diff --git a/plotting/layout.R b/plotting/layout.R
index 08267e73cd621889da2b3643637356fc02b40e06..d90002c041d8471e48fa2b6dca7d78db8a1f7dcf 100644
--- a/plotting/layout.R
+++ b/plotting/layout.R
@@ -14,7 +14,7 @@ library(RColorBrewer)
source('plotting/panel.R', encoding='latin1')
-panels_layout = function (df_data, df_meta, layout_matrix, figdir='', filedir_opt='', filename_opt='', variable='', df_trend=NULL, p_threshold=0.1, unit2day=365.25, type='', trend_period=NULL, mean_period=NULL, axis_xlim=NULL, missRect=FALSE, time_header=NULL, info_header=TRUE, info_ratio=1, time_ratio=2, var_ratio=3, fr_shpdir=NULL, fr_shpname=NULL, bs_shpdir=NULL, bs_shpname=NULL, rv_shpdir=NULL, rv_shpname=NULL, computer_data_path=NULL) {
+panels_layout = function (df_data, df_meta, layout_matrix, isplot=c('datasheet', 'matrix', 'map'), figdir='', filedir_opt='', filename_opt='', variable='', df_trend=NULL, p_threshold=0.1, unit2day=365.25, type='', trend_period=NULL, mean_period=NULL, axis_xlim=NULL, missRect=FALSE, time_header=NULL, info_header=TRUE, info_ratio=1, time_ratio=2, var_ratio=3, fr_shpdir=NULL, fr_shpname=NULL, bs_shpdir=NULL, bs_shpname=NULL, rv_shpdir=NULL, rv_shpname=NULL, computer_data_path=NULL) {
outfile = "Panels"
if (filename_opt != '') {
@@ -121,291 +121,296 @@ panels_layout = function (df_data, df_meta, layout_matrix, figdir='', filedir_op
list_df2plot[[i]] = df2plot
}
- Start_code = vector(mode='list', length=nCode)
- End_code = vector(mode='list', length=nCode)
- Code_code = vector(mode='list', length=nCode)
- Periods_code = vector(mode='list', length=nCode)
- for (j in 1:nCode) {
-
- code = Code[j]
-
- df_trend_code = df_trendtmp[df_trendtmp$code == code,]
-
- Start = df_trend_code$period_start
- UStart = levels(factor(Start))
-
- End = df_trend_code$period_end
- UEnd = levels(factor(End))
-
- nPeriod = max(length(UStart), length(UEnd))
+ if ('datasheet' %in% isplot) {
- Periods = c()
-
- for (i in 1:nPeriod_max) {
- Periods = append(Periods,
- paste(substr(Start[i], 1, 4),
- substr(End[i], 1, 4),
- sep=' / '))
- }
- Start_code[[j]] = Start
- End_code[[j]] = End
- Code_code[[j]] = code
- Periods_code[[j]] = Periods
- }
+ Start_code = vector(mode='list', length=nCode)
+ End_code = vector(mode='list', length=nCode)
+ Code_code = vector(mode='list', length=nCode)
+ Periods_code = vector(mode='list', length=nCode)
- TrendMean_code = array(rep(1, nPeriod_max*nbp*nCode),
- dim=c(nPeriod_max, nbp, nCode))
+ for (j in 1:nCode) {
+
+ code = Code[j]
- for (j in 1:nPeriod_max) {
+ df_trend_code = df_trendtmp[df_trendtmp$code == code,]
- for (k in 1:nCode) {
+ Start = df_trend_code$period_start
+ UStart = levels(factor(Start))
- code = Code[k]
+ End = df_trend_code$period_end
+ UEnd = levels(factor(End))
- for (i in 1:nbp) {
-
- df_data = list_df2plot[[i]]$data
- df_trend = list_df2plot[[i]]$trend
- p_threshold = list_df2plot[[i]]$p_threshold
-
- df_data_code = df_data[df_data$code == code,]
- df_trend_code = df_trend[df_trend$code == code,]
-
- Start = Start_code[Code_code == code][[1]][j]
- End = End_code[Code_code == code][[1]][j]
- Periods = Periods_code[Code_code == code][[1]][j]
-
