useDynLib(arules)

importFrom("stats", "predict")  ## otherwise predict in stats does not work
importFrom("Matrix", "summary") ## we need the generic 
importFrom("Matrix", "t")       ## we add/replace some methods for ngCMatrix 

export(
        "read.transactions", 
        "random.transactions", 
        "random.patterns",
        "apriori", 
        "eclat"
      )

exportClasses(
        "itemMatrix", "summary.itemMatrix",
        "transactions", "summary.transactions",
        "tidLists", "summary.tidLists", 
        "associations", "summary.associations",
        "itemsets", "summary.itemsets",
        "rules", "summary.rules",
        "ASparameter", "AScontrol",
        "APparameter", "APcontrol", "APappearance",
        "ECparameter", "ECcontrol",
        "ar_similarity", "ar_cross_dissimilarity", "dist"
        )

exportMethods(
        "%in%",
        "%ain%",
        "%pin%",
        "LIST",
        "SORT",
        "WRITE",
        "[",
        "coverage",
        "crossTable",
        "c", 
        "coerce",           ### for setAs
        "decode", 
        "dim", 
        "duplicated",
        "encode",
        "generatingItemsets",
        "image", 
        "initialize", 
        "inspect", 
        "intersect", 
        "itemInfo", "itemInfo<-", 
        "itemsetInfo", "itemsetInfo<-", 
        "items", "items<-",
        "itemLabels", "itemLabels<-", 
        "itemFrequency", 
        "itemFrequencyPlot",
        "is.closed",
        "is.element",
        "is.maximal",
        "is.subset",
        "is.superset",
        "labels", 
        "length", 
        "lhs", "lhs<-",
        "match",
        "interestMeasure",
        "nitems",
        "quality", "quality<-",
        "recode",
        "rhs", "rhs<-", 
        "ruleInduction",
        "sample",
        "setdiff",
        "setequal",
        "show", 
        "size",
        "sort",
        "subset", 
        "summary", 
        "support", 
        "t", 
        "tidLists", 
        "transactionInfo", "transactionInfo<-",
        "union",
        "unique",
        "affinity", 
        "predict",
        "dissimilarity"
        )
