# Usefull library
library(ggplot2)
library(scales)
library(qpdf)
library(gridExtra)
library(gridtext)
library(dplyr)
library(grid)
# Time panel
panel = function (df_data, df_meta, figdir, filedir_opt='', filename_opt='', variable='', df_trend=NULL, p_threshold=0.1, unit2day=365.25, type='', missRect=FALSE) {
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)
}}
# print(df_data)
# print(df_trend)
# print(p_threshold)
# print(unit2day)
# print(missRect)
list_df2plot = vector(mode='list', length=nbp)
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]])
list_df2plot[[i]] = df2plot
}
# print(list_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$code))
for (code in Code) {
# Print code of the station for the current plotting
print(paste("Plotting for sation :", code))
nbg = nbp+1
P = vector(mode='list', length=nbg)
# P = as.list(rep(void, nbp))
# print(nbp)
# print(P)
gtext = text_panel(code, df_meta)
P[[1]] = gtext
for (i in 1:nbp) {
df_data = list_df2plot[[i]]$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]]$type
p = time_panel(code, df_data, df_trend, missRect,
p_threshold, unit2day, type)
P[[i+1]] = p
}
# plot = grid.arrange(gtext, P[[1]], P[[2]], P[[3]], P[[4]],
# heights=c(1/8, 1/8, 2/8, 2/8, 2/8),
# ncol=1, nrow=5)
plot = grid.arrange(grobs=P,
heights=c(rep(1/((nbg-2)*2+2), 2),
rep(2/((nbg-2)*2+2), nbg-2)),
ncol=1, nrow=nbg)
# Saving
ggsave(plot=plot,
path=outdirTmp,
filename=paste(as.character(code), '.pdf', sep=''),
width=21, height=29.7, units='cm', dpi=100)
}
pdf_combine(input=file.path(outdirTmp, list.files(outdirTmp)),
output=file.path(outdir, outfile))
unlink(outdirTmp, recursive=TRUE)
}
time_panel = function (code, df_data, df_trend, missRect, p_threshold, unit2day, type) {
if (type == 'sqrt') {
df_data[, 'Qm3s'] = apply(df_data[, 'Qm3s'], 1, sqrt)
}
df_data_code = df_data[df_data$code == code,]
dDate = df_data_code$Date[length(df_data_code$Date)] -
df_data_code$Date[1]
datebreak = round(as.numeric(dDate) / unit2day / 11 , 0)
p = ggplot() + theme_bw() +
geom_line(aes(x=df_data_code$Date, y=df_data_code$Qm3s),
color='black')
if (missRect) {
NAdate = df_data_code$Date[is.na(df_data_code$Qm3s)]
dNAdate = diff(NAdate)
NAdate_Down = NAdate[append(Inf, dNAdate) != 1]
NAdate_Up = NAdate[append(dNAdate, Inf) != 1]
p = p +
geom_rect(aes(xmin=NAdate_Down,
ymin=0,
xmax=NAdate_Up,
ymax=max(df_data_code$Qm3s, na.rm=TRUE)*1.1),
linetype=0, fill='Wheat', alpha=0.3)
}
if (!is.null(df_trend)) {
if (df_trend[df_trend$code == code,]$p < p_threshold) {
abs = c(df_data_code$Date[1],
df_data_code$Date[length(df_data_code$Date)])
abs_num = as.numeric(abs)/unit2day
ord = abs_num * df_trend$trend[df_trend$code == code] +
df_trend$intercept[df_trend$code == code]
p = p +
geom_line(aes(x=abs, y=ord),
color='cornflowerblue')
}}
p = p +
# ggtitle(paste(variable, 'station',
# as.character(code), sep=' ')) +
ylab(expression(paste('débit [', m^{3}, '.',
s^{-1}, ']', sep=''))) +
xlab('date') +
scale_x_date(date_breaks=paste(as.character(datebreak),
'year', sep=' '),
date_labels="%Y",
limits=c(min(df_data_code$Date),
max(df_data_code$Date)),
expand=c(0, 0))
if (type == 'sqrt') {
p = p +
scale_y_continuous(breaks=seq(0, 100, 10),
minor_breaks=seq(0, 100, 5),
limits=c(0,
max(df_data_code$Qm3s,
na.rm=TRUE)*1.1),
expand=c(0, 0))
} else if (type == 'time') {
p = p +
scale_y_continuous(breaks=seq(0, 10000, 1000),
minor_breaks=seq(0, 10000, 500),
limits=c(0,
max(df_data_code$Qm3s,
na.rm=TRUE)*1.1),
expand=c(0, 0))
} else {
p = p +
scale_y_continuous(limits=c(0,
max(df_data_code$Qm3s,
na.rm=TRUE)*1.1),
expand=c(0, 0))
}
p = p +
theme(
panel.background=element_rect(fill="white"),
plot.margin=margin(0, 5, 0, 5, unit="mm"))
return(p)
}
text_panel = function(code, df_meta) {
df_meta_code = df_meta[df_meta$code == code,]
text = paste(
"<span style='font-size:18pt'> station <b>", code, "</b></span><br>",
"nom : ", df_meta_code$nom, "<br>",
"territoire : ", df_meta_code$territoire, "<br>",
"position : (", df_meta_code$L93X, "; ", df_meta_code$L93Y, ")", "<br>",
"surface : ", df_meta_code$surface_km2, " km<sup>2</sup>",
sep='')
gtext = richtext_grob(text,
x=0, y=1,
margin=unit(c(5, 5, 5, 5), "mm"),
hjust=0, vjust=1,
gp=gpar(col="grey20", fontsize=12))
return(gtext)
}
void = ggplot() + geom_blank(aes(1,1)) +
theme(
plot.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
axis.ticks = element_blank(),
axis.line = element_blank()
)