Scoring refactoring

.changeset/bright-yaks-fold.md

@@ -0,0 +1,5 @@
+---
+"@quri/squiggle-lang": patch
+---
+
+Breaking: Replaces Dist.logScore with Dist.logScoreDistAnswer and Dist.logScoreScalarAnswer

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

@@ -1,9 +1,6 @@
 import { BaseDist } from "../../../src/dist/BaseDist.js";
-import { distErrorToString } from "../../../src/dist/DistError.js";
-import {
-  logScoreDistAnswer,
-  mixture,
-} from "../../../src/dist/distOperations/index.js";
+import { mixture } from "../../../src/dist/distOperations/index.js";
+import { logScoreDistAnswer } from "../../../src/fr/scoring.js";
 import { getDefaultRng } from "../../../src/rng/index.js";
 import {
   floatDist,
@@ -23,19 +20,12 @@ import {
 
 const rng = getDefaultRng();
 
-const klDivergence = (prediction: BaseDist, answer: BaseDist): number => {
-  const result = logScoreDistAnswer({
+const klDivergence = (prediction: BaseDist, answer: BaseDist): number =>
+  logScoreDistAnswer({
     estimate: prediction,
     answer,
-    prior: undefined,
     env,
-  });
-  if (!result.ok) {
-    console.log(distErrorToString(result.value));
-    throw new Error("logScore failed");
-  }
-  return result.value;
-};
+  }).integralSum();
 
 // integral from low to high of 1 / (high - low) log(normal(mean, stdev)(x) / (1 / (high - low))) dx
 const klNormalUniform = (

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

@@ -1,7 +1,5 @@
-import {
-  logScoreScalarAnswer,
-  mixture,
-} from "../../../src/dist/distOperations/index.js";
+import { mixture } from "../../../src/dist/distOperations/index.js";
+import { logScoreScalarAnswer } from "../../../src/dist/scoring/ScalarAnswer.js";
 import { getDefaultRng } from "../../../src/rng/index.js";
 import { env, mkPointMass, unpackResult } from "../../helpers/distHelpers.js";
 
@@ -27,14 +25,11 @@ describe("WithScalarAnswer: discrete -> scalar -> score", () => {
     );
 
     const answer = 2.0; // So this is: assigning 100% probability to 2.0
-    const x = unpackResult(
-      logScoreScalarAnswer({
-        estimate: prediction,
-        answer,
-        prior: undefined,
-        env,
-      })
-    );
+    const x = logScoreScalarAnswer({
+      estimate: prediction,
+      answer,
+      env,
+    }).getOrThrow().discrete;
     expect(x).toEqual(-Math.log(0.25 / 1.0));
   });
 
@@ -54,42 +49,12 @@ describe("WithScalarAnswer: discrete -> scalar -> score", () => {
       logScoreScalarAnswer({
         estimate: prediction,
         answer,
-        prior: undefined,
-        env,
-      })
-    );
-    expect(x).toEqual(-Math.log(0.75 / 1.0));
-  });
-
-  test("scoreWithPrior: agrees with analytical answer when finite", () => {
-    const prior = unpackResult(
-      mixture(
-        [
-          [pointA, 0.5],
-          [pointB, 0.5],
-        ],
-        { env, rng }
-      )
-    );
-    const prediction = unpackResult(
-      mixture(
-        [
-          [pointA, 0.75],
-          [pointB, 0.25],
-        ],
-        { env, rng }
-      )
-    );
-
-    const answer = 3.0; // So this is: assigning 100% probability to 2.0
-    const x = unpackResult(
-      logScoreScalarAnswer({
-        estimate: prediction,
-        answer,
-        prior,
         env,
       })
     );
-    expect(x).toEqual(-Math.log(0.75 / 1.0) - -Math.log(0.5 / 1.0));
+    expect(x).toEqual({
+      continuous: Infinity,
+      discrete: -Math.log(0.75 / 1.0),
+    });
   });
 });

packages/squiggle-lang/__tests__/helpers/distHelpers.ts

@@ -6,7 +6,8 @@ export const env: Env = defaultEnv;
 
 export const unpackResult = <T>(x: Result.result<T, unknown>): T => {
   if (!x.ok) {
-    throw new Error("failed");
+    console.error(x.value);
+    throw new Error("unpacking failed");
   }
   return x.value;
 };

packages/squiggle-lang/__tests__/library/dist_test.ts

@@ -22,7 +22,7 @@ describe("Dist", () => {
     "[PointMass(4),PointMass(-2)]"
   );
   testEvalToBe(
-    "Dist.logScore({estimate: mx(Sym.normal(5,2), Sym.uniform(-1000, 1000), [.5, .5]), answer: Sym.normal(5.2,2.2)})",
-    "0.5787500741731704"
+    "Dist.logScoreDistAnswer(mx(Sym.normal(5,2), Sym.uniform(-1000, 1000), [.5, .5]), Sym.normal(5.2,2.2))",
+    "{score: 0.5787500741731704, shape: Point Set Distribution}"
   );
 });

packages/squiggle-lang/__tests__/library/scoring_test.ts

@@ -2,15 +2,11 @@ import { testEvalToBe } from "../helpers/reducerHelpers.js";
 
 describe("Scoring", () => {
   testEvalToBe(
-    "Dist.logScore({estimate: Sym.normal(5,2), answer: Sym.normal(5.2,1), prior: Sym.normal(5.5,3)})",
-    "-0.33591375663884876"
-  );
-  testEvalToBe(
-    "Dist.logScore({estimate: Sym.normal(5,2), answer: Sym.normal(5.2,1)})",
+    "Dist.logScoreDistAnswer(Sym.normal(5,2), Sym.normal(5.2,1)).score",
     "0.32244107041564646"
   );
   testEvalToBe(
-    "Dist.logScore({estimate: Sym.normal(5,2), answer: 4.5})",
+    "Dist.logScoreNumericAnswer(Sym.normal(5,2), 4.5).continuous",
     "1.6433360626394853"
   );
   testEvalToBe(

packages/squiggle-lang/src/PointSet/Continuous.ts

@@ -122,13 +122,19 @@ export class ContinuousShape implements PointSet<ContinuousShape> {
   }
 
   xToY(f: number) {
-    switch (this.interpolation) {
-      case "Stepwise":
-        return MixedPoint.makeContinuous(
-          XYShape.XtoY.stepwiseIncremental(this.xyShape, f) ?? 0
-        );
-      case "Linear":
-        return MixedPoint.makeContinuous(XYShape.XtoY.linear(this.xyShape, f));
+    if (this.xyShape.xs.length === 0) {
+      return MixedPoint.makeContinuous(0);
+    } else {
+      switch (this.interpolation) {
+        case "Stepwise":
+          return MixedPoint.makeContinuous(
+            XYShape.XtoY.stepwiseIncremental(this.xyShape, f) ?? 0
+          );
+        case "Linear":
+          return MixedPoint.makeContinuous(
+            XYShape.XtoY.linear(this.xyShape, f)
+          );
+      }
     }
   }
 

packages/squiggle-lang/src/dist/distOperations/index.ts

@@ -1,5 +1,4 @@
 export { type BinaryOperation, binaryOperations } from "./binaryOperations.js";
-export { logScoreDistAnswer, logScoreScalarAnswer } from "./logScore.js";
 export { mixture } from "./mixture.js";
 export { pointwiseCombinationFloat } from "./pointwiseCombination.js";
 export { scaleLog, scaleLogWithThreshold } from "./scaleOperations.js";