Swap the bytes of the masked array data in Numpy

NumpyServer Side ProgrammingProgramming

To swap the bytes of the array elements, use the ma.MaskedArray.byteswap() method in Numpy. Toggle between low-endian and big-endian data representation by returning a byteswapped array, optionally swapped in-place. Arrays of byte-strings are not swapped. The real and imaginary parts of a complex number are swapped individually. It returns the byteswapped array. If inplace is True, this is a view to self.

The numpy.ma.MaskedArray is a subclass of ndarray designed to manipulate numerical arrays with missing data. An instance of MaskedArray can be thought as the combination of several elements −

Steps

At first, import the required library −

import numpy as np
import numpy.ma as ma

Create an array with int elements using the numpy.array() method −

arr = np.array([[35, 85, 45], [67, 33, 59]])
print("Array...\n", arr)
print("\nArray type...\n", arr.dtype)

Get the dimensions of the Array −

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

Create a masked array and mask some of them as invalid −

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

Get the dimensions of the Masked Array −

print("\nOur Masked Array Dimensions...\n",maskArr.ndim)

Get the shape of the Masked Array −

print("\nOur Masked Array Shape...\n",maskArr.shape)

Get the number of elements of the Masked Array −

print("\nElements in the Masked Array...\n",maskArr.size)

Swap the bytes of the array elements, use the numpy.byteswap() method in Numpy −

print("\nAfter Swap...\n",maskArr.byteswap())

Example

# Python ma.MaskedArray - Swap the bytes of the masked array data

import numpy as np
import numpy.ma as ma

# Create an array with int elements using the numpy.array() method
arr = np.array([[35, 85, 45], [67, 33, 59]])
print("Array...\n", arr)
print("\nArray type...\n", arr.dtype)

# Get the dimensions of the Array
print("Array Dimensions...\n",arr.ndim)

# Create a masked array and mask some of them as invalid
maskArr = ma.masked_array(arr, mask =[[0, 0, 1], [ 0, 1, 0]])
print("\nOur Masked Array\n", maskArr)
print("\nOur Masked Array type...\n", maskArr.dtype)

# Get the dimensions of the Masked Array
print("\nOur Masked Array Dimensions...\n",maskArr.ndim)

# Get the shape of the Masked Array
print("\nOur Masked Array Shape...\n",maskArr.shape)

# Get the number of elements of the Masked Array
print("\nElements in the Masked Array...\n",maskArr.size)

# To swap the bytes of the array elements, use the byteswap() method in Numpy
print("\nAfter Swap...\n",maskArr.byteswap())

Output

Array...
[[35 85 45]
[67 33 59]]

Array type...
int64

Array Dimensions...
2

Our Masked Array
[[35 85 --]
[67 -- 59]]

Our Masked Array type...
int32

Our Masked Array Dimensions...
2

Our Masked Array Shape...
(2, 3)

Elements in the Masked Array...
6

After Swap...
[[2522015791327477760 6124895493223874560 --]  
[4827858800541171712 -- 4251398048237748224]]
raja
Updated on 02-Feb-2022 07:11:33

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