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/* Copyright (C) 2013-2020 TU Dortmund
 * This file is part of LearnLib, http://www.learnlib.de/.
 *
 * 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 de.learnlib.api.algorithm;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collection;
import java.util.Collections;
import java.util.List;

import de.learnlib.api.query.DefaultQuery;
import net.automatalib.automata.fsa.DFA;
import net.automatalib.automata.fsa.FiniteStateAcceptor;
import net.automatalib.automata.fsa.NFA;
import net.automatalib.automata.transducers.MealyMachine;
import net.automatalib.words.Word;

public interface PassiveLearningAlgorithm {

    void addSamples(Collection> samples);

    @SuppressWarnings("unchecked")
    default void addSamples(DefaultQuery... samples) {
        addSamples(Arrays.asList(samples));
    }

    @SuppressWarnings("unchecked")
    default void addSamples(D output, Word... words) {
        addSamples(output, Arrays.asList(words));
    }

    default void addSamples(D output, Collection> words) {
        List> queries = new ArrayList<>(words.size());
        for (Word word : words) {
            queries.add(new DefaultQuery<>(word, output));
        }

        addSamples(queries);
    }

    default void addSample(Word input, D output) {
        addSample(new DefaultQuery<>(input, output));
    }

    default void addSample(DefaultQuery sample) {
        addSamples(Collections.singleton(sample));
    }

    M computeModel();

    /**
     * Basic interface for passive learning algorithms that infer {@link DFA}s.
     *
     * @param 
     *         input symbol type
     *
     * @author Malte Isberner
     */
    interface PassiveDFALearner extends PassiveAcceptorLearner, I> {}

    /**
     * Basic interface for passive learning algorithms that infer {@link MealyMachine Mealy machines}.
     *
     * @param 
     *         input symbol type
     * @param 
     *         output symbol type
     *
     * @author Malte Isberner
     */
    interface PassiveMealyLearner extends PassiveLearningAlgorithm, I, Word> {}

    /**
     * Basic interface for passive learning algorithms that infer {@link NFA}s.
     *
     * @param 
     *         input symbol type
     *
     * @author Malte Isberner
     */
    interface PassiveNFALearner extends PassiveAcceptorLearner, I> {}

    /**
     * Basic interface for passive learning algorithms that infer finite-state acceptors ({@link DFA}s or {@link
     * NFA}s).
     *
     * @param 
     *         model type
     * @param 
     *         input symbol type
     *
     * @author Malte Isberner
     */
    interface PassiveAcceptorLearner, I>
            extends PassiveLearningAlgorithm {

        default void addPositiveSample(Word word) {
            addSample(word, true);
        }

        default void addPositiveSamples(Collection> words) {
            addSamples(true, words);
        }

        @SuppressWarnings("unchecked")
        default void addPositiveSamples(Word... words) {
            addSamples(true, words);
        }

        default void addNegativeSample(Word word) {
            addSample(word, false);
        }

        default void addNegativeSamples(Collection> words) {
            addSamples(false, words);
        }

        @SuppressWarnings("unchecked")
        default void addNegativeSamples(Word... words) {
            addSamples(false, words);
        }
    }

}