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

Example 56 with Parameter

use of cbit.vcell.opt.Parameter 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 57 with Parameter

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

the class DisplayProfileLikelihoodPlotsOp method getSummaryFromProfileData.

// getting a profileSummary for each parameter that has acquired a profile likelihood distribution
ProfileSummaryData getSummaryFromProfileData(ProfileData profileData) {
    ArrayList<ProfileDataElement> profileElements = profileData.getProfileDataElements();
    int dataSize = profileElements.size();
    double[] paramValArray = new double[dataSize];
    double[] errorArray = new double[dataSize];
    if (dataSize > 0) {
        // profile likelihood curve
        String paramName = profileElements.get(0).getParamName();
        // find the parameter to locate the upper and lower bounds
        Parameter parameter = null;
        Parameter[] bestParameters = profileElements.get(0).getBestParameters();
        for (int i = 0; i < bestParameters.length; i++) {
            if (bestParameters[i] != null && bestParameters[i].getName().equals(paramName)) {
                parameter = bestParameters[i];
            }
        }
        // double logLowerBound = (lowerBound == 0)? 0: Math.log10(lowerBound);
        for (int i = 0; i < dataSize; i++) {
            paramValArray[i] = profileElements.get(i).getParameterValue();
            errorArray[i] = profileElements.get(i).getLikelihood();
        }
        PlotData dataPlot = new PlotData(paramValArray, errorArray);
        // get confidence interval line
        // make array copy in order to not change the data orders afte the sorting
        double[] paramValArrayCopy = new double[paramValArray.length];
        System.arraycopy(paramValArray, 0, paramValArrayCopy, 0, paramValArray.length);
        double[] errorArrayCopy = new double[errorArray.length];
        System.arraycopy(errorArray, 0, errorArrayCopy, 0, errorArray.length);
        DescriptiveStatistics paramValStat = DescriptiveStatistics.CreateBasicStatistics(paramValArrayCopy);
        DescriptiveStatistics errorStat = DescriptiveStatistics.CreateBasicStatistics(errorArrayCopy);
        double[] xArray = new double[2];
        double[][] yArray = new double[ConfidenceInterval.NUM_CONFIDENCE_LEVELS][2];
        // get confidence level plot lines
        xArray[0] = paramValStat.getMin() - (Math.abs(paramValStat.getMin()) * 0.2);
        xArray[1] = paramValStat.getMax() + (Math.abs(paramValStat.getMax()) * 0.2);
        for (int i = 0; i < ConfidenceInterval.NUM_CONFIDENCE_LEVELS; i++) {
            yArray[i][0] = errorStat.getMin() + ConfidenceInterval.DELTA_ALPHA_VALUE[i];
            yArray[i][1] = yArray[i][0];
        }
        PlotData confidence80Plot = new PlotData(xArray, yArray[ConfidenceInterval.IDX_DELTA_ALPHA_80]);
        PlotData confidence90Plot = new PlotData(xArray, yArray[ConfidenceInterval.IDX_DELTA_ALPHA_90]);
        PlotData confidence95Plot = new PlotData(xArray, yArray[ConfidenceInterval.IDX_DELTA_ALPHA_95]);
        PlotData confidence99Plot = new PlotData(xArray, yArray[ConfidenceInterval.IDX_DELTA_ALPHA_99]);
        // generate plot2D data
        Plot2D plots = new Plot2D(null, null, new String[] { "profile Likelihood Data", "80% confidence", "90% confidence", "95% confidence", "99% confidence" }, new PlotData[] { dataPlot, confidence80Plot, confidence90Plot, confidence95Plot, confidence99Plot }, new String[] { "Profile likelihood of " + paramName, "Log base 10 of " + paramName, "Profile Likelihood" }, new boolean[] { true, true, true, true, true });
        // get the best parameter for the minimal error
        int minErrIndex = -1;
        for (int i = 0; i < errorArray.length; i++) {
            if (errorArray[i] == errorStat.getMin()) {
                minErrIndex = i;
                break;
            }
        }
        double bestParamVal = Math.pow(10, paramValArray[minErrIndex]);
        // find confidence interval points
        ConfidenceInterval[] intervals = new ConfidenceInterval[ConfidenceInterval.NUM_CONFIDENCE_LEVELS];
