############ 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 (it needs to end with '/ASH' directory) 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 from the work path filedir = # "" "BanqueHydro_Export2021" ### MANUAL SELECTION ### # Name of the file that will be analysed from the AG directory filename = # "" # c( # "S2235610_HYDRO_QJM.txt", # "P1712910_HYDRO_QJM.txt", # "P0885010_HYDRO_QJM.txt", # "O5055010_HYDRO_QJM.txt", # "Q7002910_HYDRO_QJM.txt" # ) c("S4214010_HYDRO_QJM.txt", "O0384010_HYDRO_QJM.txt", "Q7002910_HYDRO_QJM.txt") ### AGENCE EAU ADOUR GARONNE SELECTION ### # Path to the list file of AG data that will be analysed AGlistdir = "" AGlistname = "" # "Liste-station_RRSE.docx" ### NIVALE SELECTION ### # Path to the list file of metadata about station that will be analysed NVlistdir = "" NVlistname = "" # "nival_selection.txt" ### TREND ANALYSIS ### # Time period to analyse periodAll = c("1800-01-01", "2019-12-31") periodSub = c("1968-01-01", "2019-12-31") trend_period = list(periodAll, periodSub) # Time period to mean period1 = c("1968-01-01", "1994-12-31") period2 = c("1995-01-01", "2019-12-31") mean_period = list(period1, period2) # p value p_thresold = 0.1 #c(0.01, 0.05, 0.1) ### MAP ### fr_shpdir = 'map/france' fr_shpname = 'gadm36_FRA_0.shp' bs_shpdir = 'map/bassin' bs_shpname = 'BassinHydrographique.shp' rv_shpdir = 'map/river' rv_shpname = 'CoursEau_FXX.shp' #################################### # FILE STRUCTURE # # Set working directory setwd(computer_work_path) # Sourcing R file source('processing/extract.R', encoding='latin1') source('processing/format.R', encoding='latin1') source('processing/analyse.R', encoding='latin1') source('plotting/panel.R', encoding='latin1') source('plotting/layout.R', encoding='latin1') # 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)) # Initialization of null data frame if there is no data selected df_data_AG = NULL df_data_NV = NULL df_meta_AG = NULL df_meta_NV = NULL # AGENCE EAU ADOUR GARONNE SELECTION # if (AGlistname != ""){ # Get only the selected station from a list station file df_selec_AG = get_selection_AG(computer_data_path, AGlistdir, AGlistname, cnames=c('code', 'station', 'BV_km2', 'axe_principal_concerne', 'longueur_serie', 'commentaires', 'choix'), c_num=c('BV_km2', 'longueur_serie')) # Get filenames of the selection filename = df_selec_AG[df_selec_AG$ok,]$filename ##### # filename = filename[(1+30):(16+30)] ##### # Extract metadata about selected stations df_meta_AG = extract_meta(computer_data_path, filedir, filename) # Extract data about selected stations df_data_AG = extract_data(computer_data_path, filedir, filename) } # NIVALE SELECTION # if (NVlistname != ""){ # Get only the selected station from a list station file df_selec_NV = get_selection_NV(computer_data_path, NVlistdir, NVlistname) # Get filenames of the selection filename = df_selec_NV[df_selec_NV$ok,]$filename ##### # filename = filename[(1+20):(16+20)] ##### # Extract metadata about selected stations df_meta_NV = extract_meta(computer_data_path, filedir, filename) # Extract data about selected stations df_data_NV = extract_data(computer_data_path, filedir, filename) } # MANUAL SELECTION # if (AGlistname == "" & NVlistname == "") { # Extract metadata about selected stations df_meta_AG = extract_meta(computer_data_path, filedir, filename) # Extract data about selected stations df_data_AG = extract_data(computer_data_path, filedir, filename) } # JOIN # # Make the join df_join = join(df_data_AG, df_data_NV, df_meta_AG, 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=trend_period, p_thresold=p_thresold) # QMNA TREND # res_QMNAtrend = get_QMNAtrend(df_data, period=trend_period, p_thresold=p_thresold) # VCN10 TREND # res_VCN10trend = get_VCN10trend(df_data, df_meta, period=trend_period, p_thresold=p_thresold) # df_break = get_break(res_QAtrend$data, df_meta) # df_break = get_break(res_QMNAtrend$data, df_meta) # df_break = get_break(res_VCN10trend$data, df_meta) # histogram(df_break$Date, df_meta, # figdir=figdir) # cumulative(df_break$Date, df_meta, dyear=8, # figdir=figdir) # TIME PANEL # # Plot time panel of debit by stations # panels_layout(list(df_data, df_data), # layout_matrix=c(1, 2), # df_meta=df_meta, # missRect=list(TRUE, TRUE), # type=list('Q', 'sqrt(Q)'), # info_header=TRUE, # time_header=NULL, # var_ratio=3, # figdir=figdir, # filename_opt='time') panels_layout(list(res_QAtrend$data, res_QMNAtrend$data, res_VCN10trend$data), layout_matrix=c(1, 2, 3), df_meta=df_meta, df_trend=list(res_QAtrend$trend, res_QMNAtrend$trend, res_VCN10trend$trend), type=list(bquote(Q[A]), bquote(Q[MNA]), bquote(V[CN10])), missRect=list(TRUE, TRUE, TRUE), trend_period=trend_period, mean_period=mean_period, info_header=TRUE, time_header=df_data, info_ratio=2, time_ratio=2, var_ratio=3, computer_data_path=computer_data_path, fr_shpdir=fr_shpdir, fr_shpname=fr_shpname, bs_shpdir=bs_shpdir, bs_shpname=bs_shpname, rv_shpdir=rv_shpdir, rv_shpname=rv_shpname, figdir=figdir, filename_opt='') # map_panel(computer_data_path, # fr_shpdir, fr_shpname, # bs_shpdir, bs_shpname, # rv_shpdir, rv_s hpname) ### /!\ Removed 185 row(s) containing missing values (geom_path) -> remove NA ###