Abelian sandpile model: Difference between revisions
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{{libheader|xtensor}} |
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<lang cpp> |
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Revision as of 09:38, 4 November 2019
You are encouraged to solve this task according to the task description, using any language you may know.
| This page uses content from Wikipedia. The original article was at Abelian sandpile model. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance) |
Implement the Abelian sandpile model also known as Bak–Tang–Wiesenfeld model. It's history, mathematical definition and properties can be found under it's wikipedia article.
The task requires the creation of a 2D grid of arbitrary size on which "piles of sand" can be placed. Any "pile" that has 4 or more sand particles on it collapses, resulting in four particles being subtracted from the pile and distributed among it's neighbors.
It is recommended to display the output in some kind of image format, as terminal emulators are usually too small to display images larger than a few dozen characters tall. As an example of how to accomplish this, see the Bitmap/Write a PPM file task.
Examples:
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 4 0 0 -> 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 6 0 0 -> 0 1 2 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 1 2 0 0 0 16 0 0 -> 1 1 0 1 1 0 0 0 0 0 0 2 1 2 0 0 0 0 0 0 0 0 1 0 0
C++
<lang cpp>
- include <iostream>
- include "xtensor/xarray.hpp"
- include "xtensor/xio.hpp"
- include "xtensor-io/ximage.hpp"
xt::xarray<int> init_grid (unsigned long x_dim, unsigned long y_dim) {
xt::xarray<int>::shape_type shape = { x_dim, y_dim };
xt::xarray<int> grid(shape);
grid(x_dim/2, y_dim/2) = 64000; return grid;
}
int print_grid(xt::xarray<int>& grid) {
// for output to the terminal uncomment next line // only makes sense for small grid < 32x32; // std::cout << grid << std::endl << std::endl;
// output result to an image
xt::dump_image("grid.jpg", grid);
return 0;
}
bool iterate_grid(xt::xarray<int>& grid, const unsigned long& x_dim, const unsigned long& y_dim) {
bool changed = false;
for (unsigned long i=0; i < x_dim; ++i)
{
for (unsigned long j=0; j < y_dim; ++j)
{
if ( grid(i, j) >= 4 )
{
grid(i, j) -= 4;
changed = true;
try
{
grid.at(i-1, j) += 1;
grid.at(i+1, j) += 1;
grid.at(i, j-1) += 1;
grid.at(i, j+1) += 1;
}
catch (const std::out_of_range& oor)
{
}
}
}
}
return changed;
}
int main(int argc, char* argv[]) {
const unsigned long x_dim { 200 };
const unsigned long y_dim { 200 };
xt::xarray<int> grid = init_grid(x_dim, y_dim);
bool changed { true };
iterate_grid(grid, x_dim, y_dim);
while (changed == true)
{
changed = iterate_grid(grid, x_dim, y_dim);
}
print_grid(grid);
return 0;
}
</lang>
Fōrmulæ
In this page you can see the solution of this task.
Fōrmulæ programs are not textual, visualization/edition of programs is done showing/manipulating structures but not text (more info). Moreover, there can be multiple visual representations of the same program. Even though it is possible to have textual representation —i.e. XML, JSON— they are intended for transportation effects more than visualization and edition.
The option to show Fōrmulæ programs and their results is showing images. Unfortunately images cannot be uploaded in Rosetta Code.
Forth
<lang forth>#! /usr/bin/gforth -d 20M
\ Abelian Sandpile Model
0 assert-level !
