|
| 1 | +--- |
| 2 | +Title: 'byteswap()' |
| 3 | +Description: 'Swaps the byte order of each element in a NumPy ndarray.' |
| 4 | +Subjects: |
| 5 | + - 'Computer Science' |
| 6 | + - 'Data Science' |
| 7 | +Tags: |
| 8 | + - 'Array' |
| 9 | + - 'Data' |
| 10 | + - 'NumPy' |
| 11 | +CatalogContent: |
| 12 | + - 'learn-python-3' |
| 13 | + - 'paths/data-science' |
| 14 | +--- |
| 15 | + |
| 16 | +The **`byteswap()`** method reverses the byte order of every element in a NumPy array. This is used when converting data between systems with different endianness (byte-ordering conventions). The operation either returns a new array or modifies the original one in place when `inplace=True`. |
| 17 | + |
| 18 | +## Syntax |
| 19 | + |
| 20 | +```pseudo |
| 21 | +ndarray.byteswap(inplace=False) |
| 22 | +``` |
| 23 | + |
| 24 | +**Parameters:** |
| 25 | + |
| 26 | +- `inplace` (optional): When set to `True`, the byte order of the existing array is swapped in place. When `False`, a new array with swapped bytes is returned. |
| 27 | + |
| 28 | +**Return value:** |
| 29 | + |
| 30 | +Returns a new ndarray with swapped byte order, unless `inplace=True`, in which case the original array is modified and returned. |
| 31 | + |
| 32 | +## Example 1 |
| 33 | + |
| 34 | +In this example, the array's byte order is swapped to convert the data into the opposite endianness: |
| 35 | + |
| 36 | +```py |
| 37 | +import numpy as np |
| 38 | + |
| 39 | +arr = np.array([1, 256, 1024], dtype=np.int32) |
| 40 | + |
| 41 | +print("Original array:") |
| 42 | +print(arr) |
| 43 | +print("Original dtype:", arr.dtype) |
| 44 | + |
| 45 | +swapped = arr.byteswap() |
| 46 | + |
| 47 | +print("\nAfter byteswap():") |
| 48 | +print(swapped) |
| 49 | +print("Swapped dtype:", swapped.dtype) |
| 50 | +``` |
| 51 | + |
| 52 | +The output of this code is: |
| 53 | + |
| 54 | +```shell |
| 55 | +Original array: |
| 56 | +[ 1 256 1024] |
| 57 | +Original dtype: int32 |
| 58 | + |
| 59 | +After byteswap(): |
| 60 | +[16777216 65536 262144] |
| 61 | +Swapped dtype: int32 |
| 62 | +``` |
| 63 | + |
| 64 | +## Example 2 |
| 65 | + |
| 66 | +This example demonstrates `byteswap(inplace=True)` and shows how the original data is altered directly: |
| 67 | + |
| 68 | +```py |
| 69 | +import numpy as np |
| 70 | + |
| 71 | +arr = np.array([100, 200, 300], dtype=np.int32) |
| 72 | + |
| 73 | +print("Before inplace byteswap:", arr) |
| 74 | + |
| 75 | +arr.byteswap(inplace=True) |
| 76 | + |
| 77 | +print("After inplace byteswap:", arr) |
| 78 | +``` |
| 79 | + |
| 80 | +The output of this code is: |
| 81 | + |
| 82 | +```shell |
| 83 | +Before inplace byteswap: [100 200 300] |
| 84 | +After inplace byteswap: [1677721600 -939524096 738263040] |
| 85 | +``` |
| 86 | + |
| 87 | +## Codebyte Example |
| 88 | + |
| 89 | +Use the codebyte below to inspect how `byteswap()` affects a 2-D array and observe the internal memory representation change: |
| 90 | + |
| 91 | +```codebyte/python |
| 92 | +import numpy as np |
| 93 | +
|
| 94 | +matrix = np.array([[1, 2], [3, 4]], dtype=np.int16) |
| 95 | +
|
| 96 | +print("Original:") |
| 97 | +print(matrix) |
| 98 | +
|
| 99 | +swapped = matrix.byteswap() |
| 100 | +
|
| 101 | +print("\nByteswapped:") |
| 102 | +print(swapped) |
| 103 | +``` |
| 104 | + |
| 105 | +## Frequently Asked Questions |
| 106 | + |
| 107 | +### 1. What is the function of byteswap() in Python? |
| 108 | + |
| 109 | +The `byteswap()` method reverses the byte order of every element in a NumPy array. It is commonly used when preparing data for systems with different endianness or when interpreting binary data from external sources. |
| 110 | + |
| 111 | +### 2. What are bytes and bytearrays in Python? |
| 112 | + |
| 113 | +A `bytes` object in Python is an immutable sequence of byte values, while a bytearray is a mutable version of the same concept. Both store raw binary data and are often used for file handling, networking, and low-level memory operations. |
| 114 | + |
| 115 | +### 3. How to shuffle a NumPy ndarray? |
| 116 | + |
| 117 | +A NumPy array can be shuffled using `np.random.shuffle()` for in-place row-wise shuffling or `np.random.permutation()` to return a shuffled copy. These functions randomize the order of elements while preserving the array’s structure. |
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