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man/complexity.Rd has changed.
DESCRIPTION has changed.

@@ -11,6 +11,9 @@
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#' @param features A list of features names or \code{"all"} to include all them.
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#'  The supported values are described in the details section. (Default: 
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#'  \code{"all"})
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#' @param summary A list of summarization functions or empty for all values. See
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#'  \link{post.processing} method to more information. (Default: 
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#'  \code{c("mean", "sd")})
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#' @param formula A formula to define the class column.
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#' @param data A data.frame dataset contained the input attributes and class
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#' @param ... Not used.
@@ -75,7 +78,8 @@
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#' @rdname complexity
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#' @export
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complexity.default <- function(x, y, features="all", ...) {
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complexity.default <- function(x, y, features="all", 
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                               summary=c("mean", "sd"), ...) {
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  if(!is.data.frame(x)) {
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    stop("data argument must be a data.frame")
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  }
@@ -98,27 +102,31 @@
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  }
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  if (any(features %in% ls.complexity.groups("class"))) {
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    features <- unique(c(features, unlist(sapply(features, ls.complexity.groups))))
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    features <- unique(c(features, unlist(sapply(features, 
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                                                 ls.complexity.groups))))
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  }
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  features <- match.arg(features, ls.complexity(), TRUE)
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  colnames(x) <- make.names(colnames(x), unique=TRUE)
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  groups <- names(which(sapply(ls.complexity.groups("class"), 
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                 function(x) any(features %in% ls.complexity.groups(x)))))
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  groups <- gsub("linearity", "linearity.class", groups)
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  unlist(
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    lapply(groups, function(group) {
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      fmethod <- get(group, asNamespace("ECoL"))
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      measures <- intersect(features, ls.complexity.groups(group))
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      do.call(fmethod, list(x=x, y=y, measures=measures, summary="return", ...))
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    })
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  )[features]
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  do.call(c, lapply(groups, function(group) {
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    fmethod <- get(group, asNamespace("ECoL"))
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    measures <- intersect(features, ls.complexity.groups(group))
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    subgroups <- do.call(fmethod, list(x=x, y=y, measures=measures, 
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                                       summary="return", ...))
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    sapply(names(subgroups), function(measure){
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      post.processing(subgroups[[measure]], summary, 
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                      measure %in% ls.complexity.multiples(), ...)
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    }, simplify = FALSE)
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  }))[features]
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}
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#' @rdname complexity
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#' @export
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complexity.formula <- function(formula, data, features="all", ...) {
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complexity.formula <- function(formula, data, features="all", 
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                               summary=c("mean", "sd"), ...) {
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  if(!inherits(formula, "formula")) {
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    stop("method is only for formula datas")
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  }
@@ -130,7 +138,7 @@
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  modFrame <- stats::model.frame(formula, data)
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  attr(modFrame, "terms") <- NULL
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  complexity.default(modFrame[-1], modFrame[1], features, ...)
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  complexity.default(modFrame[-1], modFrame[1], features, summary, ...)
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}
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#' List the complexity meta-features
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}
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ls.complexity.multiples <- function() {
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  c()
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  c(c("F1", "F1v", "F2", "F3", "F4"), #overlapping
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    c("N2", "N3", "N4", "T1"), #neighborhood
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    c("L1", "L2", "L3"), #linearity
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    c(), #dimensionality
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    c(), #balance
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    c("Hubs") #network
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  )
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}
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ls.complexity.groups <- function(type) {
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  switch(type,
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         class = {
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           c("overlapping", "neighborhood", 
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             "linearity", "dimensionality",
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           c("overlapping", "neighborhood", "linearity", "dimensionality",
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             "balance", "network")
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         }, regr = {
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           c("correlation", "linearity", 
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         linearity = {
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           c("L1", "L2", "L3")
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         },
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         linearity.class = {
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           c("L1", "L2", "L3")
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         },
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         dimensionality = {
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           c("T2", "T3", "T4")
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         },
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