-
Notifications
You must be signed in to change notification settings - Fork 0
/
day20.R
527 lines (460 loc) · 14.9 KB
/
day20.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
library(magrittr)
test_input <- c(
"Tile 2311:",
"..##.#..#.",
"##..#.....",
"#...##..#.",
"####.#...#",
"##.##.###.",
"##...#.###",
".#.#.#..##",
"..#....#..",
"###...#.#.",
"..###..###",
"",
"Tile 1951:",
"#.##...##.",
"#.####...#",
".....#..##",
"#...######",
".##.#....#",
".###.#####",
"###.##.##.",
".###....#.",
"..#.#..#.#",
"#...##.#..",
"",
"Tile 1171:",
"####...##.",
"#..##.#..#",
"##.#..#.#.",
".###.####.",
"..###.####",
".##....##.",
".#...####.",
"#.##.####.",
"####..#...",
".....##...",
"",
"Tile 1427:",
"###.##.#..",
".#..#.##..",
".#.##.#..#",
"#.#.#.##.#",
"....#...##",
"...##..##.",
"...#.#####",
".#.####.#.",
"..#..###.#",
"..##.#..#.",
"",
"Tile 1489:",
"##.#.#....",
"..##...#..",
".##..##...",
"..#...#...",
"#####...#.",
"#..#.#.#.#",
"...#.#.#..",
"##.#...##.",
"..##.##.##",
"###.##.#..",
"",
"Tile 2473:",
"#....####.",
"#..#.##...",
"#.##..#...",
"######.#.#",
".#...#.#.#",
".#########",
".###.#..#.",
"########.#",
"##...##.#.",
"..###.#.#.",
"",
"Tile 2971:",
"..#.#....#",
"#...###...",
"#.#.###...",
"##.##..#..",
".#####..##",
".#..####.#",
"#..#.#..#.",
"..####.###",
"..#.#.###.",
"...#.#.#.#",
"",
"Tile 2729:",
"...#.#.#.#",
"####.#....",
"..#.#.....",
"....#..#.#",
".##..##.#.",
".#.####...",
"####.#.#..",
"##.####...",
"##..#.##..",
"#.##...##.",
"",
"Tile 3079:",
"#.#.#####.",
".#..######",
"..#.......",
"######....",
"####.#..#.",
".#...#.##.",
"#.#####.##",
"..#.###...",
"..#.......",
"..#.###..."
)
real_input <- readLines("./inputs/day20-input.txt")
#- LOGIC ----------------------------------------------------------------------#
monster_text <-
c(
" # ",
"# ## ## ###",
" # # # # # # "
)
parse_monster_text <- function(monster_text) {
monster_text %>%
strsplit(split = "") %>%
unlist() %>%
matrix(nrow = length(monster_text), byrow = T)
}
#' produces list of tiles every element of each is an object with properties
#' id: number
#' content: [character]
#' orientation:
#' flipped: logical
#' turned: integer (from 0 to 3, shows rotation by 90 degree counterclockwise)
parse_input <- function(input) {
input <- input[input != ""]
g <-
input %>%
Reduce(f = function(z,x) {
z + grepl("^Tile \\d+:$", x)
}, accumulate = T, init = 0) %>%
magrittr::extract(-1)
input_split <-
input %>%
split(g) %>%
Map(f = function(x) {
first_line <- x[1]
tile_content <- x[-1]
id <- first_line %>%
gregexpr(pattern = "\\d+") %>%
regmatches(x = first_line) %>%
magrittr::extract2(1) %>%
as.integer()
content <- {
rows <- length(tile_content)
cols <- nchar(tile_content[1])
tile_content %>%
strsplit(split = "") %>%
unlist() %>%
matrix(rows, cols, byrow = T)
}
list(id = id, content = content, flipped = FALSE, turned = 0, type = "tile")
})
}
## TILE MODIFIERS
flip <- function(m) m %>% apply(2, rev)
