R/nfunctions.R

In koheiw/quanteda.core: Quantitative Analysis of Textual Data

#' Count the number of documents or features
#'
#' Get the number of documents or features in an object.
#' @details `ndoc` returns the number of documents in an object
#'   whose texts are organized as "documents" (a [corpus],
#'   [dfm], or [tokens] object, a readtext object from the
#'   \pkg{readtext} package).
#'
#' @param x a \pkg{quanteda} object: a [corpus], [dfm], or
#'   [tokens] object, or a readtext object from the \pkg{readtext} package.
#' @return an integer (count) of the number of documents or features
#' @export
#' @examples
#' # number of documents
#' ndoc(data_corpus_inaugural)
#' ndoc(corpus_subset(data_corpus_inaugural, Year > 1980))
#' ndoc(tokens(data_corpus_inaugural))
#' ndoc(dfm(corpus_subset(data_corpus_inaugural, Year > 1980)))
#'
ndoc <- function(x) {
    UseMethod("ndoc")
}

#' @export
ndoc.default <- function(x) {
    stop(friendly_class_undefined_message(class(x), "ndoc"))
}

#' @export
ndoc.corpus <- function(x) {
    length(as.corpus(x))
}

#' @export
ndoc.dfm <- function(x) {
    nrow(as.dfm(x))
}

#' @export
ndoc.tokens <- function(x) {
    length(as.tokens(x))
}


#' @rdname ndoc
#' @details `nfeat` returns the number of features from a dfm; it is an
#'   alias for `ntype` when applied to dfm objects.  This function is only
#'   defined for [dfm] objects because only these have "features".  (To count
#'   tokens, see [ntoken()].)
#' @export
#' @seealso [ntoken()]
#' @examples
#' # number of features
#' nfeat(dfm(corpus_subset(data_corpus_inaugural, Year > 1980), remove_punct = FALSE))
#' nfeat(dfm(corpus_subset(data_corpus_inaugural, Year > 1980), remove_punct = TRUE))
nfeat <- function(x) {
    UseMethod("nfeat")
}

#' @export
nfeat.default <- function(x) {
    stop(friendly_class_undefined_message(class(x), "nfeat"))
}

#' @export
nfeat.dfm <- function(x) {
    x <- as.dfm(x)
    ncol(x)
}

#' Count the number of tokens or types
#'
#' Get the count of tokens (total features) or types (unique tokens).
#' @param x a \pkg{quanteda} object: a character, [corpus],
#'   [tokens], or [dfm] object
#' @param ... additional arguments passed to [tokens()]
#' @note Due to differences between raw text tokens and features that have been
#'   defined for a [dfm], the counts may be different for dfm objects and the
#'   texts from which the dfm was generated.  Because the method tokenizes the
#'   text in order to count the tokens, your results will depend on the options
#'   passed through to [tokens()].
#' @return named integer vector of the counts of the total tokens or types
#' @details
#' The precise definition of "tokens" for objects not yet tokenized (e.g.
#' [character] or [corpus] objects) can be controlled through optional
#' arguments passed to [tokens()] through `...`.
#' @examples
#' # simple example
#' txt <- c(text1 = "This is a sentence, this.", text2 = "A word. Repeated repeated.")
#' ntoken(txt)
#' ntype(txt)
#' ntoken(char_tolower(txt))  # same
#' ntype(char_tolower(txt))   # fewer types
#' ntoken(char_tolower(txt), remove_punct = TRUE)
#' ntype(char_tolower(txt), remove_punct = TRUE)
#'
#' # with some real texts
#' ntoken(corpus_subset(data_corpus_inaugural, Year < 1806), remove_punct = TRUE)
#' ntype(corpus_subset(data_corpus_inaugural, Year < 1806), remove_punct = TRUE)
#' ntoken(dfm(corpus_subset(data_corpus_inaugural, Year < 1800)))
#' ntype(dfm(corpus_subset(data_corpus_inaugural, Year < 1800)))
#' @export
ntoken <- function(x, ...) {
    UseMethod("ntoken")
}

