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plot_agg_nn_fluxnet2015.R
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library(dplyr)
source( "analyse_modobs.R" )
source( "remove_outliers.R" )
## Manual settings ----------------
nam_target = "lue_obs_evi"
use_weights= FALSE
use_fapar = FALSE
package = "nnet"
nrep = 5
dotrain = FALSE
overwrite_modis = TRUE
overwrite_mte = TRUE
##--------------------------
## check and override if necessary
if ( nam_target=="lue_obs_evi" || nam_target=="lue_obs_fpar" ){
plotlue <- TRUE
if (nam_target=="lue_obs_evi"){
fapar_data <- "evi"
} else if (nam_target=="lue_obs_fpar"){
fapar_data <- "fpar"
}
if (use_fapar){
print("WARNING: setting use_fapar to FALSE")
use_fapar <- FALSE
}
}
## identifier for output files
if (use_fapar){
if (nam_target=="lue_obs_evi"){
char_fapar <- "_withEVI"
} else if (nam_target=="lue_obs_fpar"){
char_fapar <- "_withFPAR"
} else {
print("ERROR: PROVIDE VALID FAPAR DATA!")
}
} else {
char_fapar <- ""
}
if (use_weights){
char_wgt <- "_wgt"
} else {
char_wgt <- ""
}
siteinfo <- read.csv( "siteinfo_fluxnet2015_sofun.csv" )
## Load aggregated data from all sites, created by plot_nn_fVAR_fluxnet2015.R:
load( paste( "data/nice_agg_", char_wgt, nam_target, ".Rdata", sep="" ) ) # loads 'nice_agg'
load( "data/overview_data_fluxnet2015_L5.Rdata" ) # loads 'overview', written by cluster_fvar_vs_soilm.R or cluster_aligned_fluxnet2015.R
## Load aligned aggregated data
load( "data/data_aligned_agg.Rdata" ) # loads 'df_dday_agg', 'df_dday_modis_agg', 'df_dday_mte_agg',
## add vegetation type info to nice_agg
nice_agg <- nice_agg %>% left_join( dplyr::select( siteinfo, mysitename, classid ), by="mysitename" )
## Add cluster information to nice_agg
nice_agg <- nice_agg %>% left_join( dplyr::select( overview, mysitename, alignedcluster, quadfitcluster, finalcluster ) )
##--------------------------------------
## SPEI by fLUE drought
##--------------------------------------
nice_agg <- nice_agg %>% mutate( alpha=aet_pmodel/pet_pmodel )
plotfiln <- paste( "fig_nn_fluxnet2015/boxplot_fluedrought_vs_alpha_spi_spei_1mo.pdf", sep="")
pdf( plotfiln, width=6, height=4, bg="white" )
print( paste( "plotting", plotfiln ) )
par( las=1, mfrow=c(1,3) )
## spi 1
var1 <- unique( dplyr::filter( nice_agg, is_drought_byvar & finalcluster %in% c(1,2) & !is.na(spi1) & !is.infinite(spi1) )$spi1 )
var2 <- unique( dplyr::filter( nice_agg, !is_drought_byvar & finalcluster %in% c(1,2) & !is.na(spi1) & !is.infinite(spi1) )$spi1 )
ttest <- t.test( var1, var2, paired=FALSE, na.action=na.omit )
wtest <- wilcox.test( var1, var2, na.action=na.omit )
nsites <- dplyr::filter( nice_agg, finalcluster %in% c(1,2) & !is.na(spi1) & !is.infinite(spi1) ) %>% dplyr::select( mysitename ) %>% unique() %>% nrow()
