refactor: semantic port TS to AffineScript

playground/examples/uncertainty.affine

@@ -1,11 +1,8 @@
 // SPDX-License-Identifier: MPL-2.0
-// Ported via Harvard Engine mechanical processor
+// Ported via Harvard Engine (Semantic pass)
 
 module uncertainty;
 
-// TODO: Complete semantic implementation
-
-/* === ORIGINAL TYPESCRIPT CONTEXT ===
 // SPDX-License-Identifier: MPL-2.0
 // Copyright (c) Jonathan D.A. Jewell <j.d.a.jewell@open.ac.uk>
 // SPDX-FileCopyrightText: 2025 hyperpolymath
@@ -20,66 +17,66 @@ module uncertainty;
 import { type Tri } from '../src/ternary.ts';
 
 /** Closed real interval [lo, hi]. */
-export interface Interval {
+struct Interval {
   lo: number;
   hi: number;
 }
 
-export const iv = (lo: number, hi: number): Interval => ({
+let iv = (lo: number, hi: number): Interval => ({
   lo: Math.min(lo, hi),
   hi: Math.max(lo, hi),
 });
 
-export function addI(a: Interval, b: Interval): Interval {
+fn addI(a: Interval, b: Interval): Interval {
   return iv(a.lo + b.lo, a.hi + b.hi);
 }
 
-export function mulI(a: Interval, b: Interval): Interval {
-  const ps = [a.lo * b.lo, a.lo * b.hi, a.hi * b.lo, a.hi * b.hi];
+fn mulI(a: Interval, b: Interval): Interval {
+  let ps = [a.lo * b.lo, a.lo * b.hi, a.hi * b.lo, a.hi * b.hi];
   return iv(Math.min(...ps), Math.max(...ps));
 }
 
 /** Ternary comparison: definite when disjoint, Unknown when they overlap. */
-export function ltI(a: Interval, b: Interval): Tri {
+fn ltI(a: Interval, b: Interval): Tri {
   if (a.hi < b.lo) return 'T';
   if (a.lo > b.hi) return 'F';
   return 'U';
 }
 
 /** Gaussian number: mean with standard deviation. */
-export interface Gaussian {
+struct Gaussian {
   mu: number;
   sd: number;
 }
 
-export const gauss = (mu: number, sd: number): Gaussian => ({ mu, sd: Math.abs(sd) });
+let gauss = (mu: number, sd: number): Gaussian => ({ mu, sd: Math.abs(sd) });
 
 /** First-order (uncorrelated) propagation through sum and product. */
-export function addG(a: Gaussian, b: Gaussian): Gaussian {
+fn addG(a: Gaussian, b: Gaussian): Gaussian {
   return gauss(a.mu + b.mu, Math.hypot(a.sd, b.sd));
 }
 
-export function mulG(a: Gaussian, b: Gaussian): Gaussian {
-  const mu = a.mu * b.mu;
-  const rel = Math.hypot(a.sd / a.mu, b.sd / b.mu);
+fn mulG(a: Gaussian, b: Gaussian): Gaussian {
+  let mu = a.mu * b.mu;
+  let rel = Math.hypot(a.sd / a.mu, b.sd / b.mu);
   return gauss(mu, Math.abs(mu) * rel);
 }
 
-function main(): void {
+fn main(): void {
   console.log('=== BetLang Uncertainty Modeling ===\n');
 
-  const a = iv(2, 4);
-  const b = iv(3, 5);
+  let a = iv(2, 4);
+  let b = iv(3, 5);
   console.log(`Intervals: a=[${a.lo},${a.hi}]  b=[${b.lo},${b.hi}]`);
   console.log(`  a + b = [${addI(a, b).lo}, ${addI(a, b).hi}]`);
   console.log(`  a * b = [${mulI(a, b).lo}, ${mulI(a, b).hi}]`);
   console.log(`  a < b ? -> ${ltI(a, b)}  (overlap => Unknown, not a false certainty)`);
   console.log(`  [0,1] < [5,6] ? -> ${ltI(iv(0, 1), iv(5, 6))}`);
 
