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Commit e2ce457b authored by Heraut Louis's avatar Heraut Louis
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Plot aes matrix

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with 266 additions and 291 deletions
+266 -291
plotting/panel.R
+ 168
− 265
View file @ e2ce457b
...@@ -10,216 +10,7 @@ library(ggh4x) ...@@ -10,216 +10,7 @@ library(ggh4x)
library(RColorBrewer) library(RColorBrewer)
# Time panel 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) {
panel = function (df_data, df_meta, layout_matrix, figdir='', filedir_opt='', filename_opt='', variable='', df_trend=NULL, p_threshold=0.1, unit2day=365.25, type='', period=NULL, missRect=FALSE, time_header=NULL, info_header=TRUE, header_ratio=2) {
if (all(class(df_data) != 'list')) {
df_data = list(df_data)
}
nbp = length(df_data)
if (all(class(df_trend) != 'list')) {
df_trend = list(df_trend)
if (length(df_trend) == 1) {
df_trend = replicate(nbp, df_trend)
}}
if (all(class(p_threshold) != 'list')) {
p_threshold = list(p_threshold)
if (length(p_threshold) == 1) {
p_threshold = replicate(nbp, p_threshold)
}}
if (all(class(unit2day) != 'list')) {
unit2day = list(unit2day)
if (length(unit2day) == 1) {
unit2day = replicate(nbp, unit2day)
}}
if (all(class(type) != 'list')) {
type = list(type)
if (length(type) == 1) {
type = replicate(nbp, type)
}}
if (all(class(missRect) != 'list')) {
missRect = list(missRect)
if (length(missRect) == 1) {
missRect = replicate(nbp, missRect)
}}
list_df2plot = vector(mode='list', length=nbp)
minTrend = c()
maxTrend = c()
nokTrend = c()
for (i in 1:nbp) {
df2plot = list(data=df_data[[i]],
trend=df_trend[[i]],
p_threshold=p_threshold[[i]],
unit2day=unit2day[[i]],
type=type[[i]],
missRect=missRect[[i]])
okTrend = df_trend[[i]]$p[df_trend[[i]]$p <= p_threshold[[i]]]
print(okTrend)
minTrend[i] = min(okTrend, na.rm=TRUE)
maxTrend[i] = max(okTrend, na.rm=TRUE)
nokTrend[i] = length(okTrend)
list_df2plot[[i]] = df2plot
}
outfile = "Panels"
if (filename_opt != '') {
outfile = paste(outfile, '_', filename_opt, sep='')
}
outfile = paste(outfile, '.pdf', sep='')
# If there is not a dedicated figure directory it creats one
outdir = file.path(figdir, filedir_opt, sep='')
if (!(file.exists(outdir))) {
dir.create(outdir)
}
outdirTmp = file.path(outdir, 'tmp')
if (!(file.exists(outdirTmp))) {
dir.create(outdirTmp)
}
# Get all different stations code
Code = levels(factor(df_meta$code))
nCode = length(Code)
for (code in Code) {
# Print code of the station for the current plotting
print(paste("Plotting for sation :", code))
nbh = as.numeric(info_header) + as.numeric(!is.null(time_header))
nbg = nbp + nbh
P = vector(mode='list', length=nbg)
if (info_header) {
Htext = text_panel(code, df_meta)
P[[1]] = Htext
}
if (!is.null(time_header)) {
time_header_code = time_header[time_header$code == code,]
Htime = time_panel(time_header_code, df_trend_code=NULL,
period=period, missRect=TRUE,
unit2day=365.25, type='Q')
P[[2]] = Htime
}
nbcol = ncol(as.matrix(layout_matrix))
for (i in 1:nbp) {
df_data = list_df2plot[[i]]$data
df_trend = list_df2plot[[i]]$trend
p_threshold = list_df2plot[[i]]$p_threshold
unit2day = list_df2plot[[i]]$unit2day
