Simple matplotlib plot. Here is my code
from matplotlib import pyplot as plt
from matplotlib.animation import FuncAnimation
from itertools import count
import random
x = []
y = []
index=count()
def animate(i):
x.append(next(index))
y.append(random.randint(0,10))
plt.plot(x,y)
a = FuncAnimation(plt.gcf(),animate,interval=1000)
plt.tight_layout()
plt.show()
Running the code above I get
<Figure size 576x396 with 0 Axes>
but no chart appears.
Are you using Jupyter notebooks to run it? I tried with native libraries and it works just fine. The plots are visible.
Checking here i see the same situation. Could you try to use %matplotlib inline before importing matplotlib as:
%matplotlib inline # this line before importing matplotlib
from matplotlib import pyplot as plt
That said, the animation can be displayed using JavaScript. This is similar to the ani.to_html5() solution, except that it does not require any video codecs.
from IPython.display import HTML
HTML(a.to_jshtml())
this answer brings a more complete overview...
Related
I am working on a project that involves generating a matplotlib animation using pyplot.imshow for the frames. I am doing this in a jupyter notebook. I have managed to get it working, but there is one annoying bug (or feature?) left. After the animation is created, Jupyter shows the last frame of the animation in the output cell. I would like the output to include the animation, captured as html, but not this final frame. Here is a simple example:
import numpy as np
from matplotlib import animation
from IPython.display import HTML
grid = np.zeros((10,10),dtype=int)
fig1 = plt.figure(figsize=(8,8))
ax1 = fig1.add_subplot(1,1,1)
def animate(i):
grid[i,i]=1
ax1.imshow(grid)
return
ani = animation.FuncAnimation(fig1, animate,frames=10);
html = HTML(ani.to_jshtml())
display(html)
I can use the capture magic, but that suppresses everything. This would be OK, but my final goal is to make this public, via binder, and make it as simple as possible for students to use.
I have seen matplotlib animations on the web that don't seem to have this problems, but those used plot, rather than imshow, which might be an issue.
Any suggestions would be greatly appreciated.
Thanks,
David
That's the answer I got from the same thing I was looking for in 'jupyter lab'. Just add plt.close().
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
from IPython.display import HTML
grid = np.zeros((10,10),dtype=int)
fig1 = plt.figure(figsize=(8,8))
ax1 = fig1.add_subplot(1,1,1)
def animate(i):
grid[i,i]=1
ax1.imshow(grid)
return
ani = animation.FuncAnimation(fig1, animate,frames=10);
html = HTML(ani.to_jshtml())
display(html)
plt.close() # update
I recently used jupyter lab instead of jupyter notebook.
But the following code can't work expectations.
import matplotlib.pyplot as plt
import numpy as np
from tqdm.notebook import tqdm, trange
#%matplotlib widget # For jupyter lab
%matplotlib notebook # For jupyter notebook
plt.ion()
fig, ax = plt.subplots()
xs = []
for i in trange(100):
x = i / 10
xs.append(x)
ax.clear()
ax.plot(xs, np.sin(xs))
fig.canvas.draw()
It works on the jupyter notebook, the plot will update dynamically.
But It doesn't work on the jupyter lab.
Of cause, the magic code of %matplotlib is changed on the individual environment.
By the way, I know another method to plot dynamically.
This method also work jupyter lab.
But this method can't work tqdm because clear_output will clear progress bar too.
How to avoid this problem instead of the above question?
I seem the below question is more simple than the above question.
import matplotlib.pyplot as plt
import numpy as np
from tqdm.notebook import tqdm, trange
from io import BytesIO
import imageio
from IPython.display import Image, display_png, clear_output
#%matplotlib widget
%matplotlib notebook
plt.ion()
fig, ax = plt.subplots()
xs = []
for i in trange(100):
x = i / 10
xs.append(x)
ax.clear()
ax.plot(xs, np.sin(xs))
io = BytesIO()
fig.savefig(io, format='png')
clear_output(wait=True)
display_png(Image(io.getvalue()))
Updated:
The result of the above script is the following gif.
This plot is dynamically rendering while running the script.
(This script is not complitely because the tqdm progress bar is cleared.
the problem is side effect of IPython.display.clear_output.)
Here's how to create a "stateful" plot in matplotlib and show it in non-interactive mode:
import matplotlib.pyplot as plt
plt.plot([1,2,8])
plt.show()
I am more interested in the "stateless" approach as I wish to embed matplotlib in my own python library. The same plot can be constructed "statelessly" as follows:
from matplotlib.figure import Figure
fig = Figure()
ax = fig.subplots()
lines = ax.plot([1,2,8])
However I don't know how to show it without resorting to pyplot , which I don't want to do as I would like to build up my own display mechanism.
