diff --git a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/CanonicalProgramParameters.java b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/CanonicalProgramParameters.java
index e3746ca2edb6c95448d58f6713912b9a7392f7a0..2161372aebe27fcbc652c4229a7e644be1b82f90 100644
--- a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/CanonicalProgramParameters.java
+++ b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/CanonicalProgramParameters.java
@@ -4,23 +4,28 @@ package plugins.nchenouard.linearprogrammingfullsimplex;
* Parameters used for the simplex algorithm
*
* By definition, the optimization problem is of the form:
+ *
+ * <pre>
* min_x c'*x or max_x c'*x
- * A*x <= b
- * with x >=0
- * where x, b, c are column vectors and c' is the transpose of c. * stands for the matrix multiplication.
- * Here each constraint A[i]*x can be either "equal" or "lower than or equal" constraints
- * based on the boolean value in the equalityConstraints vector:
+ * A*x <= b
+ * with x >=0
+ * </pre>
+ *
+ * where x, b, c are column vectors and c' is the transpose of c. * stands for
+ * the matrix multiplication.
+ * <p>
+ * Here each constraint A[i]*x can be either "equal" or "lower than or equal"
+ * constraints based on the boolean value in the equalityConstraints vector:
+ * <p>
* A[i]*x == b if equalityConstraints[i]
- * A[i]*x <= b if equalityConstraints[i]
+ * <p>
+ * A[i]*x <= b if equalityConstraints[i]
+ * <p>
*
*
* Part of the Linear Programming plugin for ICY http://icy.bioimageanalysis.org
*
* @author Nicolas Chenouard (nicolas.chenouard.dev@gmail.com)
- * @version 1.0
- * @date 2014-04-21
- * @license gpl v3.0
- *
*/
public class CanonicalProgramParameters
@@ -42,10 +47,13 @@ public class CanonicalProgramParameters
* The value for each constraint.
*/
public double[] b;
+
/**
* Defines the type of constraint
+ * <p>
* A[i]*x == b if equalityConstraints[i]
- * A[i]*x <= b if equalityConstraints[i]
+ * <p>
+ * A[i]*x <= b if equalityConstraints[i]
*/
public boolean[] equalityConstraints;
}
\ No newline at end of file
diff --git a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/CanonicalSimplexProgram.java b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/CanonicalSimplexProgram.java
index bf3791c92db2a3ca726a1b8e9916b47d6d671676..451e9c12f39a09e2cff73125a30a3e67f472b34b 100644
--- a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/CanonicalSimplexProgram.java
+++ b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/CanonicalSimplexProgram.java
@@ -10,26 +10,27 @@ import java.io.IOException;
import java.io.InputStreamReader;
/**
- * Linear program for the Simplex algorithm. Inheriting classes should implement the pivoting rule.
+ * Linear program for the Simplex algorithm. Inheriting classes should implement
+ * the pivoting rule.
*
- * By definition, the optimization problem is of the form:
- * min_x c'*x or max_x c'*x
- * A*x <= b
- * with x >=0
- * where x, b, c are column vectors and c' is the transpose of c. * stands for the matrix multiplication.
- * Here each constraint A[i]*x can be either "equal" or "lower than or equal" constraints
- * based on the boolean value in the equalityConstraints vector:
- * A[i]*x == b if equalityConstraints[i]
- * A[i]*x <= b if equalityConstraints[i]
+ * By definition, the optimization problem is of the form: min_x c'*x or max_x
+ * c'*x A*x <= b with x >=0 where x, b, c are column vectors and c' is the
+ * transpose of c.
+ *
+ * * stands for the matrix multiplication.
*
+ * Here each constraint <code>A[i]*x</code> can be either "equal" or "lower than
+ * or equal" constraints based on the boolean value in the equality constraints
+ * vector:
+ * <p>
+ * A[i]*x == b if equalityConstraints[i]
+ * <p>
+ * A[i]*x <= b if equalityConstraints[i]
+ * <p>
*
* Part of the Linear Programming plugin for ICY http://icy.bioimageanalysis.org
*
* @author Nicolas Chenouard (nicolas.chenouard.dev@gmail.com)
- * @version 1.0
- * @date 2014-04-21
- * @license gpl v3.0
- *
*/
public abstract class CanonicalSimplexProgram
@@ -65,13 +66,20 @@ public abstract class CanonicalSimplexProgram
/**
* Constructor specifying parameters of the linear programming problem.
- * @param A constraint matrix
- * @param b constraint values
- * @param c linear objective function weights
- * @param maximization maximization problem if true, minimization else.
- * @param equality indicates whether each constraint is an equality. Else it is <=.