-  const g1 = gauss(10, 1);
-  const g2 = gauss(20, 2);
-  const s = addG(g1, g2);
-  const p = mulG(g1, g2);
+  let g1 = gauss(10, 1);
+  let g2 = gauss(20, 2);
+  let s = addG(g1, g2);
+  let p = mulG(g1, g2);
   console.log(`\nGaussians: g1=${g1.mu}±${g1.sd}  g2=${g2.mu}±${g2.sd}`);
   console.log(`  g1 + g2 = ${s.mu}±${s.sd.toFixed(4)}`);
   console.log(`  g1 * g2 = ${p.mu}±${p.sd.toFixed(4)}`);
@@ -89,4 +86,3 @@ if (import.meta.main) {
   main();
 }
 
-==================================== */

playground/src/main.affine

@@ -1,11 +1,8 @@
 // SPDX-License-Identifier: MPL-2.0
-// Ported via Harvard Engine mechanical processor
+// Ported via Harvard Engine (Semantic pass)
 
 module main;
 
-// TODO: Complete semantic implementation
-
-/* === ORIGINAL TYPESCRIPT CONTEXT ===
 // SPDX-License-Identifier: MPL-2.0
 // Copyright (c) Jonathan D.A. Jewell <j.d.a.jewell@open.ac.uk>
 // SPDX-FileCopyrightText: 2025 hyperpolymath
@@ -18,7 +15,7 @@ module main;
 import { main as ternaryDemo } from './ternary.ts';
 import { main as probabilityDemo } from './probability.ts';
 
-function main(): void {
+fn main(): void {
   console.log('BetLang Playground — Symbolic Probabilistic Metalanguage\n');
   ternaryDemo();
   console.log('\n' + '-'.repeat(60) + '\n');
@@ -30,4 +27,3 @@ if (import.meta.main) {
   main();
 }
 
-==================================== */

playground/src/probability.affine

@@ -1,11 +1,8 @@
 // SPDX-License-Identifier: MPL-2.0
-// Ported via Harvard Engine mechanical processor
+// Ported via Harvard Engine (Semantic pass)
 
 module probability;
 
-// TODO: Complete semantic implementation
-
-/* === ORIGINAL TYPESCRIPT CONTEXT ===
 // SPDX-License-Identifier: MPL-2.0
 // Copyright (c) Jonathan D.A. Jewell <j.d.a.jewell@open.ac.uk>
 // SPDX-FileCopyrightText: 2025 hyperpolymath
@@ -23,13 +20,13 @@ module probability;
 import { bet, type Tri } from './ternary.ts';
 
 /** A lazy, weighted branch: a relative weight and a thunk producing a value. */
-export interface Branch<A> {
+struct Branch<A> {
   weight: number;
   value: () => A;
 }
 
 /** Deterministic, seedable PRNG (mulberry32) so demos/tests are reproducible. */
-export function rng(seed: number): () => number {
+fn rng(seed: number): () => number {
   let s = seed >>> 0;
   return () => {
     s = (s + 0x6d2b79f5) >>> 0;
@@ -41,8 +38,8 @@ export function rng(seed: number): () => number {
 }
 
 /** Force exactly one branch, chosen with probability proportional to weight. */
-export function betWeighted<A>(branches: Branch<A>[], draw: () => number): A {
-  const total = branches.reduce((acc, b) => acc + b.weight, 0);
+fn betWeighted<A>(branches: Branch<A>[], draw: () => number): A {
+  let total = branches.reduce((acc, b) => acc + b.weight, 0);
   if (total <= 0) throw new Error('betWeighted: weights must sum to a positive number');
   let r = draw() * total;
   for (const b of branches) {
@@ -56,7 +53,7 @@ export function betWeighted<A>(branches: Branch<A>[], draw: () => number): A {
  * Predicate-driven ternary selection. The predicate yields a Tri; a definite
  * answer takes the matching branch, Unknown defers to the `uncertain` branch.
  */
-export function betConditional<A>(
+fn betConditional<A>(
   predicate: () => Tri,
   ifTrue: () => A,
   uncertain: () => A,
@@ -66,13 +63,13 @@ export function betConditional<A>(
 }
 
