From bc0d22b57689dd41750b5eb91c0c2d50b426fe97 Mon Sep 17 00:00:00 2001
From: "louis.heraut" <louis.heraut@inrae.fr>
Date: Fri, 10 Dec 2021 16:17:57 +0100
Subject: [PATCH] Map
---
plotting/layout.R | 71 +++--
plotting/panel.R | 773 ++++++++++++++++++++++++++++------------------
script.R | 61 ++--
3 files changed, 549 insertions(+), 356 deletions(-)
diff --git a/plotting/layout.R b/plotting/layout.R
index fa5aedb..7f10a41 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, time_ratio=2, var_ratio=3, shpdir=NULL, fr_shpname=NULL, rv_shpname=NULL, computer_data_path=NULL) {
+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, 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 != '') {
@@ -343,49 +343,56 @@ panels_layout = function (df_data, df_meta, layout_matrix, figdir='', filedir_op
}
- # By
- slice = 12
- nMat = as.integer(nCode/slice) + 1
- sublist_df2plot = list_df2plot
+ # # By
+ # slice = 12
+ # nMat = as.integer(nCode/slice) + 1
+ # sublist_df2plot = list_df2plot
- for (i in 1:nMat) {
+ # for (i in 1:nMat) {
- subdf_meta = df_meta[(slice*(i-1)+1):(slice*i),]
- subdf_meta = subdf_meta[!is.na(subdf_meta$code),]
- subCode = subdf_meta$code
+ # 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
+ # for (j in 1:nbp) {
+ # df_datatmp = list_df2plot[[j]]$data
+ # df_trendtmp = list_df2plot[[j]]$trend
- subdf_data = df_datatmp[(df_datatmp$code %in% subCode),]
- subdf_trend = df_trendtmp[(df_trendtmp$code %in% subCode),]
+ # 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
- }
+ # sublist_df2plot[[j]]$data = subdf_data
+ # sublist_df2plot[[j]]$trend = subdf_trend
+ # }
- mat = matrice_panel(sublist_df2plot,
- subdf_meta,
- trend_period=trend_period)
+ # mat = matrice_panel(sublist_df2plot,
+ # subdf_meta,
+ # trend_period=trend_period)
# Saving matrix plot
- ggsave(plot=mat,
- path=outdirTmp,
- filename=paste('matrix_', i, '.pdf', sep=''),
- width=29.7, height=21, units='cm', dpi=100)
+ # ggsave(plot=mat,
+ # path=outdirTmp,
+ # filename=paste('matrix_', i, '.pdf', sep=''),
+ # width=29.7, height=21, units='cm', dpi=100)
- }
-
-
- map = map_panel(computer_data_path=computer_data_path,
- shpdir=shpdir,
- fr_shpname=fr_shpname,
- rv_shpname=rv_shpname)
-
+ # }
+ matrice_panel(list_df2plot, df_meta, trend_period,
+ slice=12, outdirTmp=outdirTmp)
+
+ map_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,
+ outdirTmp=outdirTmp)
+
# PDF combine
pdf_combine(input=file.path(outdirTmp, list.files(outdirTmp)),
output=file.path(outdir, outfile))
diff --git a/plotting/panel.R b/plotting/panel.R
index fab6e0c..bffa737 100644
--- a/plotting/panel.R
+++ b/plotting/panel.R
@@ -658,21 +658,459 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
}
-matrice_panel = function (list_df2plot, df_meta, trend_period) {
-
+matrice_panel = function (list_df2plot, df_meta, trend_period, slice=NULL, outdirTmp='', outnameTmp='matrix') {
+
nbp = length(list_df2plot)
+
+ # Get all different stations code
+ Code = levels(factor(df_meta$code))
+ nCode = length(Code)
+
+ if (!is.null(slice)) {
+
+ # By
+ nMat = as.integer(nCode/slice) + 1
