diff --git a/README.txt b/README.txt
index 9a49439cae4be631e3f5c22da4a8636fb61af9e4..a933a7a1db643e0b27e7763437f10dbbb7a01c7c 100644
--- a/README.txt
+++ b/README.txt
@@ -1,7 +1 @@
-
-
-tools
-
-install_github("https://github.com/benRenard/BFunk")
-
-install.packages("ggplot2")
+ASH package
diff --git a/plotting/panel.R b/plotting/panel.R
index 0501dcec5c183b407dd7ad274c6afb972fae2edb..79a330b60550e03cf6e1518396aa80e03b87eca1 100644
--- a/plotting/panel.R
+++ b/plotting/panel.R
@@ -1,25 +1,45 @@
+# Usefull library
library(ggplot2)
+width = 30
+height = 14
+dpi = 100
+
# Time panel
panel = function (df_data, df_info, figdir, filedir, span=Inf) {
-
+
# 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, '_years', sep='')
+ outdir = file.path(figdir, filedir, sep='')
if (!(file.exists(outdir))) {
dir.create(outdir)
}
- # Create name for the figure file
- outfile = paste('Panel_', df_info$code, '.png', sep='')
-
- plot =
- ggplot(df_data, aes(x=Date, y=Qls)) +
- geom_line()
+ # Get all different stations code
+ Code = levels(factor(df_info$code))
+ for (code in Code) {
+ # Create name for the figure file
+ outfile = paste('Panel_', code, '.pdf', sep='')
+ print(paste("Plotting for sation :", code))
+
+ df_data_code = df_data[df_data$code==code,]
+
+ # Plot
+ plot =
+ ggplot(df_data_code, aes(x=Date, y=Qls)) +
+ geom_line()
+
+ # Save the plot
+ ggsave(path=outdir,
+ filename=outfile,
+ plot=plot,
+ width=width,
+ height=height,
+ dpi=dpi,
+ units='cm')
+ }
-
- return (plot)
}
diff --git a/processing/analyse.R b/processing/analyse.R
new file mode 100644
index 0000000000000000000000000000000000000000..b7441a6443d7a9a3c3687a8c264a4de90094e428
--- /dev/null
+++ b/processing/analyse.R
@@ -0,0 +1,59 @@
+# Usefull library
+# library(StatsAnalysisTrend)
+library(dplyr)
+
+
+# Compute the time gap by station
+get_lacune = function (df_data, df_info) {
+
+ # Get all different stations code
+ Code = levels(factor(df_info$code))
+
+ # Create new vector to stock results for cumulative time gap by station
+ tLac = c()
+ # Create new vector to stock results for mean time gap by station
+ meanLac = c()
+
+ # Get rows where there is no NA
+ NoNA = complete.cases(df_data)
+ # Get data where there is no NA
+ df_data_NoNA = df_data[NoNA,]
+
+ # For every station
+ for (code in Code) {
+
+ # Get only the data rows for the selected station
+ df_data_code = df_data[df_data$code==code,]
+ # Get date for the selected station
+ Date = df_data_code$Date
+ # Get time span for the selection station
+ span = as.numeric(Date[length(Date)] - Date[1])
+
+ # Get only the data rows with no NA for the selected station
+ df_data_NoNA_code = df_data_NoNA[df_data_NoNA$code==code,]
+ # Get date for the selected station
+ Date_NoNA = df_data_NoNA_code$Date
+
+ # Compute the time gap
+ lac = as.numeric(diff(Date_NoNA) - 1)
+
+ # Compute the cumulative gap
+ lac_sum = sum(lac)
+ # Store the cumulative gap rate
+ tLac = c(tLac, lac_sum/span)
+
+ # Compute the mean gap
+ lac_mean = mean(lac[lac != 0])
+ # Store the mean gap
+ meanLac = c(meanLac, lac_mean)
+
+ }
+
+ # Compute the cumulative gap rate in pourcent
+ tLac100 = tLac * 100
+
+ # Create a tibble
+ df_lac = tibble(code=Code, tLac100=tLac100, meanLac=meanLac)
+
+ return (df_lac)
+}
diff --git a/processing/extract.R b/processing/extract.R
index 1bac2919aad5a921d7f4d5f2c6df81a51236249f..7da776274a2630065e214c97dd579782aa1b66de 100644
--- a/processing/extract.R
+++ b/processing/extract.R
@@ -1,6 +1,7 @@
+# Usefull library
library(tools)
library(dplyr)
-# library(readr)
+
# General information on station
iStatut = c('0'='inconnu',
@@ -48,40 +49,70 @@ iQHE = c('0'='qualité hautes eaux inconnue',
# Extraction of information
-extract_info = function (data_path, filedir, filename) {
-
+extract_info = function (data_path, filedir, filename, verbose=TRUE) {
+
+ # Convert the filename in vector
filename = c(filename)
+ # If the filename is 'all' or regroup more than one filename
if (all(filename == 'all') | length(filename) > 1) {
+
+ # If the filename is 'all'
if (all(filename == 'all')) {
+ # Create a filelist to store all the filename
filelist = c()
+ # Get all the filename in the data directory selected
filelist_tmp = list.files(file.path(data_path,
filedir))
+
+ # For all the filename in the directory selected
for (f in filelist_tmp) {
+ # If the filename extention is 'txt'
if (file_ext(f) == 'txt') {
+ # Store the filename in the filelist
filelist = c(filelist, f)
}
}
+
+ # If the filename regroup more than one filename
} else if (length(filename > 1)) {
+ # The filelist correspond to the filename
filelist = filename
- }
+ }
+
+ # Create a blank data frame
df_info = data.frame()
+
+ # For all the file in the filelist
for (f in filelist) {
+
+ # Concatenate by raw data frames created by this function when filename correspond to only one filename
df_info = rbind(df_info,
extract_info(data_path,
filedir,
- f)
- )
+ f))
}
+
+ # Set the rownames by default (to avoid strange numbering)