ndays <- dplyr::filter( nice_agg, finalcluster %in% c(1,2) & !is.na(spi1) & !is.infinite(spi1) ) %>% nrow()
with( dplyr::filter( nice_agg, finalcluster %in% c(1,2) & !is.na(spi1) & !is.infinite(spi1) ), boxplot( spi1 ~ is_drought_byvar, xlab="fLUE drought", ylab="SPI, 1 mo.", col="grey70", outline=FALSE) )
mtext( paste( "p =", format( ttest$p.value, digits=2 ) ), adj=1, cex=0.8 )
mtext( paste( "N =", as.character( ndays ) ), adj=1, line=1, cex=0.8 )
mtext( paste( "sites =", as.character( nsites ) ), adj=1, line=2, cex=0.8 )
mtext( "a)", adj=0, line=1, font=2 )
## spei 1
var1 <- unique( dplyr::filter( nice_agg, is_drought_byvar & finalcluster %in% c(1,2) & !is.na(spei1) & !is.infinite(spei1) )$spei1 )
var2 <- unique( dplyr::filter( nice_agg, !is_drought_byvar & finalcluster %in% c(1,2) & !is.na(spei1) & !is.infinite(spei1) )$spei1 )
ttest <- t.test( var1, var2, paired=FALSE, na.action=na.omit )
wtest <- wilcox.test( var1, var2, na.action=na.omit )
nsites <- dplyr::filter( nice_agg, finalcluster %in% c(1,2) & !is.na(spei1) & !is.infinite(spei1) ) %>% dplyr::select( mysitename ) %>% unique() %>% nrow()
ndays <- dplyr::filter( nice_agg, finalcluster %in% c(1,2) & !is.na(spei1) & !is.infinite(spei1) ) %>% nrow()
with( dplyr::filter( nice_agg, finalcluster %in% c(1,2) & !is.na(spei1) & !is.infinite(spei1) ), boxplot( spei1 ~ is_drought_byvar, xlab="fLUE drought", ylab="SPEI, 1 mo.", col="grey70", outline=FALSE) )
mtext( paste( "p =", format( ttest$p.value, digits=2 ) ), adj=1, cex=0.8 )
mtext( paste( "N =", as.character( ndays ) ), adj=1, line=1, cex=0.8 )
mtext( paste( "sites =", as.character( nsites ) ), adj=1, line=2, cex=0.8 )
mtext( "b)", adj=0, line=1, font=2 )
## AET/PET
var1 <- unique( dplyr::filter( nice_agg, is_drought_byvar & finalcluster %in% c(1,2) & !is.na(alpha) & !is.infinite(alpha) )$alpha )
var2 <- unique( dplyr::filter( nice_agg, !is_drought_byvar & finalcluster %in% c(1,2) & !is.na(alpha) & !is.infinite(alpha) )$alpha )
ttest <- t.test( var1, var2, paired=FALSE, na.action=na.omit )
wtest <- wilcox.test( var1, var2, na.action=na.omit )
nsites <- dplyr::filter( nice_agg, finalcluster %in% c(1,2) & !is.na(alpha) & !is.infinite(alpha) ) %>% dplyr::select( mysitename ) %>% unique() %>% nrow()
ndays <- dplyr::filter( nice_agg, finalcluster %in% c(1,2) & !is.na(alpha) & !is.infinite(alpha) ) %>% nrow()
with( dplyr::filter( nice_agg, finalcluster %in% c(1,2) ), boxplot( alpha ~ is_drought_byvar, outline=FALSE, xlab="fLUE drought", ylab="AET/PET", col="grey70" ) )
mtext( paste( "p =", format( ttest$p.value, digits=2 ) ), adj=1, cex=0.8 )
mtext( paste( "N =", as.character( ndays ) ), adj=1, line=1, cex=0.8 )
mtext( paste( "sites =", as.character( nsites ) ), adj=1, line=2, cex=0.8 )
mtext( "c)", adj=0, line=1, font=2 )
dev.off()
