You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@ignite.apache.org by ch...@apache.org on 2018/04/17 08:22:26 UTC

ignite git commit: IGNITE-8292: Broken yardstick compilation.

Repository: ignite
Updated Branches:
  refs/heads/master 5614621d1 -> e76fcb4a5


IGNITE-8292: Broken yardstick compilation.

this closes #3838


Project: http://git-wip-us.apache.org/repos/asf/ignite/repo
Commit: http://git-wip-us.apache.org/repos/asf/ignite/commit/e76fcb4a
Tree: http://git-wip-us.apache.org/repos/asf/ignite/tree/e76fcb4a
Diff: http://git-wip-us.apache.org/repos/asf/ignite/diff/e76fcb4a

Branch: refs/heads/master
Commit: e76fcb4a538aece58498f43d7e82b2054ca96c51
Parents: 5614621
Author: YuriBabak <y....@gmail.com>
Authored: Tue Apr 17 11:22:14 2018 +0300
Committer: Yury Babak <yb...@gridgain.com>
Committed: Tue Apr 17 11:22:14 2018 +0300

----------------------------------------------------------------------
 ...uzzyCMeansDistributedClustererBenchmark.java | 130 -------------------
 ...gniteFuzzyCMeansLocalClustererBenchmark.java |  93 -------------
 2 files changed, 223 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/ignite/blob/e76fcb4a/modules/yardstick/src/main/java/org/apache/ignite/yardstick/ml/clustering/IgniteFuzzyCMeansDistributedClustererBenchmark.java
----------------------------------------------------------------------
diff --git a/modules/yardstick/src/main/java/org/apache/ignite/yardstick/ml/clustering/IgniteFuzzyCMeansDistributedClustererBenchmark.java b/modules/yardstick/src/main/java/org/apache/ignite/yardstick/ml/clustering/IgniteFuzzyCMeansDistributedClustererBenchmark.java
deleted file mode 100644
index e356746..0000000
--- a/modules/yardstick/src/main/java/org/apache/ignite/yardstick/ml/clustering/IgniteFuzzyCMeansDistributedClustererBenchmark.java
+++ /dev/null
@@ -1,130 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF 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
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License 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 org.apache.ignite.yardstick.ml.clustering;
-
-import java.util.Map;
-import org.apache.ignite.Ignite;
-import org.apache.ignite.ml.clustering.BaseFuzzyCMeansClusterer;
-import org.apache.ignite.ml.clustering.FuzzyCMeansDistributedClusterer;
-import org.apache.ignite.ml.clustering.FuzzyCMeansModel;
-import org.apache.ignite.ml.math.StorageConstants;
-import org.apache.ignite.ml.math.distances.DistanceMeasure;
-import org.apache.ignite.ml.math.distances.EuclideanDistance;
-import org.apache.ignite.ml.math.impls.matrix.SparseDistributedMatrix;
-import org.apache.ignite.resources.IgniteInstanceResource;
-import org.apache.ignite.thread.IgniteThread;
-import org.apache.ignite.yardstick.IgniteAbstractBenchmark;
-import org.apache.ignite.yardstick.ml.DataChanger;
-
-/**
- * Ignite benchmark that performs ML Grid operations.
- */
-@SuppressWarnings("unused")
-public class IgniteFuzzyCMeansDistributedClustererBenchmark extends IgniteAbstractBenchmark {
-    /** */
-    @IgniteInstanceResource
-    private Ignite ignite;
-
-    /** {@inheritDoc} */
-    @Override public boolean test(Map<Object, Object> ctx) throws Exception {
-        // Create IgniteThread, we must work with SparseDistributedMatrix inside IgniteThread
-        // because we create ignite cache internally.
-        IgniteThread igniteThread = new IgniteThread(ignite.configuration().getIgniteInstanceName(),
-            this.getClass().getSimpleName(), new Runnable() {
-            /** {@inheritDoc} */
-            @Override public void run() {
-                // IMPL NOTE originally taken from FuzzyCMeansExample.
-                // Distance measure that computes distance between two points.
-                DistanceMeasure distanceMeasure = new EuclideanDistance();
-
-                // "Fuzziness" - specific constant that is used in membership calculation (1.0+-eps ~ K-Means).
-                double exponentialWeight = 2.0;
-
-                // Condition that indicated when algorithm must stop.
-                // In this example algorithm stops if memberships have changed insignificantly.
-                BaseFuzzyCMeansClusterer.StopCondition stopCond =
-                    BaseFuzzyCMeansClusterer.StopCondition.STABLE_MEMBERSHIPS;
-
-                // Maximum difference between new and old membership values with which algorithm will continue to work.
-                double maxDelta = 0.01;
-
-                // The maximum number of FCM iterations.
-                int maxIterations = 50;
-
-                // Number of steps of primary centers selection (more steps more candidates).
-                int initializationSteps = 2;
-
-                // Number of K-Means iteration that is used to choose required number of primary centers from candidates.
-                int kMeansMaxIterations = 50;
-
-                // Create new distributed clusterer with parameters described above.
-                FuzzyCMeansDistributedClusterer clusterer = new FuzzyCMeansDistributedClusterer(
-                    distanceMeasure, exponentialWeight, stopCond, maxDelta, maxIterations,
-                    null, initializationSteps, kMeansMaxIterations);
-
-                // Create sample data.
-                double[][] points = shuffle((int)(DataChanger.next()));
-
-                // Initialize matrix of data points. Each row contains one point.
-                int rows = points.length;
-                int cols = points[0].length;
-
-                // Create the matrix that contains sample points.
-                SparseDistributedMatrix pntMatrix = new SparseDistributedMatrix(rows, cols,
-                    StorageConstants.ROW_STORAGE_MODE, StorageConstants.RANDOM_ACCESS_MODE);
-
-                // Store points into matrix.
-                pntMatrix.assign(points);
-
-                // Call clusterization method with some number of centers.
-                // It returns model that can predict results for new points.
-                int numCenters = 4;
-                FuzzyCMeansModel mdl = clusterer.cluster(pntMatrix, numCenters);
-
-                // Get centers of clusters that is computed by Fuzzy C-Means algorithm.
-                mdl.centers();
-
-                pntMatrix.destroy();
-            }
-        });
-
-        igniteThread.start();
-
-        igniteThread.join();
-
-        return true;
-    }
-
-    /** */
-    private double[][] shuffle(int off) {
-        final double[][] points = new double[][] {
-            {-10, -10}, {-9, -11}, {-10, -9}, {-11, -9},
-            {10, 10}, {9, 11}, {10, 9}, {11, 9},
-            {-10, 10}, {-9, 11}, {-10, 9}, {-11, 9},
-            {10, -10}, {9, -11}, {10, -9}, {11, -9}};
-
-        final int size = points.length;
-
-        final double[][] res = new double[size][];
-
-        for (int i = 0; i < size; i++)
-            res[i] = points[(i + off) % size];
-
-        return res;
-    }
-}