missRect = list_df2plot[[i]]$missRect
type = list_df2plot[[i]]$type
df_data_code = df_data[df_data$code == code,]
df_trend_code = df_trend[df_trend$code == code,]
if (df_trend_code$p <= p_threshold){
color_res = get_color(df_trend_code$p,
minTrend[i],
maxTrend[i],
ncolor=10,
palette_name="RdYlBu",
reverse=TRUE)
color = color_res$color
palette = color_res$palette
} else {
color = NULL
palette = NULL
}
print(paste('min', minTrend[i]))
print(df_trend_code$p)
print(paste('max', maxTrend[i]))
if (i == 1) {print(palette)}
print(paste('color', color))
print("")
p = time_panel(df_data_code, df_trend_code, type=type,
p_threshold=p_threshold, missRect=missRect,
unit2day=unit2day, last=(i > nbp-nbcol),
color=color)
P[[i+nbh]] = p
}
layout_matrix = as.matrix(layout_matrix)
nel = nrow(layout_matrix)*ncol(layout_matrix)
##
idNA = which(is.na(layout_matrix), arr.ind=TRUE)
layout_matrix[idNA] = seq(max(layout_matrix, na.rm=TRUE) + 1,
max(layout_matrix, na.rm=TRUE) + 1 +
nel)
##
layout_matrix_H = layout_matrix + nbh
LM = c()
LMcol = ncol(layout_matrix_H)
LMrow = nrow(layout_matrix_H)
for (i in 1:(LMrow+nbh)) {
if (i <= nbh) {
LM = rbind(LM, rep(i, times=LMcol))
} else {
LM = rbind(LM,
matrix(rep(layout_matrix_H[i-nbh,],
times=header_ratio),
ncol=LMcol, byrow=TRUE))
}}
plot = grid.arrange(grobs=P, layout_matrix=LM)
# plot = grid.arrange(rbind(cbind(ggplotGrob(P[[2]]), ggplotGrob(P[[2]])), cbind(ggplotGrob(P[[3]]), ggplotGrob(P[[3]]))), heights=c(1/3, 2/3))
# Saving
ggsave(plot=plot,
path=outdirTmp,
filename=paste(as.character(code), '.pdf', sep=''),
width=21, height=29.7, units='cm', dpi=100)
}
pdf_combine(input=file.path(outdirTmp, list.files(outdirTmp)),
output=file.path(outdir, outfile))
unlink(outdirTmp, recursive=TRUE)
}
time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missRect=FALSE, unit2day=365.25, period=NULL, norm=TRUE, last=FALSE, color=NULL) {
if (type == 'sqrt(Q)') { if (type == 'sqrt(Q)') {
...@@ -238,33 +29,31 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR ...@@ -238,33 +29,31 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
} }
dbrk = 10^power dbrk = 10^power
### /!\ PROBLME entre 11 et 10 ### df_data_code$Qm3sN = df_data_code$Qm3s / dbrk
if (norm) {
df_data_code$Qm3s = df_data_code$Qm3s / dbrk
if (!is.null(df_trend_code)) {
df_trend_code$p = df_trend_code$p / dbrk
df_trend_code$intercept = df_trend_code$intercept / dbrk
}
maxQ = max(df_data_code$Qm3s, na.rm=TRUE) if (!is.null(df_trend_code)) {
if (maxQ >= 5) { df_trend_code$trendN = df_trend_code$trend / dbrk
dbrk = 1.0 df_trend_code$interceptN = df_trend_code$intercept / dbrk
accuracy = 0.1 }
} else if (maxQ < 5 & maxQ >= 3) {
dbrk = 0.5 maxQN = max(df_data_code$Qm3sN, na.rm=TRUE)
accuracy = 0.1
} else if (maxQ < 3 & maxQ >= 2) { if (maxQN >= 5) {
dbrk = 0.4 dbrk = 1.0
accuracy = 0.1 accuracy = 0.1
} else if (maxQ < 2 & maxQ >= 1) { } else if (maxQN < 5 & maxQN >= 3) {
dbrk = 0.2 dbrk = 0.5
accuracy = 0.1 accuracy = 0.1
} else if (maxQ < 1) { } else if (maxQN < 3 & maxQN >= 2) {
dbrk = 0.1 dbrk = 0.4
accuracy = 0.1 accuracy = 0.1
} } else if (maxQN < 2 & maxQN >= 1) {
dbrk = 0.2
accuracy = 0.1
} else if (maxQN < 1) {
dbrk = 0.1
accuracy = 0.1
} }
