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script_management.R
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# Copyright 2021-2023 Louis Héraut ([email protected])*1,
# Éric Sauquet ([email protected])*1
#
# *1 INRAE, France
#
# This file is part of Explore2 R toolbox.
#
# Explore2 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.
#
# Explore2 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 Explore2 R toolbox.
# If not, see <https://www.gnu.org/licenses/>.
manage_data = function () {
for (i in 1:length(extract_data)) {
extract = extract_data[[i]]
if (exists("meta")) {
rm ("meta", envir=.GlobalEnv)
rm ("meta")
gc()
}
if (exists("metaEX")) {
rm ("metaEX", envir=.GlobalEnv)
rm ("metaEX")
gc()
}
if (exists("dataEX")) {
rm ("dataEX", envir=.GlobalEnv)
rm ("dataEX")
gc()
}
for (j in 1:nSubsets_save) {
subset_name = names(Subsets_save)[j]
filename = paste0("meta_", files_name_opt.,
subset_name, ".fst")
if (file.exists(file.path(tmppath, filename))) {
meta_tmp = ASHE::read_tibble(filedir=tmppath,
filename=filename)
if (!exists("meta")) {
meta = meta_tmp
} else {
meta = dplyr::bind_rows(meta, meta_tmp)
}
rm ("meta_tmp")
gc()
}
if (!exists("metaEX")) {
filename = paste0("metaEX_", extract$name, "_",
files_name_opt.,
subset_name, ".fst")
if (file.exists(file.path(tmppath, filename))) {
metaEX = ASHE::read_tibble(filedir=tmppath,
filename=filename)
}
}
dirname = paste0("dataEX_", extract$name, "_",
files_name_opt.,
subset_name)
filename = paste0(dirname, ".fst")
if (file.exists(file.path(tmppath, dirname)) |
file.exists(file.path(tmppath, filename))) {
dataEX_tmp = ASHE::read_tibble(filedir=tmppath,
filename=filename)
if (!exists("dataEX")) {
dataEX = dataEX_tmp
} else {
if (extract$type == "criteria") {
dataEX = dplyr::bind_rows(dataEX,
dataEX_tmp)
} else if (extract$type == "serie") {
for (k in 1:length(dataEX)) {
dataEX[[k]] =
dplyr::bind_rows(dataEX[[k]],
dataEX_tmp[[k]])
}
}
}
rm ("dataEX_tmp"); gc()
}
}
if (exists("dataEX")) {
if (extract$type == "criteria") {
regexp_bool = "^HYP.*"
regexp_time =
"(^t)|([{]t)|(^debut)|([{]debut)|(^centre)|([{]centre)|(^fin)|([{]fin)"
regexp_ratio_alpha = "^alpha"
regexp_ratio = "(Rc)|(^epsilon)|(^a)|(^STD)"
regexp_diff = "(R.*[_]ratio)|(moyTA)|(moyRA)"
dataEX = dataEX[order(dataEX$HM),]
Variables = colnames(dataEX)
containSO = "([_]obs$)|([_]sim$)"
Variables = Variables[grepl(containSO, Variables)]
if (length(Variables) > 0) {
VariablesREL = gsub(containSO, "", Variables)
VariablesREL = VariablesREL[!duplicated(VariablesREL)]
nVariablesREL = length(VariablesREL)
for (j in 1:nVariablesREL) {
variableREL = VariablesREL[j]
if (grepl(regexp_bool, variableREL)) {
dataEX[[variableREL]] =
dataEX[[paste0(variableREL,
"_sim")]] &
dataEX[[paste0(variableREL,
"_obs")]]
metaEX$glose[metaEX$variable_en == variableREL] =
paste0(metaEX$glose[metaEX$variable_en == variableREL],
" (Comparaison entre les valeurs simulées et observées)")
