# Euclidean Minimum Spanning Tree Stat Function A Stat extension for 'ggplot2' to plot a 2D MST by making a scatter plot with segments. `stat_MST` uses the information returned by `ComputeMST` for producing a 2D Minimum Spanning Tree plot with 'ggplot2' and should be combined with `geom_point()`. ```r stat_MST( mapping = NULL, data = NULL, geom = "segment", position = "identity", na.rm = FALSE, linetype = "dotted", show.legend = NA, inherit.aes = TRUE, ... ) ``` ## Arguments - `mapping`: The aesthetic mapping, usually constructed with `aes` or `aes_`. The required aesthetics are `x`, `y`, `from`, and `to`. Those are columns of the `mst` object returned by `ComputeMST`. - `data`: a `mst` class object returned by the `ComputeMST` function. - `geom`: The geometric object to display the data. The default value is `"segment"` in order to produce the edges between the vertices. - `position`: The position adjustment to use for overlapping points on this layer - `na.rm`: a logical value indicating whether `NA` values should be stripped before the computation proceeds. - `linetype`: an integer or name: `0 = "blank"`, `1 = "solid"`, `2 = "dashed"`, `3 = "dotted"`, `4 = "dotdash"`, `5 = "longdash"`, `6 = "twodash"`. The default for `'MST'` objects is "dotted". - `show.legend`: logical. Should this layer be included in the legends? `NA`, the default, includes if any aesthetics are mapped. `FALSE` never includes, and `TRUE` always includes. - `inherit.aes`: If `FALSE`, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. `borders`. - `...`: other arguments passed on to `layer`. This can include aesthetics whose values you want to set, not map. See `layer` for more details. ## Computed variables - **x**: x coordinates of the MST start points - **y**: y coordinates of the MST start points - **xend**: x coordinates of the MST end points - **yend**: y coordinates of the MST end points ## Examples ```r ## 2D artificial data: set.seed(1984) n <- 15 c1 <- data.frame(x = rnorm(n, -0.2, sd = 0.2), y = rnorm(n, -2, sd = 0.2)) c2 <- data.frame(x = rnorm(n, -1.1, sd = 0.15), y = rnorm(n, -2, sd = 0.3)) d <- rbind(c1, c2) d <- as.data.frame(d) ## MST: out <- ComputeMST(d) #1) simple plot library(ggplot2) ggplot(data = out, aes(x = x, y = y, from = from, to = to))+ geom_point()+ stat_MST(colour = "red", linetype = 2) #2) curved edges library(ggplot2) ggplot(data = out, aes(x = x, y = y, from = from, to = to))+ geom_point()+ stat_MST(geom = "curve", colour = "red", linetype = 2) ## Not run: ## plotting MST on maps: library(ggmap) #3) honeymoon cruise example # define ports df.port_locations <- data.frame(location = c("Civitavecchia, Italy", "Genova, Italy", "Marseille, France", "Barcelona, Spain", "Tunis, Tunisia", "Palermo, Italy"), stringsAsFactors = FALSE) # get latitude and longitude geo.port_locations <- geocode(df.port_locations$location, source = "dsk") # combine data df.port_locations <- cbind(df.port_locations, geo.port_locations) # MST out <- ComputeMST(df.port_locations[,2:3]) plot(out) #just to check # Plot #' map <- c(left = -8, bottom = 32, right = 20, top = 47) get_stamenmap(map, zoom = 5) %>% ggmap()+ stat_MST(data = out, aes(x = lon, y = lat, from = from, to = to), colour = "red", linetype = 2)+ geom_point(data = out, aes(x = lon, y = lat), size = 3) #4) World Map travels: library(ggplot2) library(ggmaps) country_coords_txt <- " 1 3.00000 28.00000 Algeria 2 54.00000 24.00000 UAE 3 139.75309 35.68536 Japan 4 45.00000 25.00000 'Saudi Arabia' 5 9.00000 34.00000 Tunisia 6 5.75000 52.50000 Netherlands 7 103.80000 1.36667 Singapore 8 124.10000 -8.36667 Korea 9 -2.69531 54.75844 UK 10 34.91155 39.05901 Turkey 11 -113.64258 60.10867 Canada 12 77.00000 20.00000 India 13 25.00000 46.00000 Romania 14 135.00000 -25.00000 Australia 15 10.00000 62.00000 Norway" d <- read.delim(text = country_coords_txt, header = FALSE, quote = "'", sep = "", col.names = c('id', 'lon', 'lat', 'name')) out <- ComputeMST(d[,2:3]) country_shapes <- geom_polygon(aes(x = long, y = lat, group = group), data = map_data('world'), fill = "#CECECE", color = "#515151", size = 0.15) ggplot()+ country_shapes+ stat_MST(geomdata = out, aes(x = lon, y = lat, from = from, to = to), colour = "red", linetype = 2)+ geom_point(data = out, aes(x = lon, y = lat), size=2) ## End(Not run) ```

stat_MST function