 /** Monte-Carlo expectation of a numeric weighted bet over `n` samples. */
-export function expectation(branches: Branch<number>[], n: number, draw: () => number): number {
+fn expectation(branches: Branch<number>[], n: number, draw: () => number): number {
   let sum = 0;
   for (let i = 0; i < n; i++) sum += betWeighted(branches, draw);
   return sum / n;
 }
 
-export function main(): void {
+fn main(): void {
   console.log('=== BetLang Probabilistic Layer ===\n');
 
   // A loaded three-sided "coin": 60% True, 30% Unknown, 10% False.
@@ -81,9 +78,9 @@ export function main(): void {
     { weight: 0.3, value: () => 'U' as Tri },
     { weight: 0.1, value: () => 'F' as Tri },
   ];
-  const draw = rng(42);
+  let draw = rng(42);
   const counts: Record<Tri, number> = { T: 0, U: 0, F: 0 };
-  const N = 100_000;
+  let N = 100_000;
   for (let i = 0; i < N; i++) counts[betWeighted(loaded, draw)]++;
   console.log(`Empirical distribution over ${N.toLocaleString()} draws (target 0.60/0.30/0.10):`);
   console.log(
@@ -97,11 +94,11 @@ export function main(): void {
     { weight: 2, value: () => 10 },
     { weight: 7, value: () => 0 },
   ];
-  const ev = expectation(payout, 200_000, rng(7));
+  let ev = expectation(payout, 200_000, rng(7));
   console.log(`\nExpected payout (analytic = 12.0): ${ev.toFixed(2)}`);
 
   // Conditional choice that stays total under Unknown.
-  const choice = betConditional(
+  let choice = betConditional(
     () => 'U' as Tri,
     () => 'committed',
     () => 'hedged (predicate was Unknown)',
@@ -114,4 +111,3 @@ if (import.meta.main) {
   main();
 }
 
-==================================== */

playground/src/ternary.affine

@@ -1,11 +1,8 @@
 // SPDX-License-Identifier: MPL-2.0
-// Ported via Harvard Engine mechanical processor
+// Ported via Harvard Engine (Semantic pass)
 
 module ternary;
 
-// TODO: Complete semantic implementation
-
-/* === ORIGINAL TYPESCRIPT CONTEXT ===
 // SPDX-License-Identifier: MPL-2.0
 // Copyright (c) Jonathan D.A. Jewell <j.d.a.jewell@open.ac.uk>
 // SPDX-FileCopyrightText: 2025 hyperpolymath
@@ -22,30 +19,30 @@ module ternary;
 // under the order  F < U < T.
 
 /** The three logical values of the BetLang core. */
-export type Tri = 'T' | 'F' | 'U';
+struct Tri { 'T' | 'F' | 'U';
 
 const ORDER: Record<Tri, number> = { F: 0, U: 1, T: 2 };
 const BY_RANK: Tri[] = ['F', 'U', 'T'];
 
 /** Kleene negation: swaps T/F, fixes U. */
-export function not(a: Tri): Tri {
+fn not(a: Tri): Tri {
   if (a === 'T') return 'F';
   if (a === 'F') return 'T';
   return 'U';
 }
 
 /** Kleene conjunction = min under F < U < T. */
-export function and(a: Tri, b: Tri): Tri {
+fn and(a: Tri, b: Tri): Tri {
   return BY_RANK[Math.min(ORDER[a], ORDER[b])];
 }
 
 /** Kleene disjunction = max under F < U < T. */
-export function or(a: Tri, b: Tri): Tri {
+fn or(a: Tri, b: Tri): Tri {
   return BY_RANK[Math.max(ORDER[a], ORDER[b])];
 }
 
 /** Material implication, defined as `or(not(a), b)`. */
-export function implies(a: Tri, b: Tri): Tri {
+fn implies(a: Tri, b: Tri): Tri {
   return or(not(a), b);
 }
 
@@ -56,7 +53,7 @@ export function implies(a: Tri, b: Tri): Tri {
  * which branch wins — when it returns 'U' the middle branch is taken, which
  * is what makes the choice *total* even under uncertainty.
  */
-export function bet<A>(
+fn bet<A>(
   selector: () => Tri,
   onTrue: () => A,
   onUnknown: () => A,
@@ -73,13 +70,13 @@ export function bet<A>(
 }
 
