# -*- noplot -*-
# Demo of using multiprocessing for generating data in one process and plotting
# in another.
# Written by Robert Cimrman
from __future__ import print_function
import time
from multiprocessing import Process, Pipe
import numpy as np
import matplotlib
matplotlib.use('GtkAgg')
import matplotlib.pyplot as plt
import gobject
class ProcessPlotter(object):
def __init__(self):
self.x = []
self.y = []
def terminate(self):
plt.close('all')
def poll_draw(self):
def call_back():
while 1:
if not self.pipe.poll():
break
command = self.pipe.recv()
if command is None:
self.terminate()
return False
else:
self.x.append(command[0])
self.y.append(command[1])
self.ax.plot(self.x, self.y, 'ro')
self.fig.canvas.draw()
return True
return call_back
def __call__(self, pipe):
print('starting plotter...')
self.pipe = pipe
self.fig, self.ax = plt.subplots()
self.gid = gobject.timeout_add(1000, self.poll_draw())
print('...done')
plt.show()
class NBPlot(object):
def __init__(self):
self.plot_pipe, plotter_pipe = Pipe()
self.plotter = ProcessPlotter()
self.plot_process = Process(target=self.plotter,
args=(plotter_pipe,))
self.plot_process.daemon = True
self.plot_process.start()
def plot(self, finished=False):
send = self.plot_pipe.send
if finished:
send(None)
else:
data = np.random.random(2)
send(data)
def main():
pl = NBPlot()
for ii in range(10):
pl.plot()
time.sleep(0.5)
raw_input('press Enter...')
pl.plot(finished=True)
if __name__ == '__main__':
main()
Keywords: python, matplotlib, pylab, example, codex (see Search examples)