I'm trying to make plots in a Jupyter Notebook that update every second or so. Right now, I just have a simple code which is working:
%matplotlib inline
import time
import pylab as plt
import numpy as np
from IPython import display
for i in range(10):
plt.close()
a = np.random.randint(100,size=100)
b = np.random.randint(100,size=100)
fig, ax = plt.subplots(2,1)
ax[0].plot(a)
ax[0].set_title('A')
ax[1].plot(b)
ax[1].set_title('B')
display.clear_output(wait=True)
display.display(plt.gcf())
time.sleep(1.0)
Which updated the plots I have created every second. However, at the end, there is an extra copy of the plots:
Why is it doing this? And how can I make this not happen? Thank you in advance.
The inline backend is set-up so that when each cell is finished executing, any matplotlib plot created in the cell will be displayed.
You are displaying your figure once using the display function, and then the figure is being displayed again automatically by the inline backend.
The easiest way to prevent this is to add plt.close() at the end of the code in your cell.
Another alternative would be to add ; at the end of the line! I am experiencing the same issue with statsmodels methods to plot the autocorrelation of a time series (statsmodels.graphics.tsaplot.plot_acf()):
from statsmodels.graphics.tsaplots import plot_acf
plot_acf(daily_outflow["count"]);
Despite using %matplotlib inline, it's not working for some libraries, such as statsmodels. I recommend always use plt.show() at the end of your code.
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've implemented a GUI that displays two dropdown menus in which you can choose two different set of graphs to be displayed. However when I create the graphs with the following code:
import matplotlib.pyplot as plt
from matplotlib.backends.backedn_qt4agg import FigureCanvasQTAgg as FigureCanvas
self.comparison_figure1 = plt.figure(figsize=(15,5))
self.comparison_canvas1 = FigureCanvas(self.comparison_figure1)
self.comparison_figure2 = plt.figure(figsize=15,5))
self.comparison_canvas2 = FigureCanvas(self.comparison_figure2)
And then I try to update the plots (plt.tight_layout() for example)
def on_resize(event):
plt.tight_layout()
self.comparison_canvas2.draw()
self.comparison_canvas1.draw() #this would do nothing
cid = self.comparison_canvas2.mpl_connect('resize_event', on_resize)
only the last plot called with "plt." is updated. How do I write my code so that I can reference both plots.
I've also tried to create one plot where I have both graphs being displayed side by side but because of the need to update the graphs independently I encountered more problems. If you are able to make it work that way instead, great! I'm just thinking that fixing the previous problem may be simpler.
If you need more code I can post it!
#
#
Solution (Thanks to ImportanceOfBeingErnest and Ash Sharma):
replace any "plt." with the specific figure
for example:
plt.tight_layout() #replace with self.comparison_figure1.tight_layout()
So this is some of the fixed code:
def on_resize(event):
self.comparison_figure1.tight_layout()
self.comparison_figure2.tight_layout()
self.comparison_canvas1.draw()
self.comparison_canvas2.draw()
cid = self.comparison_canvas2.mpl_connect('resize_event', on_resize)
#
#
Problem:
Previous solution hasn't fixed all plot updating issues. Though "plt" can be replaced with self.comparison_figure1 when using tight_layout(), the same cannot be done when using cla() to clear the plot.
Code where I'm using cla():
sns.set(style="whitegrid")
plt.cla()
ax = self.comparison_figure2.add_subplot(111)
.....
.....
I can post more code if you need it!
