#######################################################################################################################################################################
# This program is meant to take the Click1 and Click2 values determined by the TTimes.py program and cut out everything that is not within these values.

# Note that this program assumes that you have the "SavedData_formatted_NoNeg.csv" file in a directory with only the files contained within the file. If you include
# files in the directory that are not in the "SavedData_formatted_NoNeg.csv" file, then the program will give you an error when it encounters a file that is not in the
# SavedData.csv file. 
#######################################################################################################################################################################

library(tidyverse)

# create the output folder
path_var <- r"(E:\12.8.2021\s0201\ck\Analysis\Pie_Charts\Sampling_and_Accommodation\Lifetime_of_Initial_Sampling_Events\SavedData)"

dir.create(paste(toString(path_var), "T1_to_T2_Synchronized", sep = "///"), showWarnings = FALSE)
output_dir <- paste(path_var, "T1_to_T2_Synchronized", sep = "\\")


# get the names of the input files with their full path
files <- list.files(path_var, "pairProfile", full.name = TRUE)
savedData <- read.csv(list.files(path_var, "SavedData.csv", full.name = TRUE), header = FALSE, sep = ",")


# loop through all the input files
for (file in files) {
  
  # read the file, specify the correct separator
  data <- read.csv(file, header = FALSE, sep = ",")
  
  #Use the select function in Dplyr to select only the V1 and V2 columns
  varSelected_data <- select(data, V1, V2)
  
  #Use the slice function in Dplyr to cut coordinate row out of the dataframe
  cut_data <- slice(varSelected_data, 2:nrow(varSelected_data))
  
  #Use the filter and grepl function in Dplyr to select the row that has the same filename as the current file
  formatted_Name <- strsplit(file, "/")[[1]][2]
  dummyTest2 <- dplyr::filter(savedData, grepl(formatted_Name, V13))
  
  #Use the pull function in Dplyr to obtain the T1 and T2 values that correspond to the current file
  T1_dummyTest2 <- pull(dummyTest2, V3)
  T2_dummyTest2 <- pull(dummyTest2, V4)
  
  #Cut the current file according to the (T1 - certain number of frames) and (T2 + certain number of frames) values. This can be changed depending on how you want to display the data.
  
  synch_data <- slice(cut_data, (T1_dummyTest2):(T2_dummyTest2))
  
  #Define the new file name
  
  outfile <- paste(strsplit(formatted_Name, ".csv")[[1]][1], "T1_to_T2_Synchronized", sep = "-")
  outfile <- paste(outfile, "csv", sep = ".")
  
  # write the file. 
  write.table(synch_data, paste(output_dir, outfile, sep = "\\"), sep = ",", col.names = FALSE, row.names = FALSE, quote = FALSE)
  
}