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/*
 *
 *  * Copyright 2015 Skymind,Inc.
 *  *
 *  *    Licensed 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.deeplearning4j.util;

import org.deeplearning4j.berkeley.Pair;
import org.nd4j.linalg.api.ndarray.INDArray;

import java.util.ArrayList;
import java.util.List;
import java.util.Random;


public class InputSplit {

	private InputSplit() {
	}

	public static void splitInputs(INDArray inputs, INDArray outcomes, List> train, List> test, double split) {
		List> list = new ArrayList<>();
		for(int i = 0; i < inputs.rows(); i++) {
			list.add(new Pair<>(inputs.getRow(i),outcomes.getRow(i)));
		}

		splitInputs(list,train,test,split);
	}

	public static void splitInputs(List> pairs,List> train,List> test,double split) {
		Random rand = new Random();

		for(Pair pair : pairs)
			if(rand.nextDouble() <= split) 
				train.add(pair);
			else
				test.add(pair);

			
	}

}