\ command-line
- parse-number s>number? invert throw drop ;
- parse-size ." size : " next-arg parse-number dup . cr ;
- parse-height ." height: " next-arg parse-number dup . cr ;
- parse-args cr parse-size parse-height ;
parse-args constant HEIGHT constant SIZE
- allot-erase create here >r dup allot r> swap erase ;
- size^2 SIZE dup * cells ;
- 2cells [ 2 cells ] literal ;
- -2cells [ 2cells negate ] literal ;
size^2 allot-erase arr
\ array processing
- ix swap SIZE * + cells arr + ;
- center SIZE 2/ dup ;
- write-cell ix @ u. ;
- write-row SIZE 0 ?do dup i write-cell loop drop cr ;
- arr. SIZE 0 ?do i write-row loop ;
\ stack processing
- stack-empty? dup -1 = ;
- stack-full? stack-empty? invert ;
\ pgm-handling
- concat { a1 l1 a2 l2 } l1 l2 + allocate throw dup dup a1 swap l1 cmove a2 swap l1 + l2 cmove l1 l2 + ;
- write-pgm ." P2" cr SIZE u. SIZE u. cr ." 3" cr arr. ;
- u>s 0 <# #s #> ;
- filename s" sandpile-" SIZE u>s concat s" -" concat HEIGHT u>s concat s" .pgm" concat ;
- to-pgm filename w/o create-file throw ['] write-pgm over outfile-execute close-file throw ;
\ sandpile
- prep-arr HEIGHT center ix ! ;
- prep-stack -1 HEIGHT 4 u>= if center then ;
- prepare prep-arr prep-stack ;
- ensure if else 2drop 0 2rdrop exit then ;
- col>=0 dup 0>= ensure ;
- col<SIZE dup SIZE < ensure ;
- row>=0 over 0>= ensure ;
- row<SIZE over SIZE < ensure ;
- legal? col>=0 col<SIZE row>=0 row<SIZE 2drop true ;
- north 1. d- ;
- east 1+ ;
- south 1. d+ ;
- west 1- ;
- reduce 2dup ix dup -4 swap +! @ 4 < if 2drop then ;
- increase 2dup legal? if 2dup ix dup 1 swap +! @ 4 = if 2swap else 2drop then else 2drop then ;
- inc-north 2dup north increase ;
- inc-east 2dup east increase ;
- inc-south 2dup south increase ;
- inc-west 2dup west increase ;
- inc-all inc-north inc-east inc-south inc-west 2drop ;
- simulate prepare begin stack-full? while 2dup 2>r reduce 2r> inc-all repeat drop to-pgm ." written to " filename type cr ;
simulate bye</lang>
- Output:
sandpile with 5000 grains of sand:
./sandpile.fs 61 5000:
[1]
sandpile with 50000 grains of sand:
./sandpile.fs 201 50000:
[2]
sandpile with 500000 grains of sand:
./sandpile.fs 601 500000:
[3]
![[1]](http://commons.wikimedia.org/wiki/File:Sandpile-61-5000.png){kind=link}
![[2]](http://commons.wikimedia.org/wiki/File:Sandpile-201-50000.png){kind=link}
![[3]](http://commons.wikimedia.org/wiki/File:Sandpile-601-500000.png){kind=link}
Go
Stack management in Go is automatic, starting very small (2KB) for each goroutine and expanding as necessary until the maximum allowed size is reached.
<lang go>package main
import (
"fmt" "log" "os" "strings"
)
const dim = 16 // image size
func check(err error) {
if err != nil {
log.Fatal(err)
}
}
// Outputs the result to the terminal using UTF-8 block characters. func drawPile(pile [][]uint) {
chars:= []rune(" ░▓█")
for _, row := range pile {
line := make([]rune, len(row))
for i, elem := range row {
if elem > 3 { // only possible when algorithm not yet completed.
elem = 3
}
line[i] = chars[elem]
}
fmt.Println(string(line))
}
}
// Creates a .ppm file in the current directory, which contains // a colored image of the pile. func writePile(pile [][]uint) {
file, err := os.Create("output.ppm")
check(err)
defer file.Close()
// Write the signature, image dimensions and maximum color value to the file.
fmt.Fprintf(file, "P3\n%d %d\n255\n", dim, dim)
bcolors := []string{"125 0 25 ", "125 80 0 ", "186 118 0 ", "224 142 0 "}
var line strings.Builder
for _, row := range pile {
for _, elem := range row {
line.WriteString(bcolors[elem])
}
file.WriteString(line.String() + "\n")
line.Reset()
}
}
// Main part of the algorithm, a simple, recursive implementation of the model. func handlePile(x, y uint, pile [][]uint) {
if pile[y][x] >= 4 {
pile[y][x] -= 4
// Check each neighbor, whether they have enough "sand" to collapse and if they do,
// recursively call handlePile on them.
if y > 0 {
pile[y-1][x]++
if pile[y-1][x] >= 4 {
handlePile(x, y-1, pile)
}
}
if x > 0 {
pile[y][x-1]++
if pile[y][x-1] >= 4 {
handlePile(x-1, y, pile)
}
}
if y < dim-1 {
pile[y+1][x]++
if pile[y+1][x] >= 4 {
handlePile(x, y+1, pile)
}
}
if x < dim-1 {
pile[y][x+1]++
if pile[y][x+1] >= 4 {
handlePile(x+1, y, pile)
}
}
// Uncomment this line to show every iteration of the program.
