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VPython significantly slower in Jupyter

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I'm trying to rewrite some vpython script in jupyter notebooks. So far I've not ran into many problems, but the last one I've tried to rewrite became significantly slower. It runs very quickly in VIDLE. I'm using sierraOS with Python 3.5.0 and Jupyter 4.1.0.

The code creates some objects, and then changes their positions in a while-loop.Initially the loop had visual.rate(5000), but I tried reducing that to 50 with no avail. I also tried reducing the number of objects to only two but still working very slowly. Here's my simplest version of the code:

from vpython import scene, sphere, color, curve, arrow, mag, vector, rate,canvasscene = canvas(width=800, height=600)obj0 = sphere(pos=vector(0,0,0), radius=5e11)obj1 = sphere(pos=vector(5e12,0,0), radius=5e11)trail1= curve()#some initial valueG = 6.7E-11obj0.mass = 2.0E30obj0.momentum = vector(0,0,0)obj1.mass = 1.0E26obj1.momentum = vector(0,0,0)dt=200000.          CrashFlag=0         while(CrashFlag==0):    rate(1000)    obj1.force= -G*(obj0.mass*obj1.mass*obj1.pos)/(mag(obj1.pos)**3)    obj1.momentum = obj1.momentum+ dt*(obj1.force)    obj1.pos = obj1.pos + dt*obj1.momentum/obj1.mass    trail1.append(pos=obj1.pos)    if (mag(obj1.pos)<2.e11) :        CrashFlag=1

Can you identify anything that would cause this to be particularly slow in a Jupyter notebook, or suggest any way around it? Otherwise, is it possible to have the simulation outputted in VIDLE rather than inline in the Jupyter notebook (while the code would still run from the Jupyter notebook)


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