The simple_plot function from the syuzhet package

syuzhet::simple_plot.R

function (raw_values, title = "Syuzhet Plot", legend_pos = "top", 
  lps = 10, window = 0.1) 
{
  wdw <- round(length(raw_values) * window)
  rolled <- rescale(zoo::rollmean(raw_values, k = wdw, fill = 0))
  half <- round(wdw/2)
  rolled[1:half] <- NA
  end <- length(rolled) - half
  rolled[end:length(rolled)] <- NA
  trans <- get_dct_transform(raw_values, low_pass_size = lps, 
    x_reverse_len = length(raw_values), scale_range = T)
  x <- 1:length(raw_values)
  y <- raw_values
  raw_lo <- stats::loess(y ~ x, span = 0.5)
  low_line <- rescale(stats::predict(raw_lo))
  graphics::par(mfrow = c(2, 1))
  graphics::plot(low_line, type = "l", ylim = c(-1, 1), main = title, 
    xlab = "Full Narrative Time", ylab = "Scaled Sentiment", 
    col = "blue", lty = 2)
  graphics::lines(rolled, col = "grey", lty = 2)
  graphics::lines(trans, col = "red")
  graphics::abline(h = 0, lty = 3)
  graphics::legend(legend_pos, c("Loess Smooth", "Rolling Mean", 
    "Syuzhet DCT"), lty = 1, lwd = 1, col = c("blue", "grey", 
    "red"), bty = "n", cex = 0.75)
  normed_trans <- get_dct_transform(raw_values, scale_range = T, 
    low_pass_size = 5)
  graphics::plot(normed_trans, type = "l", ylim = c(-1, 1), 
    main = "Simplified Macro Shape", xlab = "Normalized Narrative Time", 
    ylab = "Scaled Sentiment", col = "red")
  graphics::par(mfrow = c(1, 1))
}