Package org.apache.commons.math.linear

Examples of org.apache.commons.math.linear.ArrayRealVector

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        assertEquals(0, es.solve(b).subtract(xRef).getNorm(), 2.0e-12);

        // using double[]
        for (int i = 0; i < b.getColumnDimension(); ++i) {
            assertEquals(0,
                         new ArrayRealVector(es.solve(b.getColumn(i))).subtract(xRef.getColumnVector(i)).getNorm(),
                         2.0e-11);
        }

        // using Array2DRowRealMatrix
        for (int i = 0; i < b.getColumnDimension(); ++i) {
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        assertEquals(0, solver.solve(b).subtract(xRef).getNorm(), normTolerance);

        // using double[]
        for (int i = 0; i < b.getColumnDimension(); ++i) {
            assertEquals(0,
                         new ArrayRealVector(solver.solve(b.getColumn(i))).subtract(xRef.getColumnVector(i)).getNorm(),
                         1.0e-13);
        }

        // using Array2DRowRealMatrix
        for (int i = 0; i < b.getColumnDimension(); ++i) {
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            for (int j = index + 1; j < length; j++) {
                sum += coefficients.getEntry(index, j) * x[j];
            }
            x[index] = (constants.getEntry(index) - sum) / coefficients.getEntry(index, index);
        }
        return new ArrayRealVector(x);
    }
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    /**
     * @param coefficients The coefficients for the linear equation being optimized
     * @param constantTerm The constant term of the linear equation
     */
    public LinearObjectiveFunction(double[] coefficients, double constantTerm) {
        this(new ArrayRealVector(coefficients), constantTerm);
    }
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     * @param relationship The type of (in)equality used in the constraint
     * @param value The value of the constraint (right hand side)
     */
    public LinearConstraint(final double[] coefficients, final Relationship relationship,
                            final double value) {
        this(new ArrayRealVector(coefficients), relationship, value);
    }
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                            final double[] rhsCoefficients, final double rhsConstant) {
        double[] sub = new double[lhsCoefficients.length];
        for (int i = 0; i < sub.length; ++i) {
            sub[i] = lhsCoefficients[i] - rhsCoefficients[i];
        }
        this.coefficients = new ArrayRealVector(sub, false);
        this.relationship = relationship;
        this.value        = rhsConstant - lhsConstant;
    }
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        assertEquals(0, solver.solve(b).subtract(xRef).getNorm(), 1.0e-13);

        // using double[]
        for (int i = 0; i < b.getColumnDimension(); ++i) {
            assertEquals(0,
                         new ArrayRealVector(solver.solve(b.getColumn(i))).subtract(xRef.getColumnVector(i)).getNorm(),
                         1.0e-13);
        }

        // using ArrayRealVector
        for (int i = 0; i < b.getColumnDimension(); ++i) {
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            for (int j = 1; j < nvars + 1; j++) {
                x[i][j] = data[pointer++];
            }
        }
        this.X = new Array2DRowRealMatrix(x);
        this.Y = new ArrayRealVector(y);
    }
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     * Loads new y sample data, overriding any previous sample
     *
     * @param y the [n,1] array representing the y sample
     */
    protected void newYSampleData(double[] y) {
        this.Y = new ArrayRealVector(y);
    }
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    /**
     * @param coefficients The coefficients for the linear equation being optimized
     * @param constantTerm The constant term of the linear equation
     */
    public LinearObjectiveFunction(double[] coefficients, double constantTerm) {
        this(new ArrayRealVector(coefficients), constantTerm);
    }
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