R/InfographicPlot.R

In sagrudd/nanopoRe: Accessory Methods for the Analysis of Oxford Nanopore Technologies DNA Sequence Data

#' prepare an 3x infographic-styled summary plot
#'
#' This method will prepare a 3x graphical plot summarising user data with an
#' emphasis on visualisation
#'
#' @importFrom emojifont fontawesome
#' @import emojifont
#' @usage infoGraphicPlot3(identifier, panelA, panelB, panelC,
#'     reportDPI = 90)
#' @param identifier a key for the plot
#' @param panelA information for panel1 in format of panelA=c(key='', value='',
#' icon='')
#' @param panelB see panelA
#' @param panelC see panelA
#' @param reportDPI resolution for plot
#' @return link to a figure for display
#'
#' @examples
#' library(emojifont)
#' infoGraphicPlot3(identifier='mappingSummary',
#'     panelA=c(key='Alignments', value='123456', icon='fa-sliders'),
#'     panelB=c(key='Mapping Yield', value='680M', icon='fa-calculator'),
#'     panelC=c(key='Average Accuracy', value='89.0 %', icon='fa-area-chart'))
#'
#' @export
infoGraphicPlot3 <- function(identifier, panelA, panelB, panelC,
    reportDPI = 90) {
    figures <- 3

    df <- data.frame(x = cumsum(c(2, rep(6.5, figures - 1))), y=rep(2,figures),
        h = rep(4, figures), w = rep(6, figures))

    df$key <- c(panelA[["key"]], panelB[["key"]], panelC[["key"]])
    df$info <- c(panelA[["value"]], panelB[["value"]], panelC[["value"]])
    df$icon <- emojifont::fontawesome(c(panelA[["icon"]], panelB[["icon"]],
        panelC[["icon"]]))

    df$colour <- rep("steelblue", figures)

    InfoGraphicValueBoxes <- ggplot(df, aes_string("x", "y", height = "h",
        width = "w", label = "key", fill = "colour")) + geom_tile(fill =
        brewer.pal(9, "Blues")[7]) + geom_text(color=brewer.pal(9, "Blues")[3],
        hjust = "left", nudge_y = -1.5, nudge_x = -2.6, size = 5) +
        geom_text(label = df$icon, family = "fontawesome-webfont", colour =
        brewer.pal(9, "Blues")[5], size = 23, hjust = "right", nudge_x = 2.85,
        nudge_y = 0.8) + geom_text(label = df$info, size = 10, color =
        brewer.pal(9, "Blues")[2], fontface = "bold", nudge_x = -2.6, hjust =
        "left") + coord_fixed() + scale_fill_brewer(type = "qual", palette =
        "Dark2") + theme_void() + guides(fill = FALSE)

    infographicFile <- file.path(
        getRpath(), paste0(identifier, ".igraphic.png"))

    ggplot2::ggsave(infographicFile, plot = InfoGraphicValueBoxes, device =
        "png", units = "cm", width = 25, height = 5, dpi = reportDPI)

    # knitr::include_graphics(infographicFile)
    return(infographicFile)
}




#' prepare a 4x infographic-styled summary plot
#'
#' This method will prepare a 4x graphical plot summarising user data with an
#' emphasis on visualisation
#'
#' @importFrom emojifont fontawesome
#' @import emojifont
#' @usage infoGraphicPlot4(identifier, panelA, panelB, panelC,
#'     panelD, reportDPI = 90)
#' @param identifier a key for the plot
#' @param panelA information for panel1 in format of panelA=c(key='', value='',
#' icon='')
#' @param panelB see panelA
#' @param panelC see panelA
#' @param panelD see panelA
#' @param reportDPI resolution for plot
#' @return link to a figure for display
#'
#' @examples
#' library(emojifont)
#' infoGraphicPlot4(identifier='mappingSummary',
#'     panelA=c(key='Alignments', value='123456', icon='fa-sliders'),
#'     panelB=c(key='Mapping Yield', value='680M', icon='fa-calculator'),
#'     panelC=c(key='Average Accuracy', value='89.0 %', icon='fa-area-chart'),
#'     panelD=c(key='Average Identity', value='96.2 %', icon='fa-info'))
#'
#' @export
infoGraphicPlot4 <- function(
    identifier, panelA, panelB, panelC, panelD, reportDPI = 90) {
    figures <- 4

    df <- data.frame(x = cumsum(c(2, rep(6.5, figures - 1))), y=rep(2,figures),
        h = rep(4, figures), w = rep(6, figures))

    df$key <- c(panelA[["key"]], panelB[["key"]], panelC[["key"]],
        panelD[["key"]])
    df$info <- c(panelA[["value"]], panelB[["value"]], panelC[["value"]],
        panelD[["value"]])
    df$icon <- emojifont::fontawesome(c(panelA[["icon"]], panelB[["icon"]],
        panelC[["icon"]], panelD[["icon"]]))

    df$colour <- rep("steelblue", figures)

