Example usage for org.apache.commons.math3.linear RealVector toArray

Introduction

In this page you can find the example usage for org.apache.commons.math3.linear RealVector toArray.

Prototype

public double[] toArray() 

Source Link

Document

Convert the vector to an array of double s.

Usage

From source file:edu.washington.gs.skyline.model.quantification.WeightedRegression.java

public static double[] weighted(double[][] x, double[] y, double[] weights, boolean intercept) {
    RealMatrix predictor;/*from   w  ww . j a  va  2  s. c  om*/
    if (intercept) {
        int nRows = x.length;
        int nCols = x[0].length + 1;
        predictor = MatrixUtils.createRealMatrix(nRows, nCols);
        for (int iRow = 0; iRow < nRows; iRow++) {
            predictor.setEntry(iRow, 0, 1.0);
            for (int iCol = 1; iCol < nCols; iCol++) {
                predictor.setEntry(iRow, iCol, x[iRow][iCol - 1]);
            }
        }
    } else {
        predictor = MatrixUtils.createRealMatrix(x);
    }
    RealVector responseVector = MatrixUtils.createRealVector(y);
    RealMatrix weightsMatrix = MatrixUtils.createRealDiagonalMatrix(weights);
    RealMatrix predictorTransposed = predictor.transpose();
    RealMatrix predictorTransposedTimesWeights = predictorTransposed
            .multiply(weightsMatrix.multiply(predictor));
    CholeskyDecomposition choleskyDecomposition = new CholeskyDecomposition(predictorTransposedTimesWeights);
    RealVector vectorToSolve = predictorTransposed.operate(weightsMatrix.operate(responseVector));
    RealVector result = choleskyDecomposition.getSolver().solve(vectorToSolve);
    return result.toArray();
}

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From source file:edu.stanford.cfuller.imageanalysistools.fitting.GaussianFitter3D.java

/**
 * Calculates the fit residual between a set of parameters and a value at a supplied point.
 * @param value         The observed value at the point.
 * @param x             The x-coordinate of the point (in absolute original image coordinates)
 * @param y             The y-coordinate of the point (in absolute original image coordinates)
 * @param z             The z-coordinate of the point (in absolute original image coordinates.
 * @param parameters    The gaussian parameters in the same order as would be required for or returned from {@link #fit}
 * @return              The fit residual at the specified point.
 *///  w  w  w . ja v  a  2  s. co  m
public static double fitResidual(double value, double x, double y, double z, RealVector parameters) {

    return value - gaussian(x, y, z, parameters.toArray());
}

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From source file:com.analog.lyric.math.MoreMatrixUtils.java

/**
 * Returns vector as a an array.//from w w  w  .j  ava  2s  .  c  o  m
 * <p>
 * If {@code vector} is a {@link ArrayRealVector}, this returns its underlying array,
 * otherwise returns a newly allocated array.
 * @since 0.08
 */
public static double[] vectorGetDataRef(RealVector vector) {
    if (vector instanceof ArrayRealVector) {
        return ((ArrayRealVector) vector).getDataRef();
    }

    return vector.toArray();
}

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From source file:com.opengamma.strata.math.impl.util.CommonsMathWrapper.java

/**
 * Unwraps a vector./*from   w ww.j  av a2s  . c  o m*/
 * 
 * @param x  a Commons vector
 * @return an OG 1-D matrix of doubles
 */
public static DoubleArray unwrap(RealVector x) {
    ArgChecker.notNull(x, "x");
    return DoubleArray.ofUnsafe(x.toArray());
}

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From source file:eagle.security.userprofile.model.UserProfileEigenModelEntity.java

public static MLModelAPIEntity serializeModel(UserProfileEigenModel model) throws IOException {
    if (model == null)
        return null;
    if (model.user() == null)
        throw new IllegalArgumentException("user is null");

    MLModelAPIEntity entity = new MLModelAPIEntity();
    UserProfileEigenModelEntity content = new UserProfileEigenModelEntity();
    entity.setVersion(model.version());//from  w  ww.j av a 2s .  c  o m
    if (model.uMatrix() != null)
        content.setUMatrix(model.uMatrix().getData());
    if (model.diagonalMatrix() != null)
        content.setDiagonalMatrix(model.diagonalMatrix().getData());
    content.setDimension(model.dimension());
    if (model.minVector() != null)
        content.setMinVector(model.minVector().toArray());
    if (model.maxVector() != null)
        content.setMaxVector(model.maxVector().toArray());