- df_data_code_per =
- df_data_code[df_data_code$Date >= Start
- & df_data_code$Date <= End,]
+ nPeriod = max(length(UStart), length(UEnd))
- df_trend_code_per =
- df_trend_code[df_trend_code$period_start == Start
- & df_trend_code$period_end == End,]
-
- Ntrend = nrow(df_trend_code_per)
- if (Ntrend > 1) {
- df_trend_code_per = df_trend_code_per[1,]
- }
-
- dataMean = mean(df_data_code_per$Qm3s, na.rm=TRUE)
- trendMean = df_trend_code_per$trend / dataMean
+ Periods = c()
- TrendMean_code[j, i, k] = trendMean
+ for (i in 1:nPeriod_max) {
+ Periods = append(Periods,
+ paste(substr(Start[i], 1, 4),
+ substr(End[i], 1, 4),
+ sep=' / '))
}
+ Start_code[[j]] = Start
+ End_code[[j]] = End
+ Code_code[[j]] = code
+ Periods_code[[j]] = Periods
}
- }
- minTrendMean = apply(TrendMean_code, c(1, 2), min, na.rm=TRUE)
- maxTrendMean = apply(TrendMean_code, c(1, 2), max, na.rm=TRUE)
-
- for (code in Code) {
-
- # Print code of the station for the current plotting
- print(paste("Plotting for station :", code))
-
- nbh = as.numeric(info_header) + as.numeric(!is.null(time_header))
- nbg = nbp + nbh
-
- P = vector(mode='list', length=nbg)
+ TrendMean_code = array(rep(1, nPeriod_max*nbp*nCode),
+ dim=c(nPeriod_max, nbp, nCode))
- if (info_header) {
- time_header_code = time_header[time_header$code == code,]
-
- Hinfo = info_panel(list_df2plot,
- df_meta,
- computer_data_path=computer_data_path,
- fr_shpdir=fr_shpdir,
- fr_shpname=fr_shpname,
- bs_shpdir=bs_shpdir,
- bs_shpname=bs_shpname,
- rv_shpdir=rv_shpdir,
- rv_shpname=rv_shpname,
- codeLight=code,
- df_data_code=time_header_code)
- P[[1]] = Hinfo
- }
+ for (j in 1:nPeriod_max) {
- if (!is.null(time_header)) {
+ for (k in 1:nCode) {
+
+ code = Code[k]
+
+ for (i in 1:nbp) {
+
+ df_data = list_df2plot[[i]]$data
+ df_trend = list_df2plot[[i]]$trend
+ p_threshold = list_df2plot[[i]]$p_threshold
- time_header_code = time_header[time_header$code == code,]
- axis_xlim = c(min(time_header_code$Date),
- max(time_header_code$Date))
-
- Htime = time_panel(time_header_code, df_trend_code=NULL,
- trend_period=trend_period, missRect=TRUE,
- unit2day=365.25, type='Q', first=FALSE)
+ df_data_code = df_data[df_data$code == code,]
+ df_trend_code = df_trend[df_trend$code == code,]
- P[[2]] = Htime
- }
-
- # map = map_panel()
-
- nbcol = ncol(as.matrix(layout_matrix))
- for (i in 1:nbp) {
- df_data = list_df2plot[[i]]$data
- df_trend = list_df2plot[[i]]$trend
- p_threshold = list_df2plot[[i]]$p_threshold
- unit2day = list_df2plot[[i]]$unit2day
- missRect = list_df2plot[[i]]$missRect
- type = list_df2plot[[i]]$type
-
- df_data_code = df_data[df_data$code == code,]
- df_trend_code = df_trend[df_trend$code == code,]
-
- color = c()
- # for (j in 1:nrow(df_trend_code)) {
- grey = 85
- for (j in 1:nPeriod_max) {
- if (df_trend_code$p[j] <= p_threshold){
- # color_res = get_color(df_trend_code$trend[j],
- # minTrend[i],
- # maxTrend[i],
- # palette_name='perso',
- # reverse=TRUE)
-
Start = Start_code[Code_code == code][[1]][j]
End = End_code[Code_code == code][[1]][j]
Periods = Periods_code[Code_code == code][[1]][j]
-
+
df_data_code_per =
df_data_code[df_data_code$Date >= Start
