List of operate() Examples

Examples of operate()

com.scaleunlimited.helpful.operations.MboxSplitterFunction.operate()
com.sun.corba.se.spi.orb.Operation.operate()
Apply some function to a value and return the result.
edu.pku.sei.metric.analyzer.math.MathOperator.operate()
Do the math operation on the metric values and set to the metric element @param metricElement @param descriptor
org.apache.commons.math.linear.Array2DRowRealMatrix.operate()
{@inheritDoc}
org.apache.commons.math.linear.RealMatrix.operate()
Returns the result of multiplying this by the vector v. @param v the vector to operate on @return this*v @throws IllegalArgumentException if columnDimension != v.size()
org.apache.commons.math3.linear.Array2DRowRealMatrix.operate()
{@inheritDoc}
org.apache.commons.math3.linear.RealMatrix.operate()
Returns the result of multiplying this by the vector v. @param v the vector to operate on @return this*v @throws IllegalArgumentException if columnDimension != v.size()
org.springframework.expression.OperatorOverloader.operate()
Execute the specified operation on two operands, returning a result. See {@link Operation} for supported operations. @param operation the operation to be performed @param leftOperand the left operand @param rightOperand the right operand @return the result of performing the operation on the two operands @throws EvaluationException if there is a problem performing the operation

Examples of org.apache.commons.math.linear.Array2DRowRealMatrix.operate()

              { 1.0, 0.0 },
              { 0.0, 1.0 }
          }, false);
      LeastSquaresConverter ls = new LeastSquaresConverter(new MultivariateVectorialFunction() {
          public double[] value(double[] variables) {
              return factors.operate(variables);
          }
      }, new double[] { 2.0, -3.0 }, new Array2DRowRealMatrix(new double [][] {
          { 1.0, 1.2 }, { 1.2, 2.0 }
      }));
      NelderMead optimizer = new NelderMead();

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Examples of org.apache.commons.math.linear.RealMatrix.operate()

              { 1.0, 0.0 },
              { 0.0, 1.0 }
          }, false);
      LeastSquaresConverter ls = new LeastSquaresConverter(new MultivariateVectorialFunction() {
          public double[] value(double[] variables) {
              return factors.operate(variables);
          }
      }, new double[] { 2.0, -3.0 });
      NelderMead optimizer = new NelderMead();
      optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1.0, 1.0e-6));
      optimizer.setMaxIterations(200);

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Examples of org.apache.commons.math.linear.RealMatrix.operate()

              { 1.0, 0.0 },
              { 0.0, 1.0 }
          }, false);
      LeastSquaresConverter ls = new LeastSquaresConverter(new MultivariateVectorialFunction() {
          public double[] value(double[] variables) {
              return factors.operate(variables);
          }
      }, new double[] { 2.0, -3.0 }, new double[] { 10.0, 0.1 });
      NelderMead optimizer = new NelderMead();
      optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1.0, 1.0e-6));
      optimizer.setMaxIterations(200);

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Examples of org.apache.commons.math.linear.RealMatrix.operate()

              { 1.0, 0.0 },
              { 0.0, 1.0 }
          }, false);
      LeastSquaresConverter ls = new LeastSquaresConverter(new MultivariateVectorialFunction() {
          public double[] value(double[] variables) {
              return factors.operate(variables);
          }
      }, new double[] { 2.0, -3.0 }, new Array2DRowRealMatrix(new double [][] {
          { 1.0, 1.2 }, { 1.2, 2.0 }
      }));
      NelderMead optimizer = new NelderMead();

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Examples of org.apache.commons.math.linear.RealMatrix.operate()

        final int nModels = 10000;
        for (int i = 0; i < nModels; i++) {
            
            // Generate y = xb + u with u cov
            RealVector u = MatrixUtils.createRealVector(gen.nextVector());
            double[] y = u.add(x.operate(b)).getData();
            
            // Estimate OLS parameters
            ols.newYSampleData(y);
            RealVector olsBeta = ols.calculateBeta();

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Examples of org.apache.commons.math.linear.RealMatrix.operate()

              { 1.0, 0.0 },
              { 0.0, 1.0 }
          }, false);
      LeastSquaresConverter ls = new LeastSquaresConverter(new MultivariateVectorialFunction() {
          public double[] value(double[] variables) {
              return factors.operate(variables);
          }
      }, new double[] { 2.0, -3.0 });
      NelderMead optimizer = new NelderMead();
      optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1.0, 1.0e-6));
      optimizer.setMaxIterations(200);

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Examples of org.apache.commons.math.linear.RealMatrix.operate()

              { 1.0, 0.0 },
              { 0.0, 1.0 }
          }, false);
      LeastSquaresConverter ls = new LeastSquaresConverter(new MultivariateVectorialFunction() {
          public double[] value(double[] variables) {
              return factors.operate(variables);
          }
      }, new double[] { 2.0, -3.0 }, new double[] { 10.0, 0.1 });
      NelderMead optimizer = new NelderMead();
      optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1.0, 1.0e-6));
      optimizer.setMaxIterations(200);

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Examples of org.apache.commons.math3.linear.Array2DRowRealMatrix.operate()

                    { 1, 0 },
                    { 0, 1 }
                }, false);
        LeastSquaresConverter ls = new LeastSquaresConverter(new MultivariateVectorFunction() {
                public double[] value(double[] variables) {
                    return factors.operate(variables);
                }
            }, new double[] { 2.0, -3.0 });
        SimplexOptimizer optimizer = new SimplexOptimizer(-1, 1e-6);
        optimizer.setSimplex(new NelderMeadSimplex(2));
        PointValuePair optimum =

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Examples of org.apache.commons.math3.linear.Array2DRowRealMatrix.operate()

                    { 1, 0 },
                    { 0, 1 }
                }, false);
        LeastSquaresConverter ls = new LeastSquaresConverter(new MultivariateVectorFunction() {
                public double[] value(double[] variables) {
                    return factors.operate(variables);
                }
            }, new double[] { 2, -3 }, new double[] { 10, 0.1 });
        SimplexOptimizer optimizer = new SimplexOptimizer(-1, 1e-6);
        optimizer.setSimplex(new NelderMeadSimplex(2));
        PointValuePair optimum =

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Examples of org.apache.commons.math3.linear.Array2DRowRealMatrix.operate()

                    { 1, 0 },
                    { 0, 1 }
                }, false);
        LeastSquaresConverter ls = new LeastSquaresConverter(new MultivariateVectorFunction() {
                public double[] value(double[] variables) {
                    return factors.operate(variables);
                }
            }, new double[] { 2, -3 }, new Array2DRowRealMatrix(new double [][] {
                    { 1, 1.2 }, { 1.2, 2 }
                }));
        SimplexOptimizer optimizer = new SimplexOptimizer(-1, 1e-6);

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