turn <- function(m) m %>% apply(2, rev) %>% t()
#' flip rows: 1st row becomes last and last row becomes 1st
flip_tile <- function(tile) {
tile %>%
magrittr::inset2("flipped", xor(tile$flipped, TRUE)) %>%
magrittr::inset2("content", flip(tile$content))
}
turn_tile <- function(tile) {
tile %>%
magrittr::inset2("turned", (tile$turned + 1) %% 4) %>%
magrittr::inset2("content", turn(tile$content))
}
## TILE PROPERTIES
#' returns tile borders, based on tile content and orientation
#' object with properties
#' top: [character]
#' bottom: [character]
#' left: [character]
#' right: [character]
tile_borders <- function(tile) {
content <- tile$content
rows <- nrow(content)
cols <- ncol(content)
list(
top = content[1, 1:cols],
bottom = content[rows, 1:cols],
left = content[1:rows, 1],
right = content[1:rows, cols]
)
}
## FIELD
#' empty field with no tiles
empty_field <- list()
#' convert position coordinates into text for field element names
position_to_txt <- function(position) {
paste0("(", position[1], ",", position[2], ")")
}
#' function adds tile to the given position (c(x,y)) of the field and returns new field including added tile
#' if tile is occupied then function raises an error
place_tile_on_field <- function(field, position, tile_or_outer) {
field %>%
magrittr::inset2(
position_to_txt(position),
tile_or_outer %>% magrittr::inset2("position", position)
)
}
#' read tile information from the position on the field
read_tile_on_field <- function(field, position) {
field %>% magrittr::extract2(position_to_txt(position))
}
#' returns list of neighbor positions for a given position
field_position_neighbor_positions <- function(field, position) {
list(right = c(1,0), top = c(0,1), left = c(-1,0), bottom = c(0,-1)) %>%
Map(f = function(x) x + position)
}
#' check whether given position on the field is empty
field_position_is_empty <- function(field, position) {
pos_txt <- position_to_txt(position)
is.null(field[[pos_txt]])
}
#' check whether given position on the field filled with tile
field_position_is_tile <- function(field, position) {
pos_txt <- position_to_txt(position)
!is.null(field[[pos_txt]]) && field[[pos_txt]][["type"]] == "tile"
}
#' function that returns constraints in form of tile borders for a given position in the field
#' if there are no adjacent tiles on a side then side is not included into result.
#' for example if position has adjacent tiles only on left and bottom sides, function will return list(left = ..., bottom = ...)
field_position_constraints <- function(field, position) {
# named vector of sides around the position
mirror <- c(right = "left", left = "right", top = "bottom", bottom = "top")
# find surrounding tiles on the field
neighbor_tiles <-
field_position_neighbor_positions(field, position) %>%
Filter(f = function(x) field_position_is_tile(field, x)) %>%
Map(f = function(x) field %>% read_tile_on_field(x))