dDate = as.numeric(df_data_code$Date[length(df_data_code$Date)] - dDate = as.numeric(df_data_code$Date[length(df_data_code$Date)] -
...@@ -286,8 +75,6 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR ...@@ -286,8 +75,6 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
p = ggplot() + p = ggplot() +
# theme_bw() + # theme_bw() +
ggtitle(bquote(.(type)~' ['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))})) +
theme(panel.background=element_rect(fill='white'), theme(panel.background=element_rect(fill='white'),
text=element_text(family='sans'), text=element_text(family='sans'),
...@@ -325,19 +112,19 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR ...@@ -325,19 +112,19 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
if (type == 'sqrt(Q)' | type == 'Q') { if (type == 'sqrt(Q)' | type == 'Q') {
p = p + p = p +
geom_line(aes(x=df_data_code$Date, y=df_data_code$Qm3s), geom_line(aes(x=df_data_code$Date, y=df_data_code$Qm3sN),
color='grey20', color='grey20',
size=0.3) size=0.3)
} else { } else {
p = p + p = p +
# geom_line(aes(x=df_data_code$Date, y=df_data_code$Qm3s), # geom_line(aes(x=df_data_code$Date, y=df_data_code$Qm3sN),
# color='grey70') + # color='grey70') +
geom_point(aes(x=df_data_code$Date, y=df_data_code$Qm3s), geom_point(aes(x=df_data_code$Date, y=df_data_code$Qm3sN),
shape=1, color='grey20', size=1) shape=1, color='grey20', size=1)
} }
if (missRect) { if (missRect) {
NAdate = df_data_code$Date[is.na(df_data_code$Qm3s)] NAdate = df_data_code$Date[is.na(df_data_code$Qm3sN)]
dNAdate = diff(NAdate) dNAdate = diff(NAdate)
NAdate_Down = NAdate[append(Inf, dNAdate) != 1] NAdate_Down = NAdate[append(Inf, dNAdate) != 1]
NAdate_Up = NAdate[append(dNAdate, Inf) != 1] NAdate_Up = NAdate[append(dNAdate, Inf) != 1]
...@@ -346,8 +133,8 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR ...@@ -346,8 +133,8 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
geom_rect(aes(xmin=NAdate_Down, geom_rect(aes(xmin=NAdate_Down,
ymin=0, ymin=0,
xmax=NAdate_Up, xmax=NAdate_Up,
ymax=maxQ*1.1), ymax=maxQN*1.1),
linetype=0, fill='Wheat', alpha=0.3) linetype=0, fill='Wheat', alpha=0.4)
} }
if ((type == 'sqrt(Q)' | type == 'Q') & !is.null(period)) { if ((type == 'sqrt(Q)' | type == 'Q') & !is.null(period)) {
...@@ -356,13 +143,13 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR ...@@ -356,13 +143,13 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
geom_rect(aes(xmin=min(df_data_code$Date), geom_rect(aes(xmin=min(df_data_code$Date),
ymin=0, ymin=0,
xmax=period[1], xmax=period[1],
ymax= maxQ*1.1), ymax= maxQN*1.1),
linetype=0, fill='grey85', alpha=0.3) + linetype=0, fill='grey85', alpha=0.3) +
geom_rect(aes(xmin=period[2], geom_rect(aes(xmin=period[2],
ymin=0, ymin=0,
xmax=max(df_data_code$Date), xmax=max(df_data_code$Date),
ymax= maxQ*1.1), ymax= maxQN*1.1),
linetype=0, fill='grey85', alpha=0.3) linetype=0, fill='grey85', alpha=0.3)
} }
...@@ -374,19 +161,31 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR ...@@ -374,19 +161,31 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
abs_num = as.numeric(abs) / unit2day abs_num = as.numeric(abs) / unit2day
ord = abs_num * df_trend_code$trend + ord = abs_num * df_trend_code$trendN +
df_trend_code$intercept df_trend_code$interceptN
