/*
* 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.ml.math.impls.vector;
import org.apache.ignite.ml.math.Matrix;
import org.apache.ignite.ml.math.Vector;
import org.apache.ignite.ml.math.impls.storage.vector.SparseLocalOffHeapVectorStorage;
/**
* Implementation for {@link Vector} assuming sparse logic and local offheap JVM storage.
* It is suitable for data sets where local, non-distributed execution is satisfactory and on-heap JVM storage
* is not enough to keep the entire data set.
* <p>See also: <a href="https://en.wikipedia.org/wiki/Sparse_array">Wikipedia article</a>.</p>
*/
public class SparseLocalOffHeapVector extends AbstractVector {
/**
* @param crd Vector cardinality.
*/
public SparseLocalOffHeapVector(int crd) {
setStorage(new SparseLocalOffHeapVectorStorage(crd));
}
/** {@inheritDoc} */
@Override public Vector like(int crd) {
return new SparseLocalOffHeapVector(crd);
}
/** {@inheritDoc} */
@Override public Matrix likeMatrix(int rows, int cols) {
return null;
}
}