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package org.broadinstitute.gatk.utils.pairhmm;

import com.google.java.contract.Ensures;
import com.google.java.contract.Requires;
import org.broadinstitute.gatk.utils.QualityUtils;

import java.util.Arrays;

import static org.broadinstitute.gatk.utils.pairhmm.PairHMMModel.*;

/**
 * Created with IntelliJ IDEA.
 * User: bradt
 * Date: 6/11/13
 */
public class ArrayLoglessPairHMM extends PairHMM {
    private static final double INITIAL_CONDITION = Math.pow(2, 1020);
    private static final double INITIAL_CONDITION_LOG10 = Math.log10(INITIAL_CONDITION);

    // we divide e by 3 because the observed base could have come from any of the non-observed alleles
    protected static final double TRISTATE_CORRECTION = 3.0;

    protected double[][] transition = null; // The transition probabilities cache
    protected double[][] prior = null;      // The prior probabilities cache

    // Array declarations for arrays implementation
    private double[] currentMatchArray = null;
    private double[] currentDeleteArray = null;
    private double[] currentInsertArray = null;
    private double[] parentMatchArray = null;
    private double[] parentDeleteArray = null;
    private double[] parentInsertArray = null;
    private double[] grandparentMatchArray = null;
    private double[] grandparentDeleteArray = null;
    private double[] grandparentInsertArray = null;

    // When successive haplotypes have a common prefix, these arrays store cached info from the previous haplotype; for reading
    private double[] matchCacheArray = null;
    private double[] deleteCacheArray = null;
    private double[] insertCacheArray = null;

    // These arrays store cache info for use with the next haplotype; for writing
    private double[] nextMatchCacheArray = null;
    private double[] nextDeleteCacheArray = null;
    private double[] nextInsertCacheArray = null;

    // Used when caching to store our intermediate sum at point of first difference bw successive haplotypes
    private double partialSum;


    /**
     * {@inheritDoc}
     */
    @Override
    public void initialize(final int readMaxLength, final int haplotypeMaxLength ) {
        super.initialize(readMaxLength, haplotypeMaxLength);

        transition = PairHMMModel.createTransitionMatrix(maxReadLength);
        prior = new double[paddedMaxReadLength][paddedMaxHaplotypeLength];

        // Initialize all arrays
        // Final Cell of array is a padding cell, initialized to zero.
        currentMatchArray = new double[paddedMaxReadLength];
        currentDeleteArray = new double[paddedMaxReadLength];
        currentInsertArray = new double[paddedMaxReadLength];

        parentMatchArray = new double[paddedMaxReadLength];
        parentDeleteArray = new double[paddedMaxReadLength];
        parentInsertArray = new double[paddedMaxReadLength];

        grandparentMatchArray = new double[paddedMaxReadLength];
        grandparentDeleteArray = new double[paddedMaxReadLength];
        grandparentInsertArray = new double[paddedMaxReadLength];

        // Initialize the special arrays used for caching when successive haplotypes have a common prefix
        matchCacheArray = new double[paddedMaxReadLength];
        deleteCacheArray = new double[paddedMaxReadLength];
        insertCacheArray = new double[paddedMaxReadLength];

        nextMatchCacheArray = new double[paddedMaxReadLength];
        nextDeleteCacheArray = new double[paddedMaxReadLength];
        nextInsertCacheArray = new double [paddedMaxReadLength];
    }


    /**
     * {@inheritDoc}
     */
    @Override
    public double subComputeReadLikelihoodGivenHaplotypeLog10( final byte[] haplotypeBases,
                                                               final byte[] readBases,
                                                               final byte[] readQuals,
                                                               final byte[] insertionGOP,
                                                               final byte[] deletionGOP,
                                                               final byte[] overallGCP,
                                                               int hapStartIndex,
                                                               final boolean recacheReadValues,
                                                               final int nextHapStartIndex) {

        if ( ! constantsAreInitialized) {
            initializeProbabilities(transition, insertionGOP, deletionGOP, overallGCP);

            // note that we initialized the constants
            constantsAreInitialized = true;
        }
        initializePriors(haplotypeBases, readBases, readQuals, hapStartIndex);

