From f89d857415a76ca2d09010414ca1d5279819439c Mon Sep 17 00:00:00 2001
From: "louis.heraut" <louis.heraut@inrae.fr>
Date: Sun, 19 Dec 2021 04:43:26 +0100
Subject: [PATCH] End layout
---
plotting/panel.R | 1053 ++++++++++++++++++++++++++++------------------
script.R | 12 +-
2 files changed, 648 insertions(+), 417 deletions(-)
diff --git a/plotting/panel.R b/plotting/panel.R
index f508e29..0993455 100644
--- a/plotting/panel.R
+++ b/plotting/panel.R
@@ -686,7 +686,7 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
}
-matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice=NULL, outdirTmp='', outnameTmp='matrix', A3=FALSE) {
+matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice=NULL, outdirTmp='', outnameTmp='matrix', title=NULL, A3=FALSE) {
nbp = length(list_df2plot)
@@ -694,518 +694,745 @@ matrice_panel = function (list_df2plot, df_meta, trend_period, mean_period, slic
Code = levels(factor(df_meta$code))
nCode = length(Code)
- if (!is.null(slice)) {
+ # nbp = length(list_df2plot)
- # By
- nMat = as.integer(nCode/slice) + 1
- sublist_df2plot = list_df2plot
+ # # Get all different stations code
+ # Code = levels(factor(df_meta$code))
+ # nCode = length(Code)
- for (i in 1:nMat) {
+ df_trend = list_df2plot[[1]]$trend
- subdf_meta = df_meta[(slice*(i-1)+1):(slice*i),]
- subdf_meta = subdf_meta[!is.na(subdf_meta$code),]
- subCode = subdf_meta$code
-
- for (j in 1:nbp) {
- df_datatmp = list_df2plot[[j]]$data
- df_trendtmp = list_df2plot[[j]]$trend
+ # Convert 'trend_period' to list
+ trend_period = as.list(trend_period)
+ # Number of trend period
+ nPeriod_trend = length(trend_period)
+
+ nPeriod_max = 0
+ for (code in Code) {
+
+ df_trend_code = df_trend[df_trend$code == code,]
- subdf_data = df_datatmp[(df_datatmp$code %in% subCode),]
- subdf_trend = df_trendtmp[(df_trendtmp$code %in% subCode),]
-
- sublist_df2plot[[j]]$data = subdf_data
- sublist_df2plot[[j]]$trend = subdf_trend
- }
-
- mat = matrice_panel(sublist_df2plot,
- subdf_meta,
- trend_period=trend_period,
- mean_period=mean_period,
- outdirTmp=outdirTmp,
- outnameTmp=paste(outnameTmp,
- '_', i,
- sep=''),
- A3=A3)
- }
+ Start = df_trend_code$period_start
+ UStart = levels(factor(Start))
+
+ End = df_trend_code$period_end
+ UEnd = levels(factor(End))
- } else {
+ nPeriod = max(length(UStart), length(UEnd))
- print(paste('matrix :', outnameTmp))
- # nbp = length(list_df2plot)
+ if (nPeriod > nPeriod_max) {
+ nPeriod_max = nPeriod
+ }
+ }
+
+ 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)
- # # Get all different stations code
- # Code = levels(factor(df_meta$code))
- # nCode = length(Code)
+ for (j in 1:nCode) {
+
+ code = Code[j]
- df_trend = list_df2plot[[1]]$trend
+ df_trend_code = df_trend[df_trend$code == code,]
- nPeriod_max = 0
- for (code in Code) {
-
- df_trend_code = df_trend[df_trend$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))
- 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))
+ Periods = c()
- if (nPeriod > nPeriod_max) {
- nPeriod_max = nPeriod
- }
+ for (i in 1:nPeriod_trend) {
+ Periods = append(Periods,
+ paste(Start[i],
+ End[i],
+ 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)
+ }
- for (j in 1:nCode) {
-
- code = Code[j]
+ TrendMean_code = array(rep(1, nPeriod_trend*nbp*nCode),
+ dim=c(nPeriod_trend, nbp, nCode))