} else if (grepl(regexp_time, variableREL)) {
dataEX[[variableREL]] =
circular_minus(
dataEX[[paste0(variableREL,
"_sim")]],
dataEX[[paste0(variableREL,
"_obs")]],
period=365.25)/30.4375
metaEX$unit[metaEX$variable_en == variableREL] = "mois"
metaEX$isDate[metaEX$variable_en == variableREL] = FALSE
metaEX$glose[metaEX$variable_en == variableREL] =
paste0(metaEX$glose[metaEX$variable_en == variableREL],
" (Écart normalisé entre les valeurs simulées et observées)")
} else if (grepl(regexp_ratio_alpha,
variableREL)) {
dataEX[[variableREL]] =
dataEX[[paste0(variableREL, "_sim")]] /
dataEX[[paste0(variableREL, "_obs")]]
dataEX[[variableREL]][
!dataEX[[paste0("HYP",
variableREL,
"_obs")]]
] = NA
metaEX$unit[metaEX$variable_en == variableREL] = "sans unité"
metaEX$glose[metaEX$variable_en == variableREL] =
paste0(metaEX$glose[metaEX$variable_en == variableREL],
" (Ratio entre les valeurs simulées et observées)")
} else if (grepl(regexp_ratio, variableREL)) {
dataEX[[variableREL]] =
dataEX[[paste0(variableREL, "_sim")]] /
dataEX[[paste0(variableREL, "_obs")]]
metaEX$unit[metaEX$variable_en == variableREL] = "sans unité"
metaEX$glose[metaEX$variable_en == variableREL] =
paste0(metaEX$glose[metaEX$variable_en == variableREL],
" (Ratio entre les valeurs simulées et observées)")
} else if (grepl(regexp_diff, variableREL)) {
dataEX[[variableREL]] =
round(dataEX[[paste0(variableREL, "_sim")]] -
dataEX[[paste0(variableREL, "_obs")]], 5)
metaEX$glose[metaEX$variable_en == variableREL] =
paste0(metaEX$glose[metaEX$variable_en == variableREL],
" (Écart entre les valeurs simulées et observées)")
} else {
dataEX[[variableREL]] =
(dataEX[[paste0(variableREL,
"_sim")]] -
dataEX[[paste0(variableREL,
"_obs")]]) /
dataEX[[paste0(variableREL,
"_obs")]]
metaEX$unit[metaEX$variable_en == variableREL] = "sans unité"
metaEX$glose[metaEX$variable_en == variableREL] =
paste0(metaEX$glose[metaEX$variable_en == variableREL],
" (Ratio relatif entre les valeurs simulées et observées)")
}
dataEX =
dplyr::relocate(dataEX,
!!variableREL,
.after=!!paste0(variableREL,
"_sim"))
}
}
} else if (extract$type == "serie") {
if ("HM" %in% names(dataEX[[1]])) {
for (j in 1:length(dataEX)) {
if (nrow(dataEX[[j]]) == 0) {
next
}
dataEX[[j]] =
dataEX[[j]][order(dataEX[[j]]$HM),]
}
}
}
}
if (exists("meta")) {
meta = meta[order(meta$code),]
ASHE::write_tibble(meta,
filedir=tmppath,
filename=paste0("meta_", extract$name,
.files_name_opt,
".fst"))
rm ("meta"); gc()
}
if (exists("dataEX")) {
ASHE::write_tibble(dataEX,
filedir=tmppath,
filename=paste0("dataEX_", extract$name,
.files_name_opt,
".fst"))
rm ("dataEX"); gc()
}
if (exists("metaEX")) {
ASHE::write_tibble(metaEX,
filedir=tmppath,
filename=paste0("metaEX_", extract$name,
.files_name_opt,
".fst"))
rm ("metaEX"); gc()
}
}
}
save_data = function () {
files_name_regexp = gsub("[_]", "[_]",
gsub("[-]", "[-]",
files_name_opt))
if (by_files | MPI == "file") {
today_resdir_tmp = file.path(today_resdir,