    InfoGraphicValueBoxes <- ggplot(df, aes_string("x", "y", height = "h",
        width = "w", label = "key", fill = "colour")) + geom_tile(fill =
        brewer.pal(9, "Blues")[7]) + geom_text(color =brewer.pal(9,"Blues")[3],
        hjust = "left", nudge_y = -1.5, nudge_x = -2.6, size = 3.5) +
        geom_text(label = df$icon, family = "fontawesome-webfont", colour =
        brewer.pal(9, "Blues")[5], size = 14, hjust = "right", nudge_x = 2.85,
        nudge_y = 0.9) + geom_text(label = df$info, size = 9, color =
        brewer.pal(9, "Blues")[2], fontface = "bold", nudge_x = -2.6, hjust =
        "left") + coord_fixed() + scale_fill_brewer(type = "qual", palette =
        "Dark2") + theme_void() + guides(fill = FALSE)

    infographicFile <- file.path(
        getRpath(), paste0(identifier, ".igraphic.png"))

    ggplot2::ggsave(infographicFile, plot=InfoGraphicValueBoxes, device="png",
        units = "cm", width = 25, height = 5, dpi = reportDPI)

    # knitr::include_graphics(infographicFile)
    return(infographicFile)
}




#' prepare a 5x infographic-styled summary plot
#'
#' This method will prepare a 5x graphical plot summarising user data with an
#' emphasis on visualisation
#'
#' @importFrom emojifont fontawesome
#' @import emojifont
#' @usage infoGraphicPlot5(identifier, panelA, panelB, panelC,
#'     panelD, panelE, reportDPI = 90)
#' @param identifier a key for the plot
#' @param panelA information for panel1 in format of panelA=c(key='', value='',
#' icon='')
#' @param panelB see panelA
#' @param panelC see panelA
#' @param panelD see panelA
#' @param panelE see panelA
#' @param reportDPI resolution for plot
#' @return link to a figure for display
#'
#' @examples
#' library(emojifont)
#' infoGraphicPlot5(identifier='mappingSummary',
#'     panelA=c(key='Alignments', value='123456', icon='fa-sliders'),
#'     panelB=c(key='Mapping Yield', value='680M', icon='fa-calculator'),
#'     panelC=c(key='Average Accuracy', value='89.0 %', icon='fa-area-chart'),
#'     panelD=c(key='Average IdentityX', value='96.2 %', icon='fa-info'),
#'     panelE=c(key='Average IdentityY', value='16.2 %', icon='fa-info'))
#'
#' @export
infoGraphicPlot5 <- function(identifier, panelA, panelB, panelC, panelD, panelE,
    reportDPI = 90) {
    # panelA=c(key='', value='', icon='')
    figures <- 5

    df <- data.frame(x = cumsum(c(2, rep(6.5, figures - 1))), y=rep(2, figures),
        h = rep(4, figures), w = rep(6, figures))

    df$key <- c(panelA[["key"]], panelB[["key"]], panelC[["key"]],
        panelD[["key"]], panelE[["key"]])
    df$info <- c(panelA[["value"]], panelB[["value"]], panelC[["value"]],
        panelD[["value"]], panelE[["value"]])
    df$icon <- emojifont::fontawesome(c(panelA[["icon"]], panelB[["icon"]],
        panelC[["icon"]], panelD[["icon"]], panelE[["icon"]]))

    df$colour <- rep("steelblue", figures)

    InfoGraphicValueBoxes <- ggplot(df, aes_string("x", "y", height = "h",
        width = "w", label = "key", fill = "colour")) + geom_tile(fill =
        brewer.pal(9, "Blues")[7]) + geom_text(color = brewer.pal(9,"Blues")[3],
        hjust = "left", nudge_y = -1.5, nudge_x = -2.6, size = 3.5) + geom_text(
        label = df$icon,family = "fontawesome-webfont", colour = brewer.pal(9,
        "Blues")[5], size = 13.3, hjust = "right", nudge_x=2.85, nudge_y=0.8) +
        geom_text(label = df$info, size = 9, color = brewer.pal(9,"Blues")[2],
        fontface = "bold", nudge_x = -2.6, hjust = "left") + coord_fixed() +
        scale_fill_brewer(type = "qual", palette = "Dark2") + theme_void() +
        guides(fill = FALSE)

    infographicFile <- file.path(
        getRpath(), paste0(identifier, ".igraphic.png"))

    ggplot2::ggsave(infographicFile, plot = InfoGraphicValueBoxes, device="png",
        units = "cm", width = 25, height = 5, dpi = reportDPI)

    # knitr::include_graphics(infographicFile)
    return(infographicFile)
}