diff --git a/plotting/panel.R b/plotting/panel.R
index 49642ea83de0291048fe7d7d8ede141b298de14f..655f562a9bcd1f658faa8f9599fbc477aaef013a 100644
--- a/plotting/panel.R
+++ b/plotting/panel.R
@@ -19,14 +19,8 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
maxQ = max(df_data_code$Qm3s, na.rm=TRUE)
- if (maxQ > 1) {
- power = nchar(as.character(as.integer(maxQ))) - 1
- } else {
- dec = gsub('0.', '', as.character(maxQ), fixed=TRUE)
- ndec = nchar(dec)
- nnum = nchar(as.character(as.numeric(dec)))
- power = -(ndec - nnum + 1)
- }
+ power = get_power(maxQ)
+
dbrk = 10^power
df_data_code$Qm3sN = df_data_code$Qm3s / dbrk
@@ -190,10 +184,10 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
# if (norm) {
# p = p +
- # ylab(bquote('débit ['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))}))
+ # ylab(bquote('débit ['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))}))
# } else {
# p = p +
- # ylab(expression(paste('débit [', m^{3}, '.',
+ # ylab(expression(paste('débit [', m^{3}, '.',
# s^{-1}, ']', sep='')))
# }
@@ -224,7 +218,7 @@ text_panel = function(code, df_meta) {
text = paste(
"<span style='font-size:18pt'> station <b>", code, "</b></span><br>",
"nom : ", df_meta_code$nom, "<br>",
- "région hydrographique : ", df_meta_code$region_hydro, "<br>",
+ "région hydrographique : ", df_meta_code$region_hydro, "<br>",
"position : (", df_meta_code$L93X, "; ", df_meta_code$L93Y, ")", "<br>",
"surface : ", df_meta_code$surface_km2, " km<sup>2</sup>",
sep='')
@@ -260,8 +254,15 @@ matrice_panel = function (list_df2plot, df_meta) {
# Get all different stations code
Code = levels(factor(df_meta$code))
- Type_mat = c()
+ # Type = vector(mode='list', length=nbp)
+ # for (i in 1:nbp) {
+ # Type[[i]] =
+ # }
+
+ Type_mat = list()
Code_mat = c()
+ Trend_mat = c()
+ Fill_mat = c()
Color_mat = c()
for (code in Code) {
@@ -271,8 +272,8 @@ matrice_panel = function (list_df2plot, df_meta) {
p_threshold = list_df2plot[[i]]$p_threshold
type = list_df2plot[[i]]$type
- Type_mat[i] = as.character(type)
- Code_mat[i] = code
+ Type_mat = append(Type_mat, type)
+ Code_mat = append(Code_mat, code)
df_trend_code = df_trend[df_trend$code == code,]
@@ -283,18 +284,128 @@ matrice_panel = function (list_df2plot, df_meta) {
palette_name='perso',
reverse=FALSE)
- color = color_res$color
+ trend = df_trend_code$trend
+ fill = color_res$color
+ color = 'white'
+
- } else {
+ } else {
+ trend = NA
+ fill = 'white'
color = 'white'
+
}
- Color_mat[i] = color
+ Trend_mat = append(Trend_mat, trend)
+ Fill_mat = append(Fill_mat, fill)
+ Color_mat = append(Color_mat, color)
}
}
-
+
+ X = as.integer(factor(as.character(Type_mat)))
+ Y = as.integer(factor(Code_mat))
+
mat = ggplot() +
- geom_tile(aes(x=Type_mat, y=Code_mat, fill=Color_mat))
+
+ theme(
+ panel.background=element_rect(fill='white'),
+ text=element_text(family='sans'),
+ panel.border=element_blank(),
+
+ panel.grid.major.y=element_blank(),
+ panel.grid.major.x=element_blank(),
+
+ axis.text.x=element_blank(),
+ axis.text.y=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'),
+
+ plot.title=element_text(size=9, vjust=-3,
+ hjust=-1E-3, color='grey20'),
+
+ axis.title.x=element_blank(),
+ axis.title.y=element_blank(),
+
+ axis.line.x=element_blank(),
+ axis.line.y=element_blank(),
+
+ plot.margin=margin(5, 5, 5, 5, unit="mm"),
+ )
+
+
+ # geom_point(aes(x=X, y=Y),
+ # shape=21, fill=Fill_mat, color=Color_mat,
+ # size=15, stroke=1) +
+
+ for (i in 1:length(X)) {
+ mat = mat +
+ gg_circle(r=0.5, xc=X[i], yc=Y[i], fill=Fill_mat[i], color=Color_mat[i])
+ }
+
+
+ mat = mat +
+
+ coord_fixed() +
+
+ scale_x_continuous(limits=c(min(c(X, Y)) - rel(1.5),
+ max(c(X, Y)) + rel(0.5)),
+ expand=c(0, 0)) +
+
+ scale_y_continuous(limits=c(min(c(X, Y)) - rel(0.5),
+ max(c(X, Y)) + rel(1)),
+ expand=c(0, 0))
