Lab Reflectance spectra of hand samples (optic fiber) from Puig del Roser

• Agustin.Lobo@geo3bcn.csic.es
• 20230726
• 20230721 Lab spectra acquired with Valentin
  • FS3, optic fiber + 8º forelens and ASD PROLAMP illuminator

require(ggplot2)
require(plotly)
library(RColorBrewer)
library(plyr)
require(prospectr)
#library(soilspec)
#NOTE: there is also asdreader::get_spectra() (see EspCrater_FS3_nb.Rmd)

# > getwd()
# [1] "/media/alobo/DecepNTFS2/HSI_Lab/Testllum_20230717/Rtestllum_20230717"

dirRSpect <- "/home/alobo/owncloudRSpect/RSpect"
dirdat <- "../EspCrater_HandSamples/FS3/EspCraterSamples20230721"

1. Reading data

#inital list of files and times to sort them and write csv:
#f <- list.files(dirdat, patt=glob2rx("*.asd"))
#ft <- file.mtime(file.path(dirdat,f))
#df <- data.frame(file=f, time=ft)
#df <- df[order(df$time),]
#head(df)
#write.csv(df, file=file.path(dirdat,"labNoprobe20230717.csv"))
#"labNoprobe20230717.csv" edited in LibreOffice Calc

f <- read.csv(file.path(dirdat,"labNoprobe20230717.csv"), stringsAsFactors = FALSE)
f$ID <- paste(f$sample,f$point,f$replicate, sep="_")

2. Build data frame (long format)

#The following takes a long time, it is saved and read the rda
#d.lf <-  NULL
#for (i in 1:nrow(f)) {
#  r <- readASD(file.path(dirdat,f$file[i]), out_format = 'list')[[1]]$radiance
#  rf <- readASD(file.path(dirdat,f$file[i]), out_format = 'list')[[1]]$reference
#  s <- readASD(file.path(dirdat,f$file[i]), out_format = 'list')[[1]]$reflectance
#  w <- readASD(file.path(dirdat,f$file[i]), out_format = 'list')[[1]]$wavelength
#  sc <- spliceCorrection(s,wav=w, splice = c(1000, 1800))
#  d.lf <- rbind(d.lf,data.frame(f[i,],w,r,rf,s,sc))
#}
#head(d.lf,3)
#tail(d.lf)
#d.lf <-  d.lf[ d.lf$sample !=0,]
#EspCratHandSamplesNoProbe.lf <- d.lf
#save(EspCratHandSamplesNoProbe.lf, file= "EspCratHandSamplesNoProbe.lf.rda")
load("EspCratHandSamplesNoProbe.lf.rda")
d.lf <- EspCratHandSamplesNoProbe.lf
head(d.lf,3)

#tail(d.lf)

3. Reflectance Spectra

#glabnoprobe <- ggplot(data=d.lf[d.lf$sample!="backg",],
#                      aes(label1=ID,label2=point, label3=replicate)) +
#  geom_line(aes(x=w, y=sc, color=sample, group=file), linewidth=0.3) +
#  xlab("Wavelength") + ylab("Reflectance") + 
#  theme(legend.position="none") +
#  ggtitle("Espai Crater: lab (optic fiber) Reflectance spectra")
#  #scale_color_brewer(palette = "Set1")

#d.lf is too large. We average replicates
a <- ddply(d.lf,c("sample", "point","w"), summarise, sc = mean(sc))
a$ID <- paste0(a$sample,"_",a$point)
d.lf <- a
glabnoprobe <- ggplot(data=d.lf[d.lf$sample!="backg",],
                      aes(label1=ID,label2=point)) +
  geom_line(aes(x=w, y=sc, color=sample), linewidth=0.3) +
  xlab("Wavelength") + ylab("Reflectance") + 
  theme(legend.position="none") +
  ggtitle("Espai Crater: lab (optic fiber) Reflectance spectra")

ggplotly(glabnoprobe + facet_wrap(~sample))

NA

ggplotly(glabnoprobe + facet_wrap(~sample, scales="free_y"))