diff --git a/DESCRIPTION b/DESCRIPTION
index 34279fe..09684ee 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -2,7 +2,7 @@ Package: colourvalues
 Type: Package
 Title: Assigns Colours to Values
 Version: 0.2.1
-Date: 2018-11-07
+Date: 2018-12-18
 Authors@R: c(
     person("David", "Cooley", ,"dcooley@symbolix.com.au", role = c("aut", "cre"))
     )
diff --git a/NAMESPACE b/NAMESPACE
index 94bcd27..4ad3fcb 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -29,15 +29,6 @@ S3method(convert_colour,numeric)
 S3method(palette_check,character)
 S3method(palette_check,default)
 S3method(palette_check,matrix)
-export(blue2green)
-export(blue2red)
-export(blue2yellow)
-export(blues)
-export(brbg)
-export(bugn)
-export(bupu)
-export(cividis)
-export(cm)
 export(color_palettes)
 export(color_values)
 export(color_values_rgb)
@@ -48,49 +39,6 @@ export(convert_color)
 export(convert_colors)
 export(convert_colour)
 export(convert_colours)
-export(cyan2yellow)
-export(diverge_hcl)
-export(diverge_hsv)
-export(gnbu)
-export(green2red)
-export(greens)
-export(greys)
-export(heat)
-export(heat_hcl)
-export(inferno)
-export(magenta2green)
-export(magma)
-export(matlab_like)
-export(matlab_like2)
-export(oranges)
-export(orrd)
-export(piyg)
-export(plasma)
-export(prgn)
-export(pubu)
-export(pubugn)
-export(puor)
-export(purd)
-export(purples)
-export(rainbow)
-export(rainbow_hcl)
-export(rdbu)
-export(rdgy)
-export(rdpu)
-export(rdylbu)
-export(rdylgn)
-export(reds)
-export(sequential_hcl)
 export(show_colours)
-export(spectral)
-export(terrain)
-export(terrain_hcl)
-export(topo)
-export(viridis)
-export(ygobb)
-export(ylgn)
-export(ylgnbu)
-export(ylorbr)
-export(ylorrd)
 importFrom(Rcpp,sourceCpp)
 useDynLib(colourvalues, .registration = TRUE)
diff --git a/R/palettes.R b/R/palettes.R
index 2b35802..0b9e358 100644
--- a/R/palettes.R
+++ b/R/palettes.R
@@ -63,35 +63,30 @@ show_colours <- function( colours = colour_palettes() ) {
 #'
 #' Data frame of the viridis palette
 #'
-#' @export
 viridis <- function() rcpp_viridis()
 
 #' Inferno
 #'
 #' Data frame of the inferno palette
 #'
-#' @export
 inferno <- function() rcpp_inferno()
 
 #' Plasma
 #'
 #' Data frame of the plasma palette
 #'
-#' @export
 plasma <- function() rcpp_plasma()
 
 #' Magma
 #'
 #' Data frame of the magma palette
 #'
-#' @export
 magma <- function() rcpp_magma()
 
 #' Cividis
 #'
 #' Data frame of the cividis palette
 #'
-#' @export
 cividis <- function() rcpp_cividis()
 
 
@@ -99,325 +94,281 @@ cividis <- function() rcpp_cividis()
 #'
 #' Data frame of the terrain palette
 #'
-#' @export
 terrain <- function() rcpp_terrain()
 
 #' Topo
 #'
 #' Data Frame of the topo palette
 #'
-#' @export
 topo <- function() rcpp_topo()
 
 #' Heat
 #'
 #' Data Frame of the heat palette
 #'
-#' @export
 heat <- function() rcpp_heat()
 
 #' Ylorrd
 #'
 #' Data Frame of the ylorrd palette
 #'
-#' @export
 ylorrd <- function() rcpp_ylorrd()
 
 #' Ylorbr
 #'
 #' Data Frame of the ylorbr palette
 #'
-#' @export
 ylorbr <- function() rcpp_ylorbr()
 
