R/hydroStats.R
In CentreForHydrology/MESHr: pre- and post processing for MESH
Defines functions
hydroStats
Documented in
hydroStats
#' Calculates Goodness of Fit statistics for MESH output
#'
#' @description This function is a wrapper for the function \code{gof} in the package \pkg{hydroGOF}.
#' It computes several Goodness of Fit statistics for each station. The output of this function may be
#' used on its own, or to annotate a hydrograph.
#'
#' @param MESHvals Required. A data frame of output from a MESH run, as produced by \code{readOutputTimeseriesCSV}.
#' @param stationNames Optional. A vector of strings holding station names. If specified, the station names will
#' be used in the returned data frame, otherwise the MESH station numbers will be used.
#' @param calStart Optional. The start date of the calibration period. Must be a string in the format \option{yyyy-mm-dd}. If specified, values on and after this date will be designated as the \code{Calibration} period. The remaining values will be designated as the \code{Validation} period.
#' @param calEnd Optional. The start date of the calibration period. Must be a string in the format \option{yyyy-mm-dd}. If specified, values on and after this date will be designated as the \code{Calibration} period. The remaining values will be designated as the \code{Validation} period.
#' @param removeMissing Required. Should rows with missing values be removed before statistics are calculted? Default is \code{TRUE}
#' @param digits Optional. The number of decimal places for rounding goodness of fit statistics. If \code{0} the default, then it is not set. Default value is \code{2}. Note that percentages like NRMSE and PBIAS will only use a maximum of one decimal place.
#' @param doSpearman Optional. Should Spearman correlation be computed? Default is \code{FALSE}.
#' @param doPBFDC Optional. Should percent bias of slope of the midsegment of the FDC be computed? Default is \code{FALSE}.
#' @param doLogNSE Optional. Should the NSE of the log-transformed flows be calculated?
#' Default is \code{TRUE}.
#' @param epsilon Optional. Value to be added to flows when calculating LogNSE, to prevent
#' calculating the log of zero. The default is \option{Pushpalatha2012}, which is
#' 1 percent of the mean observed values. A number may aslo be specified.
#' @param j Optional. Argument passed to the \code{mNSE} function in \pkg{hydroGOF}.
#' @param norm Optional. Argument passed to the \code{nrmse} function in \pkg{hydroGOF}.
#' @param s Optional. Argument passed to the \code{KGE} function in \pkg{hydroGOF}.
#' @param method Optional. Argument passed to the \code{KGE} function in \pkg{hydroGOF}.
#' @param lQ.thr Optional. Argument passed to the \code{pbiassfdc} function in \pkg{hydroGOF}.
#' @param hQ.thr Optional. Argument passed to the \code{pbiassfdc} function in \pkg{hydroGOF}.
#'
#' @return Returns a data frame with the following variables:
#' #' \describe{
#' \item{station}{station name or number}
#' \item{me}{Mean Error}
#' \item{mae}{Mean Absolute Error}
#' \item{mse}{Mean Squared Error}
#' \item{rmse}{Root Mean Square Error}
#' \item{nrmse}{Normalized Root Mean Square Error ( -100\% <= nrms <= 100\% )}
#' \item{PBIAS}{Percent Bias }
#' \item{pbiasfdc}{PBIAS in the slope of the midsegment of the Flow Duration Curve, if selected}
#' \item{RSR}{Ratio of RMSE to the Standard Deviation of the Observations, RSR = rms / sd(obs). ( 0 <= RSR <= +Inf )}