- * */
- public CanonicalSimplexProgram(double[][] A, double[] b, double[] c, boolean maximization, boolean[] equality)
+ *
+ * @param A
+ * constraint matrix
+ * @param b
+ * constraint values
+ * @param c
+ * linear objective function weights
+ * @param maximization
+ * maximization problem if true, minimization else.
+ * @param equality
+ * indicates whether each constraint is an equality. Else it is
+ * <=.
+ */
+ public CanonicalSimplexProgram(final double[][] A, final double[] b, final double[] c, final boolean maximization, final boolean[] equality)
{
this.parameters = new CanonicalProgramParameters();
this.parameters.A = A;
@@ -86,7 +94,7 @@ public abstract class CanonicalSimplexProgram
* Constructor specifying parameters of the linear programming problem.
* @param p Parameters of the linear programming problem.
*/
- public CanonicalSimplexProgram(CanonicalProgramParameters p)
+ public CanonicalSimplexProgram(final CanonicalProgramParameters p)
{
this.parameters = p;
this.numVariables = p.c.length;
@@ -99,13 +107,13 @@ public abstract class CanonicalSimplexProgram
* */
public boolean solvePrimalSimplex()
{
- double[][] A = parameters.A;
- double[] b = parameters.b;
- boolean[] eq = parameters.equalityConstraints;
- double[] c = parameters.c;
+ final double[][] A = parameters.A;
+ final double[] b = parameters.b;
+ final boolean[] eq = parameters.equalityConstraints;
+ final double[] c = parameters.c;
boolean onlyInequality = true;
- for (boolean e:eq)
+ for (final boolean e:eq)
{
if (e)
{
@@ -133,10 +141,10 @@ public abstract class CanonicalSimplexProgram
if(hasNegativeRHS)
{
// add slack variables and multiply by -1 when corresponding to a negative right-hand-side
- double[][] A2 = new double[numConstraints][numConstraints + numVariables];
- double[] c2 = new double[numConstraints + numVariables];
+ final double[][] A2 = new double[numConstraints][numConstraints + numVariables];
+ final double[] c2 = new double[numConstraints + numVariables];
System.arraycopy(c, 0, c2, 0, numVariables); // no cost for slack variables
- boolean[] equality = new boolean[numConstraints];
+ final boolean[] equality = new boolean[numConstraints];
for (int i = 0; i < numConstraints; i++)
{
equality[i] = true;
@@ -159,7 +167,7 @@ public abstract class CanonicalSimplexProgram
// we have now a problem with only equality constraints and non-negative right-hand-side
if(solveWithEqualities(false))
{
- double[] tmpSolution = this.solution;
+ final double[] tmpSolution = this.solution;
this.solution = new double[numVariables];
System.arraycopy(tmpSolution, 0, solution, 0, numVariables);
}
@@ -175,9 +183,9 @@ public abstract class CanonicalSimplexProgram
{
// we need to solve first a problem to find the initial tableau
// we will add slack variables and minimize the cost of the sum of the slack variables for the equality constraints
- boolean maximization = false;
- boolean[] eq2 = new boolean[numConstraints];
- boolean[] isNegativeConstraint = new boolean[numConstraints];
+ final boolean maximization = false;
+ final boolean[] eq2 = new boolean[numConstraints];
+ final boolean[] isNegativeConstraint = new boolean[numConstraints];
for (int i = 0; i < numConstraints; i++)
{
if (b[i] < 0)
@@ -188,7 +196,7 @@ public abstract class CanonicalSimplexProgram
A[i][j] = -A[i][j];
}
}
- CanonicalSimplexProgram modifiedProgram = createNewProgram(A, b, c, maximization, eq2);
+ final CanonicalSimplexProgram modifiedProgram = createNewProgram(A, b, c, maximization, eq2);
if (modifiedProgram.solvePhaseICanonicalSimplex())
{
modifiedProgram.tableau0.setUnitScoreToSlackVars(eq2);
@@ -221,7 +229,7 @@ public abstract class CanonicalSimplexProgram
* Solve a problem that contains only inequality constraints
* @return true if optimization succeeded, false otherwise.
* */
- private boolean solveWithInequalities(boolean compareWithLPSolve)
+ private boolean solveWithInequalities(final boolean compareWithLPSolve)
{
// Canonical form: initial tableau is built by introducing unit vectors
solvePhaseICanonicalSimplex();
@@ -238,7 +246,7 @@ public abstract class CanonicalSimplexProgram
* Solve a problem that contains some equality constraints
* @return true if optimization succeeded, false otherwise.
