# Usefull library
library(ggplot2)
library(scales)
library(qpdf)
library(gridExtra)
library(gridtext)
library(dplyr)
library(grid)
library(ggh4x)
library(RColorBrewer)
# Sourcing R file
source('plotting/panel.R', encoding='latin1')
panels_layout = function (df_data, df_meta, layout_matrix, figdir='', filedir_opt='', filename_opt='', variable='', df_trend=NULL, p_threshold=0.1, unit2day=365.25, type='', trend_period=NULL, mean_period=NULL, axis_xlim=NULL, missRect=FALSE, time_header=NULL, info_header=TRUE, time_ratio=2, var_ratio=3, fr_shpdir=NULL, fr_shpname=NULL, bs_shpdir=NULL, bs_shpname=NULL, rv_shpdir=NULL, rv_shpname=NULL, computer_data_path=NULL) {
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)
} else {
unlink(outdirTmp, recursive=TRUE)
dir.create(outdirTmp)
}
nbp = length(df_data)
if (all(class(df_data) != 'list')) {
df_data = list(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)
}}
# Get all different stations code
Code = levels(factor(df_meta$code))
nCode = length(Code)
# print(df_trend)
df_trendtmp = df_trend[[1]]
# print(df_trendtmp)
nPeriod_max = 0
for (code in Code) {
df_trend_code = df_trendtmp[df_trendtmp$code == code,]
Start = df_trend_code$period_start
UStart = levels(factor(Start))
End = df_trend_code$period_end
UEnd = levels(factor(End))
nPeriod = max(length(UStart), length(UEnd))
if (nPeriod > nPeriod_max) {
nPeriod_max = nPeriod
}
}
list_df2plot = vector(mode='list', length=nbp)
# minTrend = c()
# maxTrend = 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]]$trend[df_trend[[i]]$p <= p_threshold[[i]]]
# minTrend[i] = min(okTrend, na.rm=TRUE)
# maxTrend[i] = max(okTrend, na.rm=TRUE)
list_df2plot[[i]] = df2plot
}
Start_code = vector(mode='list', length=nCode)
End_code = vector(mode='list', length=nCode)
Code_code = vector(mode='list', length=nCode)
Periods_code = vector(mode='list', length=nCode)
for (j in 1:nCode) {
code = Code[j]
df_trend_code = df_trendtmp[df_trendtmp$code == code,]
Start = df_trend_code$period_start
UStart = levels(factor(Start))
End = df_trend_code$period_end
UEnd = levels(factor(End))
nPeriod = max(length(UStart), length(UEnd))
Periods = c()
for (i in 1:nPeriod_max) {
Periods = append(Periods,
paste(substr(Start[i], 1, 4),
substr(End[i], 1, 4),
sep=' / '))
}
Start_code[[j]] = Start
End_code[[j]] = End
Code_code[[j]] = code
Periods_code[[j]] = Periods
}
TrendMean_code = array(rep(1, nPeriod_max*nbp*nCode),
dim=c(nPeriod_max, nbp, nCode))
for (j in 1:nPeriod_max) {
for (k in 1:nCode) {
code = Code[k]
for (i in 1:nbp) {
df_data = list_df2plot[[i]]$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)
for (code in Code) {
# Print code of the station for the current plotting
print(paste("Plotting for station :", 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$code == code,]
axis_xlim = c(min(time_header_code$Date),
max(time_header_code$Date))
Htime = time_panel(time_header_code, df_trend_code=NULL,
trend_period=trend_period, missRect=TRUE,
unit2day=365.25, type='Q', first=FALSE)
P[[2]] = Htime
}
nbcol = ncol(as.matrix(layout_matrix))
for (i in 1:nbp) {
df_data = list_df2plot[[i]]$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$code == code,]
color = c()
# for (j in 1:nrow(df_trend_code)) {
grey = 85
for (j in 1:nPeriod_max) {
if (df_trend_code$p[j] <= p_threshold){
# color_res = get_color(df_trend_code$trend[j],
# minTrend[i],
# maxTrend[i],
# palette_name='perso',
# reverse=TRUE)
Start = Start_code[Code_code == code][[1]][j]
End = End_code[Code_code == code][[1]][j]
Periods = Periods_code[Code_code == code][[1]][j]
df_data_code_per =
df_data_code[df_data_code$Date >= Start
& df_data_code$Date <= End,]
df_trend_code_per =
df_trend_code[df_trend_code$period_start == Start
& df_trend_code$period_end == End,]
Ntrend = nrow(df_trend_code_per)
if (Ntrend > 1) {
df_trend_code_per = df_trend_code_per[1,]
}
dataMean = mean(df_data_code$Qm3s, na.rm=TRUE)
trendMean = df_trend_code_per$trend / dataMean
color_res = get_color(trendMean,
minTrendMean[j, i],
maxTrendMean[j, i],
palette_name='perso',
reverse=TRUE)
colortmp = color_res$color
} else {
colortmp = paste('grey', grey, sep='')
grey = grey - 10
}
color = append(color, colortmp)
}
p = time_panel(df_data_code, df_trend_code, type=type,
p_threshold=p_threshold, missRect=missRect,
trend_period=trend_period,
mean_period=mean_period, axis_xlim=axis_xlim,
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 (info_header & i == 1) {
LM = rbind(LM, rep(i, times=LMcol))
} else if (!is.null(time_header) & i == 2) {
LM = rbind(LM,
matrix(rep(rep(i, times=LMcol),
times=time_ratio),
ncol=LMcol, byrow=TRUE))
} else {
LM = rbind(LM,
matrix(rep(layout_matrix_H[i-nbh,],
times=var_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)
}
matrice_panel(list_df2plot, df_meta, trend_period,
slice=12, outdirTmp=outdirTmp)
map_panel(list_df2plot,
df_meta,
idPer=length(trend_period),
computer_data_path=computer_data_path,
fr_shpdir=fr_shpdir,
fr_shpname=fr_shpname,
bs_shpdir=bs_shpdir,
bs_shpname=bs_shpname,
rv_shpdir=rv_shpdir,
rv_shpname=rv_shpname,
outdirTmp=outdirTmp)
# PDF combine
pdf_combine(input=file.path(outdirTmp, list.files(outdirTmp)),
output=file.path(outdir, outfile))
# unlink(outdirTmp, recursive=TRUE)
}