scripts/Leaf.spectrum.posterior2.R
In femeunier/albedo:
rm(list = ls())
library(dplyr)
library(tidyr)
library(PEcAnRTM)
library(purrr)
library(rrtm)
library(ED2scenarios)
library(PEcAn.ED2)
library(purrr)
library(ggplot2)
library(ggridges)
file2load <- "~/Documents/R/edr-da/data/All_parameters.RDS"
All.parameters <- readRDS(file2load)
# All.parameters_sanchezFRS <- All.parameters %>% filter(ref == "Sanchez_FTS") %>% mutate(simu = c(sort(rep(c(1:10153),5)),sort(rep(c(1:7854),5)))) %>%
# pivot_wider(names_from = Param,values_from = value) %>% filter(Nlayers < 2 & Nlayers >1.3) %>% dplyr::select(-c("simu")) %>% pivot_longer(cols = -c("pft","ref"),names_to = "Param",values_to = "value")
# All.parameters_sanchezFRS %>% group_by(Param,pft) %>% summarise(m = mean(value))
# ggplot(data = All.parameters %>% filter(Param == "Cab"),
# aes(x = value, y = as.factor(pft), fill = as.factor(pft))) +
# geom_density_ridges(alpha= 0.5,scale=0.95) +
# facet_wrap(~Param,scales = "free") +
# theme_bw()
# All.parameters <- bind_rows(list(All.parameters %>% filter(ref != "Sanchez_FTS"),
# All.parameters_sanchezFRS))
Refs_for_Prospect <- c("Guzman","Kalacska","Castro_PNM","Castro_FTS","Sanchez_PNM","Sanchez_FTS")
# Refs_for_Prospect <- c("Guzman","Kalacska","Castro_PNM","Castro_FTS","Sanchez_PNM","Sanchez_FTS","Foster","Marvin","Kalacska_RTM","Sanchez")
All.parameters <- All.parameters %>% filter(ref %in% Refs_for_Prospect)
Params_for_Prospect <- c("Cab","Car","Cw","Cm","Nlayers")
waves_all <- 400:2500
Nsimulations <- 1000
Npicks <- 25
diff_sum_all <- All <- df.spectra.all <- data.frame()
for (isimu in seq(1,Nsimulations)){
print(isimu/Nsimulations)
#Pick up one reference for Prospect/ED_RTM
Ref_prospect <- Refs_for_Prospect[sample(1:length(Refs_for_Prospect),1)]
# Ref_prospect <- "Sanchez_FTS"
params_prospect <- All.parameters %>% filter(Param %in% Params_for_Prospect) %>% group_by(pft,Param) %>% sample_n(size = Npicks) %>%
ungroup() %>% arrange(Param) %>% mutate(id = rep(1:Npicks,2*length(Params_for_Prospect))) %>% dplyr::select(-ref) %>% pivot_wider(names_from = Param,
values_from = value)
Lianas_params <- params_prospect %>% filter(pft == "Liana_optical") %>% dplyr::select(Params_for_Prospect)
Trees_params <- params_prospect %>% filter(pft == "Tree_optical") %>% dplyr::select(Params_for_Prospect)
# diff_params <- Lianas_params - Trees_params
# diff_params_m <- apply(diff_params,2,mean)
# diff_params_low <- apply(diff_params,2,quantile,0.25)
# diff_params_high <- apply(diff_params,2,quantile,0.75)
# IQR <- diff_params_high - diff_params_low
# params2low <- t(matrix(rep(diff_params_low - 1.5*IQR,10000),ncol = 10000))
# params2high <- t(matrix(rep(diff_params_high + 1.5*IQR,10000),ncol = 10000))
#
# pos2keep <- which(apply((diff_params < params2high) & (diff_params > params2low),1,all))
#
# Lianas_params <- Lianas_params[pos2keep,]
# Trees_params <- Trees_params[pos2keep,]
# if (Ref_prospect == "Guzman"){Lianas_params[,3] <- Trees_params[,3]}
# Lianas_m <- apply(Lianas_params,2,mean)
# Trees_m <- apply(Trees_params,2,mean)
#
# Lianas_params <- t(matrix(rep(Lianas_m,1),ncol=1))
# Trees_params <- t(matrix(rep(Trees_m,1),ncol=1))
# print(Lianas_params/Trees_params)
df.spectra <- data.frame()
for (i in seq(1,Npicks)){
cparam_liana <- as.vector(t(Lianas_params[i,]))
cparam_tree <- as.vector(t(Trees_params[i,]))
cspectrum_liana <- prospect5(N = cparam_liana[5],cparam_liana[1],cparam_liana[2],cparam_liana[3],cparam_liana[4])
cspectrum_tree <- prospect5(N = cparam_tree[5],cparam_tree[1],cparam_tree[2],cparam_tree[3],cparam_tree[4])
df.spectra <- rbind(df.spectra,
rbind(data.frame(waves = 400:2500,
reflectance = cspectrum_liana$reflectance,
transmittance = cspectrum_liana$transmittance,
pft = "Liana",
simu = isimu,
rep = i),
data.frame(waves = 400:2500,
reflectance = cspectrum_tree$reflectance,
transmittance = cspectrum_tree$transmittance,
pft = "Tree",
simu = isimu,
rep = i)))
}
df.spectra.sum <- df.spectra %>% group_by(waves,pft) %>% summarise(reflectance = mean(reflectance),
transmittance = mean(transmittance))
ggplot(data = df.spectra.sum) +
geom_line(aes(x = waves,y = reflectance,color = pft)) +
theme_bw()
