From 97807bf72c497d7091ebc0a19d119df0ff032ddc Mon Sep 17 00:00:00 2001
From: "louis.heraut" <louis.heraut@inrae.fr>
Date: Wed, 1 Dec 2021 20:00:52 +0100
Subject: [PATCH] Aes matrix
---
plotting/layout.R | 4 +-
plotting/panel.R | 248 +++++++++++++++++++++++++++++-----------------
script.R | 18 ++--
3 files changed, 170 insertions(+), 100 deletions(-)
diff --git a/plotting/layout.R b/plotting/layout.R
index ea1f60e..d8f671e 100644
--- a/plotting/layout.R
+++ b/plotting/layout.R
@@ -204,7 +204,9 @@ panels_layout = function (df_data, df_meta, layout_matrix, figdir='', filedir_op
}
- mat = matrice_panel(list_df2plot, df_meta)
+ ### by 16
+
+ mat = matrice_panel(list_df2plot, df_meta, period)
# Saving matrix plot
ggsave(plot=mat,
diff --git a/plotting/panel.R b/plotting/panel.R
index bda9bdb..33e063e 100644
--- a/plotting/panel.R
+++ b/plotting/panel.R
@@ -343,24 +343,10 @@ text_panel = function(code, df_meta) {
-matrice_panel = function (list_df2plot, df_meta) {
+matrice_panel = function (list_df2plot, df_meta, period) {
nbp = length(list_df2plot)
- minTrend = c()
- maxTrend = c()
-
- for (i in 1:nbp) {
-
- df_trend = list_df2plot[[i]]$trend
- p_threshold = list_df2plot[[i]]$p_threshold
-
- okTrend = df_trend$trend[df_trend$p <= p_threshold]
-
- minTrend[i] = min(okTrend, na.rm=TRUE)
- maxTrend[i] = max(okTrend, na.rm=TRUE)
- }
-
# Get all different stations code
Code = levels(factor(df_meta$code))
nCode = length(Code)
@@ -387,7 +373,7 @@ matrice_panel = function (list_df2plot, df_meta) {
nPeriod = max(length(UStart), length(UEnd))
- Periods = c()#vector(mode='list', length=nPeriod)
+ Periods = c()
for (i in 1:nPeriod) {
Periods = append(Periods,
@@ -404,14 +390,60 @@ matrice_panel = function (list_df2plot, df_meta) {
}
}
- # print(Code_code)
- # print(Periods_code)
+
+ TrendMean_code = array(rep(1, nPeriod_max*nbp*nCode),
+ dim=c(nPeriod_max, nbp, nCode))
+
+ for (j in 1:nPeriod_max) {
+
+ for (k in 1:nCode) {
+
+ code = Code[k]
+
+ for (i in 1:nbp) {
+
+ df_data = list_df2plot[[i]]$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()
- Trend_mat = c()
+ Pthresold_mat = c()
+ TrendMean_mat = c()
+ DataMean_mat = c()
Fill_mat = c()
Color_mat = c()
@@ -420,50 +452,56 @@ matrice_panel = function (list_df2plot, df_meta) {
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
- # print(code)
-
+ df_data_code = df_data[df_data$code == code,]
df_trend_code = df_trend[df_trend$code == code,]
- # print(df_trend_code)
- # print(Code_code == code )
- # print(Start_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]
- # print(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
+
if (df_trend_code_per$p <= p_threshold){
- color_res = get_color(df_trend_code_per$trend,
- minTrend[i],
- maxTrend[i],
+ color_res = get_color(trendMean,
+ minTrendMean[j, i],
+ minTrendMean[j, i],
palette_name='perso',
reverse=FALSE)
fill = color_res$color
color = 'white'
+ Pthresold = p_thresold
} else {
fill = 'white'
color = 'grey85'
+ Pthresold = NA
}
- # print(fill)
-
- trend = df_trend_code_per$trend
-
Periods_mat = append(Periods_mat, Periods)
NPeriod_mat = append(NPeriod_mat, j)
Type_mat = append(Type_mat, type)
Code_mat = append(Code_mat, code)
- Trend_mat = append(Trend_mat, trend)
+ 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)
}
@@ -473,9 +511,6 @@ matrice_panel = function (list_df2plot, df_meta) {
height = length(Code)
width = nbp * 2 * nPeriod_max
- # print(height)
- # print(width)
-
options(repr.plot.width=width, repr.plot.height=height)
mat = ggplot() +
@@ -488,11 +523,11 @@ matrice_panel = function (list_df2plot, df_meta) {
panel.grid.major.y=element_blank(),
panel.grid.major.x=element_blank(),
- # axis.text.x=element_blank(),
- # axis.text.y=element_blank(),
+ axis.text.x=element_blank(),
+ axis.text.y=element_blank(),
- # axis.ticks.y=element_blank(),
- # axis.ticks.x=element_blank(),
+ axis.ticks.y=element_blank(),
+ axis.ticks.x=element_blank(),
ggh4x.axis.ticks.length.minor=rel(0.5),
axis.ticks.length=unit(1.5, 'mm'),
@@ -509,93 +544,120 @@ matrice_panel = function (list_df2plot, df_meta) {
plot.margin=margin(5, 5, 5, 5, unit="mm"),
)
- X = c(0)
