I am trying to save an animated scatterplot using matplotlib, and I would prefer that it does not require completely different code for viewing as an animated figure and for saving a copy. The figure shows all data points after saving is completed.
This code is a modified version of Giggi on animating a 3d scatter chart in matplotlib with a fix for the Yann answer color on Matplotlib 3D the scatter color lost after redrawing (because the colors will be important on my video, so I want to make sure they work).
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.fig.canvas.mpl_connect('draw_event',self.forceUpdate)
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,frames=20)
def change_angle(self):
self.angle = (self.angle + 1)%360
def forceUpdate(self, event):
self.scat.changed()
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)
self.scat._offsets3d = ( np.ma.ravel(data[:,0]) , np.ma.ravel(data[:,1]) , np.ma.ravel(data[:,2]) )
plt.draw()
return self.scat,
def show(self):
plt.show()
if __name__ == '__main__':
a = AnimatedScatter()
a.ani.save("movie.avi", codec='avi')
a.show()
.avi , , . , . , , matplotlib?
EDIT: ( , ) , .avi , , , .
matplotlib 1.1.1rc Python 2.7.3.