# ggplot(data = df.spectra.sum) +
# geom_line(aes(x = waves,y = transmittance,color = pft)) +
# theme_bw()
df.spectra.all <- bind_rows(list(df.spectra.all,
df.spectra.sum %>% mutate(simu = isimu)))
}
# diff <- df.spectra.all %>% pivot_wider(names_from = pft,values_from = c(reflectance,transmittance)) %>% group_by(waves,simu) %>%
# summarise(diff_r = reflectance_Liana - reflectance_Tree,
# diff_t = transmittance_Liana - transmittance_Tree,
# ref = ref[1])
#
# ggplot(data = diff) +
# geom_line(aes(x = waves,y = diff_r,group=simu,color = ref)) +
# theme_bw()
#
# ggplot(data = diff) +
# geom_line(aes(x = waves,y = diff_t,group=simu,color = ref)) +
# theme_bw()
#
#
# diff_sum_all <- diff_sum <- diff %>% group_by(waves) %>% summarise(diff_r_mean = mean(diff_r),
# diff_t_mean = mean(diff_t),
# diff_r_min = min(diff_r),
# diff_r_max = max(diff_r),
# diff_r_alphamin = quantile(diff_r,0.25),
# diff_r_alphamax = quantile(diff_r,0.75),
# diff_r_alphalow = quantile(diff_r,0.025),
# diff_r_alphahigh = quantile(diff_r,0.975),
# diff_t_min = min(diff_t),
# diff_t_max = max(diff_t),
# diff_t_alphamin = quantile(diff_t,0.25),
# diff_t_alphamax = quantile(diff_t,0.75),
# diff_t_alphalow = quantile(diff_t,0.025),
# diff_t_alphahigh = quantile(diff_t,0.995))
# saveRDS(file = "./data/diff_sum_averaged.RDS",object = diff_sum)
All <- df.spectra.all %>% group_by(waves,pft) %>% summarise(r_mean = mean(reflectance),
r_min = min(reflectance),
r_max = max(reflectance),
t_mean = mean(transmittance),
t_min = min(transmittance),
t_max = max(transmittance))
saveRDS(file = "./data/All_averaged.RDS",object = All)
saveRDS(file = "./data/df.spectra_averaged.all",object = df.spectra.all)
# diff_sum <- readRDS(file = "./data/diff_sum_averaged.RDS")
# All <- readRDS(file = "./data/All_averaged.RDS")
# df.spectra.all <- readRDS(file = "./data/df.spectra.all_averaged.RDS")
All %>% mutate(Band = case_when(waves < 700 ~ "Vis",
waves < 1400 ~ "NIR",
waves <= 2500 ~ "SWIR")) %>% group_by(Band) %>% summarise(pval_r = summary(aov(r_mean ~ pft))[[1]][1,5],
pval_t = summary(aov(t_mean ~ pft))[[1]][1,5])
All %>% mutate(Band = case_when(waves < 700 ~ "Vis",
waves <= 2500 ~ "IR")) %>% group_by(Band) %>% summarise(pval_r = summary(aov(r_mean ~ pft))[[1]][1,5],
pval_t = summary(aov(t_mean ~ pft))[[1]][1,5])
diff_sum_all2 <- All %>% mutate(Band = case_when(waves <= 700 ~ 1,
waves <= 2500 ~2)) %>% group_by(Band) %>% summarise(r_verylow = quantile(r_mean[pft == "Liana"] - r_mean[pft == "Tree"],0.025),
r_low = quantile(r_mean[pft == "Liana"] - r_mean[pft == "Tree"],0.25),
r_m = mean(r_mean[pft == "Liana"] - r_mean[pft == "Tree"]),
r_high = quantile(r_mean[pft == "Liana"] - r_mean[pft == "Tree"],0.75),
r_veryhigh = quantile(r_mean[pft == "Liana"] - r_mean[pft == "Tree"],0.975),
t_verylow = quantile(t_mean[pft == "Liana"] - t_mean[pft == "Tree"],0.025),
t_low = quantile(t_mean[pft == "Liana"] - t_mean[pft == "Tree"],0.25),
t_m = mean(t_mean[pft == "Liana"] - t_mean[pft == "Tree"]),
t_high = quantile(t_mean[pft == "Liana"] - t_mean[pft == "Tree"],0.75),
t_veryhigh = quantile(t_mean[pft == "Liana"] - t_mean[pft == "Tree"],0.975))
diff_sum_all3 <- df.spectra.all %>% mutate(Band = case_when(waves <= 700 ~ 1,
waves <= 2500 ~2)) %>% group_by(Band) %>% summarise(r_verylow = quantile(reflectance[pft == "Liana"] - reflectance[pft == "Tree"],0.025),
r_low = quantile(reflectance[pft == "Liana"] - reflectance[pft == "Tree"],0.25),
r_m = mean(reflectance[pft == "Liana"] - reflectance[pft == "Tree"]),
r_high = quantile(reflectance[pft == "Liana"] - reflectance[pft == "Tree"],0.75),
r_veryhigh = quantile(reflectance[pft == "Liana"] - reflectance[pft == "Tree"],0.975),
t_verylow = quantile(transmittance[pft == "Liana"] - transmittance[pft == "Tree"],0.025),
t_low = quantile(transmittance[pft == "Liana"] - transmittance[pft == "Tree"],0.25),
t_m = mean(transmittance[pft == "Liana"] - transmittance[pft == "Tree"]),
t_high = quantile(transmittance[pft == "Liana"] - transmittance[pft == "Tree"],0.75),
t_veryhigh = quantile(transmittance[pft == "Liana"] - transmittance[pft == "Tree"],0.975))
xmin1 = 450;xmin2=720
xmax1 = 680;xmax2=2500
