diff --git a/plotting/datasheet.R b/plotting/datasheet.R
index eca2270d031ab85fd687de122896abefc5c714d1..53d670d9753c848890db0e5ebe3ea19f3ef42007 100644
--- a/plotting/datasheet.R
+++ b/plotting/datasheet.R
@@ -35,7 +35,7 @@ source('plotting/shortcut.R', encoding='UTF-8')
# Manages datasheets creations for all stations. Makes the call to
# the different headers, trend analysis graphs and realises arranging
# every plots.
-datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, colorForce, info_header, time_header, foot_note, layout_matrix, info_height, time_ratio, var_ratio, foot_height, resources_path, logo_dir, AEAGlogo_file, INRAElogo_file, FRlogo_file, outdirTmp, df_page=NULL) {
+datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, axis_xlim, colorForce, info_header, time_header, foot_note, layout_matrix, info_height, time_ratio, var_ratio, foot_height, resources_path, logo_dir, AEAGlogo_file, INRAElogo_file, FRlogo_file, outdirTmp, df_page=NULL) {
# The percentage of augmentation and diminution of the min
# and max limits for y axis
@@ -174,13 +174,19 @@ datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, co
if (!is.null(time_header)) {
# Extracts the data serie corresponding to the code
time_header_code = time_header[time_header$code == code,]
- # Gets the limits of the time serie
- axis_xlim = c(min(time_header_code$Date),
- max(time_header_code$Date))
+
+ if (is.null(axis_xlim)) {
+ # Gets the limits of the time serie
+ axis_xlim_code = c(min(time_header_code$Date),
+ max(time_header_code$Date))
+ } else {
+ axis_xlim_code = axis_xlim
+ }
+
# Gets the time serie plot
Htime = time_panel(time_header_code, df_trend_code=NULL,
trend_period=trend_period,
- axis_xlim=axis_xlim, missRect=TRUE,
+ axis_xlim=axis_xlim_code, missRect=TRUE,
unit2day=365.25, var='Q', type='sévérité',
grid=TRUE, ymin_lim=0,
NspaceMax=NspaceMax[k],
@@ -272,8 +278,6 @@ datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, co
color = append(color, colortmp)
grid = FALSE
}
- } else {
- axis_xlim = NULL
}
if (var != 'sqrt(Q)' & var != 'Q') {
@@ -294,7 +298,8 @@ datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, co
p = time_panel(df_data_code, df_trend_code, var=var,
type=type, alpha=alpha, colorForce=colorForce,
missRect=missRect, trend_period=trend_period,
- mean_period=mean_period, axis_xlim=axis_xlim,
+ mean_period=mean_period,
+ axis_xlim=axis_xlim_code,
unit2day=unit2day, grid=grid,
ymin_lim=ymin_lim, color=color,
NspaceMax=NspaceMax[k], first=first,
@@ -467,12 +472,12 @@ time_panel = function (df_data_code, df_trend_code, var, type, alpha=0.1, colorF
i = i + 1
}
maxQ_lim = maxQtmp
-
-
+
# If x axis limits are specified
if (!is.null(axis_xlim)) {
- minor_minDatetmp_lim = as.Date(axis_xlim[1])
- minor_maxDatetmp_lim = as.Date(axis_xlim[2])
+ axis_xlim = as.Date(axis_xlim)
+ minor_minDatetmp_lim = axis_xlim[1]
+ minor_maxDatetmp_lim = axis_xlim[2]
# Otherwise
} else {