// Not recommended with large input values.
// drawPile(pile)
// Finally call the function on the current cell again,
// in case it had more than 4 particles.
handlePile(x, y, pile)
}
}
func main() {
// Create 2D grid and set size using the 'dim' constant.
pile := make([][]uint, dim)
for i := 0; i < dim; i++ {
pile[i] = make([]uint, dim)
}
// Place some sand particles in the center of the grid and start the algorithm. hdim := uint(dim/2 - 1) pile[hdim][hdim] = 16 handlePile(hdim, hdim, pile) drawPile(pile)
// Uncomment this to save the final image to a file // after the recursive algorithm has ended. // writePile(pile)
}</lang>
- Output:
░
▓░▓
░░ ░░
▓░▓
░
Haskell
Using a custom monad to make the code cleaner.
<lang haskell>{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE GeneralizedNewtypeDeriving #-}
{-# LANGUAGE ScopedTypeVariables #-}
module Rosetta.AbelianSandpileModel.ST
( simulate , test , toPGM ) where
import Control.Monad.Reader (asks, MonadReader (..), ReaderT, runReaderT) import Control.Monad.ST (runST, ST) import Control.Monad.State (evalStateT, forM_, lift, MonadState (..), StateT, modify, when) import Data.Array.ST (freeze, readArray, STUArray, thaw, writeArray) import Data.Array.Unboxed (array, assocs, bounds, UArray, (!)) import Data.Word (Word32) import System.IO (hPutStr, hPutStrLn, IOMode (WriteMode), withFile) import Text.Printf (printf)
type Point = (Int, Int) type ArrayST s = STUArray s Point Word32 type ArrayU = UArray Point Word32
newtype M s a = M (ReaderT (S s) (StateT [Point] (ST s)) a)
deriving (Functor, Applicative, Monad, MonadReader (S s), MonadState [Point])
data S s = S
{ bMin :: !Point
, bMax :: !Point
, arr :: !(ArrayST s)
}
runM :: M s a -> S s -> [Point]-> ST s a runM (M m) = evalStateT . runReaderT m
liftST :: ST s a -> M s a liftST = M . lift . lift
simulate :: ArrayU -> ArrayU simulate a = runST $ simulateST a
simulateST :: forall s. ArrayU -> ST s ArrayU simulateST a = do
let (p1, p2) = bounds a
s = [p | (p, c) <- assocs a, c >= 4]
b <- thaw a :: ST s (ArrayST s)
let st = S { bMin = p1
, bMax = p2
, arr = b
}
runM simulateM st s
simulateM :: forall s. M s ArrayU simulateM = do
ps <- get
case ps of
[] -> asks arr >>= liftST . freeze
p : ps' -> do
c <- changeArr p $ \x -> x - 4
when (c < 4) $ put ps'
forM_ [north, east, south, west] $ inc . ($ p)
simulateM
changeArr :: Point -> (Word32 -> Word32) -> M s Word32 changeArr p f = do
a <- asks arr oldC <- liftST $ readArray a p let newC = f oldC liftST $ writeArray a p newC return newC
inc :: Point -> M s () inc p = do
b <- inBounds p
when b $ do
c <- changeArr p succ
when (c == 4) $ modify $ (p :)
inBounds :: Point -> M s Bool inBounds p = do
st <- ask return $ p >= bMin st && p <= bMax st
north, east, south, west :: Point -> Point north (x, y) = (x, y + 1) east (x, y) = (x + 1, y) south (x, y) = (x, y - 1) west (x, y) = (x - 1, y)
toPGM :: ArrayU -> FilePath -> IO () toPGM a fp = withFile fp WriteMode $ \h -> do
let ((x1, y1), (x2, y2)) = bounds a
width = x2 - x1 + 1
height = y2 - y1 + 1
hPutStrLn h "P2"
hPutStrLn h $ show width ++ " " ++ show height
hPutStrLn h "3"
forM_ [y1 .. y2] $ \y -> do
forM_ [x1 .. x2] $ \x -> do
let c = min 3 $ a ! (x, y)
hPutStr h $ show c ++ " "
hPutStrLn h ""
initArray :: Int -> Word32 -> ArrayU initArray size height = array
((-size, -size), (size, size)) [((x, y), if x == 0 && y == 0 then height else 0) | x <- [-size .. size], y <- [-size .. size]]
test :: Int -> Word32 -> IO () test size height = do
