If you do sage: RealNumber=float sage: Integer=int before defining the functions, the ode solver runs dramatically faster. This is because the function calls get much cheaper as nothing is accidentally in RR or ZZ.
On Jan 29, 11:55 pm, "Fabio Tonti" <[EMAIL PROTECTED]> wrote: > Would be nice if someone posted the Lorenz attractor code on > planet.sagemath.org! > > For those who don't subscribe to this list... > > Fabio > > On Jan 29, 2008 8:32 PM, mhampton <[EMAIL PROTECTED]> wrote: > > > > > We really need to get xpp and/or AUTO into sage at some point. I have > > made some half-hearted stabs at it but have lacked the time to get > > serious. Like R support, its a chicken-and-egg problem: without real > > users within the sage community, it doesn't get put in, and until its > > in right there aren't any real users. I am very happy that R has been > > included, the interface can now be polished. We need to kick start > > the dynamical systems components. > > > cheers, > > Marshall > > > On Jan 29, 6:17 am, "David Joyner" <[EMAIL PROTECTED]> wrote: > > > That's cool. Good luck on your talk. > > > > BTW, have you tried this?http://www.math.pitt.edu/~bard/xpp/xpp.html > > > I could not get it to compile from source but fortunately > > > is a debian package (apt-get install xppaut). The docs say it > > > > "is a tool for solving > > > > * differential equations, > > > * difference equations, > > > * delay equations, > > > * functional equations, > > > * boundary value problems, and > > > * stochastic equations." > > > > So I thought you might be interested. The screenshot > > > section even has an animated > > gifhttp://www.math.pitt.edu/~bard/xpp/ss/screen.html > > > Lorentz plot. > > > > On Jan 29, 2008 4:38 AM, Joshua Kantor <[EMAIL PROTECTED]> wrote: > > > > > I was preparing a talk on solving ODE's in sage, and the culminating > > > > example is pretty neat so I thought I would post it. > > > > > The following code will plot a little bit of the lorenz attractor > > > > > sage: def lorenz(t,y,params): > > > > ... return [params[0]*(y[1]-y[0]),y[0]*(params[1]-y[2])- > > > > y[1],y[0]*y[1]-params[2]*y[2]] > > > > > sage: def lorenz_jac(t,y,params): > > > > ... return [ > > [-params[0],params[0],0],[(params[1]-y[2]),-1,-y[0]], > > > > [y[1],y[0],-params[2]],[0,0,0]] > > > > sage: T=ode_solver() > > > > sage: T.algorithm="bsimp" > > > > sage: T.function=lorenz > > > > sage: T.jacobian=lorenz_jac > > > > sage: T.ode_solve(y_0=[. > > > > 5,.5,.5],t_span=[0,155],params=[10,40.5,3],num_points=4000) > > > > sage: l=[T.solution[i][1] for i in range(len(T.solution))] > > > > sage: line3d(l,thickness=2) > > > > > This is somewhat computationally intensive (takes around a minute). > > > > > I thought the plot was quite neat. --~--~---------~--~----~------------~-------~--~----~ To post to this group, send email to sage-devel@googlegroups.com To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/sage-devel URLs: http://www.sagemath.org -~----------~----~----~----~------~----~------~--~---
