NumPy中使用掩码数组对给定标量值进行左移操作


在Python NumPy中,使用**ma.MaskedArray.__rlshift__()**方法可以对掩码数组的每个元素进行给定标量值的左移操作。掩码数组是标准numpy.ndarray和掩码的组合。掩码可以是nomask(表示关联数组中没有无效值)或布尔值数组,用于确定关联数组中每个元素的值是否有效。

NumPy提供了全面的数学函数、随机数生成器、线性代数例程、傅里叶变换等等。它支持各种硬件和计算平台,并且可以很好地与分布式、GPU和稀疏数组库配合使用。

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数元素的数组:

arr = np.array([[8, 6, 1, 4], [6, 3, 9, 5], [9, 8, 1, 3], [5, 4, 7, 5]])
print("Array...
", arr) print("
Array type...
", arr.dtype)

获取数组的维度:

print("Array Dimensions...
",arr.ndim)

创建一个掩码数组,并将其中一些元素标记为无效:

maskArr = ma.masked_array(arr, mask =[[1, 1, 0, 0], [ 0, 0, 1, 0], [0, 0, 0, 1], [0, 1, 0, 0]])
print("
Our Masked Array
", maskArr) print("
Our Masked Array type...
", maskArr.dtype)

获取掩码数组的维度:

print("
Our Masked Array Dimensions...
",maskArr.ndim)

获取掩码数组的形状:

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

获取掩码数组的元素个数:

print("
Elements in the Masked Array...
",maskArr.size)

标量:

val = 3
print("
The given value..
",val)

使用ma.MaskedArray.__rlshift__()方法对掩码数组的每个元素进行给定标量值的左移操作:

print("
Resultant Array...
",maskArr.__rlshift__(val))

示例

Open Compiler
import numpy as np import numpy.ma as ma # Create an array with int elements using the numpy.array() method arr = np.array([[8, 6, 1, 4], [6, 3, 9, 5], [9, 8, 1, 3], [5, 4, 7, 5]]) print("Array...", arr) print("Array type...", arr.dtype) # Get the dimensions of the Array print("Array Dimensions...",arr.ndim) # Create a masked array and mask some of them as invalid maskArr = ma.masked_array(arr, mask =[[1, 1, 0, 0], [ 0, 0, 1, 0], [0, 0, 0, 1], [0, 1, 0, 0]]) print("Our Masked Array", maskArr) print("Our Masked Array type...", maskArr.dtype) # Get the dimensions of the Masked Array print("Our Masked Array Dimensions...",maskArr.ndim) # Get the shape of the Masked Array print("Our Masked Array Shape...",maskArr.shape) # Get the number of elements of the Masked Array print("Elements in the Masked Array...",maskArr.size) # The scalar val = 3 print("The given value..",val) # Left Shift a given scalar value by every element of a masked array, # use the ma.MaskedArray.__rlshift__() method print("Resultant Array...",maskArr.__rlshift__(val))

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输出

Array...
[[8 6 1 4]
[6 3 9 5]
[9 8 1 3]
[5 4 7 5]]

Array type...
int64

Array Dimensions...
2

Our Masked Array
[[-- -- 1 4]
[6 3 -- 5]
[9 8 1 --]
[5 -- 7 5]]

Our Masked Array type...
int64

Our Masked Array Dimensions...
2

Our Masked Array Shape...
(4, 4)

Elements in the Masked Array...
16

The given value..
3

Resultant Array...
[[-- -- 6 48]
[192 24 -- 96]
[1536 768 6 --]
[96 -- 384 96]]

更新于:2022年2月7日

107 次浏览

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