#' \item{rSD}{Ratio of Standard Deviations, rSD = sd(sim) / sd(obs)}
#' \item{NSE}{Nash-Sutcliffe Efficiency ( -Inf <= NSE <= 1 )}
#' \item{mNSE}{Modified Nash-Sutcliffe Efficiency}
#' \item{rNSE}{Relative Nash-Sutcliffe Efficiency }
#' \item{d}{Index of Agreement ( 0 <= d <= 1 )}
#' \item{d1}{Modified Index of Agreement}
#' \item{rd}{Relative Index of Agreement}
#' \item{cp}{Persistence Index ( 0 <= PI <= 1 ) }
#' \item{r}{Pearson Correlation coefficient ( -1 <= r <= 1 )}
#' \item{r.Spearman}{Spearman Correlation coefficient ( -1 <= r.Spearman <= 1 ), if selected}
#' \item{R2}{Coefficient of Determination ( 0 <= R2 <= 1 ). \cr
#' Gives the proportion of the variance of one variable that is predictable from the other variable}
#' \item{bR2}{R2 multiplied by the coefficient of the regression line between \code{sim} and \code{obs} \cr ( 0 <= bR2 #' <= 1 )}
#' \item{KGE}{Kling-Gupta efficiency between \code{sim} and \code{obs} \cr ( 0 <= KGE <= 1 )}
#' \item{VE}{Volumetric efficiency between \code{sim} and \code{obs} \cr ( -Inf <= VE <= 1)}
#' \item{LogNSE}{NSE of log-transformed flows, if selected}
#' }
#' If the calibration period is specified, then statistics will be computed separately for the Calibration and Validation periods. The period names and dates will be specified in additional columns.
#' @author Kevin Shook
#' @seealso \code{\link{simpleHydrograph}} \code{\link{gof}}
#' @export
#'
#' @examples
#' stats <- hydroStats(MESH_streamflows)
#' stats$NSE
#' periodStats <- hydroStats(MESH_streamflows, calEnd = "2010-01-01")
#' periodStats[,1:7]
hydroStats <- function(MESHvals, stationNames = "", calStart = "",
calEnd = "", removeMissing = TRUE,
doSpearman = FALSE,
doPBFDC = FALSE,
doLogNSE = TRUE,
epsilon = "Pushpalatha2012",
digits = 2,
j = 1,
norm = "sd", s = c(1, 1, 1),
method = c("2009", "2012"),
lQ.thr = 0.7, hQ.thr = 0.2) {
vars <- names(MESHvals)
if (vars[1] != "DATE" & vars[1] != "DATETIME") {
cat('Error: not a time series date frame\n')
return(FALSE)
}
# check for specified station names
numCols <- ncol(MESHvals) - 1
numStations <- floor(numCols / 2)
if (length(stationNames) >= numStations) {
tempstation <- ""
} else {
tempstation <- 0
}
# check for periods
if (calEnd != "") {
calEndDate <- as.Date(calEnd)
} else {
calEndDate <- as.Date(max(MESHvals[,1]))
}
if (calStart != "") {
calStartDate <- as.Date(calStart)
} else {
calStartDate <- as.Date(min(MESHvals[,1]))
}
# add period
period <- FALSE
if ((calStart != "") | (calEnd != "")) {
period <- TRUE
MESHvals$period <- "Validation"
MESHvals$period[(as.Date(MESHvals[,1]) >= calStartDate) &
(as.Date(MESHvals[,1]) <= calEndDate)] <- "Calibration"
}
if (!period) {
for (i in 1:numStations) {
meas_col <- (i - 1) * 2 + 2
sim_col <- meas_col + 1
meas <- MESHvals[, meas_col]
sim <- MESHvals[, sim_col]
# check meas and sim to make sure that they can be used
if (all(is.na(meas)) | all(is.na(sim)) |
all(meas <= 0, na.rm = TRUE) | all(meas <= 0, na.rm = TRUE)) {
cat("Error: No values to use for calculations\n")
return(FALSE)
} else {
g <- hydroGOF::gof(sim, meas, na.rm = removeMissing,
do.spearman = doSpearman,
do.pbfsc = doPBFDC,
j = j,
norm = norm,
s = s,
method = method,
lQ.thr = lQ.thr,
hQ.thr = hQ.thr,
digits = digits)
g <- as.data.frame(t(g))
# do log NSE if required
if (doLogNSE) {
if (is.numeric(epsilon)) {
if (epsilon > 0) {
epsilon_value <- epsilon
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = "other",
