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法学沿特定轴计算被掩码元素的数量
要计算沿特定轴的被掩码元素的数量，请使用**ma.MaskedArray.count_masked()** 方法。“**axis**”参数用于设置轴。该方法返回被掩码元素的总数（axis=None）或沿给定轴的每个切片的被掩码元素的数量。
axis参数是沿其进行计数的轴。如果为None（默认值），则使用数组的扁平化版本。
步骤
首先，导入所需的库：
import numpy as np import numpy.ma as ma
使用numpy.arange()方法创建一个具有int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
要计算沿特定轴的被掩码元素的数量，请使用ma.MaskedArray.count_masked()方法。“axis”参数用于设置轴。
print("
Result (number of masked elements)...
",ma.count_masked(arr, axis = 1))
示例
# Python ma.MaskedArray - Count the number of masked elements along specific axis
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
# To count the number of masked elements along specific axis, use the ma.MaskedArray.count_masked() method
# The axis is set using the "axis" parameter
print("
Result (number of masked elements)...
",ma.count_masked(arr, axis = 1))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 Result (number of masked elements)... [1 1 2 3]
更新于：2022年2月3日
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