Inverse FFT (ifft) in SciPy - Mini Project: Build & Apply

Inverse FFT (ifft) with SciPy

📖 Scenario: You have a signal in the frequency domain and want to convert it back to the time domain to understand its original shape.

🎯 Goal: Learn how to use the ifft function from SciPy to perform an inverse Fast Fourier Transform and recover the original time-domain signal.

📋 What You'll Learn

Create a frequency domain signal as a list of complex numbers

Set the length of the inverse FFT using a variable

Use SciPy's ifft function to compute the inverse FFT

Print the real part of the recovered time-domain signal

💡 Why This Matters

🌍 Real World

Inverse FFT is used in signal processing to reconstruct original signals from their frequency components, such as in audio processing or communications.

💼 Career

Understanding inverse FFT is important for roles in data science, engineering, and research where signal analysis and transformation are common tasks.

1

Create the frequency domain signal

Create a list called freq_signal with these exact complex values: 1+0j, 0-1j, -1+0j, 0+1j.

SciPy

# Create the frequency domain signal list called freq_signal
# Your code here

Need a hint?

Use square brackets to create a list and include the complex numbers exactly as shown.

2

Set the length for the inverse FFT

Create a variable called n and set it to 4 to specify the length of the inverse FFT.

SciPy

freq_signal = [1+0j, 0-1j, -1+0j, 0+1j]
# Set the variable n to 4
# Your code here

Need a hint?

Just assign the number 4 to the variable n.

3

Compute the inverse FFT

Import ifft from scipy.fft and create a variable called time_signal that stores the inverse FFT of freq_signal with length n.

SciPy

freq_signal = [1+0j, 0-1j, -1+0j, 0+1j]
n = 4
# Import ifft and compute the inverse FFT into time_signal
# Your code here

Need a hint?

Use from scipy.fft import ifft and call ifft(freq_signal, n).

4

Print the real part of the time-domain signal

Print the real parts of the time_signal array using a list comprehension that extracts the real part of each element.

SciPy

from scipy.fft import ifft

freq_signal = [1+0j, 0-1j, -1+0j, 0+1j]
n = 4

time_signal = ifft(freq_signal, n)
# Print the real parts of time_signal
# Your code here

Need a hint?

Use a list comprehension like [x.real for x in time_signal] inside the print statement.