- df_trend_code = df_trend[df_trend$code == code,]
+ for (j in 1:nPeriod_trend) {
- Start = df_trend_code$period_start
- UStart = levels(factor(Start))
+ for (k in 1:nCode) {
- End = df_trend_code$period_end
- UEnd = levels(factor(End))
+ code = Code[k]
- nPeriod = max(length(UStart), length(UEnd))
+ for (i in 1:nbp) {
+
+ df_data = list_df2plot[[i]]$data
+ df_trend = list_df2plot[[i]]$trend
+ p_threshold = list_df2plot[[i]]$p_threshold
- Periods = c()
+ df_data_code = df_data[df_data$code == code,]
+ df_trend_code = df_trend[df_trend$code == code,]
- for (i in 1:nPeriod_max) {
- Periods = append(Periods,
- paste(substr(Start[i], 1, 4),
- substr(End[i], 1, 4),
- sep=' / '))
- }
+ Start = Start_code[Code_code == code][[1]][j]
+ End = End_code[Code_code == code][[1]][j]
+ Periods = Periods_code[Code_code == code][[1]][j]
- Start_code[[j]] = Start
- End_code[[j]] = End
- Code_code[[j]] = code
- Periods_code[[j]] = Periods
-
+ 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_per$Qm3s, na.rm=TRUE)
+ trendMean = df_trend_code_per$trend / dataMean
+
+ TrendMean_code[j, i, k] = trendMean
+ }
}
+ }
- TrendMean_code = array(rep(1, nPeriod_max*nbp*nCode),
- dim=c(nPeriod_max, nbp, nCode))
+ minTrendMean = apply(TrendMean_code, c(1, 2), min, na.rm=TRUE)
+ maxTrendMean = apply(TrendMean_code, c(1, 2), max, na.rm=TRUE)
- for (j in 1:nPeriod_max) {
+
+ Periods_trend = c()
+ NPeriod_trend = c()
+ Type_trend = list()
+ Code_trend = c()
+ Pthresold_trend = c()
+ TrendMean_trend = c()
+ DataMean_trend = c()
+ Fill_trend = c()
+ Color_trend = c()
+
+ for (j in 1:nPeriod_trend) {
- for (k in 1:nCode) {
-
- code = Code[k]
+ for (code in Code) {
+
+ for (i in 1:nbp) {
+ df_data = list_df2plot[[i]]$data
+ df_trend = list_df2plot[[i]]$trend
+ p_threshold = list_df2plot[[i]]$p_threshold
+ type = list_df2plot[[i]]$type
- 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$code == code,]
+ df_data_code = df_data[df_data$code == code,]
+ df_trend_code = df_trend[df_trend$code == code,]
- Start = Start_code[Code_code == code][[1]][j]
- End = End_code[Code_code == code][[1]][j]
- Periods = Periods_code[Code_code == code][[1]][j]
+ Start = Start_code[Code_code == code][[1]][j]
+ End = End_code[Code_code == code][[1]][j]
+ Periods = Periods_code[Code_code == code][[1]][j]
- df_data_code_per =
- df_data_code[df_data_code$Date >= Start
- & df_data_code$Date <= End,]
+ df_data_code_per =
+ df_data_code[df_data_code$Date >= Start
+ & df_data_code$Date <= End,]
- df_trend_code_per =
- df_trend_code[df_trend_code$period_start == Start
- & df_trend_code$period_end == End,]
+ df_trend_code_per =
+ df_trend_code[df_trend_code$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$trend / dataMean
+ Ntrend = nrow(df_trend_code_per)
+ if (Ntrend > 1) {
+ df_trend_code_per = df_trend_code_per[1,]
+ }
+
+ dataMean = mean(df_data_code_per$Qm3s, na.rm=TRUE)
+ trendMean = df_trend_code_per$trend / dataMean
- TrendMean_code[j, i, k] = trendMean
+ if (df_trend_code_per$p <= p_threshold){
+ color_res = get_color(trendMean,
+ minTrendMean[j, i],
+ maxTrendMean[j, i],
+ palette_name='perso',
+ reverse=TRUE)
+
+ fill = color_res
+ color = 'white'
+ Pthresold = p_thresold
+ } else {
+ fill = 'white'
+ color = 'grey85'
+ Pthresold = NA
}
+