epsilon.value = epsilon_value)
} else {
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = "0")
}
} else {
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = epsilon)
}
g$LogNSE <- l_nse
}
g$station <- tempstation
if (i == 1) {
if (length(stationNames) >= numStations & all(stationNames != "")) {
g$station <- stationNames[i]
} else {
g$station <- i
}
gvals <- g
} else {
if (length(stationNames) >= numStations & all(stationNames != "")) {
g$station <- stationNames[i]
} else {
g$station <- i
}
gvals <- rbind(gvals, g)
}
} # for loop
}
# move station to column 1
cols <- ncol(gvals)
gvals <- gvals[, c(cols, 1:(cols - 1))]
} else {
# subdivide by period
validation <- MESHvals[MESHvals$period == "Validation", ]
calibration <- MESHvals[MESHvals$period == "Calibration", ]
# do calibration first
for (i in 1:numStations) {
meas_col <- (i - 1) * 2 + 2
sim_col <- meas_col + 1
meas <- calibration[, meas_col]
sim <- calibration[, sim_col]
g <- hydroGOF::gof(sim, meas, na.rm = removeMissing,
do.spearman = doSpearman,
do.pbfsc = doPBFDC,
j = j,
norm = norm,
s = s,
method = method,
lQ.thr = lQ.thr,
hQ.thr = hQ.thr,
digits = digits)
g <- as.data.frame(t(g))
if (doLogNSE) {
if (is.numeric(epsilon)) {
if (epsilon > 0) {
epsilon_value <- epsilon
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = "other",
epsilon.value = epsilon_value)
} else {
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = "0")
}
} else {
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = epsilon)
}
g$LogNSE <- l_nse
}
g$station <- tempstation
if (i == 1) {
if (length(stationNames) >= numStations & all(stationNames != "")) {
g$station <- stationNames[i]
} else {
g$station <- i
}
gvals1 <- g
} else {
if (length(stationNames) >= numStations & all(stationNames != "")) {
g$station <- stationNames[i]
} else {
g$station <- i
}
gvals1 <- rbind(gvals1, g)
}
}
# do validation
for (i in 1:numStations) {
meas_col <- (i - 1) * 2 + 2
sim_col <- meas_col + 1
meas <- validation[, meas_col]
sim <- validation[, sim_col]
g <- hydroGOF::gof(sim, meas,
do.spearman = doSpearman,
do.pbfsc = doPBFDC,
j = j,
norm = norm,
s = s,
method = method,
lQ.thr = lQ.thr,
hQ.thr = hQ.thr,
digits = digits)
g <- as.data.frame(t(g))
if (doLogNSE) {
if (is.numeric(epsilon)) {
if (epsilon > 0) {
epsilon_value <- epsilon
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = "other",
epsilon.value = epsilon_value)
} else {
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = "0")
}
} else {
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = epsilon)
}
g$LogNSE <- l_nse
}
g$station <- tempstation
if (i == 1) {
if (length(stationNames) >= numStations & all(stationNames != "")) {
g$station <- stationNames[i]
} else {
g$station <- i
}
gvals2 <- g
} else {
if (length(stationNames) >= numStations & all(stationNames != "")) {
g$station <- stationNames[i]
} else {
g$station <- i
}
gvals2 <- rbind(gvals2, g)
}
}
# add period names and dates
gvals1$period <- "Calibration"
gvals1$start_date <- calStartDate
gvals1$end_date <- calEndDate
gvals2$period <- "Validation"
gvals2$start_date <- min(as.Date(validation[,1]))
gvals2$end_date <- max(as.Date(validation[,1]))
# combine both data sets
gvals <- rbind(gvals1, gvals2)
# move station to column 1
cols <- ncol(gvals)
last_4 <- seq((cols - 3), cols)
gvals <- gvals[, c(last_4 , 1:(cols - 3))]
}
return(gvals)
}
CentreForHydrology/MESHr documentation built on Jan. 11, 2021, 8:34 p.m.
