diff --git a/processing/analyse.R b/processing/analyse.R
index 35fea94202bad5e16a921e97a391183d26370962..f5409f7ae42aea3717c830046340ca4af9521753 100644
--- a/processing/analyse.R
+++ b/processing/analyse.R
@@ -216,19 +216,17 @@ get_VCN10trend = function (df_data, df_meta, period, p_thresold) {
df_data_roll = tibble()
# For all the code
- for (c in Code) {
+ for (code in Code) {
# Get the data associated to the code
- df_data_code = df_data[df_data$code == c,]
+ df_data_code = df_data[df_data$code == code,]
# Perform the roll mean of the flow over 10 days
- df_data_code = tibble(Date=rollmean(df_data_code$Date,
- 10,
- fill=NA),
- Value=rollmean(df_data_code$Value,
- 10,
- fill=NA),
- code=c)
+ df_data_roll_code = tibble(Date=df_data_code$Date,
+ Value=rollmean(df_data_code$Value,
+ 10,
+ fill=NA),
+ code=code)
# Store the results
- df_data_roll = bind_rows(df_data_roll, df_data_code)
+ df_data_roll = bind_rows(df_data_roll, df_data_roll_code)
}
# Make sure to convert the period to a list
@@ -274,77 +272,100 @@ get_VCN10trend = function (df_data, df_meta, period, p_thresold) {
return (res_VCN10trend)
}
+### 1.4. tINI date
+get_tINItrend = function (df_data, df_meta, period, p_thresold) {
+ # Get all different stations code
+ Code = levels(factor(df_meta$code))
+ # Gets the number of station
+ nCode = length(Code)
+
+ # Blank tibble to store the data averaged
+ df_data_roll = tibble()
-### 1.4. tINI date
-# get_tINItrend = function (df_data, df_meta, period, p_thresold) {
-
-# # Get all different stations code
-# Code = levels(factor(df_meta$code))
-# # Blank tibble to store the data averaged
-# df_data_roll = tibble()
-
-# # For all the code
-# for (c in Code) {
-# # Get the data associated to the code
-# df_data_code = df_data[df_data$code == c,]
-# # Perform the roll mean of the flow over 10 days
-# df_data_code = tibble(Date=df_data_code$Date,
-# Value=rollmean(df_data_code$Value,
-# 10,
-# fill=NA),
-# code=c)
-# # Store the results
-# df_data_roll = bind_rows(df_data_roll, df_data_code)
-# }
-
-# # Make sure to convert the period to a list
-# period = as.list(period)
-# # Set the max interval period as the minimal possible
-# Imax = 0
-# # Blank tibble for data to return
-# df_tMIDtrendB = tibble()
-
-# # For all periods
-# for (per in period) {
-# # Prepare the data to fit the entry of extract.Var
-# df_tMIDlist = prepare(df_data_roll, colnamegroup=c('code'))
-# # Compute the yearly min over the averaged data
-# df_tMIDEx = extract.Var(data.station=df_tMIDlist,
-# funct=which.min,
-# period=per,
-# timestep='year',
-# pos.datetime=1)
-
-# # Converts index of the tMID to the julian date associated
-# df_tMIDEx = prepare_date(df_tMIDEx, df_tMIDlist)
+ # For all the code
+ for (code in Code) {
+ # Get the data associated to the code
+ df_data_code = df_data[df_data$code == code,]
+ # Perform the roll mean of the flow over 10 days
+ df_data_roll_code = tibble(Date=df_data_code$Date,
+ Value=rollmean(df_data_code$Value,
+ 10,
+ fill=NA),
+ code=code)
+ # Store the results
+ df_data_roll = bind_rows(df_data_roll, df_data_roll_code)
+ }
+
+ # Make sure to convert the period to a list
+ period = as.list(period)
+ # Set the max interval period as the minimal possible
+ Imax = 0
+ # Blank tibble for data to return
+ df_tINItrendB = tibble()
+
+ # For all periods
+ for (per in period) {
+
+ df_tINIEx = tibble()
+
+ # For all the code
+ for (k in 1:nCode) {
+ # Gets the code
+ code = Code[k]
+
+ # Get the data associated to the code
+ df_data_roll_code = df_data_roll[df_data_roll$code == code,]
+
+ # Prepare the data to fit the entry of extract.Var
+ df_tINIlist_code = prepare(df_data_roll_code,
+ colnamegroup=c('code'))
+
+ per.start = df_meta$start_year[df_meta$code == code]
+ per.start = paste(sprintf("%02d", per.start), '-01', sep='')
+
+ # Compute the yearly min over the averaged data
+ df_tINIEx_code = extract.Var(data.station=df_tINIlist_code,
+ funct=which.min,
+ period=per,
+ per.start=per.start,
+ timestep='year',
+ pos.datetime=1)
+ #######
+ df_tINIEx_code$group1 = k
+
+ # Store the results
+ df_tINIEx = bind_rows(df_tINIEx, df_tINIEx_code)
+
+ }
+
+ # Converts index of the tINI to the julian date associated
