Edit: I managed to figure out what was going on. Scatter has a parameter 'line-width' (lw=n) that determines the thickness of the line surrounding the plot point for a scatter plot. Because my plot points were size 1 (s=1), the line width was so thick it was actually covering the colour of the plot point. Setting the line-width to a thickness of 0 (lw=0) should do the trick.
I want to generate a 3d scatterplot of data-points, colouring them based on the value of their y-coordinate, but I can't manage to get the points to actually colour.
If the value of the datapoint is low, the colour should be closer to the blue-end of the colour spectrum. If the value is higher the, the colour should be closer to the red-end of the spectrum.
I've managed to plot what I want in 2D, but am having trouble replicating the process in 3D. The current code only plots the points in black.
Here is my code for the 3D attempt, and a screenshot of the desired results in 2D. What exactly am I doing wrong here?
x_points, y_points, and z_points are lists of float values.
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
self, x_points, y_points, z_points, data_file
cm1 = cm.get_cmap('gist_rainbow')
fig = plt1.figure()
ax = fig.add_subplot(111, projection='3d')
You have to plot like here:
import matplotlib.pyplot as plt from matplotlib import cm from mpl_toolkits.mplot3d import Axes3D import numpy as np x = np.random.rand(25) y = np.random.rand(25) z = np.random.rand(25) fig = plt.figure() ax = fig.add_subplot(111, projection='3d') p3d = ax.scatter(x, y, z, s=30, c=y, cmap = cm.coolwarm) plt.show()