minor_minDatetmp_lim = as.Date(df_data_code$Date[1])
@@ -527,11 +532,11 @@ time_panel = function (df_data_code, df_trend_code, var, type, alpha=0.1, colorF
listDate[which.min(abs(listDate - minor_minDatetmp_lim))]
minor_maxDate_lim =
listDate[which.min(abs(listDate - minor_maxDatetmp_lim))]
- minor_minDate_lim = as.Date(paste(minor_minDate_lim,
+ minor_minDate_lim = as.Date(paste(round(minor_minDate_lim),
'-01-01', sep=''))
- minor_maxDate_lim = as.Date(paste(minor_maxDate_lim,
+ minor_maxDate_lim = as.Date(paste(round(minor_maxDate_lim),
'-01-01', sep=''))
-
+
# Open new plot
p = ggplot() + theme_ash
@@ -1158,21 +1163,29 @@ time_panel = function (df_data_code, df_trend_code, var, type, alpha=0.1, colorF
limits = axis_xlim
}
+ if (breakDate < 1) {
+ breaks = waiver()
+ minor_breaks = waiver()
+ date_labels = waiver()
+ } else {
+ breaks = seq(minDate_lim, maxDate_lim,
+ by=paste(breakDate, 'years'))
+ minor_breaks = seq(minor_minDate_lim,
+ minor_maxDate_lim,
+ by=paste(minor_breakDate,
+ 'years'))
+ date_labels = "%Y"
+ }
+
# Parameters of the x axis contain the limit of the date data
p = p +
- scale_x_date(breaks=seq(minDate_lim, maxDate_lim,
- by=paste(breakDate, 'years')),
- minor_breaks=seq(minor_minDate_lim,
- minor_maxDate_lim,
- by=paste(minor_breakDate,
- 'years')),
+ scale_x_date(breaks=breaks,
+ minor_breaks=minor_breaks,
guide='axis_minor',
- date_labels="%Y",
+ date_labels=date_labels,
limits=limits,
position=position,
- expand=c(0, 0))
-
-
+ expand=c(0, 0))
# If it is a date variable
if (type == 'saisonnalité') {
diff --git a/plotting/layout.R b/plotting/layout.R
index 4242719dab5c8a7d8d0e2b00a1606412632e01bb..b1da9cf972f30815f331e7a7f281e06c0b48919e 100644
--- a/plotting/layout.R
+++ b/plotting/layout.R
@@ -125,24 +125,24 @@ contour = void +
## 3. LAYOUT _________________________________________________________
# Generates a PDF that gather datasheets, map and summarize matrix about the trend analyses realised on selected stations
-datasheet_layout = function (df_data, df_meta, layout_matrix,
- toplot=c('datasheet', 'matrix', 'map'),
- figdir='', filedir_opt='', filename_opt='',
- variable='', df_trend=NULL,
- alpha=0.1, unit2day=365.25, var='',
- type='', glose=NULL, trend_period=NULL,
- mean_period=NULL, colorForce=FALSE,
- axis_xlim=NULL,
- missRect=TRUE, time_header=NULL,
- info_header=NULL, foot_note=TRUE,
- info_height=2.8, time_ratio=2,
- var_ratio=3, foot_height=1.25,
- df_shapefile=NULL,
- resources_path=NULL,
- logo_dir=NULL,
- AEAGlogo_file=NULL,
- INRAElogo_file=NULL,
- FRlogo_file=NULL) {
+layout_panel = function (df_data, df_meta, layout_matrix,
+ toplot=c('datasheet', 'matrix', 'map'),
+ figdir='', filedir_opt='', filename_opt='',
+ variable='', df_trend=NULL,
+ alpha=0.1, unit2day=365.25, var='',
+ type='', glose=NULL, trend_period=NULL,
+ mean_period=NULL, colorForce=FALSE,
+ axis_xlim=NULL,
+ missRect=TRUE, time_header=NULL,
+ info_header=NULL, foot_note=TRUE,
+ info_height=2.8, time_ratio=2,
