├── .gitignore
├── README.md
├── images
    ├── rstudio_01.png
    └── rstudio_02.png
├── rstudiopostcard.Rproj
└── source
    ├── rstudio_01.R
    ├── rstudio_02.R
    └── stepping_stone.cpp


/.gitignore:
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1 | .Rhistory
2 | .RData
3 | .Rproj.user
4 | 


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/README.md:
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1 | 
2 | # RStudio postcard
3 | 
4 | <img src="./images/rstudio_01.png" width = 400> &nbsp;&nbsp; <img src="./images/rstudio_02.png" width = 400>
5 | 
6 | 


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/images/rstudio_01.png:
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https://raw.githubusercontent.com/djnavarro/rstudiopostcard/6e866a21179c1f64b7d57c44a5140dfd189df1d2/images/rstudio_01.png


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/images/rstudio_02.png:
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https://raw.githubusercontent.com/djnavarro/rstudiopostcard/6e866a21179c1f64b7d57c44a5140dfd189df1d2/images/rstudio_02.png


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/rstudiopostcard.Rproj:
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 1 | Version: 1.0
 2 | 
 3 | RestoreWorkspace: Default
 4 | SaveWorkspace: Default
 5 | AlwaysSaveHistory: Default
 6 | 
 7 | EnableCodeIndexing: Yes
 8 | UseSpacesForTab: Yes
 9 | NumSpacesForTab: 2
10 | Encoding: UTF-8
11 | 
12 | RnwWeave: Sweave
13 | LaTeX: pdfLaTeX
14 | 