+ Periods_trend = append(Periods_trend, Periods)
+ NPeriod_trend = append(NPeriod_trend, j)
+ Type_trend = append(Type_trend, type)
+ Code_trend = append(Code_trend, code)
+ Pthresold_trend = append(Pthresold_trend, Pthresold)
+ TrendMean_trend = append(TrendMean_trend, trendMean)
+ DataMean_trend = append(DataMean_trend, dataMean)
+ Fill_trend = append(Fill_trend, fill)
+ Color_trend = append(Color_trend, color)
}
}
+ }
- minTrendMean = apply(TrendMean_code, c(1, 2), min, na.rm=TRUE)
- maxTrendMean = apply(TrendMean_code, c(1, 2), max, na.rm=TRUE)
-
- Periods_trend = c()
- NPeriod_trend = c()
- Type_trend = list()
- Code_trend = c()
- Pthresold_trend = c()
- TrendMean_trend = c()
- DataMean_trend = c()
- Fill_trend = c()
- Color_trend = c()
+
+ # If there is a 'mean_period'
+ if (!is.null(mean_period)) {
+
+ Periods_mean = c()
+ NPeriod_mean = c()
+ Type_mean = list()
+ Code_mean = c()
+ DataMean_mean = c()
+ BreakMean_mean = c()
+
+ # Convert 'mean_period' to list
+ mean_period = as.list(mean_period)
+ # Number of mean period
+ nPeriod_mean = length(mean_period)
- for (j in 1:nPeriod_max) {
+ BreakMean_code = array(rep(1, nPeriod_mean*nbp*nCode),
+ dim=c(nPeriod_mean, nbp, nCode))
+
+ dataMeantmp = array(rep(NA, nbp*nCode),
+ dim=c(nbp, nCode))
+
+ # For all mean period
+ for (j in 1:nPeriod_mean) {
- for (code in Code) {
+ 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]]$p_threshold
type = list_df2plot[[i]]$type
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]
-
+
+ # Get the current start and end of the sub period
+ Start_mean = mean_period[[j]][1]
+ End_mean = mean_period[[j]][2]
+
+ # Extract the data corresponding to this sub period
df_data_code_per =
- df_data_code[df_data_code$Date >= Start
- & df_data_code$Date <= End,]
+ df_data_code[df_data_code$Date >= Start_mean
+ & df_data_code$Date <= End_mean,]
+
+ # Min for the sub period
+ Datemin = min(df_data_code_per$Date)
+
+ # Max for the sub period
+ Datemax = max(df_data_code_per$Date)
- df_trend_code_per =
- df_trend_code[df_trend_code$period_start == Start
- & df_trend_code$period_end == End,]
+ Periods = paste(Datemin, Datemax,
+ sep=' / ')
- Ntrend = nrow(df_trend_code_per)
- if (Ntrend > 1) {
- df_trend_code_per = df_trend_code_per[1,]
+ # Mean of the flow over the sub period
+ dataMean = mean(df_data_code_per$Qm3s,
+ na.rm=TRUE)
+
+ if (j > 1) {
+ Break = dataMean - dataMeantmp[i, k]
+ } else {
+ Break = NA
}
- dataMean = mean(df_data_code_per$Qm3s, na.rm=TRUE)
- trendMean = df_trend_code_per$trend / dataMean
-
- if (df_trend_code_per$p <= p_threshold){
- color_res = get_color(trendMean,
- minTrendMean[j, i],
- maxTrendMean[j, i],
- palette_name='perso',
- reverse=TRUE)
-
- fill = color_res
- color = 'white'
- Pthresold = p_thresold
- } else {
- fill = 'white'
- color = 'grey85'
- Pthresold = NA
- }
-
- Periods_trend = append(Periods_trend, Periods)
- NPeriod_trend = append(NPeriod_trend, j)
- Type_trend = append(Type_trend, type)
- Code_trend = append(Code_trend, code)
- Pthresold_trend = append(Pthresold_trend, Pthresold)
- TrendMean_trend = append(TrendMean_trend, trendMean)
- DataMean_trend = append(DataMean_trend, dataMean)
- Fill_trend = append(Fill_trend, fill)
- Color_trend = append(Color_trend, color)
+ BreakMean = Break / dataMeantmp[i, k]