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Defines functions hydroStats
Documented in hydroStats
#' Calculates Goodness of Fit statistics for MESH output
#'
#' @description This function is a wrapper for the function \code{gof} in the package \pkg{hydroGOF}.
#' It computes several Goodness of Fit statistics for each station. The output of this function may be
#' used on its own, or to annotate a hydrograph.
#'
#' @param MESHvals Required. A data frame of output from a MESH run, as produced by \code{readOutputTimeseriesCSV}.
#' @param stationNames Optional. A vector of strings holding station names. If specified, the station names will
#' be used in the returned data frame, otherwise the MESH station numbers will be used.
#' @param calStart Optional. The start date of the calibration period. Must be a string in the format \option{yyyy-mm-dd}. If specified, values on and after this date will be designated as the \code{Calibration} period. The remaining values will be designated as the \code{Validation} period.
#' @param calEnd Optional. The start date of the calibration period. Must be a string in the format \option{yyyy-mm-dd}. If specified, values on and after this date will be designated as the \code{Calibration} period. The remaining values will be designated as the \code{Validation} period.
#' @param removeMissing Required. Should rows with missing values be removed before statistics are calculted? Default is \code{TRUE}
#' @param digits Optional. The number of decimal places for rounding goodness of fit statistics. If \code{0} the default, then it is not set. Default value is \code{2}. Note that percentages like NRMSE and PBIAS will only use a maximum of one decimal place.
#' @param doSpearman Optional. Should Spearman correlation be computed? Default is \code{FALSE}.
#' @param doPBFDC Optional. Should percent bias of slope of the midsegment of the FDC be computed? Default is \code{FALSE}.
#' @param doLogNSE Optional. Should the NSE of the log-transformed flows be calculated?
#' Default is \code{TRUE}.
#' @param epsilon Optional. Value to be added to flows when calculating LogNSE, to prevent
#' calculating the log of zero. The default is \option{Pushpalatha2012}, which is
#' 1 percent of the mean observed values. A number may aslo be specified.
#' @param j Optional. Argument passed to the \code{mNSE} function in \pkg{hydroGOF}.
#' @param norm Optional. Argument passed to the \code{nrmse} function in \pkg{hydroGOF}.
#' @param s Optional. Argument passed to the \code{KGE} function in \pkg{hydroGOF}.
#' @param method Optional. Argument passed to the \code{KGE} function in \pkg{hydroGOF}.
#' @param lQ.thr Optional. Argument passed to the \code{pbiassfdc} function in \pkg{hydroGOF}.
#' @param hQ.thr Optional. Argument passed to the \code{pbiassfdc} function in \pkg{hydroGOF}.
#'
#' @return Returns a data frame with the following variables:
#' #' \describe{
#' \item{station}{station name or number}
#' \item{me}{Mean Error}
#' \item{mae}{Mean Absolute Error}
#' \item{mse}{Mean Squared Error}
#' \item{rmse}{Root Mean Square Error}
#' \item{nrmse}{Normalized Root Mean Square Error ( -100\% <= nrms <= 100\% )}
#' \item{PBIAS}{Percent Bias }
#' \item{pbiasfdc}{PBIAS in the slope of the midsegment of the Flow Duration Curve, if selected}
#' \item{RSR}{Ratio of RMSE to the Standard Deviation of the Observations, RSR = rms / sd(obs). ( 0 <= RSR <= +Inf )}
#' \item{rSD}{Ratio of Standard Deviations, rSD = sd(sim) / sd(obs)}
#' \item{NSE}{Nash-Sutcliffe Efficiency ( -Inf <= NSE <= 1 )}
#' \item{mNSE}{Modified Nash-Sutcliffe Efficiency}
#' \item{rNSE}{Relative Nash-Sutcliffe Efficiency }
#' \item{d}{Index of Agreement ( 0 <= d <= 1 )}
#' \item{d1}{Modified Index of Agreement}
#' \item{rd}{Relative Index of Agreement}
#' \item{cp}{Persistence Index ( 0 <= PI <= 1 ) }
#' \item{r}{Pearson Correlation coefficient ( -1 <= r <= 1 )}
#' \item{r.Spearman}{Spearman Correlation coefficient ( -1 <= r.Spearman <= 1 ), if selected}
#' \item{R2}{Coefficient of Determination ( 0 <= R2 <= 1 ). \cr
#' Gives the proportion of the variance of one variable that is predictable from the other variable}
#' \item{bR2}{R2 multiplied by the coefficient of the regression line between \code{sim} and \code{obs} \cr ( 0 <= bR2 #' <= 1 )}
#' \item{KGE}{Kling-Gupta efficiency between \code{sim} and \code{obs} \cr ( 0 <= KGE <= 1 )}
#' \item{VE}{Volumetric efficiency between \code{sim} and \code{obs} \cr ( -Inf <= VE <= 1)}
#' \item{LogNSE}{NSE of log-transformed flows, if selected}
#' }
#' If the calibration period is specified, then statistics will be computed separately for the Calibration and Validation periods. The period names and dates will be specified in additional columns.