# take only adjucent borders of surrounding tiles (bottom border for upper tile, etc.)
names(neighbor_tiles) %>%
Map(f = function(relative_position_name) {
tile_borders(neighbor_tiles[[relative_position_name]]) %>%
magrittr::extract2(mirror[relative_position_name])
})
}
#' check whether tile conforms given all constraints
tile_conforms_contraints <- function(tile, constraints) {
borders <- tile_borders(tile)
names(constraints) %>%
Map(f = function(side) constraints[[side]] == borders[[side]]) %>%
Reduce(f = all, init = TRUE)
}
## TILE SEARCH
#' function takes all free tiles and constraints and returns
#' properly oriented tile with MODIFIED orientation that conforms constraints
find_tile_given_constraints <- function(constraints, tiles) {
# check tile with under different angles, flip it, check it again
orient_funs <- c(
# turn tile 3 times to make a full round (we will start with angle 0 and
# fold function will accumulate prior results)
# so: initial is no-flip & 0 deg, then 90, 180, 270 deg
turn_tile, turn_tile, turn_tile,
# turn tile to 0 degree angle and flip it
# so: we continue with flip & 0 deg, then 90, 180, 270 deg
function(x) x %>% turn_tile() %>% flip_tile(),
# turn flipped tile 3 more times
turn_tile, turn_tile, turn_tile
)
tiles_megaset <-
tiles %>%
Reduce(f = function(z, tile) {
tile_orientations <-
orient_funs %>%
Reduce(f = function(z, orient) orient(z),
init = tile, accumulate = T
)
c(z, tile_orientations)
}, init = list())
found <- tiles_megaset %>%
# this approach is bad because we do not see how tile must be oriented
Filter(f = function(tile) tile_conforms_contraints(tile, constraints))
if (length(found) == 0) NULL else found[[1]]
}
#' given field with placed elements and list of tiles - filter out tiles which
#' are already placed on the field (based on their id)
find_lose_tiles <- function(field, tiles) {
used_tile_ids <- field %>%
Map(f = function(x) x$position) %>%
Filter(f = function(x) field_position_is_tile(field, x)) %>%
Map(f = function(x) read_tile_on_field(field, x)$id) %>%
Reduce(f = c)
tiles %>%
Filter(f = function(x) (x$id %in% used_tile_ids) == FALSE)
}
#' find tile for a given position
find_tile_given_position <- function(field, position, lose_tiles) {
current_tile <- field %>% read_tile_on_field(position)
if (!is.null(current_tile)) current_tile
else {
found <-
field %>%
field_position_constraints(position) %>%
find_tile_given_constraints(lose_tiles)
if (is.null(found)) list(type = "outer space", position = position)
else found
}
}
#' function that recursively calls itself to populate field with tiles
#' if field is empty
#' function will take random tile and place it into
#' position (0, 0), then function will call itself
#' if field is not empty
#' function will find empty neighbors of tiled fields and search for
#' matching tile among available tiles applying constraints from tiles
#' which are already placed on the field (also considering their orientation)
fill_field_with_tiles <- function(field = NULL, tiles) {
if (length(tiles) == 0) field
else if (is.null(field) | length(field) == 0) {
init_position <- c(0,0)
first_tile <- tiles[[1]]
field <- empty_field %>% place_tile_on_field(init_position, first_tile)
remaining_tiles <- find_lose_tiles(field, tiles)
fill_field_with_tiles(field, remaining_tiles)
} else {
empty_neighor_positions <- field %>%
Map(f = function(x) x$position) %>%
Filter(f = function(x) field_position_is_tile(field, x)) %>%
Map(f = function(x) read_tile_on_field(field, x)) %>%
Map(f = function(tile) {
field_position_neighbor_positions(field, tile$position)
}) %>%
Reduce(f = c, init = list()) %>%
Filter(f = function(position) field_position_is_empty(field, position))
if (length(empty_neighor_positions) == 0) stop(paste(
"unexpected termination:",
"no empty positions on field while tiles are available"))
position <- empty_neighor_positions[[1]]
new_field <-
field %>%
find_tile_given_position(position, tiles) %>%
place_tile_on_field(field, tile_or_outer = ., position)
remaining_tiles <- find_lose_tiles(new_field, tiles)
fill_field_with_tiles(new_field, remaining_tiles)
}
}
#' simply show positions of tiles on the field
plot_field <- function(field) {
x <- field %>% Map(f = function(x) x$position[1]) %>% Reduce(f = c)
y <- field %>% Map(f = function(x) x$position[2]) %>% Reduce(f = c)
labels <- field %>% Map(f = function(x) x$type == "tile") %>% Reduce(f = c)
plot(x, y, pch = labels)
}
field_as_tile_id_matrix <- function(field) {
tile_ids <-
field %>%
Filter(f = function(x) x$type == "tile") %>%
Map(f = function(tile) with(tile, list(id = id, x = position[1], y = position[2]))) %>%
Reduce(f = rbind, init = data.frame(id = integer(), x = integer(), y = integer()))
cols <- max(tile_ids$x) - min(tile_ids$x) + 1
rows <- max(tile_ids$y) - min(tile_ids$y) + 1
ids <- tile_ids[order(tile_ids$x, tile_ids$y), "id"]
mx <- matrix(data = ids, nrow = rows, ncol = cols, byrow = F)
mx
}
#' compose image using field data
field_to_image <- function(field) {
tile_matrix <- field_as_tile_id_matrix(field)
extract_tile_content <- function(tile_id) {
field %>%
Filter(f = function(x) x$type == "tile") %>%
Filter(f = function(tile) tile$id == tile_id) %>%
magrittr::extract2(1) %>%
magrittr::extract2("content")
}
image_dim <- tile_matrix[1,1] %>% extract_tile_content() %>% dim()
1:nrow(tile_matrix) %>%
# extract all images in a field row and combine them into one wide matrix
Map(f = function(row) {
tile_matrix[row,] %>%
Map(f = extract_tile_content) %>%
Map(f = function(content) {
content[2:(image_dim[1] - 1), 2:(image_dim[2] - 1)]
}) %>%
Reduce(f = cbind)
