#' @name fig3a
#' @title
#' Plot figure 3a from Fernandez et al. (2022)
#' @description
#' This function returns figure 3a in Fernandez et al.(2022): Frequency distribution of number of N-rates used for fitting CNDC
#' in literature.
fig3a <- function() {
figFreq_rates <- cndcR::biblioCNDC %>%
dplyr::mutate(min = as.numeric(sub("to.*","",.data$nRates)),
max = as.numeric(sub(".*to","",.data$nRates)),
range = max - min) %>%
dplyr::mutate(typeStudy = dplyr::case_when(!is.na(range) & range == 0 ~ "Single N-design",
is.na(range) ~ NA_character_,
TRUE ~ "Multiple N-designs" )) %>%
tidyr::drop_na(.data$typeStudy) %>%
dplyr::mutate(nRates = dplyr::if_else(.data$typeStudy == "Single N-design",
min, min + round((range/2),0 ) )) %>%
ggplot2::ggplot(ggplot2::aes(x = .data$nRates )) +
ggplot2::geom_bar(ggplot2::aes(fill = .data$typeStudy),color = "#3d3c3c") +
ggplot2::geom_text(stat='count', ggplot2::aes(label=.data$..count..), vjust=-0.3, fontface = 3) +
ggplot2::ylab("Number of CNDCs") +
ggplot2::ggtitle("Number of N rates") + ggplot2::xlab(NULL) +
ggplot2::scale_fill_manual(values = c("#3d3c3c","#c4c2c2")) +
ggplot2::scale_x_continuous(breaks = seq(2,7,1)) +
ggplot2::scale_y_continuous(limits = c(0,45)) +
ggplot2::theme(panel.grid.minor = ggplot2::element_blank(),
panel.grid.major = ggplot2::element_line(color = "#e8e9eb"),
panel.background = ggplot2::element_rect(fill = "#f5f5f5"),
panel.border = ggplot2::element_rect(colour = "black", fill = NA),
text = ggplot2::element_text(size = 14),
legend.title = ggplot2::element_blank(),
legend.position = c(0.8,0.8),
legend.background = ggplot2::element_blank(),
axis.ticks.length=ggplot2::unit(-0.15, "cm"),
axis.text.x = ggplot2::element_text(margin=ggplot2::unit(c(0.5,0.5,0.5,0.5), "cm")),
axis.text.y = ggplot2::element_text(margin=ggplot2::unit(c(0.5,0.5,0.5,0.5), "cm"),
size = 13))
return(figFreq_rates)
}
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