& df_data_code$Date <= End,]
-
+
df_trend_code_per =
df_trend_code[df_trend_code$period_start == Start
& df_trend_code$period_end == End,]
-
+
Ntrend = nrow(df_trend_code_per)
if (Ntrend > 1) {
df_trend_code_per = df_trend_code_per[1,]
}
- dataMean = mean(df_data_code$Qm3s, na.rm=TRUE)
+ dataMean = mean(df_data_code_per$Qm3s, na.rm=TRUE)
trendMean = df_trend_code_per$trend / dataMean
-
- color_res = get_color(trendMean,
- minTrendMean[j, i],
- maxTrendMean[j, i],
- palette_name='perso',
- reverse=TRUE)
-
- colortmp = color_res
- } else {
- colortmp = paste('grey', grey, sep='')
- grey = grey - 10
+
+ TrendMean_code[j, i, k] = trendMean
}
+ }
+ }
+
+ minTrendMean = apply(TrendMean_code, c(1, 2), min, na.rm=TRUE)
+ maxTrendMean = apply(TrendMean_code, c(1, 2), max, na.rm=TRUE)
+
+ for (code in Code) {
+
+ # Print code of the station for the current plotting
+ print(paste("Plotting for station :", code))
+
+ nbh = as.numeric(info_header) + as.numeric(!is.null(time_header))
+ nbg = nbp + nbh
+
+ P = vector(mode='list', length=nbg)
- color = append(color, colortmp)
+ if (info_header) {
+ time_header_code = time_header[time_header$code == code,]
+
+ Hinfo = info_panel(list_df2plot,
+ df_meta,
+ computer_data_path=computer_data_path,
+ fr_shpdir=fr_shpdir,
+ fr_shpname=fr_shpname,
+ bs_shpdir=bs_shpdir,
+ bs_shpname=bs_shpname,
+ rv_shpdir=rv_shpdir,
+ rv_shpname=rv_shpname,
+ codeLight=code,
+ df_data_code=time_header_code)
+ P[[1]] = Hinfo
+ }
+
+ if (!is.null(time_header)) {
+
+ time_header_code = time_header[time_header$code == code,]
+ axis_xlim = c(min(time_header_code$Date),
+ max(time_header_code$Date))
+
+ Htime = time_panel(time_header_code, df_trend_code=NULL,
+ trend_period=trend_period, missRect=TRUE,
+ unit2day=365.25, type='Q', first=FALSE)
+
+ P[[2]] = Htime
}
-
- p = time_panel(df_data_code, df_trend_code, type=type,
- p_threshold=p_threshold, missRect=missRect,
- trend_period=trend_period,
- mean_period=mean_period, axis_xlim=axis_xlim,
- unit2day=unit2day, last=(i > nbp-nbcol),
- color=color)
- P[[i+nbh]] = p
- }
+ # map = map_panel()
+
+ nbcol = ncol(as.matrix(layout_matrix))
+ for (i in 1:nbp) {
+ df_data = list_df2plot[[i]]$data
+ df_trend = list_df2plot[[i]]$trend
+ p_threshold = list_df2plot[[i]]$p_threshold
+ unit2day = list_df2plot[[i]]$unit2day
+ missRect = list_df2plot[[i]]$missRect
+ type = list_df2plot[[i]]$type
- layout_matrix = as.matrix(layout_matrix)
- nel = nrow(layout_matrix)*ncol(layout_matrix)
+ df_data_code = df_data[df_data$code == code,]
+ df_trend_code = df_trend[df_trend$code == code,]
- idNA = which(is.na(layout_matrix), arr.ind=TRUE)
+ color = c()
+ # for (j in 1:nrow(df_trend_code)) {
+ grey = 85
+ for (j in 1:nPeriod_max) {
+ if (df_trend_code$p[j] <= p_threshold){
+ # color_res = get_color(df_trend_code$trend[j],
+ # minTrend[i],
+ # maxTrend[i],
+ # palette_name='perso',
+ # reverse=TRUE)
+
+ Start = Start_code[Code_code == code][[1]][j]
+ End = End_code[Code_code == code][[1]][j]
+ Periods = Periods_code[Code_code == code][[1]][j]
+
+ df_data_code_per =
+ df_data_code[df_data_code$Date >= Start
+ & df_data_code$Date <= End,]
+
+ df_trend_code_per =
