How to make a 3D plot (X, Y, Z), assigning Z values to X,Y ordered pairs?

Question

I am trying to plot a 3D chart, where my Z values would be assigned to each [X,Y] ordered pair. For example, these are my X, Y and Z values:

X = [1,2,3,4,5]
Y = [1,2,3,4,5]
Z = [10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 10, 20, 30, 40, 50,]

And the Z values, correspond to the following [X,Y] ordered pair:

Z = [X[0]Y[0], X[0]Y[1], X[0]Y[2],...., X[5]Y[4], X[5]Y[5]]

Thank you!!

Asked By: Charles Wagner

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Source

Answer 1

you can do it using np.meshgrid

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

X = [1,2,3,4,5]
Y = [1,2,3,4,5]
Z = [10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 10, 20, 30, 40, 50,]

xy = np.array(np.meshgrid(X,Y)).reshape(-1,2)

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot(xy[:,0],xy[:,1],Z)
plt.show()

you can also use scatter

ax.scatter(xy[:,0],xy[:,1],Z)

for surface plot

x , y = np.meshgrid(X,Y)
ax.plot_surface(x,y,np.array(Z).reshape(5,5))
plt.show()

Answered By: Aly Hosny

Answer 2

This will give the needed 3d array (instead of plotting it directly) which you can plot.

import numpy as np
X = [1,2,3,4,5]
Y = [1,2,3,4,5]
Z = [10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 10, 20, 30, 40, 50]

XY = np.array([[(x, y) for y in Y] for x in X])

Z = np.array(Z).reshape(XY.shape[0],XY.shape[1], 1)

XYZ = np.concatenate((XY, Z), axis = -1)

print(XYZ)

Answered By: Zabir Al Nazi

Answer 3

If you feel that mesh grid are not intuitive and can confuse future you, use plt.imshow and extent:

X = [1,2,3,4,5]
Y = [1,2,3,4,5]
Z = [10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 10, 20, 30, 40, 50, 10, 20, 30, 40, 50]

# lets works with NumPy, but this is optional
x = np.array(X)
y = np.array(Y)
z = np.array(Z).reshape(x.size, y.size)

fig = plt.figure()
ax = fig.add_subplot(111)

# assuming that you want to plot with [1,1] from bottom left:
#   1. Use [min(x), max(x), min(y), max(y)] for explicit what is wrote in axis
#   2. Use 'lower' to flip the z because numpy origin use top left
plt.imshow(z,
           extent=[min(x), max(x), min(y), max(y)],
           origin='lower',
           cmap='RdBu_r')
ax.set_aspect(x.size / y.size)
plt.colorbar()
plt.show()

# to compare with the numpy array:
print(np.flip(z, axis=0))

A better example is if we use other value for z, like this:

X = [1,2,3,4,5]
Y = [1,2,3,4,5]
Z = [10, 20, 30, 40, 50, 20, 30, 40, 50, 60, 30, 40, 50, 60, 70, 40, 50, 60, 70, 80, 50, 60, 70, 80, 90]

# lets works with NumPy, but this is optional
x = np.array(X)
y = np.array(Y)
z = np.array(Z).reshape(x.size, y.size)

fig = plt.figure()
ax = fig.add_subplot(111)

# assuming that you want to plot with [1,1] from bottom left:
#   1. Use [min(x), max(x), min(y), max(y)] for explicit what is wrote in axis
#   2. Use 'lower' to flip the z because numpy origin use top left
plt.imshow(z,
           extent=[min(x), max(x), min(y), max(y)],
           origin='lower',
           cmap='RdBu_r')
ax.set_aspect(x.size / y.size)
plt.colorbar()
plt.show()

# to compare with the numpy array:
print(np.flip(z, axis=0))

Answered By: Muhammad Yasirroni

How to make a 3D plot (X, Y, Z), assigning Z values to X,Y ordered pairs?

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