files_name_opt)
pattern = paste0("data[_]", files_name_regexp,
".*", "[.]fst")
} else {
today_resdir_tmp = today_resdir
pattern = "data[_].*[.]fst"
}
if (!(file.exists(today_resdir_tmp))) {
dir.create(today_resdir_tmp, recursive=TRUE)
}
data_paths = list.files(tmppath,
pattern=pattern,
full.names=TRUE)
data_files = gsub("[_][_]", "_",
gsub(files_name_regexp, "",
basename(data_paths)))
if ("data" %in% variable2save) {
file.copy(data_paths,
file.path(today_resdir_tmp, data_files))
}
for (i in 1:length(extract_data)) {
extract = extract_data[[i]]
dirname = paste0("dataEX_", extract$name,
.files_name_opt)
filename = paste0(dirname, ".fst")
if (file.exists(file.path(tmppath, dirname)) |
file.exists(file.path(tmppath, filename))) {
if ("meta" %in% variable2save) {
meta = ASHE::read_tibble(filedir=tmppath,
filename=paste0(
"meta_",
extract$name,
.files_name_opt,
".fst"))
}
if ("metaEX" %in% variable2save) {
metaEX = ASHE::read_tibble(filedir=tmppath,
filename=paste0(
"metaEX_",
extract$name,
.files_name_opt,
".fst"))
}
if ("dataEX" %in% variable2save) {
dataEX = ASHE::read_tibble(filedir=tmppath,
filename=paste0(
"dataEX_",
extract$name,
.files_name_opt,
".fst"))
}
} else {
next
}
if ("meta" %in% variable2save) {
ASHE::write_tibble(meta,
filedir=today_resdir_tmp,
filename="meta.fst")
if ("Rdata" %in% saving_format) {
ASHE::write_tibble(meta,
filedir=today_resdir_tmp,
filename="meta.Rdata")
}
if ("txt" %in% saving_format) {
ASHE::write_tibble(meta,
filedir=today_resdir_tmp,
filename="meta.txt")
}
}
if ("metaEX" %in% variable2save) {
ASHE::write_tibble(metaEX,
filedir=today_resdir_tmp,
filename=paste0("metaEX_",
extract$name,
".fst"))
if ("Rdata" %in% saving_format) {
ASHE::write_tibble(metaEX,
filedir=today_resdir_tmp,
filename=paste0("metaEX_",
extract$name,
".Rdata"))
}
if ("txt" %in% saving_format) {
ASHE::write_tibble(metaEX,
filedir=today_resdir_tmp,
filename=paste0("metaEX_",
extract$name,
".txt"))
}
}
if ("dataEX" %in% variable2save) {
ASHE::write_tibble(dataEX,
filedir=today_resdir_tmp,
filename=paste0("dataEX_",
extract$name,
".fst"))
if ("Rdata" %in% saving_format) {
ASHE::write_tibble(dataEX,
filedir=today_resdir_tmp,
filename=paste0("dataEX_",
extract$name,
".Rdata"))
}
if ("txt" %in% saving_format) {
ASHE::write_tibble(dataEX,
filedir=today_resdir_tmp,
filename=paste0("dataEX_",
extract$name,
".txt"))
}
}
if (exists("meta")) {
rm ("meta")
gc()
}
if (exists("metaEX")) {
rm ("metaEX")
gc()
}
if (exists("dataEX")) {
rm ("dataEX")
gc()
}
}
}
## 1. MANAGEMENT OF DATA ______________________________________________
if (!read_tmp & !clean_nc & !merge_nc & !delete_tmp) {
if (MPI == "code") {
if (rank == 0) {
Root = rep(0, times=size)
Root[1] = 1
ASHE::post(paste0(gsub("1", "-",
gsub("0", "_",
Root)), collapse=""))
for (root in 1:(size-1)) {
Root[root+1] = Rmpi::mpi.recv(as.integer(0),
type=1,
source=root,
tag=1, comm=0)
ASHE::post(paste0("End signal for extract received from rank ", root))