ggplot() +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all2$r_verylow[1],ymax =diff_sum_all2$r_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all2$r_low[1],ymax =diff_sum_all2$r_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=diff_sum_all2$r_m[1],yend=diff_sum_all2$r_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all2$r_verylow[2],ymax =diff_sum_all2$r_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all2$r_low[2],ymax =diff_sum_all2$r_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=diff_sum_all2$r_m[2],yend=diff_sum_all2$r_m[2]),color = "black") +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all2$t_verylow[1],ymin =1-diff_sum_all2$t_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all2$t_low[1],ymin =1-diff_sum_all2$t_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=1-diff_sum_all2$t_m[1],yend=1-diff_sum_all2$t_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all2$t_verylow[2],ymin =1-diff_sum_all2$t_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all2$t_low[2],ymin =1-diff_sum_all2$t_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=1-diff_sum_all2$t_m[2],yend=1-diff_sum_all2$t_m[2]),color = "black") +
geom_line(data = All, aes(x = waves,colour = pft,y = r_mean)) +
geom_line(data = All, aes(x = waves,colour = pft,y = 1-t_mean),linetype = 1) +
scale_y_continuous(sec.axis = sec_axis(trans = ~ 1 - 1 * ., name = "Transmittance [-]",breaks = seq(0,0.6,0.2)),
breaks = seq(0,0.6,0.2),expand = c(0,0)) +
geom_hline(yintercept = c(0,1),linetype=3)+
scale_color_manual(values = c("#1E64C8","#137300")) +
labs(y = "Reflectance [-]",
x = "Wavelength [nm]") +
theme_bw() + theme(text = element_text(size = 14),
axis.title.y = element_text(margin = margin(t = 0, r = 10, b = 0, l = 0),hjust=0.25),
axis.title.y.right = element_text(margin = margin(t = 0, r = 0, b = 0, l = 10)),
axis.title.x = element_text(margin = margin(t = 10, r = 0, b = 0, l = 0)))
ggsave(plot = last_plot(),dpi = 300, width = 20,height = 12, filename = file.path("./Figures","Leaf.spectrum.posterior_large_avged.png"),units = "cm")
xmin1 = 400;xmin2=710
xmax1 = 690;xmax2=1000
ggplot() +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all2$r_verylow[1],ymax =diff_sum_all2$r_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all2$r_low[1],ymax =diff_sum_all2$r_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=diff_sum_all2$r_m[1],yend=diff_sum_all2$r_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all2$r_verylow[2],ymax =diff_sum_all2$r_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all2$r_low[2],ymax =diff_sum_all2$r_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=diff_sum_all2$r_m[2],yend=diff_sum_all2$r_m[2]),color = "black") +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all2$t_verylow[1],ymin =1-diff_sum_all2$t_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all2$t_low[1],ymin =1-diff_sum_all2$t_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=1-diff_sum_all2$t_m[1],yend=1-diff_sum_all2$t_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all2$t_verylow[2],ymin =1-diff_sum_all2$t_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all2$t_low[2],ymin =1-diff_sum_all2$t_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=1-diff_sum_all2$t_m[2],yend=1-diff_sum_all2$t_m[2]),color = "black") +
geom_line(data = All, aes(x = waves,colour = pft,y = r_mean)) +
geom_line(data = All, aes(x = waves,colour = pft,y = 1-t_mean),linetype = 1) +
scale_y_continuous(sec.axis = sec_axis(trans = ~ 1 - 1 * ., name = "Transmittance [-]",breaks = seq(0,0.6,0.2)),
breaks = seq(0,0.6,0.2),expand = c(0,0)) +
scale_x_continuous(limits = c(xmin1,xmax2)) +
geom_hline(yintercept = c(0,1),linetype=3)+
scale_color_manual(values = c("#1E64C8","#137300")) +
labs(y = "Reflectance [-]",
x = "Wavelength [nm]") +
theme_bw() + theme(text = element_text(size = 14),
axis.title.y = element_text(margin = margin(t = 0, r = 10, b = 0, l = 0),hjust=0.25),
axis.title.y.right = element_text(margin = margin(t = 0, r = 0, b = 0, l = 10)),
axis.title.x = element_text(margin = margin(t = 10, r = 0, b = 0, l = 0)))
ggsave(plot = last_plot(),dpi = 300, width = 30,height = 20, filename = file.path("./Figures","Leaf.spectrum.posterior_avged.png"),units = "cm")
xmin1 = 450;xmin2=720
xmax1 = 680;xmax2=2500
