It means if we are not using the show() function, it wouldn't show any plot. When we use the show() function in the non-interactive mode. That means when we write the code in the file it will show all the figures or plots and blocks until the plots have been closed.
Matplotlib is not a built-in module (it doesn't come with the default python installation) in Python, you need to install it explicitly using the pip installer and then use it. If you looking at how to install pip or if you are getting an error installing pip checkout pip: command not found to resolve the issue.
If you are using Matplotlib from within a script, the function plt. show() is your friend. plt. show() starts an event loop, looks for all currently active figure objects, and opens one or more interactive windows that display your figure or figures.
If I set my backend to template
in ~/.matplotlib/matplotlibrc
,
then I can reproduce your symptoms:
~/.matplotlib/matplotlibrc:
# backend : GtkAgg
backend : template
Note that the file matplotlibrc
may not be in directory ~/.matplotlib/
. In this case, the following code shows where it is:
>>> import matplotlib
>>> matplotlib.matplotlib_fname()
In [1]: import matplotlib.pyplot as p
In [2]: p.plot(range(20),range(20))
Out[2]: [<matplotlib.lines.Line2D object at 0xa64932c>]
In [3]: p.show()
If you edit ~/.matplotlib/matplotlibrc
and change the backend to something like GtkAgg
, you should see a plot. You can list all the backends available on your machine with
import matplotlib.rcsetup as rcsetup
print(rcsetup.all_backends)
It should return a list like:
['GTK', 'GTKAgg', 'GTKCairo', 'FltkAgg', 'MacOSX', 'QtAgg', 'Qt4Agg',
'TkAgg', 'WX', 'WXAgg', 'CocoaAgg', 'agg', 'cairo', 'emf', 'gdk', 'pdf',
'ps', 'svg', 'template']
Reference:
I ran into the exact same problem on Ubuntu 12.04, because I installed matplotlib (within a virtualenv) using
pip install matplotlib
To make long story short, my advice is: don't try to install matplotlib using pip or by hand; let a real package manager (e.g. apt-get / synaptic) install it and all its dependencies for you.
Unfortunately, matplotlib's backends (alternative methods for actually rendering your plots) have all sorts of dependencies that pip will not deal with. Even worse, it fails silently; that is, pip install matplotlib
appears to install matplotlib successfully. But when you try to use it (e.g. pyplot.show()
), no plot window will appear. I tried all the different backends that people on the web suggest (Qt4Agg, GTK, etc.), and they all failed (i.e. when I tried to import matplotlib.pyplot, I get ImportError
because it's trying to import some dependency that's missing). I then researched how to install those dependencies, but it just made me want to give up using pip (within virtualenv) as a viable installation solution for any package that has non-Python package dependencies.
The whole experience sent me crawling back to apt-get / synaptic (i.e. the Ubuntu package manager) to install software like matplotlib. That worked perfectly. Of course, that means you can only install into your system directories, no virtualenv goodness, and you are stuck with the versions that Ubuntu distributes, which may be way behind the current version...
%matplotlib inline
For me working with notebook, adding the above line before the plot works.
For future reference,
I have encountered the same problem -- pylab was not showing under ipython. The problem was fixed by changing ipython's config file {ipython_config.py}. In the config file
c.InteractiveShellApp.pylab = 'auto'
I changed 'auto' to 'qt' and now I see graphs
Just type:
plt.ion()
See https://www.youtube.com/watch?v=1zmV8lZsHF4 at 23:30 !
plt
is used because of my import: import matplotlib.pyplot
as plt
I'm using python2.7 on a mac with iTerm2.
What solved my problem was just using the below two lines in ipython notebook at the top
%matplotib inline
%pylab inline
And it worked. I'm using Ubuntu16.04 and ipython-5.1
Adding the following two lines before importing pylab seems to work for me
import matplotlib
matplotlib.use("gtk")
import sys
import pylab
import numpy as np
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