+ df_trend_code[df_trend_code$period_start == Start
+ & df_trend_code$period_end == End,]
+
+ Ntrend = nrow(df_trend_code_per)
+ if (Ntrend > 1) {
+ df_trend_code_per = df_trend_code_per[1,]
+ }
+
+ dataMean = mean(df_data_code$Qm3s, na.rm=TRUE)
+ trendMean = df_trend_code_per$trend / dataMean
+
+ color_res = get_color(trendMean,
+ minTrendMean[j, i],
+ maxTrendMean[j, i],
+ palette_name='perso',
+ reverse=TRUE)
+
+ colortmp = color_res
+ } else {
+ colortmp = paste('grey', grey, sep='')
+ grey = grey - 10
+ }
- layout_matrix[idNA] = seq(max(layout_matrix, na.rm=TRUE) + 1,
- max(layout_matrix, na.rm=TRUE) + 1 +
- nel)
+ color = append(color, colortmp)
+ }
+
+ p = time_panel(df_data_code, df_trend_code, type=type,
+ p_threshold=p_threshold, missRect=missRect,
+ trend_period=trend_period,
+ mean_period=mean_period, axis_xlim=axis_xlim,
+ unit2day=unit2day, last=(i > nbp-nbcol),
+ color=color)
+
+ P[[i+nbh]] = p
+ }
- layout_matrix_H = layout_matrix + nbh
+ layout_matrix = as.matrix(layout_matrix)
+ nel = nrow(layout_matrix)*ncol(layout_matrix)
+ idNA = which(is.na(layout_matrix), arr.ind=TRUE)
- info_ratio_scale = info_ratio
- time_ratio_scale = time_ratio
- var_ratio_scale = var_ratio
+ layout_matrix[idNA] = seq(max(layout_matrix, na.rm=TRUE) + 1,
+ max(layout_matrix, na.rm=TRUE) + 1 +
+ nel)
- ndec_info = 0
- ndec_time = 0
- ndec_var = 0
+ layout_matrix_H = layout_matrix + nbh
- if (info_ratio_scale != round(info_ratio_scale)) {
- ndec_info = nchar(gsub('^[0-9]+.', '',
- as.character(info_ratio_scale)))
- }
- if (time_ratio_scale != round(time_ratio_scale)) {
- ndec_time = nchar(gsub('^[0-9]+.', '',
- as.character(time_ratio_scale)))
- }
-
- if (var_ratio_scale != round(var_ratio_scale)) {
- ndec_var = nchar(gsub('^[0-9]+.', '',
- as.character(var_ratio_scale)))
- }
-
- ndec = max(c(ndec_info, ndec_time, ndec_var))
-
- info_ratio_scale = info_ratio_scale * 10^ndec
- time_ratio_scale = time_ratio_scale * 10^ndec
- var_ratio_scale = var_ratio_scale * 10^ndec
-
- LM = c()
- LMcol = ncol(layout_matrix_H)
- LMrow = nrow(layout_matrix_H)
- for (i in 1:(LMrow+nbh)) {
-
- if (info_header & i == 1) {
- # LM = rbind(LM, rep(i, times=LMcol))
- LM = rbind(LM,
- matrix(rep(rep(i, times=LMcol),
- times=info_ratio_scale),
- ncol=LMcol, byrow=TRUE))
-
- } else if (!is.null(time_header) & i == 2) {
- LM = rbind(LM,
- matrix(rep(rep(i, times=LMcol),
- times=time_ratio_scale),
- ncol=LMcol, byrow=TRUE))
-
- } else {
- LM = rbind(LM,
- matrix(rep(layout_matrix_H[i-nbh,],
- times=var_ratio_scale),
- ncol=LMcol, byrow=TRUE))
- }}
-
- plot = grid.arrange(grobs=P, layout_matrix=LM)
-
- # plot = grid.arrange(rbind(cbind(ggplotGrob(P[[2]]), ggplotGrob(P[[2]])), cbind(ggplotGrob(P[[3]]), ggplotGrob(P[[3]]))), heights=c(1/3, 2/3))
-
+ info_ratio_scale = info_ratio
+ time_ratio_scale = time_ratio
+ var_ratio_scale = var_ratio
- # Saving
- ggsave(plot=plot,
- path=outdirTmp,
- filename=paste(as.character(code), '.pdf', sep=''),
- width=21, height=29.7, units='cm', dpi=100)
+ ndec_info = 0
+ ndec_time = 0
+ ndec_var = 0
- }
+ if (info_ratio_scale != round(info_ratio_scale)) {
+ ndec_info = nchar(gsub('^[0-9]+.', '',