    RealVector[] pcsInVector = model.principalComponents();
    if (pcsInVector != null) {
        List<double[]> prcsInDouleArrayList = new ArrayList<>(pcsInVector.length);
        for (RealVector vector : pcsInVector)
            prcsInDouleArrayList.add(vector.toArray());
        content.setPrincipalComponents(prcsInDouleArrayList);
    }
    if (model.maximumL2Norm() != null)
        content.setMaximumL2Norm(model.maximumL2Norm().toArray());
    if (model.minimumL2Norm() != null)
        content.setMinimumL2Norm(model.minimumL2Norm().toArray());
    if (model.statistics() != null) {
        List<Map<String, Object>> statisticsMaps = new ArrayList<>(model.statistics().length);
        for (UserCommandStatistics userCommandStatistics : model.statistics())
            statisticsMaps.add(userCommandStatistics.toMap());
        content.setStatistics(statisticsMaps);
    }

    entity.setContent(TaggedLogAPIEntity.buildObjectMapper().writeValueAsString(content));
    Map<String, String> tags = new HashMap<>();
    tags.put(UserProfileConstants.SITE_TAG, model.site());
    tags.put(UserProfileConstants.USER_TAG, model.user());
    tags.put(UserProfileConstants.ALGORITHM_TAG, model.algorithm());

    entity.setTags(tags);
    return entity;
}

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From source file:com.vsthost.rnd.commons.math.ext.linear.EMatrixUtils.java

/**
 * Converts a real vector to a JSON string.
 *
 * @param vector The vector to be represented by a JSON string.
 * @return A JSON representation of the matrix.
 *//*w  w w . ja  va  2s. c om*/
public static String toJson(RealVector vector) {
    return new Gson().toJson(vector.toArray());
}

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From source file:edu.byu.nlp.math.RealVectors.java

/**
 * Computes the log of the sum of the exponentiated elements of a vector. For any index j:
 * //from  w w w . jav a2 s . c o  m
 * <pre>
 * log(e^{x_1} + e^{x_2} + ...) = log(e^{x_j} * sum\_{i \neq j} e^{x_i - x_j} + 1)
  *                              = x_j + log(sum\_{i \neq j} e^{x_i - x_j} + 1)
  * </pre>
  * 
  * This method ignores elements that are twenty orders of magnitude different than x_j.
  * 
  * @throws NullPointerException if vector is null
  */
public static double logSumSloppy(RealVector x) {
    Preconditions.checkNotNull(x);

    // TODO(rah67): consider just using the first element
    // use max as j
    int argMax = x.getMaxIndex();
    double max = x.getEntry(argMax);

    if (max == Double.NEGATIVE_INFINITY)
        return Double.NEGATIVE_INFINITY;

    return DoubleArrays.logSum(x.toArray());
}

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From source file:hits.HitTools.java

private static PointWithPropertiesIfc rotateAndClonePointWithProperties(PointWithPropertiesIfc inputPoint,
        ResultsFromEvaluateCost result) {

    RealVector coordsVector = new ArrayRealVector(
            MathTools.convertToDoubleArray(inputPoint.getCoords().getCoords()));
    RealVector newPointCoords = PairingTools.alignPointFromShape2toShape1(result, coordsVector);
    PointWithPropertiesIfc newPoint = new PointWithProperties();
    newPoint.setCoords(new Point(MathTools.convertToFloatArray(newPointCoords.toArray())));
    newPoint.setStrikingProperties(inputPoint.getStrikingProperties());
    return newPoint;
}

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From source file:hits.HitTools.java

public static Float computeRmsdBackboneAtomBetweenHitPeptideAndQueryLigandDefinigQuery(
        ShapeContainerIfc targetShape, ResultsFromEvaluateCost result, ShapeContainerIfc queryShape,
        AlgoParameters algoParameters) {

    boolean isQueryShapeContainerHasPeptideIfc = queryShape instanceof HasPeptideIfc;
    boolean isHitShapeContainerHasPeptideIfc = targetShape instanceof HasPeptideIfc;

    boolean canBeComputed = isQueryShapeContainerHasPeptideIfc && isHitShapeContainerHasPeptideIfc;
    if (!canBeComputed) {
        return null;
    }//from www. j  a v a  2 s. c o  m

    HasPeptideIfc queryShapeWithPeptide = (HasPeptideIfc) queryShape;
    MyChainIfc peptideUsedToBuiltTheQuery = queryShapeWithPeptide.getPeptide();

