diff --git a/plotting/panel.R b/plotting/panel.R
index 79a330b60550e03cf6e1518396aa80e03b87eca1..ba163204dbdc2e337b6aa46402188d5132f23941 100644
--- a/plotting/panel.R
+++ b/plotting/panel.R
@@ -1,15 +1,24 @@
# Usefull library
library(ggplot2)
+library(gridExtra)
width = 30
height = 14
dpi = 100
# Time panel
-panel = function (df_data, df_info, figdir, filedir, span=Inf) {
+panel = function (df_data, df_info, figdir, filedir, is_sqrt=FALSE) {
+
+ outfile = "Panels"
+
+ if (is_sqrt) {
+ df_data[, 'Qm3s'] = apply(df_data[, 'Qm3s'], 1, sqrt)
+ outfile = paste(outfile, '_sqrt', sep='')
+ }
+ outfile = paste(outfile, '.pdf', sep='')
+
# If there is not a dedicated figure directory it creats one
- # outdir = file.path(figdir, filedir, paste('span_', as.character(span), '_years', sep=''))
outdir = file.path(figdir, filedir, sep='')
if (!(file.exists(outdir))) {
dir.create(outdir)
@@ -18,28 +27,32 @@ panel = function (df_data, df_info, figdir, filedir, span=Inf) {
# Get all different stations code
Code = levels(factor(df_info$code))
+ # Create a blank list in order to store plots
+ plots = list()
+
for (code in Code) {
- # Create name for the figure file
- outfile = paste('Panel_', code, '.pdf', sep='')
+ # Print code of the station for the current plotting
print(paste("Plotting for sation :", code))
df_data_code = df_data[df_data$code==code,]
# Plot
- plot =
- ggplot(df_data_code, aes(x=Date, y=Qls)) +
+ p = ggplot(df_data_code, aes(x=Date, y=Qm3s)) +
geom_line()
+
+ # Store
+ plots = append(plots, list(p))
- # Save the plot
- ggsave(path=outdir,
- filename=outfile,
- plot=plot,
- width=width,
- height=height,
- dpi=dpi,
- units='cm')
}
-
+
+ # Saving
+ ggsave(path=outdir,
+ filename=outfile,
+ plot=marrangeGrob(plots, nrow=1, ncol=1),
+ width=29.7, height=21, units='cm', dpi=100
+ )
+
+
}
diff --git a/processing/extract.R b/processing/extract.R
index 4f7f383f2191aeaff1fb9621336a3020c337e120..a636b77fefda5196abc2a3a88ee58cd275689ec6 100644
--- a/processing/extract.R
+++ b/processing/extract.R
@@ -57,24 +57,6 @@ get_selection = function (computer_data_path, listdir, listname,
# Get the file path to the data
list_path = file.path(computer_data_path, listdir, listname)
- # Extract the data as a data frame
- # df_list = read.table(list_path,
- # header=TRUE,
- # sep=';',
- # dec=',',
- # quote='',
- # skip=0,
- # nrows=3,
- # strip.white=TRUE,
- # comment.char="",
- # colClasses=c("character",
- # "character",
- # "numeric",
- # "character",
- # "numeric",
- # "character",
- # "character"))
-
sample_data = read_docx(list_path)
content = docx_summary(sample_data)
table_cells <- content %>% filter(content_type == "table cell")
@@ -285,7 +267,7 @@ extract_data = function (computer_data_path, filedir, filename, verbose=TRUE) {
header=TRUE,
na.strings=c(' -99', ' -99.000'),
sep=';',
- skip=41)[,1:2]
+ skip=41)
# Extract all the information for the station
df_info = extract_info(computer_data_path, filedir, filename, verbose=FALSE)
@@ -294,7 +276,8 @@ extract_data = function (computer_data_path, filedir, filename, verbose=TRUE) {
# 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$Date),
format="%Y%m%d"),
- df_data[-1],
+ Qm3s=df_data$Qls * 1E-3,
+ df_data[-1:-2],
code=code)
return (df_data)
diff --git a/script.R b/script.R
index 6a357f1ead97ebd77487adfb28c73442b8c63eb3..37994b7d7d808f5352d678888f4dd5ab1c9ff9e8 100644
--- a/script.R
+++ b/script.R
@@ -1,5 +1,5 @@
-### A MODIFIER ###
+###### A MODIFIER ######
# Path to the data
computer_data_path =
@@ -11,32 +11,35 @@ computer_work_path =
"/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/ASH"
# "C:\\Users\\louis.heraut\\Documents\\CDD_stationnarite\\ASH"
-# Manual selection
-# Path to data that will be analysed
-filedir =
+### BANQUE HYDRO ###
+## Manual selection ##
+# Path to data that will be analysed from the BanqueHydro
+BHfiledir =
FALSE
# "test"
# "BanqueHydro_Export2021"
-filename =
+BHfilename =
FALSE
# c("H5920011_HYDRO_QJM.txt", "K4470010_HYDRO_QJM.txt")
# "all"
-# Or list selection
+## Or list selection ##
# Path to the list file of station that will be analysed
-listdir =
+BHlistdir =
# FALSE
""
-listname =
- "Liste-station_RRSE.docx"
+BHlistname =
# FALSE
-BHdir =
- "BanqueHydro_Export2021"
+ "Liste-station_RRSE.docx"
+BHdatadir =
# FALSE
+ "BanqueHydro_Export2021"
-# selecdir = "RRSE_selection"
+### NIVALE ###
+
+
-##################
+########################
# Set working directory
@@ -66,10 +69,10 @@ print(paste('figdir :', figdir))
# Get only the selected station from a list station file
-if (is.character(listdir) & is.character(listname) & is.character(BHdir)){
+if (is.character(BHlistdir) & is.character(BHlistname) & is.character(BHdatadir)){
df_selec = get_selection(computer_data_path,
- listdir,
- listname,
+ BHlistdir,
+ BHlistname,
cnames=c('code',
'station',
'BV_km2',
@@ -79,18 +82,19 @@ if (is.character(listdir) & is.character(listname) & is.character(BHdir)){
'choix'),
cisnum=c('BV_km2',
'longueur_serie'))
- filedir = BHdir
- filename = df_selec$filename
+ BHfiledir = BHdatadir
+ BHfilename = df_selec$filename
}
# Extract information about selected stations
-df_info = extract_info(computer_data_path, filedir, filename)
+df_info = extract_info(computer_data_path, BHfiledir, BHfilename)
# Extract data about selected stations
-df_data = extract_data(computer_data_path, filedir, filename)
+df_data = extract_data(computer_data_path, BHfiledir, BHfilename)
# Plot time panel of debit by stations
-panel(df_data, df_info, figdir, filedir)
+panel(df_data, df_info, figdir, BHfiledir)
+# panel(df_data, df_info, figdir, BHfiledir, is_sqrt=TRUE)
# Compute gap parameters for stations
df_lac = get_lacune(df_data, df_info)