if (!is.null(color)) { if (!is.null(color)) {
p = p + p = p +
geom_line(aes(x=abs, y=ord), geom_line(aes(x=abs, y=ord),
color=color) color=color,
size=0.7)
} else { } else {
p = p + p = p +
geom_line(aes(x=abs, y=ord), geom_line(aes(x=abs, y=ord),
color='cornflowerblue') color='cornflowerblue')
} }
}}
p = p +
ggtitle(bquote(.(type)~~'['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))}~~~'tendance :'~.(format(df_trend_code$trend, scientific=TRUE, digits=3))~m^{3}*'.'*s^{-1}*'.'*an^{-1}))
} else {
p = p +
ggtitle(bquote(.(type)~' ['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))}))
}
} else {
p = p +
ggtitle(bquote(.(type)~' ['*m^{3}*'.'*s^{-1}*'] x'~10^{.(as.character(power))}))
}
# if (norm) { # if (norm) {
...@@ -410,8 +209,8 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR ...@@ -410,8 +209,8 @@ time_panel = function (df_data_code, df_trend_code, type, p_threshold=0.1, missR
max(df_data_code$Date)), max(df_data_code$Date)),
expand=c(0, 0)) + expand=c(0, 0)) +
scale_y_continuous(breaks=seq(0, maxQ*10, dbrk), scale_y_continuous(breaks=seq(0, maxQN*10, dbrk),
limits=c(0, maxQ*1.1), limits=c(0, maxQN*1.1),
expand=c(0, 0), expand=c(0, 0),
labels=label_number(accuracy=accuracy)) labels=label_number(accuracy=accuracy))
...@@ -425,7 +224,7 @@ text_panel = function(code, df_meta) { ...@@ -425,7 +224,7 @@ text_panel = function(code, df_meta) {
text = paste( text = paste(
"<span style='font-size:18pt'> station <b>", code, "</b></span><br>", "<span style='font-size:18pt'> station <b>", code, "</b></span><br>",
"nom : ", df_meta_code$nom, "<br>", "nom : ", df_meta_code$nom, "<br>",
"territoire : ", df_meta_code$territoire, "<br>", "rgion hydrographique : ", df_meta_code$region_hydro, "<br>",
"position : (", df_meta_code$L93X, "; ", df_meta_code$L93Y, ")", "<br>", "position : (", df_meta_code$L93X, "; ", df_meta_code$L93Y, ")", "<br>",
"surface : ", df_meta_code$surface_km2, " km<sup>2</sup>", "surface : ", df_meta_code$surface_km2, " km<sup>2</sup>",
sep='') sep='')
...@@ -440,28 +239,104 @@ text_panel = function(code, df_meta) { ...@@ -440,28 +239,104 @@ text_panel = function(code, df_meta) {
get_color = function (value, min, max, ncolor, palette_name="RdYlBu", reverse=TRUE) { matrice_panel = function (list_df2plot, df_meta) {
if (min == max) { nbp = length(list_df2plot)
palette = colorRampPalette(brewer.pal(11, palette_name))(3)
color = palette[2] minTrend = c()
return(list(color=color, palette=c(color))) 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$code))
Type_mat = c()
Code_mat = c()
Color_mat = c()
for (code in Code) {
for (i in 1:nbp) {
df_trend = list_df2plot[[i]]$trend
p_threshold = list_df2plot[[i]]$p_threshold
type = list_df2plot[[i]]$type
Type_mat[i] = as.character(type)
Code_mat[i] = 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
} else {
color = 'white'
}
Color_mat[i] = color
}
} }
mat = ggplot() +
geom_tile(aes(x=Type_mat, y=Code_mat, fill=Color_mat))
return (mat)
}
palette = colorRampPalette(brewer.pal(11, palette_name))(ncolor)
get_color = function (value, min, max, ncolor=256, palette_name='perso', reverse=FALSE) {
if (palette_name == 'perso') {
palette = colorRampPalette(c(
'#1a4157',
'#00af9d',
