# \\\
# Copyright 2021-2022 Louis Héraut*1
#
# *1   INRAE, France
#      louis.heraut@inrae.fr
#
# This file is part of ash R toolbox.
#
# ash R toolbox is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or (at
# your option) any later version.
#
# ash R toolbox is distributed in the hope that it will be useful, but 
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
# General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with ash R toolbox.  If not, see <https://www.gnu.org/licenses/>.
# ///
#
#
# plotting/layout.R
#
# Regroups general parameters about plotting like the theme used ang
# color management. It mainly deals with the calling to specific
# plotting functions and the organisation of each plot for the
# generation of the PDF.


# Usefull library
library(ggplot2)
library(scales)
library(qpdf)
library(gridExtra)
library(gridtext)
library(dplyr)
library(grid)
library(ggh4x)
library(RColorBrewer)
library(rgdal)
library(shadowtext)
library(png)


# Sourcing R file
source('plotting/datasheet.R', encoding='UTF-8')
source('plotting/map.R', encoding='UTF-8')
source('plotting/matrix.R', encoding='UTF-8')
source('plotting/break.R', encoding='UTF-8')


## 1. PERSONALISATION
### 1.1. Personal theme
theme_ash =
    theme(
        # White background
        panel.background=element_rect(fill='white'),
        # Font
        text=element_text(family='sans'),
        # Border of plot
        panel.border = element_rect(color="grey85",
                                    fill=NA,
                                    size=0.7),
        # Grid
        panel.grid.major.x=element_blank(),
        panel.grid.major.y=element_blank(),
        # Ticks marker
        axis.ticks.x=element_line(color='grey75', size=0.3),
        axis.ticks.y=element_line(color='grey75', size=0.3),
        # Ticks label
        axis.text.x=element_text(color='grey40'),
        axis.text.y=element_text(color='grey40'),
        # Ticks length
        axis.ticks.length=unit(1.5, 'mm'),
        # Ticks minor
        ggh4x.axis.ticks.length.minor=rel(0.5),
        # Title
        plot.title=element_blank(),
        # Axis title
        axis.title.x=element_blank(),
        axis.title.y=element_text(size=9, vjust=1.2, 
                                  hjust=0.5, color='grey20'),
        # Axis line
        axis.line.x=element_blank(),
        axis.line.y=element_blank(),
        )

### 1.2. Color palette
palette_perso = c('#0f3b57', # cold
                  '#1d7881',
                  '#80c4a9',
                  '#e2dac6', # mid
                  '#fadfad',
                  '#d08363',
                  '#7e392f') # hot


## 2. USEFUL GENERICAL PLOT
### 2.1. Void plot
# A plot completly blank
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()
    )

# A plot completly blank with a contour
contour = void +
    theme(plot.background=element_rect(fill=NA, color="#EC4899"),
          plot.margin=margin(t=0, r=0, b=0, l=0, unit="mm"))

### 2.2. Circle
# Allow to draw circle in ggplot2 with a radius and a center position
gg_circle = function(r, xc, yc, color="black", fill=NA, ...) {
    x = xc + r*cos(seq(0, pi, length.out=100))
    ymax = yc + r*sin(seq(0, pi, length.out=100))
    ymin = yc + r*sin(seq(0, -pi, length.out=100))
    annotate("ribbon", x=x, ymin=ymin, ymax=ymax, color=color,
             fill=fill, ...)
}


## 3. LAYOUT
# Generates a PDF that gather datasheets, map and summarize matrix about the trend analyses realised on selected stations
datasheet_layout = function (df_data, df_meta, layout_matrix,
                             toplot=c('datasheet', 'matrix', 'map'),
                             figdir='', filedir_opt='', filename_opt='',
                             variable='', df_trend=NULL,
                             alpha=0.1, unit2day=365.25, var='',
                             type='', trend_period=NULL,
                             mean_period=NULL, axis_xlim=NULL,
                             missRect=FALSE, time_header=NULL,
                             info_header=TRUE, foot_note=FALSE,
                             info_ratio=1, time_ratio=2,
                             var_ratio=3, foot_height=0.5,
                             df_shapefile=NULL,
                             resources_path=NULL,
                             AEAGlogo_file=NULL,
                             INRAElogo_file=NULL,
                             FRlogo_file=NULL) {