+ df_tINIEx = prepare_date(df_tINIEx, df_tINIlist)
-# # Compute the trend analysis
-# df_tMIDtrend = Estimate.stats(data.extract=df_tMIDEx,
-# level=p_thresold)
-
-# # Get the associated time interval
-# I = interval(per[1], per[2])
-# # If it is the largest interval
-# if (I > Imax) {
-# # Store it and the associated data and info
-# Imax = I
-# df_tMIDlistB = df_tMIDlist
-# df_tMIDExB = df_tMIDEx
-# }
-
-# # Specify the period of analyse
-# df_tMIDtrend = get_period(per, df_tMIDtrend, df_tMIDEx,
-# df_tMIDlist)
-# # Store the trend
-# df_tMIDtrendB = bind_rows(df_tMIDtrendB, df_tMIDtrend)
-# }
-# # Clean results of trend analyse
-# res_tMIDtrend = clean(df_tMIDtrendB, df_tMIDExB, df_tMIDlistB)
-# return (res_tMIDtrend)
-# }
+ # Compute the trend analysis
+ df_tINItrend = Estimate.stats(data.extract=df_tINIEx,
+ level=p_thresold)
+ # Get the associated time interval
+ I = interval(per[1], per[2])
+ # If it is the largest interval
+ if (I > Imax) {
+ # Store it and the associated data and info
+ Imax = I
+ df_tINIlistB = df_tINIlist
+ df_tINIExB = df_tINIEx
+ }
+ # Specify the period of analyse
+ df_tINItrend = get_period(per, df_tINItrend, df_tINIEx,
+ df_tINIlist)
+ # Store the trend
+ df_tINItrendB = bind_rows(df_tINItrendB, df_tINItrend)
+ }
+ # Clean results of trend analyse
+ res_tINItrend = clean(df_tINItrendB, df_tINIExB, df_tINIlistB)
+ return (res_tINItrend)
+}
### 1.5. tMID date
# Realises the trend analysis of the date of the minimum 10 day
@@ -357,17 +378,17 @@ get_tMIDtrend = function (df_data, df_meta, period, p_thresold) {
df_data_roll = tibble()
# For all the code
- for (c in Code) {
+ for (code in Code) {
# Get the data associated to the code
- df_data_code = df_data[df_data$code == c,]
+ df_data_code = df_data[df_data$code == code,]
# Perform the roll mean of the flow over 10 days
- df_data_code = tibble(Date=df_data_code$Date,
- Value=rollmean(df_data_code$Value,
- 10,
- fill=NA),
- code=c)
+ df_data_roll_code = tibble(Date=df_data_code$Date,
+ Value=rollmean(df_data_code$Value,
+ 10,
+ fill=NA),
+ code=code)
# Store the results
- df_data_roll = bind_rows(df_data_roll, df_data_code)
+ df_data_roll = bind_rows(df_data_roll, df_data_roll_code)
}
# Make sure to convert the period to a list
@@ -465,6 +486,8 @@ get_hydrograph = function (df_data, period=NULL, df_meta=NULL) {
if (!is.null(df_meta)) {
# New column in metadata for hydrological regime
df_meta$regime_hydro = NA
+ # New column in metadata for the start of the hydrological year
+ df_meta$start_year = NA
# Get all different stations code
Code = levels(factor(df_meta$code))
@@ -530,7 +553,10 @@ get_hydrograph = function (df_data, period=NULL, df_meta=NULL) {
df_QM = bind_rows(df_QM, df_QMtmp)
# Stores result of the hydrological regime
df_meta$regime_hydro[df_meta$code == code] = classRegime
-
+ # Computes the month of the max QM
+ maxMonth = which.max(df_QM$QM)
+ # Stores it as the start of the hydrological year
+ df_meta$start_year[df_meta$code == code] = maxMonth
# Otherwise
} else {
# No tibble needed
diff --git a/script.R b/script.R
index c659ff6f9167ffde6e7ba336a82009ad32361073..f478638708fdb5a5e885fad611550ecef3cd2927 100644
--- a/script.R
+++ b/script.R
@@ -244,9 +244,9 @@ res_VCN10trend = get_VCN10trend(df_data, df_meta,
p_thresold=p_thresold)
# Start date for low water trend
-# res_tINItrend = get_tINItrend(df_data, df_meta,
- # period=trend_period,
- # p_thresold=p_thresold)
+res_tINItrend = get_tINItrend(df_data, df_meta,
+ period=trend_period,
+ p_thresold=p_thresold)
# Center date for low water trend
res_tMIDtrend = get_tMIDtrend(df_data, df_meta,
@@ -297,28 +297,28 @@ datasheet_layout(toplot=c(
df_data=list(res_QAtrend$data,
res_QMNAtrend$data,
res_VCN10trend$data,
- # res_tINItrend$data,
+ res_tINItrend$data,
res_tMIDtrend$data),
df_trend=list(res_QAtrend$trend,
res_QMNAtrend$trend,
res_VCN10trend$trend,
- # res_tINItrend$trend,
+ res_tINItrend$trend,
res_tMIDtrend$trend),
var=list('QA',
'QMNA',
'VCN10',
- # 'tINI',
+ 'tINI',
'tMID'),
type=list('flow',
'flow',
'flow',
- # 'date',
+ 'date',
'date'),
- layout_matrix=matrix(c(1, 2, 3, 4), ncol=1),
+ layout_matrix=matrix(c(1, 2, 3, 4, 5), ncol=1),
missRect=TRUE,
trend_period=trend_period,