Spirograph Pattern using Python

 

import numpy as np

import matplotlib.pyplot as plt

def spirograph(a, b, delta, num_points=1000):

    t = np.linspace(0, 2 * np.pi, num_points)  

    x = np.sin(a * t + delta)

    y = np.cos(b * t)

    plt.figure(figsize=(6, 6))

    plt.plot(x, y, color='purple', linewidth=1.5)

    plt.axis("equal")

    plt.axis("off")

    plt.title("Spirograph Pattern", fontsize=14)

    plt.show()

spirograph(a=5,b=4,delta=np.pi/2)

#source code --> clcoding.com 

Code Explanation:

1. Importing Libraries

import numpy as np

import matplotlib.pyplot as plt

numpy → Used for numerical operations and generating arrays efficiently.

 

matplotlib.pyplot → Used for creating visualizations in Python.

 

2. Generating Data for the Plot

theta = np.linspace(0, 2 * np.pi, 100)

r = 1 + 0.5 * np.sin(4 * theta)

np.linspace(0, 2 * np.pi, 100) → Generates 100 evenly spaced values between 0 and 2π (360°).

 

theta → Represents the angular values in radians, making it perfect for a polar plot.

 

np.sin(4 * theta) → Calculates the sine of the angular values. The 4 in the expression means the sine wave will complete 4 oscillations in one full rotation (2π).

r = 1 + 0.5 * sin(4 * theta) →

1 → Base radius (Constant Offset)

0.5 * sin(4 * theta) → Creates the sinusoidal oscillations.

This makes the radius vary between 0.5 to 1.5 in a wave-like pattern.

 3. Creating the Plot

plt.figure(figsize=(8, 6))

plt.figure(figsize=(8, 6)) → Creates a figure of size 8x6 inches. This helps in adjusting the dimensions for better visibility.

 4. Setting Up the Polar Plot

ax = plt.subplot(111, polar=True)

plt.subplot() → Creates a subplot inside the figure.

111 → Means 1 row, 1 column, and this is the 1st subplot.

polar=True → Specifies that the plot will be in polar coordinates instead of Cartesian.

 5. Plotting the Data

ax.plot(theta, r, color='blue', linewidth=2)

ax.plot() → Plots the data on the polar plot using the generated theta (angles) and r (radius values).

color='blue' → Makes the curve blue.

linewidth=2 → Sets the line thickness to 2 points for clearer visibility.

 6. Adding Title

ax.set_title('Basic Polar Plot with Sinusoidal Pattern', va='bottom')

ax.set_title() → Adds a title to the polar plot.

va='bottom' → Aligns the title to the bottom of the plot.

 7. Displaying the Plot

plt.show()

plt.show() → Displays the plot on the screen.