I have 4 arrays x, y, z and T of length n and I want to plot a 3D curve using matplotlib. The (x, y, z) are the points positions and T is the value of each point (which is plotted as color), like the temperature of each point. How can I do it? Example code: import numpy as np from matplotlib import pyplot as plt fig = plt.figure() ax = fig.gca(projection='3d') n = 100 cmap = plt.get_cmap("bwr") theta = np.linspace(-4 * np.pi, 4 * np.pi, n) z = np.linspace(-2, 2, n) r = z**2 + 1 x = r * np.sin(theta) y = r * np.cos(theta) T = (2*np.random.rand(n) - 1) # All the values are in [-1, 1] What I found over the internet: It's possible to use cmap with scatter like shown in the docs and in this stackoverflow question ax = plt.gca() ax.scatter(x, y, z, cmap=cmap, c=T) The problem is that scatter is a set of points, not a curve. In this stackoverflow question the solution was divide in n-1 intervals and each interval we use a different color like t = (T - np.min(T))/(np.max(T)-np.min(T)) # Normalize for i in range(n-1): plt.plot(x[i:i+2], y[i:i+2], z[i:i+2], c=cmap(t) The problem is that each segment has only one color, but it should be an gradient. The last value is not even used. Useful links: Matplotlib - Colormaps Matplotlib - Tutorial 3D Continue reading...
