I found this useful (at least as a stopgap measure while waiting for
Trac#21267 <https://trac.sagemath.org/ticket/21267>, which may be not as
easy as it seems...), and thought that documenting this might be useful to
people wanting interactive displays in Sagemath Jupyter notebooks :

##
Advertising

The ipywidgets <https://github.com/ipython/ipywidgets> python package can
be installed in the Sage jupyter notebook. To enable installation "in the
right place", the installation instructions
<http://ipywidgets.readthedocs.io/en/latest/user_install.html#with-pip>
should be modified as :
sage -pip install ipywidgets
echo "jupyter nbextension enable --py --sys-prefix widgetsnbextension" | sage
-sh
if you use the Sage Jupyter notebook (the original installation instructions
are enough if you have installed your Sage kernel
in the system's Jupyter notebook). The following code snippet is enough to use
the package :
from __future__ import print_functionfrom ipywidgets import interact,
interactive, fixedimport ipywidgets as widgets
And that's all... My limited testing seems to validate this (ab?)use of the
package :
var("x,a,b")
dbeta(x,a,b)=x^(a-1)*(1-x)^(b-1)/beta(a,b)
def showbeta(a,b):
show(plot(dbeta(x,a,b),(x,0,1),figsize=4))
return(None)
interact(showbeta,
a=widgets.FloatSlider(min=0.0,max=10.0,step=0.1,value=1.0,continuous_update=False),
b=widgets.FloatSlider(min=0.0,max=10.0,step=0.1,value=1.0,continuous_update=False));
Note that the ipywidget package has no way to use a lot of Sage data types. Any
argument to them have to be cast to
native python data types (int, float, string).
Clunky, but damn useful, at least for pedagogic purposes...
HTH,
--
Emmanuel Charpentier
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