+ sublist_df2plot = list_df2plot
+
+ for (i in 1:nMat) {
+
+ subdf_meta = df_meta[(slice*(i-1)+1):(slice*i),]
+ subdf_meta = subdf_meta[!is.na(subdf_meta$code),]
+ subCode = subdf_meta$code
+
+
+ for (j in 1:nbp) {
+ df_datatmp = list_df2plot[[j]]$data
+ df_trendtmp = list_df2plot[[j]]$trend
+
+ subdf_data = df_datatmp[(df_datatmp$code %in% subCode),]
+ subdf_trend = df_trendtmp[(df_trendtmp$code %in% subCode),]
+
+ sublist_df2plot[[j]]$data = subdf_data
+ sublist_df2plot[[j]]$trend = subdf_trend
+ }
+
+ mat = matrice_panel(sublist_df2plot,
+ subdf_meta,
+ trend_period=trend_period,
+ outdirTmp=outdirTmp,
+ outnameTmp=paste(outnameTmp,
+ '_', i,
+ sep=''))
+ }
+
+ } else {
+
+ print(paste('matrix :', outnameTmp))
+ # nbp = length(list_df2plot)
+
+ # # Get all different stations code
+ # Code = levels(factor(df_meta$code))
+ # nCode = length(Code)
+
+ df_trend = list_df2plot[[1]]$trend
+
+ nPeriod_max = 0
+ for (code in Code) {
+
+ df_trend_code = df_trend[df_trend$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))
+
+ 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)
+
+ for (j in 1:nCode) {
+
+ code = Code[j]
+
+ df_trend_code = df_trend[df_trend$code == code,]
+
+ Start = df_trend_code$period_start
+ UStart = levels(factor(Start))
+
+ End = df_trend_code$period_end
+ UEnd = levels(factor(End))
+
+ nPeriod = max(length(UStart), length(UEnd))
+ Periods = c()
+
+ for (i in 1:nPeriod_max) {
+ Periods = append(Periods,
+ paste(substr(Start[i], 1, 4),
+ substr(End[i], 1, 4),
+ sep=' / '))
+ }
+
+ Start_code[[j]] = Start
+ End_code[[j]] = End
+ Code_code[[j]] = code
+ Periods_code[[j]] = Periods
+
+ }
+
+ TrendMean_code = array(rep(1, nPeriod_max*nbp*nCode),
+ dim=c(nPeriod_max, nbp, nCode))
+
+ for (j in 1:nPeriod_max) {
+
+ for (k in 1:nCode) {
+
+ code = Code[k]
+
+ for (i in 1:nbp) {
+
+ df_data = list_df2plot[[i]]$data
+ df_trend = list_df2plot[[i]]$trend
+ p_threshold = list_df2plot[[i]]$p_threshold
+
+ 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,]
+
+ 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
+ }
+ }
+ }
+
+ minTrendMean = apply(TrendMean_code, c(1, 2), min, na.rm=TRUE)
+ maxTrendMean = apply(TrendMean_code, c(1, 2), max, na.rm=TRUE)
+
+ Periods_mat = c()
+ NPeriod_mat = c()
+ Type_mat = list()
+ Code_mat = c()
+ Pthresold_mat = c()
+ TrendMean_mat = c()
+ DataMean_mat = c()
+ Fill_mat = c()
+ Color_mat = c()
+
+ for (j in 1:nPeriod_max) {
+
+ 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
+
+ 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,]
+
+ 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
+
+ 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
+ color = 'white'
+ Pthresold = p_thresold
+ } else {
+ fill = 'white'
+ color = 'grey85'
+ Pthresold = NA
+ }
+
+ Periods_mat = append(Periods_mat, Periods)
+ NPeriod_mat = append(NPeriod_mat, j)
+ Type_mat = append(Type_mat, type)
+ Code_mat = append(Code_mat, code)
+ Pthresold_mat = append(Pthresold_mat, Pthresold)
+ TrendMean_mat = append(TrendMean_mat, trendMean)
+ DataMean_mat = append(DataMean_mat, dataMean)
