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package net.sourceforge.combean.samples.mathprog.lp.matrixrounding; |
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import net.sourceforge.combean.interfaces.mathprog.linalg.Matrix; |
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import net.sourceforge.combean.interfaces.mathprog.linalg.SparseVector; |
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import net.sourceforge.combean.interfaces.mathprog.linalg.VectorOrientation; |
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import net.sourceforge.combean.interfaces.mathprog.lp.LPConstraint; |
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import net.sourceforge.combean.interfaces.mathprog.lp.LPVariable; |
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import net.sourceforge.combean.interfaces.mathprog.lp.model.LPConstraintSequence; |
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import net.sourceforge.combean.interfaces.mathprog.lp.model.LPModelRows; |
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import net.sourceforge.combean.interfaces.mathprog.lp.model.LPModelSolver; |
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import net.sourceforge.combean.interfaces.mathprog.lp.model.LPSparseVector; |
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import net.sourceforge.combean.interfaces.mathprog.lp.model.LPVariableSequence; |
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import net.sourceforge.combean.mathprog.linalg.SparseVectorWithConstantPattern; |
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import net.sourceforge.combean.mathprog.linalg.statics.SparseVectorUtil; |
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import net.sourceforge.combean.mathprog.lp.DoubleLPConstraint; |
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import net.sourceforge.combean.mathprog.lp.DoubleLPVariable; |
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import net.sourceforge.combean.mathprog.lp.model.AbstractSimpleIndexLPConstrainedRowsWithVars; |
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import net.sourceforge.combean.mathprog.lp.model.SparseVectorAsLPVector; |
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public class MatrixToRoundAsLP |
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extends AbstractSimpleIndexLPConstrainedRowsWithVars |
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implements LPModelRows, LPConstraintSequence, LPVariableSequence { |
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53 | 6 | private Matrix m = null; |
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55 | 6 | private double[] rowsums = null; |
56 | 6 | private double[] colsums = null; |
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public MatrixToRoundAsLP(Matrix matrixToRound) { |
64 | 6 | super("", ""); |
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66 | 6 | this.m = matrixToRound; |
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68 | 6 | this.rowsums = new double[this.m.getNumRows()]; |
69 | 24 | for (int row = 0; row < this.rowsums.length; row++) { |
70 | 18 | this.rowsums[row] = |
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SparseVectorUtil.sum(this.m.getRowVector(row)); |
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} |
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74 | 6 | this.colsums = new double[this.m.getNumColumns()]; |
75 | 24 | for (int col = 0; col < this.colsums.length; col++) { |
76 | 18 | this.colsums[col] = |
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SparseVectorUtil.sum(this.m.getColumnVector(col)); |
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} |
79 | 6 | } |
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public int getNumColumns() { |
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86 | 300 | return this.m.getNumColumns() * this.m.getNumRows(); |
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} |
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public int getNumRows() { |
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94 | 84 | return 2 * (this.m.getNumColumns() + this.m.getNumRows()); |
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} |
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public LPVariable getLPVariable(int localColumn) { |
102 | 54 | double val = this.m.getDoubleAt( |
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localColumn / this.m.getNumColumns(), |
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localColumn % this.m.getNumColumns()); |
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111 | 54 | return new DoubleLPVariable((localColumn + 1.0)*(localColumn + 1.0) |
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+ getNumVars()*getNumVars()*getNumVars(), |
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Math.floor(val), Math.ceil(val)); |
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} |
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public LPSparseVector getRowVector(int localRow) { |
122 | 72 | SparseVector result = null; |
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124 | 72 | if (localRow >= 2*this.m.getNumRows()) { |
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|
126 | 36 | int colInOrigM = localRow/2 - this.m.getNumRows(); |
127 | 36 | result = new SparseVectorWithConstantPattern( |
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getNumColumns(), |
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1.0, |
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colInOrigM, |
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colInOrigM + this.m.getNumColumns()*(this.m.getNumRows()-1), |
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this.m.getNumColumns()); |
133 | 36 | } |
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else { |
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|
136 | 36 | int rowInOrigM = localRow / 2; |
137 | 36 | result = new SparseVectorWithConstantPattern ( |
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getNumColumns(), |
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1.0, |
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rowInOrigM * this.m.getNumColumns(), |
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(rowInOrigM+1) * this.m.getNumColumns() - 1, |
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1); |
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} |
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145 | 72 | return new SparseVectorAsLPVector(result, "", |
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VectorOrientation.ROWWISE); |
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} |
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public LPConstraint getLPConstraint(int localRow) { |
153 | 72 | byte rel = (localRow % 2 == 0) ? LPConstraint.REL_GREATER : LPConstraint.REL_LESS; |
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155 | 72 | double val = 0.0; |
156 | 72 | if (localRow >= 2*this.m.getNumRows()) { |
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158 | 36 | val = this.colsums[localRow/2 - this.m.getNumRows()]; |
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} |
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else { |
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|
162 | 36 | val = this.rowsums[localRow/2]; |
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} |
164 | 72 | if (rel == LPConstraint.REL_GREATER) { |
165 | 36 | val = Math.floor(val); |
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} |
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else { |
168 | 36 | val = Math.ceil(val); |
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} |
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171 | 72 | return new DoubleLPConstraint("row", rel, val); |
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} |
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public double[][] getRoundedMatrix(LPModelSolver solver) { |
181 | 6 | double[][] result = |
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new double[this.m.getNumRows()][this.m.getNumColumns()]; |
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184 | 24 | for (int row = 0; row < this.m.getNumRows(); row++) { |
185 | 72 | for (int col = 0; col < this.m.getNumColumns(); col++) { |
186 | 54 | result[row][col] = |
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solver.getSolution(getColumnModelIndex( |
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row * this.m.getNumColumns() + col)); |
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} |
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} |
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192 | 6 | return result; |
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} |
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} |