* */
- private boolean solveWithEqualities(boolean compareWithLPSolve)
+ private boolean solveWithEqualities(final boolean compareWithLPSolve)
{
tableau0 = new TableauMinSlackObjective(this);
if (verbose)
@@ -261,7 +269,7 @@ public abstract class CanonicalSimplexProgram
// }
// }
// }
- boolean success = solvePhaseIICanonicalSimplex(tableau0, false); // minimization of the init tableau
+ final boolean success = solvePhaseIICanonicalSimplex(tableau0, false); // minimization of the init tableau
// {
// double c[] = new double[tableau0.numCol];
// for (int i = 0; i < numConstraints; i ++)
@@ -315,7 +323,7 @@ public abstract class CanonicalSimplexProgram
* Solve the phase II of the Simplex algorithm for canonical problem: no equality constraints nor negative constraints
* @return true if optimization succeeded, false otherwise.
* */
- public boolean solvePhaseIICanonicalSimplex(TableauWithSlackVariables tableau, boolean max)
+ public boolean solvePhaseIICanonicalSimplex(final TableauWithSlackVariables tableau, final boolean max)
{
if (tableau == null)
return false;
@@ -327,7 +335,7 @@ public abstract class CanonicalSimplexProgram
while(feasible && !reachedOptimum)
{
// start optimization
- int colIdx = getPivotColumn(tableau, max);
+ final int colIdx = getPivotColumn(tableau, max);
if (colIdx < 0)// optimal solution achieved
{
reachedOptimum = true;
@@ -335,7 +343,7 @@ public abstract class CanonicalSimplexProgram
}
else
{
- int rowIdx = getRowidx(tableau, colIdx);
+ final int rowIdx = getRowidx(tableau, colIdx);
if (rowIdx < 0) // not feasible
{
feasible = false;
@@ -374,12 +382,19 @@ public abstract class CanonicalSimplexProgram
/**
* Duplicate the program
- * @param A constraint matrix
- * @param b constraint values
- * @param c linear objective function weights
- * @param maximization maximization problem if true, minimization else.
- * @param equality indicates whether each constraint is an equality. Else it is <=.
- * */
+ *
+ * @param A
+ * constraint matrix
+ * @param b
+ * constraint values
+ * @param c
+ * linear objective function weights
+ * @param maximization
+ * maximization problem if true, minimization else.
+ * @param equality
+ * indicates whether each constraint is an equality. Else it is
+ * <=.
+ */
protected abstract CanonicalSimplexProgram createNewProgram(double[][] A, double[] b, double[] c, boolean maximization, boolean[] equality);
/**
@@ -403,8 +418,8 @@ public abstract class CanonicalSimplexProgram
* */
public void checkSolution()
{
- double[][] A0 = parameters.A;
- double[] b0 = parameters.b;
+ final double[][] A0 = parameters.A;
+ final double[] b0 = parameters.b;
if (solution != null)
{
for (int i = 0; i < numConstraints; i++)
@@ -465,7 +480,7 @@ public abstract class CanonicalSimplexProgram
/**
* Set the parameters of the linear programming problem
* */
- public void setParameters(CanonicalProgramParameters parameters) {
+ public void setParameters(final CanonicalProgramParameters parameters) {
this.parameters = parameters;
}
@@ -545,7 +560,7 @@ public abstract class CanonicalSimplexProgram
* */
public static String getHelp()
{
- String helpString = "Run the solver for example problems or for a user-defined system\n"
+ final String helpString = "Run the solver for example problems or for a user-defined system\n"
+ "Empty arguments to use the default example.\n"
+ "Enter an integer from 0 to 3 for different example scenarios.\n"
+ "Enter -1 for a user-defined scenario through text files.\n "
@@ -591,7 +606,7 @@ public abstract class CanonicalSimplexProgram
* For the equality file '0' stands for 'false' and '1' for true.
