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package org.broadinstitute.gatk.tools.walkers.haplotypecaller;

import htsjdk.variant.variantcontext.Allele;
import org.broadinstitute.gatk.utils.genotyper.SampleListUtils;
import org.broadinstitute.gatk.tools.walkers.haplotypecaller.readthreading.HaplotypeGraph;
import org.broadinstitute.gatk.utils.collections.Pair;
import org.broadinstitute.gatk.utils.genotyper.PerReadAlleleLikelihoodMap;
import org.broadinstitute.gatk.utils.haplotype.Haplotype;
import org.broadinstitute.gatk.utils.pairhmm.*;
import org.broadinstitute.gatk.utils.sam.ClippedGATKSAMRecord;
import org.broadinstitute.gatk.utils.sam.GATKSAMRecord;
import org.testng.Assert;
import org.testng.SkipException;
import org.testng.annotations.DataProvider;
import org.testng.annotations.Test;

import java.util.*;

/**
 * Created with IntelliJ IDEA.
 * User: valentin
 * Date: 8/4/13
 * Time: 10:20 PM
 * To change this template use File | Settings | File Templates.
 */
@Test(enabled=false)
public class ReadThreadingLikelihoodCalculationEngineUnitTest extends ActiveRegionTestDataSetUnitTest {


//    private static FastHMM hmm = new MLLog10PairHMM((byte)10); // new FastLoglessPairHMM((byte)10);

    private static FlexibleHMM hmm = new FastLoglessPairHMM((byte)10);

    @Test(dataProvider="activeRegionTestDataSets",enabled=false)
    public void testActiveRegionsDataSet(final ActiveRegionTestDataSet as, final int kmerSize, final int readLength, final String variation, final int readCount, final int regionSize, final byte bq, final byte iq, final byte dq) {
        super.testActiveRegionsDataSet(as,kmerSize,readLength,variation,readCount,regionSize,bq,iq,dq);
    }
        /** How many missing read record are tolerated in the graph based approach. For example a read is missed
         * if it does not map to the reference path with at least two kmers in non overlapping positions. This constant
         * indictes the proportion of reads reacords that we can miss with respect to all possible
         */
    private static final double READ_SKIP_TOLERANCE = 0.01;

    //final PairHMMLikelihoodCalculationEngine fullPairHMM = new PairHMMLikelihoodCalculationEngine((byte)10, false,
    //        PairHMM.HMM_IMPLEMENTATION.LOGLESS_CACHING, -3);
    final PairHMMLikelihoodCalculationEngine fullPairHMM = new PairHMMLikelihoodCalculationEngine((byte)10,
            PairHMM.HMM_IMPLEMENTATION.LOGLESS_CACHING, PairHMM.HMM_SUB_IMPLEMENTATION.UNVECTORIZED, true, Double.NEGATIVE_INFINITY,
            true, PairHMMLikelihoodCalculationEngine.PCR_ERROR_MODEL.NONE);

    // When using likelihoods it should be around 0.05 since
    // When using maximum-likelihoods it can be as low as 0.00001
    private static final double SIGNIFICANT_LnLK_RATIO_DIFF_FRACTION = hmm instanceof FastLoglessPairHMM ? 0.1 : 0.00001;


    // Some case is kind of expected to have differences between PairHMM and GraphBased Flexible PairHMM.
    // Is therefore difficult to test for the to give similar results in a unit test....
    // This is left for for example Integration tests like GraphBasedVsLoglessAccuracyIntegrationTest.
    // There code herein is maintain around for historical purposes, but disabled.
    @Test(dataProvider="readLikekihoodRatioTestData",enabled=false)
    public void testReadLikelihoodRatios(final ActiveRegionTestDataSet ds, final GATKSAMRecord read, final Allele a1,
                                         final Allele a2, final PerReadAlleleLikelihoodMap loglessLks,
                                         final PerReadAlleleLikelihoodMap graphLks, final List<Civar.ElementOffset> readEventOffsets, final List<Civar.ElementOffset> firstAlleleCivar, final List<Civar.ElementOffset> secondAlleleCivar ) {