+ var_ratio=3, foot_height=1.25,
+ df_shapefile=NULL,
+ resources_path=NULL,
+ logo_dir=NULL,
+ AEAGlogo_file=NULL,
+ INRAElogo_file=NULL,
+ FRlogo_file=NULL) {
# Name of the document
outfile = "Panels"
@@ -291,6 +291,7 @@ datasheet_layout = function (df_data, df_meta, layout_matrix,
df_meta,
trend_period=trend_period,
mean_period=mean_period,
+ axis_xlim=axis_xlim,
colorForce=colorForce,
info_header=info_header,
time_header=time_header,
diff --git a/processing/analyse.R b/processing/analyse.R
index 87b1d3d96a86654b31824f57408014dca28501df..42540eee35309f58ff4a47e32964aeeac1d98696 100644
--- a/processing/analyse.R
+++ b/processing/analyse.R
@@ -700,7 +700,7 @@ get_hydrograph = function (df_data, period=NULL, df_meta=NULL) {
for (j in 1:length(xref[,1])) {
distance[j] = sum((QM_code / mean(QM_code) - xref[j,])^2)
}
- regime = 1 + length(xref[,1]) - which.min(distance)
+ regime = which.min(distance)
distancemin = distance[which.min(distance)]
if (regime < 7) {
diff --git a/processing/format.R b/processing/format.R
index 11ca6fe6a1cfecd436fa954ce4d49350c8567194..88e390b6081094257c0a7d998f5c69f3cf8372f8 100644
--- a/processing/format.R
+++ b/processing/format.R
@@ -95,6 +95,15 @@ missing_data = function (df_data, df_meta, yearLac_day=3, yearStart='01-01', Cod
for (code in Code) {
# Extracts the data corresponding to the code
df_data_code = df_data[df_data$code == code,]
+
+
+
+ Date_NA = df_data_code$Date[is.na(df_data_code$Value)]
+ # print(Date_NA)
+ # Start_NA
+
+
+
DateMD = substr(df_data_code$Date, 6, 10)
idyearStart = which(DateMD == yearStart)
@@ -316,19 +325,22 @@ prepare_date = function(df_XEx, df_Xlist, per.start="01-01") {
origin = as.Date(paste(format(df_dateStart$Date, "%Y"),
'-', per.start, sep=''))
- originHydro = as.Date(paste(format(df_dateStart$Date, "%Y"),
- '-01-01', sep=''))
+ # originHydro = as.Date(paste(format(df_dateStart$Date, "%Y"),
+ # '-01-01', sep=''))
for (i in 1:nrow(df_dateStart)) {
dateJultmp = julian(date[i], origin=origin[i])
df_dateStart$Date_julian[i] = dateJultmp
- dateJulHydrotmp = julian(date[i], origin=originHydro[i])
- df_dateStart$DateHydro_julian[i] = dateJulHydrotmp
+
+ # print(date[i])
+ # dateJulHydrotmp = julian(date[i], origin=originHydro[i])
+ # df_dateStart$DateHydro_julian[i] = dateJulHydrotmp
}
df_dateStart$Year = format(df_dateStart$Date, "%Y")
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]
@@ -336,11 +348,11 @@ prepare_date = function(df_XEx, df_Xlist, per.start="01-01") {
df_XEx$values[OkXEx_code_year] =
df_XEx$values[OkXEx_code_year] + Shift
- OkXEx_code = df_XEx$group1 == group
-
- ShiftHydro = df_dateStart$DateHydro_julian[Ok_dateStart]
- df_XEx$values[OkXEx_code] = df_XEx$values[OkXEx_code] + ShiftHydro
+ # OkXEx_code = df_XEx$group1 == group
+ # ShiftHydro = df_dateStart$DateHydro_julian[Ok_dateStart]
+ # df_XEx$values[OkXEx_code] = df_XEx$values[OkXEx_code] + ShiftHydro
+