rownames(df_info) = NULL
return (df_info)
}
- filename = filename[1]
+ # Get the filename from the vector
+ filename = filename[1]
+
+ # Print information if asked
+ if (verbose) {
+ print(paste("extraction of info for file :", filename))
+ }
+ # Get the file path to the data
file_path = file.path(data_path, filedir, filename)
+
+ # Extract all the header
infotxt = c(readLines(file_path, n=41))
-
+
+ # Create a tibble with all the information needed
df_info =
tibble(code=trimws(substr(infotxt[11], 38, nchar(infotxt[11]))),
nom=trimws(substr(infotxt[12], 39, nchar(infotxt[12]))),
@@ -103,6 +134,7 @@ extract_info = function (data_path, filedir, filename) {
return (df_info)
}
+# Example
# df_info = extract_info(
# "/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/data",
# '',
@@ -110,37 +142,63 @@ extract_info = function (data_path, filedir, filename) {
# Extraction of data
-extract_data = function (data_path, filedir, filename) {
+extract_data = function (data_path, filedir, filename, verbose=TRUE) {
+ # Convert the filename in vector
filename = c(filename)
+ # If the filename is 'all' or regroup more than one filename
if (all(filename == 'all') | length(filename) > 1) {
+
+ # If the filename is 'all'
if (all(filename == 'all')) {
+ # Create a filelist to store all the filename
filelist = c()
+ # Get all the filename in the data directory selected
filelist_tmp = list.files(file.path(data_path,
filedir))
+
+ # For all the filename in the directory selected
for (f in filelist_tmp) {
+ # If the filename extention is 'txt'
if (file_ext(f) == 'txt') {
+ # Store the filename in the filelist
filelist = c(filelist, f)
}
}
+ # If the filename regroup more than one filename
} else if (length(filename > 1)) {
+ # The filelist correspond to the filename
filelist = filename
}
+
+ # Create a blank data frame
df_data = data.frame()
+
+ # For all the file in the filelist
for (f in filelist) {
+
+ # Concatenate by raw data frames created by this function when filename correspond to only one filename
df_data = rbind(df_data,
extract_data(data_path,
filedir,
- f)
- )
+ f))
}
+
+ # Set the rownames by default (to avoid strange numbering)
rownames(df_data) = NULL
return (df_data)
}
+ # Get the filename from the vector
filename = filename[1]
+
+ # Print information if asked
+ if (verbose) {
+ print(paste("extraction of data for file :", filename))
+ }
+ # Get the file path to the data
file_path = file.path(data_path, filedir, filename)
df_data = read.table(file_path,
@@ -149,9 +207,11 @@ extract_data = function (data_path, filedir, filename) {
sep=';',
skip=41)[,1:2]
- df_info = extract_info(data_path, filedir, filename)
+ # Extract all the information for the station
+ df_info = extract_info(data_path, filedir, filename, verbose=FALSE)
+ # Get the code of the station
code = df_info$code
-
+ # Create a tibble with the date as Date class and the code of the station
df_data = tibble(Date=as.Date(as.character(df_data$Date),
format="%Y%m%d"),
df_data[-1],
@@ -160,6 +220,7 @@ extract_data = function (data_path, filedir, filename) {
return (df_data)
}
+# Example
# df_data = extract_data(
# "/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/data",
# '',
diff --git a/processing/stationnarite.R b/processing/stationnarite.R
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/script.R b/script.R
index f45b8da05e93c1b3355f46ed3dffe97f6c5dc7a6..f29310455f9c9791849222530efce12336409ea4 100644
--- a/script.R
+++ b/script.R
@@ -9,7 +9,8 @@ computer_work_path = "/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/ASH"
filedir = ""
-filename = "H5920011_HYDRO_QJM.txt"
+filename = c("H5920011_HYDRO_QJM.txt", "K4470010_HYDRO_QJM.txt")
+# filename = "all"
##################
@@ -19,6 +20,7 @@ setwd(computer_work_path)
# Sourcing R file
source('processing/extract.R')
+source('processing/analyse.R')
source('plotting/panel.R')
# Usefull library
@@ -33,9 +35,14 @@ figdir = file.path(computer_work_path, 'figures')
print(paste('figdir :', figdir))
+# Extract information about selected stations
df_info = extract_info(computer_data_path, filedir, filename)
+
+# Extract data about selected stations
df_data = extract_data(computer_data_path, filedir, filename)
+# Plot time panel of debit by stations
panel(df_data, df_info, figdir, filedir)
-
+# Compute gap parameters for stations
+df_lac = get_lacune(df_data, df_info)
diff --git a/script_install.R b/script_install.R
new file mode 100644
index 0000000000000000000000000000000000000000..aa217d6a7a079ba9682d5da821511d21c1164d13
--- /dev/null
+++ b/script_install.R
@@ -0,0 +1,17 @@
+
+
+install.packages("tools")
+install.packages("devtools")
+install.packages("dplyr")
+install.packages("ggplot2")
+
+library(devtools)
+install_github("https://github.com/benRenard/BFunk")
+# install_git("git@gitlab-ssh.irstea.fr:valentin.mansanarez/statistical-analysis-of-trends.git") # SSH
+install_git("https://gitlab.irstea.fr/valentin.mansanarez/statistical-analysis-of-trends.git")
+
+
+
+
+
+