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#' Function to combine water-quality sample data and continuous (daily)
#' ancillary variables and drop unnecessary columns.
#'
#' @name combineData
#' @title Combine water-quality sample data and continuous ancillary
#' variables
#' @param qwdat is the dataset containing water-quality sample data with
#' columns that begin with a P (or other user-defined indicator) followed
#' by alphanumeric characters. These columns are concentration data. In
#' addition there need to be columns that begin with an R (or other user-
#' defined indicator) followed by alphanumeric characters that match those
#' of the associated concentration data. The R columns contain data
#' qualification codes. See example datasets for more information about
#' the data format, \link{IllRivValleyCty} and \link{qwMoRivOmaha}. This
#' package assumes that the data are in micrograms per liter.
#' @param qwcols is a character vector with column headings for
#' a station (location) identifier, a dates column identifier, beginning
#' of column headers for remarks code (default is R), and beginning of
#' column headers for concentration data (default is P for parameter).
#' @param cqwdat is the dataset containing variables that can be used as
#' explanatory variables for the seawaveQ model. See example dataset
#' for more information about the data format \link{cqwMoRivOmaha}. These
#' are daily values with no missing values allowed between the first and
#' the last date in the dataset.
#' @return A data frame
#' @format A data frame with the number of rows equal to the number of rows
#' in the data frame indicated by qwdat. The number of columns depend
#' on the two input data frames. Minimally there will be a station
#' identification column, a dates column, a column of qualification codes,
#' and a column of water-quality data.
#' @note The columns indicated by qwcols[1:2] are used to
#' combine the datasets. The first column is the station identifier and
#' the second column is the date column. These two column headings must
#' be the same in the two datasets being combined and the dates in the
#' datasets being combined must be of class Date and use the same
#' format.
#' @keywords manip
#' @author Karen R. Ryberg and Aldo V. Vecchia
#' @export
#' @examples
#' data(swData)
#' MoRivOmaha <- combineData(qwdat = qwMoRivOmaha, cqwdat = cqwMoRivOmaha,
#' qwcols = c("staid", "dates", "R", "P"))
combineData <- function(qwdat, cqwdat,
qwcols = c("staid", "dates", "R", "P")) {
# combine concentration data with continous data and anomalies
pattern <- paste("(", qwcols[1], ")|(", qwcols[2], ")|(", qwcols[3], "|",
qwcols[4], ")[[:alnum:]]+", sep="")
mycols <- grep(pattern, dimnames(qwdat)[[2]])
# drop extract columns
qwdat <- qwdat[, mycols]
dat <- merge(qwdat, cqwdat, by.x = qwcols[1:2], by.y = qwcols[1:2],
all.x = TRUE )
row.names(dat) <- NULL
dat
}
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