499 lines
12 KiB
Dart
499 lines
12 KiB
Dart
import 'dart:developer';
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import 'dart:math' as math;
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import 'dart:typed_data';
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import 'dart:ui' as ui;
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import 'dart:ui';
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import 'package:flutter/services.dart';
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class Wfc<T> {
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// parameters
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final WfcTemplate<T> _template;
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final int _mx, _my;
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// constants
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int get _n => _mx * _my;
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int get _nShingles => _template._shingles.n;
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int get _order => _template._order;
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double _weight(int shingleIx) =>
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_template._shingles._shingleWeights[shingleIx];
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// overall algo state
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List<List<bool>> _wave = [];
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List<List<List<int>>> _compatible = [];
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List<int?> _observed = [];
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// computationally expensive stuff that we keep in an incremental way
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List<double> _weightLogWeights = [];
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double _sumOfWeights = 0.0, _sumOfWeightLogWeights = 0.0;
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double _startingEntropy = 0.0;
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List<int> _sumsOfOnes = [];
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List<double> _sumsOfWeights = [];
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List<double> _sumsOfWeightLogWeights = [];
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List<double> _entropies = [];
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// temporaries
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List<double> _distribution = [];
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List<(int, int)> _stack = [];
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int _stacksize = 0;
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Wfc(this._template, this._mx, this._my) {
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_wave = [
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for (var r = 0; r < _n; r++) [for (var t = 0; t < _nShingles; t++) false]
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];
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_compatible = [
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for (var r = 0; r < _n; r++)
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[
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for (var t = 0; t < _nShingles; t++) [0, 0, 0, 0]
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]
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];
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_distribution = [for (var t = 0; t < _nShingles; t++) 0.0];
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_observed = [for (var r = 0; r < _n; r++) null];
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_weightLogWeights = [
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for (var t = 0; t < _nShingles; t++) _weight(t) * math.log(_weight(t))
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];
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_sumOfWeights = 0.0;
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_sumOfWeightLogWeights = 0.0;
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for (var t = 0; t < _nShingles; t++) {
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_sumOfWeights += _weight(t);
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_sumOfWeightLogWeights += _weightLogWeights[t];
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}
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_startingEntropy =
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math.log(_sumOfWeights) - _sumOfWeightLogWeights / _sumOfWeights;
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_sumsOfOnes = [for (var r = 0; r < _n; r++) 0];
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_sumsOfWeights = [for (var r = 0; r < _n; r++) 0.0];
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_sumsOfWeightLogWeights = [for (var r = 0; r < _n; r++) 0.0];
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_entropies = [for (var r = 0; r < _n; r++) 0.0];
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_stack = [for (var r = 0; r < _n * _nShingles; r++) (0, 0)];
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_stacksize = 0;
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}
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void clear() {
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for (var i = 0; i < _wave.length; i++) {
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for (var t = 0; t < _nShingles; t++) {
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_wave[i][t] = true;
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for (var d = 0; d < 4; d++) {
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_compatible[i][t][d] = _template
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._shingles._metadata._propagators[_opposite[d]][t].length;
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}
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}
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_sumsOfOnes[i] = _nShingles;
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_sumsOfWeights[i] = _sumOfWeights;
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_sumsOfWeightLogWeights[i] = _sumOfWeightLogWeights;
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_entropies[i] = _startingEntropy;
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_observed[i] = null;
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}
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}
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bool run(int? seed, int limit) {
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clear();
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var random = math.Random(seed);
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for (var l = 0; l < limit || limit < 0; l++) {
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var node = _nextUnobservedNode(random);
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if (node != null) {
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_observe(node, random);
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var success = _propagate();
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if (!success) {
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return false;
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}
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} else {
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for (var i = 0; i < _n; i++) {
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for (var t = 0; t < _nShingles; t++) {
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if (_wave[i][t]) {
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_observed[i] = t;
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break;
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}
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}
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}
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return true;
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}
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}
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return true;
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}
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List<T>? extract() {
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var partial = extractPartial();
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List<T> out = [];
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for (var i in partial) {
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if (i == null) {
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return null;
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}
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out.add(i);
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}
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return out;
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}
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List<T?> extractPartial() {
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List<T?> result = [];
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for (int i = 0; i < _n; i++) {
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result.add(null);
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}
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for (int y = 0; y < _my; y++) {
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var dy = y < _my - _order + 1 ? 0 : _order - 1;
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for (int x = 0; x < _mx; x++) {
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var dx = x < _mx - _order + 1 ? 0 : _order - 1;
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var shingleIx = _observed[x - dx + (y - dy) * _mx];
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if (shingleIx != null) {
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var shingle = _template._shingles._shingleValues[shingleIx];
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var content = shingle.content[dx + dy * _order];
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var real = _template._embedding.decode(content);
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result[x + y * _mx] = real;
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}
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}
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}
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return result;
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}
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int? _nextUnobservedNode(math.Random random) {
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double min = 1E+10;
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int? argmin;
