##########################################################################
# ANNOTATION SPECTRE 2D MATRICE COMPLEXE BASEE SUR UNE SEQUENCE RMN      #
# matriceComplexe : data.frame liste couples ppm de la matrice a annoter #
# BdDStandards : objet contenant la base de donnees des composes standards #
# nom_sequence : nom sequence 2D a utiliser pour annotation ("JRES", "COSY", "TOCSY", "HMBC", "HSQC") #
# ppm1Tol : tolerance ppm axe abscisses                                                               #
# ppm2Tol : tolerance ppm axe ordonnees                                                               #
# nb_ligne_template : preciser le nombre total de ligne de la feuille de calcul a annoter             #
#######################################################################################################
annotationRmn2D <- function(matriceComplexe, BdDStandards, nom_sequence, ppm1Tol = 0.01, ppm2Tol = 0.01,
                            seuil = 0, unicite = "NO") {
    ## Longueur de la peak-list de la matrice a annoter
    PeakListLength <- length(matriceComplexe[, 1])

    ## Nombre de metabolites inclus dans BdD de composes standards
    nbMetabolitesBdD <- length(BdDStandards)
    matrixAnnotation <- data.frame()
    allMetabolitesList <- data.frame()
    seuil_score <- seuil

    ## Boucle sur les metabolites inclus dans BdD
    for (i in seq_len(nbMetabolitesBdD)) {
        ## Infos metabolite en cours
        iMetabolite <- BdDStandards[[i]]
        ppm1M <- iMetabolite[, 1]
        ppm2M <- iMetabolite[, 2]
        nbPeakMetabolite <- length(ppm1M)
        MetaboliteName <- names(BdDStandards[i])

        ## Initialisation
        k <- 0
        presenceScore <- 0
        annotatedPpmRef <- data.frame()
        annotatedPpmList <- data.frame()
        annotatedPeakLength <- 0
        metabolites <- data.frame()
        metabolitesList <- data.frame()

        ## Boucle sur les couples de pics de la matrice a annoter
        for (p in seq_len(PeakListLength)) {
            ppmAnnotationF1 <- as.numeric(matriceComplexe[p, 3])
            ppmAnnotationF2 <- as.numeric(matriceComplexe[p, 2])
            e <- simpleMessage("end of file")
            tryCatch(
                {
                    if (!is.na(ppmAnnotationF1)) {
                        matrixAnnotation <- unique.data.frame(rbind.data.frame(matrixAnnotation, matriceComplexe[p, ]))
                    }
                    # Recherche du couple de pics de la matrice la liste des couples du metabolite standard
                    metaboliteIn <- (ppm1M >= (ppmAnnotationF2 - ppm1Tol) & ppm1M <= (ppmAnnotationF2 + ppm1Tol) &
                        ppm2M >= (ppmAnnotationF1 - ppm2Tol) & ppm2M <= (ppmAnnotationF1 + ppm2Tol))
                    WhichMetaboliteIn <- which(metaboliteIn)
                    # Si au moins un couple de la matrice a annoter dans liste couples metabolite standard
                    if (length(WhichMetaboliteIn) > 0) {
                        for (a in seq_len(length(WhichMetaboliteIn))) {
                            annotatedPpmList <- data.frame(ppm1 = ppm1M[WhichMetaboliteIn[a]], ppm2 = ppm2M[WhichMetaboliteIn[a]], theoricalLength = nbPeakMetabolite)
                            annotatedPpmRef <- rbind(annotatedPpmRef, annotatedPpmList)
                        }
                    }
                },
                error = function(e) {
                    cat("End of file \n")
                }
            )
        }

        # Au - 1 couple de ppm de la matrice complexe annote
        if (nrow(annotatedPpmRef) >= 1) {
            ## Nombre couples annotes
            annotatedPeakLength <- nrow(annotatedPpmRef)

            ## Recherche doublons
            annotatedDoublons <- duplicated(annotatedPpmRef)
            if (sum(duplicated(annotatedPpmRef)) > 0) {
                annotatedPeakLength <- nrow(annotatedPpmRef) - sum(duplicated(annotatedPpmRef))
                annotatedPpmRef <- annotatedPpmRef[-duplicated(annotatedPpmRef), ]
            }
            presenceScore <- round(annotatedPeakLength / nbPeakMetabolite, 2)
        }