+ as.character(info_ratio_scale)))
+ }
- matrice_panel(list_df2plot, df_meta, trend_period, mean_period,
- slice=12, outdirTmp=outdirTmp, A3=TRUE)
+ if (time_ratio_scale != round(time_ratio_scale)) {
+ ndec_time = nchar(gsub('^[0-9]+.', '',
+ as.character(time_ratio_scale)))
+ }
+
+ if (var_ratio_scale != round(var_ratio_scale)) {
+ ndec_var = nchar(gsub('^[0-9]+.', '',
+ as.character(var_ratio_scale)))
+ }
+
+ ndec = max(c(ndec_info, ndec_time, ndec_var))
+
+ info_ratio_scale = info_ratio_scale * 10^ndec
+ time_ratio_scale = time_ratio_scale * 10^ndec
+ var_ratio_scale = var_ratio_scale * 10^ndec
+
+ LM = c()
+ LMcol = ncol(layout_matrix_H)
+ LMrow = nrow(layout_matrix_H)
+ for (i in 1:(LMrow+nbh)) {
+
+ if (info_header & i == 1) {
+ # LM = rbind(LM, rep(i, times=LMcol))
+ LM = rbind(LM,
+ matrix(rep(rep(i, times=LMcol),
+ times=info_ratio_scale),
+ ncol=LMcol, byrow=TRUE))
+
+ } else if (!is.null(time_header) & i == 2) {
+ LM = rbind(LM,
+ matrix(rep(rep(i, times=LMcol),
+ times=time_ratio_scale),
+ ncol=LMcol, byrow=TRUE))
+
+ } else {
+ LM = rbind(LM,
+ matrix(rep(layout_matrix_H[i-nbh,],
+ times=var_ratio_scale),
+ ncol=LMcol, byrow=TRUE))
+ }}
+
+ plot = grid.arrange(grobs=P, layout_matrix=LM)
+
+ # plot = grid.arrange(rbind(cbind(ggplotGrob(P[[2]]), ggplotGrob(P[[2]])), cbind(ggplotGrob(P[[3]]), ggplotGrob(P[[3]]))), heights=c(1/3, 2/3))
+
-
- map_panel(list_df2plot,
- df_meta,
- idPer=length(trend_period),
- computer_data_path=computer_data_path,
- fr_shpdir=fr_shpdir,
- fr_shpname=fr_shpname,
- bs_shpdir=bs_shpdir,
- bs_shpname=bs_shpname,
- rv_shpdir=rv_shpdir,
- rv_shpname=rv_shpname,
- outdirTmp=outdirTmp,
- margin=margin(t=5, r=0, b=5, l=5, unit="mm"))
+ # Saving
+ ggsave(plot=plot,
+ path=outdirTmp,
+ filename=paste(as.character(code), '.pdf', sep=''),
+ width=21, height=29.7, units='cm', dpi=100)
+
+ }
+ }
+ if ('matrix' %in% isplot) {
+ matrice_panel(list_df2plot, df_meta, trend_period, mean_period,
+ slice=12, outdirTmp=outdirTmp, A3=TRUE)
+ }
+ if ('map' %in% isplot) {
+ map_panel(list_df2plot,
+ df_meta,
+ idPer=length(trend_period),
+ computer_data_path=computer_data_path,
+ fr_shpdir=fr_shpdir,
+ fr_shpname=fr_shpname,
+ bs_shpdir=bs_shpdir,
+ bs_shpname=bs_shpname,
+ rv_shpdir=rv_shpdir,
+ rv_shpname=rv_shpname,
+ outdirTmp=outdirTmp,
+ margin=margin(t=5, r=0, b=5, l=5, unit="mm"))
+ }
# PDF combine
pdf_combine(input=file.path(outdirTmp, list.files(outdirTmp)),
diff --git a/plotting/panel.R b/plotting/panel.R
index 09934555857811e143c601e5d2ef22cd1333f0ed..f52008299b1042f687827ed01a91477438416346 100644
--- a/plotting/panel.R
+++ b/plotting/panel.R
@@ -724,7 +724,10 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
if (nPeriod > nPeriod_max) {
nPeriod_max = nPeriod
}
- }
+ }
+
+ # print(nPeriod_trend)
+ # print(nPeriod_max)
Start_code = vector(mode='list', length=nCode)
End_code = vector(mode='list', length=nCode)
@@ -1014,51 +1017,46 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
nMat = as.integer(nsubCodefL/slice) + 1
+ print(nMat)
+
for (imat in 1:nMat) {
subCode = subCodefL[(slice*(imat-1)+1):(slice*imat)]
subCode = subCode[!is.na(subCode)]
+
+ # print('aaa')
