format.R

# \\\
# Copyright 2021-2022 Louis Héraut*1
#
# *1   INRAE, France
#      louis.heraut@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/>.
# ///
#
#
# processing/format.R
#
# Manages all the format problem of data and info. Mainly problem of
# input and output of the 'StatsAnalysisTrend' package. It also allows
# to join different selections of station and to gets exact period of
# trend analysis.


# Usefull library
library(dplyr)


## 1. INPUT
### 1.1. Preparation
# Prepares the data in order to have a list of a data tibble with
# date, group and flow column and a info tibble with the station code
# and group column to fit the entry of the 'extract.Var' function in
# the 'StatsAnalysisTrend' package
prepare = function(df_data, colnamegroup=NULL) {
    
    # Forces the column name to group to be a vector 
    colnamegroup = c(colnamegroup)
    # Converts it to index of the column to group
    colindgroup = which(colnames(df_data) == colnamegroup)
    # Groups the data by those indexes
    df_data = group_by_at(df_data, colindgroup)

    # Creates a new tibble of data with a group column
    data = tibble(Date=df_data$Date, 
                  group=group_indices(df_data),
                  Qm3s=df_data$Qm3s)
    
    # Gets the different value of the group
    Gkey = group_keys(df_data)
    # Creates a new tibble of info of the group
    info = bind_cols(group=seq(1:nrow(Gkey)),
                     Gkey)

    # Stores data and info tibble as a list that match the entry of
    # the 'extract.Var' function
    res = list(data=data, info=info)
    return (res)
}

### 1.2. Re-preparation
# Re-prepares the data in outing of the 'extract.Var' function in
# the 'StatsAnalysisTrend' package in order to fit again to the