How to change memory layout of a 2D NumPy array to C order?

Last update on March 26 2025 13:18:42 (UTC/GMT +8 hours)

10. 2D Array C-Order Contiguity

Write a NumPy program that creates a 2D array of shape (3, 3), change its memory layout to 'C' order using ascontiguousarray(), and print the array and its strides.

Sample Solution:

Python Code:

import numpy as np

# Create a 2D array of shape (3, 3)
array_2d = np.array([[1, 2, 3],
                     [4, 5, 6],
                     [7, 8, 9]])

# Change the memory layout to 'C' order
array_c_order = np.ascontiguousarray(array_2d)

# Print the array in 'C' order
print("Array in 'C' order:\n", array_c_order)

# Print the strides of the array in 'C' order
print("Strides of the array in 'C' order:", array_c_order.strides)

Output:

Array in 'C' order:
 [[1 2 3]
 [4 5 6]
 [7 8 9]]
Strides of the array in 'C' order: (12, 4)

Explanation:

• Import NumPy library: We start by importing the NumPy library to handle array operations.
• Create a 2D array: We create a 2D array array_2d of shape (3, 3) using np.array().
• Change memory layout to 'C' order: We use np.ascontiguousarray() to ensure the array is stored in row-major ('C') order, resulting in array_c_order.
• Print the array: We print array_c_order to display the array in 'C' order.
• Print the strides: We print the strides of array_c_order using the strides attribute to show the number of bytes to step in each dimension when traversing the array.

For more Practice: Solve these Related Problems:

• Write a NumPy program to convert a non-contiguous 2D array into a C-contiguous array using ascontiguousarray() and print its flags and strides.
• Write a NumPy program to compare the strides of a 2D array before and after converting it to C order.
• Write a NumPy program to check an array's contiguity and, if needed, convert it to C order and verify the change.
• Write a NumPy program to create a sliced 2D array that is non-contiguous, then use ascontiguousarray() to make it contiguous and print the new strides.

Python-Numpy Code Editor:

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