Use rng initialized with seedrandom (alea)

packages/squiggle-lang/__tests__/dist/Dotwise_test.ts

@@ -1,4 +1,5 @@
 import * as fc from "fast-check";
+import seedrandom from "seedrandom";
 
 import { binaryOperations } from "../../src/dist/distOperations/index.js";
 import { DivisionByZeroError } from "../../src/operationError.js";
@@ -9,6 +10,8 @@ import {
   unpackResult,
 } from "../helpers/distHelpers.js";
 
+const rng = seedrandom();
+
 describe("dotSubtract", () => {
   test("mean of normal minus exponential (unit)", () => {
     const mean = 0;
@@ -17,7 +20,7 @@ describe("dotSubtract", () => {
       binaryOperations.pointwiseSubtract(
         mkNormal(mean, 1.0),
         mkExponential(rate),
-        { env }
+        { env, rng }
       )
     );
     const meanValue = dotDifference.mean();
@@ -38,7 +41,7 @@ describe("dotSubtract", () => {
           const dotDifferenceR = binaryOperations.pointwiseSubtract(
             mkNormal(mean, 1.0),
             mkExponential(rate),
-            { env }
+            { env, rng }
           );
           if (!dotDifferenceR.ok) {
             const err = dotDifferenceR.value;

packages/squiggle-lang/__tests__/dist/GenericDist_test.ts

@@ -1,3 +1,5 @@
+import seedrandom from "seedrandom";
+
 import { BaseDist } from "../../src/dist/BaseDist.js";
 import { DistError } from "../../src/dist/DistError.js";
 import { SampleSetDist } from "../../src/dist/SampleSetDist/index.js";
@@ -22,6 +24,7 @@ const env: Env = {
   sampleCount: 100,
   xyPointLength: 100,
 };
+const rng = seedrandom();
 
 describe("toPointSet", () => {
   test("on symbolic normal distribution", () => {
@@ -35,7 +38,7 @@ describe("toPointSet", () => {
   const pointSet = unpackResult(
     Result.bind(
       Result.bind(normalDist5.toPointSetDist(env), (pointSet) =>
-        SampleSetDist.fromDist(pointSet, env)
+        SampleSetDist.fromDist(pointSet, env, rng)
       ),
       (sampleSet) => sampleSet.toPointSetDist(env)
     )

packages/squiggle-lang/__tests__/dist/Invariants/AlgebraicCombination_test.ts

@@ -5,6 +5,8 @@ when things substantially change.
 Also, there are some open comments in https://github.com/quantified-uncertainty/squiggle/pull/232 that haven't been addressed.
 */
 
+import seedrandom from "seedrandom";
+
 import { binaryOperations } from "../../../src/dist/distOperations/index.js";
 import * as Result from "../../../src/utility/result.js";
 import {
@@ -16,27 +18,30 @@ import {
 } from "../../fixtures/distFixtures.js";
 import { env, unpackResult } from "../../helpers/distHelpers.js";
 
+const rng = seedrandom();
 const { algebraicAdd } = binaryOperations;
 
 describe("(Algebraic) addition of distributions", () => {
   describe("mean", () => {
     test("normal(mean=5) + normal(mean=20)", () => {
       expect(
-        unpackResult(algebraicAdd(normalDist5, normalDist20, { env })).mean()
+        unpackResult(
+          algebraicAdd(normalDist5, normalDist20, { env, rng })
+        ).mean()
       ).toBe(2.5e1);
     });
 
     test("uniform(low=9, high=10) + beta(alpha=2, beta=5)", () => {
       const received = unpackResult(
-        algebraicAdd(uniformDist, betaDist, { env })
+        algebraicAdd(uniformDist, betaDist, { env, rng })
       ).mean();
       // This is nondeterministic, we could be in a situation where ci fails but you click rerun and it passes, which is bad.
       // sometimes it works with ~digits=2.
       expect(received).toBeCloseTo(9.786831807237022, 1); // (uniformMean +. betaMean)
     });
     test("beta(alpha=2, beta=5) + uniform(low=9, high=10)", () => {
       const received = unpackResult(
-        algebraicAdd(betaDist, uniformDist, { env })
+        algebraicAdd(betaDist, uniformDist, { env, rng })
       ).mean();
 
