From df4d3ee3585facbefa7edaf98f3eff801612ff57 Mon Sep 17 00:00:00 2001
From: "louis.heraut" <louis.heraut@inrae.fr>
Date: Fri, 21 Jan 2022 17:40:09 +0100
Subject: [PATCH] INI variable
---
processing/analyse.R | 29 ++++++++++++++-----------
processing/format.R | 51 +++++++++++++++++++++++++++-----------------
2 files changed, 48 insertions(+), 32 deletions(-)
diff --git a/processing/analyse.R b/processing/analyse.R
index 53691f0..6c42952 100644
--- a/processing/analyse.R
+++ b/processing/analyse.R
@@ -275,7 +275,7 @@ get_VCN10trend = function (df_data, df_meta, period, p_thresold) {
### 1.4. tINI date
which_underfirst = function (L, UpLim) {
- id = which(L < UpLim)[1]
+ id = which(L <= UpLim)[1]
return (id)
}
@@ -321,6 +321,9 @@ get_tINItrend = function (df_data, df_meta, period, p_thresold) {
# Gets the code
code = Code[k]
+ per.start = df_meta$start_year[df_meta$code == code]
+ per.start = paste(sprintf("%02d", per.start), '-01', sep='')
+
# Get the data associated to the code
df_data_roll_code = df_data_roll[df_data_roll$code == code,]
@@ -337,25 +340,22 @@ get_tINItrend = function (df_data, df_meta, period, p_thresold) {
funct=min,
timestep='year',
period=per,
+ per.start=per.start,
pos.datetime=1,
na.rm=TRUE)
- print(code)
+ # print(code)
+ # print(df_QNAEx_code)
- print(df_QNAEx_code)
QNAmax = max(df_QNAEx_code$values, na.rm=TRUE)
- print(QNAmax)
+
+ # print(QNAmax)
+ # print(per.start)
# Prepare the data to fit the entry of extract.Var
df_tINIlist_code = prepare(df_data_roll_code,
colnamegroup=c('code'))
-
- per.start = df_meta$start_year[df_meta$code == code]
- per.start = paste(sprintf("%02d", per.start), '-01', sep='')
-
-
- print(per.start)
# Compute the yearly min over the averaged data
df_tINIEx_code = extract.Var(data.station=df_tINIlist_code,
@@ -369,6 +369,11 @@ get_tINItrend = function (df_data, df_meta, period, p_thresold) {
df_tINIEx_code$group1 = k
df_tINIlist_code$data$group = k
df_tINIlist_code$info$group = k
+
+ # Converts index of the tINI to the julian date associated
+ df_tINIEx_code = prepare_date(df_tINIEx_code,
+ df_tINIlist_code,
+ per.start=per.start)
# Store the results
df_tINIEx = bind_rows(df_tINIEx, df_tINIEx_code)
@@ -382,9 +387,7 @@ get_tINItrend = function (df_data, df_meta, period, p_thresold) {
# print(df_tINIEx)
# print(df_tINIlist)
-
- # Converts index of the tINI to the julian date associated
- df_tINIEx = prepare_date(df_tINIEx, df_tINIlist)
+
# Compute the trend analysis
df_tINItrend = Estimate.stats(data.extract=df_tINIEx,
diff --git a/processing/format.R b/processing/format.R
index a7a03db..84c928f 100644
--- a/processing/format.R
+++ b/processing/format.R
@@ -110,46 +110,59 @@ reprepare = function(df_XEx, df_Xlist, colnamegroup=NULL) {
-prepare_date = function(df_XEx, df_Xlist) {
+prepare_date = function(df_XEx, df_Xlist, per.start="01-01") {
- dateStart_group = summarise(group_by(df_Xlist$data, group),
+ df_dateStart = summarise(group_by(df_Xlist$data, group),
Date = min(Date))
# filter(group_by(df_Xlist$data, group), Date == min(Date))
- dateStart_group$Date_julian = NA
- date = as.Date(dateStart_group$Date)
- origin = as.Date(paste(format(dateStart_group$Date, "%Y"),
- '-01-01', sep=''))
+ df_dateStart$Date_julian = NA
+ df_dateStart$DateHydro_julian = NA
- for (i in 1:nrow(dateStart_group)) {
+ date = as.Date(df_dateStart$Date)
+
+ date_per.start = as.Date(paste(substr(date, 1, 4),
+ '-', per.start, sep=''))
+
+ date[date < date_per.start] = date_per.start[date < date_per.start]
+ df_dateStart$Date = date
+
+ origin = as.Date(paste(format(df_dateStart$Date, "%Y"),
+ '-', per.start, sep=''))
+
+ originHydro = as.Date(paste(format(df_dateStart$Date, "%Y"),
+ '-01-01', sep=''))
+
+ for (i in 1:nrow(df_dateStart)) {
dateJultmp = julian(date[i], origin=origin[i])
- dateStart_group$Date_julian[i] = dateJultmp
+ df_dateStart$Date_julian[i] = dateJultmp
+ dateJulHydrotmp = julian(date[i], origin=originHydro[i])
+ df_dateStart$DateHydro_julian[i] = dateJulHydrotmp
}
- dateStart_group$Year = format(dateStart_group$Date, "%Y")
+ df_dateStart$Year = format(df_dateStart$Date, "%Y")
- for (group in dateStart_group$group) {
- OkdateStart_group = dateStart_group$group == group
- Shift = dateStart_group$Date_julian[OkdateStart_group]
- year = dateStart_group$Year[OkdateStart_group]
+ for (group in df_dateStart$group) {
+ Ok_dateStart = df_dateStart$group == group
+ Shift = df_dateStart$Date_julian[Ok_dateStart]
+ year = df_dateStart$Year[Ok_dateStart]
OkXEx_code_year = df_XEx$group1 == group & df_XEx$datetime == year
df_XEx$values[OkXEx_code_year] =
df_XEx$values[OkXEx_code_year] + Shift
- OkXEx_code = df_XEx$group1 == group
- XEx_code = df_XEx$values[OkXEx_code]
+ OkXEx_code = df_XEx$group1 == group
+
+ ShiftHydro = df_dateStart$DateHydro_julian[Ok_dateStart]
+ df_XEx$values[OkXEx_code] = df_XEx$values[OkXEx_code] + ShiftHydro
+ XEx_code = df_XEx$values[OkXEx_code]
meanXEx_code = mean(XEx_code, na.rm=TRUE)
dXEx_code = meanXEx_code - XEx_code
stdXEx_code = sd(XEx_code, na.rm=TRUE)
-
OkOverStd = dXEx_code >= stdXEx_code*3
OkOverStd[is.na(OkOverStd)] = FALSE
-
XEx_code[OkOverStd] = XEx_code[OkOverStd] + 365
- print(OkOverStd)
-
# print(group)
# print(df_XEx$datetime[df_XEx$group1 == group][dXEx_code >= stdXEx_code*3])
--
GitLab