I want to have colors corresponding to a colormap in my 3d quiver plot. The 2d version of the plot has an optional array that is used to map colors to the arrows. How can I create the same effect in the 3d version?
Building on @tacaswell and @sytrus answers, here is an example of coloring a 3d quiver plot
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np
# Make the grid
x, y, z = np.meshgrid(np.arange(-0.8, 1, 0.2),
np.arange(-0.8, 1, 0.2),
np.arange(-0.8, 1, 0.8))
# Make the direction data for the arrows
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
w = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) *
np.sin(np.pi * z))
# Color by azimuthal angle
c = np.arctan2(v, u)
# Flatten and normalize
c = (c.ravel() - c.min()) / c.ptp()
# Repeat for each body line and two head lines
c = np.concatenate((c, np.repeat(c, 2)))
# Colormap
c = plt.cm.hsv(c)
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.quiver(x, y, z, u, v, w, colors=c, length=0.1, normalize=True)
plt.show()
Expanding on the answer from @slek120. I had an issue where vectors of length zero were present. These messed up the correspondence between the arrow tip colors. My solution is to give them a nonzero length and make them transparent. For some reason that I don't understand, simply discarding them didn't work. Adding a small change to the last part, a colorbar can be included as well. The colorbar asks explicitely for q.set_array()
. This changes the color, but q.set_edgecolor(c); q.set_facecolor(c)
lets you insert your custom colormap.
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np
cmap = 'hsv'
# Make the grid
x, y, z = np.meshgrid(np.arange(-0.8, 1, 0.2),
np.arange(-0.8, 1, 0.2),
np.arange(-0.8, 1, 0.8))
# Make the direction data for the arrows
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
w = np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) * np.sin(np.pi * z)
# check what happens if all values are zero
# no quivers are plotted, colors don't match anymore
u[:,2:4] = v[:,2:4] = w[:,2:4] = 0
# change values that are zero to something close to zero
uvw = np.vstack((u[np.newaxis],v[np.newaxis],w[np.newaxis]))
norm = np.linalg.norm(uvw, axis = 0)
max_norm = np.max(norm)
mask = norm == 0
min_norm = 0.3 # you want every arrow to be longer than this fraction of max_norm
# rescale vs for illustrative purposes, so small vectors become visible
# and zero vectors become nonzero so colors of the arrow shaft and head correspond. Later these are made transparent
uvw = uvw + min_norm * np.tile(mask[np.newaxis], (3, 1, 1, 1)) / max_norm
# recalculate norms so you don't divide by zero
norm = np.linalg.norm(uvw, axis=0)
uvw = min_norm * uvw / norm + (1 - min_norm) * uvw / max_norm
u, v, w = uvw
# Color by azimuthal angle
c = np.arctan2(v, u)
# Flatten and normalize
c = (c.ravel() - c.min()) / c.ptp()
# Adjust for missing quivers
# c = c[np.nonzero((u.ravel() != 0) * (v.ravel() != 0) * (w.ravel() != 0))]
# Repeat for each body line and two head lines
c = np.concatenate((c, np.repeat(c, 2)))
repeated_mask = np.concatenate((mask.ravel(), np.repeat(mask.ravel(), 2)))
# Colormap
c = getattr(plt.cm, cmap)(c)
# set zero values transparent, you made them nonzero not to mess up the tip colors
c[repeated_mask, 3] = 0.1
fig = plt.figure()
ax = fig.gca(projection='3d')
q = ax.quiver(x, y, z, u, v, w, cmap = cmap, length=0.1)
q.set_array(np.linspace(0,max_norm,10))
fig.colorbar(q)
q.set_edgecolor(c)
q.set_facecolor(c)
plt.show()
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