 #' Ylgnbu
 #'
 #' Data Frame of the ylgnbu palette
 #'
-#' @export
 ylgnbu <- function() rcpp_ylgnbu()
 
 #' Ylgn
 #'
 #' Data Frame of the ylgn palette
 #'
-#' @export
 ylgn <- function() rcpp_ylgn()
 
 #' Reds
 #'
 #' Data Frame of the reds palette
 #'
-#' @export
 reds <- function() rcpp_reds()
 
 #' Rdpu
 #'
 #' Data Frame of the rdpu palette
 #'
-#' @export
 rdpu <- function() rcpp_rdpu()
 
 #' Purples
 #'
 #' Data Frame of the purples palette
 #'
-#' @export
 purples <- function() rcpp_purples()
 
 #' Purd
 #'
 #' Data Frame of the purd palette
 #'
-#' @export
 purd <- function() rcpp_purd()
 
 #' Pubugn
 #'
 #' Data Frame of the pubugn palette
 #'
-#' @export
 pubugn <- function() rcpp_pubugn()
 
 #' Pubu
 #'
 #' Data Frame of the pubu palette
 #'
-#' @export
 pubu <- function() rcpp_pubu()
 
 #' Orrd
 #'
 #' Data Frame of the orrd palette
 #'
-#' @export
 orrd <- function() rcpp_orrd()
 
 #' Oranges
 #'
 #' Data Frame of the oranges palette
 #'
-#' @export
 oranges <- function() rcpp_oranges()
 
 #' Greys
 #'
 #' Data Frame of the greys palette
 #'
-#' @export
 greys <- function() rcpp_greys()
 
 #' Greens
 #'
 #' Data Frame of the greens palette
 #'
-#' @export
 greens <- function() rcpp_greens()
 
 #' Gnbu
 #'
 #' Data Frame of the gnbu palette
 #'
-#' @export
 gnbu <- function() rcpp_gnbu()
 
 #' Bupu
 #'
 #' Data Frame of the bupu palette
 #'
-#' @export
 bupu <- function() rcpp_bupu()
 
 #' Bugn
 #'
 #' Data Frame of the bugn palette
 #'
-#' @export
 bugn <- function() rcpp_bugn()
 
 #' Blues
 #'
 #' Data Frame of the blues palette
 #'
-#' @export
 blues <- function() rcpp_blues()
 
 #' Spectral
 #'
 #' Data Frame of the spectral palette
 #'
-#' @export
 spectral <- function() rcpp_spectral()
 
 #' Rdylgn
 #'
 #' Data Frame of the rdylgn palette
 #'
-#' @export
 rdylgn <- function() rcpp_rdylgn()
 
 #' Rdylbu
 #'
 #' Data Frame of the rdylbu palette
 #'
-#' @export
 rdylbu <- function() rcpp_rdylbu()
 
 #' Rdgy
 #'
 #' Data Frame of the rdgy palette
 #'
-#' @export
 rdgy <- function() rcpp_rdgy()
 
 #' Rdbu
 #'
 #' Data Frame of the rdbu palette
 #'
-#' @export
 rdbu <- function() rcpp_rdbu()
 
 #' Puor
 #'
 #' Data Frame of the puor palette
 #'
-#' @export
 puor <- function() rcpp_puor()
 
 #' Prgn
 #'
 #' Data Frame of the prgn palette
 #'
-#' @export
 prgn <- function() rcpp_prgn()
 
 #' Piyg
 #'
 #' Data Frame of the piyg palette
 #'
-#' @export
 piyg <- function() rcpp_piyg()
 
 #' Brbg
 #'
 #' Data Frame of the brbg palette
 #'
-#' @export
 brbg <- function() rcpp_brbg()
 