+ # print(subCode)
nsubCode = length(subCode)
+
+ CodefL_trend = substr(Code_trend, 1, 1) == fL
- subPeriods_trend = Periods_trend[substr(Code_trend, 1, 1)
- == fL]
- subNPeriod_trend = NPeriod_trend[substr(Code_trend, 1, 1)
- == fL]
- subType_trend = Type_trend[substr(Code_trend, 1, 1)
- == fL]
- subCode_trend = Code_trend[substr(Code_trend, 1, 1)
- == fL]
- subPthresold_trend = Pthresold_trend[substr(Code_trend, 1, 1)
- == fL]
- subTrendMean_trend = TrendMean_trend[substr(Code_trend, 1, 1)
- == fL]
- subDataMean_trend = DataMean_trend[substr(Code_trend, 1, 1)
- == fL]
- subFill_trend = Fill_trend[substr(Code_trend, 1, 1)
- == fL]
- subColor_trend = Color_trend[substr(Code_trend, 1, 1)
- == fL]
+ subPeriods_trend = Periods_trend[CodefL_trend]
+ subNPeriod_trend = NPeriod_trend[CodefL_trend]
+ subType_trend = Type_trend[CodefL_trend]
+ subCode_trend = Code_trend[CodefL_trend]
+ subPthresold_trend = Pthresold_trend[CodefL_trend]
+ subTrendMean_trend = TrendMean_trend[CodefL_trend]
+ subDataMean_trend = DataMean_trend[CodefL_trend]
+ subFill_trend = Fill_trend[CodefL_trend]
+ subColor_trend = Color_trend[CodefL_trend]
+
+ # print(subNPeriod_trend)
- subPeriods_mean = Periods_mean[substr(Code_mean, 1, 1)
- == fL]
- subNPeriod_mean = NPeriod_mean[substr(Code_mean, 1, 1)
- == fL]
- subType_mean = Type_mean[substr(Code_mean, 1, 1)
- == fL]
- subCode_mean = Code_mean[substr(Code_mean, 1, 1)
- == fL]
- subDataMean_mean = DataMean_mean[substr(Code_mean, 1, 1)
- == fL]
- subBreakMean_mean = BreakMean_mean[substr(Code_mean, 1, 1)
- == fL]
- subFill_mean = Fill_mean[substr(Code_mean, 1, 1)
- == fL]
- subColor_mean = Color_mean[substr(Code_mean, 1, 1)
- == fL]
+ CodefL_mean = substr(Code_mean, 1, 1) == fL
- title = df_meta[df_meta$code == subCode[1],]$region_hydro
+ subPeriods_mean = Periods_mean[CodefL_mean]
+ subNPeriod_mean = NPeriod_mean[CodefL_mean]
+ subType_mean = Type_mean[CodefL_mean]
+ subCode_mean = Code_mean[CodefL_mean]
+ subDataMean_mean = DataMean_mean[CodefL_mean]
+ subBreakMean_mean = BreakMean_mean[CodefL_mean]
+ subFill_mean = Fill_mean[CodefL_mean]
+ subColor_mean = Color_mean[CodefL_mean]
+ title = df_meta[df_meta$code == subCode[1],]$region_hydro
+
+ # print('bbb')
### Plot ###
height = length(subCode)
@@ -1089,6 +1087,8 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
size=6, color="#00A3A8")
+ # print('ccc')
+
### Trend ###
for (j in 1:nPeriod_trend) {
@@ -1097,7 +1097,7 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
Code_trend_per =
subCode_trend[subNPeriod_trend == j]
Pthresold_trend_per =
- subPthresold_trend[NPeriod_trend == j]
+ subPthresold_trend[subNPeriod_trend == j]
TrendMean_trend_per =
subTrendMean_trend[subNPeriod_trend == j]
DataMean_trend_per =
@@ -1106,7 +1106,7 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
subFill_trend[subNPeriod_trend == j]
Color_trend_per =
subColor_trend[subNPeriod_trend == j]
-
+
Xtmp = as.integer(factor(as.character(Type_trend_per)))
Xc = j + (j - 1)*nbp*2
@@ -1151,7 +1151,7 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
gg_circle(r=0.45, xc=Xc, yc=Y[i],
fill='white', color='grey40')
}
-
+