+ BreakMean_code[j, i, k] = BreakMean
+
+ dataMeantmp[i, k] = dataMean
+
+
+ Periods_mean = append(Periods_mean, Periods)
+ NPeriod_mean = append(NPeriod_mean, j)
+ Type_mean = append(Type_mean, type)
+ Code_mean = append(Code_mean, code)
+ DataMean_mean = append(DataMean_mean, dataMean)
+ BreakMean_mean = append(BreakMean_mean,
+ BreakMean)
}
}
}
+
+ minBreakMean = apply(BreakMean_code, c(1, 2),
+ min, na.rm=TRUE)
+ maxBreakMean = apply(BreakMean_code, c(1, 2),
+ max, na.rm=TRUE)
-
- Periods_mean = c()
- NPeriod_mean = c()
- Type_mean = list()
- Code_mean = c()
- DataMean_mean = c()
- Break_mean = c()
Fill_mean = c()
Color_mean = c()
- # If there is a 'mean_period'
- if (!is.null(mean_period)) {
- # Convert 'mean_period' to list
- mean_period = as.list(mean_period)
- # Number of mean period
- nPeriod_mean = length(mean_period)
-
- dataMeantmp = array(rep(0, nbp*nCode),
- dim=c(nbp, nCode))
+ ii = 1
+ for (j in 1:nPeriod_mean) {
- # For all mean period
- for (j in 1:nPeriod_mean) {
-
- for (k in 1:nCode) {
+ for (k in 1:nCode) {
+
+ code = Code[k]
- code = Code[k]
+ for (i in 1:nbp) {
- for (i in 1:nbp) {
-
- df_data = list_df2plot[[i]]$data
- type = list_df2plot[[i]]$type
-
- df_data_code = df_data[df_data$code == code,]
-
- # Get the current start and end of the sub period
- Start_mean = mean_period[[j]][1]
- End_mean = mean_period[[j]][2]
-
- # Extract the data corresponding to this sub period
- df_data_code_per =
- df_data_code[df_data_code$Date >= Start_mean
- & df_data_code$Date <= End_mean,]
-
- # Min for the sub period
- Datemin = min(df_data_code_per$Date)
-
- # Max for the sub period
- Datemax = max(df_data_code_per$Date)
-
- Periods = paste(Datemin, Datemax,
- sep=' / ')
+ BreakMean = BreakMean_mean[ii]
+
+ color_res = get_color(BreakMean,
+ minBreakMean[j, i],
+ maxBreakMean[j, i],
+ palette_name='perso',
+ reverse=TRUE)
+
+ fill = color_res
+ color = 'white'
- fill = 'white'
- color = 'grey85'
-
- # Mean of the flow over the sub period
- dataMean = mean(df_data_code_per$Qm3s,
- na.rm=TRUE)
-
- Break = dataMeantmp[i, k] - dataMean
- dataMeantmp[i, k] = dataMean
-
- Periods_mean = append(Periods_mean, Periods)
- NPeriod_mean = append(NPeriod_mean, j)
- Type_mean = append(Type_mean, type)
- Code_mean = append(Code_mean, code)
- DataMean_mean = append(DataMean_mean, dataMean)
- Break_mean = append(Break_mean, Break)
- Fill_mean = append(Fill_mean, fill)
- Color_mean = append(Color_mean, color)
-
- }
+ Fill_mean = append(Fill_mean, fill)
+ Color_mean = append(Color_mean, color)
+
+ ii = ii + 1
}
}
}
+ }
- height = length(Code)
- width = nbp * 2 * nPeriod_max + nPeriod_max + nPeriod_mean * nbp + nPeriod_mean + nbp
-
- print(nPeriod_mean)
- print(width)
-
-
- options(repr.plot.width=width, repr.plot.height=height)
-
- mat = ggplot() + theme_ash +
-
- theme(
- panel.border=element_blank(),
- axis.text.x=element_blank(),
- axis.text.y=element_blank(),
- axis.ticks.y=element_blank(),
- axis.ticks.x=element_blank(),
- axis.title.y=element_blank(),
- )
-
- # xt = -1
- # yt = height + 1.75
- # Title = bquote(bold(Territoire))
-
- # mat = mat +
- # annotate("text", x=xt, y=yt,
- # label=Title,
- # hjust=0, vjust=0.5,
- # size=6, color="#00A3A8")
-
-
- ### Trend ###
- for (j in 1:nPeriod_max) {
-
- Type_trend_per = Type_trend[NPeriod_trend == j]
