From 8248b35ceee52bd5716f093759145b6e32c977cb Mon Sep 17 00:00:00 2001
From: "louis.heraut" <louis.heraut@inrae.fr>
Date: Fri, 21 Jan 2022 16:40:39 +0100
Subject: [PATCH] INI variable
---
processing/analyse.R | 50 +++++++++++++++++++++++++++++++++---
processing/format.R | 61 +++++++++++---------------------------------
2 files changed, 62 insertions(+), 49 deletions(-)
diff --git a/processing/analyse.R b/processing/analyse.R
index f5409f7..53691f0 100644
--- a/processing/analyse.R
+++ b/processing/analyse.R
@@ -273,6 +273,12 @@ get_VCN10trend = function (df_data, df_meta, period, p_thresold) {
}
### 1.4. tINI date
+
+which_underfirst = function (L, UpLim) {
+ id = which(L < UpLim)[1]
+ return (id)
+}
+
get_tINItrend = function (df_data, df_meta, period, p_thresold) {
# Get all different stations code
@@ -308,6 +314,7 @@ get_tINItrend = function (df_data, df_meta, period, p_thresold) {
for (per in period) {
df_tINIEx = tibble()
+ df_tINIlist = list(data=tibble(), info=tibble())
# For all the code
for (k in 1:nCode) {
@@ -317,27 +324,64 @@ get_tINItrend = function (df_data, df_meta, period, p_thresold) {
# Get the data associated to the code
df_data_roll_code = df_data_roll[df_data_roll$code == code,]
+
+ # Get the data associated to the code
+ df_data_code = df_data[df_data$code == code,]
+
+ # Prepare the data to fit the entry of extract.Var
+ df_QNAlist_code = prepare(df_data_code,
+ colnamegroup=c('code'))
+
+ # Compute the yearly mean over the data
+ df_QNAEx_code = extract.Var(data.station=df_QNAlist_code,
+ funct=min,
+ timestep='year',
+ period=per,
+ pos.datetime=1,
+ na.rm=TRUE)
+
+ print(code)
+
+ print(df_QNAEx_code)
+ QNAmax = max(df_QNAEx_code$values, na.rm=TRUE)
+ print(QNAmax)
+
+
# Prepare the data to fit the entry of extract.Var
df_tINIlist_code = prepare(df_data_roll_code,
colnamegroup=c('code'))
per.start = df_meta$start_year[df_meta$code == code]
per.start = paste(sprintf("%02d", per.start), '-01', sep='')
+
+
+ print(per.start)
# Compute the yearly min over the averaged data
df_tINIEx_code = extract.Var(data.station=df_tINIlist_code,
- funct=which.min,
+ funct=which_underfirst,
period=per,
per.start=per.start,
timestep='year',
- pos.datetime=1)
- #######
+ pos.datetime=1,
+ UpLim=QNAmax)
+
df_tINIEx_code$group1 = k
+ df_tINIlist_code$data$group = k
+ df_tINIlist_code$info$group = k
# Store the results
df_tINIEx = bind_rows(df_tINIEx, df_tINIEx_code)
+ df_tINIlist$data = bind_rows(df_tINIlist$data,
+ df_tINIlist_code$data)
+ df_tINIlist$info = bind_rows(df_tINIlist$info,
+ df_tINIlist_code$info)
+
}
+
+ # print(df_tINIEx)
+ # print(df_tINIlist)
# Converts index of the tINI to the julian date associated
df_tINIEx = prepare_date(df_tINIEx, df_tINIlist)
diff --git a/processing/format.R b/processing/format.R
index d6398ec..a7a03db 100644
--- a/processing/format.R
+++ b/processing/format.R
@@ -112,40 +112,6 @@ reprepare = function(df_XEx, df_Xlist, colnamegroup=NULL) {
prepare_date = function(df_XEx, df_Xlist) {
- # dateMD = substr(df_Xlist$data$Date, 6, 10)
- # idYearList = which(dateMD == "01-01")
- # YearList = df_Xlist$data$Date[idYearList]
- # groupList = df_Xlist$data$group[idYearList]
-
- # Group = levels(factor(df_XEx$group1))
- # for (group in Group) {
-
- # Year = YearList[groupList == group]
-
- # for (idyear in 1:length(Year)) {
- # year = Year[idyear]
-
- # idShift = which(df_Xlist$data$group == group
- # & df_Xlist$data$Date == year)
-
- # okEx = df_XEx$group1 == group & df_XEx$datetime == substr(year, 1, 4)
-
- # df_XEx$values[okEx] = df_XEx$values[okEx] + idShift
- # }
- # }
-
- # idDate = df_XEx$values
- # dateEx = as.Date(df_Xlist$data$Date[idDate])
- # origin = as.Date(paste(format(dateEx, "%Y"), '-01-01', sep=''))
- # ndate = length(origin)
-
- # dateExJul = rep(0, times=ndate)
- # for (i in 1:ndate) {
- # dateExJul[i] = julian(dateEx[i], origin=origin[i])
- # }
-
- # df_XEx$values = dateExJul
-
dateStart_group = summarise(group_by(df_Xlist$data, group),
Date = min(Date))
# filter(group_by(df_Xlist$data, group), Date == min(Date))
@@ -173,18 +139,16 @@ prepare_date = function(df_XEx, df_Xlist) {
OkXEx_code = df_XEx$group1 == group
XEx_code = df_XEx$values[OkXEx_code]
- # dXExUp = abs(XEx_code - c(XEx_code[2:length(XEx_code)],
- # XEx_code[length(XEx_code)]))
- # dXExDown = abs(XEx_code - c(XEx_code[1],
- # XEx_code[1:(length(XEx_code) - 1)]))
- # dExMean = apply(rbind(dXExUp, dXExDown), 2, mean, na.rm=TRUE)
-
meanXEx_code = mean(XEx_code, na.rm=TRUE)
dXEx_code = meanXEx_code - XEx_code
stdXEx_code = sd(XEx_code, na.rm=TRUE)
+
+ OkOverStd = dXEx_code >= stdXEx_code*3
+ OkOverStd[is.na(OkOverStd)] = FALSE
- XEx_code[dXEx_code >= stdXEx_code*3] =
- XEx_code[dXEx_code >= stdXEx_code*3] + 365
+ XEx_code[OkOverStd] = XEx_code[OkOverStd] + 365
+
+ print(OkOverStd)
# print(group)
# print(df_XEx$datetime[df_XEx$group1 == group][dXEx_code >= stdXEx_code*3])
@@ -306,10 +270,15 @@ get_period = function (per, df_Xtrend, df_XEx, df_Xlist) {
id = which(df_Xtrend$group1 == g)
# Computes index of the nearest accessible start and end date
- iStart = which.min(abs(df_XExtmp_code$Date
- - as.Date(per[1])))
- iEnd = which.min(abs(df_XExtmp_code$Date
- - as.Date(per[2])))
+ OkStart = df_XExtmp_code$Date >= as.Date(per[1])
+ OkEnd = df_XExtmp_code$Date <= as.Date(per[2])
+
+ distStart = abs(df_XExtmp_code$Date[OkStart] - as.Date(per[1]))
+ distEnd = abs(df_XExtmp_code$Date[OkEnd] - as.Date(per[2]))
+
+ iStart = which.min(distStart)
+ iEnd = which.min(distEnd)
+
# Stores the start and end of the trend analysis
df_Xtrend$period_start[id] =
--
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