printf "size = %d, height = %d\n" size height
let a = initArray size height
b = simulate a
fp = printf "sandpile_%d_%d.pgm" size height
toPGM b fp
putStrLn $ "wrote image to " ++ fp</lang>
- Output:
sandpile with 1000 grains of sand: test 15 1000: [4]
sandpile with 10000 grains of sand: test 40 10000: [5]
sandpile with 100000 grains of sand: test 150 100000: [6]
sandpile with 1000000 grains of sand: test 400 1000000: [7]
![[4]](http://commons.wikimedia.org/wiki/File:Sandpile_15_1000.jpg){kind=link}
![[5]](http://commons.wikimedia.org/wiki/File:Sandpile_40_10000.jpg){kind=link}
![[6]](http://commons.wikimedia.org/wiki/File:Sandpile_150_100000.jpg){kind=link}
![[7]](http://commons.wikimedia.org/wiki/File:Sandpile_400_1000000.jpg){kind=link}
Julia
Modified from code by Hayk Aleksanyan, viewable at github.com/hayk314/Sandpiles, license viewable there. <lang julia>module AbelSand
- supports output functionality for the results of the sandpile simulations
- outputs the final grid in CSV format, as well as an image file
using CSV, DataFrames, Images
function TrimZeros(A)
# given an array A trims any zero rows/columns from its borders # returns a 4 tuple of integers, i1, i2, j1, j2, where the trimmed array corresponds to A[i1:i2, j1:j2] # A can be either numeric or a boolean array
i1, j1 = 1, 1 i2, j2 = size(A)
zz = typeof(A[1, 1])(0) # comparison of a value takes into account the type as well
# i1 is the first row which has non zero element
for i = 1:size(A, 1)
q = false
for k = 1:size(A, 2)
if A[i, k] != zz
q = true
i1 = i
break
end
end
if q == true
break
end
end
# i2 is the first from below row with non zero element
for i in size(A, 1):-1:1
q = false
for k = 1:size(A, 2)
if A[i, k] != zz
q = true
i2 = i
break
end
end
if q == true
break
end
end
# j1 is the first column with non zero element
for j = 1:size(A, 2)
q = false
for k = 1:size(A, 1)
if A[k, j] != zz
j1 = j
q = true
break
end
end
if q == true
break
end
end
# j2 is the last column with non zero element
for j in size(A, 2):-1:1
q=false
for k=1:size(A,1)
if A[k, j] != zz
j2 = j
q=true
break
end
end
if q==true
break
end
end
return i1, i2, j1, j2
end
function addLayerofZeros(A, extraLayer)
# adds layer of zeros from all corners to the given array A
if extraLayer <= 0
return A
end
N, M = size(A)
Z = zeros( typeof(A[1,1]), N + 2*extraLayer, M + 2*extraLayer) Z[(extraLayer+1):(N + extraLayer ), (extraLayer+1):(M+extraLayer)] = A
return Z
end
function printIntoFile(A, extraLayer, strFileName, TrimSmallValues = false)
# exports a 2d matrix A into a csv file # @extraLayer is an integers adding layer of 0-s sorrounding the output matrix
# trimming off very small values; tiny values affect the performance of CSV export
if TrimSmallValues == true
A = map(x -> if (abs(x - floor(x)) < 0.01) floor(x) else x end, A)
end
i1, i2, j1, j2 = TrimZeros( A ) A = A[i1:i2, j1:j2]
A = addLayerofZeros(A, extraLayer)
CSV.write(string(strFileName,".csv"), DataFrame(A), writeheader = false)
return A
end
function Array_magnifier(A, cell_mag, border_mag)
# A is the main array; @cell_mag is the magnifying size of the cell, # @border_mag is the magnifying size of the border between lattice cells
# creates a new array where each cell of the original array A appears magnified by size = cell_mag
total_factor = cell_mag + border_mag
A1 = zeros(typeof(A[1, 1]), total_factor*size(A, 1), total_factor*size(A, 2))
for i = 1:size(A,1), j = 1:size(A,2), u = ((i-1)*total_factor+1):(i*total_factor),