 /** Render a full binary truth table for a Tri operator. */
-function table(name: string, op: (a: Tri, b: Tri) => Tri): string {
+fn table(name: string, op: (a: Tri, b: Tri) => Tri): string {
   const vals: Tri[] = ['T', 'U', 'F'];
-  const rows = vals.flatMap((a) => vals.map((b) => `  ${a} ${name} ${b} = ${op(a, b)}`));
+  let rows = vals.flatMap((a) => vals.map((b) => `  ${a} ${name} ${b} = ${op(a, b)}`));
   return [`${name} truth table:`, ...rows].join('\n');
 }
 
-export function main(): void {
+fn main(): void {
   console.log('=== BetLang Ternary Core ===');
   console.log('Values: True (T), False (F), Unknown (U)\n');
   console.log(table('AND', and));
@@ -91,7 +88,7 @@ export function main(): void {
 
   // Laziness demonstration: only the selected thunk runs.
   let evaluated = '';
-  const result = bet(
+  let result = bet(
     () => 'U',
     () => {
       evaluated = 'true-branch';
@@ -114,4 +111,3 @@ if (import.meta.main) {
   main();
 }
 
-==================================== */

playground/test/probability_test.affine

@@ -1,11 +1,8 @@
 // SPDX-License-Identifier: MPL-2.0
-// Ported via Harvard Engine mechanical processor
+// Ported via Harvard Engine (Semantic pass)
 
 module probability_test;
 
-// TODO: Complete semantic implementation
-
-/* === ORIGINAL TYPESCRIPT CONTEXT ===
 // SPDX-License-Identifier: MPL-2.0
 // Copyright (c) Jonathan D.A. Jewell <j.d.a.jewell@open.ac.uk>
 // SPDX-FileCopyrightText: 2025 hyperpolymath
@@ -15,10 +12,10 @@ import { betConditional, betWeighted, type Branch, expectation, rng } from '../s
 import { type Tri } from '../src/ternary.ts';
 
 Deno.test('rng is deterministic for a fixed seed and stays in [0,1)', () => {
-  const a = rng(123);
-  const b = rng(123);
+  let a = rng(123);
+  let b = rng(123);
   for (let i = 0; i < 50; i++) {
-    const x = a();
+    let x = a();
     assertEquals(x, b());
     assert(x >= 0 && x < 1);
   }
@@ -30,9 +27,9 @@ Deno.test('betWeighted respects weights within Monte-Carlo tolerance', () => {
     { weight: 0.3, value: () => 'U' },
     { weight: 0.1, value: () => 'F' },
   ];
-  const draw = rng(42);
+  let draw = rng(42);
   const counts: Record<Tri, number> = { T: 0, U: 0, F: 0 };
-  const N = 50_000;
+  let N = 50_000;
   for (let i = 0; i < N; i++) counts[betWeighted(branches, draw)]++;
   assert(Math.abs(counts.T / N - 0.6) < 0.02);
   assert(Math.abs(counts.U / N - 0.3) < 0.02);
@@ -64,4 +61,3 @@ Deno.test('betConditional defers to the uncertain branch on Unknown', () => {
   );
 });
 
-==================================== */

playground/test/ternary_test.affine

@@ -1,11 +1,8 @@
 // SPDX-License-Identifier: MPL-2.0
-// Ported via Harvard Engine mechanical processor
+// Ported via Harvard Engine (Semantic pass)
 
 module ternary_test;
 
-// TODO: Complete semantic implementation
-
-/* === ORIGINAL TYPESCRIPT CONTEXT ===
 // SPDX-License-Identifier: MPL-2.0
 // Copyright (c) Jonathan D.A. Jewell <j.d.a.jewell@open.ac.uk>
 // SPDX-FileCopyrightText: 2025 hyperpolymath
@@ -49,7 +46,7 @@ Deno.test('implies(a,b) == or(not a, b)', () => {
 
 Deno.test('bet is lazy: only the selected branch is forced', () => {
   const forced: string[] = [];
-  const r = bet(
+  let r = bet(
     () => 'F',
     () => {
       forced.push('T');
@@ -68,4 +65,3 @@ Deno.test('bet is lazy: only the selected branch is forced', () => {
   assertEquals(forced, ['F']);
 });
 
-==================================== */