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### This file is part of 'EvaluateCore' package for R.
### Copyright (C) 2018-2022, ICAR-NBPGR.
#
# EvaluateCore 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 2 of the License, or
# (at your option) any later version.
#
# EvaluateCore 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.
#
# A copy of the GNU General Public License is available at
# https://www.r-project.org/Licenses/
#' Bar Plots
#'
#' Plot Bar plots to graphically compare the frequency distributions of
#' qualitative traits between entire collection (EC) and core set (CS).
#'
#' @inheritParams chisquare.evaluate.core
#'
#' @return A list with the \code{ggplot} objects of relative frequency bar plots
#' of CS and EC for each trait specified as \code{qualitative}.
#'
#'
#' @seealso \code{\link[graphics]{barplot}}, \code{\link[ggplot2]{geom_bar}}
#'
#' @import ggplot2
#' @export
#'
#' @examples
#'
#' data("cassava_CC")
#' data("cassava_EC")
#'
#' ec <- cbind(genotypes = rownames(cassava_EC), cassava_EC)
#' ec$genotypes <- as.character(ec$genotypes)
#' rownames(ec) <- NULL
#'
#' core <- rownames(cassava_CC)
#'
#' quant <- c("NMSR", "TTRN", "TFWSR", "TTRW", "TFWSS", "TTSW", "TTPW", "AVPW",
#' "ARSR", "SRDM")
#' qual <- c("CUAL", "LNGS", "PTLC", "DSTA", "LFRT", "LBTEF", "CBTR", "NMLB",
#' "ANGB", "CUAL9M", "LVC9M", "TNPR9M", "PL9M", "STRP", "STRC",
#' "PSTR")
#'
#' ec[, qual] <- lapply(ec[, qual],
#' function(x) factor(as.factor(x)))
#'
#' bar.evaluate.core(data = ec, names = "genotypes",
#' qualitative = qual, selected = core)
#'
bar.evaluate.core <- function(data, names, qualitative, selected) {
# Checks
checks.evaluate.core(data = data, names = names,
qualitative = qualitative,
selected = selected)
if (any(c("tbl_dataf", "tbl") %in% class(data))) {
warning('"data" is of type tibble\nCoercing to data frame')
data <- as.data.frame(data)
}
dataf <- data[, c(names, qualitative)]
datafcore <- dataf[dataf[, names] %in% selected, ]
dataf$`[Type]` <- "EC"
datafcore$`[Type]` <- "CS"
dataf <- rbind(dataf, datafcore)
rm(datafcore)
outlist <- vector(mode = "list", length = length(qualitative))
names(outlist) <- qualitative
qualitative2 <- paste("`", qualitative, "`", sep = "")
for (i in seq_along(qualitative)) {
# Generate the bar plot
outlist[[i]] <- ggplot(dataf, aes_string(qualitative2[i])) +
geom_bar(aes(y = ..prop.., group = 1),
fill = "gray80", colour = "black") +
ylab("Relative frequency") +
xlab(qualitative[i]) +
facet_grid(~`[Type]`) +
theme_bw() +
theme(axis.text = element_text(colour = "black"),
axis.text.x = element_text(angle = 45, hjust = 1))
}
return(outlist)
}
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