 #' Cm
 #'
 #' Data Frame of the cm palette
 #'
-#' @export
 cm <- function() rcpp_cm()
+
 #' Rainbow
 #'
 #' Data Frame of the rainbow palette
 #'
-#' @export
 rainbow <- function() rcpp_rainbow()
+
 #' Ygobb
 #'
 #' Data Frame of the ygobb palette
 #'
-#' @export
 ygobb <- function() rcpp_ygobb()
 
 #' Matlab_like2
 #'
 #' Data Frame of the matlab_like2 palette
 #'
-#' @export
 matlab_like2 <- function() rcpp_matlab_like2()
 
 #' Matlab_like
 #'
 #' Data Frame of the matlab_like palette
 #'
-#' @export
 matlab_like <- function() rcpp_matlab_like()
 
 #' Magenta2green
 #'
 #' Data Frame of the magenta2green palette
 #'
-#' @export
 magenta2green <- function() rcpp_magenta2green()
 
 #' Cyan2yellow
 #'
 #' Data Frame of the cyan2yellow palette
 #'
-#' @export
 cyan2yellow <- function() rcpp_cyan2yellow()
 
 #' Blue2yellow
 #'
 #' Data Frame of the blue2yellow palette
 #'
-#' @export
 blue2yellow <- function() rcpp_blue2yellow()
 
 #' Green2red
 #'
 #' Data Frame of the green2red palette
 #'
-#' @export
 green2red <- function() rcpp_green2red()
 
 #' Blue2green
 #'
 #' Data Frame of the blue2green palette
 #'
-#' @export
 blue2green <- function() rcpp_blue2green()
 
 #' Blue2red
 #'
 #' Data Frame of the blue2red palette
 #'
-#' @export
 blue2red <- function() rcpp_blue2red()
 
 #' Diverge_hcl
 #'
 #' Data Frame of the diverge_hcl palette
 #'
-#' @export
 diverge_hcl <- function() rcpp_diverge_hcl()
 
 #' Diverge_hsv
 #'
 #' Data Frame of the diverge_hsv palette
 #'
-#' @export
 diverge_hsv <- function() rcpp_diverge_hsv()
 
 #' Terrain_hcl
 #'
 #' Data Frame of the terrain_hcl palette
 #'
-#' @export
 terrain_hcl <- function() rcpp_terrain_hcl()
 
 #' Heat_hcl
 #'
 #' Data Frame of the heat_hcl palette
 #'
-#' @export
 heat_hcl <- function() rcpp_heat_hcl()
 
 #' Sequential_hcl
 #'
 #' Data Frame of the sequential_hcl palette
 #'
-#' @export
 sequential_hcl <- function() rcpp_sequential_hcl()
 
 #' Rainbow_hcl
 #'
 #' Data Frame of the rainbow_hcl palette
 #'
-#' @export
 rainbow_hcl <- function() rcpp_rainbow_hcl()
+
diff --git a/README.Rmd b/README.Rmd
index fa84fd1..5f8304f 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -108,9 +108,12 @@ Of course!
 #### 256 numbers mapped to a colour
 
 ```{r}
+bar_plot <- function(df) {
+  barplot( height = df[["a"]], col = df[["col"]], border = NA, space = 0, yaxt = 'n')
+}
 df <- data.frame(a = 10, x = 1:256)
 df$col <- colour_values(df$x, palette = "viridis")
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 #### 5000 numbers on a non-linear scale
@@ -118,7 +121,7 @@ barplot(height = df$a, col = df$col, border = NA, space = 0)
 ```{r}
 df <- data.frame(a = 10, x = c((1:5000)**3))
 df$col <- colour_values(df$x, palette = "viridis")
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 #### 1000 random numbers
@@ -126,14 +129,14 @@ barplot(height = df$a, col = df$col, border = NA, space = 0)
 ```{r}
 df <- data.frame(a = 10, x = rnorm(n = 1000))
 df$col <- colour_values(df$x, palette = "inferno")
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 Eurgh!
 