v = ((j-1)*total_factor+1):(j*total_factor)
if(( u - (i - 1) * total_factor <= cell_mag) && (v - (j - 1) * total_factor <= cell_mag))
A1[u, v] = A[i, j]
end
end
return A1
end
function saveAsGrayImage(A, fileName, cell_mag, border_mag, TrimSmallValues = false)
# given a 2d matrix A, we save it as a gray image after magnifying by the given factors A1 = Array_magnifier(A, cell_mag, border_mag) A1 = A1/maximum(maximum(A1))
# trimming very small values from A1 to improve performance
if TrimSmallValues == true
A1 = map(x -> if ( x < 0.01) 0.0 else round(x, digits = 2) end, A1)
end
save(string(fileName, ".png") , colorview(Gray, A1))
end
function saveAsRGBImage(A, fileName, color_codes, cell_mag, border_mag)
# color_codes is a dictionary, where key is a value in A and value is an RGB triplet # given a 2d array A, and color codes (mapping from values in A to RGB triples), save A # into fileName as png image after applying the magnifying factors
A1 = Array_magnifier(A, cell_mag, border_mag) color_mat = zeros(UInt8, (3, size(A1, 1), size(A1, 2)))
for i = 1:size(A1,1)
for j = 1:size(A1,2)
color_mat[:, i, j] = get(color_codes, A1[i, j] , [0, 0, 0])
end
end
save(string(fileName, ".png") , colorview(RGB, color_mat/255))
end
const N_size = 700 # the radius of the lattice Z^2, the actual size becomes (2*N+1)x(2*N+1) const dx = [1, 0, -1, 0] # for a given (x,y) in Z^2, (x + dx, y + dy) for all (dx,dy) covers the neighborhood of (x,y) const dy = [0, 1, 0, -1]
struct L_coord
# represents a lattice coordinate x::Int y::Int
end
function FindCoordinate(Z::Array{L_coord,1}, a::Int, b::Int)
# in the given array Z of coordinates finds the (first) index of the tuple (a,b) # if no match, returns -1
for i=1:length(Z)
if (Z[i].x == a) && (Z[i].y == b)
return i
end
end
return -1
end
function move(N)
# the main function moving the pile sand grains of size N at the origin of Z^2 until the sandpile becomes stable
Z_lat = zeros(UInt8, 2 * N_size + 1, 2 * N_size + 1) # models the integer lattice Z^2, we will have at most 4 sands on each vertex V_sites = falses(2 * N_size + 1, 2 * N_size + 1) # all sites which are visited by the sandpile process, are being marked here Odometer = zeros(UInt64, 2 * N_size + 1, 2 * N_size + 1) # stores the values of the odometer function
walking = L_coord[] # the coordinates of sites which need to move
V_sites[N_size + 1, N_size + 1] = true
# i1, ... j2 -> show the boundaries of the box which is visited by the sandpile process i1, i2, j1, j2 = N_size + 1, N_size + 1, N_size + 1, N_size + 1 n = N
t1 = time_ns()
while n > 0
n -= 1
Z_lat[N_size + 1, N_size + 1] += 1
if (Z_lat[N_size + 1, N_size + 1] >= 4)
push!(walking, L_coord(N_size + 1, N_size + 1))
end
while(length(walking) > 0)
w = pop!(walking)
x = w.x
y = w.y
Z_lat[x, y] -= 4
Odometer[x, y] += 4
for k = 1:4
Z_lat[x + dx[k], y + dy[k]] += 1
V_sites[x + dx[k], y + dy[k]] = true
if Z_lat[x + dx[k], y + dy[k]] >= 4
if FindCoordinate(walking, x + dx[k] , y + dy[k]) == -1
push!(walking, L_coord( x + dx[k], y + dy[k]))
end
end
end
i1 = min(i1, x - 1)
i2 = max(i2, x + 1)
j1 = min(j1, y - 1)
j2 = max(j2, y + 1)
end
end #end of the main while t2 = time_ns()
println("The final boundaries are:: ", (i2 - i1 + 1),"x",(j2 - j1 + 1), "\n")
print("time elapsed: " , (t2 - t1) / 1.0e9, "\n")
Z_lat = printIntoFile(Z_lat, 0, string("Abel_Z_", N))
Odometer = printIntoFile(Odometer, 1, string("Abel_OD_", N))
saveAsGrayImage(Z_lat, string("Abel_Z_", N), 20, 0)