ASHE::post(paste0(gsub("1", "-",
gsub("0", "_",
Root)), collapse=""))
}
} else {
Rmpi::mpi.send(as.integer(1), type=1, dest=0, tag=1, comm=0)
ASHE::post(paste0("End signal for extract from rank ", rank))
}
}
if ('create_data' %in% to_do | 'extract_data' %in% to_do) {
if (MPI == "code" & rank == 0 |
MPI != "code") {
manage_data()
}
}
if ('save_extract' %in% to_do) {
if (MPI == "code" & rank == 0 |
MPI != "code") {
ASHE::post("### Saving extracts")
ASHE::post(paste0("Save extracted data and metadata in ",
paste0(saving_format, collapse=", ")))
save_data()
}
}
if ('read_saving' %in% to_do) {
# stop()
ASHE::post("### Reading saving")
ASHE::post(paste0("Reading extracted data and metadata in ",
read_saving))
data = dplyr::tibble()
meta = dplyr::tibble()
dataEX_criteria = dplyr::tibble()
dataEX_serie = dplyr::tibble()
metaEX_criteria = dplyr::tibble()
metaEX_serie = dplyr::tibble()
name_criteria = c()
name_serie = c()
for (i in 1:length(extract_data)) {
extract = extract_data[[i]]
if (grepl("diagnostic", mode)) {
path2search = file.path(resdir, read_saving)
} else if (grepl("projection", mode)) {
# path2search = file.path(resdir, read_saving,
# Projections$dir)
path2search = Projections$path
}
Paths = list.files(path2search,
include.dirs=TRUE,
full.names=TRUE,
recursive=TRUE)
Paths = Paths[!duplicated(Paths)]
pattern = variable2search
pattern = paste0("(", paste0(pattern,
collapse=")|("), ")")
if (extract$type == "criteria") {
name_criteria = c(name_criteria, extract$name)
pattern = gsub("dataEX", paste0("dataEX[_]",
gsub("[_]", "[_]",
extract$name),
"[.]"),
pattern)
} else if (extract$type == "serie") {
name_serie = c(name_serie, extract$name)
pattern = gsub("dataEX", paste0("dataEX[_]",
gsub("[_]", "[_]",
extract$name),
"$"),
pattern)
}
pattern = gsub("metaEX", paste0("metaEX[_]",
gsub("[_]", "[_]",
extract$name),
"[.]"),
pattern)
Paths = Paths[grepl(pattern, Paths)]
Paths = Paths[grepl("[.]fst", Paths) | !grepl("?[.]", Paths)]
Paths[!grepl("[.]", Paths)] =
paste0(Paths[!grepl("[.]", Paths)], ".fst")
Filenames = gsub("^.*[/]+", "", Paths)
Filenames = gsub("[.].*$", "", Filenames)
nFile = length(Filenames)
dataEX_criteria_extract = dplyr::tibble()
for (ii in 1:nFile) {
ASHE::post(paste0(gsub("([_].*)|([.].*)",
"", Filenames[ii]), " reads in ",
Paths[ii]))
if (grepl("projection", mode) &
grepl("dataEX.*serie", Filenames[ii]) &
selection_before_reading_for_projection) {
print("selection before reading for projection")
metaEX_tmp = ASHE::read_tibble(filepath=gsub("dataEX",
"metaEX",
Paths[ii]))
variables_to_read =
metaEX_tmp$variable_en[sapply(metaEX_tmp$variable_en,
any_grepl, pattern=variables_regexp)]
tmp = list()
if (length(variables_to_read) > 0) {
Paths_variable = file.path(gsub("[.]fst", "", Paths[ii]),
paste0(variables_to_read, ".fst"))
for (j in 1:length(Paths_variable)) {
tmp = append(tmp,
list(ASHE::read_tibble(filepath=Paths_variable[j])))