## Add 365 when the point is too remote
# XEx_code = df_XEx$values[OkXEx_code]
# meanXEx_code = mean(XEx_code, na.rm=TRUE)
diff --git a/script.R b/script.R
index 8ce0cc05483a5dd404e9fec5ad5db9689aca861d..18d5b49edacd6083148266b23c62ad842a68c082 100644
--- a/script.R
+++ b/script.R
@@ -55,22 +55,22 @@ filedir =
# Name of the file that will be analysed from the BH directory
# (if 'all', all the file of the directory will be chosen)
filename =
- ""
+ # ""
# "all"
- # c(
+ c(
# "S2235610_HYDRO_QJM.txt",
- # "P1712910_HYDRO_QJM.txt",
- # "P0885010_HYDRO_QJM.txt",
- # "O5055010_HYDRO_QJM.txt",
+ # "P0885010_HYDRO_QJM.txt"
+ # "O3006710_HYDRO_QJM.txt",
+ # "O4704030_HYDRO_QJM.txt"
# "O0384010_HYDRO_QJM.txt",
- # "S4214010_HYDRO_QJM.txt",
- # "Q7002910_HYDRO_QJM.txt",
+ "O0362510_HYDRO_QJM.txt"
+ # "Q7002910_HYDRO_QJM.txt"
# "Q0214010_HYDRO_QJM.txt",
# "O3035210_HYDRO_QJM.txt",
# "O0554010_HYDRO_QJM.txt",
# "Q6332510_HYDRO_QJM.txt"
# "O0362510_HYDRO_QJM.txt"
- # )
+ )
## AGENCE EAU ADOUR GARONNE SELECTION
@@ -80,8 +80,8 @@ AEAGlistdir =
""
AEAGlistname =
- # ""
- "Liste-station_RRSE.docx"
+ ""
+ # "Liste-station_RRSE.docx"
## NIVALE SELECTION
@@ -96,7 +96,17 @@ INRAElistname =
# "INRAE_selection.txt"
-## TREND ANALYSIS
+which_layout =
+ # ('serie')
+ ('analyse')
+ # ('serie', 'analyse')
+
+# Selection
+axis_xlim =
+ NULL
+ # c("2002-01-01", "2003-01-01")
+
+## ANALYSIS
# Time period to analyse
periodAll = c("1800-01-01", "2020-12-31")
periodSub = c("1968-01-01", "2020-12-31")
@@ -119,7 +129,7 @@ sampleSpan = c('05-01', '11-30')
## MAP
# Is the hydrological network needs to be plot
-is_river = TRUE
+is_river = FALSE
############### END OF REGION TO MODIFY (without risk) ###############
@@ -274,56 +284,58 @@ df_meta = get_hydrograph(df_data, df_meta, period=mean_period[[1]])$meta
df_sqrt = compute_sqrt(df_data)
### 3.2. Trend analysis ______________________________________________
-# # QA trend
-# res = get_QAtrend(df_data, df_meta,
-# period=trend_period,
-# alpha=alpha,
-# yearLac_day=yearLac_day)
-# df_QAdata = res$data
-# df_QAmod = res$mod
-# res_QAtrend = res$analyse
-
-# # QMNA tend
-# res = get_QMNAtrend(df_data, df_meta,
-# period=trend_period,
-# alpha=alpha,
-# sampleSpan=sampleSpan,
-# yearLac_day=yearLac_day)
-# df_QMNAdata = res$data
-# df_QMNAmod = res$mod
-# res_QMNAtrend = res$analyse
-
-# # VCN10 trend
-# res = get_VCN10trend(df_data, df_meta,
-# period=trend_period,
-# alpha=alpha,
-# sampleSpan=sampleSpan,
-# yearLac_day=yearLac_day)
-# df_VCN10data = res$data
-# df_VCN10mod = res$mod
-# res_VCN10trend = res$analyse
-
-# # Start date for low water trend
-# res = get_tDEBtrend(df_data, df_meta,
-# period=trend_period,
-# alpha=alpha,
-# sampleSpan=sampleSpan,
-# thresold_type='VCN10',
-# select_longest=TRUE,
-# yearLac_day=yearLac_day)
-# df_tDEBdata = res$data
-# df_tDEBmod = res$mod
-# res_tDEBtrend = res$analyse
-
-# # Center date for low water trend
-# res = get_tCENtrend(df_data, df_meta,
-# period=trend_period,
