I'm trying to get a 3d animation of a scatterplot in matplotlib, based off the 2d scatterplot animation posted here and the 3d line plot posted here.
The problems arise from set_data
and set_offsets
not working in 3D, so you're supposed to use set_3d_properties
to tack on the z information. Playing around with that it usually chokes, but with the code posted below it runs. However, the transparency increases enough that the points just fade away after a few frames. What am I doing wrong here? I want the points to jump around within the bounds of the box for a while. Even adjusting the step size to something very small doesn't slow down the transparency.
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
FLOOR = -10
CEILING = 10
class AnimatedScatter(object):
def __init__(self, numpoints=5):
self.numpoints = numpoints
self.stream = self.data_stream()
self.angle = 0
self.fig = plt.figure()
self.ax = self.fig.add_subplot(111,projection = '3d')
self.ani = animation.FuncAnimation(self.fig, self.update, interval=100,
init_func=self.setup_plot, blit=True)
def change_angle(self):
self.angle = (self.angle + 1)%360
def setup_plot(self):
x, y, z = next(self.stream)
c = ['b', 'r', 'g', 'y', 'm']
self.scat = self.ax.scatter(x, y, z,c=c, s=200, animated=True)
self.ax.set_xlim3d(FLOOR, CEILING)
self.ax.set_ylim3d(FLOOR, CEILING)
self.ax.set_zlim3d(FLOOR, CEILING)
return self.scat,
def data_stream(self):
data = np.zeros((3, self.numpoints))
xyz = data[:3, :]
while True:
xyz += 2 * (np.random.random((3, self.numpoints)) - 0.5)
yield data
def update(self, i):
data = next(self.stream)
data = np.transpose(data)
self.scat.set_offsets(data[:,:2])
#self.scat.set_3d_properties(data)
self.scat.set_3d_properties(data[:,2:],'z')
self.change_angle()
self.ax.view_init(30,self.angle)
plt.draw()
return self.scat,
def show(self):
plt.show()
if __name__ == '__main__':
a = AnimatedScatter()
a.show()
I've found this, and more generic, solution:
You shold add np.ma.ravel( x_data ) ...
before inserting your data in the collection.
But the scatter plot don't seems to be intended for animations; it's too slow.
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
FLOOR = -10
CEILING = 10
class AnimatedScatter(object):
def __init__(self, numpoints=5):
self.numpoints = numpoints
self.stream = self.data_stream()
self.angle = 0
self.fig = plt.figure()
self.ax = self.fig.add_subplot(111,projection = '3d')
self.ani = animation.FuncAnimation(self.fig, self.update, interval=100,
init_func=self.setup_plot, blit=True)
def change_angle(self):
self.angle = (self.angle + 1)%360
def setup_plot(self):
X = next(self.stream)
c = ['b', 'r', 'g', 'y', 'm']
self.scat = self.ax.scatter(X[:,0], X[:,1], X[:,2] , c=c, s=200, animated=True)
self.ax.set_xlim3d(FLOOR, CEILING)
self.ax.set_ylim3d(FLOOR, CEILING)
self.ax.set_zlim3d(FLOOR, CEILING)
return self.scat,
def data_stream(self):
data = np.zeros(( self.numpoints , 3 ))
xyz = data[:,:3]
while True:
xyz += 2 * (np.random.random(( self.numpoints,3)) - 0.5)
yield data
def update(self, i):
data = next(self.stream)
data = np.transpose(data)
self.scat._offsets3d = ( np.ma.ravel(data[:,0]) , np.ma.ravel(data[:,0]) , np.ma.ravel(data[:,0]) )
self.change_angle()
self.ax.view_init(30,self.angle)
plt.draw()
return self.scat,
def show(self):
plt.show()
if __name__ == '__main__':
a = AnimatedScatter()
a.show()
Found the solution finally, here is how to update points w/o touching colors:
from mpl_toolkits.mplot3d.art3d import juggle_axes
scat._offsets3d = juggle_axes(xs, ys, zs, 'z')
this is internally done by set_3d_properties along with re-initializing colors
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