R/interp_TDL_tanks_ref.R
In erikerhardt/isogasex: Isotopic gas exchange using TDL and Licor input. Updated version of package tdllicor
#' Interpolate TDL tank and reference values
#'
#' Create TDL$interp to hold interpolated values between measurement cycles and observed values within measurement cycles
#'
#' List of sites (hi, low, ref) to perform smooth interpolation (1).
#'
#' For those sites with interp=1, perform smooth interpolation using \code{smooth_spline}.
#'
#' Cubic spline interpolation using \code{smooth_spline} with \code{nknots}=\code{df}=number of cycles for current site.
#'
#' Extrapolate the first/last cal tank to the first/last time values for the run.
#'
#' Fill within block times with data
#'
#' List of sites (hi, low, ref) to perform "last mean value" flat interpolation (2).
#'
#' For those sites with interp=2, perform last mean value flat interpolation.
#'
#' Plot the interpolated values.
#'
#' @param TDL xxxPARAMxxx
#' @param TDL_cycle xxxPARAMxxx
#' @param plot_format_list xxxPARAMxxx
#' @param output_fn_prefix xxxPARAMxxx
#' @param sw xxxPARAMxxx
#'
#' @return TDL xxxRETURNxxx
#' @importFrom graphics par
#' @importFrom stats smooth.spline predict
#'
interp_TDL_tanks_ref <-
function# Interpolate TDL tank and reference values
###
(TDL
###
, TDL_cycle
###
, plot_format_list
###
, output_fn_prefix
###
, sw
###
)
{
##details<<
## Create TDL$interp to hold interpolated values between measurement cycles and observed values within measurement cycles
TDL$interp <- matrix(0,nrow=TDL$n,ncol=6); # create a list to return with data
colnames(TDL$interp) <- c("tank_hi_12", "tank_hi_13", "tank_low_12" , "tank_low_13", "reference_12", "reference_13");
##details<<
## List of sites (hi, low, ref) to perform smooth interpolation (1).
i_site_list_smooth = NULL;
if (sw$interp_tank_hi == 1) { i_site_list_smooth <- c(i_site_list_smooth, 1); };
if (sw$interp_tank_low == 1) { i_site_list_smooth <- c(i_site_list_smooth, 2); };
if (sw$interp_reference == 1) { i_site_list_smooth <- c(i_site_list_smooth, 3); };
##details<<
## For those sites with interp=1, perform smooth interpolation using \code{smooth.spline}.
for (i_site in i_site_list_smooth) {
#n_sites <- sum(TDL$summary$site == TDL_cycle$table[i_site,1]); # set spline nknots and df to n_sites, smooth not overfit
n_sites <- sum(TDL$last_list[,3] == TDL_cycle$table[i_site,1]); # set spline nknots and df to n_sites, smooth not overfit
ind <- (TDL$data[,"PrevSite"] == TDL_cycle$table[i_site,1]);
# the TRUE values and non-NA values
ind <- intersect((1:TDL$n)[(ind == TRUE)], (1:TDL$n)[!is.na(ind)]);
ind_first <- ind[1];
ind_last <- ind[length(ind)];
# 12CO2
##details<<
## Cubic spline interpolation using \code{smooth.spline} with \code{nknots}=\code{df}=number of cycles for current site.
ssA <- stats::smooth.spline(ind,TDL$data[ind,"ConcA"], nknots=n_sites, df=n_sites);