*
* */
- public static void main(String [] args)
+ public static void main(final String [] args)
{
int scenario = 0;
if (args.length > 0)
@@ -606,7 +621,7 @@ public abstract class CanonicalSimplexProgram
try {
scenario = Integer.parseInt(args[0]);
}
- catch (NumberFormatException e)
+ catch (final NumberFormatException e)
{
System.out.println("Invalid input argument");
System.out.println("Use input option -help to display the manual of the software");
@@ -754,14 +769,14 @@ public abstract class CanonicalSimplexProgram
equality = new boolean[tab.length-1];
for (int i = 0; i < tab.length-1; i++)
{
- double d = Double.parseDouble(tab[i]);
+ final double d = Double.parseDouble(tab[i]);
equality[i] = d > 0;
}
reader.close();
fis.close();
- int numRow = b.length;
- int numCol = c.length;
+ final int numRow = b.length;
+ final int numCol = c.length;
file = new File(fileA);
fis = new FileInputStream(file);
@@ -781,10 +796,10 @@ public abstract class CanonicalSimplexProgram
}
reader.close();
fis.close();
- } catch (FileNotFoundException e) {
+ } catch (final FileNotFoundException e) {
e.printStackTrace();
return;
- } catch (IOException e) {
+ } catch (final IOException e) {
e.printStackTrace();
return;
}
@@ -856,14 +871,14 @@ public abstract class CanonicalSimplexProgram
System.out.println("Use input option -help to display the manual of the software");
return;
}
- CanonicalSimplexProgram program = new SimplexLEXICO(A, b, c, maximization, equality);
+ final CanonicalSimplexProgram program = new SimplexLEXICO(A, b, c, maximization, equality);
if (verbose)
{
program.displayProblem();
}
if(program.solvePrimalSimplex())
{
- double[] solution = program.solution;
+ final double[] solution = program.solution;
if (verbose)
{
System.out.print("Computed solution = [");
@@ -897,7 +912,7 @@ public abstract class CanonicalSimplexProgram
out.write("\nscore\n");
out.write(Double.toString(program.tableau0.scoreValue));
out.close();
- } catch (IOException e) {
+ } catch (final IOException e) {
e.printStackTrace();
return;
}
@@ -911,7 +926,7 @@ public abstract class CanonicalSimplexProgram
}
}
- public static void runExampleScenario(int scenario)
+ public static void runExampleScenario(final int scenario)
{
if (scenario < 0 || scenario > 3)
{
@@ -924,7 +939,7 @@ public abstract class CanonicalSimplexProgram
double[] c = null;
boolean[] equality = null;
double[][] A = null;
- boolean verbose = true;
+ final boolean verbose = true;
switch (scenario) {
case 0:
{
@@ -987,7 +1002,7 @@ public abstract class CanonicalSimplexProgram
break;
}
}
- CanonicalSimplexProgram program = new SimplexLEXICO(A, b, c, maximization, equality);
+ final CanonicalSimplexProgram program = new SimplexLEXICO(A, b, c, maximization, equality);
if (verbose)
{
System.out.println();
@@ -995,7 +1010,7 @@ public abstract class CanonicalSimplexProgram
}
if(program.solvePrimalSimplex())
{
- double[] solution = program.solution;
+ final double[] solution = program.solution;
if (verbose)
{
System.out.println();
diff --git a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/SimplexBLAND.java b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/SimplexBLAND.java
index 74228c55ec4554121d467b06620f6d5ee7471c20..706a0d531e43b98d76f9ee70ab20c9df91cc316c 100644
--- a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/SimplexBLAND.java
+++ b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/SimplexBLAND.java
@@ -8,30 +8,33 @@ package plugins.nchenouard.linearprogrammingfullsimplex;
* Part of the Linear Programming plugin for ICY http://icy.bioimageanalysis.org
*
* @author Nicolas Chenouard (nicolas.chenouard.dev@gmail.com)
- * @version 1.0
- * @date 2014-04-21
- * @license gpl v3.0
- *
*/
public class SimplexBLAND extends CanonicalSimplexProgram
{
/**
* Constructor specifying parameters of the linear programming problem.
- * @param A constraint matrix
- * @param b constraint values
- * @param c linear objective function weights
- * @param maximization maximization problem if true, minimization else.
- * @param equality indicates whether each constraint is an equality. Else it is <=.
- * */
- public SimplexBLAND(double[][] A, double[] b, double[] c,
- boolean maximization, boolean[] equality) {
+ *
+ * @param A
+ * constraint matrix
+ * @param b
+ * constraint values
+ * @param c
+ * linear objective function weights
+ * @param maximization
+ * maximization problem if true, minimization else.
+ * @param equality
+ * indicates whether each constraint is an equality. Else it is
+ * <=.
+ */
+ public SimplexBLAND(final double[][] A, final double[] b, final double[] c,
+ final boolean maximization, final boolean[] equality) {
super(A, b, c, maximization, equality);
}
/**
* Constructor specifying parameters of the linear programming problem.
* @param p Parameters of the linear programming problem.
