diff --git a/plotting/layout.R b/plotting/layout.R
index b3631f909af26391f275f52d4d89cd0c2da89175..487421e8c31d412a960e4efe56794510199cb956 100644
--- a/plotting/layout.R
+++ b/plotting/layout.R
@@ -116,7 +116,7 @@ panels_layout = function (df_data, df_meta, layout_matrix, figdir='', filedir_op
Htime = time_panel(time_header_code, df_trend_code=NULL,
period=period, missRect=TRUE,
- unit2day=365.25, type='Q')
+ unit2day=365.25, type='Q', first=FALSE)
P[[2]] = Htime
}
@@ -134,21 +134,22 @@ panels_layout = function (df_data, df_meta, layout_matrix, figdir='', filedir_op
df_data_code = df_data[df_data$code == code,]
df_trend_code = df_trend[df_trend$code == code,]
- if (df_trend_code$p <= p_threshold){
- color_res = get_color(df_trend_code$trend,
- minTrend[i],
- maxTrend[i],
- palette_name='perso',
- reverse=FALSE)
-
- color = color_res$color
- palette = color_res$palette
-
- } else {
- color = NULL
- palette = NULL
+ color = c()
+ for (j in 1:nrow(df_trend_code)) {
+ 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=FALSE)
+ colortmp = color_res$color
+ } else {
+ colortmp = NA
+ }
+
+ color = append(color, colortmp)
}
-
+
p = time_panel(df_data_code, df_trend_code, type=type,
p_threshold=p_threshold, missRect=missRect,
unit2day=unit2day, last=(i > nbp-nbcol),
diff --git a/plotting/panel.R b/plotting/panel.R
index d3ae1d1695c6fbad2c604d5247541ed0ecdd6a84..b939c2bb6b7f1e96187b4893c44aead704784fce 100644
--- a/plotting/panel.R
+++ b/plotting/panel.R
@@ -10,7 +10,7 @@ library(ggh4x)
library(RColorBrewer)
-time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missRect=FALSE, unit2day=365.25, period=NULL, last=FALSE, color=NULL) {
+time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missRect=FALSE, unit2day=365.25, period=NULL, last=FALSE, first=FALSE, color=NULL) {
if (type == 'sqrt(Q)') {
df_data_code$Qm3s = sqrt(df_data_code$Qm3s)
@@ -85,11 +85,22 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
)
if (last) {
- p = p +
- theme(plot.margin=margin(1, 5, 5, 5, unit="mm"))
+ if (first) {
+ p = p +
+ theme(plot.margin=margin(5, 5, 5, 5, unit="mm"))
+ } else {
+ p = p +
+ theme(plot.margin=margin(0, 5, 5, 5, unit="mm"))
+ }
+
} else {
- p = p +
- theme(plot.margin=margin(1, 5, 1, 5, unit="mm"))
+ if (first) {
+ p = p +
+ theme(plot.margin=margin(5, 5, 0, 5, unit="mm"))
+ } else {
+ p = p +
+ theme(plot.margin=margin(0, 5, 0, 5, unit="mm"))
+ }
}
@@ -119,21 +130,31 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
}
if ((type == 'sqrt(Q)' | type == 'Q') & !is.null(period)) {
- period = as.Date(period)
- p = p +
- geom_rect(aes(xmin=min(df_data_code$Date),
- ymin=0,
- xmax=period[1],
- ymax= maxQ*1.1),
- linetype=0, fill='grey85', alpha=0.3) +
-
- geom_rect(aes(xmin=period[2],
- ymin=0,
- xmax=max(df_data_code$Date),
- ymax= maxQ*1.1),
- linetype=0, fill='grey85', alpha=0.3)
+
+ period = as.list(period)
+ Imin = 10^99
+ for (per in period) {
+ I = interval(per[1], per[2])
+ if (I < Imin) {