Solution (Thanks to ImportanceOfBeingErnest and Ash Sharma):
replace any plt with the specific figure
for example:
plt.tight_layout() #replace with self.comparison_figure1.tight_layout()
So this is some of the fixed code:
def on_resize(event):
self.comparison_figure1.tight_layout()
self.comparison_figure2.tight_layout()
self.comparison_canvas1.draw()
self.comparison_canvas2.draw()
cid = self.comparison_canvas2.mpl_connect('resize_event', on_resize)
I want to display an animation in Jupyter using Matplotlib. Here is some basic example:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig, ax = plt.subplots()
line, = ax.plot(np.random.rand(10))
ax.set_ylim(0, 1)
def update(data):
line.set_ydata(data)
return line,
def data_gen():
while True:
yield np.random.rand(10)
ani = animation.FuncAnimation(fig, update, data_gen, interval=100);
from IPython.display import HTML
HTML(ani.to_jshtml())
When I run the code for the first time (or after restarting the kernel) I get what I want:
However, when I run the very same code for the second time I get a leftover in the left bottom:
I noticed that when I add %matplotlib inline at the top, then I got the bad output even after restarting the kernel. Thus my guess is that I have to set the magic command %matplotlib to default at the top each time I create an animation, but I can't even find if %matplotlib have a default value.
I use Anaconda. Here are my versions:
Conda version: 4.4.10
Python version: Python 3.6.4 :: Anaconda, Inc.
IPython version: 6.2.1
Jupyter version: 5.4.0
I used plt.close() to stop the first (unwanted) plot, and have not seen issues running the animation in a separate cell. I believe the issue is similar to those linked in the comments, jupyter is automatically displaying an unwanted plot for the first two lines - fig, ax = plt.subplots()
line, = ax.plot(np.random.rand(10)). I tired suggestions such as using semicolons at end of lines and a few different magic attempts, but no joy. A more concrete solution will no doubt appear, but for now....
I'm trying to create an animated histogram for work, using matplotlib.animation, but animation.FuncAnimation is not functioning properly : when using this code, that i found on the official documentation,
"""
A simple example of an animated plot
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig, ax = plt.subplots()
x = np.arange(0, 2*np.pi, 0.01)
line, = ax.plot(x, np.sin(x))
def animate(i):
print(i)
line.set_ydata(np.sin(x + i/10.0)) # update the data
return line,
# Init only required for blitting to give a clean slate.
def init():
line.set_ydata(np.ma.array(x, mask=True))
return line,
ani = animation.FuncAnimation(fig, animate, np.arange(1, 200),init_func=init,interval=25, blit=True)
plt.show()
I get as final result the graph created by init() function (an empty graph also), but no animate iterations. Furthermore, I tested other codes, which practically gave me the same result : i get the initialization, or the first frame, but not more. matplotlib and matplotlib.animation are installed, everything seems to be ok, except it doesn't work. Have someone an idea how to fix it ? (Thank you in advance :) !)
I had the same issue working with Jupyter notebook and I solved it by inserting the line
%matplotlib notebook
in the code.
It may be that IPython inside your Spyder is configured to automatically use the inline backend. This would show your plots inside the console as png images. Of course png images cannot be animated.
I would suggest not to use IPython but execute the script in a dedicated Python console. In Spyder, go to Run/Configure.. and set the option to new dedicated Python console.
I am trying to use the ipython in canopy with matplotlib to prepare graphs (backend set to qt). I wrote the following code line by line int the terminal
import matplotlib.pyplot as plt
fig = plt.figure()
s = fig.add_subplot(1,1,1)
after the second line I can see the figure being made. However after the third line I do not see the sub plot being created. However If I print fig, the sub-plot is can be seen both inline and in the figure window created. This sub-plot also magically appears if I try to zoom. Similar thing happens every time i plot something on the figure. The old version is displayed till I either print the figure or if i try to modify the view using the GUI tools. This is really annoying. It would be great if someone could tell me where the problem is.
Edit: Tried using fig.show() which does not work. Also when I use the plt.plot() directly, there seems to be no problem. The problem comes only when i use fig or any of its subplots
type:
fig.show() when you need to update it.
you should try using fig.canvas.draw() instead of using fig.show() when it comes to interactive plots.
import matplotlib.pyplot as plt
fig = plt.figure()
fig.show()
## should show an empty figure ##
s = fig.add_subplot(1,1,1)
fig.show()
## things stay unchanged ##
fig.canvas.draw()
## things should be OK now ##