TDL$interp[,i_site*2-1] <- stats::predict(ssA,1:TDL$n)$y; # TDL$time
##details<<
## Extrapolate the first/last cal tank to the first/last time values for the run.
TDL$interp[1:ind_first,i_site*2-1] <- TDL$interp[ind_first,i_site*2-1];
TDL$interp[ind_last:TDL$n,i_site*2-1] <- TDL$interp[ind_last,i_site*2-1];
# 13CO2
ssB <- stats::smooth.spline(ind,TDL$data[ind,"ConcB"], nknots=n_sites, df=n_sites);
TDL$interp[,i_site*2] <- stats::predict(ssB,1:TDL$n)$y; # TDL$time
# extrapolate the first/last cal tank to the beginning/ending time values
TDL$interp[1:ind_first,i_site*2] <- TDL$interp[ind_first,i_site*2];
TDL$interp[ind_last:TDL$n,i_site*2] <- TDL$interp[ind_last,i_site*2];
##details<<
## Fill within block times with data
# Fill within block times with data (was 0s before) "0.1-16" "2012-07-10"
ind_summary <- (TDL$last_list[,3] == TDL_cycle$table[i_site,1]);
ind_table <- TDL$last_list[ind_summary,]; # table of start/end indices for site
n_meas <- dim(ind_table)[1];
ind_first <- ind_table[1,1];
ind_last <- ind_table[n_meas,2];
for (i_block in 1:(n_meas-1)) {
# fill within block times with data (was 0s before) "0.1-16" "2012-07-10"
ind_block_in <- seq(ind_table[i_block,1], ind_table[i_block,2]); # indices to fill with flat interp values
TDL$interp[ind_block_in, i_site*2-1] <- TDL$data$ConcA[ind_block_in]; # 12CO2
TDL$interp[ind_block_in, i_site*2] <- TDL$data$ConcB[ind_block_in]; # 13CO2
}
}
##details<<
## List of sites (hi, low, ref) to perform "last mean value" flat interpolation (2).
i_site_list_flat = NULL;
if (sw$interp_tank_hi == 2) { i_site_list_flat <- c(i_site_list_flat, 1); };
if (sw$interp_tank_low == 2) { i_site_list_flat <- c(i_site_list_flat, 2); };
if (sw$interp_reference == 2) { i_site_list_flat <- c(i_site_list_flat, 3); };
##details<<
## For those sites with interp=2, perform last mean value flat interpolation.
for (i_site in i_site_list_flat) {
ind_summary <- (TDL$last_list[,3] == TDL_cycle$table[i_site,1]);
ind_table <- TDL$last_list[ind_summary,]; # table of start/end indices for site
site_means <- TDL$summary$mean[ind_summary,]; # summarized means
n_meas <- dim(ind_table)[1];
ind_first <- ind_table[1,1];
ind_last <- ind_table[n_meas,2];
for (i_block in 1:(n_meas-1)) {
last_mean <- site_means[i_block,c("ConcA","ConcB")];
ind_block_out <- seq(ind_table[i_block,2]+1, ind_table[i_block+1,1]-1); # indices to fill with flat interp values
TDL$interp[ind_block_out,i_site*2-1] <- last_mean["ConcA"]; # 12CO2
TDL$interp[ind_block_out,i_site*2] <- last_mean["ConcB"]; # 13CO2
# fill within block times with data (was 0s before) "0.1-16" "2012-07-10"
ind_block_in <- seq(ind_table[i_block,1], ind_table[i_block,2]); # indices to fill with flat interp values
TDL$interp[ind_block_in, i_site*2-1] <- TDL$data$ConcA[ind_block_in]; # 12CO2
TDL$interp[ind_block_in, i_site*2] <- TDL$data$ConcB[ind_block_in]; # 13CO2
}
}
i_site_list_none <- setdiff(1:3, c(i_site_list_smooth, i_site_list_flat)); # these were not interpolated!