for (i in 1:length(TrendMean_trend_per)) {
trendMean = TrendMean_trend_per[i]
trendC = signif(trendMean*100, 2)
@@ -1222,6 +1222,8 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
}
}
+ # print('ddd')
+
### Mean ###
for (j in 1:nPeriod_mean) {
@@ -1239,6 +1241,8 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
Color_mean_per =
subColor_mean[subNPeriod_mean == j]
+ # print('ddd1')
+
Xtmp_mean = as.integer(factor(as.character(Type_mean_per)))
Xc_mean = j + (j - 1)*nbp + X[length(X)]
@@ -1269,6 +1273,8 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
label=periodName,
hjust=0, vjust=0.5,
size=3, color='grey40')
+
+ # print('ddd2')
if (j > 1) {
x = Xr_mean[1] - 0.4
@@ -1288,6 +1294,8 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
hjust=0, vjust=0.5,
size=3, color='grey40')
}
+
+ # print('ddd3')
for (i in 1:length(Xm_mean)) {
mat = mat +
@@ -1306,8 +1314,12 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
}
}
+ # print('ddd4')
+
for (i in 1:length(DataMean_mean_per)) {
dataMean = signif(DataMean_mean_per[i], 2)
+
+ # print(i)
mat = mat +
annotate('text', x=Xm_mean[i], y=Y[i],
@@ -1318,6 +1330,8 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
if (j > 1) {
BreakMean = BreakMean_mean_per[i]
BreakC = signif(BreakMean*100, 2)
+
+ # print(BreakMean)
mat = mat +
annotate('text', x=Xr_mean[i], y=Y[i],
@@ -1326,6 +1340,8 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
size=3, color='white')
}
}
+
+ # print('ddd5')
mat = mat +
annotate('text', x=Xc_mean, y=max(Y) + 0.85,
@@ -1338,6 +1354,8 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
hjust=0.5, vjust=0.5,
size=3, color='grey20')
+
+ # print('ddd6')
for (i in 1:nbp) {
type = list_df2plot[[i]]$type
@@ -1356,6 +1374,8 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
}
}
+ # print('ddd7')
+
for (k in 1:nsubCode) {
code = subCode[k]
label = Periods_mean[NPeriod_mean == j
@@ -1376,6 +1396,7 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
}
}
+ # print('eee')
### Code ###
for (k in 1:nsubCode) {
@@ -1398,7 +1419,9 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
hjust=1, vjust=0.5,
size=3.5, color="#00A3A8")
}
-
+
+
+ # print('fff')
### Environment ###
@@ -1424,12 +1447,16 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
height = 21
dpi = 100
}
+
+ # print('ggg')
ggsave(plot=mat,
path=outdirTmp,
filename=paste(outnameTmp, '_', fL, imat, '.pdf',
sep=''),
width=width, height=height, units='cm', dpi=dpi)
+
+ # print('hhh')
}
}
diff --git a/script.R b/script.R
index 323c222d3d7088623eefe9e44133e60a04145d60..09c9e59bf323698bda0917c7fdbe243403189a22 100644
--- a/script.R
+++ b/script.R
@@ -142,7 +142,7 @@ if (AGlistname != ""){
filename = df_selec_AG[df_selec_AG$ok,]$filename
#####
- # filename = filename[(1+30):(16+30)]
+ filename = filename[(1):(25)]
#####
# Extract metadata about selected stations
@@ -234,7 +234,8 @@ res_VCN10trend = get_VCN10trend(df_data, df_meta,
# figdir=figdir,
# filename_opt='time')
-panels_layout(list(res_QAtrend$data, res_QMNAtrend$data,
+panels_layout(isplot=c('matrix'),
+ df_data=list(res_QAtrend$data, res_QMNAtrend$data,
res_VCN10trend$data),
layout_matrix=c(1, 2, 3),
df_meta=df_meta,