# Plot 3D Cube and Draw Line on 3D in Python

## Question:

I know, for those who know Python well piece of cake a question.

I have an excel file and it looks like this:

1 7 5 8 2 4 6 3

1 7 4 6 8 2 5 3

6 1 5 2 8 3 7 4

My purpose is to draw a cube in Python and draw a line according to the order of these numbers.
Note: There is no number greater than 8 in arrays.

I can explain better with a pictures. First Step: Second Step Last Step: I need to print the final version of the 3D cube for each row in Excel.

My way to solution

``````import numpy as np
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection, Line3DCollection
import matplotlib.pyplot as plt

myArray = df.values

points = solutionsarray

def connectpoints(x,y,p1,p2):
x1, x2 = x[p1], x[p2]
y1, y2 = y[p1], y[p2]
plt.plot([x1,x2],[y1,y2],'k-')

# cube = 1
# cube = 2
# cube = 3
# cube = 4
# cube = 5
# cube = 6
# cube = 7
# cube = 8

for i in range():
connectpoints(cube[i][i][i],cube[],points[i],points[i+1]) # Confused!

# plot sides

facecolors='cyan', linewidths=1, edgecolors='r', alpha=.25))

ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')

plt.show()
``````

In the question here, they managed to draw something with the points given inside the cube.

I tried to use this 2D connection function.

Last Question: Can I print the result of red lines in 3D? How can I do this in Python?

First, it looks like you are using `pandas` with `pd.read_csv` without importing it. Since, you are not reading the headers and just want a list of values, it is probably sufficient to just use the `numpy` `read` function instead.

Since I don’t have access to your csv, I will define the vertex lists as variables below.

``````vertices = np.zeros([3,8],dtype=int)
vertices[0,:] = [1, 7, 5, 8, 2, 4, 6, 3]
vertices[1,:] = [1, 7, 4, 6, 8, 2, 5, 3]
vertices[2,:] = [6, 1, 5, 2, 8, 3, 7, 4]
vertices = vertices - 1 #(adjust the vertex numbers by one since python starts with zero indexing)
``````

Here I used a 2d numpy array to define the vertices. The first dimension, with length 3, is for the number of vertex list, and the second dimension, with length 8, is each vertex list.

I subtract 1 from the `vertices` list because we will use this list to index another array and python indexing starts at 0, not 1.

Then, define the cube coordaintes.

``````# Initialize an array with dimensions 8 by 3
# 8 for each vertex
# -> indices will be vertex1=0, v2=1, v3=2 ...
# 3 for each coordinate
# -> indices will be x=0,y=1,z=1
cube = np.zeros([8,3])

# Define x values
cube[:,0] = [0, 0, 0, 0, 1, 1, 1, 1]
# Define y values
cube[:,1] = [0, 1, 0, 1, 0, 1, 0, 1]
# Define z values
cube[:,2] = [0, 0, 1, 1, 0, 0, 1, 1]
``````

Then initialize the plot.

``````# First initialize the fig variable to a figure
fig = plt.figure()
# Add a 3d axis to the figure
``````

Then add the red lines for vertex list 1. You can repeat this for the other vertex list by increasing the first index of vertices.

``````# Plot first vertex list
ax.plot(cube[vertices[0,:],0],cube[vertices[0,:],1],cube[vertices[0,:],2],color='r-')
# Plot second vertex list
ax.plot(cube[vertices[1,:],0],cube[vertices[1,:],1],cube[vertices[1,:],2],color='r-')
``````

The faces can be added by defining the edges of each faces. There is a numpy array for each face. In the array there are 5 vertices, where the edge are defined by the lines between successive vertices. So the 5 vertices create 4 edges.

``````# Initialize a list of vertex coordinates for each face
# faces = [np.zeros([5,3])]*3
faces = []
faces.append(np.zeros([5,3]))
faces.append(np.zeros([5,3]))
faces.append(np.zeros([5,3]))
faces.append(np.zeros([5,3]))
faces.append(np.zeros([5,3]))
faces.append(np.zeros([5,3]))
# Bottom face
faces[:,0] = [0,0,1,1,0]
faces[:,1] = [0,1,1,0,0]
faces[:,2] = [0,0,0,0,0]
# Top face
faces[:,0] = [0,0,1,1,0]
faces[:,1] = [0,1,1,0,0]
faces[:,2] = [1,1,1,1,1]
# Left Face
faces[:,0] = [0,0,0,0,0]
faces[:,1] = [0,1,1,0,0]
faces[:,2] = [0,0,1,1,0]
# Left Face
faces[:,0] = [1,1,1,1,1]
faces[:,1] = [0,1,1,0,0]
faces[:,2] = [0,0,1,1,0]
# front face
faces[:,0] = [0,1,1,0,0]
faces[:,1] = [0,0,0,0,0]
faces[:,2] = [0,0,1,1,0]
# front face
faces[:,0] = [0,1,1,0,0]
faces[:,1] = [1,1,1,1,1]
faces[:,2] = [0,0,1,1,0]
``````