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/source/rstudio_01.R:
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  1 | 
  2 | library(Rcpp)
  3 | library(tidyverse)
  4 | library(ambient)
  5 | library(flametree)  
  6 | library(ggforce)  
  7 | library(paletteer)
  8 | library(here)
  9 | 
 10 | sourceCpp(here("source", "stepping_stone.cpp")) 
 11 | output <- here("images", "rstudio_01.png")
 12 | 
 13 | 
 14 | # generate stepping stone background --------------------------------------
 15 | 
 16 | cat("generating image...\n")
 17 | 
 18 | # parameters
 19 | seed_ss <- 339
 20 | shades <- 1000
 21 | grains_wide <- 500
 22 | grains_high <- 750
 23 | 
 24 | palette <- paletteer_c(
 25 |   palette = "ggthemes::Classic Blue", 
 26 |   n = shades
 27 | )
 28 | 
 29 | # seed for RNG
 30 | set.seed(seed_ss)
 31 | 
 32 | # create long grid for the raster with appropriate aspect ratio
 33 | ar <- grains_high / grains_wide
 34 | raster <- long_grid(
 35 |   x = seq(0, 1,  length.out = grains_wide), 
 36 |   y = seq(0, ar, length.out = grains_high)
 37 | )
 38 | 
 39 | # initialise raster using worley noise
 40 | raster$base <- fracture(
 41 |   noise = gen_worley,
 42 |   fractal = fbm,
 43 |   octaves = 5, 
 44 |   frequency = 3,
 45 |   value = "distance2",
 46 |   seed = seed_ss, 
 47 |   x = raster$x,
 48 |   y = raster$y
 49 | ) 
 50 | 
 51 | # convert base raster image to integer index
 52 | raster$base <- as.integer(ceiling(normalise(raster$base) * shades))
 53 | 
 54 | # convert to matrix and run stepping stone automaton
 55 | ss <- matrix(raster$base, grains_wide, grains_high)
 56 | ss <- t(timestep(ss, 200))
 57 | 
 58 | # read colours off the ss matrix 
 59 | raster$shade <- palette[ss]
 60 | 
 61 | 
 62 | 
 63 | 
 64 | 
 65 | # generate flametree ------------------------------------------------------
 66 | 
 67 | seed_ft <- 1
 68 | set.seed(seed_ft)
 69 | 
 70 | # create the tree
 71 | ftree <- flametree_grow(
 72 |   time = 12,
 73 |   seed = seed_ft,
 74 |   angle = c(-2:4) * 10,
 75 |   scale = c(.6, .8, .9)
 76 | )
 77 | 
 78 | # compute aspect ratio of generated tree
 79 | ar2 <- with(ftree, (max(coord_y) - min(coord_y))/(max(coord_x) - min(coord_x)))
 80 | 
 81 | # scale the tree image to fit the postcard
 82 | ftree <- ftree %>%
 83 |   mutate(
 84 |     coord_x = normalise(coord_x, to = range(raster$x)),
 85 |     coord_y = normalise(coord_y, to = range(raster$y))
 86 |   ) %>%
 87 |   mutate(
 88 |     coord_x = coord_x * min(1, ar/ar2), 
 89 |     coord_y = coord_y * min(1, ar2/ar)
 90 |   ) %>% 
 91 |   mutate(
 92 |     coord_x = .045 + coord_x * .9,
 93 |     coord_y = coord_y * .9
 94 |   )
 95 | 
 96 | 
 97 | # "leaf" coordinates are at terminal locations (id_step = 2) 
 98 | # on the terminal branches (id_leaf == TRUE) in the tree
 99 | vleaf <- ftree %>% 
100 |   filter(id_leaf == TRUE, id_step == 2)
101 | 
102 | 
103 | 
104 | 
105 | # generate raindrops ------------------------------------------------------
106 | 
107 | seed_rd <- 1
108 | set.seed(seed_rd)
109 | 
110 | # rain
111 | rain <- expand_grid(
112 |   x = seq(.01, .99, length.out = 50),
113 |   y = seq(.01 * ar, .99 * ar, length.out = round(50 * ar))
114 | ) %>% 
115 |   mutate(droplet = runif(n()) < .1) %>%  
116 |   group_by(x) %>%
117 |   mutate(droplet = droplet | lag(droplet, default = FALSE) | lag(droplet, 2, default = FALSE)) %>%
118 |   ungroup()
119 | 
120 | rain1 <- rain %>%
121 |   filter(droplet == TRUE)
122 |   
123 | rain2 <- rain %>%
124 |   group_by(x) %>%
125 |   filter(droplet, !lag(droplet) | y == min(y)) %>%
126 |   ungroup()
127 | 
128 | 
129 | 
130 | # render the image --------------------------------------------------------
131 | 
132 | cat("rendering image...\n")
133 | 
134 | pic <- ggplot(
135 |   data = raster,
136 |   mapping = aes(x, y, fill = shade)
137 | ) + 
138 |   
139 |   # background is the raster object
140 |   geom_raster() + 
141 |   
142 |   # underlay the rain sparkle
143 |   geom_point(
144 |     data = rain2, 
145 |     mapping = aes(x, y),
146 |     size = 1,
147 |     alpha = 1,
148 |     color = "white",
149 |     show.legend = FALSE,
150 |     inherit.aes = FALSE
151 |   ) +
152 |   
153 |   # add the rain drops
154 |   geom_point(
155 |     data = rain1, 
156 |     mapping = aes(x, y),
157 |     size = .5,
158 |     alpha = 1,
159 |     color = "black",
160 |     show.legend = FALSE,
161 |     inherit.aes = FALSE
162 |   ) +
163 |   
164 |   # tree trunk is drawn using geom_bezier from ggforce
165 |   geom_bezier(
166 |     data = ftree, 
167 |     mapping = aes(
168 |       x = coord_x,
169 |       y = coord_y,
170 |       group = id_path,
171 |       size = .3 + seg_wid * 3
172 |     ), 
173 |     lineend = "round", 
174 |     show.legend = FALSE,
175 |     inherit.aes = FALSE
176 |   ) +
177 |   
178 |   # overlay the leaves
179 |   geom_point(
180 |     data = vleaf,
181 |     mapping = aes(
182 |       x = coord_x,
183 |       y = coord_y
184 |     ),
185 |     size = 1,
186 |     color = "white",
187 |     show.legend = FALSE,
188 |     inherit.aes = FALSE
189 |   ) + 
190 |   
191 |   # plot settings
192 |   scale_fill_identity() + 
193 |   scale_size_identity() + 
194 |   coord_equal() + 
195 |   scale_x_continuous(expand = c(0, 0)) +
196 |   scale_y_continuous(expand = c(0, 0)) +
197 |   theme_void() + 
198 |   NULL
199 | 
200 | # export image
201 | ggsave(
202 |   filename = output,
203 |   plot = pic,
204 |   width = grains_wide / 150,
205 |   height = grains_high / 150,
206 |   dpi = 2400
207 | )
208 | 
209 | 
210 | 
211 | 
212 | 
213 | 


