray.data：
print("Result...",arr.data)
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)) # Determine whether input is an instance of masked array print("Whether input is an instance of masked array?",ma.isMaskedArray(arr)) # To return the underlying data, as a view of the masked array, use the ma.MaskedArray.data in Python Numpy print("Result...",arr.data)
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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 is an instance of masked array? True Result... [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11] [12 13 14 15]]
更新于：2022年2月21日
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