    # Name of the document
    outfile = "Panels"
    # If there is an option to mention in the filename it adds it
    if (filename_opt != '') {
        outfile = paste(outfile, '_', filename_opt, sep='')
    }
    # Add the 'pdf' extensionto the name
    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)
    }

    # Names of a temporary directory to store all the independent pages
    outdirTmp = file.path(outdir, 'tmp')
    # Creates it if it does not exist
    if (!(file.exists(outdirTmp))) {
        dir.create(outdirTmp)
    # If it already exists it deletes the pre-existent directory
    # and recreates one
    } else {
        unlink(outdirTmp, recursive=TRUE)
        dir.create(outdirTmp)
    }

    # Number of type/variable
    nbp = length(df_data)

    # Convert data tibble to list of tibble if it is not the case
    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(alpha) != 'list')) {
        alpha = list(alpha)
        # If there is only one value
        if (length(alpha) == 1) {
            # Replicates the value the number of times that there
            # is of studied variables
            alpha = replicate(nbp, alpha)
        }}

    # Same
    if (all(class(unit2day) != 'list')) {
        unit2day = list(unit2day)
        if (length(unit2day) == 1) {
            unit2day = replicate(nbp, unit2day)
        }}

    if (all(class(var) != 'list')) {
        var = list(var)
        if (length(var) == 1) {
            var = replicate(nbp, var)
        }}

    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)
        }}

    # Creates a blank list to store all the data of each type of plot
    list_df2plot = vector(mode='list', length=nbp)

    # For all the type of graph / number of studied variables
    for (i in 1:nbp) {
        # Creates a list that gather all the info for one type of graph
        df2plot = list(data=df_data[[i]], 
                       trend=df_trend[[i]],
                       alpha=alpha[[i]],
                       unit2day=unit2day[[i]],
                       var=var[[i]], type=type[[i]],
                       missRect=missRect[[i]])
        # Stores it
        list_df2plot[[i]] = df2plot
    }

    # If datasheets needs to be plot
    if ('datasheet' %in% toplot) {
        
        datasheet_panel(list_df2plot, df_meta, trend_period, info_header=info_header, time_header=time_header, foot_note=foot_note, layout_matrix=layout_matrix, info_ratio=info_ratio, time_ratio=time_ratio, var_ratio=var_ratio, foot_height=foot_height, resources_path=resources_path, AEAGlogo_file=AEAGlogo_file, INRAElogo_file=INRAElogo_file, FRlogo_file=FRlogo_file, outdirTmp=outdirTmp)

    }

    # If summarize matrix needs to be plot
    if ('matrix' %in% toplot) {
        matrix_panel(list_df2plot, df_meta, trend_period, mean_period,
                     slice=19, outdirTmp=outdirTmp, A3=TRUE,
                     foot_note=foot_note, foot_height=foot_height, resources_path=resources_path, AEAGlogo_file=AEAGlogo_file, INRAElogo_file=INRAElogo_file, FRlogo_file=FRlogo_file,)
    }

    # If map needs to be plot
    if ('map' %in% toplot) {
        map_panel(list_df2plot, 
                  df_meta,
                  idPer_trend=length(trend_period),
                  mean_period=mean_period,
                  df_shapefile=df_shapefile,
                  foot_note=foot_note,
                  foot_height=foot_height,
                  resources_path=resources_path,
                  AEAGlogo_file=AEAGlogo_file,
                  INRAElogo_file=INRAElogo_file,
                  FRlogo_file=FRlogo_file,
                  outdirTmp=outdirTmp)
    }

    # Combine independant pages into one PDF
    details = file.info(list.files(outdirTmp, full.names=TRUE))
    details = details[with(details, order(as.POSIXct(mtime))),]
    listfile_path = rownames(details)
    pdf_combine(input=listfile_path,
                output=file.path(outdir, outfile))
} 


## 4. COLOR MANAGEMENT
### 4.1. Color on colorbar
# Returns a color of a palette corresponding to a value included
# between the min and the max of the variable
get_color = function (value, min, max, ncolor=256, palette_name='perso', reverse=FALSE) {

    # If the value is a NA return NA color
    if (is.na(value)) {
        return (NA)
    }
    
    # If the palette chosen is the personal ones
    if (palette_name == 'perso') {
        colorList = palette_perso
    # Else takes the palette corresponding to the name given
    } else {
        colorList = brewer.pal(11, palette_name)
    }
    