##details<<
## Plot the interpolated values.
for (i_plot in plot_format_list)
{
plot_filename <- "plot_TDL_interp";
s_plot_settings_begin_end(output_fn_prefix, plot_filename, plot_mode = "begin", plot_format = i_plot);
graphics::par(mfrow=c(3,2), mar=c(4,4,2,2), oma=c(1,1,1,1)); # mar allows the histograms to touch top-bottom c(bot,lef,top,rig)
for (i_site in 1:3) {
#n_sites <- sum(TDL$summary$site == TDL_cycle$table[i_site,1]); # set spline nknots and df to n_sites, smooth not overfit
n_sites <- sum(TDL$last_list[,3] == TDL_cycle$table[i_site,1]); # set spline nknots and df to n_sites, smooth not overfit
ind <- (TDL$data[,"PrevSite"] == TDL_cycle$table[i_site,1]);
# the TRUE values and non-NA values
ind <- intersect((1:TDL$n)[(ind == TRUE)], (1:TDL$n)[!is.na(ind)]);
ind_first <- ind[1];
ind_last <- ind[length(ind)];
# 12CO2
plot(TDL$time,TDL$interp[,i_site*2-1],type="l" , ylab="ConcA 12CO2", xlab="");
points(TDL$time[ind],TDL$data[ind,"ConcA"], pch=20); # ind ,pch=20, type="l",ylim=c(475.3,476)
title(main=paste("Interpolation of TDL ", TDL_cycle$table_name[i_site], ", 12CO2", sep=""));
# 7/20/2012 used indices -- updated to times on x-axis
#plot(ind,TDL$data[ind,"ConcA"], ylab="ConcA 12CO2", xlim=c(1,TDL$n), xlab="", pch=20); # ind ,pch=20, type="l",ylim=c(475.3,476)
#points(1:TDL$n,TDL$interp[,i_site*2-1],type="l");
#title(main=paste("Interpolation of TDL ", TDL_cycle$table_name[i_site], ", 12CO2", sep=""));
# 13CO2
plot(TDL$time,TDL$interp[,i_site*2],type="l" , ylab="ConcB 13CO2", xlab="");
points(TDL$time[ind],TDL$data[ind,"ConcB"], pch=20); # ind ,pch=20, type="l",ylim=c(475.3,476)
title(main=paste("Interpolation of TDL ", TDL_cycle$table_name[i_site], ", 13CO2", sep=""));
# 7/20/2012 used indices -- updated to times on x-axis
#plot(ind,TDL$data[ind,"ConcB"], ylab="ConcB 13CO2", xlim=c(1,TDL$n), xlab="", pch=20); # ,pch=20, type="l" ,ylim=c(475.3,476)
#points(1:TDL$n,TDL$interp[,i_site*2],type="l");
#title(main=paste("Interpolation of TDL ", TDL_cycle$table_name[i_site], ", 13CO2", sep=""));
}
#axis(3); axis(4); # add axis labels to top and right sides
s_plot_settings_begin_end(output_fn_prefix, plot_filename, plot_mode = "end");
} # plotting loop
return(TDL);
### TDL
}
erikerhardt/isogasex documentation built on July 16, 2019, 5:25 a.m.
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#' Interpolate TDL tank and reference values
#'
#' Create TDL$interp to hold interpolated values between measurement cycles and observed values within measurement cycles
#'
#' List of sites (hi, low, ref) to perform smooth interpolation (1).
#'
#' For those sites with interp=1, perform smooth interpolation using \code{smooth_spline}.
#'
#' Cubic spline interpolation using \code{smooth_spline} with \code{nknots}=\code{df}=number of cycles for current site.
#'
#' Extrapolate the first/last cal tank to the first/last time values for the run.
#'
#' Fill within block times with data
#'
#' List of sites (hi, low, ref) to perform "last mean value" flat interpolation (2).
#'
#' For those sites with interp=2, perform last mean value flat interpolation.
#'
#' Plot the interpolated values.
#'
#' @param TDL xxxPARAMxxx
#' @param TDL_cycle xxxPARAMxxx
#' @param plot_format_list xxxPARAMxxx
#' @param output_fn_prefix xxxPARAMxxx
#' @param sw xxxPARAMxxx
#'
#' @return TDL xxxRETURNxxx
#' @importFrom graphics par
#' @importFrom stats smooth.spline predict
#'
interp_TDL_tanks_ref <-
function# Interpolate TDL tank and reference values
###
(TDL
###
, TDL_cycle
###
, plot_format_list
###
, output_fn_prefix
###
, sw
###
)
{
##details<<
## Create TDL$interp to hold interpolated values between measurement cycles and observed values within measurement cycles
TDL$interp <- matrix(0,nrow=TDL$n,ncol=6); # create a list to return with data
colnames(TDL$interp) <- c("tank_hi_12", "tank_hi_13", "tank_low_12" , "tank_low_13", "reference_12", "reference_13");