+ Imin = I
+ period_min = as.Date(per)
+ }
}
+ p = p +
+ geom_rect(aes(xmin=min(df_data_code$Date),
+ ymin=0,
+ xmax=period_min[1],
+ ymax= maxQ*1.1),
+ linetype=0, fill='grey85', alpha=0.3) +
+
+ geom_rect(aes(xmin=period_min[2],
+ ymin=0,
+ xmax=max(df_data_code$Date),
+ ymax= maxQ*1.1),
+ linetype=0, fill='grey85', alpha=0.3)
+ }
+
if (!is.null(df_trend_code)) {
@@ -152,14 +173,13 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
# }
ltype = c('solid', 'dashed', 'dotted', 'twodash')
+ lty = c('solid', '22')
for (i in 1:nPeriod) {
df_trend_code_per =
df_trend_code[df_trend_code$period_start == Start[i]
& df_trend_code$period_end == End[i],]
- # print(df_trend_code_per)
-
if (df_trend_code_per$p <= p_threshold) {
iStart = which.min(abs(df_data_code$Date - Start[i]))
@@ -167,19 +187,6 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
abs = c(df_data_code$Date[iStart],
df_data_code$Date[iEnd])
-
- # abs = seq(df_data_code$Date[1],
- # df_data_code$Date[length(df_data_code$Date)],
- # length.out=10)
-
- # abs[abs <= df_data_code$Date[iStart]] = NA
- # abs[abs >= df_data_code$Date[iEnd]] = NA
-
-
- # print(abs)
- # print(df_trend_code_per$trend)
- # print(df_trend_code_per$intercept)
-
abs_num = as.numeric(abs) / unit2day
@@ -189,61 +196,54 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
plot = tibble(abs=abs, ord=ord)
- if (!is.null(color)) {
+ if (!is.na(color[i])) {
p = p +
geom_line(data=plot, aes(x=abs, y=ord),
color=color[i],
linetype=ltype[i], size=0.7)
- } else {
+ } else {
p = p +
geom_line(aes(x=abs, y=ord),
color='cornflowerblue')
}
- }
- }
- }
+ codeDate = df_data_code$Date
+ codeQ = df_data_code$Qm3s
+
+ x = gpct(3, codeDate, shift=TRUE)
+ xend = x + gpct(3, codeDate)
+
+ dy = gpct(5, codeQ, ref=0)
+ y = gpct(108, codeQ, ref=0) - (i-1)*dy
+
+ xt = xend + gpct(1, codeDate)
+ label = bquote(bold(.(format(df_trend_code$trend, scientific=TRUE, digits=3)))~'['*m^{3}*'.'*s^{-1}*'.'*an^{-1}*']')
+
+ p = p +
+ annotate("segment",
+ x=x, xend=xend,
+ y=y, yend=y,
+ color=color[i],
+ lty=lty[i], lwd=1) +
+
+ annotate("text",
+ label=label, size=3,
+ x=xt, y=y,
+ hjust=0, vjust=0.4,
+ color=color[i])
+
+
+
+ # bquote(bold('tendance')~.(format(df_trend_code$trend, scientific=TRUE, digits=3))~'['*m^{3}*'.'*s^{-1}*'.'*an^{-1}*']')
-
- # if (norm) {
- # p = p +
- # ggtitle(bquote(bold(.(type))~~'['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))}~~~bold('tendance')~.(format(df_trend_code$trend, scientific=TRUE, digits=3))~'['*m^{3}*'.'*s^{-1}*'.'*an^{-1}*']'))
- # } else {
- # p = p +
- # ggtitle(bquote(bold(.(type))~~'['*m^{3}*'.'*s^{-1}*']'~~~bold('tendance')~.(format(df_trend_code$trend, scientific=TRUE, digits=3))~'['*m^{3}*'.'*s^{-1}*'.'*an^{-1}*']'))
- # }
-
- # } else {
- # if (norm) {
- # p = p +
- # ggtitle(bquote(bold(.(type))~~'['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))}~~~bold('tendance')~.(format(df_trend_code$trend, scientific=TRUE, digits=3))~'['*m^{3}*'.'*s^{-1}*'.'*an^{-1}*']'))
