blocks|key|515907|text|这有可怕的闪烁，但至少这为我创造了一个生动的情节。它是基于Aron的，但Aron的不能按原样工作。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|515908|import+time,+sys
from+IPython.core.display+import+clear_output
f,+ax+=+plt.subplots()

n+=+30
x+=+array([i/10.0+for+i+in+range(n)])
y+=+array([sin(i)+for+i+in+x])
for+i+in+range(5,n):
++ax.plot(x[:i],y[:i])
++time.sleep(0.1)
++clear_output()
++display(f)
++ax.cla()+#+turn+this+off+if+you'd+like+to+"build+up"+plots
plt.close()|code-block|syntax|javascript|515909|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|$]]

This has horrible flickering, but at least this creates a plot that animates for me. It is based on Aron's, but Aron's does not work as-is.

<pre><code>import time, sys
from IPython.core.display import clear_output
f, ax = plt.subplots()

n = 30
x = array([i/10.0 for i in range(n)])
y = array([sin(i) for i in x])
for i in range(5,n):
 ax.plot(x[:i],y[:i])
 time.sleep(0.1)
 clear_output()
 display(f)
 ax.cla() # turn this off if you'd like to "build up" plots
plt.close()
</code></pre>

blocks|key|515939|text|如果您使用IPython+notebook，则v2.0及更高版本支持interactive+widgets。您可以找到一个很好的示例notebook+here+(注意：你需要下载并从你自己的机器上运行才能看到滑块)。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|515940|它本质上归结为导入interact，然后向它传递一个函数，以及参数的范围。例如，从第二个链接：|style|CODE|515941|In+[8]:
def+pltsin(f,+a):
++++plot(x,a*sin(2*pi*x*f))
++++ylim(-10,10)
In+[9]:
interact(pltsin,+f=(1,10,0.1),+a=(1,10,1));|code-block|syntax|javascript|515942|这将为f和a生成一个带有两个滑块的绘图。|515943|entityMap|0|LINK|mutability|MUTABLE|url|http://nbviewer.ipython.org/github/ipython/ipython/blob/2.x/examples/Interactive%2520Widgets/Index.ipynb|1|http://earthpy.org/pyncview_pm.html^0|Y|J|0|23|4|1|0|9|8|0|0|3|1|5|1|0^^$0|@$1|2|3|4|5|6|7|Y|8|@]|9|@$A|Z|B|10|1|11]|$A|12|B|13|1|14]]|C|$]]|$1|D|3|E|5|6|7|15|8|@$A|16|B|17|F|G]]|9|@]|C|$]]|$1|H|3|I|5|J|7|18|8|@]|9|@]|C|$K|L]]|$1|M|3|N|5|6|7|19|8|@$A|1A|B|1B|F|G]|$A|1C|B|1D|F|G]]|9|@]|C|$]]|$1|O|3|-4|5|6|7|1E|8|@]|9|@]|C|$]]]|P|$Q|$5|R|S|T|C|$U|V]]|W|$5|R|S|T|C|$U|X]]]]

If you use IPython notebook, v2.0 and above support <a href="http://nbviewer.ipython.org/github/ipython/ipython/blob/2.x/examples/Interactive%20Widgets/Index.ipynb" rel="noreferrer">interactive widgets</a>. You can find a good example notebook <a href="http://earthpy.org/pyncview_pm.html" rel="noreferrer">here</a> (n.b. you need to download and run from your own machine to see the sliders).

It essentially boils down to importing <code>interact</code>, and then passing it a function, along with ranges for the paramters. e.g., from the second link:

<pre><code>In [8]:
def pltsin(f, a):
 plot(x,a*sin(2*pi*x*f))
 ylim(-10,10)
In [9]:
interact(pltsin, f=(1,10,0.1), a=(1,10,1));
</code></pre>

This will produce a plot with two sliders, for <code>f</code> and <code>a</code>.