##details<<
## List of sites (hi, low, ref) to perform smooth interpolation (1).
i_site_list_smooth = NULL;
if (sw$interp_tank_hi == 1) { i_site_list_smooth <- c(i_site_list_smooth, 1); };
if (sw$interp_tank_low == 1) { i_site_list_smooth <- c(i_site_list_smooth, 2); };
if (sw$interp_reference == 1) { i_site_list_smooth <- c(i_site_list_smooth, 3); };
##details<<
## For those sites with interp=1, perform smooth interpolation using \code{smooth.spline}.
for (i_site in i_site_list_smooth) {
#n_sites <- sum(TDL$summary$site == TDL_cycle$table[i_site,1]); # set spline nknots and df to n_sites, smooth not overfit
n_sites <- sum(TDL$last_list[,3] == TDL_cycle$table[i_site,1]); # set spline nknots and df to n_sites, smooth not overfit
ind <- (TDL$data[,"PrevSite"] == TDL_cycle$table[i_site,1]);
# the TRUE values and non-NA values
ind <- intersect((1:TDL$n)[(ind == TRUE)], (1:TDL$n)[!is.na(ind)]);
ind_first <- ind[1];
ind_last <- ind[length(ind)];
# 12CO2
##details<<
## Cubic spline interpolation using \code{smooth.spline} with \code{nknots}=\code{df}=number of cycles for current site.
ssA <- stats::smooth.spline(ind,TDL$data[ind,"ConcA"], nknots=n_sites, df=n_sites);
TDL$interp[,i_site*2-1] <- stats::predict(ssA,1:TDL$n)$y; # TDL$time
##details<<
## Extrapolate the first/last cal tank to the first/last time values for the run.
TDL$interp[1:ind_first,i_site*2-1] <- TDL$interp[ind_first,i_site*2-1];
TDL$interp[ind_last:TDL$n,i_site*2-1] <- TDL$interp[ind_last,i_site*2-1];
# 13CO2
ssB <- stats::smooth.spline(ind,TDL$data[ind,"ConcB"], nknots=n_sites, df=n_sites);
TDL$interp[,i_site*2] <- stats::predict(ssB,1:TDL$n)$y; # TDL$time
# extrapolate the first/last cal tank to the beginning/ending time values
TDL$interp[1:ind_first,i_site*2] <- TDL$interp[ind_first,i_site*2];
TDL$interp[ind_last:TDL$n,i_site*2] <- TDL$interp[ind_last,i_site*2];
##details<<
## Fill within block times with data
# Fill within block times with data (was 0s before) "0.1-16" "2012-07-10"
ind_summary <- (TDL$last_list[,3] == TDL_cycle$table[i_site,1]);
ind_table <- TDL$last_list[ind_summary,]; # table of start/end indices for site
n_meas <- dim(ind_table)[1];
ind_first <- ind_table[1,1];
ind_last <- ind_table[n_meas,2];
for (i_block in 1:(n_meas-1)) {
# fill within block times with data (was 0s before) "0.1-16" "2012-07-10"
ind_block_in <- seq(ind_table[i_block,1], ind_table[i_block,2]); # indices to fill with flat interp values
TDL$interp[ind_block_in, i_site*2-1] <- TDL$data$ConcA[ind_block_in]; # 12CO2
TDL$interp[ind_block_in, i_site*2] <- TDL$data$ConcB[ind_block_in]; # 13CO2
}
}
##details<<
## List of sites (hi, low, ref) to perform "last mean value" flat interpolation (2).
i_site_list_flat = NULL;
if (sw$interp_tank_hi == 2) { i_site_list_flat <- c(i_site_list_flat, 1); };
if (sw$interp_tank_low == 2) { i_site_list_flat <- c(i_site_list_flat, 2); };
if (sw$interp_reference == 2) { i_site_list_flat <- c(i_site_list_flat, 3); };
