lv.lumii.layoutengine.funcmin

Class QuadraticOptimizer

java.lang.Object

lv.lumii.layoutengine.funcmin.QuadraticOptimizer

Direct Known Subclasses:

ExtendedQuadraticOptimizer

public class QuadraticOptimizer
extends java.lang.Object

Contains methods to create the function and constraints used in Funcmin, as well as call Funcmin and return the results.

Constructor Summary

Constructors

Constructor and Description
QuadraticOptimizer(int variableCount) The constructor creates a zero function with no constraints.

Method Summary

Modifier and Type	Method and Description
void	addCombinedTerm(int i, int j, double coefficient) Adds the combined term coefficient*xi*xj to the function.
void	addDoubleMeanConstantDifference(int i1, int j1, int i2, int j2, double value, double weight) Add a new term in the form of weight*((xi1+xj1)/2-(xi2+xj2)/2-value)2.
void	addDoubleMeanDifference(int i1, int j1, int i2, int j2, double weight) Add a new term in the form of weight*((xi1+xj1)/2-(xi2+xj2)/2)2.
void	addEquality(int i, int j, double distance) Adds an equality constraint in the form of xj-xi=distance.
void	addInequality(int i, int j, double distance) Adds an inequality constraint in the form of xj-xi≥distance.
void	addLinearDifference(int i, int j, double weight) Add a new term in the form of weight*(xj-xi).
void	addLinearTerm(int i, double coefficient) Adds the linear term coefficient*xi to the function.
void	addMeanDifference(int i, int j, double value, double weight) Add a new term in the form of weight*((xi+xj)/2-value)2.
void	addMeanVariableDifference(int i, int j, int k, double weight) Add a new term in the form of weight*((xi+xj)/2-xk)2.
void	addQuadraticConstantDifference(int i, double value, double weight) Add a new term in the form of weight*(xi-value)2.
void	addQuadraticDifference(int i, int j, double weight) Add a new term in the form of weight*(xi-xj)2.
void	addQuadraticTerm(int i, double coefficient) Adds the quadratic term coefficient*xi2 to the function.
double[]	performOptimization() Performs the function minimization using the given terms and constraints.
void	setEpsilon(double epsilon) Sets the precision of the minimization, used both for constraints and the function's value.
void	setVariable(int i, double value) Sets the initial value of the ith variable to value.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

QuadraticOptimizer

public QuadraticOptimizer(int variableCount)

The constructor creates a zero function with no constraints.

Parameters:

variableCount - the number of variables in the function this QuadraticOptimizer will optimize

Method Detail

setVariable

public void setVariable(int i,
                        double value)

Sets the initial value of the i_th variable to value.

Parameters:

i - the index of the variable whose value to set

value - the new value of the variable

addQuadraticDifference

public void addQuadraticDifference(int i,
                                   int j,
                                   double weight)

Add a new term in the form of weight*(xi-xj)2. Use this method to minimize the distance between two objects.

Parameters:

i - the first variable of the term

j - the second variable of the term

weight - the weight of this term

addQuadraticConstantDifference

public void addQuadraticConstantDifference(int i,
                                           double value,
                                           double weight)

Add a new term in the form of weight*(xi-value)2. Use this method to minimize the drift of an object.

Parameters:

i - the variable of the term

value - the value to keep the variable close to

weight - the weight of this term

addLinearDifference

public void addLinearDifference(int i,
                                int j,
                                double weight)

Add a new term in the form of weight*(xj-xi). Use this method to minimize the distance between two objects. This term does not have a minimum, therefore it should be constrained.

Parameters:

i - the first variable of the term

j - the second variable of the term

weight - the weight of this term

addMeanDifference

public void addMeanDifference(int i,
                              int j,
                              double value,
                              double weight)

Add a new term in the form of weight*((xi+xj)/2-value)2. Use this method to minimize the drift of the mass center of two objects.

Parameters:

i - the first variable of the term

j - the second variable of the term

value - the value to keep the mass center of the two objects close to

weight - the weight of this term

addDoubleMeanDifference

public void addDoubleMeanDifference(int i1,
                                    int j1,
                                    int i2,
                                    int j2,
                                    double weight)

Add a new term in the form of
weight*((xi1+xj1)/2-(xi2+xj2)/2)2. Use this method to minimize the distance between the mass centers of two object pairs.

Parameters:

i1 - the first variable of the first pair

j1 - the second variable of the first pair

i2 - the first variable of the second pair

j2 - the second variable of the second pair

weight - the weight of this term

addDoubleMeanConstantDifference

public void addDoubleMeanConstantDifference(int i1,
                                            int j1,
                                            int i2,
                                            int j2,
                                            double value,
                                            double weight)

Add a new term in the form of
weight*((xi1+xj1)/2-(xi2+xj2)/2-value)2. Use this method to minimize the drift between the mass centers of two object pairs.

Parameters:

i1 - the first variable of the first pair

j1 - the second variable of the first pair

i2 - the first variable of the second pair

j2 - the second variable of the second pair

value - the value to keep the distance between the two mass centers at

weight - the weight of this term

addMeanVariableDifference

public void addMeanVariableDifference(int i,
                                      int j,
                                      int k,
                                      double weight)

Add a new term in the form of
weight*((xi+xj)/2-xk)2. Use this method to minimize the distance between the mass center of the (i, j) object pair and object k.

Parameters:

i - the first variable of the pair

j - the second variable of the pair

k - the solitary object

weight - the weight of this term

addInequality

public void addInequality(int i,
                          int j,
                          double distance)

Adds an inequality constraint in the form of xj-xi≥distance.

Parameters:

i - the second variable of the inequality

j - the first variable of the inequality

distance - the minimum distance between the two variables

addEquality

public void addEquality(int i,
                        int j,
                        double distance)

Adds an equality constraint in the form of xj-xi=distance.

Parameters:

i - the second variable of the equality

j - the first variable of the equality

distance - the distance between the two variables

addQuadraticTerm

public void addQuadraticTerm(int i,
                             double coefficient)

Adds the quadratic term coefficient*xi2 to the function.

Parameters:

i - the index of the variable whose quadratic term to alter

coefficient - the coefficient of the added quadratic term

addLinearTerm

public void addLinearTerm(int i,
                          double coefficient)

Adds the linear term coefficient*xi to the function.

Parameters:

i - the index of the variable whose linear term to alter

coefficient - the coefficient of the added linear term

addCombinedTerm

public void addCombinedTerm(int i,
                            int j,
                            double coefficient)

Adds the combined term coefficient*xi*xj to the function.

Parameters:

i - the index of the first variable of the combined term

j - the index of the second variable of the combined term

coefficient - the coefficient of the added combined term

setEpsilon

public void setEpsilon(double epsilon)

Sets the precision of the minimization, used both for constraints and the function's value.

Parameters:

epsilon - the new precision

performOptimization

public double[] performOptimization()

Performs the function minimization using the given terms and constraints.

Returns:

an array of the new values of the function variables.