+ # 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) {
- print(j)
Type_mat_per = Type_mat[NPeriod_mat == j]
Code_mat_per = Code_mat[NPeriod_mat == j]
- Trend_mat_per = Trend_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)))
- X = Xtmp + X[length(X)]
- # print(X)
+ Xm = Xtmp + (j - 1)*nbp*2
+ X = Xtmp + (j - 1)*nbp*2 + nbp
Y = as.integer(factor(Code_mat_per))
- # print(Y)
+ x = Xm[1] - 0.25
+ 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)
+ xt = X[1] - 0.5
+ yt = y + 0.15
+ Start = period[[j]][1]
+ End = period[[j]][2]
+ periodName = bquote(bold(.(Start))~'/'~bold(.(End)))
+
+ mat = mat +
+ annotate("text", x=xt, y=yt,
+ label=periodName,
+ hjust=0.5, 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])
- }
+ fill=Fill_mat_per[i], color=Color_mat_per[i]) +
- for (i in 1:nbp) {
- type = list_df2plot[[i]]$type
- mat = mat +
- annotate('text', x=i, y=max(Y) + 0.6,
- label=bquote(.(type)),
- hjust=0.5, vjust=0,
- size=3.5, color='grey40')
+ gg_circle(r=0.45, xc=Xm[i], yc=Y[i],
+ fill='white', color='grey40')
}
-
- for (i in 1:length(Trend_mat_per)) {
- trend = Trend_mat_per[i]
- if (!is.na(trend)) {
- power = get_power(trend)
- dbrk = 10^power
- trendN = round(trend / dbrk, 2)
- trendC1 = as.character(trendN)
- trendC2 = bquote('x '*10^{.(as.character(power))})
+
+ for (i in 1:length(TrendMean_mat_per)) {
+ trendMean = TrendMean_mat_per[i]
+ trendC = round(trendMean*100, 2)
+
+ if (!is.na(Pthresold_mat_per[i])) {
+ Tcolor = 'white'
} else {
- trendC1 = ''
- trendC2 = ''
+ Tcolor = 'grey85'
}
+
+ dataMean = round(DataMean_mat_per[i], 2)
mat = mat +
annotate('text', x=X[i], y=Y[i],
- label=trendC1,
+ label=trendC,
+ hjust=0.5, vjust=0.5,
+ size=3, color=Tcolor) +
+
+ annotate('text', x=Xm[i], y=Y[i],
+ label=dataMean,
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40')
+ }
+
+ for (i in 1:nbp) {
+ type = list_df2plot[[i]]$type
+ mat = mat +
+ annotate('text', x=X[i], y=max(Y) + 0.6,
+ label=bquote(.(type)),
hjust=0.5, vjust=0,
- size=3, color='white') +
- annotate('text', x=X[i], y=Y[i],
- label=trendC2,
- hjust=0.5, vjust=1.3,
- size=2, color='white')
-
+ size=3.5, color='grey20') +
+
+ annotate('text', x=Xm[i], y=max(Y) + 0.6,
+ label=bquote(.(type)*'b'),
+ hjust=0.5, vjust=0,
+ size=3.5, color='grey20')
}
}
for (i in 1:length(Code)) {
code = Code[i]
- name = df_meta[df_meta$code == code,]$name
- print(name)
+ name = df_meta[df_meta$code == code,]$nom
mat = mat +
annotate('text', x=-1, y=i,
- label=code,
- hjust=0, vjust=0,
- size=3.5, color='grey40') +
+ label=bquote(bold(.(code))),
+ hjust=0, vjust=-0.1,
+ size=3.5, color="#00A3A8") +
annotate('text', x=-1, y=i,
- label=name,
- hjust=0, vjust=1,
- size=3.5, color='grey40')
+ label=paste(substr(name, 1, 15), '...', sep=''),
+ hjust=0, vjust=1.1,
+ size=2.5, color="#00A3A8")
}
-
- # print(Y)
-
-
- mat = mat +
- annotate("segment",
- x = width/2 + 0.5, xend = width/2 + 0.5,
- y = 1 - 0.5, yend = height + 0.5,
- color="grey85")
mat = mat +
@@ -606,7 +668,7 @@ matrice_panel = function (list_df2plot, df_meta) {
expand=c(0, 0)) +
scale_y_continuous(limits=c(1 - rel(0.5),
- height + rel(1)),
+ height + rel(2)),
expand=c(0, 0))
return (mat)
diff --git a/script.R b/script.R
index 1101421..5702abf 100644
--- a/script.R
+++ b/script.R
@@ -23,7 +23,7 @@ filedir =
### MANUAL SELECTION ###
# Name of the file that will be analysed from the AG directory
filename =
- # ""
+ ""
# c(
# "S2235610_HYDRO_QJM.txt",
@@ -33,9 +33,9 @@ filename =
# "A2250310_HYDRO_QJM.txt"
# )
- c("O3035210_HYDRO_QJM.txt",
- "O3011010_HYDRO_QJM.txt",
- "O1442910_HYDRO_QJM.txt")
+ # c("O3035210_HYDRO_QJM.txt",
+ # "O3011010_HYDRO_QJM.txt",
+ # "O1442910_HYDRO_QJM.txt")
@@ -45,8 +45,8 @@ AGlistdir =
""
AGlistname =
- ""
- # "Liste-station_RRSE.docx"
+ # ""
+ "Liste-station_RRSE.docx"
### NIVALE SELECTION ###
@@ -126,6 +126,12 @@ if (AGlistname != ""){
filename = df_selec_AG[df_selec_AG$ok,]$filename
+
+ #####
+ filename = filename[1:16]
+ #####
+
+
# Extract metadata about selected stations
df_meta_AG = extract_meta(computer_data_path, filedir, filename)
--
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