        checkForLongEventsThatMightCauseFailures(readEventOffsets, firstAlleleCivar, secondAlleleCivar);
        final Map<Allele,Double> logless = loglessLks.getLikelihoodReadMap().get(read);
        final Map<Allele,Double> graph = graphLks.getLikelihoodReadMap().get(read);
        final double loglessA1Lk = logless.get(a1);
        final double loglessA2Lk = logless.get(a2);
        if (graph == null)
            throw new SkipException("no likelihoods produced for this read using the graph method: Lla1= " + loglessA1Lk + " Lla2= " + loglessA2Lk + "LlDiff=" + (loglessA2Lk - loglessA1Lk)  );

        final Double graphA1Lk = graph.get(a1);
        final Double graphA2Lk = graph.get(a2);
        if (graphA1Lk == null)
            throw new SkipException("no likelihoods produced for this read in the first haplotype: Lla1= " + loglessA1Lk + " Lla2= " + loglessA2Lk + "LlDiff=" + (loglessA2Lk - loglessA1Lk)  );
        if (graphA2Lk == null)
            throw new SkipException("no likelihoods produced for this read in the second haplotype:  Lla1= " + loglessA1Lk + " Lla2= " + loglessA2Lk + "LlDiff=" + (loglessA2Lk - loglessA1Lk)  );

        final double loglessDiff = loglessA1Lk - loglessA2Lk;
        final double graphDiff = graphA1Lk - graphA2Lk;
        final double epsilon = calculateEpsilon(graphDiff,loglessDiff);
        Assert.assertEquals(graphDiff,loglessDiff,epsilon,String.format("Delta(%f,%f) = %f > %f",graphDiff,loglessDiff,Math.abs(graphDiff - loglessDiff),epsilon));

    }

    private double calculateEpsilon(final double graphDiff, final double loglessDiff) {
        if (hmm instanceof FastLoglessPairHMM)
            return Math.max(0.01,Math.max(Math.abs(loglessDiff),Math.abs(graphDiff)) * SIGNIFICANT_LnLK_RATIO_DIFF_FRACTION);
        else
            return SIGNIFICANT_LnLK_RATIO_DIFF_FRACTION;
    }

    private static final double MIN_READ_ACROSS_SIZE_FOR_INDEL_EVENTS = 0.8; // 50% percent.
    private static final double MIN_LARGE_INDEL = 4;

    private void checkForLongEventsThatMightCauseFailures(final List<Civar.ElementOffset> read, final List<Civar.ElementOffset> a1, final List<Civar.ElementOffset> a2) {

        int sequenceLength = Math.max(a1.get(a1.size() - 1).templateTo, a2.get(a2.size() - 1).templateTo) + 1;

        boolean tai1 = thereAreIndels(a1);
        boolean tai2 = thereAreIndels(a2);
        boolean tair = thereAreIndels(read);
        boolean thereAreIndels = tai1 || tai2 || tair;
        if (!thereAreIndels) return;

        final boolean[] inserts = new boolean[sequenceLength];
        final boolean[] deletions = new boolean[sequenceLength];
        final int[] range = new int[2];

        int refStart = Integer.MAX_VALUE;
        int refEnd = -1;

        for (final Civar.ElementOffset ce : read) {
            if (refStart > ce.templateFrom)
                refStart = ce.templateFrom;
            if (refEnd < ce.templateTo)
                refEnd = ce.templateTo;
            switch (ce.element.operator()) {
                case DELETION:
                    deletions[ce.templateFrom] = deletions[ce.templateTo] = true;
                    break;
                case INSERTION:
                    inserts[ce.templateFrom] = inserts[ce.templateTo] = true;
                    break;
                case MATCH:
                    break;
            }
        }

        range[0] = refStart;
        range[1] = refEnd;

        checkForLongEventsThatMightCauseFailures_allele(refStart,refEnd,inserts,deletions,a1);
        checkForLongEventsThatMightCauseFailures_allele(refStart,refEnd,inserts,deletions,a2);
    }

    private void checkForLongEventsThatMightCauseFailures_allele(final int refStart, final int refEnd, final boolean[] inserts, final boolean[] deletions, final List<Civar.ElementOffset> a1) {
        for (final Civar.ElementOffset ce : a1) {
            if (ce.templateFrom <= refStart) continue;
            if (ce.templateTo >= refEnd) continue;
            int size;
            switch (ce.element.operator()) {
                case DELETION:
                    size = ce.templateTo - ce.templateFrom;
                    if (deletions[ce.templateFrom] || deletions[ce.templateTo]) continue;
                    break;
                case INSERTION:
                    size = ce.sequenceTo - ce.sequenceFrom;
                    if (inserts[ce.templateFrom] || inserts[ce.templateTo]) continue;
                    break;
                default:
                    continue;
            }
            int minMargin = (int) Math.ceil(size * MIN_READ_ACROSS_SIZE_FOR_INDEL_EVENTS);
            if (ce.templateFrom - refStart < minMargin)
                throw new SkipException("Large Indel");
            if (refEnd - ce.templateTo < minMargin)
                throw new SkipException("Large Indel");
        }