+ Fill_mat = append(Fill_mat, fill)
+ Color_mat = append(Color_mat, color)
+ }
+ }
+ }
+
+ height = length(Code)
+ width = nbp * 2 * nPeriod_max + nPeriod_max
+
+ 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")
+
+ for (j in 1:nPeriod_max) {
+
+ Type_mat_per = Type_mat[NPeriod_mat == j]
+ Code_mat_per = Code_mat[NPeriod_mat == j]
+ Pthresold_mat_per = Pthresold_mat[NPeriod_mat == j]
+ TrendMean_mat_per = TrendMean_mat[NPeriod_mat == j]
+ DataMean_mat_per = DataMean_mat[NPeriod_mat == j]
+ Fill_mat_per = Fill_mat[NPeriod_mat == j]
+ Color_mat_per = Color_mat[NPeriod_mat == j]
+
+ Xtmp = as.integer(factor(as.character(Type_mat_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_mat_per))
+
+ x = Xc - 0.4
+ xend = X[length(X)] + 0.25
+ y = height + 1
+ yend = height + 1
+
+ mat = mat +
+ 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)))
+
+ 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_mat_per[i], color=Color_mat_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_mat_per)) {
+ trendMean = TrendMean_mat_per[i]
+ trendC = round(trendMean*100, 2)
+
+ if (!is.na(Pthresold_mat_per[i])) {
+ Tcolor = 'white'
+ } else {
+ Tcolor = 'grey85'
+ }
+
+ dataMean = round(DataMean_mat_per[i], 2)
+
+ 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=Xc, y=max(Y) + 0.85,
+ label=bquote(bold('Début')),
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey20') +
+
+ annotate('text', x=Xc, y=max(Y) + 0.6,
+ label=bquote(bold('Fin')),
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey20')
+
+ for (i in 1:nbp) {
+ type = list_df2plot[[i]]$type
+ mat = mat +
+ annotate('text', x=X[i], y=max(Y) + 0.7,
+ label=bquote(.(type)),
+ hjust=0.5, vjust=0.5,
+ size=3.5, color='grey20') +
+
+ annotate('text', x=Xm[i], y=max(Y) + 0.7,
+ label=bquote('µ'*.(type)),
+ hjust=0.5, vjust=0.5,
+ size=3.5, color='grey20')
+ }
+ }
+
+ for (i in 1:length(Code)) {
+
+ code = Code[i]
+ name = df_meta[df_meta$code == code,]$nom
+ ncharMax = 30
+ if (nchar(name) > ncharMax) {
+ name = paste(substr(name, 1, ncharMax), '...', sep='')
+ }
+
+ 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") +
+
+ annotate('text', x=0.3, y=i - 0.14,
+ label=name,
+ hjust=1, vjust=0.5,
+ size=3.5, color="#00A3A8")
+
+
+ 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)
+
+ mat = mat +
+ annotate('text', x=Xc, y=i + 0.13,
+ label=bquote(bold(.(periodStart))),
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40') +
+
+ annotate('text', x=Xc, y=i - 0.13,
+ label=bquote(bold(.(periodEnd))),
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40')
+ }
+ }
+
+ 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(1.5)),
+ expand=c(0, 0))
+
+ # Saving matrix plot
+ ggsave(plot=mat,
+ path=outdirTmp,
+ filename=paste(outnameTmp, '.pdf', sep=''),
+ width=29.7, height=21, units='cm', dpi=100)
+ }
+}
+
+
+
+map_panel = function (list_df2plot, df_meta, computer_data_path, fr_shpdir, fr_shpname, bs_shpdir=bs_shpdir, bs_shpname=bs_shpname, rv_shpdir, rv_shpname, outdirTmp) {
+
+ fr_shppath = file.path(computer_data_path, fr_shpdir, fr_shpname)
