NumPy: Collapse a 3-D array into one dimension array

NumPy: Array Object Exercise-49 with Solution

Write a NumPy program to collapse a 3-D array into a one-dimensional array.

Pictorial Presentation:

Sample Solution:

Python Code:

# Importing the NumPy library with an alias 'np'
import numpy as np

# Creating a 3x3 identity matrix using np.eye
x = np.eye(3)

# Printing the original 3x3 identity matrix
print("3-D array:")
print(x)

# Raveling the 3x3 matrix in Fortran (column-major) order to create a one-dimensional array
f = np.ravel(x, order='F')

# Printing the resulting one-dimensional array after raveling
print("One dimension array:")
print(f) 

Sample Output:

3-D array:                                                             
[[ 1.  0.  0.]                                                         
 [ 0.  1.  0.]                                                         
 [ 0.  0.  1.]]                                                        
One dimension array:                                                   
[ 1.  0.  0.  0.  1.  0.  0.  0.  1.]

Explanation:

In the above code -

x = np.eye(3): This part creates a 3x3 identity matrix using the np.eye() function. In an identity matrix, the diagonal elements are 1, and the off-diagonal elements are 0.
f = np.ravel(x, order='F'): The np.ravel() function is used to flatten the input matrix x into a one-dimensional array. The order parameter is set to 'F' (Fortran order), which specifies that the elements should be flattened column-wise (i.e., going down columns first, then moving to the next column).

print(f) prints the resulting one-dimensional NumPy array f, which contains the flattened elements of the identity matrix x in Fortran order.

Python-Numpy Code Editor:

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