*/
- public SimplexBLAND(CanonicalProgramParameters p) {
+ public SimplexBLAND(final CanonicalProgramParameters p) {
super(p);
}
/**
@@ -41,13 +44,13 @@ public class SimplexBLAND extends CanonicalSimplexProgram
* @return the row index in the tableau
* */
@Override
- protected int getRowidx(TableauWithSlackVariables tableau, int colIdx) {
+ protected int getRowidx(final TableauWithSlackVariables tableau, final int colIdx) {
boolean found = false;
double maxVal = -1;
int rowIdx = -1;
for (int i = 0; i < tableau.xCol.length; i++)
{
- double val = tableau.tableau[i][colIdx];
+ final double val = tableau.tableau[i][colIdx];
if (val > tol )
{
if (!found)
@@ -75,7 +78,7 @@ public class SimplexBLAND extends CanonicalSimplexProgram
* @return the column index in the tableau
* */
@Override
- protected int getPivotColumn(TableauWithSlackVariables tableau, boolean max) {
+ protected int getPivotColumn(final TableauWithSlackVariables tableau, final boolean max) {
if (max)
{
int idx = -1;
@@ -99,17 +102,25 @@ public class SimplexBLAND extends CanonicalSimplexProgram
return idx;
}
}
+
/**
* Duplicate the program
- * @param A constraint matrix
- * @param b constraint values
- * @param c linear objective function weights
- * @param maximization maximization problem if true, minimization else.
- * @param equality indicates whether each constraint is an equality. Else it is <=.
- * */
+ *
+ * @param A
+ * constraint matrix
+ * @param b
+ * constraint values
+ * @param c
+ * linear objective function weights
+ * @param maximization
+ * maximization problem if true, minimization else.
+ * @param equality
+ * indicates whether each constraint is an equality. Else it is
+ * <=.
+ */
@Override
- protected CanonicalSimplexProgram createNewProgram(double[][] A,
- double[] b, double[] c, boolean maximization, boolean[] equality) {
+ protected CanonicalSimplexProgram createNewProgram(final double[][] A,
+ final double[] b, final double[] c, final boolean maximization, final boolean[] equality) {
return new SimplexBLAND(A, b, c, maximization, equality);
}
}
\ No newline at end of file
diff --git a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/SimplexLEXICO.java b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/SimplexLEXICO.java
index 76d5bb267be1b9fe7256b788c1f904f0ca572a49..690331f06554ab781991b24688b7322c5c72627e 100644
--- a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/SimplexLEXICO.java
+++ b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/SimplexLEXICO.java
@@ -8,30 +8,33 @@ import java.util.ArrayList;
* Part of the Linear Programming plugin for ICY http://icy.bioimageanalysis.org
*
* @author Nicolas Chenouard (nicolas.chenouard.dev@gmail.com)
- * @version 1.0
- * @date 2014-04-21
- * @license gpl v3.0
- *
*/
public class SimplexLEXICO extends CanonicalSimplexProgram
{
/**
* Constructor specifying parameters of the linear programming problem.
- * @param A constraint matrix
- * @param b constraint values
- * @param c linear objective function weights
- * @param maximization maximization problem if true, minimization else.
- * @param equality indicates whether each constraint is an equality. Else it is <=.
- * */
- public SimplexLEXICO(double[][] A, double[] b, double[] c,
- boolean maximization, boolean[] equality) {
+ *
+ * @param A
+ * constraint matrix
+ * @param b
+ * constraint values
+ * @param c
+ * linear objective function weights
+ * @param maximization
+ * maximization problem if true, minimization else.
+ * @param equality
+ * indicates whether each constraint is an equality. Else it is
+ * <=.
+ */
+ public SimplexLEXICO(final double[][] A, final double[] b, final double[] c,
+ final boolean maximization, final boolean[] equality) {
super(A, b, c, maximization, equality);
}
/**
* Constructor specifying parameters of the linear programming problem.
* @param p Parameters of the linear programming problem.
*/
- public SimplexLEXICO(CanonicalProgramParameters p) {
+ public SimplexLEXICO(final CanonicalProgramParameters p) {
super(p);
}
@@ -42,7 +45,7 @@ public class SimplexLEXICO extends CanonicalSimplexProgram
* @return the column index in the tableau
* */
@Override
- protected int getPivotColumn(TableauWithSlackVariables tableau, boolean max) {
+ protected int getPivotColumn(final TableauWithSlackVariables tableau, final boolean max) {
// max score choice strategy
if (max)
{
@@ -86,22 +89,22 @@ public class SimplexLEXICO extends CanonicalSimplexProgram
* @return the row index in the tableau
* */
@Override
- protected int getRowidx(TableauWithSlackVariables tableau, int colIdx)
+ protected int getRowidx(final TableauWithSlackVariables tableau, final int colIdx)
{
int rowIdx = -1;
int numBasicRow = 0;
- ArrayList<Integer> basicCols = new ArrayList<Integer>();
+ final ArrayList<Integer> basicCols = new ArrayList<Integer>();
for (int i = 0; i < tableau.originalColOrder.length; i++)
if (tableau.originalColOrder[i] < 0)
{
basicCols.add(i);
numBasicRow ++;
}
- double[] minLexico = new double[numBasicRow + 1];
+ final double[] minLexico = new double[numBasicRow + 1];
boolean found = false;
for (int i = 0; i < tableau.xCol.length; i++)
{
- double val = tableau.tableau[i][colIdx];
+ final double val = tableau.tableau[i][colIdx];
if (val > tol)
{
int k = 0;
@@ -116,9 +119,9 @@ public class SimplexLEXICO extends CanonicalSimplexProgram
if (tableau.xCol[i]/val == minLexico[k])
{
k++;
- for (Integer ii:basicCols)
+ for (final Integer ii:basicCols)
{
- double t = tableau.tableau[i][ii]/val;
+ final double t = tableau.tableau[i][ii]/val;
if (t > minLexico[k])
{
isMinLexico = false;
@@ -153,17 +156,25 @@ public class SimplexLEXICO extends CanonicalSimplexProgram
}
return rowIdx;
}
+
/**
* Duplicate the program
- * @param A constraint matrix
- * @param b constraint values
- * @param c linear objective function weights
- * @param maximization maximization problem if true, minimization else.
