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computer_data_path =
"/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/data"
# "C:\\Users\\louis.heraut\\Documents\\CDD_stationnarite\\data"
computer_work_path =
"/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/ASH"
# "C:\\Users\\louis.heraut\\Documents\\CDD_stationnarite\\ASH"
## Manual selection ##
# Name of the file that will be analysed from the BH directory
# ""
c("H5920011_HYDRO_QJM.txt")#, "K4470010_HYDRO_QJM.txt")
# Path to the directory where NV data is stored
NVfiledir =
# Name of the file that will be analysed from the NV directory
NVfilename =
# Path to the list file of information about station that will be analysed
NVlistdir =
""
NVlistname =
### TREND ANALYSIS ###
# Time period to analyse
period = c("1960-01-01","2019-12-31")
# period = c("1960-01-01","2020-01-01")
# Set working directory
setwd(computer_work_path)
# Sourcing R file
source('processing/extractBH.R')
source('processing/extractNV.R')
source('plotting/panel.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)
}
# Get only the selected station from a list station file
cnames=c('code',
'station',
'BV_km2',
'axe_principal_concerne',
'longueur_serie',
'commentaires',
'choix'),
# Extract information about selected stations
df_info_BH = extractBH_info(computer_data_path, BHfiledir, BHfilename)
# Extract data about selected stations
df_data_BH = extractBH_data(computer_data_path, BHfiledir, BHfilename)
# NIVALE #
# Extract information about selected stations
df_info_NV = extractNVlist_info(computer_data_path, NVfiledir, NVlistdir, NVlistname)
# Extract data about selected stations
df_data_NV = extractNV_data(computer_data_path, NVfiledir, NVfilename)
df_join = join(df_data_BH, df_data_NV, df_info_BH, df_info_NV)
df_data = df_join$data
df_info = df_join$info
# Plot time panel of debit by stations
# panel(df_data, df_info, figdir, "")
# panel(df_data, df_info, figdir, "", is_sqrt=TRUE)
### /!\ Removed 185 row(s) containing missing values (geom_path) -> remove NA ###
# Compute gap parameters for stations
# 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_info, period)