- Code_trend_per = Code_trend[NPeriod_trend == j]
- Pthresold_trend_per = Pthresold_trend[NPeriod_trend == j]
- TrendMean_trend_per = TrendMean_trend[NPeriod_trend == j]
- DataMean_trend_per = DataMean_trend[NPeriod_trend == j]
- Fill_trend_per = Fill_trend[NPeriod_trend == j]
- Color_trend_per = Color_trend[NPeriod_trend == j]
- Xtmp = as.integer(factor(as.character(Type_trend_per)))
+ if (is.null(slice)) {
+ slice = nCode
+ }
- Xc = j + (j - 1)*nbp*2
- Xm = Xtmp + (j - 1)*nbp*2 + j
- X = Xtmp + (j - 1)*nbp*2 + nbp + j
+ firstLetter = levels(factor(substr(Code, 1, 1)))
+
+ for (fL in firstLetter) {
- Y = as.integer(factor(Code_trend_per))
+ print(paste('matrix for region :', fL))
- x = Xc - 0.4
- xend = X[length(X)] + 0.25
- y = height + 1
- yend = height + 1
+ subCodefL = Code[substr(Code, 1, 1) == fL]
+ nsubCodefL = length(subCodefL)
+
+ nMat = as.integer(nsubCodefL/slice) + 1
+
+ for (imat in 1:nMat) {
+ subCode = subCodefL[(slice*(imat-1)+1):(slice*imat)]
- mat = mat +
- annotate("segment",
- x=x, xend=xend,
- y=y, yend=yend,
- color="grey40", size=0.35)
+ subCode = subCode[!is.na(subCode)]
- yt = y + 0.15
- Start = trend_period[[j]][1]
- End = trend_period[[j]][2]
- periodName = bquote(bold('Période')~bold(.(as.character(j))))
- # bquote(bold(.(Start))~'/'~bold(.(End)))
-
- mat = mat +
- annotate("text", x=x, y=yt,
- label=periodName,
- hjust=0, vjust=0.5,
- size=3, color='grey40')
+ nsubCode = length(subCode)
- for (i in 1:length(X)) {
- mat = mat +
-
- gg_circle(r=0.45, xc=X[i], yc=Y[i],
- fill=Fill_trend_per[i], color=Color_trend_per[i]) +
-
- gg_circle(r=0.45, xc=Xm[i], yc=Y[i],
- fill='white', color='grey40') +
-
- 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 = round(trendMean*100, 2)
-
- if (!is.na(Pthresold_trend_per[i])) {
- Tcolor = 'white'
- } else {
- Tcolor = 'grey85'
- }
+ 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_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]
+
+ title = df_meta[df_meta$code == subCode[1],]$region_hydro
+
+
+ ### Plot ###
+ height = length(subCode)
+ width = nbp * 2 * nPeriod_trend + nPeriod_trend + nPeriod_mean * nbp + nPeriod_mean + nbp
+
+ options(repr.plot.width=width, repr.plot.height=height)
+
+ mat = ggplot() + theme_ash +
- dataMean = round(DataMean_trend_per[i], 2)
+ theme(
+ panel.border=element_blank(),
+ axis.text.x=element_blank(),
+ axis.text.y=element_blank(),
+ axis.ticks.y=element_blank(),
+ axis.ticks.x=element_blank(),
+ axis.title.y=element_blank(),
+ plot.margin=margin(t=5, r=5, b=5, l=5, unit="mm")
+ )
+
+ xt = 1 - 6
+ yt = height + 2
+ Title = bquote(bold(.(title)))
+
+ mat = mat +
+ annotate("text", x=xt, y=yt,
+ label=Title,
+ hjust=0, vjust=1,
+ size=6, color="#00A3A8")
+
+
+ ### Trend ###
+ for (j in 1:nPeriod_trend) {
+
+ Type_trend_per =
+ subType_trend[subNPeriod_trend == j]
+ Code_trend_per =
+ subCode_trend[subNPeriod_trend == j]
+ Pthresold_trend_per =
+ subPthresold_trend[NPeriod_trend == j]
+ TrendMean_trend_per =
+ subTrendMean_trend[subNPeriod_trend == j]
+ DataMean_trend_per =
+ subDataMean_trend[subNPeriod_trend == j]
+ Fill_trend_per =
+ 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
+ Xm = Xtmp + (j - 1)*nbp*2 + j
+ X = Xtmp + (j - 1)*nbp*2 + nbp + j
+
+ Y = as.integer(factor(Code_trend_per))
+
