import * as ss from "../index.js";
ss.addToMean(14, 5, 53); ss.combineMeans(5, 3, 4, 3); ss.combineVariances(14 / 3, 5, 3, 8 / 3, 4, 3); ss.geometricMean([1.8, 1.166666, 1.428571]);ss.harmonicMean([2, 3]).toFixed(2); ss.mean([0, 10]); ss.median([10, 2, 5, 100, 2, 1]); ss.medianSorted([10, 2, 5, 100, 2, 1]);
var bayes = new ss.BayesianClassifier();bayes.train({ species: "Cat" }, "animal");bayes.score({ species: "Cat" }); bayes.score({ foo: "foo" });
ss.bernoulliDistribution(0.3); ss.bisect(Math.cos, 0, 4, 100, 0.003);
var data1019 = [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3];ss.chiSquaredGoodnessOfFit(data1019, ss.poissonDistribution, 0.05); ss.chiSquaredDistributionTable[60][0.99];ss.chunk([1, 2, 3, 4, 5, 6], 2);ss.ckmeans([-1, 2, -1, 2, 4, 5, 6, -1, 2, -1], 3);ss.combinationsReplacement([1, 2], 2); ss.combinations([1, 2, 3], 2); ss.equalIntervalBreaks([1, 2, 3, 4, 5, 6], 4); ss.errorFunction(1).toFixed(2); ss.epsilon;ss.factorial(5); ss.interquartileRange([0, 1, 2, 3]); var l = ss.linearRegressionLine( ss.linearRegression([ [0, 0], [1, 1] ]));l(0); l(2); ss.linearRegressionLine({ b: 0, m: 1 })(1); ss.linearRegressionLine({ b: 1, m: 1 })(1); ss.linearRegression([ [0, 0], [1, 1]]); ss.max([1, 2, 3, 4]);ss.maxSorted([-100, -10, 1, 2, 5]); ss.min([1, 5, -10, 100, 2]); ss.minSorted([-100, -10, 1, 2, 5]); ss.mean([0, 10]); ss.medianAbsoluteDeviation([1, 1, 2, 2, 4, 6, 9]); ss.medianSorted([10, 2, 5, 100, 2, 1]); ss.median([10, 2, 5, 100, 2, 1]); ss.modeFast(["rabbits", "rabbits", "squirrels"]); ss.mode([0, 0, 1]); ss.modeSorted([0, 0, 1]); ss.numericSort([3, 2, 1]);
var p = new ss.PerceptronModel();for (var i = 0; i < 5; i++) { p.train([1, 1], 1); p.train([0, 1], 0); p.train([1, 0], 0); p.train([0, 0], 0);}p.predict([0, 0]); p.predict([0, 1]); p.predict([1, 0]); p.predict([1, 1]); ss.product([1, 2, 3, 4]); ss.quantileSorted([3, 6, 7, 8, 8, 9, 10, 13, 15, 16, 20], 0.5); ss.quantile([3, 6, 7, 8, 8, 9, 10, 13, 15, 16, 20], 0.5); ss.quantile([3, 6, 7, 8, 8, 9, 10, 13, 15, 16, 20], [0.5, 0.6, 0.7]);var arr = [65, 28, 59, 33, 21, 56, 22, 95, 50, 12, 90, 53, 28, 77, 39];ss.quickselect(arr, 8);var samples = [ [0, 0], [1, 1]];var regressionLine = ss.linearRegressionLine(ss.linearRegression(samples));ss.rSquared(samples, regressionLine); ss.rootMeanSquare([-1, 1, -1, 1]); ss.sampleCorrelation([1, 2, 3, 4, 5, 6], [2, 2, 3, 4, 5, 60]).toFixed(2);ss.sampleCovariance([1, 2, 3, 4, 5, 6], [6, 5, 4, 3, 2, 1]); ss.sampleKurtosis([1, 2, 2, 3, 5]); ss.sampleSkewness([2, 4, 6, 3, 1]); ss.sampleStandardDeviation([2, 4, 4, 4, 5, 5, 7, 9]).toFixed(2);ss.sampleVariance([1, 2, 3, 4, 5]); ss.sampleWithReplacement([1, 2, 3, 4], 2);ss.sampleWithReplacement([1, 2, 3, 4], 2, Math.random);ss.sampleWithReplacement([1, 2, 3, 4], 2, () => 10);ss.shuffleInPlace([1, 2, 3, 4]);ss.shuffleInPlace([1, 2, 3, 4], Math.random);ss.shuffleInPlace([1, 2, 3, 4], () => 2);ss.shuffle([1, 2, 3, 4]);ss.sign(2); ss.variance([2, 4, 4, 4, 5, 5, 7, 9]); ss.standardDeviation([2, 4, 4, 4, 5, 5, 7, 9]); ss.subtractFromMean(20.5, 6, 53); ss.sumNthPowerDeviations([1, 2, 3]);ss.sumSimple([1, 2, 3]); ss.sum([1, 2, 3]); ss.tTestTwoSample([1, 2, 3, 4], [3, 4, 5, 6], 0); ss.tTest([1, 2, 3, 4, 5, 6], 3.385).toFixed(2); ss.uniqueCountSorted([1, 2, 3]); ss.uniqueCountSorted([1, 1, 1]); ss.variance([1, 2, 3, 4, 5, 6]); ss.zScore(78, 80, 5);