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 <sebastien.morin.1@xxxxxxxxx> 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@xxxxxxx 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