blocks|key|2878630|text|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2878631|有没有一种方法，我可以通过添加更多的点来更新绘图……|blockquote|2878632|2878633|2878634|有许多方法可以在matplotlib中对数据进行动画处理，具体取决于您使用的版本。你看过matplotlib+cookbook的例子吗？另外，请查看matplotlib文档中更新的animation+examples。最后，animation+API定义了一个函数FuncAnimation，它在时间上对函数进行动画处理。这个函数可能只是你用来获取数据的函数。|offset|length|2878635|每个方法基本上都会设置正在绘制的对象的data属性，因此不需要清除屏幕或图形。可以简单地扩展data属性，因此您可以保留前面的点，只需继续添加到您的线条(或图像或您正在绘制的任何内容)。|style|CODE|2878636|既然您说您的数据到达时间不确定，那么您最好的选择可能就是这样做：|2878637|import+matplotlib.pyplot+as+plt
import+numpy

hl,+=+plt.plot([],+[])

def+update_line(hl,+new_data):
++++hl.set_xdata(numpy.append(hl.get_xdata(),+new_data))
++++hl.set_ydata(numpy.append(hl.get_ydata(),+new_data))
++++plt.draw()|code-block|syntax|javascript|2878638|然后，当您从串口接收数据时，只需调用update_line即可。|2878639|entityMap|0|LINK|mutability|MUTABLE|url|http://www.scipy.org/Cookbook/Matplotlib/Animations|1|http://matplotlib.sourceforge.net/examples/animation/index.html|2|http://matplotlib.sourceforge.net/api/animation_api.html|3|http://matplotlib.sourceforge.net/api/animation_api.html#matplotlib.animation.FuncAnimation^0|0|0|0|0|18|J|0|2I|I|1|34|D|2|3O|D|3|0|J|4|1A|4|0|0|0|I|B|0^^$0|@$1|2|3|-4|4|5|6|1A|7|@]|8|@]|9|$]]|$1|A|3|B|4|C|6|1B|7|@]|8|@]|9|$]]|$1|D|3|-4|4|5|6|1C|7|@]|8|@]|9|$]]|$1|E|3|-4|4|5|6|1D|7|@]|8|@]|9|$]]|$1|F|3|G|4|5|6|1E|7|@]|8|@$H|1F|I|1G|1|1H]|$H|1I|I|1J|1|1K]|$H|1L|I|1M|1|1N]|$H|1O|I|1P|1|1Q]]|9|$]]|$1|J|3|K|4|5|6|1R|7|@$H|1S|I|1T|L|M]|$H|1U|I|1V|L|M]]|8|@]|9|$]]|$1|N|3|O|4|5|6|1W|7|@]|8|@]|9|$]]|$1|P|3|Q|4|R|6|1X|7|@]|8|@]|9|$S|T]]|$1|U|3|V|4|5|6|1Y|7|@$H|1Z|I|20|L|M]]|8|@]|9|$]]|$1|W|3|-4|4|5|6|21|7|@]|8|@]|9|$]]]|X|$Y|$4|Z|10|11|9|$12|13]]|14|$4|Z|10|11|9|$12|15]]|16|$4|Z|10|11|9|$12|17]]|18|$4|Z|10|11|9|$12|19]]]]

<blockquote>
 Is there a way in which I can update the plot just by adding more point[s] to it...
</blockquote>

There are a number of ways of animating data in matplotlib, depending on the version you have. Have you seen the <a href="http://www.scipy.org/Cookbook/Matplotlib/Animations">matplotlib cookbook</a> examples? Also, check out the more modern <a href="http://matplotlib.sourceforge.net/examples/animation/index.html">animation examples</a> in the matplotlib documentation. Finally, the <a href="http://matplotlib.sourceforge.net/api/animation_api.html">animation API</a> defines a function <a href="http://matplotlib.sourceforge.net/api/animation_api.html#matplotlib.animation.FuncAnimation">FuncAnimation</a> which animates a function in time. This function could just be the function you use to acquire your data.

Each method basically sets the <code>data</code> property of the object being drawn, so doesn't require clearing the screen or figure. The <code>data</code> property can simply be extended, so you can keep the previous points and just keep adding to your line (or image or whatever you are drawing).

