NumPy中掩盖大于给定值的数组元素


要掩盖大于给定值的数组,请使用Python NumPy中的numpy.ma.masked_greater()方法。此函数是masked_where的快捷方式,条件为(x > value)。

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),要么是布尔型数组,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.array()方法创建一个包含整型元素的数组:

arr = np.array([[83, 55, 91], [93, 33, 39], [73, 93, 51], [93, 45, 67]])
print("Array...
", arr)

获取数组的类型:

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 Array Shape...
",arr.shape)

获取数组的元素个数:

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

要掩盖大于给定值的数组,请使用numpy.ma.masked_greater()方法。这里,我们将掩盖大于90值的数组:

print("
Result...
",np.ma.masked_greater(arr, 90))

示例

import numpy as np
import numpy.ma as ma

# Create an array with int elements using the numpy.array() method
arr = np.array([[83, 55, 91], [93, 33, 39], [73, 93, 51], [93, 45, 67]])
print("Array...
", arr) # Get the type pf array print("
Array type...
", arr.dtype) # Get the dimensions of the Array print("
Array Dimensions...
",arr.ndim) # Get the shape of the Array print("
Our Array Shape...
",arr.shape) # Get the number of elements of the Array print("
Number of Elements in the Array...
",arr.size) # To mask an array where greater than a given value, use the numpy.ma.masked_greater() method in Python Numpy # Here, we will mask the array greater than value 90 print("
Result...
",np.ma.masked_greater(arr, 90))

输出

Array...
[[83 55 91]
[93 33 39]
[73 93 51]
[93 45 67]]

Array type...
int64

Array Dimensions...
2

Our Array Shape...
(4, 3)

Number of Elements in the Array...
12

Result...
[[83 55 --]
[-- 33 39]
[73 -- 51]
[-- 45 67]]

更新于:2022年2月4日

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