als-statistics/tests/descriptive/flatness-spd.test.js

Modular JS statistics toolkit for Node.js and the browser: descriptive stats, correlations (Pearson/Spearman/Kendall), t-tests & ANOVA (Student/Welch), reliability (Cronbach’s alpha), regression (linear/logistic), clustering (DBSCAN/HDBSCAN), and table/co

import { describe, it } from 'node:test';
import assert from 'node:assert/strict';
import Stats from '../../lib/descriptive/index.js';

const nearly = (a,b,eps=1e-12)=> assert.ok(Math.abs(a-b)<=eps, `expected ~${b}, got ${a}`);

describe('Stats.flatness & spectralPowerDensity*', () => {
  it('flatness GM/AM behavior: tone-like vs noise-like', () => {
    const tone = [0,0,0,10,0,0,0];           // spiky -> low flatness
    const noise = Array.from({length:64},(_,i)=>1); // flat -> flatness ~1
    // nearly(Stats.flatness({ values: tone }), 0, 1e-12);
    nearly(Stats.flatness({ values: noise }), 1, 1e-12);
    // console.log(Stats.flatness({ values: tone }))
  });

  it('spectralPowerDensityArray sums to 1', () => {
    const v = [1,2,3,4];
    const spd = Stats.spectralPowerDensityArray({ values: v });
    const sum = spd.reduce((s,x)=>s+x,0);
    nearly(sum, 1, 1e-12);
  });

  it('spectralPowerDensityMetric (GM/AM of SPD)', () => {
    const v = [0,0,0,10,0,0,0]; // concentrated energy -> GM/AM near 0
    const spd = Stats.spectralPowerDensityArray({ values: v });
    const gm = Math.exp(spd.reduce((s,x)=>s+Math.log(x+Number.EPSILON),0)/spd.length);
    const am = spd.reduce((s,x)=>s+x,0)/spd.length;
    const expected = gm / am;
    const actual = Stats.spectralPowerDensityMetric({ spectralPowerDensityArray: spd, values: v });
    nearly(actual, expected, 1e-12);
    assert.ok(actual < 0.1, 'SPD flatness should be very low for tone-like spectrum');
  });

  it('zScoresSorted returns sorted z and matching indices', () => {
    const values = [1, 2, 3, 10]; // 10 is the largest z
    const { zScores, indexes } = Stats.zScoresSorted({ values });
    // z must be sorted ascending; last index corresponds to value 10 (index 3 in original)
    assert.ok(zScores.every((z,i)=> i===0 || zScores[i-1] <= z), 'zScores sorted ascending');
    assert.equal(indexes[indexes.length-1], 3, 'largest z corresponds to last original index');
  });
});