In an ipython notebook, I used a matplotlib stylesheet to change the look of my plots using
from matplotlib.pyplot import * %matplotlib inline style.use('ggplot')
My version of matplotlib is 1.4.0. How do I go back to the default matplotlib styling? I tried all the available styles in
print style.available
but there doesn't seem to be a "default" option. I also tried
matplotlib.rcdefaults()
For some reason, this gives me a gray background. It also changes the text from gray (ggplot style) to black, which may be the default, but also could be another random style.
Use matplotlib. style. use('default') or rcdefaults() to restore the default rcParams after changes.
plt. style. use('default') worked for me. As I understand this, it tells matplotlib to switch back to its default style mode.
In modern matplotlib there is no "default backend", i.e. the rcParams['backend'] is set to a "sentinel". Upon importing matplotlib the first working backend from a candidate list ["macosx", "qt5agg", "qt4agg", "gtk3agg", "tkagg", "wxagg"] is chosen.
You should be able to set it back to default by:
import matplotlib as mpl mpl.rcParams.update(mpl.rcParamsDefault)
In ipython
, things are a little different, especially with inline
backend:
In [1]: %matplotlib inline In [2]: import matplotlib as mpl import matplotlib.pyplot as plt In [3]: inline_rc = dict(mpl.rcParams) In [4]: plt.plot(range(10)) Out[4]: [<matplotlib.lines.Line2D at 0x72d2510>]
In [5]: mpl.rcParams.update(mpl.rcParamsDefault) plt.plot(range(10)) Out[5]: [<matplotlib.lines.Line2D at 0x7354730>]
In [6]: mpl.rcParams.update(inline_rc) plt.plot(range(10)) Out[6]: [<matplotlib.lines.Line2D at 0x75a8e10>]
Basically, %matplotlib inline
uses its own rcParams
. You can grab that from the source, but the arguably easier way is probably just save the rcParams
as inline_rc
after %matplotlib inline
cell magic in this example, and reuse that later.
There actually is a default
. But it's not listed under plt.style.available
. Simply run :
plt.style.use('default')
It returns the style to the default Matplotlib settings in, for instance, Jupyter Notebook.
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