 ```{r}
 df <- df[with(df, order(x)), ]
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 That's better!
@@ -150,7 +153,7 @@ n <- 100
 m <- grDevices::colorRamp(c("red", "green"))( (1:n)/n )
 df <- data.frame(a = 10, x = 1:n)
 df$col <- colour_values(df$x, palette = m)
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 
@@ -162,7 +165,7 @@ Yep. Either supply a single alpha value for all the colours
 ## single alpha value for all colours
 df <- data.frame(a = 10, x = 1:255)
 df$col <- colour_values(df$x, alpha = 50)
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 Or use a vector of values the same length as `x`
@@ -170,7 +173,7 @@ Or use a vector of values the same length as `x`
 ```{r}
 df <- data.frame(a = 10, x = 1:300, y = rep(c(1:50, 50:1), 3) )
 df$col <- colour_values(df$x, alpha = df$y)
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 
@@ -183,7 +186,7 @@ m <- grDevices::colorRamp(c("red", "green"))( (1:n)/n )
 m <- cbind(m, seq(0, 255, length.out = 100))
 df <- data.frame(a = 10, x = 1:n)
 df$col <- colour_values(df$x, palette = m)
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 ## Some of my plotting functions don't support alpha, can I exclude it?
@@ -241,7 +244,7 @@ library(ggplot2)
 library(scales)
 library(viridisLite)
 
-n <- 1e7
+n <- 1e6
 df <- data.frame(x = rnorm(n = n))
 
 m <- microbenchmark(
@@ -263,7 +266,7 @@ library(ggplot2)
 library(scales)
 library(viridisLite)
 
-n <- 1e6
+n <- 5e5
 x <- sample(x = letters, size = n, replace = TRUE)
 df <- data.frame(x = x)
 
diff --git a/README.md b/README.md
index da2b82e..c1f3667 100644
--- a/README.md
+++ b/README.md
@@ -109,9 +109,12 @@ Of course\!
 #### 256 numbers mapped to a colour
 
