feat: add CLI random number generator supporting 6 distributions

src/dist.ts

@@ -0,0 +1,88 @@
+import { type Options } from "./types";
+
+// ---------------------------------------------------------------------------
+// Individual distribution samplers
+// ---------------------------------------------------------------------------
+
+/** Box-Muller transform. Each call consumes 2 uniform randoms. */
+function normalRandom(mean: number, stddev: number): number {
+  let u1 = Math.random();
+  while (u1 === 0) u1 = Math.random(); // avoid log(0)
+  const u2 = Math.random();
+  return mean + stddev * Math.sqrt(-2 * Math.log(u1)) * Math.cos(2 * Math.PI * u2);
+}
+
+/** Sum of Bernoulli trials. */
+function binomialRandom(n: number, p: number): number {
+  let s = 0;
+  for (let i = 0; i < n; i++) {
+    if (Math.random() < p) s++;
+  }
+  return s;
+}
+
+/** Knuth's algorithm. */
+function poissonRandom(lambda: number): number {
+  const L = Math.exp(-lambda);
+  let k = 0;
+  let p = 1;
+  do {
+    k++;
+    p *= Math.random();
+  } while (p > L);
+  return k - 1;
+}
+
+/** Inverse CDF. */
+function exponentialRandom(lambda: number): number {
+  return -Math.log(Math.random()) / lambda;
+}
+
+/** Urn model — simulate drawing without replacement. */
+function hypergeometricRandom(N: number, K: number, n: number): number {
+  let s = 0;
+  let remainingK = K;
+  let remainingTotal = N;
+  const draws = Math.min(n, N);
+  for (let i = 0; i < draws; i++) {
+    if (Math.random() < remainingK / remainingTotal) {
+      s++;
+      remainingK--;
+    }
+    remainingTotal--;
+  }
+  return s;
+}
+
+// ---------------------------------------------------------------------------
+// Dispatcher
+// ---------------------------------------------------------------------------
+
+export function generate(opts: Options): number[] {
+  const results: number[] = [];
+  for (let i = 0; i < opts.count; i++) {
+    switch (opts.dist) {
+      case "uniform":
+        results.push(Math.random() * (opts.max - opts.min) + opts.min);
+        break;
+      case "normal":
+        results.push(normalRandom(opts.mean, opts.stddev));
+        break;
+      case "binomial":
+        results.push(binomialRandom(opts.trials, opts.prob));
+        break;
+      case "poisson":
+        results.push(poissonRandom(opts.lambda));
+        break;
+      case "exponential":
+        results.push(exponentialRandom(opts.lambda));
+        break;
+      case "hypergeometric":
+        results.push(
+          hypergeometricRandom(opts.popSize, opts.successes, opts.draws),
+        );
+        break;
+    }
+  }
+  return results;
+}