names(tmp)[length(tmp)] = variables_to_read[j]
}
}
} else {
tmp = ASHE::read_tibble(filepath=Paths[ii])
}
if (tibble::is_tibble(tmp)) {
if (nrow(tmp) == 0) {
next
}
} else {
if (length(tmp) == 0) {
next
}
}
if (grepl("dataEX.*criteria", Filenames[ii])) {
tmp = dplyr::filter(tmp, code %in% Code_selection)
print(names(tmp))
by = names(tmp)[sapply(tmp, is.character)]
pattern_by = paste0("(",
paste0(by, collapse=")|("),
")|", variables_regexp)
col2keep = sapply(names(tmp), any_grepl,
pattern=pattern_by)
tmp = tmp[col2keep]
if (grepl("diagnostic", mode)) {
for (j in 1:length(diag_station_selection)) {
if (length(diag_station_selection) == 0) {
break
}
hm_selection =
names(diag_station_selection)[j]
code_selection = diag_station_selection[j]
tmp = dplyr::filter(tmp,
!(HM == hm_selection &
grepl(code_selection,
code)))
}
}
} else if (grepl("dataEX.*serie", Filenames[ii])) {
for (k in 1:length(tmp)) {
if (nrow(tmp[[k]]) == 0) {
next
}
tmp[[k]] =
dplyr::filter(tmp[[k]],
code %in% Code_selection)
}
row2keep = sapply(names(tmp), any_grepl,
pattern=variables_regexp)
tmp = tmp[row2keep]
if (grepl("diagnostic", mode)) {
for (j in 1:length(diag_period_selection)) {
hm = names(diag_period_selection)[j]
period = diag_period_selection[[j]]
start = period[1]
if (is.na(start)) {
start = min(as.Date(period_extract_diag))
}
end = period[2]
if (is.na(end)) {
end = max(as.Date(period_extract_diag))
}
for (k in 1:length(tmp)) {
if (!("date" %in% names(tmp[[k]])) |
!any(sapply(tmp[[k]],
lubridate::is.Date))) {
next
}
tmp[[k]] =
dplyr::filter(tmp[[k]],
HM != hm |
(HM == hm &
start < date &
date < end))
}
}
for (j in 1:length(diag_station_selection)) {
if (length(diag_station_selection) == 0) {
break
}
hm_selection = names(diag_station_selection)[j]
code_selection = diag_station_selection[j]
for (k in 1:length(tmp)) {
tmp[[k]] =
dplyr::filter(tmp[[k]],
!(HM == hm_selection &
grepl(code_selection,
code)))
}
}
}
} else if (grepl("metaEX.*criteria", Filenames[ii])) {
row2keep = sapply(tmp$variable_en, any_grepl,
pattern=variables_regexp)
tmp = tmp[row2keep,]
} else if (grepl("metaEX.*serie", Filenames[ii])) {
row2keep = sapply(tmp$variable_en, any_grepl,
pattern=variables_regexp)
tmp = tmp[row2keep,]
} else if (grepl("meta", Filenames[ii])) {
tmp = dplyr::filter(tmp, code %in% Code_selection)
if (grepl("diagnostic", mode)) {
for (j in 1:length(diag_station_selection)) {
if (length(diag_station_selection) == 0) {
break
}
hm = names(diag_station_selection)[j]
code = diag_station_selection[j]
tmp[[paste0("surface_",
hm, "_km2")]][grepl(code,
tmp$code)] = NA
}
}
}
if (length(tmp) > 0) {
### /!\ pour proj ###
if (grepl("dataEX.*criteria", Filenames[ii])) {
