/**
 * Fits a smooth {@link AnimationCurve} to a set of discrete 2D points using adaptive Cubic Hermite Spline fitting.
 *
 * This utility performs data reduction (lossy compression) on dense time-series data.
 * It recursively subdivides the dataset, inserting {@link Keyframe}s only where the interpolated curve deviates from the original points by more than `maxError`.
 *
 * Tangents are automatically estimated based on the slope of the input data (Catmull-Rom style), ensuring smooth transitions between keyframes.
 *
 * @param {number[]} points flat array of coordinates [x0, y0, x1, y1, ... xn, yn]
 * @param {number} [input_offset] flat offset into the input array where to start reading data
 * @param {number} [input_count] number of points to fit, counted in points i.e., pairs of (x,y) values
 * @param {number} [maxError] Maximum allowed deviation. Higher values produce fewer keys (more compression), lower values preserve more detail.
 * @returns {AnimationCurve}
 */
export function animation_curve_fit(points: number[], input_offset?: number, input_count?: number, maxError?: number): AnimationCurve;
import { AnimationCurve } from "./AnimationCurve.js";
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