+ x = Xc - 0.4
+ xend = X[length(X)] + 0.25
+ y = height + 1
+ yend = height + 1
mat = mat +
- annotate('text', x=X[i], y=Y[i],
- label=trendC,
- hjust=0.5, vjust=0.5,
- size=3, color=Tcolor) +
+ annotate("segment",
+ x=x, xend=xend,
+ y=y, yend=yend,
+ color="grey40", size=0.35)
+
+ yt = y + 0.15
+ Start = trend_period[[j]][1]
+ End = trend_period[[j]][2]
+ periodName = bquote(bold('Période')~bold(.(as.character(j))))
+ # bquote(bold(.(Start))~'/'~bold(.(End)))
- annotate('text', x=Xm[i], y=Y[i],
- label=dataMean,
- hjust=0.5, vjust=0.5,
- size=3, color='grey40')
- }
+ mat = mat +
+ annotate("text", x=x, y=yt,
+ label=periodName,
+ hjust=0, vjust=0.5,
+ size=3, color='grey40')
+
+ for (i in 1:length(X)) {
+ mat = mat +
+
+ gg_circle(r=0.45, xc=X[i], yc=Y[i],
+ fill=Fill_trend_per[i],
+ color=Color_trend_per[i]) +
+
+ gg_circle(r=0.45, xc=Xm[i], yc=Y[i],
+ fill='white', color='grey40') +
+
+ gg_circle(r=0.45, xc=Xc, yc=Y[i],
+ fill='white', color='grey40')
+ }
- mat = mat +
- annotate('text', x=Xc, y=max(Y) + 0.85,
- label=bquote(bold('Début')),
- hjust=0.5, vjust=0.5,
- size=3, color='grey20') +
+ for (i in 1:length(TrendMean_trend_per)) {
+ trendMean = TrendMean_trend_per[i]
+ trendC = signif(trendMean*100, 2)
- annotate('text', x=Xc, y=max(Y) + 0.6,
- label=bquote(bold('Fin')),
- hjust=0.5, vjust=0.5,
- size=3, color='grey20')
+ if (!is.na(Pthresold_trend_per[i])) {
+ Tcolor = 'white'
+ } else {
+ Tcolor = 'grey85'
+ }
+
+ dataMean = signif(DataMean_trend_per[i], 2)
- for (i in 1:nbp) {
- type = list_df2plot[[i]]$type
+ mat = mat +
+ annotate('text', x=X[i], y=Y[i],
+ label=trendC,
+ hjust=0.5, vjust=0.5,
+ size=3, color=Tcolor) +
+
+ annotate('text', x=Xm[i], y=Y[i],
+ label=dataMean,
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40')
+ }
+
mat = mat +
- annotate('text', x=X[i], y=max(Y) + 0.7,
- label=bquote(.(type)),
+ annotate('text', x=Xc, y=max(Y) + 0.85,
+ label=bquote(bold('Début')),
hjust=0.5, vjust=0.5,
- size=3.5, color='grey20') +
+ size=3, color='grey20') +
- annotate('text', x=Xm[i], y=max(Y) + 0.7,
- label=bquote('µ'*.(type)),
+ annotate('text', x=Xc, y=max(Y) + 0.6,
+ label=bquote(bold('Fin')),
hjust=0.5, vjust=0.5,
- size=3.5, color='grey20')
- }
- }
-
-
- ### Mean ###
-
-
+ size=3, color='grey20')
+
+ for (i in 1:nbp) {
+ type = list_df2plot[[i]]$type
+ mat = mat +
+ annotate('text', x=X[i], y=max(Y) + 0.7,
+ label=bquote(.(type)),
+ hjust=0.5, vjust=0.5,
+ size=3.5, color='grey20') +
+
+ annotate('text', x=Xm[i], y=max(Y) + 0.7,
+ label=bquote('µ'*.(type)),
+ hjust=0.5, vjust=0.5,
+ size=3.5, color='grey20')
+ }
+ for (k in 1:nsubCode) {
+ code = subCode[k]
+ label = Periods_trend[NPeriod_trend == j
+ & subCode_trend == code][1]
+ periodStart = substr(label, 1, 4)
+ periodEnd = substr(label, 14, 17)
+
+ mat = mat +
+ annotate('text', x=Xc, y=k + 0.13,
+ label=bquote(bold(.(periodStart))),
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40') +
+
+ annotate('text', x=Xc, y=k - 0.13,
+ label=bquote(bold(.(periodEnd))),
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40')
+ }
+ }
+ ### Mean ###
+ for (j in 1:nPeriod_mean) {
+ Type_mean_per =
+ subType_mean[subNPeriod_mean == j]
+ Code_mean_per =
+ subCode_mean[subNPeriod_mean == j]
+ DataMean_mean_per =
+ subDataMean_mean[subNPeriod_mean == j]