# ##--------------------------------------
# ## fLUE (rolling mean) by EVI extreme
# ##--------------------------------------
# var1 <- dplyr::filter( nice_agg, is_fapar_extreme & finalcluster %in% c(1,2,3,4) )$fvar_rollmean
# var2 <- dplyr::filter( nice_agg, !is_fapar_extreme & finalcluster %in% c(1,2,3,4) )$fvar_rollmean
# ttest <- t.test( var1, var2, paired=FALSE, na.action=na.omit )
# pdf( paste( "fig_nn_fluxnet2015/boxplot_fvar_by_eviextreme.pdf", sep=""), width=4, height=4 )
# par( las=1, mar=c(4,4,1,1) )
# boxplot(
# fvar_rollmean ~ is_fapar_extreme,
# data=dplyr::filter( nice_agg, finalcluster %in% c(1,2,3,4)),
# ylim=c(0.75,1.2),
# col="grey70",
# xlab="EVI extreme", ylab="fLUE (365 d moving average)"
# )
# # mtext( paste( "p =", format( ttest$p.value, digits=2 ) ), adj=1, cex=0.8 )
# dev.off()
##--------------------------------------
## MOD VS OBS OF ALL DATA AGGREGATED
##--------------------------------------
##--------------------------------------
## NN evaluation: LUE and GPP vs. obs.
## aggregated over soil moisture datasets and using fLUE drought identification for split
##--------------------------------------
## GPP
plotfiln <- paste( "fig_nn_fluxnet2015/modobs/modobs_gpp_rct_ALL_FROMNICE", char_wgt, ".pdf", sep="")
pdf( plotfiln, width=8, height=8 )
print( paste( "plotting mod vs obs for GPP in nice_agg:", plotfiln))
par( mfrow=c(2,2) )
stats_tmp <- analyse_modobs(
nice_agg$gpp_nn_act,
nice_agg$gpp_obs,
plot.title=expression( paste("NN"[act], " all days")),
plot.xlab=expression(paste("observed GPP (gC m"^{-2}, " d"^{-1}, ")")),
plot.ylab=expression(paste("predicted GPP (gC m"^{-2}, " d"^{-1}, ")")),
lab.xpos=0.65
)
mtext( "a)", line = 1, font = 2, adj=c(0,0) )
stats_tmp <- analyse_modobs(
dplyr::filter( nice_agg, !is_drought_byvar )$gpp_nn_pot,
dplyr::filter( nice_agg, !is_drought_byvar )$gpp_obs,
plot.title=expression( paste("NN"[pot], " moist days")),
plot.xlab=expression(paste("observed GPP (gC m"^{-2}, " d"^{-1}, ")")),
plot.ylab=expression(paste("predicted GPP (gC m"^{-2}, " d"^{-1}, ")")),
lab.xpos=0.65
)
mtext( "b)", line = 1, font = 2, adj=c(0,0) )
stats_tmp <- analyse_modobs(
dplyr::filter( nice_agg, is_drought_byvar )$gpp_nn_pot,
dplyr::filter( nice_agg, is_drought_byvar )$gpp_obs,
plot.title=expression( paste("NN"[pot], " dry days")),
plot.xlab=expression(paste("observed GPP (gC m"^{-2}, " d"^{-1}, ")")),
plot.ylab=expression(paste("predicted GPP (gC m"^{-2}, " d"^{-1}, ")")),
lab.xpos=0.65
)
mtext( "c)", line = 1, font = 2, adj=c(0,0) )