ggplot() +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all3$r_verylow[1],ymax =diff_sum_all3$r_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all3$r_low[1],ymax =diff_sum_all3$r_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=diff_sum_all3$r_m[1],yend=diff_sum_all3$r_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all3$r_verylow[2],ymax =diff_sum_all3$r_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all3$r_low[2],ymax =diff_sum_all3$r_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=diff_sum_all3$r_m[2],yend=diff_sum_all3$r_m[2]),color = "black") +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all3$t_verylow[1],ymin =1-diff_sum_all3$t_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all3$t_low[1],ymin =1-diff_sum_all3$t_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=1-diff_sum_all3$t_m[1],yend=1-diff_sum_all3$t_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all3$t_verylow[2],ymin =1-diff_sum_all3$t_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all3$t_low[2],ymin =1-diff_sum_all3$t_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=1-diff_sum_all3$t_m[2],yend=1-diff_sum_all3$t_m[2]),color = "black") +
geom_line(data = All, aes(x = waves,colour = pft,y = r_mean)) +
geom_line(data = All, aes(x = waves,colour = pft,y = 1-t_mean),linetype = 1) +
scale_y_continuous(sec.axis = sec_axis(trans = ~ 1 - 1 * ., name = "Transmittance [-]",breaks = seq(0,0.6,0.2)),
breaks = seq(0,0.6,0.2),expand = c(0,0)) +
geom_hline(yintercept = c(0,1),linetype=3)+
scale_color_manual(values = c("#1E64C8","#137300")) +
labs(y = "Reflectance [-]",
x = "Wavelength [nm]") +
theme_bw() + theme(text = element_text(size = 14),
axis.title.y = element_text(margin = margin(t = 0, r = 10, b = 0, l = 0),hjust=0.25),
axis.title.y.right = element_text(margin = margin(t = 0, r = 0, b = 0, l = 10)),
axis.title.x = element_text(margin = margin(t = 10, r = 0, b = 0, l = 0)))
ggsave(plot = last_plot(),dpi = 300, width = 20,height = 12, filename = file.path("./Figures","Leaf.spectrum.posterior_large_avged2.png"),units = "cm")
xmin1 = 400;xmin2=710
xmax1 = 690;xmax2=1000
ggplot() +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all3$r_verylow[1],ymax =diff_sum_all3$r_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all3$r_low[1],ymax =diff_sum_all3$r_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=diff_sum_all3$r_m[1],yend=diff_sum_all3$r_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all3$r_verylow[2],ymax =diff_sum_all3$r_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all3$r_low[2],ymax =diff_sum_all3$r_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=diff_sum_all3$r_m[2],yend=diff_sum_all3$r_m[2]),color = "black") +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all3$t_verylow[1],ymin =1-diff_sum_all3$t_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all3$t_low[1],ymin =1-diff_sum_all3$t_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=1-diff_sum_all3$t_m[1],yend=1-diff_sum_all3$t_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all3$t_verylow[2],ymin =1-diff_sum_all3$t_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all3$t_low[2],ymin =1-diff_sum_all3$t_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=1-diff_sum_all3$t_m[2],yend=1-diff_sum_all3$t_m[2]),color = "black") +
geom_line(data = All, aes(x = waves,colour = pft,y = r_mean)) +
geom_line(data = All, aes(x = waves,colour = pft,y = 1-t_mean),linetype = 1) +
scale_y_continuous(sec.axis = sec_axis(trans = ~ 1 - 1 * ., name = "Transmittance [-]",breaks = seq(0,0.6,0.2)),
breaks = seq(0,0.6,0.2),expand = c(0,0)) +
scale_x_continuous(limits = c(xmin1,xmax2)) +
geom_hline(yintercept = c(0,1),linetype=3)+
scale_color_manual(values = c("#1E64C8","#137300")) +
labs(y = "Reflectance [-]",
x = "Wavelength [nm]") +
theme_bw() + theme(text = element_text(size = 14),
axis.title.y = element_text(margin = margin(t = 0, r = 10, b = 0, l = 0),hjust=0.25),
axis.title.y.right = element_text(margin = margin(t = 0, r = 0, b = 0, l = 10)),
axis.title.x = element_text(margin = margin(t = 10, r = 0, b = 0, l = 0)))
ggsave(plot = last_plot(),dpi = 300, width = 30,height = 20, filename = file.path("./Figures","Leaf.spectrum.posterior_avged2.png"),units = "cm")
femeunier/albedo documentation built on Aug. 27, 2020, 12:45 a.m.