        // Some housekeeping to be done if we are starting a new read
        if (recacheReadValues) {
            hapStartIndex = 0;

            initializeProbabilities(transition, insertionGOP, deletionGOP, overallGCP);
            // note that we initialized the constants
            constantsAreInitialized = true;

            // Read length may have changed, so we need to set zero-value padding at the appropriate position.
            padMatchAndInsertArrays(readBases.length);
        }

        // if we have not cached from a previous haplotype, clear any info we may have accumulated in a previous HMM iteration
        if (hapStartIndex == 0) {
            clearPreviouslyCachedInfo(readBases.length);

            // Haplotype length may have changed, so we need to set initial-value padding at the appropriate position.
            padDeleteArrays(haplotypeBases.length, readBases.length);
        }

        // We build up our solution by looking at position [0] in the match, insert arrays. Need to set these to 0 before we start.
        clearArraySolutionPosition();

        // Some parameters to control behavior during the dynamic programming loop
        final int maxDiagonals = readBases.length + haplotypeBases.length - hapStartIndex - 1;   // Number of diagonals for a matrix  = rows + cols - 1;
        int startFill;                                                                           // The lower bound of the array indices we want to over-write
        int endFill;                                                                             // The upper bound of the array indices we want to over-write
        final int cacheSumIndex = nextHapStartIndex - hapStartIndex + readBases.length - 1;      // This array will contain the partial sum to cache for the next haplotype
        double finalArraySumProbabilities = partialSum;                                          // The final answer prior to log10 correction

        // Perform dynamic programming using arrays, as if over diagonals of a hypothetical read/haplotype alignment matrix
        for (int i = 1; i <= maxDiagonals; i++) {
            // set the bounds for cells we wish to fill in the arrays
            startFill = Math.max(readBases.length - i, 0);
            endFill = Math.min(maxDiagonals - i + 1, readBases.length);

            // apply any previously cached array information
            if (i <= readBases.length)
                applyPreviouslyCachedInfo(startFill);

            // fill in the cells for our current arrays
            updateArrays(readBases.length, hapStartIndex, nextHapStartIndex, startFill, endFill, i);

            // final probability is the log10 sum of the last element in the Match and Insertion state arrays
            // this way we ignore all paths that ended in deletions! (huge)
            // but we have to sum all the paths ending in the M and I arrays, because they're no longer extended.
            // Where i > readBases.length, array[0] corresponds to bottom row of a [read] x [haplotype] matrix. Before this, they carries the 0's we set above.
            finalArraySumProbabilities += currentInsertArray[0] + currentMatchArray[0];

            // Partial sum for caching the next haplotype:
            // At the position of the last similar base between this haplotype and the next one...
            // ...remember the partial sum, so that we can start here on the next hap.
            if (i == cacheSumIndex)
                partialSum = finalArraySumProbabilities;

            rotateArrayReferences();
        }
        // The cache arrays we wrote for this haplotype will be read for the next haplotype.
        rotateCacheArrays();

        //return result
        return Math.log10(finalArraySumProbabilities) - INITIAL_CONDITION_LOG10;
    }

    /**
     * Initializes the matrix that holds all the constants related to the editing
     * distance between the read and the haplotype.
     *
     * @param haplotypeBases the bases of the haplotype
     * @param readBases      the bases of the read
     * @param readQuals      the base quality scores of the read
     * @param startIndex     where to start updating the distanceMatrix (in case this read is similar to the previous read)
     */
    public void initializePriors(final byte[] haplotypeBases, final byte[] readBases, final byte[] readQuals, final int startIndex) {

        // initialize the pBaseReadLog10 matrix for all combinations of read x haplotype bases
        // Abusing the fact that java initializes arrays with 0.0, so no need to fill in rows and columns below 2.

        for (int i = 0; i < readBases.length; i++) {
            final byte x = readBases[i];
            final byte qual = readQuals[i];
            for (int j = startIndex; j < haplotypeBases.length; j++) {
                final byte y = haplotypeBases[j];
                prior[i+1][j+1] = ( x == y || x == (byte) 'N' || y == (byte) 'N' ?
                        QualityUtils.qualToProb(qual) : (QualityUtils.qualToErrorProb(qual) / (doNotUseTristateCorrection ? 1.0 : TRISTATE_CORRECTION)) );
            }
        }
    }

