Examples with OptimizationResultSet cbit.vcell.opt.OptimizationResultSet used on opensource projects

Example 16 with OptimizationResultSet

use of cbit.vcell.opt.OptimizationResultSet in project vcell by virtualcell.

the class ParameterEstimationTask method setOptimizationResultSet.

/**
 * Sets the optimizationResultSet property (cbit.vcell.opt.OptimizationResultSet) value.
 * @param optimizationResultSet The new value for the property.
 * @see #getOptimizationResultSet
 */
public void setOptimizationResultSet(OptimizationResultSet optimizationResultSet) {
    OptimizationResultSet oldValue = fieldOptimizationResultSet;
    fieldOptimizationResultSet = optimizationResultSet;
    firePropertyChange(PROPERTY_NAME_OPTIMIZATION_RESULT_SET, oldValue, optimizationResultSet);
}

Example 17 with OptimizationResultSet

use of cbit.vcell.opt.OptimizationResultSet in project vcell by virtualcell.

the class PowellOptimizationSolver method solve.

/**
 * Insert the method's description here.
 * Creation date: (3/5/00 11:15:15 PM)
 * @return double[]
 * @param optSpec cbit.vcell.opt.OptimizationSpec
 * @exception java.io.IOException The exception description.
 * @exception cbit.vcell.parser.ExpressionException The exception description.
 * @exception cbit.vcell.opt.OptimizationException The exception description.
 */
public OptimizationResultSet solve(OptimizationSpec os, OptimizationSolverSpec optSolverSpec, OptSolverCallbacks optSolverCallbacks) throws java.io.IOException, cbit.vcell.parser.ExpressionException, OptimizationException {
    final double power = 2.0;
    final double MU_START = 0.1;
    final double MU_END = 100000.0;
    final double MU_STEP = 10.0;
    AugmentedObjectiveFunction augmentedObjFunc = OptUtils.getAugmentedObjectiveFunction(os, power, MU_START, optSolverCallbacks);
    // 
    // initialize starting guess
    // 
    Parameter[] parameters = os.getParameters();
    double[] parameterValues = new double[parameters.length];
    for (int i = 0; i < parameters.length; i++) {
        parameterValues[i] = parameters[i].getInitialGuess();
        System.out.println("initial " + parameters[i].getName() + " = " + parameterValues[i]);
    }
    // 
    // get initial direction set
    // 
    double[][] xi = new double[parameterValues.length][parameterValues.length];
    for (int i = 0; i < parameterValues.length; i++) {
        for (int j = 0; j < parameterValues.length; j++) {
            xi[i][j] = (i == j ? 1.0 : 0.0);
        }
    }
    final double ftol = 1e-6;
    double fret = augmentedObjFunc.f(parameterValues);
    PowellSolver powellSolver = new PowellSolver();
    for (double mu = MU_START; mu <= MU_END; mu *= MU_STEP) {
        try {
            if (optSolverCallbacks.getStopRequested()) {
                break;
            }
            augmentedObjFunc.setMu(mu);
            fret = powellSolver.powell(parameterValues.length, parameterValues, xi, ftol, augmentedObjFunc);
            System.out.println("mu=" + mu + ", function value=" + fret);
            if (augmentedObjFunc.getPenalty(parameterValues) == 0.0) {
                break;
            }
        } catch (Exception ex) {
            ex.printStackTrace();
            break;
        }
    }
    OptimizationStatus optStatus = new OptimizationStatus(OptimizationStatus.NORMAL_TERMINATION, "Normal Termination");
    ODESolverResultSet odeSolverResultSet = null;
    if (optSolverCallbacks.getStopRequested()) {
        optStatus = new OptimizationStatus(OptimizationStatus.STOPPED_BY_USER, "Stopped by user");
    }
    parameterValues = optSolverCallbacks.getBestEvaluation().getParameterValues();
    fret = optSolverCallbacks.getBestEvaluation().getObjectiveFunctionValue();
    odeSolverResultSet = optSolverCallbacks.getBestResultSet();
    for (int i = 0; i < parameters.length; i++) {
        System.out.println("final " + parameters[i].getName() + " = " + parameterValues[i]);
    }
    OptRunResultSet bestResult = new OptRunResultSet(parameterValues, new Double(fret), optSolverCallbacks.getEvaluationCount(), optStatus);
    return new OptimizationResultSet(new OptSolverResultSet(os.getParameterNames(), bestResult), odeSolverResultSet);
}

Example 18 with OptimizationResultSet

use of cbit.vcell.opt.OptimizationResultSet in project vcell by virtualcell.

the class CurveFitting method solve.

