mirror of
https://github.com/MBombeck/HealthLog.git
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Marc-André Bombeck
11e35a6ba1
The feature extraction, the signals of the day, the status cards, the graded series, the Coach snapshot, the mood correlations and the report's trend arrow each still averaged pulse over its readings, so a dense workout hour decided the day and a workout day the window. They now read a pulse day as the mean of its hours' means and a window as the mean of its days, through the day-mean helper. Counts, extremes and spreads stay over every reading; every other type is unchanged.
76 lines
2.5 KiB
TypeScript
76 lines
2.5 KiB
TypeScript
/**
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* The full-history pulse mean the insight features carry (`allTimeAvg`) is the
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* mean of the day values, each day the mean of its hours' means, like every
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* other pulse mean (`day-mean.ts`). Count-weighted, a workout day's dense hour
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* outweighed every resting hour of every other day.
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*
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* Two days: a workout hour of twelve readings at 150 and three resting hours
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* at 60 (day value 82.5), and a day with one reading at 60: 71.25. The same
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* readings as systolic pressure keep the plain mean (127.5) as the control.
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*/
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import { beforeAll, describe, expect, it } from "vitest";
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import { getPrismaClient, truncateAllTables } from "./setup";
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import type { Prisma } from "@/generated/prisma/client";
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import { readAllTimeExtremes } from "@/lib/insights/feature-blocks";
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const prisma = getPrismaClient();
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const USER = "feature-blocks-pulse-day";
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const DAY = 86_400_000;
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const now = new Date();
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const midnight = (daysAgo: number) =>
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Date.UTC(now.getUTCFullYear(), now.getUTCMonth(), now.getUTCDate()) -
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daysAgo * DAY;
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function readings(
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type: "PULSE" | "BLOOD_PRESSURE_SYS",
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unit: string,
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): Prisma.MeasurementCreateManyInput[] {
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const workout = midnight(40);
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const at: Array<[number, number]> = [];
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for (let i = 0; i < 12; i += 1) {
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at.push([workout + 10 * 3_600_000 + i * 300_000, 150]);
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}
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for (const h of [12, 14, 16]) at.push([workout + h * 3_600_000, 60]);
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at.push([midnight(39) + 8 * 3_600_000, 60]);
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return at.map(([ms, value], i) => ({
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id: `${USER}-${type}-${i}`,
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userId: USER,
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type,
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unit,
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source: "APPLE_HEALTH",
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value,
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measuredAt: new Date(ms),
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}));
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}
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beforeAll(async () => {
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await truncateAllTables(prisma);
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await prisma.user.create({ data: { id: USER, username: USER } });
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await prisma.measurement.createMany({
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data: [
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...readings("PULSE", "bpm"),
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...readings("BLOOD_PRESSURE_SYS", "mmHg"),
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],
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});
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}, 120_000);
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describe("readAllTimeExtremes", () => {
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it("gives pulse the mean of its days, each the mean of its hours", async () => {
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const out = await readAllTimeExtremes(USER, [
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"PULSE",
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"BLOOD_PRESSURE_SYS",
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]);
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const pulse = out.get("PULSE");
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expect(pulse?.mean).toBeCloseTo(71.25, 9);
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// The extremes stay over every reading.
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expect(pulse?.min).toBe(60);
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expect(pulse?.max).toBe(150);
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});
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it("keeps the plain mean of the readings for every other type", async () => {
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const out = await readAllTimeExtremes(USER, ["BLOOD_PRESSURE_SYS"]);
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expect(out.get("BLOOD_PRESSURE_SYS")?.mean).toBe(127.5);
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});
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});
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