#' @author Kevin Shook
#' @seealso \code{\link{simpleHydrograph}} \code{\link{gof}}
#' @export
#'
#' @examples
#' stats <- hydroStats(MESH_streamflows)
#' stats$NSE
#' periodStats <- hydroStats(MESH_streamflows, calEnd = "2010-01-01")
#' periodStats[,1:7]
hydroStats <- function(MESHvals, stationNames = "", calStart = "",
calEnd = "", removeMissing = TRUE,
doSpearman = FALSE,
doPBFDC = FALSE,
doLogNSE = TRUE,
epsilon = "Pushpalatha2012",
digits = 2,
j = 1,
norm = "sd", s = c(1, 1, 1),
method = c("2009", "2012"),
lQ.thr = 0.7, hQ.thr = 0.2) {
vars <- names(MESHvals)
if (vars[1] != "DATE" & vars[1] != "DATETIME") {
cat('Error: not a time series date frame\n')
return(FALSE)
}
# check for specified station names
numCols <- ncol(MESHvals) - 1
numStations <- floor(numCols / 2)
if (length(stationNames) >= numStations) {
tempstation <- ""
} else {
tempstation <- 0
}
# check for periods
if (calEnd != "") {
calEndDate <- as.Date(calEnd)
} else {
calEndDate <- as.Date(max(MESHvals[,1]))
}
if (calStart != "") {
calStartDate <- as.Date(calStart)
} else {
calStartDate <- as.Date(min(MESHvals[,1]))
}
# add period
period <- FALSE
if ((calStart != "") | (calEnd != "")) {
period <- TRUE
MESHvals$period <- "Validation"
MESHvals$period[(as.Date(MESHvals[,1]) >= calStartDate) &
(as.Date(MESHvals[,1]) <= calEndDate)] <- "Calibration"
}
if (!period) {
for (i in 1:numStations) {
meas_col <- (i - 1) * 2 + 2
sim_col <- meas_col + 1
meas <- MESHvals[, meas_col]
sim <- MESHvals[, sim_col]
# check meas and sim to make sure that they can be used
if (all(is.na(meas)) | all(is.na(sim)) |
all(meas <= 0, na.rm = TRUE) | all(meas <= 0, na.rm = TRUE)) {
cat("Error: No values to use for calculations\n")
return(FALSE)
} else {
g <- hydroGOF::gof(sim, meas, na.rm = removeMissing,
do.spearman = doSpearman,
do.pbfsc = doPBFDC,
j = j,
norm = norm,
s = s,
method = method,
lQ.thr = lQ.thr,
hQ.thr = hQ.thr,
digits = digits)
g <- as.data.frame(t(g))
# do log NSE if required
if (doLogNSE) {
if (is.numeric(epsilon)) {
if (epsilon > 0) {
epsilon_value <- epsilon
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = "other",
epsilon.value = epsilon_value)
} else {
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = "0")
}
} else {
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = epsilon)
}
g$LogNSE <- l_nse
}
g$station <- tempstation
if (i == 1) {
if (length(stationNames) >= numStations & all(stationNames != "")) {
g$station <- stationNames[i]
} else {
g$station <- i
}
gvals <- g
} else {
if (length(stationNames) >= numStations & all(stationNames != "")) {
g$station <- stationNames[i]
} else {
g$station <- i
}
gvals <- rbind(gvals, g)
}
} # for loop
}
# move station to column 1
cols <- ncol(gvals)
gvals <- gvals[, c(cols, 1:(cols - 1))]
} else {
