3D Topographical Pattern using Python

 

import matplotlib.pyplot as plt

import numpy as np

from mpl_toolkits.mplot3d import Axes3D

x=np.linspace(-5,5,100)

y=np.linspace(-5,5,100)

x,y=np.meshgrid(x,y)

z=np.sin(np.sqrt(x**2+y**2))

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

ax=fig.add_subplot(111,projection='3d')

surface=ax.plot_surface(x,y,z,cmap='terrain',edgecolor='none')

fig.colorbar(surface)

ax.set_xlabel('X (Longitude)')

ax.set_ylabel('Y(Latitude)')

ax.set_zlabel('Z(Elevation)')

ax.set_title('3D Topographical pattern')

plt.show()

#source code --> clcoding.com 

Code Explanation:

1. Importing Libraries

import numpy as np

import matplotlib.pyplot as plt

from mpl_toolkits.mplot3d import Axes3D

numpy (np): Used for numerical operations like creating arrays and applying mathematical functions.

 matplotlib.pyplot (plt): Used for plotting graphs and figures.

 mpl_toolkits.mplot3d: Adds support for 3D plotting using Axes3D.

 2. Creating Grid Data

x = np.linspace(-5, 5, 100)

y = np.linspace(-5, 5, 100)

x, y = np.meshgrid(x, y)

np.linspace(-5, 5, 100): Creates 100 evenly spaced points from -5 to 5 for both x and y axes.

 np.meshgrid(x, y): Creates a 2D grid of all combinations of x and y — needed for surface plotting.

 3. Defining the Elevation (Z-values)

z = np.sin(np.sqrt(x**2 + y**2))

This creates elevation data using a sine wave based on the distance from the origin (0,0). It looks like ripples or waves radiating from the center.

 Formula breakdown:

x**2 + y**2: Computes the square of the distance.

np.sqrt(...): Takes the square root → gives radial distance.

np.sin(...): Applies the sine function to generate oscillations.

 4. Creating the Plot Figure

fig = plt.figure(figsize=(10, 7))

Initializes a new figure window.

figsize=(10, 7): Sets the width and height of the figure in inches.

 5. Adding a 3D Subplot

ax = fig.add_subplot(111, projection='3d')

Adds a 3D plotting area to the figure.

111 = 1 row, 1 column, 1st subplot.

projection='3d': Tells matplotlib to enable 3D plotting for this subplot.

 6. Plotting the 3D Surface

surface = ax.plot_surface(x, y, z, cmap='terrain', edgecolor='none')

Creates the 3D surface from x, y, and z data.

cmap='terrain': Applies a terrain color map to simulate real-world elevation colors (greens, browns, etc.).

edgecolor='none': Removes grid lines for a cleaner look.

 7. Adding a Color Bar

fig.colorbar(surface)

Adds a color bar beside the plot.

Shows how colors map to elevation values (Z-axis).

 8. Labeling the Axes

ax.set_xlabel('X (Longitude)')

ax.set_ylabel('Y (Latitude)')

ax.set_zlabel('Z (Elevation)')

Labels each axis for clarity:

 X: "Longitude"

Y: "Latitude"

Z: "Elevation"

 9. Setting the Plot Title

ax.set_title('3D Topographical Plot')

Adds a descriptive title to the top of the plot.

 10. Displaying the Plot

plt.show()

Renders the plot in a window or notebook.

Allows for interactive rotation, zoom, and pan if run in a GUI or Jupyter Notebook.