- * @param equality indicates whether each constraint is an equality. Else it is <=.
- * */
+ *
+ * @param A
+ * constraint matrix
+ * @param b
+ * constraint values
+ * @param c
+ * linear objective function weights
+ * @param maximization
+ * maximization problem if true, minimization else.
+ * @param equality
+ * indicates whether each constraint is an equality. Else it is
+ * <=.
+ */
@Override
- protected CanonicalSimplexProgram createNewProgram(double[][] A,
- double[] b, double[] c, boolean maximization, boolean[] equality) {
+ protected CanonicalSimplexProgram createNewProgram(final double[][] A,
+ final double[] b, final double[] c, final boolean maximization, final boolean[] equality) {
return new SimplexLEXICO(A, b, c, maximization, equality);
}
}
\ No newline at end of file
diff --git a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/SimplexMAX.java b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/SimplexMAX.java
index 403fa849c3686ca28e73ef794f8bbb74f07596d4..705ddab138910d7f4802c08a59432769f9030aae 100644
--- a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/SimplexMAX.java
+++ b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/SimplexMAX.java
@@ -8,30 +8,33 @@ package plugins.nchenouard.linearprogrammingfullsimplex;
* Part of the Linear Programming plugin for ICY http://icy.bioimageanalysis.org
*
* @author Nicolas Chenouard (nicolas.chenouard.dev@gmail.com)
- * @version 1.0
- * @date 2014-04-21
- * @license gpl v3.0
- *
*/
public class SimplexMAX extends CanonicalSimplexProgram
{
/**
* Constructor specifying parameters of the linear programming problem.
- * @param A constraint matrix
- * @param b constraint values
- * @param c linear objective function weights
- * @param maximization maximization problem if true, minimization else.
- * @param equality indicates whether each constraint is an equality. Else it is <=.
- * */
- public SimplexMAX(double[][] A, double[] b, double[] c,
- boolean maximization, boolean[] equality) {
+ *
+ * @param A
+ * constraint matrix
+ * @param b
+ * constraint values
+ * @param c
+ * linear objective function weights
+ * @param maximization
+ * maximization problem if true, minimization else.
+ * @param equality
+ * indicates whether each constraint is an equality. Else it is
+ * <=.
+ */
+ public SimplexMAX(final double[][] A, final double[] b, final double[] c,
+ final boolean maximization, final boolean[] equality) {
super(A, b, c, maximization, equality);
}
/**
* Constructor specifying parameters of the linear programming problem.
* @param p Parameters of the linear programming problem.
*/
- public SimplexMAX(CanonicalProgramParameters p)
+ public SimplexMAX(final CanonicalProgramParameters p)
{
super(p);
}
@@ -43,7 +46,7 @@ public class SimplexMAX extends CanonicalSimplexProgram
* @return the column index in the tableau
* */
@Override
- protected int getPivotColumn(TableauWithSlackVariables tableau, boolean max)
+ protected int getPivotColumn(final TableauWithSlackVariables tableau, final boolean max)
{
if (max)
{
@@ -83,14 +86,14 @@ public class SimplexMAX extends CanonicalSimplexProgram
* @return the row index in the tableau
* */
@Override
- protected int getRowidx(TableauWithSlackVariables tableau, int colIdx)
+ protected int getRowidx(final TableauWithSlackVariables tableau, final int colIdx)
{
boolean found = false;
double maxVal = -1;
int rowIdx = -1;
for (int i = 0; i < tableau.xCol.length; i++)
{
- double val = tableau.tableau[i][colIdx];
+ final double val = tableau.tableau[i][colIdx];
if (val > tol)
{
if (!found)
@@ -111,17 +114,25 @@ public class SimplexMAX extends CanonicalSimplexProgram
}
return rowIdx;
}
+
/**
* Duplicate the program
- * @param A constraint matrix
- * @param b constraint values
- * @param c linear objective function weights
- * @param maximization maximization problem if true, minimization else.
