add BigInt support to the normalize transform

closes #2154

Author: Fil

src/options.js

@@ -54,7 +54,7 @@ function maybeTypedMap(data, f, type) {
   return map(data, isNumberType(type) ? (d, i) => coerceNumber(f(d, i)) : f, type); // allow conversion from BigInt
 }
 
-function maybeTypedArrayify(data, type) {
+export function maybeTypedArrayify(data, type) {
   return type === undefined
     ? arrayify(data) // preserve undefined type
     : isArrowVector(data)

src/transforms/normalize.js

@@ -1,6 +1,6 @@
 import {extent, deviation, max, mean, median, min, sum} from "d3";
 import {defined} from "../defined.js";
-import {percentile, taker} from "../options.js";
+import {maybeTypedArrayify, percentile, taker} from "../options.js";
 import {mapX, mapY} from "./map.js";
 
 export function normalizeX(basis, options) {
@@ -43,7 +43,8 @@ export function normalize(basis) {
 function normalizeBasis(basis) {
   return {
     mapIndex(I, S, T) {
-      const b = +basis(I, S);
+      S = maybeTypedArrayify(S, Float64Array);
+      const b = basis(I, S);
       for (const i of I) {
         T[i] = S[i] === null ? NaN : S[i] / b;
       }

test/output/bigintNormalize.svg

@@ -25,3 +25,28 @@ export async function bigintOrdinal() {
 export async function bigintStack() {
   return Plot.barY(integers, {x: (d, i) => i % 5, y: "big1"}).plot();
 }
+
+async function olympiansByWeight() {
+  const olympians = await d3.csv<any>("data/athletes.csv", d3.autoType);
+  return d3
+    .bin()(olympians.map((d) => d.height))
+    .map((bin) => ({weightclass: bin.x0, count: BigInt(bin.length)}));
+}
+
+export async function bigintNormalize() {
+  return Plot.rectY(
+    d3.sort(await olympiansByWeight(), (d) => -d.count),
+    Plot.normalizeY({x: "weightclass", y: "count"})
+  ).plot();
+}
+
+export async function bigintNormalizeMean() {
+  return Plot.plot({
+    x: {interval: 0.05},
+    y: {label: "relative to mean"},
+    marks: [
+      Plot.barY(await olympiansByWeight(), Plot.normalizeY("mean", {x: "weightclass", y: "count"})),
+      Plot.ruleY([1], {stroke: "red"})
+    ]
+  });
+}

test/output/bigintNormalizeMean.svg

@@ -5,6 +5,10 @@ it("Plot.normalize first", () => {
   testNormalize([1, 2, 4, 5], "first", [1, 2, 4, 5]);
 });
 
+it("Plot.normalize first BigInt", () => {
+  testNormalize([1n, 2n, 4n, 5n], "first", [1, 2, 4, 5]);
+});
+
 it("Plot.normalize last", () => {
   testNormalize([1, 2, 4, 5], "last", [0.2, 0.4, 0.8, 1]);
 });
@@ -17,6 +21,10 @@ it("Plot.normalize median", () => {
   testNormalize([1, 2, 6, 6], "median", [0.25, 0.5, 1.5, 1.5]);
 });
 
+it("Plot.normalize median BigInt", () => {
+  testNormalize([1n, 2n, 6n, 6n], "median", [0.25, 0.5, 1.5, 1.5]);
+});
+
 it("Plot.normalize min", () => {
   testNormalize([10, 6, 2], "min", [5, 3, 1]);
 });