+ BreakMean_mean_per =
+ subBreakMean_mean[subNPeriod_mean == j]
+ Fill_mean_per =
+ subFill_mean[subNPeriod_mean == j]
+ Color_mean_per =
+ subColor_mean[subNPeriod_mean == j]
+
+ Xtmp_mean = as.integer(factor(as.character(Type_mean_per)))
+
+ Xc_mean = j + (j - 1)*nbp + X[length(X)]
+ Xm_mean = Xtmp_mean + (j - 1)*nbp + j + X[length(X)]
+ Xr_mean = Xtmp_mean + (j - 1)*nbp*2 + j + X[length(X)]
+
+ Y_mean = as.integer(factor(Code_mean_per))
-
- ### Code ###
- for (i in 1:length(Code)) {
-
- code = Code[i]
- name = df_meta[df_meta$code == code,]$nom
- ncharMax = 30
- if (nchar(name) > ncharMax) {
- name = paste(substr(name, 1, ncharMax), '...', sep='')
- }
+ x = Xc_mean - 0.4
+ xend = Xm_mean[length(Xm_mean)] + 0.25
+ y = height + 1
+ yend = height + 1
- mat = mat +
- annotate('text', x=0.3, y=i + 0.14,
- label=bquote(bold(.(code))),
- hjust=1, vjust=0.5,
- size=3.5, color="#00A3A8") +
+ mat = mat +
+ annotate("segment",
+ x=x, xend=xend,
+ y=y, yend=yend,
+ color="grey40", size=0.35)
+
+ yt = y + 0.15
+ Start = mean_period[[j]][1]
+ End = mean_period[[j]][2]
- annotate('text', x=0.3, y=i - 0.14,
- label=name,
- hjust=1, vjust=0.5,
- size=3.5, color="#00A3A8")
+ periodName = bquote(bold('Période')~bold(.(as.character(j+nPeriod_trend))))
+ mat = mat +
+ annotate("text", x=x, y=yt,
+ label=periodName,
+ hjust=0, vjust=0.5,
+ size=3, color='grey40')
+
+ if (j > 1) {
+ x = Xr_mean[1] - 0.4
+ xend = Xr_mean[length(Xr_mean)] + 0.25
+
+ mat = mat +
+ annotate("segment",
+ x=x, xend=xend,
+ y=y, yend=yend,
+ color="grey40", size=0.35)
+
+ breakName = bquote(bold('Rupture')~bold(.(as.character(j-1+nPeriod_trend)))*bold('-')*bold(.(as.character(j+nPeriod_trend))))
+
+ mat = mat +
+ annotate("text", x=x, y=yt,
+ label=breakName,
+ hjust=0, vjust=0.5,
+ size=3, color='grey40')
+ }
+
+ for (i in 1:length(Xm_mean)) {
+ mat = mat +
+
+ gg_circle(r=0.45, xc=Xm_mean[i], yc=Y[i],
+ fill='white', color='grey40') +
+
+ gg_circle(r=0.45, xc=Xc_mean, yc=Y[i],
+ fill='white', color='grey40')
+
+ if (j > 1) {
+ mat = mat +
+ gg_circle(r=0.45, xc=Xr_mean[i], yc=Y[i],
+ fill=Fill_mean_per[i],
+ color=Color_mean_per[i])
+ }
+ }
- for (j in 1:nPeriod_max) {
- Xc = j + (j - 1)*nbp*2
- label = Periods_code[Code_code == code][[1]][j]
- periodStart = substr(label, 1, 4)
- periodEnd = substr(label, 8, 11)
+ for (i in 1:length(DataMean_mean_per)) {
+ dataMean = signif(DataMean_mean_per[i], 2)
+
+ mat = mat +
+ annotate('text', x=Xm_mean[i], y=Y[i],
+ label=dataMean,
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40')
+
+ if (j > 1) {
+ BreakMean = BreakMean_mean_per[i]
+ BreakC = signif(BreakMean*100, 2)
+
+ mat = mat +
+ annotate('text', x=Xr_mean[i], y=Y[i],
+ label=BreakC,
+ hjust=0.5, vjust=0.5,
+ size=3, color='white')
+ }
+ }
mat = mat +
- annotate('text', x=Xc, y=i + 0.13,
- label=bquote(bold(.(periodStart))),
+ annotate('text', x=Xc_mean, y=max(Y) + 0.85,
+ label=bquote(bold('Début')),
hjust=0.5, vjust=0.5,
- size=3, color='grey40') +
+ size=3, color='grey20') +
- annotate('text', x=Xc, y=i - 0.13,
- label=bquote(bold(.(periodEnd))),
+ annotate('text', x=Xc_mean, y=max(Y) + 0.6,
+ label=bquote(bold('Fin')),
hjust=0.5, vjust=0.5,
- size=3, color='grey40')
+ size=3, color='grey20')
+
+
+ for (i in 1:nbp) {
+ type = list_df2plot[[i]]$type
