Perform 2D discrete Fourier Transform using SciPy's fftpack
NumPy: Integration with SciPy Exercise-2 with Solution
Write a NumPy program to generate a 2D array and performs a discrete Fourier transform using SciPy's fftpack module
Sample Solution:
Python Code:
# Import necessary libraries
import numpy as np
from scipy.fftpack import fft2
# Generate a 2D NumPy array of random numbers
data = np.random.rand(4, 4)
# Perform a 2D discrete Fourier transform using SciPy's fft2 function
dft_result = fft2(data)
# Print the original array
print("Original 2D array:")
print(data)
# Print the DFT result
print("\nDFT of the 2D array:")
print(dft_result)
Output:
Original 2D array: [[0.16204087 0.71466796 0.27190299 0.16085316] [0.94790095 0.40448638 0.64383355 0.36492436] [0.2436009 0.74392168 0.39621449 0.48598625] [0.59709283 0.43888981 0.40708137 0.63237158]] DFT of the 2D array: [[ 7.61576914-0.j 0.23160316-0.65783047j -0.27643324-0.j 0.23160316+0.65783047j] [-0.56025834-0.28570964j -0.19029233-0.40993533j 0.14851528-0.88941094j 0.27579526+0.18182345j] [-1.25739254-0.j -0.75655458-0.96566998j -1.78690636-0.j -0.75655458+0.96566998j] [-0.56025834+0.28570964j 0.27579526-0.18182345j 0.14851528+0.88941094j -0.19029233+0.40993533j]]
Explanation:
- Import necessary libraries:
- Import NumPy and SciPy's fft2 function from the fftpack module.
- Generate a 2D NumPy array of random numbers:
- Create a 4x4 array filled with random numbers between 0 and 1.
- Perform a 2D discrete Fourier transform:
- Use SciPy's fft2 function to compute the 2D discrete Fourier transform of the array.
- Print the original array:
- Display the original 2D array of random numbers.
- Display the result of the discrete Fourier transform.
Python-Numpy Code Editor:
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