com.cloudera.oryx.app.kmeans.KMeansPMMLUtils Maven / Gradle / Ivy

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/*
 * Copyright (c) 2015, Cloudera and Intel, 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.app.kmeans;

import java.util.List;
import java.util.stream.Collectors;

import com.google.common.base.Preconditions;
import org.dmg.pmml.DataDictionary;
import org.dmg.pmml.MiningFunction;
import org.dmg.pmml.MiningSchema;
import org.dmg.pmml.Model;
import org.dmg.pmml.PMML;
import org.dmg.pmml.clustering.ClusteringModel;

import com.cloudera.oryx.app.pmml.AppPMMLUtils;
import com.cloudera.oryx.app.schema.InputSchema;
import com.cloudera.oryx.common.math.VectorMath;
import com.cloudera.oryx.common.text.TextUtils;

/**
 * Utility methods related to PMML serialization of k-means clustering models.
 */
public final class KMeansPMMLUtils {

  private KMeansPMMLUtils() {}

  /**
   * Validates that the encoded PMML model received matches expected schema.
   *
   * @param pmml {@link PMML} encoding of KMeans Clustering
   * @param schema expected schema attributes of KMeans Clustering
   */
  public static void validatePMMLVsSchema(PMML pmml, InputSchema schema) {
    List models = pmml.getModels();
    Preconditions.checkArgument(models.size() == 1,
        "Should have exactly one model, but had %s", models.size());

    Model model = models.get(0);
    Preconditions.checkArgument(model instanceof ClusteringModel);
    Preconditions.checkArgument(model.getMiningFunction() == MiningFunction.CLUSTERING);

    DataDictionary dictionary = pmml.getDataDictionary();
    Preconditions.checkArgument(
        schema.getFeatureNames().equals(AppPMMLUtils.getFeatureNames(dictionary)),
        "Feature names in schema don't match names in PMML");

    MiningSchema miningSchema = model.getMiningSchema();
    Preconditions.checkArgument(schema.getFeatureNames().equals(
        AppPMMLUtils.getFeatureNames(miningSchema)));

  }

  /**
   * @param pmml PMML representation of Clusters
   * @return List of {@link ClusterInfo}
   */
  public static List read(PMML pmml) {
    Model model = pmml.getModels().get(0);
    Preconditions.checkArgument(model instanceof ClusteringModel);
    ClusteringModel clusteringModel = (ClusteringModel) model;

    return clusteringModel.getClusters().stream().map(cluster ->
      new ClusterInfo(Integer.parseInt(cluster.getId()),
                      VectorMath.parseVector(TextUtils.parseDelimited(cluster.getArray().getValue(), ' ')),
                      cluster.getSize())
    ).collect(Collectors.toList());
  }

}