color_code = Dict(1=>[255, 128, 255], 2=>[255, 0, 0],3 => [0, 128, 255])
saveAsRGBImage(Z_lat, string("Abel_Z_color_", N), color_code, 20, 0)
# for the total elapsed time, it's better to use the @time macros on the main call
return Z_lat, Odometer # these are trimmed in output module
end # end of function move
end # module
using .AbelSand
Z_lat, Odometer = AbelSand.move(100000)
</lang>
- Output:
Link to PNG output file for N=100000 ie. AbelSand.move(100000)
Link to PNG output file (run time >90 min) for N=1000000 (move(1000000))
Perl
<lang Perl>#!/usr/bin/perl
use strict; # http://www.rosettacode.org/wiki/Abelian_sandpile_model use warnings;
my ($high, $wide) = split ' ', qx(stty size); my $mask = "\0" x $wide . ("\0" . "\177" x ($wide - 2) . "\0") x ($high - 5) .
"\0" x $wide;
my $pile = $mask =~ s/\177/ rand() < 0.02 ? chr 64 + rand 20 : "\0" /ger;
for ( 1 .. 1e6 )
{
print "\e[H", $pile =~ tr/\0-\177/ 1-~/r, "\n$_";
my $add = $pile =~ tr/\1-\177/\0\0\0\200/r; # set high bit for >=4
$add =~ /\200/ or last;
$pile =~ tr/\4-\177/\0-\173/; # subtract 4 if >=4
for ("\0$add", "\0" x $wide . $add, substr($add, 1), substr $add, $wide)
{
$pile |= $_;
$pile =~ tr/\200-\377/\1-\176/; # add one to each neighbor of >=4
$pile &= $mask;
}
select undef, undef, undef, 0.1; # comment out for full speed
}</lang>
Perl 6
Defaults to a stack of 1000 and showing progress. Pass in a custom stack size if desired and -hide-progress to run without displaying progress (much faster.)
<lang perl6>sub cleanup { print "\e[0m\e[?25h\n"; exit(0) }
signal(SIGINT).tap: { cleanup(); exit(0) }
unit sub MAIN ($stack = 1000, :$hide-progress = False );
my @color = "\e[38;2;0;0;0m█",
"\e[38;2;255;0;0m█",
"\e[38;2;255;255;0m█",
"\e[38;2;0;0;255m█",
"\e[38;2;255;255;255m█"
;
my ($h, $w) = qx/stty size/.words».Int; my $buf = $w * $h; my @buffer = 0 xx $buf; my $done;
@buffer[$w * ($h div 2) + ($w div 2) - 1] = $stack;
print "\e[?25l\e[48;5;232m";
repeat {
$done = True;
loop (my int $row; $row < $h; $row = $row + 1) {
my int $rs = $row * $w; # row start
my int $re = $rs + $w; # row end
loop (my int $idx = $rs; $idx < $re; $idx = $idx + 1) {
if @buffer[$idx] >= 4 {
++@buffer[ $idx - $w ] if $row > 0;
++@buffer[ $idx - 1 ] if $idx - 1 > $rs;
++@buffer[ $idx + $w ] if $row < $h - 1;
++@buffer[ $idx + 1 ] if $idx + 1 < $buf;
@buffer[ $idx ] -= 4;
$done = False;
}
}
}
unless $hide-progress {
print join , @buffer.map( { @color[$_ min 4] })
}
} until $done;
print join , @buffer.map( { @color[$_ min 4] });
cleanup;</lang>
Passing in 2048 as a stack size results in: Abelian-sandpile-model-perl6.png (offsite .png image)
Phix
Generates moving images similar to the julia output. The distributed version also has variable speed, additional display modes, and a random dropping toggle. <lang Phix>-- demo\rosetta\Abelian_sandpile_model.exw include pGUI.e
Ihandle dlg, canvas cdCanvas cddbuffer
sequence board = {{0,0,0},
{0,0,0},
{0,0,0}}
procedure drop(integer y, x)
sequence moves = {}
while true do
board[y,x] += 1
if board[y,x]>=4 then
board[y,x] -= 4
moves &= {{y,x-1},{y,x+1},{y-1,x},{y+1,x}}
end if
-- extend board if rqd (maintain a border of zeroes)
if x=1 then -- extend left
for i=1 to length(board) do
board[i] = prepend(board[i],0)
end for
for i=1 to length(moves) do
moves[i][2] += 1
end for
elsif x=length(board[1]) then -- extend right
for i=1 to length(board) do
board[i] = append(board[i],0)
end for
end if
-- (copy the all-0 lines from the other end...)
