Set the colors of a point on a matplotlib scatter chart

Question

I am handling data received from an Arduine from a .txt. In the code, I Gero 4 arrays (X,Y,Z and F), where X,Y and Z are coordinates and F is the signal strength.

I would like to plot the 3D graph with the scatter function of matplotlib, but set the color of each point from the values of F. For example, set a colormap and color each point from the respective value in vector F.

The code below makes the 3D Plot of the coordinates, but all the points are of the same color. How can I control the color individually of each point?

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

def separador(string,sep):
    '''
    Função para ler os valores do Arduino e separá-los em listas
    '''
    lista = []
    k = 0
    j = k
    for i in range(len(string)):
        if string[i] in sep:
            j = i
            pal = string[k:j]
            k = j+1
            lista.append(float(pal))
    return lista

file = open('saidas_arduino\scanner_oreo.txt')
output = file.readlines()
file.close()

# distancia ate a mesa e forca do sinal
dist_mesa = float(output[4][0:len(output[4])-1])
str_mesa = float(output[6][0:len(output[6])-1])

# linha em que começa a leitura
line_xyz = 0
for i in range(20):
    if output[i] == 'x,y,z,str\n':
        line_xyz = i+1
        break
    
# salva os dados em vetores
X = []
Y = []
Z = []
F = []
for i in range(line_xyz,len(output)-1):
    linha = separador(output[i],('\n',','))
    X.append(linha[0])
    Y.append(linha[1])
    Z.append(linha[2])
    F.append(linha[3])
    
X = np.array(X)
Y = np.array(Y)
Z = np.array(Z)
F = np.array(F)
    
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
# aqui eu gostaria de definir o colormap pra cada ponto
ax.set_zlim(-20,20)
ax.scatter(X,Y,Z)
plt.show()

Answer 1

to documentation, in English, indicates that the scatter can receive an argument c which will be used to color the dots. This argument can receive a color, color sequence, etc. In particular, if this argument receives a scalar vector, then these scalars are passed to a color map (Cmap), generating a gradient.

Modifying the relevant part of the code:

# dados artificiais

rnd = np.random.default_rng()
X, Y, Z, F = rnd.uniform(-20,20, size=(4,20))

# figura

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
# aqui eu gostaria de definir o colormap pra cada ponto
ax.set_zlim(-20,20)
ax.scatter(X,Y,Z, c=F, cmap='RdYlBu')
plt.show()

you can check other color options in this website (in English).

PS: a 3D figure is a kind of visualization that only makes sense in very particular situations, often if you plot the data in 2D and use colors, sizes and shapes to represent the information you want to represent in other dimensions the result gets better.