    # Gets the number of discrete colors in the palette
    nSample = length(colorList)
    # Recreates a continuous color palette
    palette = colorRampPalette(colorList)(ncolor)
    # Separates it in the middle to have a cold and a hot palette
    Sample_hot = 1:(as.integer(nSample/2)+1)
    Sample_cold = (as.integer(nSample/2)+1):nSample
    palette_hot = colorRampPalette(colorList[Sample_hot])(ncolor)
    palette_cold = colorRampPalette(colorList[Sample_cold])(ncolor)

    # Reverses the palette if it needs to be
    if (reverse) {
        palette = rev(palette)
        palette_hot = rev(palette_hot)
        palette_cold = rev(palette_cold)
    }

    # Computes the absolute max
    maxAbs = max(abs(max), abs(min))

    # If the value is negative
    if (value < 0) {
        # Gets the relative position of the value in respect
        # to its span
        idNorm = (value + maxAbs) / maxAbs
        # The index corresponding
        id = round(idNorm*(ncolor - 1) + 1, 0)
        # The associated color
        color = palette_cold[id]
    # Same if it is a positive value
    } else {
        idNorm = value / maxAbs
        id = round(idNorm*(ncolor - 1) + 1, 0)
        color = palette_hot[id]
    }
    return(color)
}

### 4.2. Colorbar
# Returns the colorbar but also positions, labels and colors of some
# ticks along it 
get_palette = function (min, max, ncolor=256, palette_name='perso', reverse=FALSE, nbTick=10) {
    
    # If the palette chosen is the personal ones
    if (palette_name == 'perso') {
        colorList = palette_perso
    # Else takes the palette corresponding to the name given
    } else {
        colorList = brewer.pal(11, palette_name)
    }
    
    # Gets the number of discrete colors in the palette
    nSample = length(colorList)
    # Recreates a continuous color palette
    palette = colorRampPalette(colorList)(ncolor)
    # Separates it in the middle to have a cold and a hot palette
    Sample_hot = 1:(as.integer(nSample/2)+1)
    Sample_cold = (as.integer(nSample/2)+1):nSample
    palette_hot = colorRampPalette(colorList[Sample_hot])(ncolor)
    palette_cold = colorRampPalette(colorList[Sample_cold])(ncolor)

    # Reverses the palette if it needs to be
    if (reverse) {
        palette = rev(palette)
        palette_hot = rev(palette_hot)
        palette_cold = rev(palette_cold)
    }

    # If the min and the max are below zero
    if (min < 0 & max < 0) {
        # The palette show is only the cold one
        paletteShow = palette_cold
    # If the min and the max are above zero
    } else if (min > 0 & max > 0) {
        # The palette show is only the hot one
        paletteShow = palette_hot
    # Else it is the entire palette that is shown
    } else {
        paletteShow = palette
    }

    # The position of ticks is between 0 and 1
    posTick = seq(0, 1, length.out=nbTick)
    # Blank vector to store corresponding labels and colors
    labTick = c()
    colTick = c()
    # For each tick
    for (i in 1:nbTick) {
        # Computes the graduation between the min and max
        lab = (i-1)/(nbTick-1) * (max - min) + min
        # Gets the associated color
        col = get_color(lab, min=min, max=max,
                        ncolor=ncolor,
                        palette_name=palette_name,
                        reverse=reverse)
        # Stores them
        labTick = c(labTick, lab)
        colTick = c(colTick, col)
    }
    # List of results
    res = list(palette=paletteShow, posTick=posTick,
               labTick=labTick, colTick=colTick)
    return(res)
}

### 4.3. Palette tester
# Allows to display the current personal palette
palette_tester = function (n=256) {

    # An arbitrary x vector
    X = 1:n
    # All the same arbitrary y position to create a colorbar
    Y = rep(0, times=n)

    # Recreates a continuous color palette
    palette = colorRampPalette(palette_perso)(n)

    # Open a plot
    p = ggplot() + 
        # Make the theme blank
        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()
        ) +
        # Plot the palette
        geom_line(aes(x=X, y=Y), color=palette[X], size=60) +
        scale_y_continuous(expand=c(0, 0))

    # Saves the plot
    ggsave(plot=p,
           filename=paste('palette_test', '.pdf', sep=''),
           width=10, height=10, units='cm', dpi=100)
}


