I'm trying out Jupyter console for the first time, but can't get the %matplotlib inline
magic to work. Below is a screenshot of an example session:
The plot shows in a separate window after I run Line 6, and Line 7 doesn't do anything.
When I run %matplotlib --list
, inline
is given as one of the options:
Available matplotlib backends: ['osx', 'qt4', 'qt5', 'gtk3', 'notebook', 'wx', 'qt',
'nbagg', 'agg', 'gtk', 'tk', 'ipympl', 'inline']
When I try to use another backend, say qt5
, it gives an error message because I don't have any Qt installed.
ImportError: Matplotlib qt-based backends require an external PyQt4, PyQt5, or PySide
package to be installed, but it was not found.
Running %matplotlib??
reads:
If you are using the inline matplotlib backend in the IPython Notebook
you can set which figure formats are enabled using the following::
In [1]: from IPython.display import set_matplotlib_formats
In [2]: set_matplotlib_formats('pdf', 'svg')
The default for inline figures sets `bbox_inches` to 'tight'. This can
cause discrepancies between the displayed image and the identical
image created using `savefig`. This behavior can be disabled using the
`%config` magic::
In [3]: %config InlineBackend.print_figure_kwargs = {'bbox_inches':None}
But I don't know if it's something I can tweak around to solve my issue.
When I try it the magic IPython console, it says inline
is an Unknown Backend
.
UnknownBackend: No event loop integration for u'inline'. Supported event loops are: qt,
qt4, qt5, gtk, gtk2, gtk3, tk, wx, pyglet, glut, osx
I've also found this issue on github after some googling but I don't even know if it's relevant to my situation (most of their conversation didn't make sense to me lol).
Lastly, I'm not sure if this issue is related at all, but here it is, just in case: when I try to open Vim in Jupyter via the !vim
command, it glitches pretty badly, preventing me from even exiting out of Jupyter itself without closing the terminal altogther. Vim works perfectly fine when called inside IPython console, however.
I'm using matplotlib 2.0.0
.
If anyone could help me figure this out, that'd be great! Thank you!