diff --git a/processing/analyse.R b/processing/analyse.R
index b58519d2e35c8dc339bd67e843139e231602b70d..dad623eefb6a06572921e44797560f641093761b 100644
--- a/processing/analyse.R
+++ b/processing/analyse.R
@@ -150,14 +150,14 @@ get_QAtrend = function (df_data, df_meta, period, p_thresold) {
### 1.2. QMNA
# Realise the trend analysis of the monthly minimum flow in the
# year (QMNA) hydrological variable
-get_QMNAtrend = function (df_data, df_meta, period, p_thresold) {
+get_QMNAtrend = function (df_data, df_meta, period, p_thresold, sampleSpan) {
# Removes incomplete data from time series
df_data = remove_incomplete_data(df_data, df_meta,
yearLac_pct=1, yearStart='01-01')
# Samples the data
df_data = sampling_data(df_data, df_meta,
- sampleSpan=c('05-01', '11-30'))
+ sampleSpan=sampleSpan)
# Make sure to convert the period to a list
period = as.list(period)
@@ -219,7 +219,7 @@ get_QMNAtrend = function (df_data, df_meta, period, p_thresold) {
### 1.3. VCN10
# Realises the trend analysis of the minimum 10 day average flow
# over the year (VCN10) hydrological variable
-get_VCN10trend = function (df_data, df_meta, period, p_thresold) {
+get_VCN10trend = function (df_data, df_meta, period, p_thresold, sampleSpan) {
# Removes incomplete data from time series
df_data = remove_incomplete_data(df_data, df_meta,
@@ -227,7 +227,7 @@ get_VCN10trend = function (df_data, df_meta, period, p_thresold) {
# Samples the data
df_data = sampling_data(df_data, df_meta,
- sampleSpan=c('05-01', '11-30'))
+ sampleSpan=sampleSpan)
# Get all different stations code
Code = levels(factor(df_meta$code))
@@ -294,11 +294,61 @@ get_VCN10trend = function (df_data, df_meta, period, p_thresold) {
### 1.4. tINI date
which_underfirst = function (L, UpLim) {
- id = which(L <= UpLim)[1]
+ ID = which(L <= UpLim)
+
+ dID = diff(ID)
+ dID = c(10, dID)
+
+ IDjump = which(dID != 1)
+ Njump = length(IDjump)
+
+ # print('ID')
+ # print(ID)
+ # print('dID')
+ # print(dID)
+ # print('IDjump')
+ # print(IDjump)
+ # print('')
+
+ Periods = vector(mode='list', length=Njump)
+ Nperiod = c()
+
+ for (i in 1:Njump) {
+
+ idStart = IDjump[i]
+
+ if (i < Njump) {
+ idEnd = IDjump[i+1] - 1
+ } else {
+ idEnd = length(ID)
+ }
+
+ # print(paste('Start', idStart))
+ # print(paste('End', idEnd))
+
+ period = ID[idStart:idEnd]
+
+ # print(period)
+ # print('')
+
+ Periods[[i]] = period
+ Nperiod = c(Nperiod, length(period))
+ }
+
+ period_max = Periods[[which.max(Nperiod)]]
+
+ id = period_max[1]
+
+ # print(Nperiod)
+ # print(id)
+
+ # print('')
+ # print('NEXT')
+ # print('')
return (id)
}
-get_tINItrend = function (df_data, df_meta, period, p_thresold) {
+get_tINItrend = function (df_data, df_meta, period, p_thresold, sampleSpan) {
# Get all different stations code
Code = levels(factor(df_meta$code))
@@ -364,8 +414,7 @@ get_tINItrend = function (df_data, df_meta, period, p_thresold) {
# Samples the data
df_data_code = sampling_data(df_data_code,
df_meta=NULL,
- sampleSpan=c('05-01',
- '11-30'),
+ sampleSpan=sampleSpan,
Code=code)
# Removes incomplete data from the averaged time series
@@ -378,8 +427,7 @@ get_tINItrend = function (df_data, df_meta, period, p_thresold) {
# Samples the data
df_data_roll_code = sampling_data(df_data_roll_code,
df_meta=NULL,
- sampleSpan=c('05-01',
- '11-30'),
+ sampleSpan=sampleSpan,
Code=code)
# print('bb')
@@ -484,7 +532,7 @@ get_tINItrend = function (df_data, df_meta, period, p_thresold) {
### 1.5. tMID date
# Realises the trend analysis of the date of the minimum 10 day
# average flow over the year (VCN10) hydrological variable
-get_tMIDtrend = function (df_data, df_meta, period, p_thresold) {
+get_tMIDtrend = function (df_data, df_meta, period, p_thresold, sampleSpan) {
# Get all different stations code
Code = levels(factor(df_meta$code))
@@ -511,7 +559,7 @@ get_tMIDtrend = function (df_data, df_meta, period, p_thresold) {
yearStart='01-01')
# Samples the data
df_data_roll = sampling_data(df_data_roll, df_meta,
- sampleSpan=c('05-01', '11-30'))
+ sampleSpan=sampleSpan)
# Make sure to convert the period to a list
period = as.list(period)
diff --git a/script.R b/script.R
index ce5eb3868deb231729f75a44187ea614e248fd3e..2d206b77579770fd89bc1a2f96567ffb685ae585 100644
--- a/script.R
+++ b/script.R
@@ -62,12 +62,12 @@ filename =
# "P1712910_HYDRO_QJM.txt",
# "P0885010_HYDRO_QJM.txt",
# "O5055010_HYDRO_QJM.txt",
- "O0384010_HYDRO_QJM.txt"
+ # "O0384010_HYDRO_QJM.txt"
# "S4214010_HYDRO_QJM.txt",
# "Q7002910_HYDRO_QJM.txt"
# "O3035210_HYDRO_QJM.txt",
- # "O3121010_HYDRO_QJM.txt",
- # "O0362510_HYDRO_QJM.txt"
+ # "O0554010_HYDRO_QJM.txt",
+ "O1584610_HYDRO_QJM.txt"
)
@@ -106,6 +106,9 @@ mean_period = list(period1, period2)
# p value thresold
p_thresold = 0.1
+# Sampling span of the data
+sampleSpan = c('05-01', '11-30')
+
## MAP
# Path to the shapefile for france contour from 'computer_data_path'
@@ -232,23 +235,27 @@ res_QAtrend = get_QAtrend(df_data, df_meta,
# QMNA tend
res_QMNAtrend = get_QMNAtrend(df_data, df_meta,
period=trend_period,
- p_thresold=p_thresold)
+ p_thresold=p_thresold,
+ sampleSpan=sampleSpan)
# VCN10 trend
-res_VCN10trend = get_VCN10trend(df_data, df_meta,
+res_VCN10trend = get_VCN10trend(df_data, df_meta,
period=trend_period,
- p_thresold=p_thresold)
+ p_thresold=p_thresold,
+ sampleSpan=sampleSpan)
# Start date for low water trend
res_tINItrend = get_tINItrend(df_data, df_meta,
period=trend_period,
- p_thresold=p_thresold)
+ p_thresold=p_thresold,
+ sampleSpan=sampleSpan)
# res_tINItrend = read_listofdf(resdir, 'res_tINItrend')
# Center date for low water trend
res_tMIDtrend = get_tMIDtrend(df_data, df_meta,
period=trend_period,
- p_thresold=p_thresold)
+ p_thresold=p_thresold,
+ sampleSpan=sampleSpan)
### 3.3. Break analysis
# df_break = get_break(res_QAtrend$data, df_meta)