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for (var i = 0; i < _n; i++) {
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if (i % _mx + _order > _mx || i ~/ _mx + _order > _my) {
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continue;
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}
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var remainingValues = _sumsOfOnes[i];
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double entropy = remainingValues.toDouble(); // _entropies[i];
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if (remainingValues > 1 && entropy <= min) {
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double noise = 1E-6 * random.nextDouble();
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if (entropy + noise < min) {
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min = entropy + noise;
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argmin = i;
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}
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}
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}
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return argmin;
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}
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void _observe(int node, math.Random random) {
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var w = _wave[node];
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for (var t = 0; t < _nShingles; t++) {
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_distribution[t] = w[t] ? _weight(t) : 0.0;
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}
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int r = _chooseRandom(random, _distribution);
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for (var t = 0; t < _nShingles; t++) {
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if (w[t] != (t == r)) {
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_ban(node, t);
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}
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}
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}
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bool _propagate() {
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while (_stacksize > 0) {
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int i1, t1;
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(i1, t1) = _stack[_stacksize - 1];
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_stacksize--;
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int x1 = i1 % _mx;
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int y1 = i1 ~/ _mx;
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for (int d = 0; d < 4; d++) {
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var x2 = x1 + _dx[d];
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var y2 = y1 + _dy[d];
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if (x2 < 0 || y2 < 0 || x2 + _order > _mx || y2 + _order > _my) {
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continue;
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}
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int i2 = x2 + y2 * _mx;
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var p = _template._shingles._metadata._propagators[d][t1];
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var compat = _compatible[i2];
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for (var t2 in p) {
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var comp = compat[t2];
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comp[d]--;
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if (comp[d] == 0) {
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_ban(i2, t2);
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}
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}
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}
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}
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return _sumsOfOnes[0] > 0;
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}
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void _ban(int i, int t) {
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_wave[i][t] = false;
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var comp = _compatible[i][t];
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for (var d = 0; d < 4; d++) {
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comp[d] = 0;
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}
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_stack[_stacksize] = (i, t);
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_stacksize++;
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_sumsOfOnes[i] -= 1;
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_sumsOfWeights[i] -= _weight(t);
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_sumsOfWeightLogWeights[i] -= _weightLogWeights[t];
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var sum = _sumsOfWeights[i];
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_entropies[i] = math.log(sum) - _sumsOfWeightLogWeights[i] / sum;
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}
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}
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class WfcTemplate<T> {
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final Shingles _shingles;
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final Embedding<T> _embedding;
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final int _order;
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WfcTemplate(this._shingles, this._embedding, this._order);
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static Future<WfcTemplate<T>> loadAsync<T>(
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String name, int order, T Function(int) cb) async {
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final assetImageByteData = await rootBundle.load(name);
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final codec =
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await ui.instantiateImageCodec(assetImageByteData.buffer.asUint8List());
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final image = (await codec.getNextFrame()).image;
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final bytedata =
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(await image.toByteData(format: ImageByteFormat.rawStraightRgba))!;
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final sx = image.width;
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final sy = image.height;
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final List<T> bitmap = [];
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for (var i = 0; i < sx * sy; i++) {
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var pixel = bytedata.getUint32(i * 4, Endian.little);
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log("pixel: $pixel");
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bitmap.add(cb(pixel));
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}
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return loadBitmap(bitmap, sx, sy, order);
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}
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static WfcTemplate<T> loadBitmap<T>(
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List<T> bitmap, int sx, int sy, int order) {
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if (bitmap.length != sx * sy) {
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throw Exception("malformed bitmap");
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}
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var embedding = Embedding<T>();
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List<int> sample = [
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for (var i = 0; i < bitmap.length; i++) embedding.encode(bitmap[i])
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];
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embedding.freeze();
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var shingles = Shingles();
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var xmax = sx - order + 1;
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var ymax = sy - order + 1;
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for (var y = 0; y < ymax; y++) {
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for (var x = 0; x < xmax; x++) {
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var ps = [
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Shingle(order, embedding.c,
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(dx, dy) => sample[(x + dx) % sx + (y + dy) % sy * sx])
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];
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ps.add(ps[0].reflect());
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ps.add(ps[0].rotate());
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ps.add(ps[2].reflect());
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ps.add(ps[2].rotate());
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ps.add(ps[4].reflect());
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ps.add(ps[4].rotate());
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ps.add(ps[6].reflect());
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for (var p in ps) {
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shingles.observe(p, 1.0);
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}
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}
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}
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shingles.freeze();
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return WfcTemplate(shingles, embedding, order);
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}
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}
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class Shingles {
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bool _frozen = false;
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final Map<int, int> _shingleIndices = {};
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final List<Shingle> _shingleValues = [];
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final List<double> _shingleWeights = [];
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late ShingleMetadata _metadata;
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int get n {
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if (!_frozen) {
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throw StateError("can't use Shingles#get n until frozen");
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}
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return _shingleValues.length;
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}