+ rv_shppath = file.path(computer_data_path, rv_shpdir, rv_shpname)
+ bs_shppath = file.path(computer_data_path, bs_shpdir, bs_shpname)
+
+ # France
+ fr_spdf = readOGR(dsn=fr_shppath, verbose=FALSE)
+ proj4string(fr_spdf) = CRS("+proj=longlat +ellps=WGS84")
+ # Trasnformation en Lambert93
+ france = spTransform(fr_spdf, CRS("+init=epsg:2154"))
+ df_france = tibble(fortify(france))
+
+ # Bassin hydrographique
+ bassin = readOGR(dsn=bs_shppath, verbose=FALSE)
+ df_bassin = tibble(fortify(bassin))
+
+ # Réseau hydrographique
+ # river = readOGR(dsn=rv_shppath, verbose=FALSE) ### trop long ###
+ # river = river[which(river$Classe == 1),]
+ # df_river = tibble(fortify(river))
+
+ nbp = length(list_df2plot)
+
# Get all different stations code
Code = levels(factor(df_meta$code))
nCode = length(Code)
- df_trend = list_df2plot[[1]]$trend
+
+
+ df_trend = list_df2plot[[1]]$trend
+
nPeriod_max = 0
for (code in Code) {
df_trend_code = df_trend[df_trend$code == code,]
-
+
Start = df_trend_code$period_start
UStart = levels(factor(Start))
@@ -680,7 +1118,7 @@ matrice_panel = function (list_df2plot, df_meta, trend_period) {
UEnd = levels(factor(End))
nPeriod = max(length(UStart), length(UEnd))
-
+
if (nPeriod > nPeriod_max) {
nPeriod_max = nPeriod
}
@@ -722,7 +1160,7 @@ matrice_panel = function (list_df2plot, df_meta, trend_period) {
}
TrendMean_code = array(rep(1, nPeriod_max*nbp*nCode),
- dim=c(nPeriod_max, nbp, nCode))
+ dim=c(nPeriod_max, nbp, nCode))
for (j in 1:nPeriod_max) {
@@ -765,309 +1203,46 @@ matrice_panel = function (list_df2plot, df_meta, trend_period) {
}
minTrendMean = apply(TrendMean_code, c(1, 2), min, na.rm=TRUE)
- maxTrendMean = apply(TrendMean_code, c(1, 2), max, na.rm=TRUE)
-
- Periods_mat = c()
- NPeriod_mat = c()
- Type_mat = list()
- Code_mat = c()
- Pthresold_mat = c()
- TrendMean_mat = c()
- DataMean_mat = c()
- Fill_mat = c()
- Color_mat = c()
-
- for (j in 1:nPeriod_max) {
+ maxTrendMean = apply(TrendMean_code, c(1, 2), max, na.rm=TRUE)
- for (code in Code) {
-
- for (i in 1:nbp) {
- df_data = list_df2plot[[i]]$data
- df_trend = list_df2plot[[i]]$trend
- p_threshold = list_df2plot[[i]]$p_threshold
- type = list_df2plot[[i]]$type
-
- df_data_code = df_data[df_data$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$Date <= End,]
-
- df_trend_code_per =
- df_trend_code[df_trend_code$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$trend / dataMean
-
- if (df_trend_code_per$p <= p_threshold){
- color_res = get_color(trendMean,
- minTrendMean[j, i],
- maxTrendMean[j, i],
- palette_name='perso',
- reverse=TRUE)
-
- fill = color_res$color
- color = 'white'
- Pthresold = p_thresold
- } else {
- fill = 'white'
- color = 'grey85'
- Pthresold = NA
- }
-
- Periods_mat = append(Periods_mat, Periods)
- NPeriod_mat = append(NPeriod_mat, j)
- Type_mat = append(Type_mat, type)
- Code_mat = append(Code_mat, code)
- Pthresold_mat = append(Pthresold_mat, Pthresold)
- TrendMean_mat = append(TrendMean_mat, trendMean)
- DataMean_mat = append(DataMean_mat, dataMean)
- Fill_mat = append(Fill_mat, fill)
