FFT with np.fft module in NumPy - Mini Project: Build & Apply

FFT with np.fft module

📖 Scenario: You are analyzing a simple signal that changes over time. You want to find out the main frequencies in this signal using a tool called FFT (Fast Fourier Transform).

🎯 Goal: Build a program that creates a time signal, sets up the sampling rate, applies FFT using np.fft.fft, and prints the frequency components.

📋 What You'll Learn

Create a numpy array called time_signal with specific values

Create a variable called sampling_rate with a given value

Use np.fft.fft on time_signal and store the result in frequency_components

Print the frequency_components array

💡 Why This Matters

🌍 Real World

FFT is used in audio processing, image analysis, and many fields to find hidden frequencies in signals.

💼 Career

Understanding FFT helps in roles like data analyst, signal processing engineer, and any job involving time series data.

1

Create the time signal

Create a numpy array called time_signal with these exact values: [0, 1, 0, -1].

NumPy

import numpy as np
# Create the numpy array time_signal with values [0, 1, 0, -1]
# Your code here

Need a hint?

Use np.array to create the array with the exact values.

2

Set the sampling rate

Create a variable called sampling_rate and set it to 4.

NumPy

import numpy as np

time_signal = np.array([0, 1, 0, -1])
# Set the sampling_rate variable to 4
# Your code here

Need a hint?

Sampling rate is how many samples per second. Just assign the number 4 to sampling_rate.

3

Apply FFT to the time signal

Use np.fft.fft on time_signal and save the result in a variable called frequency_components.

NumPy

import numpy as np

time_signal = np.array([0, 1, 0, -1])
sampling_rate = 4
# Apply FFT on time_signal and store in frequency_components
# Your code here

Need a hint?

Use np.fft.fft(time_signal) to get the frequency components.

4

Print the frequency components

Print the variable frequency_components to see the FFT result.

NumPy

import numpy as np

time_signal = np.array([0, 1, 0, -1])
sampling_rate = 4

frequency_components = np.fft.fft(time_signal)
# Print frequency_components
# Your code here

Need a hint?

Use print(frequency_components) to display the FFT output.