http://git-wip-us.apache.org/repos/asf/ignite/blob/e76fcb4a/modules/yardstick/src/main/java/org/apache/ignite/yardstick/ml/clustering/IgniteFuzzyCMeansLocalClustererBenchmark.java
----------------------------------------------------------------------
diff --git a/modules/yardstick/src/main/java/org/apache/ignite/yardstick/ml/clustering/IgniteFuzzyCMeansLocalClustererBenchmark.java b/modules/yardstick/src/main/java/org/apache/ignite/yardstick/ml/clustering/IgniteFuzzyCMeansLocalClustererBenchmark.java
deleted file mode 100644
index 8c4c9ce..0000000
--- a/modules/yardstick/src/main/java/org/apache/ignite/yardstick/ml/clustering/IgniteFuzzyCMeansLocalClustererBenchmark.java
+++ /dev/null
@@ -1,93 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF 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
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License 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 org.apache.ignite.yardstick.ml.clustering;
-
-import java.util.Map;
-import org.apache.ignite.ml.clustering.BaseFuzzyCMeansClusterer;
-import org.apache.ignite.ml.clustering.FuzzyCMeansLocalClusterer;
-import org.apache.ignite.ml.clustering.FuzzyCMeansModel;
-import org.apache.ignite.ml.math.distances.DistanceMeasure;
-import org.apache.ignite.ml.math.distances.EuclideanDistance;
-import org.apache.ignite.ml.math.impls.matrix.DenseLocalOnHeapMatrix;
-import org.apache.ignite.yardstick.IgniteAbstractBenchmark;
-import org.apache.ignite.yardstick.ml.DataChanger;
-
-/**
- * Ignite benchmark that performs ML Grid operations.
- */
-@SuppressWarnings("unused")
-public class IgniteFuzzyCMeansLocalClustererBenchmark extends IgniteAbstractBenchmark {
-    /** {@inheritDoc} */
-    @Override public boolean test(Map<Object, Object> ctx) throws Exception {
-        // IMPL NOTE originally taken from FuzzyLocalCMeansExample.
-        // Distance measure that computes distance between two points.
-        DistanceMeasure distanceMeasure = new EuclideanDistance();
-
-        // "Fuzziness" - specific constant that is used in membership calculation (1.0+-eps ~ K-Means).
-        double exponentialWeight = 2.0;
-
-        // Condition that indicated when algorithm must stop.
-        // In this example algorithm stops if memberships have changed insignificantly.
-        BaseFuzzyCMeansClusterer.StopCondition stopCond =
-            BaseFuzzyCMeansClusterer.StopCondition.STABLE_MEMBERSHIPS;
-
-        // Maximum difference between new and old membership values with which algorithm will continue to work.
-        double maxDelta = 0.01;
-
-        // The maximum number of FCM iterations.
-        int maxIterations = 50;
-
-        // Create new local clusterer with parameters described above.
-        FuzzyCMeansLocalClusterer clusterer = new FuzzyCMeansLocalClusterer(distanceMeasure,
-            exponentialWeight, stopCond, maxDelta, maxIterations, null);
-
-        // Create sample data.
-        double[][] points = shuffle((int)(DataChanger.next()));
-
-        // Create the matrix that contains sample points.
-        DenseLocalOnHeapMatrix pntMatrix = new DenseLocalOnHeapMatrix(points);
-
-        // Call clusterization method with some number of centers.
-        // It returns model that can predict results for new points.
-        int numCenters = 4;
-        FuzzyCMeansModel mdl = clusterer.cluster(pntMatrix, numCenters);
-
-        // Get centers of clusters that is computed by Fuzzy C-Means algorithm.
-        mdl.centers();
-
-        return true;
-    }
-
-    /** */
-    private double[][] shuffle(int off) {
-        final double[][] points = new double[][] {
-            {-10, -10}, {-9, -11}, {-10, -9}, {-11, -9},
-            {10, 10}, {9, 11}, {10, 9}, {11, 9},
-            {-10, 10}, {-9, 11}, {-10, 9}, {-11, 9},
-            {10, -10}, {9, -11}, {10, -9}, {11, -9}};
-
-        final int size = points.length;
-
-        final double[][] res = new double[size][];
-
-        for (int i = 0; i < size; i++)
-            res[i] = points[(i + off) % size];
-
-        return res;
-    }
-}