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3648.js

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+"use strict";(self.webpackChunkmy_application=self.webpackChunkmy_application||[]).push([[3648],{3648:(n,e,t)=>{t.r(e),t.d(e,{default:()=>i});const i="import 'dart:math' show Random;\n\nvoid main() async {\n  print('Compute π using the Monte Carlo method.');\n  await for (final estimate in computePi().take(100)) {\n    print('π ≅ $estimate');\n  }\n}\n\n/// Generates a stream of increasingly accurate estimates of π.\nStream<double> computePi({int batch = 100000}) async* {\n  var total = 0; // Inferred to be of type int\n  var count = 0;\n  while (true) {\n    final points = generateRandom().take(batch);\n    final inside = points.where((p) => p.isInsideUnitCircle);\n\n    total += batch;\n    count += inside.length;\n    final ratio = count / total;\n\n    // Area of a circle is A = π⋅r², therefore π = A/r².\n    // So, when given random points with x ∈ <0,1>,\n    // y ∈ <0,1>, the ratio of those inside a unit circle\n    // should approach π / 4. Therefore, the value of π\n    // should be:\n    yield ratio * 4;\n  }\n}\n\nIterable<Point> generateRandom([int? seed]) sync* {\n  final random = Random(seed);\n  while (true) {\n    yield Point(random.nextDouble(), random.nextDouble());\n  }\n}\n\nclass Point {\n  final double x;\n  final double y;\n\n  const Point(this.x, this.y);\n\n  bool get isInsideUnitCircle => x * x + y * y <= 1;\n}\n"}}]);
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