       // This is nondeterministic, we could be in a situation where ci fails but you click rerun and it passes, which is bad.
@@ -51,8 +56,9 @@ describe("(Algebraic) addition of distributions", () => {
       (x) => {
         const received = unpackResult(normalDist10.pdf(x)); // this should be normal(10, sqrt(8))
         const calculated: number = unpackResult(
-          Result.bind(algebraicAdd(normalDist5, normalDist5, { env }), (d) =>
-            d.pdf(x, { env })
+          Result.bind(
+            algebraicAdd(normalDist5, normalDist5, { env, rng }),
+            (d) => d.pdf(x, { env })
           )
         );
 
@@ -63,16 +69,17 @@ describe("(Algebraic) addition of distributions", () => {
     test("(normal(mean=10) + normal(mean=10)).pdf(1.9e1)", () => {
       const received = unpackResult(normalDist20.pdf(1.9e1));
       const calculated: number = unpackResult(
-        Result.bind(algebraicAdd(normalDist10, normalDist10, { env }), (d) =>
-          d.pdf(1.9e1, { env })
+        Result.bind(
+          algebraicAdd(normalDist10, normalDist10, { env, rng }),
+          (d) => d.pdf(1.9e1, { env })
         )
       );
 
       expect(received).toBeCloseTo(calculated, 1);
     });
     test("(uniform(low=9, high=10) + beta(alpha=2, beta=5)).pdf(10)", () => {
       const received: number = unpackResult(
-        Result.bind(algebraicAdd(uniformDist, betaDist, { env }), (d) =>
+        Result.bind(algebraicAdd(uniformDist, betaDist, { env, rng }), (d) =>
           d.pdf(1e1, { env })
         )
       );
@@ -84,7 +91,7 @@ describe("(Algebraic) addition of distributions", () => {
     });
     test("(beta(alpha=2, beta=5) + uniform(low=9, high=10)).pdf(10)", () => {
       const received = unpackResult(
-        Result.bind(algebraicAdd(betaDist, uniformDist, { env }), (d) =>
+        Result.bind(algebraicAdd(betaDist, uniformDist, { env, rng }), (d) =>
           d.pdf(1e1, { env })
         )
       );
@@ -99,7 +106,7 @@ describe("(Algebraic) addition of distributions", () => {
       (x) => {
         const received = normalDist10.cdf(x);
         const calculated = unpackResult(
-          algebraicAdd(normalDist5, normalDist5, { env })
+          algebraicAdd(normalDist5, normalDist5, { env, rng })
         ).cdf(x);
 
         expect(received).toBeCloseTo(calculated, 0);
@@ -110,14 +117,14 @@ describe("(Algebraic) addition of distributions", () => {
       const received = normalDist20.cdf(1.25e1);
 
       const calculated = unpackResult(
-        algebraicAdd(normalDist10, normalDist10, { env })
+        algebraicAdd(normalDist10, normalDist10, { env, rng })
       ).cdf(1.25e1);
 
       expect(received).toBeCloseTo(calculated, 2);
     });
     test("(uniform(low=9, high=10) + beta(alpha=2, beta=5)).cdf(10)", () => {
       const received = unpackResult(
-        algebraicAdd(uniformDist, betaDist, { env })
+        algebraicAdd(uniformDist, betaDist, { env, rng })
       ).cdf(1e1);
 
       // This is nondeterministic, we could be in a situation where ci fails but you click rerun and it passes, which is bad.
@@ -126,7 +133,7 @@ describe("(Algebraic) addition of distributions", () => {
     });
     test("(beta(alpha=2, beta=5) + uniform(low=9, high=10)).cdf(10)", () => {
       const received = unpackResult(
-        algebraicAdd(betaDist, uniformDist, { env })
+        algebraicAdd(betaDist, uniformDist, { env, rng })
       ).cdf(1e1);
 
