I'm trying to plot streaming data in matplotlib. I can update the plot using interactive mode and the set_ydata function. It animates and everything looks good until the loop ends. Then the python kernel crashes and I get this message:
C:\Conda\lib\site-packages\matplotlib\backend_bases.py:2437:
MatplotlibDeprecationWarning: Using default event loop until function specific to
this GUI is implemented
warnings.warn(str, mplDeprecation)
Here's the code:
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(0, 10, 0.1)
y = np.sin(x)
plt.ion() #interactive mode on
ax = plt.gca()
line, = ax.plot(x,y)
ax.set_ylim([-5,5])
for i in np.arange(100):
line.set_ydata(y)
plt.draw()
y = y*1.01
plt.pause(0.1)
Can anyone tell me why this is crashing instead of just exiting the loop? I'm doing this in Jupyter with Python 3. And of course, if there's a better way to do this, I would love to hear about it. Thanks!
This code was adapted from How to update a plot in matplotlib?
It works well for me with mac_osx backend from Jupyter notebook in python 3.4.
Maybe you want to add plt.close() at the end to keep things tidy and prevent a hang up?
Related
So I have been trying to get a plot to update every iteration through a loop. A stripped down version of my code is as follows:
1 import matplotlib.pyplot as plt
2 import numpy as np
3
4 x = np.linspace(0, 9, 10)
5 for j in range(10):
6 y = np.random.random(10)
7 plt.plot(x,y)
8 plt.show()
9 plt.pause(1)
10 plt.clf()
My issue is that I have to close each plot before the next one is created; it seems like the plot is stuck on plt.show(), whereas I expect a new plot to replace the current one every second without needing my interaction. I've consulted the following questions:
When to use cla(), clf() or close() for clearing a plot in matplotlib?
Python plt: close or clear figure does not work
Matplotlib pyplot show() doesn't work once closed
But none of the solutions seemed to work for me. Any help would be appreciated!
You should set interactive mode with plt.ion(), and use draw to update
import matplotlib.pyplot as plt
import numpy as np
plt.ion()
fig=plt.figure()
x = np.linspace(0, 9, 10)
for j in range(10):
y = np.random.random(10)
plt.plot(x,y)
fig.canvas.draw()
plt.pause(1)
plt.clf()
link to tutorial
Note that it might not work on all platforms; I tested on Pythonista/ios, which didn't work as expected.
From
matplotlib tutorial
Note
Interactive mode works with suitable backends in ipython and in the ordinary python shell, but it does not work in the IDLE IDE. If the default backend does not support interactivity, an interactive backend can be explicitly activated using any of the methods discussed in What is a backend?.
I am using Matplotlib on MacOS with Sulime Text.
I use Python 3.5 and Matplotlib 2.0.
When I work on a figure, I usually have a script that plot the data, and save the figure in a .pdf file with plt.savefig(). Then I use Skim (a pdf viewer) in order to refresh the file each time I modify and run the script. This allows me to set my working layout as clean as: there is one window for the script, and one window for the figure which is automatically refreshing.
I would like to do keep the same layout, but using the Matplotlib figures (because they are interactive). I am looking for a way to use plt.show() but always in the same figure that has been created the first time I've run the script.
For instance:
1. First run
import matplotlib.pyplot as plt
import numpy as np
fig, ax = plt.figure()
noise = np.random.rand(1, 100)
ax(noise)
plt.show()
2. Following runs
import matplotlib.pyplot as plt
import numpy as np
# This is the super command I am looking for
fig = plt.get_previous_run_figure()
ax = fig.axes
noise = np.random.rand(1, 100)
ax.plot(noise)
plt.draw()
In that case of course, I would have to do a first-run script separately from the main script. Does anyone know if it is possible ?
You want to have multiple consecutive python sessions share a common Matplotlib window. I see no way to share this windows from separate processes, especially when the original owner may terminate at any point in time.
However, you could do something similar to your current workflow in which you have an external pdf viewer to view a output file which you update from multiple python instances.
See this question/answer on how to pickle a matplotlib figure:
Store and reload matplotlib.pyplot object
In every script, output your matplotlib figure as a pickled object, rather than calling plt.show():
import matplotlib.pyplot as plt
import numpy as np
import pickle
ax = plt.subplot(111)
x = np.linspace(0, 10)
y = np.exp(x)
plt.plot(x, y)
pickle.dump(ax, file('myplot.pickle', 'w'))
Then, start a dedicated python session which loads this pickled object and calls plt.show(). Have this script run in a loop, checking for updates of the pickled file on disk, and reloading when necessary:
import matplotlib.pyplot as plt
import pickle
while True:
ax = pickle.load(file('myplot.pickle'))
plt.show()
Alternative
Instead of having separate python sessions, I usually have a single Ipython session in which I run different script. By selecting the same figure windows, I end up with a mostly similar setup as you describe, in which the same figure window is reused throughout the day.
import matplotlib.pyplot as plt
fig = plt.figure(0)
fig.clf()
plt.show()
In principle establishing a connection between two different scripts could be done using a system-wide clipboard. (As far as I know the clipboard in windows and macos are system-wide.)
So the idea can be to set up an application using tk or pyqt, and implement a generic FigureCanvas. This application could have an event listener for changes in the clipboard.
The other main workflow script would then call some function that wraps the current figure into a pickle object and sends it to the clipboard, from where it gets caught by the GUI application, is unpickled and shown in the canvas.
This sounds like a little bit of work, but should meet the very restrictive requirements from the question.