 ``` r
+bar_plot <- function(df) {
+  barplot( height = df[["a"]], col = df[["col"]], border = NA, space = 0, yaxt = 'n')
+}
 df <- data.frame(a = 10, x = 1:256)
 df$col <- colour_values(df$x, palette = "viridis")
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 <img src="man/figures/README-unnamed-chunk-3-1.png" width="100%" height="200" />
@@ -121,7 +124,7 @@ barplot(height = df$a, col = df$col, border = NA, space = 0)
 ``` r
 df <- data.frame(a = 10, x = c((1:5000)**3))
 df$col <- colour_values(df$x, palette = "viridis")
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 <img src="man/figures/README-unnamed-chunk-4-1.png" width="100%" height="200" />
@@ -131,7 +134,7 @@ barplot(height = df$a, col = df$col, border = NA, space = 0)
 ``` r
 df <- data.frame(a = 10, x = rnorm(n = 1000))
 df$col <- colour_values(df$x, palette = "inferno")
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 <img src="man/figures/README-unnamed-chunk-5-1.png" width="100%" height="200" />
@@ -140,7 +143,7 @@ Eurgh\!
 
 ``` r
 df <- df[with(df, order(x)), ]
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 <img src="man/figures/README-unnamed-chunk-6-1.png" width="100%" height="200" />
@@ -159,7 +162,7 @@ n <- 100
 m <- grDevices::colorRamp(c("red", "green"))( (1:n)/n )
 df <- data.frame(a = 10, x = 1:n)
 df$col <- colour_values(df$x, palette = m)
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 <img src="man/figures/README-unnamed-chunk-7-1.png" width="100%" height="200" />
@@ -172,7 +175,7 @@ Yep. Either supply a single alpha value for all the colours
 ## single alpha value for all colours
 df <- data.frame(a = 10, x = 1:255)
 df$col <- colour_values(df$x, alpha = 50)
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 <img src="man/figures/README-unnamed-chunk-8-1.png" width="100%" height="200" />
@@ -182,7 +185,7 @@ Or use a vector of values the same length as `x`
 ``` r
 df <- data.frame(a = 10, x = 1:300, y = rep(c(1:50, 50:1), 3) )
 df$col <- colour_values(df$x, alpha = df$y)
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 <img src="man/figures/README-unnamed-chunk-9-1.png" width="100%" height="200" />
@@ -196,7 +199,7 @@ m <- grDevices::colorRamp(c("red", "green"))( (1:n)/n )
 m <- cbind(m, seq(0, 255, length.out = 100))
 df <- data.frame(a = 10, x = 1:n)
 df$col <- colour_values(df$x, palette = m)
-barplot(height = df$a, col = df$col, border = NA, space = 0)
+bar_plot( df )
 ```
 
 <img src="man/figures/README-unnamed-chunk-10-1.png" width="100%" height="200" />
@@ -241,11 +244,11 @@ summary
 ``` r
 colour_values(rnorm(n = 10), n_summaries = 3, digits = 2)
 # $colours
-#  [1] "#20918CFF" "#98D83EFF" "#26838EFF" "#B3DD2CFF" "#B3DD2DFF"
-#  [6] "#2C738EFF" "#FDE725FF" "#355E8DFF" "#B7DE2AFF" "#440154FF"
+#  [1] "#49C16EFF" "#31668EFF" "#20938CFF" "#54C568FF" "#FDE725FF"
+#  [6] "#440154FF" "#F6E61FFF" "#47C06FFF" "#1F998AFF" "#38578CFF"
 # 
 # $summary_values
-# [1] "-2.76" "-1.17" "0.41" 
+# [1] "-1.55" "0.11"  "1.77" 
 # 
 # $summary_colours
 # [1] "#440154FF" "#21908CFF" "#FDE725FF"
@@ -295,27 +298,26 @@ values, and their associated colours
 ``` r
 colour_values(sample(letters, size = 50, replace = T), summary = T)
 # $colours
-#  [1] "#440154FF" "#31688EFF" "#C7E020FF" "#481F71FF" "#FDE725FF"
-#  [6] "#472D7BFF" "#472D7BFF" "#3B528BFF" "#471163FF" "#E3E418FF"
-# [11] "#8FD744FF" "#E3E418FF" "#472D7BFF" "#2C728EFF" "#20A486FF"
-# [16] "#ABDC32FF" "#2C728EFF" "#24868EFF" "#35B779FF" "#28AE80FF"
-# [21] "#ABDC32FF" "#E3E418FF" "#24868EFF" "#31688EFF" "#47C06FFF"
-# [26] "#20A486FF" "#404688FF" "#24868EFF" "#28AE80FF" "#443A83FF"
-# [31] "#47C06FFF" "#3B528BFF" "#75D054FF" "#404688FF" "#404688FF"
-# [36] "#481F71FF" "#287C8EFF" "#20A486FF" "#5DC963FF" "#ABDC32FF"
-# [41] "#1F9A8AFF" "#443A83FF" "#355D8DFF" "#28AE80FF" "#E3E418FF"
-# [46] "#28AE80FF" "#8FD744FF" "#21908CFF" "#28AE80FF" "#8FD744FF"
+#  [1] "#481567FF" "#453781FF" "#73D055FF" "#404788FF" "#29AF7FFF"
+#  [6] "#238A8DFF" "#29AF7FFF" "#1F968BFF" "#95D840FF" "#482677FF"
+# [11] "#3CBB75FF" "#FDE725FF" "#238A8DFF" "#39568CFF" "#95D840FF"
+# [16] "#39568CFF" "#DCE319FF" "#73D055FF" "#440154FF" "#FDE725FF"
+# [21] "#238A8DFF" "#1F968BFF" "#B8DE29FF" "#39568CFF" "#95D840FF"
+# [26] "#440154FF" "#95D840FF" "#33638DFF" "#404788FF" "#453781FF"
+# [31] "#287D8EFF" "#33638DFF" "#FDE725FF" "#2D708EFF" "#55C667FF"
+# [36] "#2D708EFF" "#404788FF" "#482677FF" "#2D708EFF" "#B8DE29FF"
+# [41] "#95D840FF" "#1F968BFF" "#20A387FF" "#20A387FF" "#482677FF"
+# [46] "#287D8EFF" "#453781FF" "#404788FF" "#39568CFF" "#20A387FF"
 # 
 # $summary_values
-#  [1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "m" "n" "o" "p" "q" "r"
-# [18] "s" "t" "u" "v" "w" "x" "y" "z"
+#  [1] "a" "b" "e" "f" "g" "h" "i" "j" "l" "m" "n" "o" "q" "r" "s" "u" "w"
+# [18] "x" "y" "z"
 # 
 # $summary_colours
-#  [1] "#440154FF" "#471163FF" "#481F71FF" "#472D7BFF" "#443A83FF"
-#  [6] "#404688FF" "#3B528BFF" "#355D8DFF" "#31688EFF" "#2C728EFF"
-# [11] "#287C8EFF" "#24868EFF" "#21908CFF" "#1F9A8AFF" "#20A486FF"
-# [16] "#28AE80FF" "#35B779FF" "#47C06FFF" "#5DC963FF" "#75D054FF"
-# [21] "#8FD744FF" "#ABDC32FF" "#C7E020FF" "#E3E418FF" "#FDE725FF"
+#  [1] "#440154FF" "#481567FF" "#482677FF" "#453781FF" "#404788FF"
+#  [6] "#39568CFF" "#33638DFF" "#2D708EFF" "#287D8EFF" "#238A8DFF"
+# [11] "#1F968BFF" "#20A387FF" "#29AF7FFF" "#3CBB75FF" "#55C667FF"
+# [16] "#73D055FF" "#95D840FF" "#B8DE29FF" "#DCE319FF" "#FDE725FF"
 ```
 