        // half loop through the errors(left side curve)
        int[] smallLeftIdx = new int[ConfidenceInterval.NUM_CONFIDENCE_LEVELS];
        int[] bigLeftIdx = new int[ConfidenceInterval.NUM_CONFIDENCE_LEVELS];
        for (int i = 0; i < ConfidenceInterval.NUM_CONFIDENCE_LEVELS; i++) {
            smallLeftIdx[i] = -1;
            bigLeftIdx[i] = -1;
            for (// loop from bigger error to smaller error
            int j = 1; // loop from bigger error to smaller error
            j < minErrIndex + 1; // loop from bigger error to smaller error
            j++) {
                if ((errorArray[j] < (errorStat.getMin() + ConfidenceInterval.DELTA_ALPHA_VALUE[i])) && (errorArray[j - 1] > (errorStat.getMin() + ConfidenceInterval.DELTA_ALPHA_VALUE[i]))) {
                    smallLeftIdx[i] = j - 1;
                    bigLeftIdx[i] = j;
                    break;
                }
            }
        }
        // another half loop through the errors(right side curve)
        int[] smallRightIdx = new int[ConfidenceInterval.NUM_CONFIDENCE_LEVELS];
        int[] bigRightIdx = new int[ConfidenceInterval.NUM_CONFIDENCE_LEVELS];
        for (int i = 0; i < ConfidenceInterval.NUM_CONFIDENCE_LEVELS; i++) {
            smallRightIdx[i] = -1;
            bigRightIdx[i] = -1;
            for (// loop from bigger error to smaller error
            int j = (minErrIndex + 1); // loop from bigger error to smaller error
            j < errorArray.length; // loop from bigger error to smaller error
            j++) {
                if ((errorStat.getMin() + ConfidenceInterval.DELTA_ALPHA_VALUE[i]) < errorArray[j] && (errorStat.getMin() + ConfidenceInterval.DELTA_ALPHA_VALUE[i]) > errorArray[j - 1]) {
                    smallRightIdx[i] = j - 1;
                    bigRightIdx[i] = j;
                    break;
                }
            }
        }
        // calculate intervals
        for (int i = 0; i < ConfidenceInterval.NUM_CONFIDENCE_LEVELS; i++) {
            double lowerBound = Double.NEGATIVE_INFINITY;
            boolean bLowerBoundOpen = true;
            double upperBound = Double.POSITIVE_INFINITY;
            boolean bUpperBoundOpen = true;
            if (// no lower bound
            smallLeftIdx[i] == -1 && bigLeftIdx[i] == -1) {
                lowerBound = parameter.getLowerBound();
                bLowerBoundOpen = false;
            } else if (// there is a lower bound
            smallLeftIdx[i] != -1 && bigLeftIdx[i] != -1) {
                // x=x1+(x2-x1)*(y-y1)/(y2-y1);
                double x1 = paramValArray[smallLeftIdx[i]];
                double x2 = paramValArray[bigLeftIdx[i]];
                double y = errorStat.getMin() + ConfidenceInterval.DELTA_ALPHA_VALUE[i];
                double y1 = errorArray[smallLeftIdx[i]];
                double y2 = errorArray[bigLeftIdx[i]];
                lowerBound = x1 + (x2 - x1) * (y - y1) / (y2 - y1);
                lowerBound = Math.pow(10, lowerBound);
                bLowerBoundOpen = false;
            }
            if (// no upper bound
            smallRightIdx[i] == -1 && bigRightIdx[i] == -1) {
                upperBound = parameter.getUpperBound();
                bUpperBoundOpen = false;
            } else if (// there is a upper bound
            smallRightIdx[i] != -1 && bigRightIdx[i] != -1) {
                // x=x1+(x2-x1)*(y-y1)/(y2-y1);
                double x1 = paramValArray[smallRightIdx[i]];
                double x2 = paramValArray[bigRightIdx[i]];
                double y = errorStat.getMin() + ConfidenceInterval.DELTA_ALPHA_VALUE[i];
                double y1 = errorArray[smallRightIdx[i]];
                double y2 = errorArray[bigRightIdx[i]];
                upperBound = x1 + (x2 - x1) * (y - y1) / (y2 - y1);
                upperBound = Math.pow(10, upperBound);
                bUpperBoundOpen = false;
            }
            intervals[i] = new ConfidenceInterval(lowerBound, bLowerBoundOpen, upperBound, bUpperBoundOpen);
        }
        return new ProfileSummaryData(plots, bestParamVal, intervals, paramName);
    }
    return null;
}