The alternative from Daan worked for me. Here's a bit more code. I used this in a Tkinter interactive GUI for reusing/updating a matplotlib figure window:
fig1 = None
if fig1:
#if exists, clear figure 1
plt.figure(1).clf()
plt.suptitle("New Fig Title", fontsize=18, fontweight='bold')
#reuse window of figure 1 for new figure
fig1 = plt.scatter(points.T[0], points.T[1], color='red', **plot_kwds)
else:
#initialize
fig1 = plt.figure(num=1,figsize=(7, int(7*imgRatio)), dpi=80)
plt.tick_params(axis='both', which='major', labelsize=14)
plt.tick_params(axis='both', which='minor', labelsize=14)
plt.suptitle("Title", fontsize=18, fontweight='bold')
fig1 = plt.scatter(points.T[0], points.T[1], color='red', **plot_kwds)
The figure is reusing the (interactive) plt window. For this to work, I had to set interactive : True in the matplotlibrc file (see my comment here)
Hi I would like to show a few figures in matplotlib without stopping calculations. I would like the figure to show up right after the calculations that concern it are finished for example:
import numpy as np
import pylab as py
x=np.linspace(0,50,51)
y=x
fig, axs = plt.subplots(1, 1)
cs = axs.plot(x, y)
now i want to show the plot without blocking the possibility to make some other calculations
plt.show(block=False)
plt.pause(5)
I create the second plot
y1=2*x
fig1, axs1 = plt.subplots(1, 1)
cs1 = axs1.plot(x, y1)
plt.show()
This works however the first freezes (after 5 secound pause which I added) until I call plt.show() at the end. It is crucial that the first figure shows and works, then after calculations another figure is added to it.
The following code should do what you want. I did this in an IPython Notebook.
from IPython import display
import matplotlib.pyplot as plt
def stream_plot(iterable, plotlife=10.):
for I in iterable:
display.clear_output(wait=True)
output = do_calculations_on_i(I)
plt.plot(output)
display.display(plt.gca());
time.sleep(plotlife); #how long to show the plot for
the wait=True will wait to clear the old plot until it has something new to plot, or any other output is printed.
I put the sleep in there so I can observe each plot before it is wiped away. This was useful for having to observe distributions for several entities. You may or may not need it for what you want to do.
Is there any way to draw to a plot within a function and then have the changes show up on the plot before the function is finished executing?
For instance, in this function I would like to get the window extent of the text, but the function gives the error Cannot get window extent w/o renderer
because at the time s.get_window_extent() is called the text has not been drawn on the plot.
import matplotlib.pyplot as plt
import time
plt.ion()
myfig, myax = plt.subplots()
def plot_now():
s = myax.annotate("foo", [0.5, 0.5])
myfig.canvas.draw_idle()
s.get_window_extent()
plot_now()
I'm using iPython, python 2.7.6, matplotlib 1.4.3, and the Qt4Agg backend
Add plt.draw() before it goes sleep.
Try plt.pause(60) instead of time.sleep(60). Someone answering this question says that time.sleep doesn't work with Qt4Agg.
I have a question regarding windows/figures in matplotlib. I'm not sure if this is possible, but would like to know if it is.
Basically when I run my whole script, at the end a graph is plotted using matplotlib. In order to produce a new graph after running my script again I have to close that graph window.
Is there a way of keeping open the figure without closing it?
Let me give an example:
I would plot graph x by running my script.
I would then like to keep this graph on my screen, make a change to my script, plot the graph again so you may see the old graph and the new graph. Therefore n number of graphs may be visible.
Please note that I do NOT want to plot a new figure within my script. I simply would like to be able to see the graph, make a change and see the new graph WITHOUT having to save the graph.
EDIT:
This is the plotting secion of my code:
def plot_data(atb_mat_2, sd_index, sd_grad):#, rtsd):#, sd_index, sd_grad):
fig = plt.figure()
fig, (ax0, ax1, ax4, ax2, ax3) = plt.subplots(nrows=5, figsize=(15,10), num='Current Relative Method'+' ' + path)
ax0.plot(atb_mat_2)
ax0.set_title('Relative Track',fontsize=11)
ax0.set_ylim([-10,10])
if len(sd_index)!=0:
if len(sd_index)>1:
for i in range(1, len(sd_index)):
if sd_grad[i]==1:
ax0.axvspan(sd_index[i-1],sd_index[i], edgecolor='r', lw=None, alpha=0.1)
ax1.plot(rtsd)
ax1.set_title('RT Standard Deviation',fontsize=11)
ax1.set_ylim([0,250])
ax4.plot(abs_track_data)
ax4.set_title('Absolute Track',fontsize=11)
ax4.set_ylim([3000,5000])
ax2.plot(splitpo)
ax2.set_title('Track Split',fontsize=11)
ax2.set_ylim([0,20])
ax3.plot(ts)
ax3.set_title('TS Standard Deviation',fontsize=11)
ax3.set_ylim([0,100])
fig.tight_layout()
plt.show()
Thanks alot of any advice and sorry if this answer is obvious as I'm fairly new.
You can do it using ipython.
Write your script and save it as (for example) test.py. The script should create a figure, do the plotting and show the plot:
import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure()
x = np.linspace(-1, 1, 100)
y = np.sin(x)
plt.plot(x, y)
plt.show()
Start the ipython console using:
ipython --pylab=qt
Or whatever backend you want to use.
In the ipython shell type:
%run /path/to/the/test.py
This will create a figure, and show the plot.
After that change your script. For example change the 5th line to:
x = np.linspace(-0, 2, 100)
Repeat the %run command in the ipython shell:
%run /path/to/the/test.py
Another figure will pop up with the new plot. Old figure will be also visible (this won't remove it or replace it).