/*
 *  ******************************************************************************
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 *  * This program and the accompanying materials are made available under the
 *  * terms of the Apache License, Version 2.0 which is available at
 *  * https://www.apache.org/licenses/LICENSE-2.0.
 *  *
 *  *  See the NOTICE file distributed with this work for additional
 *  *  information regarding copyright ownership.
 *  * 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.
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 *  * SPDX-License-Identifier: Apache-2.0
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package org.eclipse.deeplearning4j.nd4j.linalg.dataset;

import org.apache.commons.io.IOUtils;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.dataset.DataSet;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.common.io.ClassPathResource;

import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

public class IrisUtils {

    public static List<DataSet> loadIris(int from, int to) throws IOException {
        ClassPathResource resource = new ClassPathResource("iris.dat", IrisUtils.class.getClassLoader());
        @SuppressWarnings("unchecked")
        List<String> lines = IOUtils.readLines(resource.getInputStream());
        List<DataSet> list = new ArrayList<>();
        INDArray ret = Nd4j.ones(Math.abs(to - from), 4);
        double[][] outcomes = new double[lines.size()][3];
        int putCount = 0;

        for (int i = from; i < to; i++) {
            String line = lines.get(i);
            String[] split = line.split(",");

            addRow(ret, putCount++, split);

            String outcome = split[split.length - 1];
            double[] rowOutcome = new double[3];
            rowOutcome[Integer.parseInt(outcome)] = 1;
            outcomes[i] = rowOutcome;
        }

        for (int i = 0; i < ret.rows(); i++)
            list.add(new DataSet(ret.getRow(i), Nd4j.create(outcomes[from + i])));

        return list;
    }

    private static void addRow(INDArray ret, int row, String[] line) {
        double[] vector = new double[4];
        for (int i = 0; i < 4; i++)
            vector[i] = Double.parseDouble(line[i]);

        ret.putRow(row, Nd4j.create(vector));
    }
}