How do I show the figure without resorting to pyplot?
I am trying to use IPython notebook on MacOS X with Python 2.7.2 and IPython 1.1.0.
I cannot get matplotlib graphics to show up inline.
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
I have also tried %pylab inline and the ipython command line arguments --pylab=inline but this makes no difference.
x = np.linspace(0, 3*np.pi, 500)
plt.plot(x, np.sin(x**2))
plt.title('A simple chirp')
plt.show()
Instead of inline graphics, I get this:
<matplotlib.figure.Figure at 0x110b9c450>
And matplotlib.get_backend() shows that I have the 'module://IPython.kernel.zmq.pylab.backend_inline' backend.
I used %matplotlib inline in the first cell of the notebook and it works. I think you should try:
%matplotlib inline
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
You can also always start all your IPython kernels in inline mode by default by setting the following config options in your config files:
c.IPKernelApp.matplotlib=<CaselessStrEnum>
Default: None
Choices: ['auto', 'gtk', 'gtk3', 'inline', 'nbagg', 'notebook', 'osx', 'qt', 'qt4', 'qt5', 'tk', 'wx']
Configure matplotlib for interactive use with the default matplotlib backend.
If your matplotlib version is above 1.4, it is also possible to use
IPython 3.x and above
%matplotlib notebook
import matplotlib.pyplot as plt
older versions
%matplotlib nbagg
import matplotlib.pyplot as plt
Both will activate the nbagg backend, which enables interactivity.
Ctrl + Enter
%matplotlib inline
Magic Line :D
See: Plotting with Matplotlib.
Use the %pylab inline magic command.
To make matplotlib inline by default in Jupyter (IPython 3):
Edit file ~/.ipython/profile_default/ipython_config.py
Add line c.InteractiveShellApp.matplotlib = 'inline'
Please note that adding this line to ipython_notebook_config.py would not work.
Otherwise it works well with Jupyter and IPython 3.1.0
I have to agree with foobarbecue (I don't have enough recs to be able to simply insert a comment under his post):
It's now recommended that python notebook isn't started wit the argument --pylab, and according to Fernando Perez (creator of ipythonnb) %matplotlib inline should be the initial notebook command.
See here: http://nbviewer.ipython.org/github/ipython/ipython/blob/1.x/examples/notebooks/Part%203%20-%20Plotting%20with%20Matplotlib.ipynb
I found a workaround that is quite satisfactory. I installed Anaconda Python and this now works out of the box for me.
I did the anaconda install but matplotlib is not plotting
It starts plotting when i did this
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
I had the same problem when I was running the plotting commands in separate cells in Jupyter:
In [1]: %matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
In [2]: x = np.array([1, 3, 4])
y = np.array([1, 5, 3])
In [3]: fig = plt.figure()
<Figure size 432x288 with 0 Axes> #this might be the problem
In [4]: ax = fig.add_subplot(1, 1, 1)
In [5]: ax.scatter(x, y)
Out[5]: <matplotlib.collections.PathCollection at 0x12341234> # CAN'T SEE ANY PLOT :(
In [6]: plt.show() # STILL CAN'T SEE IT :(
The problem was solved by merging the plotting commands into a single cell:
In [1]: %matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
In [2]: x = np.array([1, 3, 4])
y = np.array([1, 5, 3])
In [3]: fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.scatter(x, y)
Out[3]: <matplotlib.collections.PathCollection at 0x12341234>
# AND HERE APPEARS THE PLOT AS DESIRED :)
You can simulate this problem with a syntax mistake, however, %matplotlib inline won't resolve the issue.
First an example of the right way to create a plot. Everything works as expected with the imports and magic that eNord9 supplied.
df_randNumbers1 = pd.DataFrame(np.random.randint(0,100,size=(100, 6)), columns=list('ABCDEF'))
df_randNumbers1.ix[:,["A","B"]].plot.kde()
However, by leaving the () off the end of the plot type you receive a somewhat ambiguous non-error.
Erronious code:
df_randNumbers1.ix[:,["A","B"]].plot.kde
Example error:
<bound method FramePlotMethods.kde of <pandas.tools.plotting.FramePlotMethods object at 0x000001DDAF029588>>
Other than this one line message, there is no stack trace or other obvious reason to think you made a syntax error. The plot doesn't print.