# subdivide by period
validation <- MESHvals[MESHvals$period == "Validation", ]
calibration <- MESHvals[MESHvals$period == "Calibration", ]
# do calibration first
for (i in 1:numStations) {
meas_col <- (i - 1) * 2 + 2
sim_col <- meas_col + 1
meas <- calibration[, meas_col]
sim <- calibration[, sim_col]
g <- hydroGOF::gof(sim, meas, na.rm = removeMissing,
do.spearman = doSpearman,
do.pbfsc = doPBFDC,
j = j,
norm = norm,
s = s,
method = method,
lQ.thr = lQ.thr,
hQ.thr = hQ.thr,
digits = digits)
g <- as.data.frame(t(g))
if (doLogNSE) {
if (is.numeric(epsilon)) {
if (epsilon > 0) {
epsilon_value <- epsilon
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = "other",
epsilon.value = epsilon_value)
} else {
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = "0")
}
} else {
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = epsilon)
}
g$LogNSE <- l_nse
}
g$station <- tempstation
if (i == 1) {
if (length(stationNames) >= numStations & all(stationNames != "")) {
g$station <- stationNames[i]
} else {
g$station <- i
}
gvals1 <- g
} else {
if (length(stationNames) >= numStations & all(stationNames != "")) {
g$station <- stationNames[i]
} else {
g$station <- i
}
gvals1 <- rbind(gvals1, g)
}
}
# do validation
for (i in 1:numStations) {
meas_col <- (i - 1) * 2 + 2
sim_col <- meas_col + 1
meas <- validation[, meas_col]
sim <- validation[, sim_col]
g <- hydroGOF::gof(sim, meas,
do.spearman = doSpearman,
do.pbfsc = doPBFDC,
j = j,
norm = norm,
s = s,
method = method,
lQ.thr = lQ.thr,
hQ.thr = hQ.thr,
digits = digits)
g <- as.data.frame(t(g))
if (doLogNSE) {
if (is.numeric(epsilon)) {
if (epsilon > 0) {
epsilon_value <- epsilon
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = "other",
epsilon.value = epsilon_value)
} else {
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = "0")
}
} else {
l_nse <- hydroGOF::NSE(sim, meas, na.rm = removeMissing,
FUN = log10, epsilon = epsilon)
}
g$LogNSE <- l_nse
}
g$station <- tempstation
if (i == 1) {
if (length(stationNames) >= numStations & all(stationNames != "")) {
g$station <- stationNames[i]
} else {
g$station <- i
}
gvals2 <- g
} else {
if (length(stationNames) >= numStations & all(stationNames != "")) {
g$station <- stationNames[i]
} else {
g$station <- i
}
gvals2 <- rbind(gvals2, g)
}
}
# add period names and dates
gvals1$period <- "Calibration"
gvals1$start_date <- calStartDate
gvals1$end_date <- calEndDate
gvals2$period <- "Validation"
gvals2$start_date <- min(as.Date(validation[,1]))
gvals2$end_date <- max(as.Date(validation[,1]))
# combine both data sets
gvals <- rbind(gvals1, gvals2)
# move station to column 1
cols <- ncol(gvals)
last_4 <- seq((cols - 3), cols)
gvals <- gvals[, c(last_4 , 1:(cols - 3))]
}
return(gvals)
}
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