在 Numpy 中计算沿着轴 0 的掩码元素数量


若要统计特定轴上掩码元素的数量,请使用ma.MaskedArray.count_masked()方法。 轴 0 使用“axis”参数设置。 该方法返回掩码元素总数(axis=None)或给定轴的每个切片的掩码元素数。

axis 参数是在其上进行计数的轴。 如果是 None(默认值),则使用数组的扁平版本。

步骤

首先,导入需要的库 −

import numpy as np
import numpy.ma as ma

使用 numpy.arange() 方法创建一个包含 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) print("
Our Array type...
", arr.dtype)

获取数组的形状 −

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

获取数组的元素数量 −

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

若要统计特定轴上掩码元素的数量,请使用 ma.MaskedArray.count_masked() 方法。 轴使用“axis”参数设置

print("
Result (number of masked elements)...
",ma.count_masked(arr, axis = 0))

示例

# Python ma.MaskedArray - Count the number of masked elements along axis 0 to count

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 = 0))

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 3 2 1]

更新于: 03-Feb-2022

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