Example usage for org.apache.commons.math.linear RealVector append

Introduction

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

Prototype

RealVector append(double[] a);

Source Link

Document

Construct a vector by appending a double array to this vector.

Usage

From source file:it.univaq.incipict.profilemanager.common.utility.Utility.java

public static HashMap<Profile, Double> getEuclideanDistances(List<Profile> profilesList, User user) {
    Map<Profile, Double> result = new HashMap<Profile, Double>();
    Set<ProfileInformation> profileInformationSet;
    Set<Information> userInformationSet;

    // Retrieve user information set
    userInformationSet = user.getInformationSet();
    if (userInformationSet.isEmpty()) {
        return (HashMap<Profile, Double>) result;
    }//ww  w  .  j  av a 2s . c o m

    // For each Profile
    for (Profile profile : profilesList) {
        profileInformationSet = profile.getProfileInformationSet();
        int vectorsLenght = Math.max(profileInformationSet.size(), userInformationSet.size());
        RealVector ranksRealVector = new ArrayRealVector(new double[] {});
        RealVector userInformationVector = new ArrayRealVector(new double[] {});

        // Loop userInformationSet and
        // profileInformationSet (i.e. one specific column vector in the
        // knowledge base representation)
        for (Information information : userInformationSet) {
            Long x = information.getId();
            for (ProfileInformation profileInformation : profileInformationSet) {
                Long y = profileInformation.getInformation().getId();
                // User selected information was stored in a RealVector at same
                // position of relative ranksVector
                // This permit to calculate Euclidean distance right.
                if (x == y) {
                    userInformationVector = userInformationVector.append(1d); // Associated:1, Else:0
                    ranksRealVector = ranksRealVector.append(profileInformation.getRank());

                    profileInformationSet.remove(profileInformation);
                    break;
                }
            }
        }
        // At this point we aren't interested to elements position
        // because every other information worth zero.
        // Euclidean distance are not influenced from position of 0-elements in
        // a "sub-vector".
        // if they are all zeros.
        // => Append the zeros until completion of the length of the vectors
        userInformationVector = userInformationVector
                .append(new double[vectorsLenght - userInformationSet.size()]);

        for (ProfileInformation profileInformation : profileInformationSet) {
            // Append the remaining elements of this set (profileInformationSet)
            ranksRealVector = ranksRealVector.append(profileInformation.getRank());
        }

        // Calculate Euclidean Distance
        double distance = userInformationVector.getDistance(ranksRealVector);
        // add the distance to Distance's Map
        result.put(profile, distance);

    } // END, goto Next Profile

    // return the HashMap sorted by value (ASC)
    return (HashMap<Profile, Double>) MapUtil.sortByValueASC(result);
}

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