apop_linear_constraint.c File Reference

Functions
long double	apop_linear_constraint (gsl_vector *beta, apop_data *constraint, double margin)

Detailed Description

apop_linear_constraint finds a point that meets a set of linear constraints. This takes a lot of machinery, so it gets its own file.

Copyright (c) 2007, 2009 by Ben Klemens. Licensed under the modified GNU GPL v2; see COPYING and COPYING2.

Function Documentation

long double apop_linear_constraint	(	gsl_vector *	beta,
		apop_data *	constraint,
		double	margin
	)

This is designed to be called from within the constraint method of your apop_model. Just write the constraint vector+matrix and this will do the rest. See the outline page for detailed discussion on setting contrasts.

Parameters

beta	The proposed vector about to be tested. No default, must not be NULL.
constraint	A vector/matrix pair [v | m1 m2 ... mn] where each row is interpreted as a less-than inequality: . For example, say your constraints are and is positive, i.e. . Allocate and fill the matrix representing these two constraints via: apop_data *constr = apop_data_falloc((2,2,3), 3, 2, 4, 7, 0, 0, 1, 0); . Default: each elements is greater than zero. E.g., for three parameters: apop_data *constr = apop_data_falloc((3,3,3), 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1);
margin	If zero, then this is a >= constraint, otherwise I will return a point this amount within the borders. You could try GSL_DBL_EPSILON, which is the smallest value a double can hold, or something like 1e-3. Default = 0.

return The penalty = the distance between beta and the closest point that meets the constraints. If the constraint is not met, this beta is shifted by margin (Euclidean distance) to meet the constraints.

• If your apop_data is not just a vector, try apop_data_pack to pack it into a vector. This is what apop_maximum_likelihood does.

• This function uses the Designated initializers syntax for inputs. todo The apop_linear_constraint function doesn't check for odd cases like coplanar constraints.