+ mat = mat +
+ annotate('text', x=Xm_mean[i], y=max(Y) + 0.7,
+ label=bquote('µ'*.(type)),
+ hjust=0.5, vjust=0.5,
+ size=3.5, color='grey20')
+
+ if (j > 1) {
+ mat = mat +
+ annotate('text', x=Xr_mean[i], y=max(Y) + 0.7,
+ label=bquote('d'*.(type)),
+ hjust=0.5, vjust=0.5,
+ size=3.5, color='grey20')
+ }
+ }
+
+ for (k in 1:nsubCode) {
+ code = subCode[k]
+ label = Periods_mean[NPeriod_mean == j
+ & subCode_mean == code][1]
+ periodStart = substr(label, 1, 4)
+ periodEnd = substr(label, 14, 17)
+
+ mat = mat +
+ annotate('text', x=Xc_mean, y=k + 0.13,
+ label=bquote(bold(.(periodStart))),
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40') +
+
+ annotate('text', x=Xc_mean, y=k - 0.13,
+ label=bquote(bold(.(periodEnd))),
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40')
+ }
}
- }
- ### Environment ###
+
+ ### Code ###
+ for (k in 1:nsubCode) {
+
+ code = subCode[k]
+ name = df_meta[df_meta$code == code,]$nom
+ ncharMax = 40
+ if (nchar(name) > ncharMax) {
+ name = paste(substr(name, 1, ncharMax), '...', sep='')
+ }
- mat = mat +
+ mat = mat +
+ annotate('text', x=0.3, y=k + 0.14,
+ label=bquote(bold(.(code))),
+ hjust=1, vjust=0.5,
+ size=3.5, color="#00A3A8") +
+
+ annotate('text', x=0.3, y=k - 0.14,
+ label=name,
+ hjust=1, vjust=0.5,
+ size=3.5, color="#00A3A8")
+ }
+
- coord_fixed() +
-
- scale_x_continuous(limits=c(1 - rel(6),
- width + rel(0.5)),
- expand=c(0, 0)) +
-
- scale_y_continuous(limits=c(1 - rel(0.5),
- height + rel(1.5)),
- expand=c(0, 0))
-
- # Saving matrix plot
- if (A3) {
- width = 42
- height = 29.7
- dpi = 300
- print('aaaa')
- } else {
- width = 29.7
- height = 21
- dpi = 100
+ ### Environment ###
+
+ mat = mat +
+
+ coord_fixed() +
+
+ scale_x_continuous(limits=c(1 - rel(6),
+ width + rel(0.5)),
+ expand=c(0, 0)) +
+
+ scale_y_continuous(limits=c(1 - rel(0.5),
+ height + rel(2)),
+ expand=c(0, 0))
+
+ # Saving matrix plot
+ if (A3) {
+ width = 42
+ height = 29.7
+ dpi = 300
+ } else {
+ width = 29.7
+ height = 21
+ dpi = 100
+ }
+
+ ggsave(plot=mat,
+ path=outdirTmp,
+ filename=paste(outnameTmp, '_', fL, imat, '.pdf',
+ sep=''),
+ width=width, height=height, units='cm', dpi=dpi)
+
}
-
- ggsave(plot=mat,
- path=outdirTmp,
- filename=paste(outnameTmp, '.pdf', sep=''),
- width=width, height=height, units='cm', dpi=dpi)
- }
+ }
}
@@ -2096,6 +2323,10 @@ get_color = function (value, min, max, ncolor=256, palette_name='perso', reverse
palette_cold = rev(palette_cold)
}
+ if (is.na(value)) {
+ return (NA)
+ }
+
if (value < 0) {
idNorm = (value - min) / (0 - min)
id = round(idNorm*(ncolor - 1) + 1, 0)
diff --git a/script.R b/script.R
index 9d4acc3..323c222 100644
--- a/script.R
+++ b/script.R
@@ -22,7 +22,7 @@ filedir =
### MANUAL SELECTION ###
# Name of the file that will be analysed from the AG directory
filename =
- # ""
+ ""
# c(
# "S2235610_HYDRO_QJM.txt",
@@ -32,9 +32,9 @@ filename =
# "Q7002910_HYDRO_QJM.txt"
# )
- c("S4214010_HYDRO_QJM.txt",
- "O0384010_HYDRO_QJM.txt",
- "Q7002910_HYDRO_QJM.txt")
+ # c("S4214010_HYDRO_QJM.txt",
+ # "O0384010_HYDRO_QJM.txt",
+ # "Q7002910_HYDRO_QJM.txt")
@@ -44,8 +44,8 @@ AGlistdir =
""
AGlistname =
- ""
- # "Liste-station_RRSE.docx"
+ # ""
+ "Liste-station_RRSE.docx"
### NIVALE SELECTION ###
--
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