3D Wireframe Grid using Python

 

import numpy as np

import matplotlib.pyplot as plt

from mpl_toolkits.mplot3d import Axes3D

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

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

vertices = np.array([

    [0, 0, 0],

    [1, 0, 0],

    [1, 1, 0],

    [0, 1, 0],

    [0, 0, 1],

    [1, 0, 1],

    [1, 1, 1],

    [0, 1, 1]

])

edges = [

    [0, 1], [1, 2], [2, 3], [3, 0],  

    [4, 5], [5, 6], [6, 7], [7, 4], 

    [0, 4], [1, 5], [2, 6], [3, 7]   

]

for edge in edges:

    ax.plot3D(*zip(*vertices[edge]),color="b",linewidth=2)

ax.set_title("3D wireframe Grid",fontsize=20)

ax.set_xlabel('X')

ax.set_ylabel('Y')

ax.set_zlabel('Z')

ax.set_box_aspect([1,1,1])

plt.show()

#source code --> clcoding.com 

Code Explanation:

1. Importing Required Libraries

import numpy as np

import matplotlib.pyplot as plt

from mpl_toolkits.mplot3d import Axes3D

numpy: This is used for efficient numerical operations, especially creating arrays. In this case, it is used to store the vertices of the 3D wireframe.

 matplotlib.pyplot: This is a plotting library used for creating static, animated, and interactive visualizations. It is used here for generating the plot.

 mpl_toolkits.mplot3d.Axes3D: This is an extension of the matplotlib library that enables 3D plotting. It allows us to create 3D visualizations like wireframes.

 2. Creating the Figure and Axes

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

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

plt.figure(figsize=(10, 10)): This creates a figure of size 10x10 inches. The figsize argument sets the overall size of the plot.

 fig.add_subplot(111, projection='3d'): This adds a 3D subplot to the figure, meaning we will be plotting 3D data. The '111' means "1x1 grid, 1st subplot" (which is just one subplot in this case). The projection='3d' argument specifies that we want a 3D plot.

 3. Defining the Cube's Vertices

vertices = np.array([

    [0, 0, 0],

    [1, 0, 0],

    [1, 1, 0],

    [0, 1, 0],

    [0, 0, 1],

    [1, 0, 1],

    [1, 1, 1],

    [0, 1, 1]

])

Here, vertices is a NumPy array containing the 8 vertices of a cube. Each vertex is represented by its (x, y, z) coordinates in 3D space.

 [0, 0, 0] is the origin, the starting point.

 The other vertices define the corners of a unit cube, with each coordinate either being 0 or 1 to form the edges of the cube.

 

4. Defining the Cube's Edges

edges = [

    [0, 1], [1, 2], [2, 3], [3, 0],  # Bottom square

    [4, 5], [5, 6], [6, 7], [7, 4],  # Top square

    [0, 4], [1, 5], [2, 6], [3, 7]   # Vertical connections between top and bottom

]

edges defines the connections (or lines) between the vertices of the cube. Each pair of indices (e.g., [0, 1], [1, 2]) refers to the vertices that should be connected.

 The first four edges form the bottom square of the cube.

 The next four edges form the top square.

 The last four edges are the vertical connections that connect the top and bottom squares, forming the sides of the cube.

 5. Plotting the Cube's Wireframe

for edge in edges:

    ax.plot3D(*zip(*vertices[edge]), color="b", linewidth=2)

for edge in edges: This loop iterates over all the edges defined in the edges list.

vertices[edge]: This selects the pair of vertices from the vertices array using the indices specified in the edges list.

 zip(*vertices[edge]): The zip function unpacks the vertices and prepares them in the format required for plotting (separating the x, y, and z coordinates).

 ax.plot3D(...): This function plots the 3D lines connecting the pairs of vertices for each edge. It takes the x, y, and z coordinates of the two vertices and plots the line between them.

 color="b": This sets the color of the lines to blue.

 linewidth=2: This sets the thickness of the lines to 2.

 6. Setting the Title and Labels

ax.set_title("3D Wireframe Grid", fontsize=20)

ax.set_xlabel('X')

ax.set_ylabel('Y')

ax.set_zlabel('Z')

ax.set_title("3D Wireframe Grid", fontsize=20): This sets the title of the plot to "3D Wireframe Grid" with a font size of 20.

 ax.set_xlabel('X'): This labels the x-axis as 'X'.

 ax.set_ylabel('Y'): This labels the y-axis as 'Y'.

 ax.set_zlabel('Z'): This labels the z-axis as 'Z'.

 7. Setting the Aspect Ratio

ax.set_box_aspect([1, 1, 1])

ax.set_box_aspect([1, 1, 1]): This ensures that the aspect ratio of the plot is equal in all three dimensions. This makes sure the cube looks proportionate, rather than distorted, regardless of the plot window size.

 8. Displaying the Plot

plt.show()