if y=1 then -- extend up
board = prepend(board,board[$])
for i=1 to length(moves) do
moves[i][1] += 1
end for
elsif y=length(board) then -- extend down
board = append(board,board[1])
end if
if length(moves)=0 then exit end if
{y,x} = moves[$]
moves = moves[1..$-1]
end while
IupUpdate(canvas)
end procedure
function timer_cb(Ihandle /*ih*/)
integer y = floor(length(board)/2)+1,
x = floor(length(board[1])/2)+1
drop(y,x)
return IUP_DEFAULT
end function
function redraw_cb(Ihandle ih, integer /*posx*/, integer /*posy*/)
IupGLMakeCurrent(ih)
cdCanvasActivate(cddbuffer)
cdCanvasClear(cddbuffer)
for y=1 to length(board) do
for x=1 to length(board[1]) do
integer c = board[y][x]
if c!=0 then
integer colour = {CD_VIOLET,CD_RED,CD_BLUE}[c]
cdCanvasPixel(cddbuffer, x, y, colour)
end if
end for
end for
cdCanvasFlush(cddbuffer)
return IUP_DEFAULT
end function
function map_cb(Ihandle ih)
IupGLMakeCurrent(ih)
atom res = IupGetDouble(NULL, "SCREENDPI")/25.4
cddbuffer = cdCreateCanvas(CD_GL, "300x100 %g", {res})
cdCanvasSetBackground(cddbuffer, CD_PARCHMENT)
return IUP_DEFAULT
end function
procedure main()
IupOpen()
canvas = IupGLCanvas("RASTERSIZE=300x100")
IupSetCallbacks({canvas}, {"ACTION", Icallback("redraw_cb"),
"MAP_CB", Icallback("map_cb")})
dlg = IupDialog(canvas,"TITLE=\"Abelian sandpile model\"")
IupCloseOnEscape(dlg)
IupShow(dlg)
Ihandle timer = IupTimer(Icallback("timer_cb"), 10)
IupMainLoop()
IupClose()
end procedure
main()</lang>
Python
<lang Python> import numpy as np import matplotlib.pyplot as plt
def iterate(grid):
changed = False
for ii, arr in enumerate(grid):
for jj, val in enumerate(arr):
if val > 3:
grid[ii, jj] -= 4
if ii > 0:
grid[ii - 1, jj] += 1
if ii < len(grid)-1:
grid[ii + 1, jj] += 1
if jj > 0:
grid[ii, jj - 1] += 1
if jj < len(grid)-1:
grid[ii, jj + 1] += 1
changed = True
return grid, changed
def simulate(grid):
while True:
grid, changed = iterate(grid)
if not changed:
return grid
if __name__ == '__main__':
start_grid = np.zeros((10, 10)) start_grid[4:5, 4:5] = 64 final_grid = simulate(start_grid.copy()) plt.figure() plt.gray() plt.imshow(start_grid) plt.figure() plt.gray() plt.imshow(final_grid)
</lang> Output: </n> Before: <lang Python> [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0.64. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]]
</lang> After: <lang Python> [[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 1. 2. 1. 0. 0. 0. 0.] [0. 0. 2. 2. 2. 2. 2. 0. 0. 0.] [0. 1. 2. 2. 2. 2. 2. 1. 0. 0.] [0. 2. 2. 2. 0. 2. 2. 2. 0. 0.] [0. 1. 2. 2. 2. 2. 2. 1. 0. 0.] [0. 0. 2. 2. 2. 2. 2. 0. 0. 0.] [0. 0. 0. 1. 2. 1. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]]
</lang>
Rust
<lang rust>// Set image size. const DIM: usize = 16;
// This function outputs the result to the console using UTF-8 block characters. fn draw_pile(pile: &Vec<Vec<usize>>) {
for row in pile {
let mut line = String::with_capacity(row.len());
for elem in row {
line.push(match elem {
0 => ' ',
1 => '░',
2 => '▒',
3 => '▓',
_ => '█'
});
}
println!("{}", line);
}
}
// This function creates a file called "output.ppm" in the directory the program was run, which contains // a colored image of the pile. fn write_pile(pile: &Vec<Vec<usize>>) {
use std::fs::File; // Used for opening the file. use std::io::Write; // Used for writing to the file.