Given that you say that your data arrival time is uncertain your best bet is probably just to do something like:

<pre><code>import matplotlib.pyplot as plt
import numpy

hl, = plt.plot([], [])

def update_line(hl, new_data):
 hl.set_xdata(numpy.append(hl.get_xdata(), new_data))
 hl.set_ydata(numpy.append(hl.get_ydata(), new_data))
 plt.draw()
</code></pre>

Then when you receive data from the serial port just call <code>update_line</code>.

blocks|key|2878654|text|为了在不使用FuncAnimation的情况下执行此操作(例如，您希望在生成绘图时执行代码的其他部分，或者您希望同时更新多个绘图)，单独调用draw不会生成绘图(至少使用qt后端)。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|2878655|下面的方法对我很有效：|2878656|import+matplotlib.pyplot+as+plt
plt.ion()
class+DynamicUpdate():
++++#Suppose+we+know+the+x+range
++++min_x+=+0
++++max_x+=+10

++++def+on_launch(self):
++++++++#Set+up+plot
++++++++self.figure,+self.ax+=+plt.subplots()
++++++++self.lines,+=+self.ax.plot([],[],+'o')
++++++++#Autoscale+on+unknown+axis+and+known+lims+on+the+other
++++++++self.ax.set_autoscaley_on(True)
++++++++self.ax.set_xlim(self.min_x,+self.max_x)
++++++++#Other+stuff
++++++++self.ax.grid()
++++++++...

++++def+on_running(self,+xdata,+ydata):
++++++++#Update+data+(with+the+new+_and_+the+old+points)
++++++++self.lines.set_xdata(xdata)
++++++++self.lines.set_ydata(ydata)
++++++++#Need+both+of+these+in+order+to+rescale
++++++++self.ax.relim()
++++++++self.ax.autoscale_view()
++++++++#We+need+to+draw+*and*+flush
++++++++self.figure.canvas.draw()
++++++++self.figure.canvas.flush_events()

++++#Example
++++def+__call__(self):
++++++++import+numpy+as+np
++++++++import+time
++++++++self.on_launch()
++++++++xdata+=+[]
++++++++ydata+=+[]
++++++++for+x+in+np.arange(0,10,0.5):
++++++++++++xdata.append(x)
++++++++++++ydata.append(np.exp(-x**2)%2B10*np.exp(-(x-7)**2))
++++++++++++self.on_running(xdata,+ydata)
++++++++++++time.sleep(1)
++++++++return+xdata,+ydata

d+=+DynamicUpdate()
d()|code-block|syntax|javascript|2878657|entityMap^0|1Y|4|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|R|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|S|8|@]|D|@]|E|$K|L]]|$1|M|3|-4|5|6|7|T|8|@]|D|@]|E|$]]]|N|$]]

In order to do this without FuncAnimation (eg you want to execute other parts of the code while the plot is being produced or you want to be updating several plots at the same time), calling <code>draw</code> alone does not produce the plot (at least with the qt backend).

The following works for me:

<pre><code>import matplotlib.pyplot as plt
plt.ion()
class DynamicUpdate():
 #Suppose we know the x range
 min_x = 0
 max_x = 10

 def on_launch(self):
 #Set up plot
 self.figure, self.ax = plt.subplots()
 self.lines, = self.ax.plot([],[], 'o')
 #Autoscale on unknown axis and known lims on the other
 self.ax.set_autoscaley_on(True)
 self.ax.set_xlim(self.min_x, self.max_x)
 #Other stuff
 self.ax.grid()
 ...

 def on_running(self, xdata, ydata):
 #Update data (with the new _and_ the old points)
 self.lines.set_xdata(xdata)
 self.lines.set_ydata(ydata)
 #Need both of these in order to rescale
 self.ax.relim()
 self.ax.autoscale_view()
 #We need to draw *and* flush
 self.figure.canvas.draw()
 self.figure.canvas.flush_events()