}) %>%
# combine list of wide matrices into one tall and wide matrix
# but higher number rows must go up!
Reduce(f = function(z, x) rbind(x, z))
}
#' check whether specific part of image contains monster. frame must be of the
#' same size as a monster
image_frame_contains_monster <- function(image_frame, monster_pattern) {
monster_pattern_bool <- monster_pattern == "#"
image_frame_bool <- image_frame == "#"
# monster pattern should fully present on image
all((image_frame_bool & monster_pattern_bool) == monster_pattern_bool)
}
#' scan image and count monsters
count_monsters_on_image <- function(image, monster_pattern) {
wi <- ncol(image)
hi <- nrow(image)
wm <- ncol(monster_pattern)
hm <- nrow(monster_pattern)
z <- 0
for (x in 0:(wi-wm)) for (y in 0:(hi-hm)) {
image_frame <- image[(y+1):(y+hm), (x+1):(x+wm)]
z <- z + image_frame_contains_monster(image_frame, monster_pattern)
}
z
}
#' find monsters
find_all_monsters <- function(image, monster_pattern) {
# check tile with under different angles, flip it, check it again
orient_funs <- c(
turn, turn, turn,
function(x) x %>% turn() %>% flip(),
turn, turn, turn
)
orient_funs %>%
Reduce(f = function(img, fun) fun(img), init = image, accumulate = T) %>%
Map(f = function(image) count_monsters_on_image(image, monster_pattern)) %>%
Reduce(f = max)
}
#- SOLUTION PART 1 ------------------------------------------------------------#
day20_part1_solution <- function(input) {
tiles <- input %>% parse_input()
field <- empty_field %>% fill_field_with_tiles(tiles)
m <- field_as_tile_id_matrix(field)
print(m)
matrix_corners <- function(mx) {
cols <- ncol(mx)
rows <- nrow(mx)
c(mx[1,1], mx[1,cols], mx[rows,1], mx[rows, cols])
}
m %>% matrix_corners() %>% as.double() %>% prod()
}
test_output_part1 <- 20899048083289
test_result <- day20_part1_solution(test_input)
print(paste(
"test result:", test_result,
"valid:", test_result == test_output_part1))
real_result_part1 <- day20_part1_solution(real_input)
print(format(real_result_part1, scientific = FALSE))
#- SOLUTION PART 2 ------------------------------------------------------------#
day20_part2_solution <- function(input) {
tiles <- input %>% parse_input()
field <- empty_field %>% fill_field_with_tiles(tiles)
image <- field_to_image(field)
monster_pattern <- monster_text %>% parse_monster_text()
monsters_count <- image %>% find_all_monsters(monster_pattern)
roughness <- sum(image == "#") - sum(monster_pattern == "#") * monsters_count
roughness
}
test_output_part2 <- 273
test_result <- day20_part2_solution(test_input)
print(paste(
"test result:", test_result,
"valid:", test_result == test_output_part2))
real_result_part2 <- day20_part2_solution(real_input)
print(format(real_result_part2, scientific = FALSE))