utils for inspection of S-curves

R/s_curve.R

@@ -0,0 +1,39 @@
+# df <- get_s_curve(2400, n_bands_min = 40, n_rows_per_band_min = 20)
+#' @export
+get_s_curve <- function(number_hashfun,
+                        n_bands_min = 1,
+                        n_rows_per_band_min = 1,
+                        s = seq(0.5, 1, 0.01),
+                        plot = TRUE) {
+
+  bands_number <- divisors(number_hashfun)
+  rows_per_band <- number_hashfun / bands_number
+  i <- bands_number >= n_bands_min & rows_per_band >= n_rows_per_band_min
+
+  bands_number <- bands_number[i]
+  rows_per_band <- rows_per_band[i]
+
+  s_curve <-
+    mapply(function(n_band, n_rows_per_band) {
+      data.table(probability_become_candidate = 1 - (1 - s ^ n_rows_per_band) ^ n_band,
+                 similarity = s,
+                 n_bands = n_band,
+                 n_rows_per_band = n_rows_per_band)
+                 #setup = paste0("bands=", n_band, ";rows_per_band=", n_rows_per_band))
+    }, bands_number, rows_per_band, SIMPLIFY = F) %>%
+      rbindlist
+
+  if (plot) {
+    g <-
+      ggplot(s_curve) +
+        geom_line(aes(x = similarity,
+                      y = probability_become_candidate,
+                      col = interaction(n_bands, n_rows_per_band, sep = " : " ))) +
+        scale_color_discrete("bands_number : rows_per_band")
+    print(g)
+  }
+
+  invisible(s_curve)
+}
+
+

R/utils.R

@@ -7,3 +7,9 @@ split_vector <- function(x, splits) {
   knots = ceiling(seq.int(from = 1, to = length(x) + 1, length.out = splits  + 1))
   mapply(FUN = function(lower, upper) list(c(lower, upper)), knots[-length(knots)], knots[-1] - 1)
 }
+
+divisors <- function(x) {
+  y <- seq_len(x)
+  y <- y[-c(1, length(y))]
+  y[ x %% y == 0 ]
+}