 #Example
 def __call__(self):
 import numpy as np
 import time
 self.on_launch()
 xdata = []
 ydata = []
 for x in np.arange(0,10,0.5):
 xdata.append(x)
 ydata.append(np.exp(-x**2)+10*np.exp(-(x-7)**2))
 self.on_running(xdata, ydata)
 time.sleep(1)
 return xdata, ydata

d = DynamicUpdate()
d()
</code></pre>

blocks|key|2878714|text|我知道我回答这个问题来晚了，但对于您的问题，您可以查看“操纵杆”包。我设计它是为了绘制来自串行端口的数据流，但它适用于任何数据流。它还允许交互式文本记录或图像绘制(除了图形绘制之外)。不需要在单独的线程中做你自己的循环，包会处理它，只需给出你想要的更新频率。此外，终端在绘图时仍可用于监控命令。请参阅http://www.github.com/ceyzeriat/joystick/或https://pypi.python.org/pypi/joystick+(使用pip+install操纵杆安装)|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|2878715|只需在以下代码中将np.random.random()替换为从串行端口读取的实际数据点：|2878716|import+joystick+as+jk
import+numpy+as+np
import+time

class+test(jk.Joystick):
++++#+initialize+the+infinite+loop+decorator
++++_infinite_loop+=+jk.deco_infinite_loop()

++++def+_init(self,+*args,+**kwargs):
++++++++"""
++++++++Function+called+at+initialization,+see+the+doc
++++++++"""
++++++++self._t0+=+time.time()++#+initialize+time
++++++++self.xdata+=+np.array([self._t0])++#+time+x-axis
++++++++self.ydata+=+np.array([0.0])++#+fake+data+y-axis
++++++++#+create+a+graph+frame
++++++++self.mygraph+=+self.add_frame(jk.Graph(name="test",+size=(500,+500),+pos=(50,+50),+fmt="go-",+xnpts=10000,+xnptsmax=10000,+xylim=(None,+None,+0,+1)))

++++@_infinite_loop(wait_time=0.2)
++++def+_generate_data(self):++#+function+looped+every+0.2+second+to+read+or+produce+data
++++++++"""
++++++++Loop+starting+with+the+simulation+start,+getting+data+and
++++pushing+it+to+the+graph+every+0.2+seconds
++++++++"""
++++++++#+concatenate+data+on+the+time+x-axis
++++++++self.xdata+=+jk.core.add_datapoint(self.xdata,+time.time(),+xnptsmax=self.mygraph.xnptsmax)
++++++++#+concatenate+data+on+the+fake+data+y-axis
++++++++self.ydata+=+jk.core.add_datapoint(self.ydata,+np.random.random(),+xnptsmax=self.mygraph.xnptsmax)
++++++++self.mygraph.set_xydata(t,+self.ydata)

t+=+test()
t.start()
t.stop()|code-block|syntax|javascript|2878717|entityMap|0|LINK|mutability|MUTABLE|url|http://www.github.com/ceyzeriat/joystick/|1|https://pypi.python.org/pypi/joystick^0|46|15|0|5C|11|1|0|0|0^^$0|@$1|2|3|4|5|6|7|U|8|@]|9|@$A|V|B|W|1|X]|$A|Y|B|Z|1|10]]|C|$]]|$1|D|3|E|5|6|7|11|8|@]|9|@]|C|$]]|$1|F|3|G|5|H|7|12|8|@]|9|@]|C|$I|J]]|$1|K|3|-4|5|6|7|13|8|@]|9|@]|C|$]]]|L|$M|$5|N|O|P|C|$Q|R]]|S|$5|N|O|P|C|$Q|T]]]]

I know I'm late to answer this question, but for your issue you could look into the "joystick" package. I designed it for plotting a stream of data from the serial port, but it works for any stream. It also allows for interactive text logging or image plotting (in addition to graph plotting).
No need to do your own loops in a separate thread, the package takes care of it, just give the update frequency you wish. Plus the terminal remains available for monitoring commands while plotting.
See <a href="http://www.github.com/ceyzeriat/joystick/" rel="nofollow">http://www.github.com/ceyzeriat/joystick/</a> or <a href="https://pypi.python.org/pypi/joystick" rel="nofollow">https://pypi.python.org/pypi/joystick</a> (use pip install joystick to install)

