Hi, Thanks for the professional comment :) The program has been carefully designed to have as little limitations as possible - so that the only limit is imagination and CPU time. If you do encounter limits (not the constraint type though), these can be removed from relax straight away. I would like to have these constraints, as well as the diagonal scaling values, more accessible to the user, but unfortunately I have never managed to design a flexible system for this. The constraint values for model-free analysis are documented in my model-free model elimination paper (http://www.nmr-relax.com/refs.html#dAuvergneGooley06), but these may one day change. For example an upper limit on tm of 200 ns may need to be changed for studying extremely large systems a la Kay.
Regards, Edward On Tue, Mar 25, 2008 at 6:31 PM, Sébastien Morin <[EMAIL PROTECTED]> wrote: > > Hi Ed, > > Thanks for these informations... I was afraid that you could have limited > relax to small proteins in the first drafts of the program with forgetting > to change these limits afterwards... thus creating artefacts when used with > bigger systems. > > However, as I see, the limits are all general and the size of the protein > (up to the huge correlation time of 200 ns !) does not influence the > results... > > As usual, relax is extremely professional... > Thanks Ed ! > Cheers ! > > > Séb > > > > > > > Edward d'Auvergne wrote: > Hi, > > Unless turned off, the constraints are used all of the time. In the > minimisation this turns on the Method of Multipliers (also known as > the Augmented Lagrangian) algorithm. In the grid search, any points > outside of the limits are dropped. Unfortunately these constraints > are hard coded as I couldn't, at the time, come up with a flexible way > for the user to modify the default values. There are a number of > methods for applying constraints, but currently only linear > constraints are supported. These are in the form: > > A.x >= b, > > where A is an matrix of coefficients, x is an array of parameter > values, and b is a vector of scalars. These translate into > constraints such as: > > S2 >= 0, > -S2 >= -1, > etc. > > The full list of constraints can be seen in the documentation string > for the linear_constraints() method in the specific_fns/model_free.py > file (relax-1.2). The diffusion tensor parameter constraints aren't > yet documented, but can be seen in the comments in the code of > linear_constraints(). I hope this info helps. > > Regards, > > Edward > > > On Fri, Feb 22, 2008 at 5:38 PM, Sébastien Morin > <[EMAIL PROTECTED]> wrote: > > > Hi, > > I have a question about constraints in relax... > > I would like to know what are the built-in constraints in relax, > especially for what concerns 'tau' (tau_m, tau_e, tau_s, tau_f) as well > as 'r' and 'csa' (for models m1x and m2x). > > What I'd like to know is if those parameters are contrained during grid > search, optimization, elimination and selection, except for > 'tau_(e,f,s)' values which should not exceed '1.5 x tau_m'... > > I understand that constraint are used by default within the method of > multipliers algorithm, but don't really get what are those constraint > and on which variables they act... > > Thanks for help ! > > Cheers, > > > Séb :) > > > > _______________________________________________ > relax (http://nmr-relax.com) > > This is the relax-users mailing list > relax-users@gna.org > > To unsubscribe from this list, get a password > reminder, or change your subscription options, > visit the list information page at > https://mail.gna.org/listinfo/relax-users > > > > _______________________________________________ relax (http://nmr-relax.com) This is the relax-users mailing list relax-users@gna.org To unsubscribe from this list, get a password reminder, or change your subscription options, visit the list information page at https://mail.gna.org/listinfo/relax-users
