R/ma24.35.R

In jlthomps/EflowStats: Returns HIT/HAT Hydrologic Indicator stats for a given set of data

#' Function to return the MA24-35 hydrologic indicator statistics for a given data frame
#' 
#' This function accepts a data frame that contains columns named "discharge", "year_val" and "month_val" and 
#' calculates the variability (coefficient of variation) of monthly flow values. compute the standard deviation for each month in each 
#' year over the entire flow record. Divide the standard deviation by the mean for each month. Average (or median - use preference option) these values for 
#' each month across all years (percent - temporal). 
#' 
#' @param qfiletempf data frame containing a "discharge" column containing daily flow values
#' @param pref string containing a "mean" or "median" preference
#' @return ma234.35 data frame containing the MA24-MA35 statistics for the given data frame
#' @export
#' @examples
#' qfiletempf<-sampleData
#' ma24.35(qfiletempf)
ma24.35 <- function(qfiletempf, pref = "mean") {
  sdmonbyyr <- aggregate(qfiletempf$discharge, list(qfiletempf$year_val, 
                                                    qfiletempf$month_val), FUN = sd, na.rm=TRUE)
  colnames(sdmonbyyr) <- c("Year", "Month", "sdq")
  meanmonbyyr <- aggregate(qfiletempf$discharge, list(qfiletempf$year_val, 
                                                      qfiletempf$month_val), FUN = mean, na.rm=TRUE)
  colnames(meanmonbyyr) <- c("Year", "Month", "meanq")
  dfcvmonbyyr <- data.frame(meanmonbyyr$Year, meanmonbyyr$Month, 
                            sdmonbyyr$sdq, meanmonbyyr$meanq)
  colnames(dfcvmonbyyr) <- c("Year", "Month", "sdq", 
                             "meanq")
  cvmonbyyr <- dfcvmonbyyr$sdq/dfcvmonbyyr$meanq
  dfcvmonbyyrf <- data.frame(dfcvmonbyyr, cvmonbyyr)
  colnames(dfcvmonbyyrf) <- c("Year", "Month", "sdq", 
                              "meanq", "cvq")
  if (pref == "median") {
    medmoncv <- aggregate(dfcvmonbyyrf$cvq, list(dfcvmonbyyrf$Month), 
                          median, na.rm=TRUE)
    ma24.35 <- data.frame(medmoncv[2] * 100)
  }
  else {
    meanmoncv <- aggregate(dfcvmonbyyrf$cvq, list(dfcvmonbyyrf$Month), 
                           mean, na.rm=TRUE)
    ma24.35 <- data.frame(meanmoncv[2] * 100)
  }
  return(ma24.35)
}