Analyzing entropy visually in jupyter notebook

analyze.py

# ChatGPT: i have a binary file called "output.bin". 
# i want to read it with python as a stream of integers triplets 
# that map as coordinates in a 3d space and then plot those data points with mathplotlib. 
# all of this is happening in jupyter notebook.
# + some additional small tweaking

# Output:
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

def plot_file_3d(filename):
    # Step 1: Read the binary file in chunks and convert to a list of integers
    chunk_size = 4 * 3  # Each triplet has 3 integers, each integer is 4 bytes
    
    x_coords = []
    y_coords = []
    z_coords = []
    
    with open(filename, 'rb') as file:
        while True:
            chunk = file.read(chunk_size)
            if not chunk:
                break
            if len(chunk) == chunk_size:  # Discard the incomplete chunk at the end
                # Convert the chunk to a list of integers
                data = [int.from_bytes(chunk[i:i+4], byteorder='little') for i in range(0, len(chunk), 4)]
                # Append the coordinates to their respective lists
                x_coords.extend(data[::3])
                y_coords.extend(data[1::3])
                z_coords.extend(data[2::3])
    
    # Step 2: Plot the data points in 3D space
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
    ax.scatter(x_coords, y_coords, z_coords, s=1, c='black')
    
    # Add labels and title
    ax.set_xlabel('X')
    ax.set_ylabel('Y')
    ax.set_zlabel('Z')
    plt.title('Data Points in 3D Space')
    
    # Show the plot
    plt.show()

output.md