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/source/rstudio_02.R:
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  1 | 
  2 | library(Rcpp)
  3 | library(tidyverse)
  4 | library(ambient)
  5 | library(flametree)
  6 | library(voronoise)
  7 | library(paletteer)
  8 | library(here)
  9 | 
 10 | sourceCpp(here("source", "stepping_stone.cpp")) 
 11 | output <- here("images", "rstudio_02.png")
 12 | 
 13 | 
 14 | # generate stepping stone background --------------------------------------
 15 | 
 16 | cat("generating image...\n")
 17 | 
 18 | # parameters
 19 | seed_ss <- 340
 20 | shades <- 1000
 21 | grains_wide <- 500
 22 | grains_high <- 750
 23 | 
 24 | palette <- paletteer_c(
 25 |   palette = "viridis::magma", 
 26 |   n = shades
 27 | )
 28 | 
 29 | # seed for RNG
 30 | set.seed(seed_ss)
 31 | 
 32 | # create long grid for the raster with appropriate aspect ratio
 33 | ar <- grains_high / grains_wide
 34 | raster <- long_grid(
 35 |   x = seq(0, 1,  length.out = grains_wide), 
 36 |   y = seq(0, ar, length.out = grains_high)
 37 | )
 38 | 
 39 | # initialise raster using worley noise
 40 | raster$base <- fracture(
 41 |   noise = gen_worley,
 42 |   fractal = fbm,
 43 |   octaves = 5, 
 44 |   frequency = 3,
 45 |   value = "distance2",
 46 |   seed = seed_ss, 
 47 |   x = raster$x,
 48 |   y = raster$y
 49 | ) 
 50 | 
 51 | # convert base raster image to integer index
 52 | raster$base <- as.integer(ceiling(normalise(raster$base) * shades))
 53 | 
 54 | # convert to matrix and run stepping stone automaton
 55 | ss <- matrix(raster$base, grains_wide, grains_high)
 56 | ss <- t(timestep(ss, 200))
 57 | 
 58 | # read colours off the ss matrix 
 59 | raster$shade <- palette[ss]
 60 | 
 61 | 
 62 | 
 63 | # generate flametree ------------------------------------------------------
 64 | 
 65 | seed_ft <- 1
 66 | set.seed(seed_ft)
 67 | 
 68 | # the "flametree" itself
 69 | ftree <- flametree_grow(
 70 |   time = 10,
 71 |   seed = seed_ft,
 72 |   angle = c(-2:4) * 10,
 73 |   scale = c(.6, .8, .9)
 74 | )
 75 | 
 76 | # compute aspect ratio of generated tree
 77 | ar2 <- with(ftree, (max(coord_y) - min(coord_y))/(max(coord_x) - min(coord_x)))
 78 | 
 79 | # scale the tree image to fit the postcard
 80 | ftree <- ftree %>%
 81 |   mutate(
 82 |     coord_x = normalise(coord_x, to = range(raster$x)),
 83 |     coord_y = normalise(coord_y, to = range(raster$y))
 84 |   ) %>%
 85 |   mutate(
 86 |     coord_x = coord_x * min(1, ar/ar2), 
 87 |     coord_y = coord_y * min(1, ar2/ar)
 88 |   ) %>% 
 89 |   mutate(
 90 |     coord_x = .075 + coord_x * .85,
 91 |     coord_y = coord_y * 1.05
 92 |   )
 93 | 
 94 | # "leaf" coordinates are at terminal locations (id_step = 2) 
 95 | # on the terminal branches (id_leaf == TRUE) in the tree
 96 | vleaf <- ftree %>% 
 97 |   filter(id_leaf == TRUE, id_step == 2) %>%
 98 |   sample_frac(.7)
 99 | 
100 | 
101 | # render the image --------------------------------------------------------
102 | 
103 | cat("rendering image...\n")
104 | 
105 | pic <- ggplot(
106 |   data = raster,
107 |   mapping = aes(x, y, fill = shade)
108 | ) + 
109 |   
110 |   # the raster object forms the background
111 |   geom_raster() + 
112 |   
113 |   # tree trunk is drawn using geom_bezier from the 
114 |   # ggforce package (loaded by voronoise)
115 |   geom_bezier(
116 |     data = ftree, 
117 |     mapping = aes(
118 |       x = coord_x,
119 |       y = coord_y,
120 |       group = id_path,
121 |       size = .2 + seg_wid * 3
122 |     ), 
123 |     lineend = "round", 
124 |     colour = "white",
125 |     alpha = .5,
126 |     show.legend = FALSE,
127 |     inherit.aes = FALSE
128 |   ) +
129 |   
130 |   # leaves generated using the voronoise package (in this instance
131 |   # it's more or less identical to geom_voronoi_tile)
132 |   geom_voronoise(
133 |     data = vleaf,
134 |     mapping = aes(
135 |       x = coord_x,
136 |       y = coord_y
137 |     ),
138 |     expand = -.0005,
139 |     radius = 0,
140 |     max.radius = .02,
141 |     size = 2,
142 |     alpha = 1,
143 |     fill = "white",
144 |     show.legend = FALSE,
145 |     inherit.aes = FALSE
146 |   ) + 
147 |   
148 |   # add the marginal distributions
149 |   geom_rug(
150 |     data = vleaf,
151 |     mapping = aes(
152 |       x = coord_x,
153 |       y = coord_y
154 |     ),
155 |     length = unit(3, "mm"),
156 |     sides = "bl",
157 |     size = .1,
158 |     alpha = .4, 
159 |     color = "white",
160 |     show.legend = FALSE,
161 |     inherit.aes = FALSE
162 |   ) + 
163 |   
164 |   # bunch of settings...
165 |   scale_fill_identity() + 
166 |   scale_size_identity() + 
167 |   coord_equal() + 
168 |   scale_x_continuous(expand = c(0, 0)) +
169 |   scale_y_continuous(expand = c(0, 0)) +
170 |   theme_void() + 
171 |   NULL
172 | 
173 | # export image
174 | ggsave(
175 |   filename = output,
176 |   plot = pic,
177 |   width = grains_wide / 150,
178 |   height = grains_high / 150,
179 |   dpi = 2400
180 | )
181 | 