    /**
     * Initializes the matrix that holds all the constants related to quality scores.
     *
     * @param insertionGOP   insertion quality scores of the read
     * @param deletionGOP    deletion quality scores of the read
     * @param overallGCP     overall gap continuation penalty
     */
    @Requires({
            "insertionGOP != null",
            "deletionGOP != null",
            "overallGCP != null"
    })
    @Ensures("constantsAreInitialized")
    protected static void initializeProbabilities(final double[][] transition, final byte[] insertionGOP, final byte[] deletionGOP, final byte[] overallGCP) {
        PairHMMModel.qualToTransProbs(transition,insertionGOP,deletionGOP,overallGCP);
    }

    /**
     * Pad the ends of the Match and Insert arrays with 0.
     * Analogous to setting zeros in the first row in the Match, Insert matrices of N2MemoryPairHMM.
     *
     * @param padPosition Which index in the arrays we wish to pad
     */
    private void padMatchAndInsertArrays(final int padPosition) {
        grandparentMatchArray[padPosition] = 0;
        grandparentInsertArray[padPosition] = 0;
        parentMatchArray[padPosition] = 0;
        parentInsertArray[padPosition] = 0;
        currentMatchArray[padPosition] = 0;
        currentInsertArray[padPosition] = 0;
        matchCacheArray[padPosition] = 0;
        insertCacheArray[padPosition] = 0;
        nextMatchCacheArray[padPosition] = 0;
        nextInsertCacheArray[padPosition] = 0;
    }

    /**
     * Pad the Delete arrays with an intial value. Let's us have free deletions at the beginning of the alignment.
     * Analogous to padding the first row of the Delete matrix of N2MemoryPairHMM.
     *
     * @param haplotypeLength   The length of the present haplotype. Necessary for calculating initial padding value
     * @param padPosition       Which index in the arrays we wish to pad
     */
    private void padDeleteArrays(final int haplotypeLength, final int padPosition) {
        final double initialValue = INITIAL_CONDITION / haplotypeLength;

        // Pad the deletion arrays. Akin to padding the first row in the deletion matrix
        parentDeleteArray[padPosition] = initialValue;
        grandparentDeleteArray[padPosition] = initialValue;
        currentDeleteArray[padPosition] = initialValue;
        deleteCacheArray[padPosition] = initialValue;
        nextDeleteCacheArray[padPosition] = initialValue;
    }

    /**
     * We build up our solution by looking at position [0] in the match, insert arrays. Need to set these to 0 before we start.
     *
     */
    private void clearArraySolutionPosition() {
        grandparentMatchArray[0] = 0;
        grandparentInsertArray[0] = 0;
        parentMatchArray[0] = 0;
        parentInsertArray[0] = 0;
        currentMatchArray[0] = 0;
        currentInsertArray[0] = 0;
    }

    /**
     * Clears cached information saved from the last haplotype,
     * allowing us to start at the beginning of the present haplotype with intitial values of 0.
     *
     * @param fillLength How much of the cache arrays do we need to zero
     */
    private void clearPreviouslyCachedInfo(final int fillLength) {
        Arrays.fill(matchCacheArray, 0, fillLength, 0);
        Arrays.fill(deleteCacheArray, 0, fillLength, 0);
        Arrays.fill(insertCacheArray, 0, fillLength, 0);

        partialSum = 0;
    }

    /**
     * Applies cached information saved from the last haplotype,
     * allowing us to start in the middle of the present haplotype.
     *
     * @param indK the index in the arrays we wish to update with cached info
     */
    private void applyPreviouslyCachedInfo(int indK) {
        // apply caching info necessary for calculating current DELETE array values
        parentMatchArray[indK] = matchCacheArray[indK];
        parentDeleteArray[indK] = deleteCacheArray[indK];

        // apply caching info necessary for calculating current MATCH array values
        grandparentMatchArray[indK + 1] = matchCacheArray[indK + 1];
        grandparentDeleteArray[indK + 1] = deleteCacheArray[indK + 1];
        grandparentInsertArray[indK + 1] = insertCacheArray[indK + 1];
    }