- Color_mat = append(Color_mat, color)
- }
- }
- }
-
- height = length(Code)
- width = nbp * 2 * nPeriod_max + nPeriod_max
-
- 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")
-
- for (j in 1:nPeriod_max) {
-
- Type_mat_per = Type_mat[NPeriod_mat == j]
- Code_mat_per = Code_mat[NPeriod_mat == j]
- Pthresold_mat_per = Pthresold_mat[NPeriod_mat == j]
- TrendMean_mat_per = TrendMean_mat[NPeriod_mat == j]
- DataMean_mat_per = DataMean_mat[NPeriod_mat == j]
- Fill_mat_per = Fill_mat[NPeriod_mat == j]
- Color_mat_per = Color_mat[NPeriod_mat == j]
-
- Xtmp = as.integer(factor(as.character(Type_mat_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_mat_per))
-
- x = Xc - 0.4
- xend = X[length(X)] + 0.25
- y = height + 1
- yend = height + 1
-
- mat = mat +
- annotate("segment",
- x=x, xend=xend,
- y=y, yend=yend,
- color="grey40", size=0.35)
+ for (j in 1:nbp) {
- 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')
+ map = ggplot() + theme_void() +
- for (i in 1:length(X)) {
- mat = mat +
-
- gg_circle(r=0.45, xc=X[i], yc=Y[i],
- fill=Fill_mat_per[i], color=Color_mat_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_mat_per)) {
- trendMean = TrendMean_mat_per[i]
- trendC = round(trendMean*100, 2)
-
- if (!is.na(Pthresold_mat_per[i])) {
- Tcolor = 'white'
- } else {
- Tcolor = 'grey85'
- }
+ coord_fixed() +
- dataMean = round(DataMean_mat_per[i], 2)
-
- 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=Xc, y=max(Y) + 0.85,
- label=bquote(bold('Début')),
- hjust=0.5, vjust=0.5,
- size=3, color='grey20') +
-
- annotate('text', x=Xc, y=max(Y) + 0.6,
- label=bquote(bold('Fin')),
- hjust=0.5, vjust=0.5,
- 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 (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='')
- }
-
- 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") +
+ geom_polygon(data=df_france,
+ aes(x=long, y=lat, group=group),
+ color=NA, fill="grey97") +
- annotate('text', x=0.3, y=i - 0.14,
- label=name,
- hjust=1, vjust=0.5,
- size=3.5, color="#00A3A8")
-
-
- 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)
-
- mat = mat +
- annotate('text', x=Xc, y=i + 0.13,
- label=bquote(bold(.(periodStart))),
- hjust=0.5, vjust=0.5,
- size=3, color='grey40') +
-
- annotate('text', x=Xc, y=i - 0.13,
- label=bquote(bold(.(periodEnd))),
- hjust=0.5, vjust=0.5,
- size=3, color='grey40')
- }
-
- }
-
- mat = mat +
-
- coord_fixed() +
-
- scale_x_continuous(limits=c(1 - rel(6),
- width + rel(0.5)),
- expand=c(0, 0)) +
+ # geom_path(data=df_river,
+ # aes(x=long, y=lat, group=group),
+ # color="grey85", size=0.15) +
+
+ geom_polygon(data=df_bassin,
+ aes(x=long, y=lat, group=group),
+ color="grey70", fill=NA, size=0.1) +
+
+ geom_polygon(data=df_france,
+ aes(x=long, y=lat, group=group),
+ color="grey40", fill=NA, size=0.2)
+
+ # marker color="grey50"
+
+ # for (code in Code) {
+
+ # }
- scale_y_continuous(limits=c(1 - rel(0.5),
- height + rel(1.5)),
- expand=c(0, 0))
-
- return (mat)
-}
-
-
-map_panel = function (computer_data_path, shpdir, fr_shpname, rv_shpname) {
-
