Real FFT (rfft) in SciPy - Mini Project: Build & Apply

Real FFT (rfft) Analysis of a Signal

📖 Scenario: You have recorded a simple signal that changes over time. You want to find out which frequencies are present in this signal. This is useful in many areas like music, engineering, and science.

🎯 Goal: You will create a list of signal values, set up the sampling rate, use the real FFT function to find the frequencies, and then print the frequency values.

📋 What You'll Learn

Create a list called signal with exact values: 0, 1, 0, -1, 0, 1, 0, -1

Create a variable called sampling_rate and set it to 8

Use scipy.fft.rfft on signal to get the frequency components

Print the frequencies using scipy.fft.rfftfreq with len(signal) and 1/sampling_rate

💡 Why This Matters

🌍 Real World

Real FFT is used in audio processing, vibration analysis, and any field where understanding the frequency content of real signals is important.

💼 Career

Data scientists and engineers use FFT to analyze signals, detect patterns, and extract features for machine learning and diagnostics.

1

Create the signal data

Create a list called signal with these exact values: 0, 1, 0, -1, 0, 1, 0, -1

SciPy

# Create the signal list with the exact values
# Your code here

Need a hint?

Use square brackets to create a list and separate values with commas.

2

Set the sampling rate

Create a variable called sampling_rate and set it to 8

SciPy

signal = [0, 1, 0, -1, 0, 1, 0, -1]
# Set the sampling_rate variable to 8
# Your code here

Need a hint?

Sampling rate is how many samples per second the signal has.

3

Calculate the real FFT of the signal

Import scipy.fft and use scipy.fft.rfft on signal to get the frequency components. Store the result in a variable called freq_components

SciPy

signal = [0, 1, 0, -1, 0, 1, 0, -1]
sampling_rate = 8
# Import scipy.fft and calculate freq_components using rfft on signal
# Your code here

Need a hint?

Use import scipy.fft and then call scipy.fft.rfft(signal).

4

Print the frequency values

Use scipy.fft.rfftfreq with len(signal) and 1/sampling_rate to get the frequencies. Print the frequencies.

SciPy

import scipy.fft

signal = [0, 1, 0, -1, 0, 1, 0, -1]
sampling_rate = 8

freq_components = scipy.fft.rfft(signal)
# Calculate frequencies using rfftfreq and print them
# Your code here

Need a hint?

Use scipy.fft.rfftfreq(len(signal), 1/sampling_rate) to get the frequency values.