panel.R 8.30 KiB
# 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)
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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]]$type p = time_panel(code, df_data, df_trend, missRect, p_threshold, unit2day, type) P[[i+1]] = p } # plot = grid.arrange(gtext, P[[1]], P[[2]], P[[3]], P[[4]], # heights=c(1/8, 1/8, 2/8, 2/8, 2/8), # ncol=1, nrow=5) plot = grid.arrange(grobs=P, heights=c(rep(1/((nbg-2)*2+2), 2), rep(2/((nbg-2)*2+2), nbg-2)), ncol=1, nrow=nbg) # Saving ggsave(plot=plot, path=outdirTmp, filename=paste(as.character(code), '.pdf', sep=''), width=21, height=29.7, units='cm', dpi=100) } pdf_combine(input=file.path(outdirTmp, list.files(outdirTmp)), output=file.path(outdir, outfile)) unlink(outdirTmp, recursive=TRUE)
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} time_panel = function (code, df_data, df_trend, missRect, p_threshold, unit2day, type) { if (type == 'sqrt') { df_data[, 'Qm3s'] = apply(df_data[, 'Qm3s'], 1, sqrt) } df_data_code = df_data[df_data$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$Date)), expand=c(0, 0)) if (type == 'sqrt') { p = p + scale_y_continuous(breaks=seq(0, 100, 10), minor_breaks=seq(0, 100, 5),
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limits=c(0, max(df_data_code$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() )