stats_tmp <- analyse_modobs(
dplyr::filter( nice_agg, !is_drought_byvar )$gpp_nn_pot,
dplyr::filter( nice_agg, !is_drought_byvar )$gpp_nn_act,
plot.title=expression( paste("NN"[pot], " vs. NN"[act], " moist days")),
plot.xlab=expression(paste("actual GPP (gC m"^{-2}, " d"^{-1}, ")")),
plot.ylab=expression(paste("potential GPP (gC m"^{-2}, " d"^{-1}, ")")),
lab.xpos=0.65
)
mtext( "d)", line = 1, font = 2, adj=c(0,0) )
dev.off()
## LUE
plotfiln <- paste( "fig_nn_fluxnet2015/modobs/modobs_lue_rct_ALL_FROMNICE", char_wgt, ".pdf", sep="")
pdf( plotfiln, width=8, height=8 )
print( paste( "plotting mod vs obs for LUE in nice_agg:", plotfiln))
par( mfrow=c(2,2) )
stats_tmp <- analyse_modobs(
nice_agg$var_nn_act,
nice_agg$lue_obs_evi,
plot.title=expression( paste("NN"[act], " all days")),
plot.xlab=expression(paste("observed LUE (gC mol"^{-1}, ")")),
plot.ylab=expression(paste("predicted LUE (gC mol"^{-1}, ")")),
lab.xpos=0.65
)
mtext( "a", line = 1, font = 2, adj=c(0,0) )
stats_tmp <- analyse_modobs(
dplyr::filter( nice_agg, !is_drought_byvar )$var_nn_pot,
dplyr::filter( nice_agg, !is_drought_byvar )$lue_obs_evi,
plot.title=expression( paste("NN"[pot], " moist days")),
plot.xlab=expression(paste("observed LUE (gC mol"^{-1}, ")")),
plot.ylab=expression(paste("predicted LUE (gC mol"^{-1}, ")")),
lab.xpos=0.65
)
mtext( "b", line = 1, font = 2, adj=c(0,0) )
stats_tmp <- analyse_modobs(
dplyr::filter( nice_agg, is_drought_byvar )$var_nn_pot,
dplyr::filter( nice_agg, is_drought_byvar )$lue_obs_evi,
plot.title=expression( paste("NN"[pot], " dry days")),
plot.xlab=expression(paste("observed LUE (gC mol"^{-1}, ")")),
plot.ylab=expression(paste("predicted LUE (gC mol"^{-1}, ")")),
lab.xpos=0.65
)
mtext( "c", line = 1, font = 2, adj=c(0,0) )
stats_tmp <- analyse_modobs(
dplyr::filter( nice_agg, !is_drought_byvar )$var_nn_pot,
dplyr::filter( nice_agg, !is_drought_byvar )$var_nn_act,
plot.title=expression( paste("NN"[pot], " vs. NN"[act], " moist days")),
plot.xlab=expression(paste("actual LUE (gC mol"^{-1}, ")")),
plot.ylab=expression(paste("potential LUE (gC mol"^{-1}, ")")),
lab.xpos=0.65
)
mtext( "d", line = 1, font = 2, adj=c(0,0) )
dev.off()
# ##--------------------------------------
# ## EXPANDED BY SOIL MOISTURE DATASET
# ##--------------------------------------
# ## GPP
# print("plotting mod vs obs for GPP in nice_resh ...")
# pdf( paste( "fig_nn_fluxnet2015/modobs/modobs_gpp_rct_ALL_FROMNICE_RESH", char_wgt, ".pdf", sep=""), width=8, height=8 )