    }

    private boolean thereAreIndels(final List<Civar.ElementOffset> a1) {
        for (final Civar.ElementOffset ce : a1)  {
             switch (ce.element.operator()) {
                 case DELETION:
                     if (ce.templateTo - ce.templateFrom >= MIN_LARGE_INDEL) return true;
                     break;
                 case INSERTION:
                     if (ce.sequenceTo - ce.sequenceFrom >= MIN_LARGE_INDEL) return true;
                     break;
             }
        }
        return false;
    }


    @DataProvider(name="readLikekihoodRatioTestData")
    public Iterator<Object[]> readLikelihoodRatioTestDataSets() {
           final Iterator<Object[]> activeRegionTestDataSetIterator = super.activeRegionTestDataSets();
           return new java.util.Iterator<Object[]>() {

               public static final boolean INTRODUCE_READ_ERRORS = true;

               private List<Pair<Allele,Allele>> allelePairs;
               private Iterator<Pair<Allele,Allele>> allelePairsIt;
               private Iterator<GATKSAMRecord> readIt;
               private GATKSAMRecord read;
               private Iterator<List<Civar.ElementOffset>> civarEventOffsetsIt;
               private List<Civar.ElementOffset> civarEventOffsets;
               private ActiveRegionTestDataSet dataSet;
               private GraphBasedLikelihoodCalculationEngineInstance graphEngine;
               private PerReadAlleleLikelihoodMap graphLks;
               private PerReadAlleleLikelihoodMap loglessLks;
               private Map<Allele,Civar> civarByAllele;
               private String reference;

               @Override
               public boolean hasNext() {
                   return activeRegionTestDataSetIterator.hasNext()  || (readIt != null && readIt.hasNext()) || (allelePairsIt != null && allelePairsIt.hasNext());
               }

               @Override
               public Object[] next() {
                   if (allelePairsIt != null && allelePairsIt.hasNext()) {
                       final Pair<Allele,Allele> allelePair = allelePairsIt.next();
                       return new Object[] { dataSet, read, allelePair.getFirst(), allelePair.getSecond(), loglessLks, graphLks, civarEventOffsets, civarByAllele.get(allelePair.getFirst()).eventOffsets(reference,0,Integer.MAX_VALUE), civarByAllele.get(allelePair.getSecond()).eventOffsets(reference,0,Integer.MAX_VALUE)};
                   }
                   if (readIt != null && readIt.hasNext()) {
                        allelePairsIt = allelePairs.iterator();
                        final Pair<Allele,Allele> allelePair = allelePairsIt.next();
                        return new Object[] {dataSet, read = readIt.next(), allelePair.getFirst(), allelePair.getSecond(), loglessLks, graphLks, civarEventOffsets = civarEventOffsetsIt.next(), civarByAllele.get(allelePair.getFirst()).eventOffsets(reference,0,Integer.MAX_VALUE), civarByAllele.get(allelePair.getSecond()).eventOffsets(reference,0,Integer.MAX_VALUE) };
                   }
                   final Object[] params = activeRegionTestDataSetIterator.next();
                   dataSet = (ActiveRegionTestDataSet) params[0];
                   if (INTRODUCE_READ_ERRORS) dataSet.introduceErrors(new Random(13));
                   graphEngine = new GraphBasedLikelihoodCalculationEngineInstance(dataSet.assemblyResultSet(),hmm,Double.NEGATIVE_INFINITY, HeterogeneousKmerSizeResolution.COMBO_MAX);
                   graphLks = graphEngine.computeReadLikelihoods(dataSet.haplotypeList(), SampleListUtils.singletonList("anonymous"),Collections.singletonMap("anonymous",dataSet.readList())).toPerReadAlleleLikelihoodMap(0);

