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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.
 *  *
 *  * SPDX-License-Identifier: Apache-2.0
 *  *****************************************************************************
 */

package org.nd4j.evaluation.serde;

import org.nd4j.evaluation.classification.ConfusionMatrix;
import org.nd4j.shade.jackson.core.JsonParser;
import org.nd4j.shade.jackson.core.JsonProcessingException;
import org.nd4j.shade.jackson.databind.DeserializationContext;
import org.nd4j.shade.jackson.databind.JsonDeserializer;
import org.nd4j.shade.jackson.databind.JsonNode;
import org.nd4j.shade.jackson.databind.node.ArrayNode;
import org.nd4j.shade.jackson.databind.node.ObjectNode;

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

public class ConfusionMatrixDeserializer extends JsonDeserializer> {
    @Override
    public ConfusionMatrix deserialize(JsonParser jp, DeserializationContext ctxt)
                    throws IOException, JsonProcessingException {
        JsonNode n = jp.getCodec().readTree(jp);

        //Get class names/labels
        ArrayNode classesNode = (ArrayNode) n.get("classes");
        List classes = new ArrayList<>();
        for (JsonNode cn : classesNode) {
            classes.add(cn.asInt());
        }

        ConfusionMatrix cm = new ConfusionMatrix<>(classes);

        ObjectNode matrix = (ObjectNode) n.get("matrix");
        Iterator> matrixIter = matrix.fields();
        while (matrixIter.hasNext()) {
            Map.Entry e = matrixIter.next();

            int actualClass = Integer.parseInt(e.getKey());
            ArrayNode an = (ArrayNode) e.getValue();

            ArrayNode innerMultiSetKey = (ArrayNode) an.get(0);
            ArrayNode innerMultiSetCount = (ArrayNode) an.get(1);

            Iterator iterKey = innerMultiSetKey.iterator();
            Iterator iterCnt = innerMultiSetCount.iterator();
            while (iterKey.hasNext()) {
                int predictedClass = iterKey.next().asInt();
                int count = iterCnt.next().asInt();

                cm.add(actualClass, predictedClass, count);
            }
        }

        return cm;
    }
}