Just replace np.random.random() by your real data point read from the serial port in the code below:

<pre><code>import joystick as jk
import numpy as np
import time

class test(jk.Joystick):
 # initialize the infinite loop decorator
 _infinite_loop = jk.deco_infinite_loop()

 def _init(self, *args, **kwargs):
 """
 Function called at initialization, see the doc
 """
 self._t0 = time.time() # initialize time
 self.xdata = np.array([self._t0]) # time x-axis
 self.ydata = np.array([0.0]) # fake data y-axis
 # create a graph frame
 self.mygraph = self.add_frame(jk.Graph(name="test", size=(500, 500), pos=(50, 50), fmt="go-", xnpts=10000, xnptsmax=10000, xylim=(None, None, 0, 1)))

 @_infinite_loop(wait_time=0.2)
 def _generate_data(self): # function looped every 0.2 second to read or produce data
 """
 Loop starting with the simulation start, getting data and
 pushing it to the graph every 0.2 seconds
 """
 # concatenate data on the time x-axis
 self.xdata = jk.core.add_datapoint(self.xdata, time.time(), xnptsmax=self.mygraph.xnptsmax)
 # concatenate data on the fake data y-axis
 self.ydata = jk.core.add_datapoint(self.ydata, np.random.random(), xnptsmax=self.mygraph.xnptsmax)
 self.mygraph.set_xydata(t, self.ydata)

t = test()
t.start()
t.stop()
</code></pre>

blocks|key|225588|text|这是一种允许在绘制一定数量的点之后删除点的方法：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|225589|import+matplotlib.pyplot+as+plt
#+generate+axes+object
ax+=+plt.axes()

#+set+limits
plt.xlim(0,10)+
plt.ylim(0,10)

for+i+in+range(10):++++++++
+++++#+add+something+to+axes++++
+++++ax.scatter([i],+[i])+
+++++ax.plot([i],+[i%2B1],+'rx')

+++++#+draw+the+plot
+++++plt.draw()+
+++++plt.pause(0.01)+#is+necessary+for+the+plot+to+update+for+some+reason

+++++#+start+removing+points+if+you+don't+want+all+shown
+++++if+i>2:
+++++++++ax.lines[0].remove()
+++++++++ax.collections[0].remove()|code-block|syntax|javascript|225590|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

Here is a way which allows to remove points after a certain number of points plotted:

<pre><code>import matplotlib.pyplot as plt
# generate axes object
ax = plt.axes()

# set limits
plt.xlim(0,10) 
plt.ylim(0,10)

for i in range(10): 
 # add something to axes 
 ax.scatter([i], [i]) 
 ax.plot([i], [i+1], 'rx')

 # draw the plot
 plt.draw() 
 plt.pause(0.01) #is necessary for the plot to update for some reason

 # start removing points if you don't want all shown
 if i&gt;2:
 ax.lines[0].remove()
 ax.collections[0].remove()
</code></pre>

I am making an application in Python which collects data from a serial port and plots a graph of the collected data against arrival time. The time of arrival for the data is uncertain. I want the plot to be updated when data is received. I searched on how to do this and found two methods:

<ol>
<li>Clear the plot and re-draw the plot with all the points again.</li>
<li>Animate the plot by changing it after a particular interval.</li>
</ol>

I do not prefer the first one as the program runs and collects data for a long time (a day for example), and redrawing the plot will be pretty slow.
The second one is also not preferable as time of arrival of data is uncertain and I want the plot to update only when the data is received.

Is there a way in which I can update the plot just by adding more points to it only when the data is received?

Dynamically updating plot in matplotlib

数据流

Python

我正在用Python编写一个应用程序，它从串行端口收集数据，并根据到达时间绘制收集的数据的图形。数据到达的时间是不确定的。我希望在收到数据时更新绘图。我搜索了一下如何做到这一点，找到了两种方法：清除绘图并重新绘制包含所有点的绘图。通过在特定时间间隔后更改绘图来使其具有动画效果。我不喜欢第一种方法，因为程序运行和收集数据...

问在matplotlib中动态更新绘图
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