#' Logistic function
#'
#' Implementation of the logistic function
#'
#' @param x value to apply the function to.
#' @param x0 midpoint parameter. Gives the centre of the function.
#' @param k shape parameter. Gives the slope of the function.
#'
#' @return Value of logistic funciton with given parameters
logistic <- function(x, x0, k) {
    1 / (1 + exp(-k * (x - x0)))
}

#' Bind rows (matched)
#'
#' Bind the rows of two data frames, keeping only the columns that are common
#' to both.
#'
#' @param df1 first data.frame to bind.
#' @param df2 second data.frame to bind.
#'
#' @return data.frame containing rows from \code{df1} and \code{df2} but only
#'         common columns.
rbindMatched <- function(df1, df2) {
    common.names <- intersect(colnames(df1), colnames(df2))
    combined <- rbind(df1[, common.names], df2[, common.names])

    return(combined)
}

#' Winsorize vector
#'
#' Set outliers in a numeric vector to a specified percentile.
#'
#' @param x Numeric vector to winsorize
#' @param q Percentile to set from each end
#'
#' @return Winsorized numeric vector
winsorize <- function(x, q) {

    checkmate::check_numeric(x, any.missing = FALSE)
    checkmate::check_number(q, lower = 0, upper = 1)

    lohi <- stats::quantile(x, c(q, 1 - q), na.rm = TRUE)

    if (diff(lohi) < 0) { lohi <- rev(lohi) }

    x[!is.na(x) & x < lohi[1]] <- lohi[1]
    x[!is.na(x) & x > lohi[2]] <- lohi[2]

    return(x)
}