       // This is nondeterministic, we could be in a situation where ci fails but you click rerun and it passes, which is bad.
@@ -142,7 +149,7 @@ describe("(Algebraic) addition of distributions", () => {
         const received = normalDist10.inv(x);
 
         const calculated = unpackResult(
-          algebraicAdd(normalDist5, normalDist5, { env })
+          algebraicAdd(normalDist5, normalDist5, { env, rng })
         ).inv(x);
 
         expect(received).toBeCloseTo(calculated, -1);
@@ -152,14 +159,14 @@ describe("(Algebraic) addition of distributions", () => {
       const received = normalDist20.inv(1e-1);
 
       const calculated = unpackResult(
-        algebraicAdd(normalDist10, normalDist10, { env })
+        algebraicAdd(normalDist10, normalDist10, { env, rng })
       ).inv(1e-1);
 
       expect(received).toBeCloseTo(calculated, -1);
     });
     test("(uniform(low=9, high=10) + beta(alpha=2, beta=5)).inv(2e-2)", () => {
       const received = unpackResult(
-        algebraicAdd(uniformDist, betaDist, { env })
+        algebraicAdd(uniformDist, betaDist, { env, rng })
       ).inv(2e-2);
 
       // This is nondeterministic, we could be in a situation where ci fails but you click rerun and it passes, which is bad.
@@ -168,7 +175,7 @@ describe("(Algebraic) addition of distributions", () => {
     });
     test("(beta(alpha=2, beta=5) + uniform(low=9, high=10)).inv(2e-2)", () => {
       const received = unpackResult(
-        algebraicAdd(betaDist, uniformDist, { env })
+        algebraicAdd(betaDist, uniformDist, { env, rng })
       ).inv(2e-2);
 
       // This is nondeterministic, we could be in a situation where ci fails but you click rerun and it passes, which is bad.

packages/squiggle-lang/__tests__/dist/Invariants/Means_test.ts

@@ -8,6 +8,8 @@ Details in https://squiggle-language.com/docs/internal/invariants/
 Note: epsilon of 1e3 means the invariants are, in general, not being satisfied. 
 */
 
+import seedrandom from "seedrandom";
+
 import { BaseDist } from "../../../src/dist/BaseDist.js";
 import {
   BinaryOperation,
@@ -28,6 +30,7 @@ import {
 import { expectErrorToBeBounded } from "../../helpers/helpers.js";
 
 const epsilon = 5e1;
+const rng = seedrandom();
 
 const distributions = [
   mkNormal(4, 1),
@@ -58,7 +61,7 @@ const testOperationMean = (
   dist2: BaseDist,
   { epsilon, env }: { epsilon: number; env: Env }
 ) => {
-  const received = unpackResult(distOp(dist1, dist2, { env })).mean();
+  const received = unpackResult(distOp(dist1, dist2, { env, rng })).mean();
 
   const expected = floatOp(dist1.mean(), dist2.mean());
 

packages/squiggle-lang/__tests__/dist/Mixture_test.ts

@@ -1,3 +1,5 @@
+import seedrandom from "seedrandom";
+
 import { mixture } from "../../src/dist/distOperations/index.js";
 import {
   env,
@@ -9,6 +11,8 @@ import {
   unpackResult,
 } from "../helpers/distHelpers.js";
 
+const rng = seedrandom();
+
 describe("mixture", () => {
   test.each([
     [0.0, 1e2],
@@ -23,7 +27,7 @@ describe("mixture", () => {
           [mkNormal(mean1, 9e-1), 0.5],
           [mkNormal(mean2, 9e-1), 0.5],
         ],
-        { env }
+        { env, rng }
       )
     ).mean();
     expect(meanValue).toBeCloseTo((mean1 + mean2) / 2, -1);
@@ -45,7 +49,7 @@ describe("mixture", () => {
           [mkBeta(alpha, beta), betaWeight],
           [mkExponential(rate), exponentialWeight],
         ],
-        { env }
+        { env, rng }
       )
     ).mean();
     const betaMean = 1 / (1 + beta / alpha);
@@ -81,7 +85,7 @@ describe("mixture", () => {
             [mkUniform(low, high), uniformWeight],
             [mkLognormal(mu, sigma), lognormalWeight],
           ],
-          { env }
+          { env, rng }
         )
       ).mean();
       const uniformMean = (low + high) / 2;