#' @export
ntoken.default <- function(x, ...) {
    stop(friendly_class_undefined_message(class(x), "ntoken"))
}

#' @rdname ntoken
#' @details
#' For [dfm] objects, `ntype` will only return the count of features
#' that occur more than zero times in the dfm.
#' @export
ntype <- function(x, ...) {
    UseMethod("ntype")
}

#' @export
ntype.default <- function(x, ...) {
    stop(friendly_class_undefined_message(class(x), "ntype"))
}

#' @export
ntoken.corpus <- function(x, ...) {
    x <- as.corpus(x)
    ntoken(texts(x), ...)
}

#' @export
ntoken.character <- function(x, ...) {
    ntoken(tokens(x, ...))
}

#' @export
ntoken.tokens <- function(x, ...) {
    if (length(list(...))) {
        lengths(tokens(x, ...))
    } else {
        lengths(x)
    }
}

#' @export
ntoken.dfm <- function(x, ...) {
    x <- as.dfm(x)
    unused_dots(...)
    result <- as.integer(rowSums(x))
    names(result) <- docnames(x)
    result
}

#' @export
ntype.character <- function(x, ...) {
    if (length(list(...)))
        ntype(tokens(x, ...))
    else
        ntype(tokens(x))
}

#' @export
ntype.corpus <- function(x, ...) {
    x <- as.corpus(x)
    ntype(texts(x), ...)
}

#' @export
ntype.dfm <- function(x, ...) {
    unused_dots(...)
    x <- as.dfm(x)
    # only returns total non-zero features
    result <- as.integer(rowSums(x > 0))
    names(result) <- docnames(x)
    result
}

#' @export
ntype.tokens <- function(x, ...) {
    if (length(list(...)))
        x <- tokens(x, ...)
    vapply(unclass(x), function(y) length(unique(y[y > 0])), integer(1))
}

#' Count the number of sentences
#'
#' Return the count of sentences in a corpus or character object.
#' @param x a character or [corpus] whose sentences will be counted
#' @note `nsentence()` relies on the boundaries definitions in the \pkg{stringi}
#'   package (see [stri_opts_brkiter][stringi::stri_opts_brkiter]).  It does not
#'   count sentences correctly if the text has been transformed to lower case,
#'   and for this reason `nsentence()` will issue a warning if it detects all
#'   lower-cased text.
#' @return count(s) of the total sentences per text
#' @examples
#' # simple example
#' txt <- c(text1 = "This is a sentence: second part of first sentence.",
#'          text2 = "A word. Repeated repeated.",
#'          text3 = "Mr. Jones has a PhD from the LSE.  Second sentence.")
#' nsentence(txt)
#' @export
nsentence <- function(x) {
    UseMethod("nsentence")
}

#' @export
nsentence.default <- function(x) {
    stop(friendly_class_undefined_message(class(x), "nsentence"))
}

#' @export
#' @importFrom stringi stri_detect_charclass
nsentence.character <- function(x) {
    upcase <- try(any(stri_detect_charclass(x, "[A-Z]")), silent = TRUE)
    if (!is.logical(upcase)) {
        # warning("Input text contains non-UTF-8 characters.")
    } else if (!upcase)
        warning("nsentence() does not correctly count sentences in all lower-cased text")
    ntoken(tokens(x, what = "sentence"))
}

#' @export
nsentence.corpus <- function(x) {
    x <- as.corpus(x)
    nsentence(texts(x))
}

#' @export
nsentence.tokens <- function(x) {
    x <- as.tokens(x)
    attrs <- attributes(x)
    if (field_object(attrs, "what") != "sentence")
        stop("nsentence on a tokens object only works if what = \"sentence\"")
    return(lengths(x))
}