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Dorchies David authored
When running SD model without defining the routing model as before. Refs HYCAR-Hydro/airgr#152, HYCAR-Hydro/airgr#153
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HYCAR-Hydro / airGR
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# \\\# Copyright 2021-2022 Louis Héraut*1,# Éric Sauquet*2,# Valentin Mansanarez## *1 INRAE, France# louis.heraut@inrae.fr# *2 INRAE, France# eric.sauquet@inrae.fr## This file is part of ash R toolbox.## Ash R toolbox is free software: you can redistribute it and/or# modify it under the terms of the GNU General Public License as# published by the Free Software Foundation, either version 3 of the# License, or (at your option) any later version.## Ash R toolbox is distributed in the hope that it will be useful, but# WITHOUT ANY WARRANTY; without even the implied warranty of# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU# General Public License for more details.## You should have received a copy of the GNU General Public License# along with ash R toolbox.# If not, see <https://www.gnu.org/licenses/>.# ///### Rcode/processing/results_manager.R## Manages the writing and reading of results data of the trend analysis.## 1. WRITING ________________________________________________________### 1.1. List of dataframe ___________________________________________write_analyse = function (Ldf, resdir, filedir) { outdir = file.path(resdir, filedir) if (!(file.exists(outdir))) { dir.create(outdir, recursive=TRUE) } print(paste('Writing of list of dataframe in : ', outdir, sep='')) Lname = names(Ldf) Nname = length(Lname) for (i in 1:Nname) { outfile = paste(Lname[i], '.txt', sep='') write.table(Ldf[[i]], file=file.path(outdir, outfile), sep=";", quote=TRUE, row.names=FALSE) }}### 1.2. Dataframe of modified data __________________________________write_data = function (df_data, df_mod, resdir, filedir) { Code = rle(sort(df_mod$code))$values outdir = file.path(resdir, filedir) if (!(file.exists(outdir))) { dir.create(outdir, recursive=TRUE) } print(paste('Writing of modified data in : ', outdir, sep='')) for (code in Code) {7172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140
df_data_code = df_data[df_data$code == code,]
df_mod_code = df_mod[df_mod$code == code,]
outfile1 = paste(code, '.txt', sep='')
write.table(df_data_code,
file=file.path(outdir, outfile1),
sep=";",
quote=TRUE,
row.names=FALSE)
outfile2 = paste(code, '_modification', '.txt', sep='')
write.table(df_mod_code,
file=file.path(outdir, outfile2),
sep=";",
quote=TRUE,
row.names=FALSE)
}
}
### 1.3. Dataframe of criticism ______________________________________
write_critique = function (df_critique, resdir, filename='critique') {
outdir = file.path(resdir)
if (!(file.exists(outdir))) {
dir.create(outdir, recursive=TRUE)
}
print(paste('Writing criticism in : ', outdir, sep=''))
outfile = paste(filename, '.txt', sep='')
write.table(df_critique,
file=file.path(outdir, outfile),
sep=";",
quote=FALSE,
row.names=FALSE)
}
# write_critique(df_critique, resdir)
### 1.4. Fast for R __________________________________________________
write_dataFST = function (df_data, resdir, filedir='fst',
filename='data.fst') {
outdir = file.path(resdir, filedir)
if (!(file.exists(outdir))) {
dir.create(outdir, recursive=TRUE)
}
outfile = file.path(outdir, filename)
fst::write_fst(df_data, outfile, compress=0)
}
write_metaFST = function (df_meta, resdir, filedir='fst',
filename='meta.fst') {
outdir = file.path(resdir, filedir)
if (!(file.exists(outdir))) {
dir.create(outdir, recursive=TRUE)
}
outfile = file.path(outdir, filename)
fst::write_fst(df_meta, outfile, compress=0)
}
## 2. READING ________________________________________________________
### 2.1. List of dataframe ___________________________________________
read_listofdf = function (resdir, filedir) {
outdir = file.path(resdir, filedir)
files = list.files(outdir)
Nfile = length(files)
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print(paste('Reading of list of dataframe in : ', outdir, sep=''))
Ldf = list()
for (i in 1:Nfile) {
name = splitext(files[i])$name
df = as_tibble(read.table(file=file.path(outdir, files[i]),
header=TRUE,
sep=";",
quote='"'))
for (j in 1:ncol(df)) {
if (is.factor(df[[j]])) {
d = try(as.Date(df[[1, j]], format="%Y-%m-%d"))
if("try-error" %in% class(d) || is.na(d)) {
df[j] = as.character(df[[j]])
} else {
df[j] = as.Date(df[[j]])
}
}
}
# OkFact = sapply(df, is.factor)
# df[OkFact] = lapply(df[OkFact], as.character)
Ldf = append(Ldf, list(df))
names(Ldf)[length(Ldf)] = name
}
return (Ldf)
}
### 2.2. Dataframe of modified data __________________________________
read_data = function (resdir, 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(resdir,
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,
read_data(resdir,
filedir,
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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 metadata if asked
if (verbose) {
print(paste("reading of extracted data for file :", filename))
}
# Get the file path to the data
file_path = file.path(resdir, 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 = as_tibble(read.table(file_path,
header=TRUE,
na.strings=c('NA'),
sep=';',
quote='"',
skip=0))
for (j in 1:ncol(df_data)) {
if (is.factor(df_data[[j]])) {
d = try(as.Date(df_data[[1, j]], format="%Y-%m-%d"))
if("try-error" %in% class(d) || is.na(d)) {
df_data[j] = as.character(df_data[[j]])
} else {
df_data[j] = as.Date(df_data[[j]])
}
}
}
return (df_data)
} else {
print(paste('filename', file_path, 'do not exist'))
return (NULL)
}
}
### 2.3. Dataframe of criticism ______________________________________
read_critique = function (resdir, filename='critique') {
outdir = file.path(resdir)
outfile = paste(filename, '.txt', sep='')
file_path = file.path(outdir, outfile)
print(paste('Reading criticism in : ', file_path, sep=''))
df = as_tibble(read.table(file=file_path,
header=TRUE,
sep=";"))
for (j in 1:ncol(df)) {
if (is.factor(df[[j]])) {
d = try(as.Date(df[[1, j]], format="%Y-%m-%d"))
if("try-error" %in% class(d) || is.na(d)) {
df[j] = as.character(df[[j]])
} else {
df[j] = as.Date(df[[j]])
}
}
}
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return (df)
}
# df_critique = read_critique(resdir)
### 2.4. Fast for R __________________________________________________
read_FST = function (resdir, filename, filedir='fst') {
outfile = file.path(resdir, filedir, filename)
df = tibble(fst::read_fst(outfile))
return (df)
}
## 3. OTHER __________________________________________________________
splitext = function(file) {
ex = strsplit(basename(file), split="\\.")[[1]]
res = list(name=ex[1], extension=ex[2])
return (res)
}