All together it looks like this.

``````import numpy as np
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
import matplotlib.pyplot as plt

vertices = np.zeros([3,8],dtype=int)
vertices[0,:] = [1, 7, 5, 8, 2, 4, 6, 3]
vertices[1,:] = [1, 7, 4, 6, 8, 2, 5, 3]
vertices[2,:] = [6, 1, 5, 2, 8, 3, 7, 4]
vertices = vertices - 1 #(adjust the indices by one since python starts with zero indexing)

# Define an array with dimensions 8 by 3
# 8 for each vertex
# -> indices will be vertex1=0, v2=1, v3=2 ...
# 3 for each coordinate
# -> indices will be x=0,y=1,z=1
cube = np.zeros([8,3])

# Define x values
cube[:,0] = [0, 0, 0, 0, 1, 1, 1, 1]
# Define y values
cube[:,1] = [0, 1, 0, 1, 0, 1, 0, 1]
# Define z values
cube[:,2] = [0, 0, 1, 1, 0, 0, 1, 1]

# First initialize the fig variable to a figure
fig = plt.figure()
# Add a 3d axis to the figure

# plotting cube
# Initialize a list of vertex coordinates for each face
# faces = [np.zeros([5,3])]*3
faces = []
faces.append(np.zeros([5,3]))
faces.append(np.zeros([5,3]))
faces.append(np.zeros([5,3]))
faces.append(np.zeros([5,3]))
faces.append(np.zeros([5,3]))
faces.append(np.zeros([5,3]))
# Bottom face
faces[:,0] = [0,0,1,1,0]
faces[:,1] = [0,1,1,0,0]
faces[:,2] = [0,0,0,0,0]
# Top face
faces[:,0] = [0,0,1,1,0]
faces[:,1] = [0,1,1,0,0]
faces[:,2] = [1,1,1,1,1]
# Left Face
faces[:,0] = [0,0,0,0,0]
faces[:,1] = [0,1,1,0,0]
faces[:,2] = [0,0,1,1,0]
# Left Face
faces[:,0] = [1,1,1,1,1]
faces[:,1] = [0,1,1,0,0]
faces[:,2] = [0,0,1,1,0]
# front face
faces[:,0] = [0,1,1,0,0]
faces[:,1] = [0,0,0,0,0]
faces[:,2] = [0,0,1,1,0]
# front face
faces[:,0] = [0,1,1,0,0]
faces[:,1] = [1,1,1,1,1]
faces[:,2] = [0,0,1,1,0]

# plotting lines
ax.plot(cube[vertices[0,:],0],cube[vertices[0,:],1],cube[vertices[0,:],2],color='r')
ax.plot(cube[vertices[1,:],0],cube[vertices[1,:],1],cube[vertices[1,:],2],color='r')
ax.plot(cube[vertices[2,:],0],cube[vertices[2,:],1],cube[vertices[2,:],2],color='r')

ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')

plt.show()
``````

Alternatively, If you want each set of lines to have their own color, replace

``````ax.plot(cube[vertices[0,:],0],cube[vertices[0,:],1],cube[vertices[0,:],2],color='r')
ax.plot(cube[vertices[1,:],0],cube[vertices[1,:],1],cube[vertices[1,:],2],color='r')
ax.plot(cube[vertices[2,:],0],cube[vertices[2,:],1],cube[vertices[2,:],2],color='r')

``````

with

``````colors = ['r','g','b']
for i in range(3):
ax.plot(cube[vertices[i,:],0],cube[vertices[i,:],1],cube[vertices[i,:],2],color=colors[i])
`````` Categories: questions Tags: , ,
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