- * @param equality indicates whether each constraint is an equality. Else it is <=.
- * */
+ *
+ * @param A
+ * constraint matrix
+ * @param b
+ * constraint values
+ * @param c
+ * linear objective function weights
+ * @param maximization
+ * maximization problem if true, minimization else.
+ * @param equality
+ * indicates whether each constraint is an equality. Else it is
+ * <=.
+ */
@Override
- protected CanonicalSimplexProgram createNewProgram(double[][] A,
- double[] b, double[] c, boolean maximization, boolean[] equality) {
+ protected CanonicalSimplexProgram createNewProgram(final double[][] A,
+ final double[] b, final double[] c, final boolean maximization, final boolean[] equality) {
return new SimplexMAX(A, b, c, maximization, equality);
}
}
\ No newline at end of file
diff --git a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/TableauMinSlackObjective.java b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/TableauMinSlackObjective.java
index 1529bc281af79379e764b4515a059e717f3c23a5..229fc310425747f79541fbb6dfec99f370a43f03 100644
--- a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/TableauMinSlackObjective.java
+++ b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/TableauMinSlackObjective.java
@@ -7,28 +7,26 @@ package plugins.nchenouard.linearprogrammingfullsimplex;
* Part of the Linear Programming plugin for ICY http://icy.bioimageanalysis.org
*
* @author Nicolas Chenouard (nicolas.chenouard.dev@gmail.com)
- * @version 1.0
- * @date 2014-04-21
- * @license gpl v3.0
- *
*/
public class TableauMinSlackObjective extends TableauWithSlackVariables
{
/**
- * Create the tableau based on a linear program.
- * The scores in the tableau will not be initialized to their standard value but set to handle equality constraints.
+ * Create the tableau based on a linear program. The scores in the tableau
+ * will not be initialized to their standard value but set to handle
+ * equality constraints.
*
- * @param parameters parameters defining the linear optimization problem.
+ * @param simplexProgram
+ * parameters defining the linear optimization problem.
*/
- public TableauMinSlackObjective(CanonicalSimplexProgram simplexProgram) {
+ public TableauMinSlackObjective(final CanonicalSimplexProgram simplexProgram) {
super(simplexProgram.parameters.A);
// now make the slacks feasible
xCol = simplexProgram.parameters.b.clone(); // equal to b since we start with unit vectors as initial left vectors
// build the score row
scoreRow = new double[numCol];
// add a score for slacks corresponding to equality constraints
- double[] slackScores = new double[simplexProgram.parameters.equalityConstraints.length];
+ final double[] slackScores = new double[simplexProgram.parameters.equalityConstraints.length];
this.scoreValue = 0;
for (int i = 0; i < slackScores.length; i++)
if (simplexProgram.parameters.equalityConstraints[i])
@@ -59,9 +57,9 @@ public class TableauMinSlackObjective extends TableauWithSlackVariables
* @param c standard score for variables.
* @param slackScore score values for slack variables.
*/
- public void initScores(double[] c, double[] slackScore)
+ public void initScores(final double[] c, final double[] slackScore)
{
- double[] scoreValues = new double[numCol];
+ final double[] scoreValues = new double[numCol];
for (int i = 0; i < slackScore.length; i++)
scoreValues[i] = slackScore[i];
for (int i = 0; i < numCol; i++)
diff --git a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/TableauWithSlackVariables.java b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/TableauWithSlackVariables.java
index 6fb4246099e744ac9df59a9a3913abb511e943a8..bb5799272aef235bc45b337a000f0325bf79d295 100644
--- a/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/TableauWithSlackVariables.java
+++ b/src/main/java/plugins/nchenouard/linearprogrammingfullsimplex/TableauWithSlackVariables.java
@@ -8,10 +8,6 @@ package plugins.nchenouard.linearprogrammingfullsimplex;
* Part of the Linear Programming plugin for ICY http://icy.bioimageanalysis.org
*
* @author Nicolas Chenouard (nicolas.chenouard.dev@gmail.com)
- * @version 1.0
- * @date 2014-04-21
- * @license gpl v3.0
- *
*/
public class TableauWithSlackVariables {
/**
@@ -65,7 +61,7 @@ public class TableauWithSlackVariables {
*
* @param A table of linear combinations of the variable, each defining a constraint.
*/
- public TableauWithSlackVariables(double[][] A)
+ public TableauWithSlackVariables(final double[][] A)
{
createVectors(A);
}
@@ -75,7 +71,7 @@ public class TableauWithSlackVariables {
*
* @param parameters parameters defining the linear optimization problem.