R Package Documentation
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rm(list = ls())
library(dplyr)
library(tidyr)
library(PEcAnRTM)
library(purrr)
library(rrtm)
library(ED2scenarios)
library(PEcAn.ED2)
library(purrr)
library(ggplot2)
library(ggridges)
file2load <- "~/Documents/R/edr-da/data/All_parameters.RDS"
All.parameters <- readRDS(file2load)
# All.parameters_sanchezFRS <- All.parameters %>% filter(ref == "Sanchez_FTS") %>% mutate(simu = c(sort(rep(c(1:10153),5)),sort(rep(c(1:7854),5)))) %>%
# pivot_wider(names_from = Param,values_from = value) %>% filter(Nlayers < 2 & Nlayers >1.3) %>% dplyr::select(-c("simu")) %>% pivot_longer(cols = -c("pft","ref"),names_to = "Param",values_to = "value")
# All.parameters_sanchezFRS %>% group_by(Param,pft) %>% summarise(m = mean(value))
# ggplot(data = All.parameters %>% filter(Param == "Cab"),
# aes(x = value, y = as.factor(pft), fill = as.factor(pft))) +
# geom_density_ridges(alpha= 0.5,scale=0.95) +
# facet_wrap(~Param,scales = "free") +
# theme_bw()
# All.parameters <- bind_rows(list(All.parameters %>% filter(ref != "Sanchez_FTS"),
# All.parameters_sanchezFRS))
Refs_for_Prospect <- c("Guzman","Kalacska","Castro_PNM","Castro_FTS","Sanchez_PNM","Sanchez_FTS")
# Refs_for_Prospect <- c("Guzman","Kalacska","Castro_PNM","Castro_FTS","Sanchez_PNM","Sanchez_FTS","Foster","Marvin","Kalacska_RTM","Sanchez")
All.parameters <- All.parameters %>% filter(ref %in% Refs_for_Prospect)
Params_for_Prospect <- c("Cab","Car","Cw","Cm","Nlayers")
waves_all <- 400:2500
Nsimulations <- 1000
Npicks <- 25
diff_sum_all <- All <- df.spectra.all <- data.frame()
for (isimu in seq(1,Nsimulations)){
print(isimu/Nsimulations)
#Pick up one reference for Prospect/ED_RTM
Ref_prospect <- Refs_for_Prospect[sample(1:length(Refs_for_Prospect),1)]
# Ref_prospect <- "Sanchez_FTS"
params_prospect <- All.parameters %>% filter(Param %in% Params_for_Prospect) %>% group_by(pft,Param) %>% sample_n(size = Npicks) %>%
ungroup() %>% arrange(Param) %>% mutate(id = rep(1:Npicks,2*length(Params_for_Prospect))) %>% dplyr::select(-ref) %>% pivot_wider(names_from = Param,
values_from = value)
Lianas_params <- params_prospect %>% filter(pft == "Liana_optical") %>% dplyr::select(Params_for_Prospect)
Trees_params <- params_prospect %>% filter(pft == "Tree_optical") %>% dplyr::select(Params_for_Prospect)
# diff_params <- Lianas_params - Trees_params
# diff_params_m <- apply(diff_params,2,mean)
# diff_params_low <- apply(diff_params,2,quantile,0.25)
# diff_params_high <- apply(diff_params,2,quantile,0.75)
# IQR <- diff_params_high - diff_params_low
# params2low <- t(matrix(rep(diff_params_low - 1.5*IQR,10000),ncol = 10000))
# params2high <- t(matrix(rep(diff_params_high + 1.5*IQR,10000),ncol = 10000))
#
# pos2keep <- which(apply((diff_params < params2high) & (diff_params > params2low),1,all))
#
# Lianas_params <- Lianas_params[pos2keep,]
# Trees_params <- Trees_params[pos2keep,]
# if (Ref_prospect == "Guzman"){Lianas_params[,3] <- Trees_params[,3]}
# Lianas_m <- apply(Lianas_params,2,mean)
# Trees_m <- apply(Trees_params,2,mean)
#
# Lianas_params <- t(matrix(rep(Lianas_m,1),ncol=1))
# Trees_params <- t(matrix(rep(Trees_m,1),ncol=1))
# print(Lianas_params/Trees_params)
df.spectra <- data.frame()
for (i in seq(1,Npicks)){
cparam_liana <- as.vector(t(Lianas_params[i,]))
cparam_tree <- as.vector(t(Trees_params[i,]))
cspectrum_liana <- prospect5(N = cparam_liana[5],cparam_liana[1],cparam_liana[2],cparam_liana[3],cparam_liana[4])
cspectrum_tree <- prospect5(N = cparam_tree[5],cparam_tree[1],cparam_tree[2],cparam_tree[3],cparam_tree[4])
df.spectra <- rbind(df.spectra,
rbind(data.frame(waves = 400:2500,
reflectance = cspectrum_liana$reflectance,
transmittance = cspectrum_liana$transmittance,
pft = "Liana",
simu = isimu,
rep = i),
data.frame(waves = 400:2500,
reflectance = cspectrum_tree$reflectance,
transmittance = cspectrum_tree$transmittance,
pft = "Tree",
simu = isimu,
rep = i)))
}
df.spectra.sum <- df.spectra %>% group_by(waves,pft) %>% summarise(reflectance = mean(reflectance),
transmittance = mean(transmittance))
ggplot(data = df.spectra.sum) +
geom_line(aes(x = waves,y = reflectance,color = pft)) +
theme_bw()
# ggplot(data = df.spectra.sum) +
# geom_line(aes(x = waves,y = transmittance,color = pft)) +
# theme_bw()
df.spectra.all <- bind_rows(list(df.spectra.all,