        ## Conservation metabolites dont score > seuil
        if (presenceScore > seuil_score) {
            metabolites <- data.frame(Metabolite = MetaboliteName, score = presenceScore)
            metabolitesList <- cbind.data.frame(annotatedPpmRef, metabolites)
            allMetabolitesList <- rbind.data.frame(allMetabolitesList, metabolitesList)
        }
    }

    # Initialisation
    commonPpm <- data.frame()
    commonPpmList <- data.frame()
    metaboliteAdd <- data.frame()
    metaboliteAddList <- data.frame()
    commonMetabolitesList <- data.frame()
    commonMetabolitesPpmList <- data.frame()
    commonMetabolitesPpmAllList1 <- data.frame()
    commonMetabolitesPpmAllList <- data.frame()
    listeTotale_2D_unicite <- allMetabolitesList[, 1:4]
    allMetabolitesList <- allMetabolitesList[, -3]
    metabolitesAllUnicite <- data.frame()

    ## Boucle sur tous couples annotes
    for (j in seq_len(length(allMetabolitesList$ppm1))) {
        ## Boucle sur metabolites dans BdD composes standards
        for (i in seq_len(nbMetabolitesBdD)) {
            ppmMetaboliteBdD <- BdDStandards[[i]]
            ppm1M <- ppmMetaboliteBdD[, 1]
            ppm2M <- ppmMetaboliteBdD[, 2]
            # Nombre de couples metabolite
            nbPeakMetabolite <- length(ppm1M)
            MetaboliteName <- names(BdDStandards[i])

            metabolitesInAll <- (ppm1M >= (allMetabolitesList[j, 1] - ppm1Tol) & ppm1M <= (allMetabolitesList[j, 1] + ppm1Tol) &
                ppm2M >= (allMetabolitesList[j, 2] - ppm2Tol) & ppm2M <= (allMetabolitesList[j, 2] + ppm2Tol))
            WhichMetabolitesInAll <- which(metabolitesInAll)

            if (MetaboliteName != allMetabolitesList[j, 3] & length(WhichMetabolitesInAll) > 0) {
                metabolitesAllUnicite <- rbind.data.frame(metabolitesAllUnicite, listeTotale_2D_unicite[j, ])
                commonPpm <- data.frame(ppm1 = allMetabolitesList[j, 1], ppm2 = allMetabolitesList[j, 2])
                commonPpmList <- rbind.data.frame(commonPpmList, commonPpm)
                commonPpmList <- unique(commonPpmList)
                metaboliteAdd <- data.frame(nom_metabolite = MetaboliteName)
                metaboliteAddList <- rbind.data.frame(metaboliteAddList, metaboliteAdd)
                commonMetabolitesList <- rbind.data.frame(data.frame(nom_metabolite = allMetabolitesList[j, 3]), metaboliteAddList)
                commonMetabolitesPpmList <- cbind.data.frame(commonPpm, commonMetabolitesList)
                commonMetabolitesPpmAllList1 <- rbind.data.frame(commonMetabolitesPpmAllList1, commonMetabolitesPpmList)
                commonMetabolitesPpmAllList1 <- unique.data.frame(commonMetabolitesPpmAllList1)
            }
        }
        commonMetabolitesPpmAllList <- rbind.data.frame(commonMetabolitesPpmAllList, commonMetabolitesPpmAllList1)
        commonMetabolitesPpmAllList <- unique.data.frame(commonMetabolitesPpmAllList)

        # initialisation des data.frame
        commonPpm <- data.frame()
        metaboliteAdd <- data.frame()
        metaboliteAddList <- data.frame()
        metabolite_ref <- data.frame()
        commonMetabolitesList <- data.frame()
        commonMetabolitesPpmList <- data.frame()
        commonMetabolitesPpmAllList1 <- data.frame()
    }

    unicityAllList <- listeTotale_2D_unicite
    if (nrow(listeTotale_2D_unicite) != 0 & nrow(metabolitesAllUnicite) != 0) {
        unicityAllList <- setdiff(listeTotale_2D_unicite, metabolitesAllUnicite)
    }

    unicitynbCouplesRectif <- data.frame()
    for (g in seq_len(nrow(unicityAllList))) {
        metaboliteUnicity <- (unicityAllList$Metabolite == unicityAllList$Metabolite[g])
        WhichMetaboliteUnicity <- which(metaboliteUnicity)
        nb_occurence <- length(WhichMetaboliteUnicity)
        unicitynbCouplesRectif <- rbind.data.frame(unicitynbCouplesRectif, nb_occurence)
    }
    names(unicitynbCouplesRectif) <- "NbCouplesAnnotes"
    unicityAllList <- cbind.data.frame(unicityAllList, unicitynbCouplesRectif)

