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/* eslint no-shadow: 0 */
const test = require("tap").test;const ss = require("../");
// Data generated in R// sample:// X <- rnorm(50)// toString(X)//// density:// d <- density(X, from=-3, to=3, n=7, bw="nrd")// paste(paste("[", d$x, ", ", d$y, "]", sep=""), collapse=", ")const normallyDistributed = {    sample: [        -1.85884822191703, 0.602520739129486, 0.888077007699802,        -0.196371268020604, -0.261434475360111, -0.555806535734196,        -0.535685767427025, -0.805785306288279, -0.0542408941260752,        -1.99949822804059, -1.31781357407021, 0.551938395645566,        -0.243919697027738, -0.39133049951603, -0.0197245301228612,        -0.448827587584495, -1.28606487855844, 1.52470482345308,        -1.92242657930281, 1.50862845897339, 0.756698701211952,        1.03637617724389, 1.2724121144235, 0.227137867400568, 0.614194690129868,        2.03223772207173, -1.29814099266873, -0.474986717342843,        -0.153962343622878, -0.730739393654425, -1.12457125027309,        -0.444103197987559, 0.459771149889531, 0.445498717584673,        0.0736304465553301, 0.340392907537276, 0.807820303672019,        -0.0478512608947293, -0.485938052839795, -0.249702764311268,        0.847717867319239, -0.631380378496465, -1.23218376426349,        1.8274052037247, 0.303031661057796, 0.940686211521394,        -0.565932683487323, -0.793791866093677, -0.950742000255766,        -2.05768339176415    ],    density: [        [-3, 0.00622253574711248],        [-2, 0.0955008985482363],        [-1, 0.26278412857974],        [0, 0.35334369527338],        [1, 0.214348469979353],        [2, 0.0652701909587952],        [3, 0.00303679902517155]    ]};
test("kernel density estimation", function (t) {    t.test("default kernel and bandwidth", function (t) {        const kde = ss.kernelDensityEstimation(normallyDistributed.sample);        for (let i = 0; i < normallyDistributed.density.length; i++) {            const x = normallyDistributed.density[i][0];            const expected = normallyDistributed.density[i][1];            const actual = kde(x);            t.ok(                Math.abs(actual - expected) / expected < 0.1,                "density(" + x + ") = " + actual + " != " + expected            );        }        t.end();    });
    t.test("gaussian default kernel", function (t) {        t.same(            ss.kernelDensityEstimation(normallyDistributed.sample),            ss.kernelDensityEstimation(                normallyDistributed.sample,                "gaussian",                "nrd"            )        );        const SQRT_2PI = Math.sqrt(2 * Math.PI);        t.same(            ss.kernelDensityEstimation(normallyDistributed.sample),            ss.kernelDensityEstimation(                normallyDistributed.sample,                function (u) {                    return Math.exp(-0.5 * u * u) / SQRT_2PI;                }            )        );
        t.end();    });
    t.test("invalid kernel", function (t) {        t.throws(() => {            ss.kernelDensityEstimation(normallyDistributed.sample, "bz");        });        t.throws(() => {            ss.kernelDensityEstimation(                normallyDistributed.sample,                "gaussian",                "bz"            );        });        t.end();    });
    t.end();});