df.spectra.sum %>% mutate(simu = isimu)))
}
# diff <- df.spectra.all %>% pivot_wider(names_from = pft,values_from = c(reflectance,transmittance)) %>% group_by(waves,simu) %>%
# summarise(diff_r = reflectance_Liana - reflectance_Tree,
# diff_t = transmittance_Liana - transmittance_Tree,
# ref = ref[1])
#
# ggplot(data = diff) +
# geom_line(aes(x = waves,y = diff_r,group=simu,color = ref)) +
# theme_bw()
#
# ggplot(data = diff) +
# geom_line(aes(x = waves,y = diff_t,group=simu,color = ref)) +
# theme_bw()
#
#
# diff_sum_all <- diff_sum <- diff %>% group_by(waves) %>% summarise(diff_r_mean = mean(diff_r),
# diff_t_mean = mean(diff_t),
# diff_r_min = min(diff_r),
# diff_r_max = max(diff_r),
# diff_r_alphamin = quantile(diff_r,0.25),
# diff_r_alphamax = quantile(diff_r,0.75),
# diff_r_alphalow = quantile(diff_r,0.025),
# diff_r_alphahigh = quantile(diff_r,0.975),
# diff_t_min = min(diff_t),
# diff_t_max = max(diff_t),
# diff_t_alphamin = quantile(diff_t,0.25),
# diff_t_alphamax = quantile(diff_t,0.75),
# diff_t_alphalow = quantile(diff_t,0.025),
# diff_t_alphahigh = quantile(diff_t,0.995))
# saveRDS(file = "./data/diff_sum_averaged.RDS",object = diff_sum)
All <- df.spectra.all %>% group_by(waves,pft) %>% summarise(r_mean = mean(reflectance),
r_min = min(reflectance),
r_max = max(reflectance),
t_mean = mean(transmittance),
t_min = min(transmittance),
t_max = max(transmittance))
saveRDS(file = "./data/All_averaged.RDS",object = All)
saveRDS(file = "./data/df.spectra_averaged.all",object = df.spectra.all)
# diff_sum <- readRDS(file = "./data/diff_sum_averaged.RDS")
# All <- readRDS(file = "./data/All_averaged.RDS")
# df.spectra.all <- readRDS(file = "./data/df.spectra.all_averaged.RDS")
All %>% mutate(Band = case_when(waves < 700 ~ "Vis",
waves < 1400 ~ "NIR",
waves <= 2500 ~ "SWIR")) %>% group_by(Band) %>% summarise(pval_r = summary(aov(r_mean ~ pft))[[1]][1,5],
pval_t = summary(aov(t_mean ~ pft))[[1]][1,5])
All %>% mutate(Band = case_when(waves < 700 ~ "Vis",
waves <= 2500 ~ "IR")) %>% group_by(Band) %>% summarise(pval_r = summary(aov(r_mean ~ pft))[[1]][1,5],
pval_t = summary(aov(t_mean ~ pft))[[1]][1,5])
diff_sum_all2 <- All %>% mutate(Band = case_when(waves <= 700 ~ 1,
waves <= 2500 ~2)) %>% group_by(Band) %>% summarise(r_verylow = quantile(r_mean[pft == "Liana"] - r_mean[pft == "Tree"],0.025),
r_low = quantile(r_mean[pft == "Liana"] - r_mean[pft == "Tree"],0.25),
r_m = mean(r_mean[pft == "Liana"] - r_mean[pft == "Tree"]),
r_high = quantile(r_mean[pft == "Liana"] - r_mean[pft == "Tree"],0.75),
r_veryhigh = quantile(r_mean[pft == "Liana"] - r_mean[pft == "Tree"],0.975),
t_verylow = quantile(t_mean[pft == "Liana"] - t_mean[pft == "Tree"],0.025),
t_low = quantile(t_mean[pft == "Liana"] - t_mean[pft == "Tree"],0.25),
t_m = mean(t_mean[pft == "Liana"] - t_mean[pft == "Tree"]),
t_high = quantile(t_mean[pft == "Liana"] - t_mean[pft == "Tree"],0.75),
t_veryhigh = quantile(t_mean[pft == "Liana"] - t_mean[pft == "Tree"],0.975))
diff_sum_all3 <- df.spectra.all %>% mutate(Band = case_when(waves <= 700 ~ 1,
waves <= 2500 ~2)) %>% group_by(Band) %>% summarise(r_verylow = quantile(reflectance[pft == "Liana"] - reflectance[pft == "Tree"],0.025),
r_low = quantile(reflectance[pft == "Liana"] - reflectance[pft == "Tree"],0.25),
r_m = mean(reflectance[pft == "Liana"] - reflectance[pft == "Tree"]),
r_high = quantile(reflectance[pft == "Liana"] - reflectance[pft == "Tree"],0.75),
r_veryhigh = quantile(reflectance[pft == "Liana"] - reflectance[pft == "Tree"],0.975),
t_verylow = quantile(transmittance[pft == "Liana"] - transmittance[pft == "Tree"],0.025),
t_low = quantile(transmittance[pft == "Liana"] - transmittance[pft == "Tree"],0.25),
t_m = mean(transmittance[pft == "Liana"] - transmittance[pft == "Tree"]),
t_high = quantile(transmittance[pft == "Liana"] - transmittance[pft == "Tree"],0.75),
t_veryhigh = quantile(transmittance[pft == "Liana"] - transmittance[pft == "Tree"],0.975))
xmin1 = 450;xmin2=720
xmax1 = 680;xmax2=2500