    /**
     * Records the mid-process state of one location in the read/haplotype alignment.
     * Writes new cache information for use with the next haplotype we see.
     *
     * @param indK the index in the cache arrays we wish to store information in
     */
    private void recordNewCacheInfo(int indK) {
        nextMatchCacheArray[indK] = currentMatchArray[indK];
        nextDeleteCacheArray[indK] = currentDeleteArray[indK];
        nextInsertCacheArray[indK] = currentInsertArray[indK];
    }

    /**
     * Update the HMM arrays for the current diagonal.
     *
     * @param readLength        The length of the read
     * @param hapStartIndex     An offset that tells us if we are starting in the middle of the present haplotype
     * @param nextHapStartIndex An offset that tells us which base in the NEXT haplotype we need to look at to record new caching info
     * @param startFill         The lower bound of the array indices we want to over-write
     * @param endFill           The upper bound of the array indices we want to over-write
     * @param iii               The index indicating which diagonal of the read/haplotype alignment we are working on
     */
    private void updateArrays(final int readLength,
                              final int hapStartIndex,
                              final int nextHapStartIndex,
                              final int startFill,
                              final int endFill,
                              final int iii) {

        // The coordinate in our priors and transition matrices corresponding to a given position in the read/haplotype alignment
        int matrixRow;
        int matrixCol;

        int arrayIndex;
        for (arrayIndex = startFill; arrayIndex < endFill; arrayIndex++) {
            // translate the array position into a row, column in the priors and transition matrices
            matrixRow = readLength - arrayIndex - 1;
            matrixCol = iii - matrixRow - 1 + hapStartIndex;

            // update cell for each of our current arrays. Prior, transition matrices are padded +1 row,col
            updateArrayCell(arrayIndex, prior[matrixRow+1][matrixCol+1], transition[matrixRow+1]);

            // Set up caching for the next haplotype
            // At the position of the final similar base between this haplotype and the next one, remember the mid-array values
            if (matrixCol == nextHapStartIndex - 1)
                recordNewCacheInfo(arrayIndex);
        }
    }

    /**
     * Updates a cell in the HMM arrays
     *
     * @param indK             index in the arrays to update
     * @param prior            the likelihood editing distance matrix for the read x haplotype
     * @param transition       an array with the six transition relevant to this location
     */
    private void updateArrayCell( final int indK, final double prior, final double[] transition) {
        currentMatchArray[indK] = prior * ( grandparentMatchArray[indK + 1] * transition[matchToMatch] +
                grandparentInsertArray[indK + 1] * transition[indelToMatch] +
                grandparentDeleteArray[indK + 1] * transition[indelToMatch] );
        currentInsertArray[indK] = parentMatchArray[indK + 1] * transition[matchToInsertion] + parentInsertArray[indK + 1] * transition[insertionToInsertion];
        currentDeleteArray[indK] = parentMatchArray[indK] * transition[matchToDeletion] + parentDeleteArray[indK] * transition[deletionToDeletion];
    }

    /**
     * To prepare for the next diagonal in our loop, each array must be bumped to an older generation
     *
     */
    private void rotateArrayReferences() {
        double[] tempMatchArray = grandparentMatchArray;
        double[] tempDeleteArray = grandparentDeleteArray;
        double[] tempInsertArray = grandparentInsertArray;

        grandparentMatchArray = parentMatchArray;
        grandparentDeleteArray = parentDeleteArray;
        grandparentInsertArray = parentInsertArray;

        parentMatchArray = currentMatchArray;
        parentDeleteArray = currentDeleteArray;
        parentInsertArray = currentInsertArray;

        currentMatchArray = tempMatchArray;
        currentDeleteArray = tempDeleteArray;
        currentInsertArray = tempInsertArray;
    }

    /**
     * To prepare for the next haplotype, the caching info we wrote is copied into the cach-read arrays
     *
     */
    private void rotateCacheArrays() {
        matchCacheArray = nextMatchCacheArray.clone();
        deleteCacheArray = nextDeleteCacheArray.clone();
        insertCacheArray = nextInsertCacheArray.clone();
    }
}