If you're using Jupyter notebooks in Visual Studio Code (VSCode) then the inline backend doesn't seem to work so you need to specify widget/ipympl (which you may need to install support for e.g. pip install ipympl):
%matplotlib widget
I am trying to use IPython notebook on MacOS X with Python 2.7.2 and IPython 1.1.0.
I cannot get matplotlib graphics to show up inline.
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
I have also tried %pylab inline and the ipython command line arguments --pylab=inline but this makes no difference.
x = np.linspace(0, 3*np.pi, 500)
plt.plot(x, np.sin(x**2))
plt.title('A simple chirp')
plt.show()
Instead of inline graphics, I get this:
<matplotlib.figure.Figure at 0x110b9c450>
And matplotlib.get_backend() shows that I have the 'module://IPython.kernel.zmq.pylab.backend_inline' backend.
I used %matplotlib inline in the first cell of the notebook and it works. I think you should try:
%matplotlib inline
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
You can also always start all your IPython kernels in inline mode by default by setting the following config options in your config files:
c.IPKernelApp.matplotlib=<CaselessStrEnum>
Default: None
Choices: ['auto', 'gtk', 'gtk3', 'inline', 'nbagg', 'notebook', 'osx', 'qt', 'qt4', 'qt5', 'tk', 'wx']
Configure matplotlib for interactive use with the default matplotlib backend.
If your matplotlib version is above 1.4, it is also possible to use
IPython 3.x and above
%matplotlib notebook
import matplotlib.pyplot as plt
older versions
%matplotlib nbagg
import matplotlib.pyplot as plt
Both will activate the nbagg backend, which enables interactivity.
Ctrl + Enter
%matplotlib inline
Magic Line :D
See: Plotting with Matplotlib.
Use the %pylab inline magic command.
To make matplotlib inline by default in Jupyter (IPython 3):
Edit file ~/.ipython/profile_default/ipython_config.py
Add line c.InteractiveShellApp.matplotlib = 'inline'
Please note that adding this line to ipython_notebook_config.py would not work.
Otherwise it works well with Jupyter and IPython 3.1.0
I have to agree with foobarbecue (I don't have enough recs to be able to simply insert a comment under his post):
It's now recommended that python notebook isn't started wit the argument --pylab, and according to Fernando Perez (creator of ipythonnb) %matplotlib inline should be the initial notebook command.
See here: http://nbviewer.ipython.org/github/ipython/ipython/blob/1.x/examples/notebooks/Part%203%20-%20Plotting%20with%20Matplotlib.ipynb
I found a workaround that is quite satisfactory. I installed Anaconda Python and this now works out of the box for me.
I did the anaconda install but matplotlib is not plotting
It starts plotting when i did this
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
I had the same problem when I was running the plotting commands in separate cells in Jupyter:
In [1]: %matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
In [2]: x = np.array([1, 3, 4])
y = np.array([1, 5, 3])
In [3]: fig = plt.figure()
<Figure size 432x288 with 0 Axes> #this might be the problem
In [4]: ax = fig.add_subplot(1, 1, 1)
In [5]: ax.scatter(x, y)
Out[5]: <matplotlib.collections.PathCollection at 0x12341234> # CAN'T SEE ANY PLOT :(
In [6]: plt.show() # STILL CAN'T SEE IT :(
The problem was solved by merging the plotting commands into a single cell:
In [1]: %matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
In [2]: x = np.array([1, 3, 4])
y = np.array([1, 5, 3])
In [3]: fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.scatter(x, y)
Out[3]: <matplotlib.collections.PathCollection at 0x12341234>
# AND HERE APPEARS THE PLOT AS DESIRED :)
You can simulate this problem with a syntax mistake, however, %matplotlib inline won't resolve the issue.
First an example of the right way to create a plot. Everything works as expected with the imports and magic that eNord9 supplied.
df_randNumbers1 = pd.DataFrame(np.random.randint(0,100,size=(100, 6)), columns=list('ABCDEF'))
df_randNumbers1.ix[:,["A","B"]].plot.kde()
However, by leaving the () off the end of the plot type you receive a somewhat ambiguous non-error.
Erronious code:
df_randNumbers1.ix[:,["A","B"]].plot.kde
Example error:
<bound method FramePlotMethods.kde of <pandas.tools.plotting.FramePlotMethods object at 0x000001DDAF029588>>
Other than this one line message, there is no stack trace or other obvious reason to think you made a syntax error. The plot doesn't print.
If you're using Jupyter notebooks in Visual Studio Code (VSCode) then the inline backend doesn't seem to work so you need to specify widget/ipympl (which you may need to install support for e.g. pip install ipympl):
%matplotlib widget