ggplot() +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all2$r_verylow[1],ymax =diff_sum_all2$r_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all2$r_low[1],ymax =diff_sum_all2$r_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=diff_sum_all2$r_m[1],yend=diff_sum_all2$r_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all2$r_verylow[2],ymax =diff_sum_all2$r_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all2$r_low[2],ymax =diff_sum_all2$r_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=diff_sum_all2$r_m[2],yend=diff_sum_all2$r_m[2]),color = "black") +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all2$t_verylow[1],ymin =1-diff_sum_all2$t_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all2$t_low[1],ymin =1-diff_sum_all2$t_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=1-diff_sum_all2$t_m[1],yend=1-diff_sum_all2$t_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all2$t_verylow[2],ymin =1-diff_sum_all2$t_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all2$t_low[2],ymin =1-diff_sum_all2$t_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=1-diff_sum_all2$t_m[2],yend=1-diff_sum_all2$t_m[2]),color = "black") +
geom_line(data = All, aes(x = waves,colour = pft,y = r_mean)) +
geom_line(data = All, aes(x = waves,colour = pft,y = 1-t_mean),linetype = 1) +
scale_y_continuous(sec.axis = sec_axis(trans = ~ 1 - 1 * ., name = "Transmittance [-]",breaks = seq(0,0.6,0.2)),
breaks = seq(0,0.6,0.2),expand = c(0,0)) +
geom_hline(yintercept = c(0,1),linetype=3)+
scale_color_manual(values = c("#1E64C8","#137300")) +
labs(y = "Reflectance [-]",
x = "Wavelength [nm]") +
theme_bw() + theme(text = element_text(size = 14),
axis.title.y = element_text(margin = margin(t = 0, r = 10, b = 0, l = 0),hjust=0.25),
axis.title.y.right = element_text(margin = margin(t = 0, r = 0, b = 0, l = 10)),
axis.title.x = element_text(margin = margin(t = 10, r = 0, b = 0, l = 0)))
ggsave(plot = last_plot(),dpi = 300, width = 20,height = 12, filename = file.path("./Figures","Leaf.spectrum.posterior_large_avged.png"),units = "cm")
xmin1 = 400;xmin2=710
xmax1 = 690;xmax2=1000
ggplot() +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all2$r_verylow[1],ymax =diff_sum_all2$r_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all2$r_low[1],ymax =diff_sum_all2$r_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=diff_sum_all2$r_m[1],yend=diff_sum_all2$r_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all2$r_verylow[2],ymax =diff_sum_all2$r_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all2$r_low[2],ymax =diff_sum_all2$r_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=diff_sum_all2$r_m[2],yend=diff_sum_all2$r_m[2]),color = "black") +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all2$t_verylow[1],ymin =1-diff_sum_all2$t_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all2$t_low[1],ymin =1-diff_sum_all2$t_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=1-diff_sum_all2$t_m[1],yend=1-diff_sum_all2$t_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all2$t_verylow[2],ymin =1-diff_sum_all2$t_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all2$t_low[2],ymin =1-diff_sum_all2$t_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=1-diff_sum_all2$t_m[2],yend=1-diff_sum_all2$t_m[2]),color = "black") +
geom_line(data = All, aes(x = waves,colour = pft,y = r_mean)) +
geom_line(data = All, aes(x = waves,colour = pft,y = 1-t_mean),linetype = 1) +
scale_y_continuous(sec.axis = sec_axis(trans = ~ 1 - 1 * ., name = "Transmittance [-]",breaks = seq(0,0.6,0.2)),
breaks = seq(0,0.6,0.2),expand = c(0,0)) +
scale_x_continuous(limits = c(xmin1,xmax2)) +
geom_hline(yintercept = c(0,1),linetype=3)+
scale_color_manual(values = c("#1E64C8","#137300")) +
labs(y = "Reflectance [-]",
x = "Wavelength [nm]") +
theme_bw() + theme(text = element_text(size = 14),
axis.title.y = element_text(margin = margin(t = 0, r = 10, b = 0, l = 0),hjust=0.25),
axis.title.y.right = element_text(margin = margin(t = 0, r = 0, b = 0, l = 10)),
axis.title.x = element_text(margin = margin(t = 10, r = 0, b = 0, l = 0)))
ggsave(plot = last_plot(),dpi = 300, width = 30,height = 20, filename = file.path("./Figures","Leaf.spectrum.posterior_avged.png"),units = "cm")
xmin1 = 450;xmin2=720
xmax1 = 680;xmax2=2500
