Johan Hake wrote: > On Sunday 24 January 2010 16:39:14 Garth N. Wells wrote: >> Johan Hake wrote: >>> On Sunday 24 January 2010 16:12:37 Garth N. Wells wrote: >>>> Johan Hake wrote: >>>>> On Sunday 24 January 2010 00:03:41 Garth N. Wells wrote: >>>>>> Johan Hake wrote: >>>>>>> On Saturday 23 January 2010 14:55:08 Garth N. Wells wrote: >>>>>>>> Johan Hake wrote: >>>>>>>>> On Saturday 23 January 2010 08:42:14 Garth N. Wells wrote: >>>>>>>>>> Is it correct that behind the scenes that >>>>>>>>>> >>>>>>>>>> U0 = Function(V) >>>>>>>>>> U = Function(V) >>>>>>>>>> U0.vector()[:] = U.vector()[:] >>>>>>>>>> >>>>>>>>>> involves a GenericVector::get(..) call and a >>>>>>>>>> GenericVector::set(..) call? If so, it isn't ideal since it >>>>>>>>>> introduces unnecessary new/delete operations and unnecessary >>>>>>>>>> copying of data. >>>>>>>>> None of GenericVector::get(..) or GenericVector::set(..) are >>>>>>>>> invoked, see __getslice__ and __setslice__ in la_post.i. >>>>>>>>> >>>>>>>>> U0.vector()[:] >>>>>>>>> >>>>>>>>> involves >>>>>>>>> >>>>>>>>> GenericVector::operator =(..) >>>>>>>>> >>>>>>>>> and >>>>>>>>> >>>>>>>>> U.vector()[:] >>>>>>>>> >>>>>>>>> involves >>>>>>>>> >>>>>>>>> GenericVector::copy() >>>>>>>>> >>>>>>>>> However the latter is unnecessary as you instead can do: >>>>>>>>> >>>>>>>>> U0.vector()[:] = U.vector() >>>>>>>>> >>>>>>>>> invoking the assignment operator of U0's vector with U's vector. >>>>>>>> What happens if I do >>>>>>>> >>>>>>>> x = U.vector()[:] >>>>>>> It just triggers the copy method of GenericVector, which is the same >>>>>>> behavior as for other itterable Python types. >>>>>>> >>>>>>>> ? Is x a numpy array? >>>>>>> No you need to call array() to accomplish that. >>>>>> OK. What I'm trying to do is >>>>>> >>>>>> # Get vectors >>>>>> u_vec = u.vector()[:] >>>>>> u0_vec = u0.vector()[:] >>>>>> v0_vec = v0.vector()[:] >>>>>> a0_vec = a0.vector()[:] >>>>> You should not need to make a copy of the vectors here. >>>> How can I avoid it? >>> a_vec and v_vec are new vectors. None of the four vectors below get >>> modified by the a_vec and v_vec expressions so no need of copying, and >>> the v0 and a0 assignment should work with GenericVectors too. >> Do you mean that just >> >> a_vec = 1.0/(2.0*beta)*((u - u0 - v0*dt)/(0.5*dt*dt) \ >> - (1.0-2.0*beta)*a0 ) >> >> where u and u0 are GenericVectors should work? > > Have you tried? >
Can I somehow get a 'reference' to the vector so I don't have to use u.vector()[:] in the expressions? Garth > As long as the rest (besides a0, which I assume also is a GenericVector) are > scalars everything should just work. The Python LA interface (at least for > GenericVector) should work more or less as the NumPy interface which I think > is nice :) > > We cannot take 1./v, where v is a GenericVector. > >>> Do you get any error messages? >> No errors. What I have now seems to work fine. > > Ok, and that is because what you do obviously works for NumPy arrays. > > Johan > >> Garth _______________________________________________ Mailing list: https://launchpad.net/~dolfin Post to : [email protected] Unsubscribe : https://launchpad.net/~dolfin More help : https://help.launchpad.net/ListHelp
