在Python解释器中的这些指令之后,你会看到一个带有图形的窗口:
from matplotlib.pyplot import *
plot([1,2,3])
show()
# other code
不幸的是,我不知道如何在程序进行进一步计算时继续交互式地探索show()创建的图形。
这可能吗?有时计算很长,如果在检查中间结果时进行计算将会有所帮助。
在Python解释器中的这些指令之后,你会看到一个带有图形的窗口:
from matplotlib.pyplot import *
plot([1,2,3])
show()
# other code
不幸的是,我不知道如何在程序进行进一步计算时继续交互式地探索show()创建的图形。
这可能吗?有时计算很长,如果在检查中间结果时进行计算将会有所帮助。
当前回答
在我的系统上,show()没有阻塞,尽管我希望脚本在继续之前等待用户与图形交互(并使用'pick_event'回调来收集数据)。
为了阻止执行直到绘图窗口关闭,我使用了以下方法:
fig = plt.figure()
ax = fig.add_subplot(1,1,1)
ax.plot(x,y)
# set processing to continue when window closed
def onclose(event):
fig.canvas.stop_event_loop()
fig.canvas.mpl_connect('close_event', onclose)
fig.show() # this call does not block on my system
fig.canvas.start_event_loop_default() # block here until window closed
# continue with further processing, perhaps using result from callbacks
但是请注意,canvas.start_event_loop_default()产生了以下警告:
C:\Python26\lib\site-packages\matplotlib\backend_bases.py:2051: DeprecationWarning: Using default event loop until function specific to this GUI is implemented
warnings.warn(str,DeprecationWarning)
尽管脚本仍然在运行。
其他回答
如果你想打开多个图形,同时保持它们全部打开,这段代码适合我:
show(block=False)
draw()
如果你在控制台工作,即IPython,你可以使用plt.show(block=False),正如在其他答案中指出的那样。但如果你很懒,你可以输入:
plt.show(0)
这是一样的。
下面是我找到的最简单的解决方案(线程阻塞代码)
plt.show(block=False) # this avoids blocking your thread
plt.pause(1) # comment this if you do not want a time delay
# do more stuff
plt.show(block=True) # this prevents the window from closing on you
Try
import matplotlib.pyplot as plt
plt.plot([1,2,3])
plt.show(block=False)
# other code
# [...]
# Put
plt.show()
# at the very end of your script to make sure Python doesn't bail out
# before you finished examining.
show()文档说:
在非交互模式下,显示所有图形并阻塞直到图形关闭;在交互模式下,除非在从非交互模式切换到交互模式之前创建了图形,否则没有效果(不推荐)。在这种情况下,它会显示数字,但不会阻塞。 单个实验关键字参数block可以被设置为True或False以覆盖上面描述的阻塞行为。
嗯,我在搞清楚非阻塞命令方面遇到了很大的困难……但最后,我成功地重做了“Cookbook/Matplotlib/Animations -动画选定的绘图元素”的例子,所以它可以在Ubuntu 10.04的Python 2.6.5上与线程一起工作(并通过全局变量或多进程管道在线程之间传递数据)。
脚本可以在这里找到:Animating_selected_plot_elements-thread.py -否则粘贴在下面(注释更少)以供参考:
import sys
import gtk, gobject
import matplotlib
matplotlib.use('GTKAgg')
import pylab as p
import numpy as nx
import time
import threading
ax = p.subplot(111)
canvas = ax.figure.canvas
# for profiling
tstart = time.time()
# create the initial line
x = nx.arange(0,2*nx.pi,0.01)
line, = ax.plot(x, nx.sin(x), animated=True)
# save the clean slate background -- everything but the animated line
# is drawn and saved in the pixel buffer background
background = canvas.copy_from_bbox(ax.bbox)
# just a plain global var to pass data (from main, to plot update thread)
global mypass
# http://docs.python.org/library/multiprocessing.html#pipes-and-queues
from multiprocessing import Pipe
global pipe1main, pipe1upd
pipe1main, pipe1upd = Pipe()
# the kind of processing we might want to do in a main() function,
# will now be done in a "main thread" - so it can run in
# parallel with gobject.idle_add(update_line)
def threadMainTest():
global mypass
global runthread
global pipe1main
print "tt"
interncount = 1
while runthread:
mypass += 1
if mypass > 100: # start "speeding up" animation, only after 100 counts have passed
interncount *= 1.03
pipe1main.send(interncount)
time.sleep(0.01)
return
# main plot / GUI update
def update_line(*args):
global mypass
global t0
global runthread
global pipe1upd
if not runthread:
return False
if pipe1upd.poll(): # check first if there is anything to receive
myinterncount = pipe1upd.recv()
update_line.cnt = mypass
# restore the clean slate background
canvas.restore_region(background)
# update the data
line.set_ydata(nx.sin(x+(update_line.cnt+myinterncount)/10.0))
# just draw the animated artist
ax.draw_artist(line)
# just redraw the axes rectangle
canvas.blit(ax.bbox)
if update_line.cnt>=500:
# print the timing info and quit
print 'FPS:' , update_line.cnt/(time.time()-tstart)
runthread=0
t0.join(1)
print "exiting"
sys.exit(0)
return True
global runthread
update_line.cnt = 0
mypass = 0
runthread=1
gobject.idle_add(update_line)
global t0
t0 = threading.Thread(target=threadMainTest)
t0.start()
# start the graphics update thread
p.show()
print "out" # will never print - show() blocks indefinitely!
希望这能帮助到一些人, 干杯!