-# alpha=alpha,
-# sampleSpan=sampleSpan,
-# yearLac_day=yearLac_day)
-# df_tCENdata = res$data
-# df_tCENmod = res$mod
-# res_tCENtrend = res$analyse
+if ('analyse' %in% which_layout) {
+ # QA trend
+ res = get_QAtrend(df_data, df_meta,
+ period=trend_period,
+ alpha=alpha,
+ yearLac_day=yearLac_day)
+ df_QAdata = res$data
+ df_QAmod = res$mod
+ res_QAtrend = res$analyse
+
+ # QMNA tend
+ res = get_QMNAtrend(df_data, df_meta,
+ period=trend_period,
+ alpha=alpha,
+ sampleSpan=sampleSpan,
+ yearLac_day=yearLac_day)
+ df_QMNAdata = res$data
+ df_QMNAmod = res$mod
+ res_QMNAtrend = res$analyse
+
+ # VCN10 trend
+ res = get_VCN10trend(df_data, df_meta,
+ period=trend_period,
+ alpha=alpha,
+ sampleSpan=sampleSpan,
+ yearLac_day=yearLac_day)
+ df_VCN10data = res$data
+ df_VCN10mod = res$mod
+ res_VCN10trend = res$analyse
+
+ # Start date for low water trend
+ res = get_tDEBtrend(df_data, df_meta,
+ period=trend_period,
+ alpha=alpha,
+ sampleSpan=sampleSpan,
+ thresold_type='VCN10',
+ select_longest=TRUE,
+ yearLac_day=yearLac_day)
+ df_tDEBdata = res$data
+ df_tDEBmod = res$mod
+ res_tDEBtrend = res$analyse
+
+ # Center date for low water trend
+ res = get_tCENtrend(df_data, df_meta,
+ period=trend_period,
+ alpha=alpha,
+ sampleSpan=sampleSpan,
+ yearLac_day=yearLac_day)
+ df_tCENdata = res$data
+ df_tCENmod = res$mod
+ res_tCENtrend = res$analyse
+}
### 3.3. Break analysis ______________________________________________
# df_break = get_break(res_QAtrend$data, df_meta)
@@ -362,28 +374,31 @@ df_shapefile = ini_shapefile(resources_path,
### 5.1. Simple time panel to criticize station data _________________
# Plot time panel of debit by stations
-# datasheet_layout(toplot=c('datasheet'),
-# df_meta=df_meta,
-# df_data=list(df_data,
-# df_sqrt),
-# var=list('Q', 'sqrt(Q)'),
-# type=list('data', 'data'),
-# layout_matrix=matrix(c(1, 2), ncol=1),
-# info_header=df_data,
-# df_shapefile=df_shapefile,
-# figdir=figdir,
-# resources_path=resources_path,
-# logo_dir=logo_dir,
-# AEAGlogo_file=AEAGlogo_file,
-# INRAElogo_file=INRAElogo_file,
-# FRlogo_file=FRlogo_file)
-
+if ('serie' %in% which_layout) {
+ layout_panel(toplot=c('datasheet'),
+ df_meta=df_meta,
+ df_data=list(df_data,
+ df_sqrt),
+ var=list('Q', 'sqrt(Q)'),
+ type=list('data', 'data'),
+ axis_xlim=axis_xlim,
+ layout_matrix=matrix(c(1, 2), ncol=1),
+ info_header=df_data,
+ df_shapefile=df_shapefile,
+ figdir=figdir,
+ resources_path=resources_path,
+ logo_dir=logo_dir,
+ AEAGlogo_file=AEAGlogo_file,
+ INRAElogo_file=INRAElogo_file,
+ FRlogo_file=FRlogo_file)
+}
### 5.2. Analysis layout _____________________________________________
-datasheet_layout(toplot=c(
- 'datasheet',
- 'matrix',
- 'map'
+if ('analyse' %in% which_layout) {
+ layout_panel(toplot=c(
+ 'datasheet'
+ # 'matrix',
+ # 'map'
),
df_meta=df_meta,
@@ -428,3 +443,4 @@ datasheet_layout(toplot=c(
AEAGlogo_file=AEAGlogo_file,
INRAElogo_file=INRAElogo_file,
FRlogo_file=FRlogo_file)
+}