+
+ # scale_x_continuous(limits=c(min(X)-0.4, max(X)+0.2),
+ # expand=c(0, 0)) +
+
+ # scale_y_continuous(limits=c(min(Y)-0.2, max(Y)+0.4),
+ # expand=c(0, 0))
+
+ for (i in 1:length(Code)) {
+ mat = mat +
+ annotate('text', x=-0.5, y=i,
+ label=Code[i],
+ hjust=0, vjust=0.5,
+ size=3.5, color='grey40')
+ }
+
+ 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')
+ }
+
+
+ for (i in 1:length(Trend_mat)) {
+ trend = Trend_mat[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))})
+ } else {
+ trendC1 = ''
+ trendC2 = ''
+ }
+ mat = mat +
+ annotate('text', x=X[i], y=Y[i],
+ label=trendC1,
+ 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')
+
+ }
return (mat)
}
@@ -383,3 +494,26 @@ palette_tester = function () {
}
# palette_teste()
+
+
+get_power = function (value) {
+
+ if (value > 1) {
+ power = nchar(as.character(as.integer(value))) - 1
+ } else {
+ dec = gsub('0.', '', as.character(value), fixed=TRUE)
+ ndec = nchar(dec)
+ nnum = nchar(as.character(as.numeric(dec)))
+ power = -(ndec - nnum + 1)
+ }
+
+ return(power)
+}
+
+
+gg_circle = function(r, xc, yc, color="black", fill=NA, ...) {
+ x = xc + r*cos(seq(0, pi, length.out=100))
+ ymax = yc + r*sin(seq(0, pi, length.out=100))
+ ymin = yc + r*sin(seq(0, -pi, length.out=100))
+ annotate("ribbon", x=x, ymin=ymin, ymax=ymax, color=color, fill=fill, ...)
+}
diff --git a/processing/analyse.R b/processing/analyse.R
index 417719a73bb060ea15f1854f7221fc5eeb1460be..e83f5bdb5e1336dbd7148d768d143ba0c8fac946 100644
--- a/processing/analyse.R
+++ b/processing/analyse.R
@@ -4,7 +4,7 @@ library(zoo)
library(StatsAnalysisTrend)
# Sourcing R file
-source('processing/format.R')
+source('processing/format.R', encoding='latin1')
# Compute the time gap by station
diff --git a/script.R b/script.R
index 93ba19fc7ed0c348a1cf94a887d93b2899ef2e74..b684f2732af24004fdb046ca7ec286c77da90746 100644
--- a/script.R
+++ b/script.R
@@ -22,9 +22,13 @@ BHfiledir =
## Manual selection ##
# Name of the file that will be analysed from the BH directory
BHfilename =
- # ""
- c("S2235610_HYDRO_QJM.txt", "P1712910_HYDRO_QJM.txt", "P0885010_HYDRO_QJM.txt")
- # "all"
+ ""
+ # c("S2235610_HYDRO_QJM.txt",
+ # "P1712910_HYDRO_QJM.txt",
+ # "P0885010_HYDRO_QJM.txt",
+ # "A1000030_HYDRO_QJM.txt",
+ # "A2250310_HYDRO_QJM.txt"
+ # )
## Or list selection ##
# Path to the list file of BH data that will be analysed
@@ -32,8 +36,8 @@ BHlistdir =
""
BHlistname =
- ""
- # "Liste-station_RRSE.docx"
+ # ""
+ "Liste-station_RRSE.docx"
### NIVALE ###
@@ -116,6 +120,12 @@ if (BHlistname != ""){
BHfilename = df_selec[df_selec$ok,]$filename
}
+
+######
+BHfilename = BHfilename[1:10]
+######
+
+
# Extract metadata about selected stations
df_meta_BH = extractBH_meta(computer_data_path, BHfiledir, BHfilename)
@@ -166,14 +176,29 @@ res_VCN10trend = get_VCN10trend(df_data, df_meta, period)
# figdir=figdir,
# filename_opt='time')
-panels_layout(list(res_QAtrend$data, res_QMNAtrend$data,
- res_VCN10trend$data),
- layout_matrix=c(1, 2, 3),
+# 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),
+ # period=period,
+ # info_header=TRUE,
+ # time_header=df_data,
+ # header_ratio=2,
+ # figdir=figdir,
+ # filename_opt='')
+
+
+panels_layout(list(res_QAtrend$data, res_VCN10trend$data),
+ layout_matrix=c(1, 2),
df_meta=df_meta,
- df_trend=list(res_QAtrend$trend, res_QMNAtrend$trend,
+ df_trend=list(res_QAtrend$trend,
res_VCN10trend$trend),
- type=list('Q[A]', 'Q[MNA]', 'V[CN10]'),
- missRect=list(TRUE, TRUE, TRUE),
+ type=list(bquote(Q[A]), bquote(V[CN10])),
+ missRect=list(TRUE, TRUE),
period=period,
info_header=TRUE,
time_header=df_data,
@@ -181,6 +206,7 @@ panels_layout(list(res_QAtrend$data, res_QMNAtrend$data,
figdir=figdir,
filename_opt='')
+
### /!\ Removed 185 row(s) containing missing values (geom_path) -> remove NA ###