blocks|key|516102|text|IPython+widgets允许您使用Notebook中的图形用户界面对象来操作内核中的Python对象。你可能也会喜欢Sage+hosted+IPython+Notebooks。在笔记本中共享小部件或交互性可能会遇到一个问题，那就是如果其他人没有IPython，他们就无法运行您的工作。为了解决这个问题，您可以使用Domino来share+Notebooks其他人可以运行的小部件。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|516103|下面是您可以在Notebook中使用pandas过滤数据、分形和3D绘图滑块的三个小部件示例。了解更多信息并查看代码和Notebook+here。|516104|​|516105|516106|516107|516108|📷|atomic|516109|516110|516111|516112|516113|516114|516115|516116|516117|516118|516119|516120|516121|516122|516123|516124|516125|如果您想要实况流数据或设置模拟作为循环运行，您还可以stream+data到笔记本中的绘图。免责声明:我为Plotly工作。|516126|entityMap|0|LINK|mutability|MUTABLE|url|https://ipython.org/ipython-doc/dev/whatsnew/version2.0.html#interactive-widgets|1|http://sagemath.blogspot.com/2013/09/ipython-notebooks-in-cloud-with.html|2|http://blog.dominodatalab.com/interactive-charts-with-plotly-and-domino/|3|http://moderndata.plot.ly/widgets-in-ipython-notebook-and-plotly/|4|IMAGE|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/1984c5963015e4fc4503653d160722a1.gif|imageAlt|5|https://ask.qcloudimg.com/http-save/yehe-900000/4fd7b0e89dde64c8aeb048ab2413abd7.gif|6|https://ask.qcloudimg.com/http-save/yehe-900000/64574d38bbda489ca6cdfd1ac4144051.gif|7|https://plot.ly/python/streaming-tutorial/^0|0|F|0|1U|O|1|4M|F|2|0|1W|4|3|0|0|0|0|0|0|1|4|0|0|0|0|0|0|0|1|5|0|0|0|0|0|0|0|1|6|0|0|0|0|0|Q|B|7|0^^$0|@$1|2|3|4|5|6|7|1V|8|@]|9|@$A|1W|B|1X|1|1Y]|$A|1Z|B|20|1|21]|$A|22|B|23|1|24]]|C|$]]|$1|D|3|E|5|6|7|25|8|@]|9|@$A|26|B|27|1|28]]|C|$]]|$1|F|3|G|5|6|7|29|8|@]|9|@]|C|$]]|$1|H|3|G|5|6|7|2A|8|@]|9|@]|C|$]]|$1|I|3|G|5|6|7|2B|8|@]|9|@]|C|$]]|$1|J|3|G|5|6|7|2C|8|@]|9|@]|C|$]]|$1|K|3|L|5|M|7|2D|8|@]|9|@$A|2E|B|2F|1|2G]]|C|$]]|$1|N|3|G|5|6|7|2H|8|@]|9|@]|C|$]]|$1|O|3|G|5|6|7|2I|8|@]|9|@]|C|$]]|$1|P|3|G|5|6|7|2J|8|@]|9|@]|C|$]]|$1|Q|3|G|5|6|7|2K|8|@]|9|@]|C|$]]|$1|R|3|G|5|6|7|2L|8|@]|9|@]|C|$]]|$1|S|3|L|5|M|7|2M|8|@]|9|@$A|2N|B|2O|1|2P]]|C|$]]|$1|T|3|G|5|6|7|2Q|8|@]|9|@]|C|$]]|$1|U|3|G|5|6|7|2R|8|@]|9|@]|C|$]]|$1|V|3|G|5|6|7|2S|8|@]|9|@]|C|$]]|$1|W|3|G|5|6|7|2T|8|@]|9|@]|C|$]]|$1|X|3|G|5|6|7|2U|8|@]|9|@]|C|$]]|$1|Y|3|L|5|M|7|2V|8|@]|9|@$A|2W|B|2X|1|2Y]]|C|$]]|$1|Z|3|G|5|6|7|2Z|8|@]|9|@]|C|$]]|$1|10|3|G|5|6|7|30|8|@]|9|@]|C|$]]|$1|11|3|G|5|6|7|31|8|@]|9|@]|C|$]]|$1|12|3|G|5|6|7|32|8|@]|9|@]|C|$]]|$1|13|3|14|5|6|7|33|8|@]|9|@$A|34|B|35|1|36]]|C|$]]|$1|15|3|-4|5|6|7|37|8|@]|9|@]|C|$]]]|16|$17|$5|18|19|1A|C|$1B|1C]]|1D|$5|18|19|1A|C|$1B|1E]]|1F|$5|18|19|1A|C|$1B|1G]]|1H|$5|18|19|1A|C|$1B|1I]]|1J|$5|1K|19|1L|C|$1M|1N|1O|-4]]|1P|$5|1K|19|1L|C|$1M|1Q|1O|-4]]|1R|$5|1K|19|1L|C|$1M|1S|1O|-4]]|1T|$5|18|19|1A|C|$1B|1U]]]]