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/source/stepping_stone.cpp:
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 1 | #include<Rcpp.h>
 2 | using namespace Rcpp;
 3 | 
 4 | // [[Rcpp::export]]
 5 | IntegerMatrix timestep(IntegerMatrix x, int iter) {
 6 |   
 7 |   // size of the matrix
 8 |   int nrow = x.nrow();
 9 |   int ncol = x.ncol();
10 |   
11 |   // indexing and weighting variables
12 |   double wt;
13 |   int rind;
14 |   int cind;
15 |   int rstp;
16 |   int cstp;
17 |   
18 |   for(int i = 0; i < iter; i++) {
19 |     for(int r = 0; r < nrow; r++) {
20 |       for(int c = 0; c < ncol; c++) {
21 |         
22 |           // sample from binomial distributions
23 |           rstp = R::rbinom(4, 0.5);
24 |           cstp = R::rbinom(4, 0.5);
25 |           
26 |           // find corresponding indices
27 |           rind = r + rstp - 2;
28 |           cind = c + cstp - 2;
29 |           
30 |           // truncate at the boundaries
31 |           if(rind < 0) {rind = 0;}
32 |           if(cind < 0) {cind = 0;}
33 |           if(rind >= nrow) {rind = nrow - 1;}
34 |           if(cind >= ncol) {cind = ncol - 1;}
35 |           
36 |           // replace
37 |           x(r,c) = x(rind, cind);
38 |       }
39 |     }
40 |   }
41 |   
42 |   return x;
43 | }


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