packages/squiggle-lang/__tests__/dist/Scoring/KlDivergence_test.ts

@@ -1,3 +1,4 @@
+import seedrandom from "seedrandom";
 import { BaseDist } from "../../../src/dist/BaseDist.js";
 import { distErrorToString } from "../../../src/dist/DistError.js";
 import {
@@ -20,6 +21,8 @@ import {
   unpackResult,
 } from "../../helpers/distHelpers.js";
 
+const rng = seedrandom();
+
 const klDivergence = (prediction: BaseDist, answer: BaseDist): number => {
   const result = logScoreDistAnswer({
     estimate: prediction,
@@ -106,7 +109,7 @@ describe("klDivergence: discrete -> discrete -> float", () => {
         [point1, 1],
         [point2, 1],
       ],
-      { env }
+      { env, rng }
     )
   );
   const b = unpackResult(
@@ -116,7 +119,7 @@ describe("klDivergence: discrete -> discrete -> float", () => {
         [point2, 1],
         [point3, 1],
       ],
-      { env }
+      { env, rng }
     )
   );
 
@@ -143,7 +146,7 @@ describe("klDivergence: mixed -> mixed -> float", () => {
         [point1, 1.0],
         [uniformDist, 1.0],
       ],
-      { env }
+      { env, rng }
     )
   );
   const b = unpackResult(
@@ -153,7 +156,7 @@ describe("klDivergence: mixed -> mixed -> float", () => {
         [floatDist, 1.0],
         [normalDist10, 1.0],
       ],
-      { env }
+      { env, rng }
     )
   );
   const c = unpackResult(
@@ -164,7 +167,7 @@ describe("klDivergence: mixed -> mixed -> float", () => {
         [point3, 1.0],
         [uniformDist, 1.0],
       ],
-      { env }
+      { env, rng }
     )
   );
   const d = unpackResult(
@@ -176,7 +179,7 @@ describe("klDivergence: mixed -> mixed -> float", () => {
         [floatDist, 1.0],
         [uniformDist2, 1.0],
       ],
-      { env }
+      { env, rng }
     )
   );
 

packages/squiggle-lang/__tests__/dist/Scoring/WithScalarAnswer_test.ts

@@ -1,9 +1,13 @@
+import seedrandom from "seedrandom";
+
 import {
   logScoreScalarAnswer,
   mixture,
 } from "../../../src/dist/distOperations/index.js";
 import { env, mkPointMass, unpackResult } from "../../helpers/distHelpers.js";
 
+const rng = seedrandom();
+
 describe("WithScalarAnswer: discrete -> scalar -> score", () => {
   const pointA = mkPointMass(3.0);
   const pointB = mkPointMass(2.0);
@@ -19,7 +23,7 @@ describe("WithScalarAnswer: discrete -> scalar -> score", () => {
           [pointC, 0.25],
           [pointD, 0.25],
         ],
-        { env }
+        { env, rng }
       )
     );
 
@@ -42,7 +46,7 @@ describe("WithScalarAnswer: discrete -> scalar -> score", () => {
           [pointA, 0.75],
           [pointB, 0.25],
         ],
-        { env }
+        { env, rng }
       )
     );
 
@@ -65,7 +69,7 @@ describe("WithScalarAnswer: discrete -> scalar -> score", () => {
           [pointA, 0.5],
           [pointB, 0.5],
         ],
-        { env }
+        { env, rng }
       )
     );
     const prediction = unpackResult(
@@ -74,7 +78,7 @@ describe("WithScalarAnswer: discrete -> scalar -> score", () => {
           [pointA, 0.75],
           [pointB, 0.25],
         ],
-        { env }
+        { env, rng }
       )
     );