### Foot note panel
foot_panel = function (name, n_page, N_page, resources_path, AEAGlogo_file, INRAElogo_file, FRlogo_file, foot_height) {
    
    text_page = paste(
        name, " <b>p. ", n_page, "/", N_page, "</b>",
        sep='')
    
    text_date = paste (
        format(Sys.Date(), "%B %Y"),
        sep='')

    # Converts all texts to graphical object in the right position
    gtext_page = richtext_grob(text_page,
                               x=1, y=0,
                               margin=unit(c(t=0, r=0, b=0, l=0), "mm"),
                               hjust=1, vjust=0.5,
                               gp=gpar(col="#00A3A8", fontsize=8))

    gtext_date = richtext_grob(text_date,
                               x=1, y=0.4,
                               margin=unit(c(t=0, r=0, b=0, l=0), "mm"),
                               hjust=1, vjust=0.5,
                               gp=gpar(col="#00A3A8", fontsize=6))
    
    AEAGlogo_path = file.path(resources_path, AEAGlogo_file)
    INRAElogo_path = file.path(resources_path, INRAElogo_file)
    FRlogo_path = file.path(resources_path, FRlogo_file)
    
    AEAGlogo_img = readPNG(AEAGlogo_path)
    AEAGlogo_grob = rasterGrob(AEAGlogo_img,
                               width=unit(0.7*foot_height, "cm"))
    
    INRAElogo_img = readPNG(INRAElogo_path)
    INRAElogo_grob = rasterGrob(INRAElogo_img,
                                y=0.57,
                                vjust=0.5,
                                width=unit(1.1*foot_height, "cm"))
    
    FRlogo_img = readPNG(FRlogo_path)
    FRlogo_grob = rasterGrob(FRlogo_img,
                             x=0, hjust=0,
                             width=unit(1*foot_height, "cm"))
    
    P = list(void,
             FRlogo_grob, INRAElogo_grob, AEAGlogo_grob,
             gtext_page, gtext_date) 

    # Creates the matrix layout
    LM = matrix(c(1, 2, 3, 4, 5,
                  1, 2, 3, 4, 6),
                nrow=2, 
                byrow=TRUE)

    # And sets the relative width of each plot
    widths = rep(1, times=ncol(LM))
    widths[2] = 0.18
    widths[3] = 0.25
    widths[4] = 0.2
    
    # Arranges all the graphical objetcs
    plot = grid.arrange(grobs=P,
                        layout_matrix=LM,
                        widths=widths)
    
    # Return the plot object
    return (plot)
}


## 5. OTHER TOOLS
### 5.1. Number formatting
# Returns the power of ten of the scientific expression of a value
get_power = function (value) {

    # Do not care about the sign
    value = abs(value)
    
    # If the value is greater than one
    if (value >= 1) {
        # The magnitude is the number of character of integer part
        # of the value minus one
        power = nchar(as.character(as.integer(value))) - 1
    # If value is zero
    } else if (value == 0) {
        # The power is zero
        power = 0
    # If the value is less than one
    } else {
        # Extract the decimal part
        dec = gsub('0.', '', as.character(value), fixed=TRUE)
        # Number of decimal with zero
        ndec = nchar(dec)
        # Number of decimal without zero
        nnum = nchar(as.character(as.numeric(dec)))
        # Compute the power of ten associated
        power = -(ndec - nnum + 1)
    }
    return(power)
}

### 5.2. Pourcentage of variable
# Returns the value corresponding of a certain percentage of a
# data serie
gpct = function (pct, L, min_lim=NULL, shift=FALSE) {

    # If no reference for the serie is given
    if (is.null(min_lim)) {
        # The minimum of the serie is computed
        minL = min(L, na.rm=TRUE)
    # If a reference is specified
    } else {
        # The reference is the minimum
        minL = min_lim
    }

    # Gets the max
    maxL = max(L, na.rm=TRUE)
    # And the span
    spanL = maxL - minL
    # Computes the value corresponding to the percentage
    xL = pct/100 * as.numeric(spanL)

    # If the value needs to be shift by its reference
    if (shift) {
        xL = xL + minL
    }
    return (xL)
}

### 5.3. Add months
add_months = function (date, n) {
    new_date = seq(date, by = paste (n, "months"), length = 2)[2]
    return (new_date)
}