Python 3d scatterplot colormap issue
color-mapping, matplotlib, python
Solution
ax.scatter can take a color parameter `c` which is a sequence (e.g. a `list` or an `array`) of scalars, and a `cmap` parameter to specify a color map. So to make the colors vary according to the magnitude of the voltages, you could define:
c = np.abs(v)
This makes positive and negative voltages have the same color. If instead you wished each color (positive or negative) to have its own color, you could just use `c = v`.
For example,
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
x, y, z, v = (np.random.random((4,100))-0.5)*15
c = np.abs(v)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
cmhot = plt.get_cmap("hot")
cax = ax.scatter(x, y, z, v, s=50, c=c, cmap=cmhot)
plt.show()
Problem
I have four dimensional data (x, y, z displacements; and respective voltages) which I wish to plot in a 3d scatterplot in python. I've gotten the 3d plot to render, but I want to have the colour of the points change using a colourmap, dependent upon the magnitude of the point's voltage. I've tried a few things, but can't seem to get it to work I'm getting the error `ValueError: Cannot convert argument type <type 'numpy.ndarray'> to rgba array`. I'm not sure exactly how to convert what I need to convert, so if anybody could please offer some help, I'd be most appreciative. My code is here: ``` fig = plt.figure() from mpl_toolkits.mplot3d import Axes3D cmhot = plt.cm.get_cmap("hot") ax = fig.add_subplot(111, projection='3d',) ax.scatter(x, y, z, v, s=50, c = cmhot) plt.show() ```