flir

# Required packages to parallelize
library(parallel)
library(foreach)
library(doParallel)

# Number of cores
n.core<-detectCores()-1

# Starting parallel
cl <- makeCluster(n.core, output = "")
registerDoParallel(cl)

#Declaring variables
treatments<-c("T1","T2","T3")
graphColorMax<-c("blue", "red", "green", "violet", "orange", "black", "brown", "dark blue")

#Choosing folders
folder_input<-choose.dir(default = "D:/", caption = "Select INPUT folder")
folder_output<-choose.dir(default = folder_input, caption = "Select OUTPUT folder")




foreach (i=1:length(treatments), .combine = "c", .inorder=FALSE, .packages=c("raster", "rasterVis","lattice", "ThermStats", "Thermimage", "readxl","tiff", "openxlsx", "stringr","moments", "viridis", "viridisLite" )) %dopar% {

#Importing file list and adjusting
flir_file_list2 <- read_excel(paste0(folder_output,"\\",treatments[i],"FLIR_file.xlsx"))
flir_file_list2$photo_name<-paste0(substr(flir_file_list2$photo_name,1,9))
flir_file_list2<-as.data.frame(flir_file_list2)

flir_file_list2$photo_name<-as.numeric(flir_file_list2$photo_name)
flir_file_list2$photo_name<-as.integer(flir_file_list2$photo_name)


#Batch extraction from images and saving results
flir_rawPICS<-batch_extract(in_dir=paste0(folder_input,"\\",treatments[i]),
                        write_results=TRUE,
                        file_name = paste0(treatments[i],"_flir_batch_converted_",Sys.Date()),
                        inc=flir_file_list,
                        out_dir=folder_output,
                        exiftoolpath="D:/AgriSearchInnovations/Comuni/termocamera/Exiftools/")


PIC_index <-match(
 names(flir_rawPICS$raw_dat),
 flir_file_list2$photo_name)


#onversion from avalues to temperatures
flir_converted<-batch_convert(flir_rawPICS$raw_dat,
  E = 0.98,
  OD = flir_file_list2$object_distance[PIC_index],
  RTemp = flir_file_list2$ambient_temp[PIC_index],
  ATemp = flir_file_list2$ambient_temp[PIC_index],
  IRWTemp = flir_file_list2$ambient_temp[PIC_index],
  IRT = 1,
  RH = flir_file_list2$ambient_humidity[PIC_index],
  PR1 = flir_rawPICS$camera_params$PlanckR1,
  PB = flir_rawPICS$camera_params$PlanckB,
  PF = flir_rawPICS$camera_params$PlanckF,
  PO = flir_rawPICS$camera_params$PlanckO,
  PR2 = flir_rawPICS$camera_params$PlanckR2,
  write_results = TRUE,
  out_dir = folder_output,
  file_name = paste0(treatments[i],"_flir_batch_converted_raw2temp_",Sys.Date())
)


# Average matrices in list

averageFLIR<-average_by_group(metadata = flir_file_list2,
                              img_list =flir_converted,
                              id = "photo_name",
                              grouping_var = "spatial_rep")





# Coerce matrix list to raster stack
stackFLIR<-stack_imgs(flir_converted)
saveRDS(stackFLIR, file = paste0(folder_output,"\\",treatments[i],"_stackFLIR"))

# Average in raster stack
averageFLIRstack<-average_by_group(metadata = flir_file_list2,
                              img_list =stackFLIR,
                              id = "photo_name",
                              grouping_var = "spatial_rep")


saveRDS(averageFLIRstack, file = paste0(folder_output,"\\",treatments[i],"_averageFLIRstack.rds"))


# Export stack image (average of N picture by grouping var
tiff(   paste0(folder_output,"\\",treatments[i],"_stack_",Sys.Date(),".tiff"),
    width = 1080, height = 1440, units = "px", compression ="lzw", res=300)
raster::plot(averageFLIRstack, col=heat.colors(round(max(averageFLIRstack[])-min(averageFLIRstack[]))*5))
dev.off()

#Export histogram density picture
tiff(   paste0(folder_output,"\\",treatments[i],"_histogram_density_",Sys.Date(),".tiff"),
    width = 1440, height = 1080, units = "px", compression ="lzw", res=300)

averageFLIRstackhist<-raster::hist(averageFLIRstack,
     freq=FALSE,
     breaks=seq(from=round(min(averageFLIRstack[]), digits=1)-0.1,to=round(max(averageFLIRstack[]), digits=1)+0.1,by=0.1),
     ylim=c(0,1.0),
        xlab="average temperature bin in °C",
        ylab="bin density",
     main=paste0(treatments[i]," temperature density distribution"),
     col=inferno(length(seq(from=round(min(averageFLIRstack[]), digits=1)-0.1,to=round(max(averageFLIRstack[]), digits=1)+0.1,by=0.1))))
dev.off()

#Export histogram table
averageFLIRstackhist<-raster::hist(averageFLIRstack,
     freq=FALSE,
     breaks=seq(from=0,to=100,by=0.1))

write.xlsx(
    data.frame(Mids=averageFLIRstackhist$mids, Density=averageFLIRstackhist$density,Counts=averageFLIRstackhist$counts),
    file=paste0(folder_output,"\\",treatments[i],"_histogram_density_",Sys.Date(),".xlsx"),
    sheetName=treatments[i], asTable = TRUE )

}


stopCluster(cl)