public static OptimizationResultSet solve(ExplicitFitObjectiveFunction.ExpressionDataPair[] expDataPairs, Parameter[] parameters, double[] time, double[][] data, String[] colNames, Weights weights) throws ExpressionException, OptimizationException, IOException {
    // choose optimization solver, currently we have Powell
    PowellOptimizationSolver optService = new PowellOptimizationSolver();
    OptimizationSpec optSpec = new OptimizationSpec();
    // create simple reference data, columns: t + dataColumns
    double[][] realData = new double[1 + data.length][time.length];
    for (// add time column
    int i = 0; // add time column
    i < time.length; // add time column
    i++) {
        realData[0][i] = time[i];
    }
    for (// add each data column to realData
    int i = 0; // add each data column to realData
    i < data.length; // add each data column to realData
    i++) {
        for (int j = 0; j < time.length; j++) {
            realData[1 + i][j] = data[i][j];
        }
    }
    SimpleReferenceData refData = new SimpleReferenceData(colNames, weights, realData);
    // send to optimization service
    optSpec.setObjectiveFunction(new ExplicitFitObjectiveFunction(expDataPairs, refData));
    double[] parameterValues = new double[parameters.length];
    for (int i = 0; i < parameters.length; i++) {
        parameterValues[i] = parameters[i].getInitialGuess();
        System.out.println("initial " + parameters[i].getName() + " = " + parameterValues[i] + ";\tLB = " + parameters[i].getLowerBound() + ";\tUB = " + parameters[i].getUpperBound());
    }
    // get the initial guess to send it to the f() function. ....
    for (int i = 0; i < parameters.length; i++) {
        optSpec.addParameter(parameters[i]);
    }
    // Parameters in OptimizationSolverSpec are solver type and objective function change tolerance.
    OptimizationSolverSpec optSolverSpec = new OptimizationSolverSpec(OptimizationSolverSpec.SOLVERTYPE_POWELL, 0.000001);
    OptSolverCallbacks optSolverCallbacks = new DefaultOptSolverCallbacks();
    OptimizationResultSet optResultSet = null;
    optResultSet = optService.solve(optSpec, optSolverSpec, optSolverCallbacks);
    return optResultSet;
}

Example 19 with OptimizationResultSet

use of cbit.vcell.opt.OptimizationResultSet in project vcell by virtualcell.

the class CurveFitting method solve.

public static OptimizationResultSet solve(ExplicitFitObjectiveFunction.ExpressionDataPair[] expDataPairs, Parameter[] parameters, double[] time, double[][] data, String[] colNames, Weights weights) throws ExpressionException, OptimizationException, IOException {
    // choose optimization solver, currently we have Powell and CFSQP
    PowellOptimizationSolver optService = new PowellOptimizationSolver();
    OptimizationSpec optSpec = new OptimizationSpec();
    // create simple reference data, columns: t + dataColumns
    double[][] realData = new double[1 + data.length][time.length];
    for (// add time column
    int i = 0; // add time column
    i < time.length; // add time column
    i++) {
        realData[0][i] = time[i];
    }
    for (// add each data column to realData
    int i = 0; // add each data column to realData
    i < data.length; // add each data column to realData
    i++) {
        for (int j = 0; j < time.length; j++) {
            realData[1 + i][j] = data[i][j];
        }
    }
    SimpleReferenceData refData = new SimpleReferenceData(colNames, weights, realData);
    // send to optimization service
    optSpec.setObjectiveFunction(new ExplicitFitObjectiveFunction(expDataPairs, refData));
    double[] parameterValues = new double[parameters.length];
    for (int i = 0; i < parameters.length; i++) {
        parameterValues[i] = parameters[i].getInitialGuess();
        System.out.println("initial " + parameters[i].getName() + " = " + parameterValues[i] + ";\tLB = " + parameters[i].getLowerBound() + ";\tUB = " + parameters[i].getUpperBound());
    }
    // get the initial guess to send it to the f() function. ....
    for (int i = 0; i < parameters.length; i++) {
        optSpec.addParameter(parameters[i]);
    }
    // Parameters in OptimizationSolverSpec are solver type and objective function change tolerance.
    OptimizationSolverSpec optSolverSpec = new OptimizationSolverSpec(OptimizationSolverSpec.SOLVERTYPE_POWELL, 0.000001);
    OptSolverCallbacks optSolverCallbacks = new DefaultOptSolverCallbacks();
    OptimizationResultSet optResultSet = null;
    optResultSet = optService.solve(optSpec, optSolverSpec, optSolverCallbacks);
    return optResultSet;
}

Example 20 with OptimizationResultSet

use of cbit.vcell.opt.OptimizationResultSet in project vcell by virtualcell.

the class CurveFitting method solveSpatial.

public static OptimizationResultSet solveSpatial(Simulation sim, Parameter[] parameters, SpatialReferenceData refData, File dataDir, FieldDataIdentifierSpec[] fieldDataIDSs) throws ExpressionException, OptimizationException, IOException {
    // choose optimization solver, currently we have Powell and CFSQP
    PowellOptimizationSolver optService = new PowellOptimizationSolver();
    OptimizationSpec optSpec = new OptimizationSpec();
    // send to optimization service
    optSpec.setObjectiveFunction(new PdeObjectiveFunction(sim.getMathDescription(), refData, dataDir, fieldDataIDSs));
    double[] parameterValues = new double[parameters.length];
    for (int i = 0; i < parameters.length; i++) {
        parameterValues[i] = parameters[i].getInitialGuess();
        System.out.println("initial " + parameters[i].getName() + " = " + parameterValues[i] + ";\tLB = " + parameters[i].getLowerBound() + ";\tUB = " + parameters[i].getUpperBound());
    }
    // get the initial guess to send it to the f() function. ....
    for (int i = 0; i < parameters.length; i++) {
        optSpec.addParameter(parameters[i]);
    }
    // Parameters in OptimizationSolverSpec are solver type and objective function change tolerance.
    OptimizationSolverSpec optSolverSpec = new OptimizationSolverSpec(OptimizationSolverSpec.SOLVERTYPE_POWELL, 0.000001);
    OptSolverCallbacks optSolverCallbacks = new DefaultOptSolverCallbacks();
    OptimizationResultSet optResultSet = null;
    optResultSet = optService.solve(optSpec, optSolverSpec, optSolverCallbacks);
    OptSolverResultSet optSolverResultSet = optResultSet.getOptSolverResultSet();
    String[] paramNames = optSolverResultSet.getParameterNames();
    double[] paramValues = optSolverResultSet.getBestEstimates();
    for (int i = 0; i < paramNames.length; i++) {
        System.out.println("finally:   " + paramNames[i] + " = " + paramValues[i]);
    }
    return optResultSet;
}