    unicityAllList <- cbind.data.frame(unicityAllList, score_unicite = unicityAllList$NbCouplesAnnotes / unicityAllList$theoricalLength)
    unicityAllList <- unicityAllList[, -3]
    unicityAllList <- unicityAllList[, -4]

    unicityAllList <- unicityAllList[unicityAllList$score_unicite > seuil_score, ]

    listeTotale_metabo <- data.frame()
    if (nrow(commonPpmList) != 0) {
        for (o in seq_len(length(commonPpmList[, 1]))) {
            tf6 <- (commonMetabolitesPpmAllList$ppm1 == commonPpmList[o, 1] & commonMetabolitesPpmAllList$ppm2 == commonPpmList[o, 2])
            w6 <- which(tf6)

            for (s in seq_len(length(w6))) {
                metaboliteAdd <- data.frame(nom_metabolite = commonMetabolitesPpmAllList[w6[s], 3])
                commonMetabolitesList <- paste(commonMetabolitesList, metaboliteAdd[1, ], sep = " ")
            }
            liste_metabo_ppm <- cbind.data.frame(ppm1 = commonPpmList[o, 1], ppm2 = commonPpmList[o, 2], commonMetabolitesList)
            listeTotale_metabo <- rbind.data.frame(listeTotale_metabo, liste_metabo_ppm)
            commonMetabolitesList <- data.frame()
        }
    }

    # Representation graphique
    if (nom_sequence == "HSQC" | nom_sequence == "HMBC") {
        atome <- "13C"
        indice_positif <- 1
        indice_negatif <- -10
    } else {
        atome <- "1H"
        indice_positif <- 0.5
        indice_negatif <- -0.5
    }

    matriceComplexe <- matrixAnnotation
    ppm1 <- as.numeric(matriceComplexe[, 2])
    ppm2 <- as.numeric(matriceComplexe[, 3])

    if (unicite == "NO") {
        listeTotale_2D_a_utiliser <- allMetabolitesList
        d1.ppm <- allMetabolitesList$ppm1
        d2.ppm <- allMetabolitesList$ppm2
    } else {
        listeTotale_2D_a_utiliser <- unicityAllList
        d1.ppm <- listeTotale_2D_a_utiliser$ppm1
        d2.ppm <- listeTotale_2D_a_utiliser$ppm2
    }

    if (nrow(listeTotale_2D_a_utiliser) > 0) {
        ## Taches de correlations
        # Matrice biologique + Annotations
        maxX <- max(round(max(as.numeric(matriceComplexe[, 2]))) + 0.5, round(max(as.numeric(matriceComplexe[, 2]))))
        maxY <- max(round(max(as.numeric(matriceComplexe[, 3]))) + indice_positif, round(max(as.numeric(matriceComplexe[, 3]))))
        probability.score <- as.factor(round(listeTotale_2D_a_utiliser[, 4], 2))
        lgr <- length(unique(probability.score))
        sp <- ggplot(matriceComplexe, aes(x = ppm1, y = ppm2))
        sp <- sp + geom_point(size = 2) + scale_x_reverse(breaks = seq(maxX, 0, -0.5)) +
            scale_y_reverse(breaks = seq(maxY, 0, indice_negatif)) +
            xlab("1H chemical shift (ppm)") + ylab(paste(atome, " chemical shift (ppm)")) + ggtitle(nom_sequence) +
            geom_text(
                data = listeTotale_2D_a_utiliser, aes(d1.ppm, d2.ppm, label = str_to_lower(substr(listeTotale_2D_a_utiliser[, 3], 1, 3)), col = probability.score),
                size = 4, hjust = 0, nudge_x = 0.02, vjust = 0, nudge_y = 0.2
            ) + scale_colour_manual(values = viridis(lgr))
        print(sp)
    }

    # Liste des resultats (couples pmm / metabolite / score) + liste ppms metabolites communs
    if (unicite == "NO") {
        return(list(liste_resultat = allMetabolitesList, listing_ppm_commun = listeTotale_metabo))
    } else {
        return(list(liste_resultat_unicite = unicityAllList, listing_ppm_commun_affichage = listeTotale_metabo))
    }
}