Example 58 with Parameter

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

the class OptModelParamPanel method runAndSetBestParameters.

public void runAndSetBestParameters() throws Exception {
    Parameter[] parameters = optContext.getParameters();
    final Parameter[] inParameters = new Parameter[parameters.length];
    double[] values = getCurrentParameterValues();
    for (int i = 0; i < inParameters.length; i++) {
        Parameter p = parameters[i];
        inParameters[i] = new Parameter(p.getName(), p.getLowerBound(), p.getUpperBound(), p.getScale(), values[i]);
    }
    AsynchClientTask optTask = new AsynchClientTask("Running optimization ...", AsynchClientTask.TASKTYPE_NONSWING_BLOCKING) {

        public void run(Hashtable<String, Object> hashTable) throws Exception {
            String[] outParaNames = new String[inParameters.length];
            double[] outParaValues = new double[inParameters.length];
            OptContextSolver.estimate(optContext, inParameters, outParaNames, outParaValues);
            hashTable.put("outParaValues", outParaValues);
        }
    };
    AsynchClientTask showResultTask = new AsynchClientTask("Running optimization ...", AsynchClientTask.TASKTYPE_SWING_BLOCKING) {

        public void run(Hashtable<String, Object> hashTable) throws Exception {
            double[] outParaVales = (double[]) hashTable.get("outParaValues");
            setParameterValues(outParaVales);
            plotDerivedSimulationResults();
        }
    };
    // dispatch
    ClientTaskDispatcher.dispatch(OptModelParamPanel.this, new Hashtable<String, Object>(), new AsynchClientTask[] { optTask, showResultTask }, false, false, null, true);
}

Example 59 with Parameter

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

the class RunProfileLikelihoodGeneralOp method getBestParameters.

private Parameter[] getBestParameters(OptContext optContext, Parameter[] inParams, Parameter fixedParam) throws Exception {
    int numFixedParam = (fixedParam == null) ? 0 : 1;
    // return to the caller, parameter should be a whole set including the fixed parameter
    Parameter[] outputParams = new Parameter[inParams.length + numFixedParam];
    // send to optimizer
    String[] outParaNames = new String[inParams.length];
    // send to optimizer
    double[] outParaVals = new double[inParams.length];
    // optimization
    leastError = OptContextSolver.estimate(optContext, inParams, outParaNames, outParaVals);
    // get results as Parameters (take fixed parameter into account)
    for (int fullParamIndex = 0; fullParamIndex < optContext.getParameters().length; fullParamIndex++) {
        Parameter p = optContext.getParameters()[fullParamIndex];
        for (int estParamIndex = 0; estParamIndex < outParaNames.length; estParamIndex++) {
            if (outParaNames[estParamIndex].equals(p.getName())) {
                double value = outParaVals[estParamIndex];
                if (value > p.getUpperBound()) {
                    value = p.getUpperBound();
                } else if (value < p.getLowerBound()) {
                    value = p.getLowerBound();
                }
                outputParams[fullParamIndex] = new Parameter(p.getName(), p.getLowerBound(), p.getUpperBound(), 1.0, value);
            }
        }
        // add fixed parameter to the best parameter output to make a whole set
        if (fixedParam != null && p.getName().equals(fixedParam.getName())) {
            outputParams[fullParamIndex] = fixedParam;
        }
    }
    // }
    return outputParams;
}