@jrc03c/js-math-tools/src/variance.test.mjs

some math tools for JS

import { abs } from "./abs.mjs"
import { DataFrame, Series } from "./dataframe/index.mjs"
import { expect, test } from "@jrc03c/fake-jest"
import { forEach } from "./for-each.mjs"
import { normal } from "./normal.mjs"
import { random } from "./random.mjs"
import { variance } from "./variance.mjs"

test("tests that variance can be correctly computed", () => {
  expect(abs(variance(normal(10000)) - 1)).toBeLessThan(0.05)
  expect(abs(variance(normal([10, 10, 10, 10])) - 1)).toBeLessThan(0.05)
  expect(abs(variance(random(10000)) - 0.084)).toBeLessThan(0.05)

  const a = new Series({ hello: normal(100) })
  expect(variance(a)).toBe(variance(a.values))

  const b = new DataFrame({ foo: normal(100), bar: normal(100) })
  expect(variance(b)).toBe(variance(b.values))

  expect(variance([2n, 3n, 4n, 5n, 6n])).toBe(variance([2, 3, 4, 5, 6]))

  const c = normal(100)
  c[0] = "uh-oh!"
  expect(variance(c)).toBeNaN()
  expect(variance(c, true)).not.toBeNaN()

  const wrongs = [
    0,
    1,
    2.3,
    -2.3,
    Infinity,
    -Infinity,
    NaN,
    "foo",
    true,
    false,
    null,
    undefined,
    Symbol.for("Hello, world!"),
    x => x,
    function (x) {
      return x
    },
    { hello: "world" },
  ]

  forEach(wrongs, item => {
    expect(() => variance(item)).toThrow()
  })
})