'#fbdd7e',
'#fdb147',
'#fd4659'
))(ncolor)
} else {
palette = colorRampPalette(brewer.pal(11, palette_name))(ncolor)
}
if (reverse) { if (reverse) {
palette = rev(palette) palette = rev(palette)
} }
idNorm = (value - min) / (max - min) palette_cold = palette[1:as.integer(ncolor/2)]
palette_hot = palette[(as.integer(ncolor/2)+1):ncolor]
id = round(idNorm*(ncolor-1) + 1, 0)
print(idNorm) ncolor_cold = length(palette_cold)
print(id) ncolor_hot = length(palette_hot)
color = palette[id] if (value < 0) {
idNorm = (value - min) / (0 - min)
id = round(idNorm*(ncolor_cold - 1) + 1, 0)
color = palette_cold[id]
} else {
idNorm = (value - 0) / (max - 0)
id = round(idNorm*(ncolor_hot - 1) + 1, 0)
color = palette_hot[id]
}
return(list(color=color, palette=palette)) return(list(color=color, palette=palette))
} }
...@@ -480,3 +355,31 @@ void = ggplot() + geom_blank(aes(1,1)) + ...@@ -480,3 +355,31 @@ void = ggplot() + geom_blank(aes(1,1)) +
axis.ticks = element_blank(), axis.ticks = element_blank(),
axis.line = element_blank() axis.line = element_blank()
) )
palette_tester = function () {
n = 300
X = 1:n
Y = rep(0, times=n)
palette = colorRampPalette(c(
'#1a4157',
'#00af9d',
'#fbdd7e',
'#fdb147',
'#fd4659'
))(n)
p = ggplot() +
geom_line(aes(x=X, y=Y), color=palette[X], size=10) +
scale_y_continuous(expand=c(0, 0))
ggsave(plot=p,
path='/figures',
filename=paste('palette_test', '.pdf', sep=''),
width=10, height=10, units='cm', dpi=100)
}
# palette_teste()
processing/extractBH.R
+ 36
− 0
View file @ e2ce457b
...@@ -49,6 +49,40 @@ iQHE = c('0'='qualit ...@@ -49,6 +49,40 @@ iQHE = c('0'='qualit
'2'='qualit hautes eaux douteuse') '2'='qualit hautes eaux douteuse')
iRegHydro = c('D'='Affluents du Rhin',
'E'="Fleuves ctiers de l'Artois-Picardie",
'A'='Rhin',
'B'='Meuse',
'F'='Seine aval (Marne incluse)',
'G'='Fleuves ctiers haut normands',
'H'='Seine amont',
'I'='Fleuves ctiers bas normands',
'J'='Bretagne',
'K'='Loire',
'L'='Loire',
'M'='Loire',
'N'='Fleuves ctiers au sud de la Loire',
'O'='Garonne',
'P'='Dordogne',
'Q'='Adour',
'R'='Charente',
'S'="Fleuves ctiers de l'Adour-Garonne",
'U'='Sane',
'V'='Rhne',
'W'='Isre',
'X'='Durance',
'Y'='Fleuves ctiers du Rhne-Mditranne et Corse',
'Z'='les',
'1'='Guadeloupe',
'2'='Martinique',
'5'='Guyane',
'6'='Guyane',
'7'='Guyane',
'8'='Guyane',
'9'='Guyane',
'4'='Runion')
# Get the selection of data from the 'Liste-station_RRSE' file and the BanqueHydro directory # Get the selection of data from the 'Liste-station_RRSE' file and the BanqueHydro directory
get_selection = function (computer_data_path, listdir, listname, get_selection = function (computer_data_path, listdir, listname,
cnames=c('code','station', 'BV_km2', 'axe_principal_concerne', 'longueur_serie', 'commentaires', 'choix'), cnames=c('code','station', 'BV_km2', 'axe_principal_concerne', 'longueur_serie', 'commentaires', 'choix'),
...@@ -190,6 +224,8 @@ extractBH_meta = function (computer_data_path, filedir, filename, verbose=TRUE) ...@@ -190,6 +224,8 @@ extractBH_meta = function (computer_data_path, filedir, filename, verbose=TRUE)
source='BH' source='BH'
) )
df_meta$region_hydro = iRegHydro[substr(df_meta$code, 1, 1)]
return (df_meta) return (df_meta)
} else { } else {
......
