script.R 4.04 KiB
###### 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 #
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# 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') # 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 # TIME PANEL #
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# Plot time panel of debit by stations # panel(df_data, df_meta, figdir, "") # panel(df_data, df_meta, figdir, "", is_sqrt=TRUE) ### /!\ Removed 185 row(s) containing missing values (geom_path) -> remove NA ### # ANALYSE # # Compute gap parameters for stations # df_lac = get_lacune(df_data, df_meta) # QA TREND # res_QAtrend = get_QAtrend(df_data, period) panel(df_data=res_QAtrend$data, df_meta=df_meta, df_trend=res_QAtrend$trend, p_threshold=0.1, figdir=figdir, filedir_opt='QA', variable='QA') # QMNA TREND # # res_QMNAtrend = get_QMNAtrend(df_data, period) # VCN10 TREND # # res_VCN10trend = get_VCN10trend(df_data, df_meta, period) # panel(df_data=res_VCN10trend$data, # df_meta=df_meta, # df_trend=res_VCN10trend$trend, # figdir=figdir, filedir="VCN10")