<a href="https://ipython.org/ipython-doc/dev/whatsnew/version2.0.html#interactive-widgets" rel="noreferrer">IPython widgets</a> let you manipulate Python objects in the kernel with GUI objects in the Notebook. You might also like Sage <a href="http://sagemath.blogspot.com/2013/09/ipython-notebooks-in-cloud-with.html" rel="noreferrer">hosted IPython Notebooks</a>. One problem you might have with sharing widgets or interactivity in Notebooks is that if someone else doesn't have IPython, they can't run your work. To solve that, you can use Domino to <a href="http://blog.dominodatalab.com/interactive-charts-with-plotly-and-domino/" rel="noreferrer">share Notebooks</a> with widgets that others can run.
Below are three examples of widgets you can build in a Notebook using pandas to filter data, fractals, and a slider for a 3D plot. Learn more and see the code and Notebooks <a href="http://moderndata.plot.ly/widgets-in-ipython-notebook-and-plotly/" rel="noreferrer">here</a>.
 
 
 
<img src="https://i.stack.imgur.com/Q0oMy.gif" alt="enter image description here" />
 
 
 
<img src="https://i.stack.imgur.com/DcbA7.gif" alt="enter image description here" />
 
 
 
<img src="https://i.stack.imgur.com/cN9Ip.gif" alt="enter image description here" />
 
 
 
If you want to live-stream data or set up a simulation to run as a loop, you can also <a href="https://plot.ly/python/streaming-tutorial/" rel="noreferrer">stream data</a> into plots in a Notebook. Disclaimer: I work for Plotly.

blocks|key|299528|text|在@goger关于“可怕的闪烁”的评论中，我发现调用clear_output(wait=True)解决了我的问题。该标志告诉clear_output等待渲染，直到它有新的东西要渲染。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|299529|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

On @goger's comment of 'horrible flickering', I found that calling clear_output(wait=True) solved my problem. The flag tells clear_output to wait to render till it has something new to render.

blocks|key|299563|text|bqplot是现在这样做的一个非常好的选择。它是通过笔记本中的python专门为动画构建的。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|299564|https://github.com/bloomberg/bqplot|offset|length|299565|entityMap|0|LINK|mutability|MUTABLE|url^0|0|0|Z|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|N|8|@]|9|@$D|O|E|P|1|Q]]|A|$]]|$1|F|3|-4|5|6|7|R|8|@]|9|@]|A|$]]]|G|$H|$5|I|J|K|A|$L|C]]]]

bqplot is a really good option to do this now. its built specifically for animation through python in the notebook

<a href="https://github.com/bloomberg/bqplot" rel="nofollow noreferrer">https://github.com/bloomberg/bqplot</a>

blocks|key|299628|text|如果你想要3D散点图动画，Ipyvolume+Jupyter小部件是非常令人印象深刻的。http://ipyvolume.readthedocs.io/en/latest/animation.html#|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|299629|entityMap|0|LINK|mutability|MUTABLE|url|http://ipyvolume.readthedocs.io/en/latest/animation.html#^0|18|1L|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

If you want 3D scatter plot animations, the Ipyvolume Jupyter widget is very impressive. 
<a href="http://ipyvolume.readthedocs.io/en/latest/animation.html#" rel="nofollow noreferrer">http://ipyvolume.readthedocs.io/en/latest/animation.html#</a>

Is there a way of creating animated graphs. For example showing the same graph, with different parameters.

For example is SAGE notebook, one can write:

<pre><code>a = animate([circle((i,i), 1-1/(i+1), hue=i/10) for i in srange(0,2,0.2)], 
 xmin=0,ymin=0,xmax=2,ymax=2,figsize=[2,2])
a.show()
</code></pre>

Animated graphs in ipython notebook

流数据

Python

有没有一种方法可以创建动画图形。例如，使用不同的参数显示相同的图形。例如SAGE notebook，你可以这样写：a = animate([circle((i,i), 1-1/(i+1), hue=i/10) for i in srange(0,2,0.2)],             xmin=0,ymin=0,xm...

问ipython notebook中的动画图形
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