 -----
@@ -329,13 +331,8 @@ library(microbenchmark)
 library(ggplot2)
 library(scales)
 library(viridisLite)
-# 
-# Attaching package: 'viridisLite'
-# The following objects are masked from 'package:colourvalues':
-# 
-#     cividis, inferno, magma, plasma, viridis
 
-n <- 1e7
+n <- 1e6
 df <- data.frame(x = rnorm(n = n))
 
 m <- microbenchmark(
@@ -344,10 +341,13 @@ m <- microbenchmark(
   times = 25
 )
 m
-# Unit: seconds
-#          expr      min       lq     mean   median       uq      max neval
-#  colourvalues 1.617392 1.650307 1.707740 1.688513 1.757597 1.866051    25
-#        scales 2.772918 2.889632 2.958089 2.922623 3.016068 3.344712    25
+# Unit: milliseconds
+#          expr      min       lq     mean    median        uq      max
+#  colourvalues 413.7846 465.2459  667.549  533.3406  775.9402 1768.377
+#        scales 865.6236 985.3206 1476.348 1357.1543 2078.2787 2857.309
+#  neval
+#     25
+#     25
 
 autoplot(m)
 # Coordinate system already present. Adding new coordinate system, which will replace the existing one.
@@ -363,7 +363,7 @@ library(ggplot2)
 library(scales)
 library(viridisLite)
 
-n <- 1e6
+n <- 5e5
 x <- sample(x = letters, size = n, replace = TRUE)
 df <- data.frame(x = x)
 
@@ -375,8 +375,8 @@ m <- microbenchmark(
 m
 # Unit: milliseconds
 #          expr      min       lq     mean   median       uq      max neval
-#  colourvalues 183.6266 191.3288 196.3723 192.1881 192.8737 304.3512    25
-#        scales 288.9669 311.4043 320.7450 313.7732 318.0472 378.1733    25
+#  colourvalues 219.6011 251.1079 281.4803 257.8884 268.8997 457.7094    25
+#        scales 392.0473 418.4014 536.5625 453.4664 566.0392 999.5088    25
 
 autoplot(m)
 # Coordinate system already present. Adding new coordinate system, which will replace the existing one.
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