*/
- public TableauWithSlackVariables(CanonicalProgramParameters parameters)
+ public TableauWithSlackVariables(final CanonicalProgramParameters parameters)
{
createVectors(parameters.A); // constraint value column
xCol = parameters.b.clone(); // equal to b since we start with unit vectors as initial left vectors
@@ -88,9 +84,9 @@ public class TableauWithSlackVariables {
*
* @param changeSlack indicate whether the score of each slack variable should be changed
*/
- protected void setUnitScoreToSlackVars(boolean[] changeSlack)
+ protected void setUnitScoreToSlackVars(final boolean[] changeSlack)
{
- double[] scoreValues = new double[numCol];
+ final double[] scoreValues = new double[numCol];
// recompute scoreValues based on c
int k = 0;
for (int i = 0; i < originalColOrder.length; i++)
@@ -134,9 +130,9 @@ public class TableauWithSlackVariables {
* Create column and basis vectors based on the constraint matrix
* @param A Constraint matrix. Each element A[i] defines a linear combination of the variable corresponding to a constraint.
* */
- protected void createVectors(double[][] A)
+ protected void createVectors(final double[][] A)
{
- int numConstraints = A.length;
+ final int numConstraints = A.length;
numVariables = A[0].length;
numCol = numConstraints + numVariables;
numRows = numConstraints;
@@ -173,7 +169,7 @@ public class TableauWithSlackVariables {
System.out.println("Column vectors");
for (int i = 0; i < columnVectors.length; i++)
{
- double[] vector = columnVectors[i];
+ final double[] vector = columnVectors[i];
System.out.print("a"+i+" = [");
for (int j = 0; j < vector.length; j++)
System.out.print(vector[j]+", ");
@@ -182,7 +178,7 @@ public class TableauWithSlackVariables {
System.out.println("Basis vectors");
for (int i = 0; i < leftVectorsIdx.length; i++)
{
- double[] vector = columnVectors[leftVectorsIdx[i]];
+ final double[] vector = columnVectors[leftVectorsIdx[i]];
System.out.print("v"+i+" = [");
for (int j = 0; j < vector.length; j++)
System.out.print(vector[j]+", ");
@@ -216,16 +212,16 @@ public class TableauWithSlackVariables {
* @param colIdx index of the pivoting column in the tableau
* @param rowIdx index of the pivoting row in the tableau
*/
- public void pivot(int colIdx, int rowIdx)
+ public void pivot(final int colIdx, final int rowIdx)
{
leftVectorsIdx[rowIdx] = colIdx;
- double pivotVal = tableau[rowIdx][colIdx];
- double[] pivotRow = tableau[rowIdx];
- double[] pivotCol = new double[numRows];
+ final double pivotVal = tableau[rowIdx][colIdx];
+ final double[] pivotRow = tableau[rowIdx];
+ final double[] pivotCol = new double[numRows];
for (int i = 0; i < numRows; i++)
pivotCol[i] = tableau[i][colIdx];
- double scorePivot = scoreRow[colIdx];
+ final double scorePivot = scoreRow[colIdx];
// update the score row
for (int j = 0; j < colIdx; j++)
@@ -271,10 +267,10 @@ public class TableauWithSlackVariables {
* */
public double[] getSolution()
{
- double[] solution = new double[numVariables];
+ final double[] solution = new double[numVariables];
for (int i = 0; i < leftVectorsIdx.length; i++)
{
- int originalIdx = originalColOrder[leftVectorsIdx[i]];
+ final int originalIdx = originalColOrder[leftVectorsIdx[i]];
if (originalIdx >= 0)
solution[originalIdx] = xCol[i];
@@ -284,9 +280,9 @@ public class TableauWithSlackVariables {
/**
* Modify scores in the tableau according to a set of scores for the constraints
* */
- public void modifyScores(double[] c)
+ public void modifyScores(final double[] c)
{
- double[] scoreValues = new double[numCol];
+ final double[] scoreValues = new double[numCol];
for (int i = 0; i < numCol; i++)
{
if (originalColOrder[i] >= 0)
@@ -322,9 +318,9 @@ public class TableauWithSlackVariables {
* Modify scores in the tableau according to a set of scores for the constraints
* Same as modifyScoresBis. Just a backup function. Still working on it.
* */
- public void modifyScoresBis(double[] c)
+ public void modifyScoresBis(final double[] c)
{
- double[] scoreValues = new double[numCol];
+ final double[] scoreValues = new double[numCol];
for (int i = 0; i < numCol; i++)
{
if (originalColOrder[i] >= 0)