Author: bugman Date: Wed Jan 9 10:26:19 2008 New Revision: 4521 URL: http://svn.gna.org/viewcvs/relax?rev=4521&view=rev Log: Changed a few of the arguments of the N-state model grid_search() function. The 'print_flag' arg has been renamed to 'verbosity' and the 0/1 args have been converted to True/False args. Modified: branches/N_state_model/specific_fns/n_state_model.py Modified: branches/N_state_model/specific_fns/n_state_model.py URL: http://svn.gna.org/viewcvs/relax/branches/N_state_model/specific_fns/n_state_model.py?rev=4521&r1=4520&r2=4521&view=diff ============================================================================== --- branches/N_state_model/specific_fns/n_state_model.py (original) +++ branches/N_state_model/specific_fns/n_state_model.py Wed Jan 9 10:26:19 2008 @@ -35,7 +35,7 @@ """Class containing functions for the N-state model.""" - def grid_search(self, lower, upper, inc, constraints, print_flag, sim_index=None): + def grid_search(self, lower, upper, inc, constraints=False, verbosity=0, sim_index=None): """The grid search function. @param lower: The lower bounds of the grid search which must be equal to the number of @@ -48,12 +48,12 @@ number of elements in the array must equal to the number of parameters in the model. @type inc: array of int - @param constraints: If true, constraints are applied during the grid search (elinating parts - of the grid). If false, no constraints are used. + @param constraints: If True, constraints are applied during the grid search (elinating parts + of the grid). If False, no constraints are used. @type constraints: bool - @param print_flag: A flag specifying the amount of information to print. The higher the + @param verbosity: A flag specifying the amount of information to print. The higher the value, the greater the verbosity. - @type print_flag: int + @type verbosity: int """ # Arguments. @@ -62,7 +62,7 @@ self.inc = inc # Minimisation. - self.minimise(min_algor='grid', constraints=constraints, print_flag=print_flag, sim_index=sim_index) + self.minimise(min_algor='grid', constraints=constraints, verbosity=verbosity, sim_index=sim_index) def overfit_deselect(self):