How to use numpy.ravel() in Python

How to use numpy.ravel() in Python

In Python, the numpy.ravel() function is a method of the NumPy module that returns a flatten (i.e., one-dimensional) version of an input array.

This function is useful for converting a multi-dimensional array into a single-dimensional array, which can be easier to work with or can be used as input to certain functions that only accept one-dimensional arrays.

Syntax

The syntax for using the numpy.ravel() function is as follows:

numpy.ravel(a, order='C')

a is the array that you want to flatten.

order is an optional parameter that specifies the order in which the elements of the array should be processed.

The default value for order is 'C', which means that the elements will be processed in row-major order (i.e., moving across rows from left to right).

The possible values for order are 'C', 'F', 'A', and 'K'.

• 'C' means that the elements will be flattened in row-major order (i.e., in the order of increasing memory addresses)
• 'F' means that the elements will be flattened in column-major order,
• 'A' means that the elements will be flattened in the same order as they appear in the array's memory
• 'K' means that the elements will be flattened in the order that ensures the most efficient use of memory.

Examples

Here are some examples of using the numpy.ravel() function:

Example 1

Suppose we have a two-dimensional NumPy array, arr, with shape (m, n). We can use numpy.ravel() to flatten the array into a one-dimensional array with shape (m\*n,) like this:

import numpy as np

# Create a 2x2 array
a = np.array([[1, 2], [3, 4]])

# Flatten the array using numpy.ravel()
b = np.ravel(a)

# Print the flattened array
print(b)

The output of this code will be:

[1 2 3 4]

In this example, we create a 2x2 array a and then use numpy.ravel() to flatten it into a one-dimensional array b.

Example 2

import numpy as np

# Create a 2D array
arr = np.array([[1, 2, 3], [4, 5, 6]])


# Use ravel() with the 'order' parameter
# to flatten the array in different orders
flattened = np.ravel(arr, order='C')  # Flatten in row-major (C-style) order
print(flattened)  # Output: [1 2 3 4 5 6]

flattened = np.ravel(arr, order='F')  # Flatten in column-major (Fortran-style) order
print(flattened)  # Output: [1 4 2 5 3 6]