- # } else {
- # p = p +
- # ggtitle(bquote(bold(.(type))~~'['*m^{3}*'.'*s^{-1}*']'~~~bold('tendance')~.(format(df_trend_code$trend, scientific=TRUE, digits=3))~'['*m^{3}*'.'*s^{-1}*'.'*an^{-1}*']'))
- # }
- # }
- # } else {
- # if (norm) {
- # p = p +
- # ggtitle(bquote(bold(.(type))~' ['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))}))
- # } else {
- # p = p +
- # ggtitle(bquote(bold(.(type))~' ['*m^{3}*'.'*s^{-1}*']'))
- # }
- # }
-
+ }
+ }
+ }
- # if (norm) {
- # p = p +
- # ylab(bquote('débit ['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))}))
- # } else {
- # p = p +
- # ylab(expression(paste('débit [', m^{3}, '.',
- # s^{-1}, ']', sep='')))
- # }
+ p = p +
+ ggtitle(bquote(bold(.(type))~~'['*m^{3}*'.'*s^{-1}*']')) +
- p = p +
# xlab('date') +
scale_x_date(date_breaks=paste(as.character(datebreak),
'year', sep=' '),
@@ -269,33 +269,38 @@ text_panel = function(code, df_meta) {
df_meta_code = df_meta[df_meta$code == code,]
text1 = paste(
- "<b>", code, '</b> - ', df_meta_code$nom, "<br>",
+ "<b>", code, '</b> - ', df_meta_code$nom, ' (',
+ df_meta_code$region_hydro, ')',
sep='')
text2 = paste(
"<b>",
- "Région hydro : ", df_meta_code$region_hydro, "<br>",
+ "Gestionnaire : ", df_meta_code$gestionnaire, "<br>",
"</b>",
sep='')
text3 = paste(
"<b>",
- "Superficie : ", df_meta_code$surface_km2, " [km<sup>2</sup>] <br>",
- "X = ", df_meta_code$L93X, " [m ; Lambert 93]",
+ "Superficie : ", df_meta_code$surface_km2_IN,
+ ' (', df_meta_code$surface_km2_BH, ')', " [km<sup>2</sup>] <br>",
+ "X = ", df_meta_code$L93X_m_IN,
+ ' (', df_meta_code$L93X_m_BH, ')', " [m ; Lambert 93]",
"</b>",
sep='')
text4 = paste(
"<b>",
- "Altitude : ", df_meta_code$altitude_m, " [m]<br>",
- "Y = ", df_meta_code$L93Y, " [m ; Lambert 93]",
+ "Altitude : ", df_meta_code$altitude_m_IN,
+ ' (', df_meta_code$altitude_m_BH, ')', " [m]<br>",
+ "Y = ", df_meta_code$L93Y_m_IN,
+ ' (', df_meta_code$L93Y_m_BH, ')', " [m ; Lambert 93]",
"</b>",
sep='')
text5 = paste(
"<b>",
- "(Banque Hydro)<br>",
- "(Banque Hydro)",
+ "INRAE (Banque Hydro)<br>",
+ "INRAE (Banque Hydro)",
"</b>",
sep='')
@@ -306,10 +311,10 @@ text_panel = function(code, df_meta) {
gp=gpar(col="#00A3A8", fontsize=14))
gtext2 = richtext_grob(text2,
- x=0, y=0.6,
+ x=0, y=0.55,
margin=unit(c(t=0, r=5, b=0, l=5), "mm"),
hjust=0, vjust=1,
- gp=gpar(col="grey20", fontsize=9))
+ gp=gpar(col="grey20", fontsize=8))
gtext3 = richtext_grob(text3,
x=0, y=1,
@@ -363,11 +368,6 @@ matrice_panel = function (list_df2plot, df_meta) {
# Get all different stations code
Code = levels(factor(df_meta$code))
- # Type = vector(mode='list', length=nbp)
- # for (i in 1:nbp) {
- # Type[[i]] =
- # }
-
Type_mat = list()
Code_mat = c()
Trend_mat = c()
@@ -616,3 +616,24 @@ gg_circle = function(r, xc, yc, color="black", fill=NA, ...) {
ymin = yc + r*sin(seq(0, -pi, length.out=100))
annotate("ribbon", x=x, ymin=ymin, ymax=ymax, color=color, fill=fill, ...)