# if (nrow(dataEX_criteria) == 0) {
# dataEX_criteria = tmp
# } else {
# character_cols =
# names(tmp)[sapply(tmp, is.character)]
# cols2join = names(tmp)[!(names(tmp) %in%
# names(dataEX_criteria))]
# cols2join = cols2join[!(cols2join %in%
# character_cols)]
# if (length(cols2join) > 0) {
# print("join")
# stop()
# dataEX_criteria =
# dplyr::full_join(
# dataEX_criteria,
# dplyr::select(tmp,
# dplyr::all_of(c(character_cols,
# cols2join))),
# by=character_cols)
# }
# cols2bind = names(tmp)[(names(tmp) %in%
# names(dataEX_criteria))]
# cols2bind = cols2bind[!(cols2bind %in%
# character_cols)]
# if (length(cols2bind) > 0) {
# print("bind")
# # stop()
# dataEX_criteria =
# dplyr::bind_rows(
# dataEX_criteria,
# dplyr::select(tmp,
# dplyr::all_of(c(character_cols,
# cols2bind))))
# }
# dataEX_criteria =
# dplyr::full_join(
# dataEX_criteria,
# tmp,
# by=character_cols)
if (grepl("projection", mode)) {
if ("GCM" %in% names(tmp)) {
tmp = tidyr::unite(tmp,
"climateChain",
"GCM", "EXP",
"RCM", "BC",
sep="|",
remove=FALSE)
tmp = tidyr::unite(tmp,
"Chain",
"GCM", "EXP",
"RCM", "BC",
"HM",
sep="|",
remove=FALSE)
} else {
tmp$climateChain = "SAFRAN"
tmp = tidyr::unite(tmp,
"Chain",
"climateChain",
"HM",
sep="|",
remove=FALSE)
tmp = dplyr::relocate(tmp,
climateChain,
.after=Chain)
}
}
dataEX_criteria_extract =
dplyr::bind_rows(dataEX_criteria_extract, tmp)
# }
### /!\ pour proj ###
} else if (grepl("dataEX.*serie", Filenames[ii])) {
if (grepl("projection", mode)) {
if ("GCM" %in% names(tmp[[1]])) {
for (k in 1:length(tmp)) {
if (nrow(tmp[[k]]) == 0) {
next
}
tmp[[k]] = tidyr::unite(tmp[[k]],
"climateChain",
"GCM", "EXP",
"RCM", "BC",
sep="|",
remove=FALSE)
tmp[[k]] = tidyr::unite(tmp[[k]],
"Chain",
"GCM", "EXP",
"RCM", "BC",
"HM",
sep="|",
remove=FALSE)
}
} else {
for (k in 1:length(tmp)) {
if (nrow(tmp[[k]]) == 0) {
next
}
tmp[[k]]$climateChain = "SAFRAN"
tmp[[k]] = tidyr::unite(tmp[[k]],
"Chain",
"climateChain",
"HM",
sep="|",
remove=FALSE)
tmp[[k]] = dplyr::relocate(tmp[[k]],
climateChain,
.after=Chain)
}
}
names_in = names(tmp)[names(tmp) %in%
names(dataEX_serie)]
names_out = names(tmp)[!(names(tmp) %in%
names(dataEX_serie))]
if (length(names_in) > 0) {
for (name in names_in) {
dataEX_serie[[name]] =
dplyr::bind_rows(dataEX_serie[[name]],
tmp[[name]])
}
}
if (length(names_out) > 0) {
dataEX_serie =
append(dataEX_serie, tmp[names_out])
}
} else if (grepl("diagnostic", mode)) {
dataEX_serie =
append(dataEX_serie, tmp)
}
} else if (grepl("metaEX.*criteria", Filenames[ii])) {
metaEX_criteria =
dplyr::bind_rows(metaEX_criteria,
tmp[!(tmp$variable_en %in% metaEX_criteria$variable_en),])
} else if (grepl("metaEX.*serie", Filenames[ii])) {
metaEX_serie =
dplyr::bind_rows(metaEX_serie,
tmp[!(tmp$variable_en %in% metaEX_serie$variable_en),])
} else if (grepl("data[_]", Filenames[ii])) {
data = dplyr::bind_rows(data, tmp)
} else if (grepl("^meta$", Filenames[ii])) {
if (nrow(meta) == 0) {
meta = tmp
} else {
meta = dplyr::full_join(meta, tmp)
}
} else {
assign(Filenames[ii], tmp)
}
} else {
assign(Filenames[ii], tmp)
}
}
if (nrow(dataEX_criteria) == 0) {
dataEX_criteria = dataEX_criteria_extract
} else {
character_cols =
