org.apache.sysml.udf.lib.OrderWrapper Maven / Gradle / Ivy

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Declarative Machine Learning
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/*
 * 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.sysml.udf.lib;

import java.util.Arrays;
import java.util.Comparator;

import org.apache.sysml.udf.FunctionParameter;
import org.apache.sysml.udf.Matrix;
import org.apache.sysml.udf.PackageFunction;
import org.apache.sysml.udf.PackageRuntimeException;
import org.apache.sysml.udf.Scalar;
import org.apache.sysml.udf.Matrix.ValueType;
/**
 * Wrapper class for Order rows based on values in a column
 *
 */
public class OrderWrapper extends PackageFunction 
{
	
	private static final long serialVersionUID = 1L;
	private static final String OUTPUT_FILE = "TMP";

	//return matrix
	private Matrix ret;

	@Override
	public int getNumFunctionOutputs() 
	{
		return 1;	
	}

	@Override
	public FunctionParameter getFunctionOutput(int pos) 
	{	
		if(pos == 0)
			return ret;
		
		throw new PackageRuntimeException("Invalid function output being requested");
	}

	@Override
	public void execute() 
	{ 
		try 
		{
			Matrix inM = (Matrix) getFunctionInput(0);
			double [][] inData = inM.getMatrixAsDoubleArray();
			int col = Integer.parseInt(((Scalar)getFunctionInput(1)).getValue());			
			boolean desc = Boolean.parseBoolean(((Scalar)getFunctionInput(2)).getValue());	
			
			//sort input matrix (in-place)
			if( !desc ) //asc
				Arrays.sort(inData, new AscRowComparator(col-1));
			else //desc
				Arrays.sort(inData, new DescRowComparator(col-1));
				
			//create and copy output matrix		
			String dir = createOutputFilePathAndName( OUTPUT_FILE );	
			ret = new Matrix( dir, inM.getNumRows(), inM.getNumCols(), ValueType.Double );
			ret.setMatrixDoubleArray(inData);
		} 
		catch (Exception e) 
		{
			throw new PackageRuntimeException("Error executing external order function", e);
		}
	}

	/**
	 * 
	 *
	 */
	private static class AscRowComparator implements Comparator 
	{
		private int _col = -1;
		
		public AscRowComparator( int col )
		{
			_col = col;
		}

		@Override
		public int compare(double[] arg0, double[] arg1) 
		{			
			return (arg0[_col] < arg1[_col] ? -1 : (arg0[_col] == arg1[_col] ? 0 : 1));
		}		
	}
	
	/**
	 * 
	 * 
	 */
	private static class DescRowComparator implements Comparator 
	{
		private int _col = -1;
		
		public DescRowComparator( int col )
		{
			_col = col;
		}

		@Override
		public int compare(double[] arg0, double[] arg1) 
		{			
			return (arg0[_col] > arg1[_col] ? -1 : (arg0[_col] == arg1[_col] ? 0 : 1));
		}		
	}
}