ggplot() +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all3$r_verylow[1],ymax =diff_sum_all3$r_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all3$r_low[1],ymax =diff_sum_all3$r_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=diff_sum_all3$r_m[1],yend=diff_sum_all3$r_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all3$r_verylow[2],ymax =diff_sum_all3$r_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all3$r_low[2],ymax =diff_sum_all3$r_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=diff_sum_all3$r_m[2],yend=diff_sum_all3$r_m[2]),color = "black") +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all3$t_verylow[1],ymin =1-diff_sum_all3$t_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all3$t_low[1],ymin =1-diff_sum_all3$t_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=1-diff_sum_all3$t_m[1],yend=1-diff_sum_all3$t_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all3$t_verylow[2],ymin =1-diff_sum_all3$t_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all3$t_low[2],ymin =1-diff_sum_all3$t_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=1-diff_sum_all3$t_m[2],yend=1-diff_sum_all3$t_m[2]),color = "black") +
geom_line(data = All, aes(x = waves,colour = pft,y = r_mean)) +
geom_line(data = All, aes(x = waves,colour = pft,y = 1-t_mean),linetype = 1) +
scale_y_continuous(sec.axis = sec_axis(trans = ~ 1 - 1 * ., name = "Transmittance [-]",breaks = seq(0,0.6,0.2)),
breaks = seq(0,0.6,0.2),expand = c(0,0)) +
geom_hline(yintercept = c(0,1),linetype=3)+
scale_color_manual(values = c("#1E64C8","#137300")) +
labs(y = "Reflectance [-]",
x = "Wavelength [nm]") +
theme_bw() + theme(text = element_text(size = 14),
axis.title.y = element_text(margin = margin(t = 0, r = 10, b = 0, l = 0),hjust=0.25),
axis.title.y.right = element_text(margin = margin(t = 0, r = 0, b = 0, l = 10)),
axis.title.x = element_text(margin = margin(t = 10, r = 0, b = 0, l = 0)))
ggsave(plot = last_plot(),dpi = 300, width = 20,height = 12, filename = file.path("./Figures","Leaf.spectrum.posterior_large_avged2.png"),units = "cm")
xmin1 = 400;xmin2=710
xmax1 = 690;xmax2=1000
ggplot() +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all3$r_verylow[1],ymax =diff_sum_all3$r_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymin= diff_sum_all3$r_low[1],ymax =diff_sum_all3$r_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=diff_sum_all3$r_m[1],yend=diff_sum_all3$r_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all3$r_verylow[2],ymax =diff_sum_all3$r_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymin= diff_sum_all3$r_low[2],ymax =diff_sum_all3$r_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=diff_sum_all3$r_m[2],yend=diff_sum_all3$r_m[2]),color = "black") +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all3$t_verylow[1],ymin =1-diff_sum_all3$t_veryhigh[1]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin1,xmax1),ymax= 1-diff_sum_all3$t_low[1],ymin =1-diff_sum_all3$t_high[1]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin1,xend=xmax1,y=1-diff_sum_all3$t_m[1],yend=1-diff_sum_all3$t_m[1]),color = "black") +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all3$t_verylow[2],ymin =1-diff_sum_all3$t_veryhigh[2]),fill ="grey",alpha = 0.4) +
geom_ribbon(aes(x = c(xmin2,xmax2),ymax= 1-diff_sum_all3$t_low[2],ymin =1-diff_sum_all3$t_high[2]),fill ="darkgrey",alpha = 0.4) +
geom_segment(aes(x = xmin2,xend=xmax2,y=1-diff_sum_all3$t_m[2],yend=1-diff_sum_all3$t_m[2]),color = "black") +
geom_line(data = All, aes(x = waves,colour = pft,y = r_mean)) +
geom_line(data = All, aes(x = waves,colour = pft,y = 1-t_mean),linetype = 1) +
scale_y_continuous(sec.axis = sec_axis(trans = ~ 1 - 1 * ., name = "Transmittance [-]",breaks = seq(0,0.6,0.2)),
breaks = seq(0,0.6,0.2),expand = c(0,0)) +
scale_x_continuous(limits = c(xmin1,xmax2)) +
geom_hline(yintercept = c(0,1),linetype=3)+
scale_color_manual(values = c("#1E64C8","#137300")) +
labs(y = "Reflectance [-]",
x = "Wavelength [nm]") +
theme_bw() + theme(text = element_text(size = 14),
axis.title.y = element_text(margin = margin(t = 0, r = 10, b = 0, l = 0),hjust=0.25),
axis.title.y.right = element_text(margin = margin(t = 0, r = 0, b = 0, l = 10)),
axis.title.x = element_text(margin = margin(t = 10, r = 0, b = 0, l = 0)))
ggsave(plot = last_plot(),dpi = 300, width = 30,height = 20, filename = file.path("./Figures","Leaf.spectrum.posterior_avged2.png"),units = "cm")
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