##details<<
## For those sites with interp=2, perform last mean value flat interpolation.
for (i_site in i_site_list_flat) {
ind_summary <- (TDL$last_list[,3] == TDL_cycle$table[i_site,1]);
ind_table <- TDL$last_list[ind_summary,]; # table of start/end indices for site
site_means <- TDL$summary$mean[ind_summary,]; # summarized means
n_meas <- dim(ind_table)[1];
ind_first <- ind_table[1,1];
ind_last <- ind_table[n_meas,2];
for (i_block in 1:(n_meas-1)) {
last_mean <- site_means[i_block,c("ConcA","ConcB")];
ind_block_out <- seq(ind_table[i_block,2]+1, ind_table[i_block+1,1]-1); # indices to fill with flat interp values
TDL$interp[ind_block_out,i_site*2-1] <- last_mean["ConcA"]; # 12CO2
TDL$interp[ind_block_out,i_site*2] <- last_mean["ConcB"]; # 13CO2
# fill within block times with data (was 0s before) "0.1-16" "2012-07-10"
ind_block_in <- seq(ind_table[i_block,1], ind_table[i_block,2]); # indices to fill with flat interp values
TDL$interp[ind_block_in, i_site*2-1] <- TDL$data$ConcA[ind_block_in]; # 12CO2
TDL$interp[ind_block_in, i_site*2] <- TDL$data$ConcB[ind_block_in]; # 13CO2
}
}
i_site_list_none <- setdiff(1:3, c(i_site_list_smooth, i_site_list_flat)); # these were not interpolated!
##details<<
## Plot the interpolated values.
for (i_plot in plot_format_list)
{
plot_filename <- "plot_TDL_interp";
s_plot_settings_begin_end(output_fn_prefix, plot_filename, plot_mode = "begin", plot_format = i_plot);
graphics::par(mfrow=c(3,2), mar=c(4,4,2,2), oma=c(1,1,1,1)); # mar allows the histograms to touch top-bottom c(bot,lef,top,rig)
for (i_site in 1:3) {
#n_sites <- sum(TDL$summary$site == TDL_cycle$table[i_site,1]); # set spline nknots and df to n_sites, smooth not overfit
n_sites <- sum(TDL$last_list[,3] == TDL_cycle$table[i_site,1]); # set spline nknots and df to n_sites, smooth not overfit
ind <- (TDL$data[,"PrevSite"] == TDL_cycle$table[i_site,1]);
# the TRUE values and non-NA values
ind <- intersect((1:TDL$n)[(ind == TRUE)], (1:TDL$n)[!is.na(ind)]);
ind_first <- ind[1];
ind_last <- ind[length(ind)];
# 12CO2
plot(TDL$time,TDL$interp[,i_site*2-1],type="l" , ylab="ConcA 12CO2", xlab="");
points(TDL$time[ind],TDL$data[ind,"ConcA"], pch=20); # ind ,pch=20, type="l",ylim=c(475.3,476)
title(main=paste("Interpolation of TDL ", TDL_cycle$table_name[i_site], ", 12CO2", sep=""));
# 7/20/2012 used indices -- updated to times on x-axis
#plot(ind,TDL$data[ind,"ConcA"], ylab="ConcA 12CO2", xlim=c(1,TDL$n), xlab="", pch=20); # ind ,pch=20, type="l",ylim=c(475.3,476)
#points(1:TDL$n,TDL$interp[,i_site*2-1],type="l");
#title(main=paste("Interpolation of TDL ", TDL_cycle$table_name[i_site], ", 12CO2", sep=""));
# 13CO2
plot(TDL$time,TDL$interp[,i_site*2],type="l" , ylab="ConcB 13CO2", xlab="");
points(TDL$time[ind],TDL$data[ind,"ConcB"], pch=20); # ind ,pch=20, type="l",ylim=c(475.3,476)
title(main=paste("Interpolation of TDL ", TDL_cycle$table_name[i_site], ", 13CO2", sep=""));
# 7/20/2012 used indices -- updated to times on x-axis
#plot(ind,TDL$data[ind,"ConcB"], ylab="ConcB 13CO2", xlim=c(1,TDL$n), xlab="", pch=20); # ,pch=20, type="l" ,ylim=c(475.3,476)
#points(1:TDL$n,TDL$interp[,i_site*2],type="l");
#title(main=paste("Interpolation of TDL ", TDL_cycle$table_name[i_site], ", 13CO2", sep=""));
}
#axis(3); axis(4); # add axis labels to top and right sides
s_plot_settings_begin_end(output_fn_prefix, plot_filename, plot_mode = "end");
} # plotting loop
return(TDL);
### TDL
}
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