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Fibonacci Fast Fourier Transform Visualization

This repository contains a Python script that generates Fibonacci numbers, selects a random subset of them, computes the Fast Fourier Transform (FFT) on the data, and visualizes the results through scatter plots. The visualizations include both the original data and its frequency domain representation.

Overview

  1. Generate Fibonacci Numbers: Create a sequence of Fibonacci numbers up to a specified count.
  2. Random Selection: Randomly select a subset of Fibonacci numbers.
  3. Apply FFT: Perform a Fast Fourier Transform (FFT) on the randomly selected Fibonacci numbers to analyze their frequency components.
  4. Visualize Data: Generate two scatter plots:
    • Original Data: Visualizes the selected Fibonacci numbers.
    • FFT Data: Visualizes the FFT results, displaying the real and imaginary components of the frequency domain.

Requirements

The script requires the following Python libraries:

Install the required dependencies using pip:

pip install numpy pandas matplotlib scipy

How to Run the Script

  1. Clone this repository to your local machine:
    2. git clone https://github.com/your-username/fibonacci-fft-visualization.git
  2. Navigate to the project directory:
    3. cd fibonacci-fft-visualization
  3. Run the script:
    4. python fibonacci_fft_visualization.py

Example Output

Scatter Plot 1: Shows the original Fibonacci numbers, with the x-axis representing the index and the y-axis representing the value.

Scatter Plot 1

Scatter Plot 2: Displays the real vs. imaginary parts of the FFT, with colors representing the phase.

Scatter Plot 2

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Feel free to fork this repository, open issues, and submit pull requests if you'd like to contribute to this project.

Acknowledgments