    HasPeptideIfc currentBestHitWithPeptide = (HasPeptideIfc) targetShape;
    MyChainIfc peptideCurrentBestHit = currentBestHitWithPeptide.getPeptide();

    if (peptideUsedToBuiltTheQuery != null) {

        List<MyAtomIfc> backboneAtomPeptideQuery = extractBackBoneAtoms(peptideUsedToBuiltTheQuery,
                algoParameters);
        List<MyAtomIfc> backboneAtomPeptideHit = extractBackBoneAtoms(peptideCurrentBestHit, algoParameters);
        // put hit in ref frame of query
        List<double[]> coordinatesHit = new ArrayList<>();
        for (MyAtomIfc atomHit : backboneAtomPeptideHit) {
            RealVector newPointCoords = PairingTools.alignPointFromShape2toShape1(result,
                    new ArrayRealVector(MathTools.convertToDoubleArray(atomHit.getCoords())));
            coordinatesHit.add(newPointCoords.toArray());
        }
        List<double[]> coordinatesQuery = new ArrayList<>();
        for (MyAtomIfc atomQuery : backboneAtomPeptideQuery) {
            coordinatesQuery.add(MathTools.convertToDoubleArray(atomQuery.getCoords()));
        }

        List<double[]> smallestChainCoords = coordinatesHit;
        List<double[]> longestChainCoords = coordinatesQuery;
        List<MyAtomIfc> smallestChain = backboneAtomPeptideHit;
        List<MyAtomIfc> longestChain = backboneAtomPeptideQuery;

        if (backboneAtomPeptideHit.size() > backboneAtomPeptideQuery.size()) {
            smallestChain = backboneAtomPeptideQuery;
            longestChain = backboneAtomPeptideHit;
            smallestChainCoords = coordinatesQuery;
            longestChainCoords = coordinatesHit;
        }
        // 10
        // 6
        // pos 0 to pos 4 as start

        List<Integer> posibleStart = new ArrayList<>();

        int countPossibleOverlays = longestChain.size() - smallestChain.size() + 1;
        A: for (int j = 0; j <= countPossibleOverlays; j++) {

            for (int k = 0; k < smallestChain.size(); k++) {
                MyAtomIfc currentAtomLongestchain = longestChain.get(k + j);
                // if any mismatch in atom name I skip the current comparaison
                //System.out.println(String.valueOf(smallestChain.get(k).getAtomName()) + " compared to " + String.valueOf(currentAtomLongestchain.getAtomName()));
                if (!String.valueOf(smallestChain.get(k).getAtomName())
                        .equals(String.valueOf(currentAtomLongestchain.getAtomName()))) {
                    continue A;
                }
            }
            posibleStart.add(j);
        }
        //System.out.println("posibleStart : " + posibleStart);

        // for each possible start I compute the rmsd
        float minRmsd = Float.MAX_VALUE;
        for (int j = 0; j < posibleStart.size(); j++) {

            double rmsd = 0.0;
            for (int k = 0; k < smallestChain.size(); k++) {
                double[] currentAtomSmallestchain = smallestChainCoords.get(k);
                double[] currentAtomLongestchain = longestChainCoords.get(k + posibleStart.get(j));
                double contribRmsd = MathTools.computeDistance(currentAtomSmallestchain,
                        currentAtomLongestchain);
                rmsd += contribRmsd * contribRmsd;
            }
            rmsd = rmsd / smallestChain.size();
            float finalRmsd = (float) Math.sqrt(rmsd);
            if (finalRmsd < minRmsd) {
                minRmsd = finalRmsd;
            }
        }

        return minRmsd;
    }
    return null;
}

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From source file:de.termininistic.serein.examples.benchmarks.functions.multimodal.LevyFunction.java

@Override
public double map(RealVector v) {
    double[] x = v.toArray();
    double sum = Math.pow(Math.sin(Math.PI * w(x[0])), 2);
    for (int i = 0; i < x.length - 1; i++) {
        sum += Math.pow((w(x[i]) - 1), 2) * (1 + 10 * Math.pow(Math.sin(2 * Math.PI * w(x[0]) + 1), 2)
                + Math.pow(w(x[x.length - 1]) - 1, 2)
                        * (1 + Math.pow(Math.sin(2 * Math.PI * w(x[x.length - 1]) + 1), 2)));
    }/*from   w ww .  jav  a2s.c o  m*/
    return sum;
}

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