@ai-on-browser/data-analysis-models
Version:
Data analysis model package without any dependencies
42 lines (40 loc) • 987 B
JavaScript
/**
* Cosine interpolation
*/
export default class CosineInterpolation {
// http://paulbourke.net/miscellaneous/interpolation/
/**
* Fit model parameters.
* @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])
const m = (1 - Math.cos(p * Math.PI)) / 2
return (1 - m) * this._y[i - 1] + m * this._y[i]
}
}
return this._y[n - 1]
})
}
}