processing/extractNV.R
+ 37
− 1
View file @ e2ce457b
...@@ -3,6 +3,40 @@ library(tools) ...@@ -3,6 +3,40 @@ library(tools)
library(dplyr) library(dplyr)
iRegHydro = c('D'='Affluents du Rhin',
'E'="Fleuves ctiers de l'Artois-Picardie",
'A'='Rhin',
'B'='Meuse',
'F'='Seine aval (Marne incluse)',
'G'='Fleuves ctiers haut normands',
'H'='Seine amont',
'I'='Fleuves ctiers bas normands',
'J'='Bretagne',
'K'='Loire',
'L'='Loire',
'M'='Loire',
'N'='Fleuves ctiers au sud de la Loire',
'O'='Garonne',
'P'='Dordogne',
'Q'='Adour',
'R'='Charente',
'S'="Fleuves ctiers de l'Adour-Garonne",
'U'='Sane',
'V'='Rhne',
'W'='Isre',
'X'='Durance',
'Y'='Fleuves ctiers du Rhne-Mditranne et Corse',
'Z'='les',
'1'='Guadeloupe',
'2'='Martinique',
'5'='Guyane',
'6'='Guyane',
'7'='Guyane',
'8'='Guyane',
'9'='Guyane',
'4'='Runion')
# Extraction of metadata # Extraction of metadata
extractNVlist_meta = function (computer_data_path, filedir, listdir, listname, verbose=TRUE) { extractNVlist_meta = function (computer_data_path, filedir, listdir, listname, verbose=TRUE) {
...@@ -57,7 +91,7 @@ extractNVlist_meta = function (computer_data_path, filedir, listdir, listname, v ...@@ -57,7 +91,7 @@ extractNVlist_meta = function (computer_data_path, filedir, listdir, listname, v
altitude_m=df_meta$Alt, altitude_m=df_meta$Alt,
file_path=file.path(dir_path, file_path=file.path(dir_path,
paste(df_meta$CODE, '.txt', sep='')), paste(df_meta$CODE, '.txt', sep='')),
source='NV' source='NV',
) )
df_meta = bind_rows(df_meta, df_meta = bind_rows(df_meta,
...@@ -68,6 +102,8 @@ extractNVlist_meta = function (computer_data_path, filedir, listdir, listname, v ...@@ -68,6 +102,8 @@ extractNVlist_meta = function (computer_data_path, filedir, listdir, listname, v
sep='')))) sep=''))))
df_meta = df_meta[order(df_meta$code),] df_meta = df_meta[order(df_meta$code),]
df_meta$region_hydro = iRegHydro[substr(df_meta$code, 1, 1)]
} else { } else {
print(paste('filename', list_path, 'do not exist')) print(paste('filename', list_path, 'do not exist'))
......
script.R
+ 25
− 25
View file @ e2ce457b
...@@ -77,7 +77,7 @@ source('processing/extractNV.R', encoding='latin1') ...@@ -77,7 +77,7 @@ source('processing/extractNV.R', encoding='latin1')
source('processing/format.R', encoding='latin1') source('processing/format.R', encoding='latin1')
source('processing/analyse.R', encoding='latin1') source('processing/analyse.R', encoding='latin1')
source('plotting/panel.R', encoding='latin1') source('plotting/panel.R', encoding='latin1')
# source('plotting/layout.R') source('plotting/layout.R', encoding='latin1')
# Usefull library # Usefull library
...@@ -155,31 +155,31 @@ res_VCN10trend = get_VCN10trend(df_data, df_meta, period) ...@@ -155,31 +155,31 @@ res_VCN10trend = get_VCN10trend(df_data, df_meta, period)
# TIME PANEL # # TIME PANEL #
# Plot time panel of debit by stations # Plot time panel of debit by stations
# panel(list(df_data, df_data), # panels_layout(list(df_data, df_data),
# layout_matrix=c(1, 2), # layout_matrix=c(1, 2),
# df_meta=df_meta, # df_meta=df_meta,
# missRect=list(TRUE, TRUE), # missRect=list(TRUE, TRUE),
# type=list('Q', 'sqrt(Q)'), # type=list('Q', 'sqrt(Q)'),
# info_header=TRUE, # info_header=TRUE,
# time_header=NULL, # time_header=NULL,
# header_ratio=3, # header_ratio=3,
# figdir=figdir, # figdir=figdir,
# filename_opt='time') # filename_opt='time')
panel(list(res_QAtrend$data, res_QMNAtrend$data, panels_layout(list(res_QAtrend$data, res_QMNAtrend$data,
res_VCN10trend$data), res_VCN10trend$data),
layout_matrix=c(1, 2, 3), layout_matrix=c(1, 2, 3),
df_meta=df_meta, df_meta=df_meta,
df_trend=list(res_QAtrend$trend, res_QMNAtrend$trend, df_trend=list(res_QAtrend$trend, res_QMNAtrend$trend,
res_VCN10trend$trend), res_VCN10trend$trend),
type=list(bquote(Q[A]), bquote(Q[MNA]), bquote(V[CN10])), type=list('Q[A]', 'Q[MNA]', 'V[CN10]'),
missRect=list(TRUE, TRUE, TRUE), missRect=list(TRUE, TRUE, TRUE),
period=period, period=period,
info_header=TRUE, info_header=TRUE,
time_header=df_data, time_header=df_data,
header_ratio=2, header_ratio=2,
figdir=figdir, figdir=figdir,
filename_opt='') filename_opt='')
### /!\ Removed 185 row(s) containing missing values (geom_path) -> remove NA ### ### /!\ Removed 185 row(s) containing missing values (geom_path) -> remove NA ###
......
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