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@ai-on-browser/data-analysis-models

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Data analysis model package without any dependencies

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/** * Spherical linear interpolation */ export default class Slerp { // https://en.wikipedia.org/wiki/Slerp // http://marupeke296.com/DXG_No57_SheareLinearInterWithoutQu.html /** * @param {number} [o] Angle subtended by the arc */ constructor(o = 1) { this._o = o this._sino = Math.sin(this._o) } /** * Fit model. * @param {number[]} x Training data * @param {number[]} y Target values */ fit(x, y) { const d = x.map((v, i) => [v, y[i]]) d.sort((a, b) => a[0] - b[0]) this._x = d.map(v => v[0]) this._y = d.map(v => v[1]) } /** * Returns predicted interpolated values. * @param {number[]} target Sample data * @returns {number[]} Predicted values */ predict(target) { const n = this._x.length return target.map(t => { if (t <= this._x[0]) { return this._y[0] } else if (t >= this._x[n - 1]) { return this._y[n - 1] } for (let i = 1; i < n; i++) { if (t <= this._x[i]) { const p = (t - this._x[i - 1]) / (this._x[i] - this._x[i - 1]) if (this._o === 0) { return (1 - p) * this._y[i - 1] + p * this._y[i] } return ( (Math.sin((1 - p) * this._o) * this._y[i - 1] + Math.sin(p * this._o) * this._y[i]) / this._sino ) } } return this._y[n - 1] }) } }