###### A MODIFIER ######


# Path to the data
computer_data_path = 
    "/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/data"
    # "C:\\Users\\louis.heraut\\Documents\\CDD_stationnarite\\data"
  
# Work path
computer_work_path = 
    "/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/ASH"
    # "C:\\Users\\louis.heraut\\Documents\\CDD_stationnarite\\ASH"


### BANQUE HYDRO ###
# Path to the directory where BH data is stored
BHfiledir = 
    # ""
    "BanqueHydro_Export2021"

## Manual selection ##
# Name of the file that will be analysed from the BH directory
BHfilename =
    # ""
    c("H5920011_HYDRO_QJM.txt", "K4470010_HYDRO_QJM.txt")
    # "all"

## Or list selection ##
# Path to the list file of BH data that will be analysed
BHlistdir = 
    ""

BHlistname = 
    ""
    # "Liste-station_RRSE.docx" 
    

### NIVALE ###
# Path to the directory where NV data is stored
NVfiledir = 
    ""
    # "France207"

# Name of the file that will be analysed from the NV directory
NVfilename = 
    ""
    # "all"


# Path to the list file of metadata about station that will be analysed
NVlistdir =
    ""

NVlistname = 
    ""
    # "liste_bv_principaux_global.txt"


### TREND ANALYSIS ###
# Time period to analyse
period = c("1960-01-01","2019-12-31")
# period = c("1960-01-01","2020-01-01")



########################


# FILE STRUCTURE #
# Set working directory
setwd(computer_work_path)

# Sourcing R file
source('processing/extractBH.R')
source('processing/extractNV.R')
source('processing/format.R')
source('processing/analyse.R')
source('plotting/panel.R')
# source('plotting/layout.R')

# Usefull library


# Result directory
resdir = file.path(computer_work_path, 'results')
if (!(file.exists(resdir))) {
  dir.create(resdir)
}
print(paste('resdir :', resdir))

# Figure directory
figdir = file.path(computer_work_path, 'figures')
if (!(file.exists(figdir))) {
  dir.create(figdir)
}
print(paste('figdir :', figdir))


# BANQUE HYDRO #
# Get only the selected station from a list station file
if (BHlistname != ""){
    df_selec = get_selection(computer_data_path, 
                             BHlistdir,
                             BHlistname,
                             cnames=c('code',
                                      'station', 
                                      'BV_km2',
                                      'axe_principal_concerne',
                                      'longueur_serie',
                                      'commentaires',
                                      'choix'), 
                             c_num=c('BV_km2',
                                      'longueur_serie'))

    BHfilename = df_selec[df_selec$ok,]$filename
}

# Extract metadata about selected stations
df_meta_BH = extractBH_meta(computer_data_path, BHfiledir, BHfilename)

# Extract data about selected stations
df_data_BH = extractBH_data(computer_data_path, BHfiledir, BHfilename)


# NIVALE #
# Extract metadata about selected stations
df_meta_NV = extractNVlist_meta(computer_data_path, NVfiledir, NVlistdir, NVlistname)
### /!\ missing station info ###

# Extract data about selected stations
df_data_NV = extractNV_data(computer_data_path, NVfiledir, NVfilename)


# JOIN #
df_join = join(df_data_BH, df_data_NV, df_meta_BH, df_meta_NV)
df_data = df_join$data
df_meta = df_join$meta


# ANALYSE #
# Compute gap parameters for stations
# df_lac = get_lacune(df_data, df_meta)


# QA TREND #
res_QAtrend = get_QAtrend(df_data, period)

# QMNA TREND #
res_QMNAtrend = get_QMNAtrend(df_data, period)

# VCN10 TREND #
res_VCN10trend = get_VCN10trend(df_data, df_meta, period)


# TIME PANEL #
# Plot time panel of debit by stations
panel(list(df_data, res_QAtrend$data, res_QMNAtrend$data,
           res_VCN10trend$data), 
      df_meta=df_meta, 
      figdir=figdir,
      df_trend=list(NULL, res_QAtrend$trend, res_QMNAtrend$trend,
                    res_VCN10trend$trend), 
      type=list('time', '', '', ''),
      missRect=list(TRUE, TRUE, TRUE, TRUE),
      )

# panel(df_data, df_meta=df_meta, figdir=figdir, missRect=TRUE, type='sqrt')
### /!\ Removed 185 row(s) containing missing values (geom_path) -> remove NA ###