                   // clip reads at the anchors.
                   final Map<GATKSAMRecord,GATKSAMRecord> clippedReads = anchorClippedReads(graphEngine.getHaplotypeGraph(),dataSet.readList());
                   final List<GATKSAMRecord> clippedReadList = new ArrayList<>(dataSet.readList().size());

                   for (final GATKSAMRecord r : dataSet.readList()) {
                       clippedReadList.add(clippedReads.containsKey(r) ? clippedReads.get(r) : r);
                   }

                   loglessLks = fullPairHMM.computeReadLikelihoods(dataSet.assemblyResultSet(),SampleListUtils.singletonList("anonymous"),Collections.singletonMap("anonymous",clippedReadList)).toPerReadAlleleLikelihoodMap(0);

                   // Change clipped by unclipped in the resulting likelihood map.
                   for (final GATKSAMRecord r : clippedReads.keySet()) {
                       loglessLks.getLikelihoodReadMap().put(r,loglessLks.getLikelihoodReadMap().remove(clippedReads.get(r)));
                   }
                   final List<Haplotype> haplotypes = dataSet.haplotypeList();
                   final Map<Haplotype,Allele> alleleByHaplotype = new HashMap<>(haplotypes.size());
                   final Map<String,Civar> civarBySequence = new HashMap<>(haplotypes.size());
                   final Map<String,Haplotype> haplotypeBySequence = new HashMap<>(haplotypes.size());
                   civarByAllele = new HashMap<>(haplotypes.size());
                   final List<Civar> unrolledCivars = dataSet.unrolledCivars();
                   for (int i = 0; i < haplotypes.size(); i++)  {
                       final Haplotype h = haplotypes.get(i);
                       haplotypeBySequence.put(h.getBaseString(),h);
                       civarBySequence.put(h.getBaseString(),unrolledCivars.get(i));
                   }
                   for (final Allele a : loglessLks.getAllelesSet()) {
                       alleleByHaplotype.put(haplotypeBySequence.get(a.getBaseString()),a);
                       civarByAllele.put(a,civarBySequence.get(a.getBaseString()));
                   }
                   allelePairs = new ArrayList<>(haplotypes.size() * 2);
                   final Haplotype[] haplotypeArray = haplotypes.toArray(new Haplotype[haplotypes.size()]);
                   for (int i = 0; i < haplotypeArray.length; i++)
                       for (int j = i + 1; j < haplotypeArray.length; j++)
                           allelePairs.add(new Pair<>(alleleByHaplotype.get(haplotypeArray[i]),alleleByHaplotype.get(haplotypeArray[j])));
                   allelePairsIt = allelePairs.iterator();
                   readIt = dataSet.readList().iterator();
                   final Pair<Allele,Allele> allelePair = allelePairsIt.next();
                   civarEventOffsetsIt = dataSet.readEventOffsetList().iterator();
                   reference = dataSet.getReference();
                   return new Object[] { dataSet , read = readIt.next(), allelePair.getFirst(), allelePair.getSecond(), loglessLks, graphLks, civarEventOffsets = civarEventOffsetsIt.next(), civarByAllele.get(allelePair.getFirst()).eventOffsets(reference,0,Integer.MAX_VALUE), civarByAllele.get(allelePair.getSecond()).eventOffsets(reference,0,Integer.MAX_VALUE)};
               }

               @Override
               public void remove() {
                   throw new UnsupportedOperationException();
               }
           };
    }


    /**
     * Returns the reads clipped at their anchors.
     *
     * @param reads target reads.
     * @return never {@code null}.
     */
    protected Map<GATKSAMRecord, GATKSAMRecord> anchorClippedReads(final HaplotypeGraph haplotypeGraph, final List<GATKSAMRecord> reads) {
        final Map<GATKSAMRecord, GATKSAMRecord> result = new HashMap<>(reads.size());
        for (final GATKSAMRecord r : reads) {
            final ReadAnchoring anchoring = new ReadAnchoring(r,haplotypeGraph);
            if (anchoring.isAnchoredSomewhere())
                continue;
            final int start = anchoring.leftAnchorIndex;
            final int end = anchoring.rightAnchorIndex + haplotypeGraph.getKmerSize();
            final GATKSAMRecord clipped = new ClippedGATKSAMRecord(r, start, end);
            result.put(r, clipped);
        }
        return result;
    }



}