// Learn more about PPM here: http://netpbm.sourceforge.net/doc/ppm.html let mut file = File::create("./output.ppm").unwrap();
// We write the signature, image dimensions and maximum color value to the file.
let _ = write!(file, "P3\n {} {}\n255\n", DIM, DIM).unwrap();
for row in pile {
let mut line = String::with_capacity(row.len()*6);
for elem in row {
line.push_str(match elem {
0 => "125 0 25 ", // Background color for cells that have no "sand" in them.
// Depending on how many particles of sand is there in the cell we use a different shade of yellow.
1 => "125 80 0 ",
2 => "186 118 0 ",
3 => "224 142 0 ",
// It is impossible to have more than 3 particles of sand in one cell after the program has run,
// however, Rust demands that all branches have to be considered in a match statement, so we
// explicitly tell the compiler, that this is an unreachable branch.
_ => unreachable!()
});
}
let _ = write!(file, "{}", line).unwrap();
}
}
// This is the main part of the algorithm, a simple, recursive implementation of the model. fn handle_pile(x: usize, y: usize, pile: &mut Vec<Vec<usize>>) {
if pile[y][x] >= 4 {
pile[y][x] -= 4;
// We check each neighbor, whether they have enough "sand" to collapse and if they do,
// we recursively call handle_pile on them.
if y > 0 {
pile[y-1][x] += 1;
if pile[y-1][x] >= 4 {handle_pile(x, y-1, pile)}}
if x > 0 {
pile[y][x-1] += 1;
if pile[y][x-1] >= 4 {handle_pile(x-1, y, pile)}}
if y < DIM-1 {
pile[y+1][x] += 1;
if pile[y+1][x] >= 4 {handle_pile(x, y+1, pile)}}
if x < DIM-1 {
pile[y][x+1] += 1;
if pile[y][x+1] >= 4 {handle_pile(x+1, y, pile)}}
// Uncomment this line to show every iteration of the program. Not recommended with large input values.
//draw_pile(&pile);
// Finally we call the function on the current cell again, in case it had more than 4 particles.
handle_pile(x,y,pile);
}
}
fn main() {
use std::thread::Builder; // Used to spawn a new thread.
/* Rust by default uses a 2Mb stack, which gets quickly filled (resulting in a stack overflow) if we use any value larger than
* about 30,000 as our input value. To circumvent this, we spawn a thread with 32Mbs of stack memory, which can easily handle
* hundreds of thousands of sand particles. I tested the program using 256,000, but it should theoretically work with larger
* values too.
*/
let _ = Builder::new().stack_size(33554432).spawn(|| {
// This is our 2D grid. It's size can be set using the DIM constant found at the top of the code.
let mut pile: Vec<Vec<usize>> = vec![vec![0;DIM]; DIM];
// We place this much sand in the center of the grid.
pile[DIM/2 - 1][DIM/2 - 1] = 16;
// We start the algorithm on the pile we just created.
handle_pile(DIM/2 - 1, DIM/2 - 1, &mut pile);
draw_pile(&pile)
// Uncomment this to save the image to a file after the recursive algorithm has ended.
//write_pile(&pile)
}).unwrap().join();
}</lang>
Output:
░
▒░▒
░░ ░░
▒░▒
░