com.cloudera.oryx.kmeans.computation.covariance.CovarianceData.java Source code

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Here is the source code for com.cloudera.oryx.kmeans.computation.covariance.CovarianceData.java

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/*
 * Copyright (c) 2013, Cloudera, Inc. All Rights Reserved.
 *
 * Cloudera, Inc. licenses this file to you under the Apache License,
 * Version 2.0 (the "License"). You may not use this file except in
 * compliance with the License. You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * This software is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
 * CONDITIONS OF ANY KIND, either express or implied. See the License for
 * the specific language governing permissions and limitations under the
 * License.
 */

package com.cloudera.oryx.kmeans.computation.covariance;

import com.google.common.base.Preconditions;

import com.cloudera.oryx.common.io.DelimitedDataUtils;

public final class CovarianceData {

    private final int clusteringId;
    private final int centerId;
    private final int row;
    private final int column;
    private final double meanX;
    private final double cov;

    public static CovarianceData parse(String line) {
        String[] pieces = DelimitedDataUtils.decode(line);
        Preconditions.checkArgument(pieces.length == 6, "Invalid covariance data: %s", line);
        return new CovarianceData(Integer.valueOf(pieces[0]), Integer.valueOf(pieces[1]),
                Integer.valueOf(pieces[2]), Integer.valueOf(pieces[3]), Double.valueOf(pieces[4]),
                Double.valueOf(pieces[5]));
    }

    public CovarianceData(int clusteringId, int centerId, int row, int column, double meanX, double cov) {
        this.clusteringId = clusteringId;
        this.centerId = centerId;
        this.row = row;
        this.column = column;
        this.meanX = meanX;
        this.cov = cov;
    }

    public int getClusteringId() {
        return clusteringId;
    }

    public int getCenterId() {
        return centerId;
    }

    public int getRow() {
        return row;
    }

    public int getColumn() {
        return column;
    }

    public double getMeanX() {
        return meanX;
    }

    public double getCov() {
        return cov;
    }

    @Override
    public String toString() {
        return DelimitedDataUtils.encode(clusteringId, centerId, row, column, meanX, cov);
    }

    @Override
    public boolean equals(Object o) {
        if (!(o instanceof CovarianceData)) {
            return false;
        }

        CovarianceData other = (CovarianceData) o;

        return centerId == other.centerId && clusteringId == other.clusteringId && column == other.column
                && Double.compare(other.cov, cov) == 0 && Double.compare(other.meanX, meanX) == 0
                && row == other.row;
    }

    @Override
    public int hashCode() {
        int result = clusteringId;
        result = 31 * result + centerId;
        result = 31 * result + row;
        result = 31 * result + column;
        long temp = Double.doubleToLongBits(meanX);
        result = 31 * result + (int) (temp ^ (temp >>> 32));
        temp = Double.doubleToLongBits(cov);
        result = 31 * result + (int) (temp ^ (temp >>> 32));
        return result;
    }
}