# par( mfrow=c(2,2) )
# with( nice_resh,
# stats_tmp <- analyse_modobs(
# var_nn_act * iabs,
# lue_obs_evi * iabs,
# plot.title=expression( paste("NN"[pot])),
# plot.xlab=expression(paste("observed GPP (gC m"^{-2}, " d"^{-1}, ")")),
# plot.ylab=expression(paste("predicted GPP (gC m"^{-2}, " d"^{-1}, ")")),
# lab.xpos=0.65
# )
# )
# mtext( "d", line = 1, font = 2, adj=c(0,0) )
# with( dplyr::filter( nice_resh, moist ),
# stats_tmp <- analyse_modobs(
# var_nn_pot * iabs,
# lue_obs_evi * iabs,
# plot.title=expression( paste("NN"[pot], " moist days")),
# plot.xlab=expression(paste("observed GPP (gC m"^{-2}, " d"^{-1}, ")")),
# plot.ylab=expression(paste("predicted GPP (gC m"^{-2}, " d"^{-1}, ")")),
# lab.xpos=0.65
# )
# )
# mtext( "c", line = 1, font = 2, adj=c(0,0) )
# with( dplyr::filter( nice_resh, !moist ),
# stats_tmp <- analyse_modobs(
# var_nn_pot * iabs,
# lue_obs_evi * iabs,
# plot.title=expression( paste("NN"[pot], " dry days")),
# plot.xlab=expression(paste("observed GPP (gC m"^{-2}, " d"^{-1}, ")")),
# plot.ylab=expression(paste("predicted GPP (gC m"^{-2}, " d"^{-1}, ")")),
# lab.xpos=0.65
# )
# )
# mtext( "b", line = 1, font = 2, adj=c(0,0) )
# with( dplyr::filter( nice_resh, moist ),
# stats_tmp <- analyse_modobs(
# var_nn_pot * iabs,
# var_nn_act * iabs,
# plot.title=expression( paste("NN"[pot], " vs. NN"[act], " moist days")),
# plot.xlab=expression(paste("actual GPP (gC m"^{-2}, " d"^{-1}, ")")),
# plot.ylab=expression(paste("potential GPP (gC m"^{-2}, " d"^{-1}, ")")),
# lab.xpos=0.65
# )
# )
# mtext( "a", line = 1, font = 2, adj=c(0,0) )
# dev.off()
# ## LUE
# print("plotting mod vs obs for LUE in nice_resh ...")
# pdf( paste( "fig_nn_fluxnet2015/modobs/modobs_lue_rct_ALL_FROMNICE_RESH", char_wgt, ".pdf", sep=""), width=8, height=8 )
# par( mfrow=c(2,2) )
# with( nice_resh,
# stats_tmp <- analyse_modobs(
# var_nn_act,
# lue_obs_evi,
# plot.title=expression( paste("NN"[pot])),
# plot.xlab=expression(paste("observed LUE (gC mol"^{-1}, ")")),
# plot.ylab=expression(paste("predicted LUE (gC mol"^{-1}, ")")),
# lab.xpos=0.65
# )
# )
# mtext( "d", line = 1, font = 2, adj=c(0,0) )
# with( dplyr::filter( nice_resh, moist ),
# stats_tmp <- analyse_modobs(
# var_nn_pot,
# lue_obs_evi,
# plot.title=expression( paste("NN"[pot], " moist days")),
# plot.xlab=expression(paste("observed LUE (gC mol"^{-1}, ")")),
# plot.ylab=expression(paste("predicted LUE (gC mol"^{-1}, ")")),
# lab.xpos=0.65
# )
# )
# mtext( "c", line = 1, font = 2, adj=c(0,0) )
# with( dplyr::filter( nice_resh, !moist ),
# stats_tmp <- analyse_modobs(
# var_nn_pot,
# lue_obs_evi,
# plot.title=expression( paste("NN"[pot], " dry days")),
# plot.xlab=expression(paste("observed LUE (gC mol"^{-1}, ")")),
# plot.ylab=expression(paste("predicted LUE (gC mol"^{-1}, ")")),
# lab.xpos=0.65
# )
# )
# mtext( "b", line = 1, font = 2, adj=c(0,0) )
# with( dplyr::filter( nice_resh, moist ),
# stats_tmp <- analyse_modobs(
# var_nn_pot,
# var_nn_act,
# plot.title=expression( paste("NN"[pot], " vs. NN"[act], " moist days")),
# plot.xlab=expression(paste("actual LUE (gC mol"^{-1}, ")")),
# plot.ylab=expression(paste("potential LUE (gC mol"^{-1}, ")")),
# lab.xpos=0.65
# )
# )
# mtext( "a", line = 1, font = 2, adj=c(0,0) )
# dev.off()
##------------------------------------------------
## EVI vs. FPAR
##------------------------------------------------
plotfiln <- "fig_nn_fluxnet2015/fpar_vs_evi.pdf"
print( paste( "plotting ", plotfiln ) )
pdf( plotfiln )
par(las=1)
with( nice_agg,
heatscatter( evi, fpar, main="", xlab="EVI", ylab="FPAR", xlim=c(0,1), ylim=c(0,1) )
)
abline( c(0,0), c(1,1), col="red" )
legend( "bottomright", legend=c("low density", "", "", "", "high density"), pch=16, col=colorRampPalette( c("gray80", "navy", "red", "yellow"))(5), bty="n", cex=0.8 )
dev.off()