names(dataEX_criteria_extract)[sapply(dataEX_criteria_extract,
is.character)]
dataEX_criteria =
dplyr::full_join(dataEX_criteria,
dataEX_criteria_extract,
by=character_cols)
}
}
# if (merge_read_saving) {
extract_data_tmp = list()
if (any(sapply(extract_data, '[[', 'type') == "criteria")) {
extract_data_tmp =
append(extract_data_tmp,
list(list(name=name_criteria,
type="criteria",
variables=
metaEX_criteria$variable_en)))
names(extract_data_tmp)[length(extract_data_tmp)] =
"criteria"
}
if (any(sapply(extract_data, '[[', 'type') == "serie")) {
extract_data_tmp =
append(extract_data_tmp,
list(list(name=name_serie,
type="serie",
variables=metaEX_serie$variable_en)))
names(extract_data_tmp)[length(extract_data_tmp)] =
"serie"
}
extract_data = extract_data_tmp
# }
# if (!is.null(names(codes_to_use)) & exists("meta")) {
# info = dplyr::tibble(code=codes_to_use,
# info=names(codes_to_use))
# meta = dplyr::left_join(meta, info, by="code")
# }
if (type == "piezometrie" & exists("meta")) {
meta = get_couche_in_meta(meta)
}
}
ratio_lim = 2
fact = 3
if ('find_chain_out' %in% to_do) {
if (any(grepl("serie", extract_data))) {
if ("QA" %in% names(dataEX_serie)) {
dataEX_tmp = dataEX_serie$QA
dataEX_tmp =
dplyr::filter(dataEX_tmp,
historical[1] <= date &
date <= historical[2])
dataEX_tmp_mean =
dplyr::summarise(
dplyr::group_by(dataEX_tmp,
code, Chain),
meanQA=mean(QA, na.rm=TRUE),
GCM=GCM[1], EXP=EXP[1], RCM=RCM[1],
BC=BC[1], HM=HM[1])
dataEX_tmp_med =
dplyr::summarise(dplyr::group_by(dataEX_tmp_mean,
code),
medmeanQA=median(meanQA, na.rm=TRUE))
dataEX_tmp_mean =
dplyr::full_join(dataEX_tmp_mean,
dataEX_tmp_med,
by="code")
dataEX_tmp_mean$ratio =
dataEX_tmp_mean$meanQA / dataEX_tmp_mean$medmeanQA
# dataEX_serieQA_ALL = dplyr::bind_rows(dataEX_serieQA_ALL,
# dataEX_tmp_mean)
chain_to_remove_tmp =
dplyr::filter(dataEX_tmp_mean,
ratio < 1/ratio_lim |
ratio_lim < ratio)
chain_to_remove_tmp =
dplyr::select(chain_to_remove_tmp,
code, Chain,
GCM, EXP, RCM,
BC, HM)
chain_to_remove_tmp$on = "serie"
chain_to_remove = dplyr::bind_rows(chain_to_remove,
chain_to_remove_tmp)
} else {
stop("You need to have QA variable in dataEX_serie")
}
}
if (any(grepl("criteria", extract_data))) {
if ("deltaQA_H3" %in% names(dataEX_criteria)) {
dataEX_tmp = dataEX_criteria
dataEX_tmp_stat =
dplyr::summarise(dplyr::group_by(dataEX_tmp,
code),
medQA=median(deltaQA_H3, na.rm=TRUE),
stdQA=sd(deltaQA_H3, na.rm=TRUE))
dataEX_tmp =
dplyr::full_join(dataEX_tmp,
dataEX_tmp_stat,
by="code")
# dataEX_criteriaQA_ALL =
# dplyr::bind_rows(dataEX_criteriaQA_ALL,
# dataEX_tmp)
chain_to_remove_tmp =
dplyr::filter(dataEX_tmp,
deltaQA_H3 < medQA-fact*stdQA |
medQA+fact*stdQA < deltaQA_H3)
chain_to_remove_tmp =
dplyr::select(chain_to_remove_tmp,
code, Chain,
GCM, EXP, RCM,
BC, HM)
chain_to_remove_tmp$on = "criteria"
chain_to_remove = dplyr::bind_rows(chain_to_remove,
chain_to_remove_tmp)
} else {
stop("You need to have deltaQA_H3 variable in dataEX_criteria")
}
}
}