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Heraut Louis authored676665a2
# Usefull librarylibrary(ggplot2)library(scales)library(qpdf)library(gridExtra)library(gridtext)library(dplyr)library(grid)library(ggh4x)library(RColorBrewer)# Sourcing R filesource('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='', period=NULL, missRect=FALSE, time_header=NULL, info_header=TRUE, time_ratio=2, var_ratio=3) { 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() 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)7172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140
maxTrend[i] = max(okTrend, na.rm=TRUE)
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)
} else {
unlink(outdirTmp, recursive=TRUE)
dir.create(outdirTmp)
}
# Get all different stations code
Code = levels(factor(df_meta$code))
nCode = length(Code)
for (code in Code) {
# Print code of the station for the current plotting
print(paste("Plotting for station :", code))
nbh = as.numeric(info_header) + as.numeric(!is.null(time_header))
nbg = nbp + nbh
P = vector(mode='list', length=nbg)
if (info_header) {
Htext = text_panel(code, df_meta)
P[[1]] = Htext
}
if (!is.null(time_header)) {
time_header_code = time_header[time_header$code == code,]
Htime = time_panel(time_header_code, df_trend_code=NULL,
period=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()
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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=TRUE)
colortmp = color_res$color
} else {
colortmp = NA
}
color = append(color, colortmp)
}
p = time_panel(df_data_code, df_trend_code, type=type,
p_threshold=p_threshold, missRect=missRect,
unit2day=unit2day, last=(i > nbp-nbcol),
color=color)
P[[i+nbh]] = p
}
layout_matrix = as.matrix(layout_matrix)
nel = nrow(layout_matrix)*ncol(layout_matrix)
idNA = which(is.na(layout_matrix), arr.ind=TRUE)
layout_matrix[idNA] = seq(max(layout_matrix, na.rm=TRUE) + 1,
max(layout_matrix, na.rm=TRUE) + 1 +
nel)
layout_matrix_H = layout_matrix + nbh
LM = c()
LMcol = ncol(layout_matrix_H)
LMrow = nrow(layout_matrix_H)
for (i in 1:(LMrow+nbh)) {
if (info_header & i == 1) {
LM = rbind(LM, rep(i, times=LMcol))
} else if (!is.null(time_header) & i == 2) {
LM = rbind(LM,
matrix(rep(rep(i, times=LMcol),
times=time_ratio),
ncol=LMcol, byrow=TRUE))
} else {
LM = rbind(LM,
matrix(rep(layout_matrix_H[i-nbh,],
times=var_ratio),
ncol=LMcol, byrow=TRUE))
}}
plot = grid.arrange(grobs=P, layout_matrix=LM)
# plot = grid.arrange(rbind(cbind(ggplotGrob(P[[2]]), ggplotGrob(P[[2]])), cbind(ggplotGrob(P[[3]]), ggplotGrob(P[[3]]))), heights=c(1/3, 2/3))
# Saving
ggsave(plot=plot,
path=outdirTmp,
filename=paste(as.character(code), '.pdf', sep=''),
width=21, height=29.7, units='cm', dpi=100)
}
# By
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slice = 12 ##
nMat = as.integer(nCode/slice) + 1
sublist_df2plot = list_df2plot
for (i in 1:nMat) {
subdf_meta = df_meta[(slice*(i-1)+1):(slice*i),]
subdf_meta = subdf_meta[!is.na(subdf_meta$code),]
subCode = subdf_meta$code
for (j in 1:nbp) {
df_datatmp = list_df2plot[[j]]$data
df_trendtmp = list_df2plot[[j]]$trend
subdf_data = df_datatmp[(df_datatmp$code %in% subCode),]
subdf_trend = df_trendtmp[(df_trendtmp$code %in% subCode),]
sublist_df2plot[[j]]$data = subdf_data
sublist_df2plot[[j]]$trend = subdf_trend
}
mat = matrice_panel(sublist_df2plot,
subdf_meta,
period)
# Saving matrix plot
ggsave(plot=mat,
path=outdirTmp,
filename=paste('matrix_', i, '.pdf', sep=''),
width=29.7, height=21, units='cm', dpi=100)
}
# PDF combine
pdf_combine(input=file.path(outdirTmp, list.files(outdirTmp)),
output=file.path(outdir, outfile))
# unlink(outdirTmp, recursive=TRUE)
}