example

gistfile1.txt

draw_plot <- function(funs = list('S' = function(x) x, 'D' = function(x) 100 - x), 
                      xlim = c(0, 100)) {

    # data.frame of 1000 points to trace smooth functions
    dat <- tibble(x = seq(xlim[1], xlim[2], length.out = 1000),
                  y1 = funs[[1]](x),
                  y2 = funs[[2]](x))

    # find equilibrium and add it to data.frame
    equilibrium <- curve_intersect(funs[[1]], funs[[2]], domain = xlim)
    tmp <- tibble(x_eq = equilibrium[[1]],
                  y_eq = equilibrium[[2]],
                  equilibrium = 'Equilibrium')
    dat <- bind_rows(dat, tmp)

    # TODO: smart segment detection
    zero_y <- min(c(dat$y1, dat$y2), na.rm = TRUE)
    zero_x <- min(dat$x, na.rm = TRUE)

    # plot
    p <- ggplot(dat, aes(x, y1, label = equilibrium)) +
         geom_line() +
         geom_line(aes(x, y2)) +
         geom_point(aes(x_eq, y_eq), size = 2) +
         geom_segment(aes(x = 50, y = 0, xend = 50, yend = 50), linetype = 'dashed') +
         geom_segment(aes(x = 0, y = 50, xend = 50, yend = 50), linetype = 'dashed') +
         theme_minimal() +
         scale_x_continuous(expand = c(0, 0)) +
         scale_y_continuous(expand = c(0, 0)) +
         theme(panel.grid = element_blank(),
               axis.line = element_line(size = 1),
               axis.text = element_blank(),
               axis.title.x = element_text(hjust = 1),
               axis.title.y = element_text(hjust = 1, angle = 0)) +
         labs(x = 'Q', y = 'P')
    p

}