dev/AQSysFormulas2.R

In Hutchr/LLSR: Data Analysis of Liquid-Liquid Systems using R

options(digits = 14)
####################################################################################################################
#' @import rootSolve minpack.lm
#
mrchk <- function(XYdt, P1 = 10, P2 = 1, P3 = 0, ...) {
    # Output initialization
    FFn <- NULL
    # define header
    names(XYdt) <- c("XC", "YC")
    # define nonlinear system and solve it
    FFn <- tryCatch({
      nls(
        YC ~ P1 * exp(P2 * (XC ^ (0.5)) - P3 * (XC ^ 3)),
        start = list(P1 = P1, P2 = P2, P3 = P3),
        data = XYdt,
        na.action = na.exclude
      )
    },
    error = function(e) {
      return(NULL)
    })
    # return output from anaysis
    FFn
  }

mrgsn <- function(XYdt, ...) {
  # Output initialization
  FFn <- NULL
  # define header
  names(XYdt) <- c("XC", "YC")
  ##  controll<-nls.control(maxiter=50,
  ##  tol=1e-10, minFactor = 1/1024,
  ##  printEval = FALSE, warnOnly = FALSE)
  # define nonlinear system and solve it
  FFn <- tryCatch({
    nls(
      YC ~ P1 + P2 * (XC) ^ 0.5 + P3 * XC,
      start = list(P1 = 50, P2 = 1, P3 = 0),
      data = XYdt,
      na.exclude
    )
  },
  error = function(e) {
    return(NULL)
  })
  # return output from anaysis
  FFn
}

tello <- function(XYdt, ...) {
  # tello's method is highly dependent of guess values to obtain its parameters
  # so the method for calculating a more approximated guess value is described in
  # his article and implemented below
  #
  # Output initialization
  FFn <- NULL
  # calculate derivative of data
  tryCatch({
  df.sys <- diff(XYdt[, 1]) / diff(XYdt[, 2])
  nrow.sys <- nrow(XYdt)
  S <- smooth.spline(df.sys)$fit$coef[1:nrow.sys]
  XC <- XYdt[, 1]
  # merge data in a dataframe
  coef.est <- LLSRxy(XC, S)
  # define header
  names(coef.est) <- c("XC", "S")
  # define header
  names(XYdt) <- c("XC", "YC")
  # define nonlinear system and solve it using estimated parameters as guess
  FFn <- nlsLM(
    XC ~ exp((YC - P3) / P1) - P2,
    #YC ~ P1*log(XC + P2) + P3,
    start = list(P1 = -100, P2 = 10, P3 = 0),
    data = XYdt,
    na.action = na.exclude,
    control = nls.lm.control(maxiter = 25)
  )
  # return output from anaysis
  },
  error = function(e) {
    return(NULL)
  })
  # return output from anaysis
  FFn
}

tang <- function(XYdt, P1 = 10, P2 = 0, P3 = 0, P4 = 0, ...) {
    # Output initialization
    FFn <- NULL
    # define header
    names(XYdt) <- c("XC", "YC")
    # define nonlinear system and solve it
    FFn <- tryCatch({
      nls(
        YC ~ exp(P1 + P2 * (XC ^ (0.5)) + P3 * XC + P4 * (XC ^ 2)),
        start = list(
          P1 = P1,
          P2 = P2,
          P3 = P3,
          P4 = P4
        ),
        data = XYdt,
        na.action = na.exclude
      )
    },
    error = function(e) {
      return(NULL)
    })
    # return output from anaysis
    FFn
  }