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iStatut = c('0'='inconnu',
'1'='station avec signification hydrologique',
'2'='station sans signification hydrologique',
'3'="station d'essai")
iFinalite = c('0'='inconnue',
'3'="hydromtrie gnrale et alerte de crue",
'6'="suivi d'tiage",
'7'='bassin exprimental',
'1'='une chelle',
'2'='deux chelles, station mre',
'3'='deux chelles, station fille',
'4'='dbits mesurs',
'5'='virtuelle')
iInfluence = c('0'='inconnue',
'1'='nulle ou faible',
iDebit = c('0'='reconstitu',
'1'="rel (prise en compte de l'eau rajoute ou retire du bassin selon amnagements)",
iQBE = c('0'='qualit basses eaux inconnue',
'1'='qualit basses eaux bonne',
'2'='qualit basses eaux douteuse')
iQME = c('0'='qualit moyennes eaux inconnue',
'1'='qualit moyennes eaux bonne',
'2'='qualit moyennes eaux douteuse')
iQHE = c('0'='qualit hautes eaux inconnue',
'1'='qualit hautes eaux bonne',
'2'='qualit hautes eaux douteuse')
# Get the selection of data from the 'Liste-station_RRSE' file and the BanqueHydro directory
get_selection = function (computer_data_path, listdir, listname,
cnames=c('code','station', 'BV_km2', 'axe_principal_concerne', 'longueur_serie', 'commentaires', 'choix'),
# Get the file path to the data
list_path = file.path(computer_data_path, listdir, listname)
sample_data = read_docx(list_path)
content = docx_summary(sample_data)
table_cells <- content %>% filter(content_type == "table cell")
table_data <- table_cells %>% filter(!is_header) %>% select(row_id, cell_id, text)
# Split data into individual columns
splits <- split(table_data, table_data$cell_id)
splits <- lapply(splits, function(x) x$text)
# Combine columns back together in wide format
for (c in c_num) {
df_selec$c = as.numeric(sub(",", ".",
pull(df_selec, c)))
selec = (df_selec$choix == 'A garder' | df_selec$choix == 'Ajout')
filename=paste(df_selec$code, '_HYDRO_QJM.txt', sep=''),
ok=selec
)
return (df_selec)
}
# Example
# df_selec = get_selection(
# "/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/data",
# "Liste-station_RRSE.docx",
# cnames=c('code','station',
# 'BV_km2',
# 'axe_principal_concerne',
# 'longueur_serie',
# 'commentaires',
# 'choix'),
# Extraction of metadata
extractBH_meta = function (computer_data_path, filedir, filename, verbose=TRUE) {
# Convert the filename in vector
# If the filename is 'all' or regroup more than one filename
# Create a filelist to store all the filename
# Get all the filename in the data directory selected
filelist_tmp = list.files(file.path(computer_data_path,
# For all the filename in the directory selected
# If the filename extention is 'txt'
# Store the filename in the filelist
# If the filename regroup more than one filename
# The filelist correspond to the filename
}
# Create a blank data frame
# For all the file in the filelist
# Concatenate by raw data frames created by this function when filename correspond to only one filename
df_meta = rbind(df_meta,
extractBH_meta(computer_data_path,
# Set the rownames by default (to avoid strange numbering)
# Get the filename from the vector
filename = filename[1]
print(paste("extraction of BH info for file :", filename))
file_path = file.path(computer_data_path, filedir, filename)
if (file.exists(file_path) & substr(file_path, nchar(file_path), nchar(file_path)) != '/') {
metatxt = c(readLines(file_path, n=41, encoding="latin1"))
# Create a tibble with all the metadata needed
df_meta =
tibble(code=trimws(substr(metatxt[11], 38, nchar(metatxt[11]))),
nom=trimws(substr(metatxt[12], 39, nchar(metatxt[12]))),
territoire=trimws(substr(metatxt[13], 39, nchar(metatxt[13]))),
L93X=as.numeric(substr(metatxt[16], 38, 50)),
L93Y=as.numeric(substr(metatxt[16], 52, 63)),
surface_km2=as.numeric(substr(metatxt[19], 38, 50)),
statut=iStatut[trimws(substr(metatxt[26], 38, 50))],
finalite=iFinalite[trimws(substr(metatxt[26], 52, 56))],
type=iType[trimws(substr(metatxt[26], 58, 58))],
influence=iInfluence[trimws(substr(metatxt[26], 60, 60))],
debit=iDebit[trimws(substr(metatxt[26], 62, 62))],
QBE=iQBE[trimws(substr(metatxt[26], 72, 72))],
QME=iQME[trimws(substr(metatxt[26], 74, 74))],
QHE=iQHE[trimws(substr(metatxt[26], 76, 76))],
} else {
print(paste('filename', file_path, 'do not exist'))
return (NULL)
}
# "/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/data",
# '',
# c('H5920011_HYDRO_QJM.txt', 'K4470010_HYDRO_QJM.txt'))
extractBH_data = function (computer_data_path, filedir, filename, verbose=TRUE) {
# If the filename is 'all' or regroup more than one filename
# Create a filelist to store all the filename
# Get all the filename in the data directory selected
filelist_tmp = list.files(file.path(computer_data_path,
# For all the filename in the directory selected
# If the filename extention is 'txt'
# Store the filename in the filelist
# If the filename regroup more than one filename
# The filelist correspond to the filename
# For all the file in the filelist
# Concatenate by raw data frames created by this function when filename correspond to only one filename
extractBH_data(computer_data_path,
filedir,
f))
# Set the rownames by default (to avoid strange numbering)
# Get the filename from the vector
print(paste("extraction of BH data for file :", filename))
file_path = file.path(computer_data_path, filedir, filename)
if (file.exists(file_path) & substr(file_path, nchar(file_path), nchar(file_path)) != '/') {
# Extract the data as a data frame
df_data = read.table(file_path,
header=TRUE,
na.strings=c(' -99', ' -99.000'),
sep=';',
# Extract all the metadata for the station
df_meta = extractBH_meta(computer_data_path, filedir, filename, verbose=FALSE)
# Create a tibble with the date as Date class and the code of the station
df_data = tibble(Date=as.Date(as.character(df_data$Date),
format="%Y%m%d"),
Qm3s=df_data$Qls * 1E-3,
df_data[-1:-2],
code=code)
return (df_data)
} else {
print(paste('filename', file_path, 'do not exist'))
return (NULL)
}
# "/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/data",
# '',
# c('H5920011_HYDRO_QJM.txt', 'K4470010_HYDRO_QJM.txt'))