- fr_shppath = file.path(computer_data_path, shpdir, fr_shpname)
- rv_shppath = file.path(computer_data_path, shpdir, rv_shpname)
-
- # France
- fr_spdf = readOGR(dsn=fr_shppath, verbose=FALSE)
- proj4string(fr_spdf) = CRS("+proj=longlat +ellps=WGS84")
- # Trasnformation en Lambert93
- france = spTransform(fr_spdf, CRS("+init=epsg:2154"))
- df_france = tibble(fortify(france))
- # Réseau hydrographique
- print('aaa')
- river = readOGR(dsn=rv_shppath, verbose=FALSE)
- print('bbb')
- river = river[which(river$Classe == 1),]
- print('ccc')
- df_river = tibble(fortify(river))
-
- print(df_river)
-
- # map = ggplot() + theme_void() +
- # geom_polygon(data=df_france,
- # aes(x=long, y=lat, group=group),
- # color="grey40", fill="grey97", size=0.15) +
-
- # geom_line(data=df_river,
- # aes(x=long, y=lat, group=group),
- # color="grey70", size=0.25)
-
-
- # marker color="grey50"
-
- # Saving matrix plot
- ggsave(plot=map,
- filename='map.pdf',
- width=10, height=10, units='cm', dpi=100)
-
- return (map)
+ # Saving matrix plot
+ ggsave(plot=map,
+ path=outdirTmp,
+ filename='map.pdf',
+ width=29.7, height=21, units='cm', dpi=100)
+ }
}
diff --git a/script.R b/script.R
index a6c89c2..3229703 100644
--- a/script.R
+++ b/script.R
@@ -74,8 +74,13 @@ p_thresold = 0.1 #c(0.01, 0.05, 0.1)
### MAP ###
-shpdir = 'map'
+fr_shpdir = 'map/france'
fr_shpname = 'gadm36_FRA_0.shp'
+
+bs_shpdir = 'map/bassin'
+bs_shpname = 'BassinHydrographique.shp'
+
+rv_shpdir = 'map/river'
rv_shpname = 'CoursEau_FXX.shp'
@@ -229,30 +234,36 @@ res_VCN10trend = get_VCN10trend(df_data, df_meta,
# figdir=figdir,
# filename_opt='time')
-# panels_layout(list(res_QAtrend$data, res_QMNAtrend$data,
-# res_VCN10trend$data),
-# layout_matrix=c(1, 2, 3),
-# df_meta=df_meta,
-# df_trend=list(res_QAtrend$trend, res_QMNAtrend$trend,
-# res_VCN10trend$trend),
-# type=list(bquote(Q[A]), bquote(Q[MNA]), bquote(V[CN10])),
-# missRect=list(TRUE, TRUE, TRUE),
-# trend_period=trend_period,
-# mean_period=mean_period,
-# info_header=TRUE,
-# time_header=df_data,
-# time_ratio=2,
-# var_ratio=3,
-# computer_data_path=computer_data_path,
-# shpdir=shpdir,
-# fr_shpname=fr_shpname,
-# rv_shpname=rv_shpname,
-# figdir=figdir,
-# filename_opt='')
-
-
-
-map_panel(computer_data_path, shpdir, fr_shpname, rv_shpname)
+panels_layout(list(res_QAtrend$data, res_QMNAtrend$data,
+ res_VCN10trend$data),
+ layout_matrix=c(1, 2, 3),
+ df_meta=df_meta,
+ df_trend=list(res_QAtrend$trend, res_QMNAtrend$trend,
+ res_VCN10trend$trend),
+ type=list(bquote(Q[A]), bquote(Q[MNA]), bquote(V[CN10])),
+ missRect=list(TRUE, TRUE, TRUE),
+ trend_period=trend_period,
+ mean_period=mean_period,
+ info_header=TRUE,
+ time_header=df_data,
+ time_ratio=2,
+ var_ratio=3,
+ 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,
+ figdir=figdir,
+ filename_opt='')
+
+
+
+# map_panel(computer_data_path,
+ # fr_shpdir, fr_shpname,
+ # bs_shpdir, bs_shpname,
+ # rv_shpdir, rv_shpname)
### /!\ Removed 185 row(s) containing missing values (geom_path) -> remove NA ###
--
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