update simple_plot function

R/syuzhet.R

@@ -282,25 +282,35 @@ rescale_x_2 <- function(v){
 #' calculated for each sentence
 #' @param title for image
 #' @param legend_pos positon for legend
+#' @param number of components for the filter
 #' @export
-simple_plot <- function(raw_values, title="Syuzhet Plot", legend_pos="top"){
-  wdw <- round(length(raw_values)*.1) # wdw = 10% of length
+simple_plot <- 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, x_reverse_len = length(raw_values), scale_range = T)
-  raw_lo <- stats::loess(raw_values ~ seq_along(raw_values), span=.5)
+  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")
-  graphics::lines(rolled, col="blue")
-  graphics::lines(trans, col="red")
-  graphics::legend(legend_pos, c("Loess Smooth", "Rolling Mean", "Syuzhet DCT"), lty=1, lwd=1,col=c('black', 'blue', 'red'), bty='n', cex=.75)
-  normed_trans <- get_dct_transform(raw_values, scale_range = T)
-  graphics::plot(normed_trans,type = "l", ylim = c(-1,1), main = "Normalized Simple Shape", xlab = "Normalized Narrative Time", ylab = "Scaled Sentiment", col="red")
-  graphics::par(mfrow=c(1, 1))
+  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")
+  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))
 }
 
 #' Discrete Cosine Transformation with Reverse Transform.