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void freeze() {
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if (_frozen) {
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throw StateError("can't freeze when already frozen");
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}
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_frozen = true;
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_metadata = ShingleMetadata(this);
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}
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void observe(Shingle s, double n) {
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if (_frozen) {
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throw StateError("can't observe when already frozen");
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}
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// double n: weights can be fractional
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var index = _shingleIndices[s.hashCode];
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if (index == null) {
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index = _shingleValues.length;
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_shingleValues.add(s);
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_shingleWeights.add(n);
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} else {
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_shingleWeights[index] += n;
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}
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}
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}
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class ShingleMetadata {
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// [direction][source] => list of agreeing items
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List<List<List<int>>> _propagators = [];
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ShingleMetadata(Shingles s) {
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_propagators = [
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for (var d = 0; d < 4; d++)
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[
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for (var t = 0; t < s.n; t++)
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[
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for (var t2 = 0; t2 < s.n; t2++)
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if (s._shingleValues[t]
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.agrees(s._shingleValues[t2], _dx[d], _dy[d]))
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t2
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]
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]
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];
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}
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}
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class Shingle {
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int order;
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int c;
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List<int> content = [];
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@override
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int hashCode = 0;
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Shingle(this.order, this.c, int Function(int, int) f) {
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content = [
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for (var y = 0; y < order; y++)
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for (var x = 0; x < order; x++) f(x, y)
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];
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int result = 0, power = 1;
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for (var i = 0; i < content.length; i++) {
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result += content[content.length - 1 - i] * power;
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power *= c;
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}
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hashCode = result;
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}
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Shingle rotate() {
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return Shingle(order, c, (x, y) => content[order - 1 - y + x * order]);
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}
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Shingle reflect() {
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return Shingle(order, c, (x, y) => content[order - 1 - x + y * order]);
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}
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bool agrees(Shingle other, int dx, int dy) {
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var p1 = content;
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var p2 = other.content;
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var n = order;
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int xmin = dx < 0 ? 0 : dx;
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int xmax = dx < 0 ? dx + n : n;
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int ymin = dy < 0 ? 0 : dy;
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int ymax = dy < 0 ? dy + n : n;
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for (var y = ymin; y < ymax; y++) {
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for (var x = xmin; x < xmax; x++) {
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if (p1[x + n * y] != p2[x - dx + n * (y - dy)]) {
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return false;
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}
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}
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}
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return true;
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}
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@override
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bool operator ==(Object other) {
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return (other is Shingle) &&
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other.hashCode == hashCode &&
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other.order == order &&
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other.c == c;
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}
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}
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class Embedding<T> {
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bool _frozen = false;
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final List<T> _colorOf = [];
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final Map<T, int> _codeOf = {};
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void freeze() {
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if (_frozen) {
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throw StateError("can't freeze when already frozen");
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}
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_frozen = true;
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}
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int get c {
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if (!_frozen) {
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throw StateError("can't use Embedding#get c until frozen");
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}
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return _colorOf.length;
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}
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int encode(T t) {
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var code = _codeOf[t];
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if (code == null) {
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if (_frozen) {
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throw StateError("can't create new code when frozen");
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}
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code = _colorOf.length;
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_codeOf[t] = code;
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_colorOf.add(t);
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}
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return code;
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}
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T decode(int i) {
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return _colorOf[i]!;
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}
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}
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int _chooseRandom(math.Random rand, List<double> distribution) {
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if (distribution.isEmpty) {
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throw Exception("can't sample empty distribution");
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}
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var sum = 0.0;
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for (var i = 0; i < distribution.length; i++) {
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sum += distribution[i];
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}
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if (sum == 0.0) {
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return rand.nextInt(distribution.length);
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}
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var rnd = rand.nextDouble() * sum;
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var i = 0;
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while (rnd > 0) {
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rnd -= distribution[i];
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if (rnd < 0) {
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return i;
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}
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i += 1;
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}
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return distribution.length - 1;
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}
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final List<int> _dx = [-1, 0, 1, 0];
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final List<int> _dy = [0, 1, 0, -1];
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final List<int> _opposite = [2, 3, 0, 1];
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