}
+
+
+
+gpct = function (pct, L, ref=NULL, shift=FALSE) {
+
+ if (is.null(ref)) {
+ minL = min(L, na.rm=TRUE)
+ } else {
+ minL = ref
+ }
+
+ maxL = max(L, na.rm=TRUE)
+ spanL = maxL - minL
+
+ xL = pct/100 * as.numeric(spanL)
+
+ if (shift) {
+ xL = xL + minL
+ }
+ return (xL)
+}
diff --git a/processing/extract.R b/processing/extract.R
index 606877d4aa4cb3f57921aaf381a92854501eac21..b7835335745c4b9efde67ff754a98e8956e40f88 100644
--- a/processing/extract.R
+++ b/processing/extract.R
@@ -263,9 +263,21 @@ extract_meta = function (computer_data_path, filedir, filename, verbose=TRUE) {
tibble(code=trimws(substr(metatxt[11], 38, nchar(metatxt[11]))),
nom=trimws(substr(metatxt[12], 39, nchar(metatxt[12]))),
territoire=trimws(substr(metatxt[13], 39, nchar(metatxt[13]))),
- L93X=as.numeric(substr(metatxt[16], 38, 50)),
- L93Y=as.numeric(substr(metatxt[16], 52, 63)),
- surface_km2=as.numeric(substr(metatxt[19], 38, 50)),
+
+ gestionnaire=trimws(substr(metatxt[7], 60, nchar(metatxt[7]))),
+
+ L93X_m_IN=as.numeric(substr(metatxt[16], 65, 77)),
+ L93X_m_BH=as.numeric(substr(metatxt[16], 38, 50)),
+
+ L93Y_m_IN=as.numeric(substr(metatxt[16], 79, 90)),
+ L93Y_m_BH=as.numeric(substr(metatxt[16], 52, 63)),
+
+ surface_km2_IN=as.numeric(substr(metatxt[19], 52, 63)),
+ surface_km2_BH=as.numeric(substr(metatxt[19], 38, 50)),
+
+ altitude_m_IN=as.numeric(substr(metatxt[20], 52, 63)),
+ altitude_m_BH=as.numeric(substr(metatxt[20], 38, 50)),
+
statut=iStatut[trimws(substr(metatxt[26], 38, 50))],
finalite=iFinalite[trimws(substr(metatxt[26], 52, 56))],
type=iType[trimws(substr(metatxt[26], 58, 58))],
@@ -289,9 +301,9 @@ extract_meta = function (computer_data_path, filedir, filename, verbose=TRUE) {
# Example
# df_meta = extract_meta(
- # "/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/data",
- # '',
- # c('H5920011_HYDRO_QJM.txt', 'K4470010_HYDRO_QJM.txt'))
+# "/home/louis/Documents/bouleau/INRAE/CDD_stationnarite/data",
+# "BanqueHydro_Export2021",
+# c('H5920011_HYDRO_QJM.txt', 'K4470010_HYDRO_QJM.txt'))
# Extraction of data
diff --git a/script.R b/script.R
index d7763d0ea80cacc1820e3d50b3932aecaf58902d..7f1d69bbf4c6d4f72e2c2dd7e602761d1c0ec841 100644
--- a/script.R
+++ b/script.R
@@ -38,6 +38,7 @@ filename =
"O1442910_HYDRO_QJM.txt")
+
### AGENCE ADOUR GARONNE SELECTION ###
# Path to the list file of AG data that will be analysed
AGlistdir =
@@ -199,7 +200,7 @@ res_VCN10trend = get_VCN10trend(df_data, df_meta,
# res_VCN10trend$trend),
# type=list(bquote(Q[A]), bquote(Q[MNA]), bquote(V[CN10])),
# missRect=list(TRUE, TRUE, TRUE),
-# period=period_all,
+# period=list(period_all, period2),
# info_header=TRUE,
# time_header=df_data,
# time_ratio=2,
@@ -215,7 +216,7 @@ panels_layout(list(res_QAtrend$data, res_VCN10trend$data),
res_VCN10trend$trend),
type=list(bquote(Q[A]), bquote(V[CN10])),
missRect=list(TRUE, TRUE),
- period=period_all,
+ period=list(period_all, period2),
info_header=TRUE,
time_header=df_data,
time_ratio=2,
@@ -231,7 +232,7 @@ panels_layout(list(res_QAtrend$data, res_VCN10trend$data),
# df_trend=list(res_QAtrend$trend),
# type=list(bquote(Q[A])),
# missRect=list(TRUE),
-# period=period_all,
+# period=list(period_all, period2),
# info_header=TRUE,
# time_header=df_data,
# time_ratio=2,