/** @import {InputType} from "../index.js" */
/** @import {ParametersPCA, ParametersMDS, ParametersSAMMON} from "./index.js" */
/** @typedef {"PCA" | "MDS" | "random"} AvailableInit */
/** @typedef {{ PCA: ParametersPCA; MDS: ParametersMDS; random: {} }} ChooseDR */
/**
 * Sammon's Mapping
 *
 * A nonlinear dimensionality reduction technique that minimizes a stress
 * function based on the ratio of pairwise distances in high and low dimensional spaces.
 *
 * @class
 * @template {InputType} T
 * @extends DR<T, ParametersSAMMON<AvailableInit>>
 * @category Dimensionality Reduction
 */
export class SAMMON<T extends InputType> extends DR<T, ParametersSAMMON<AvailableInit>> {
  /**
   * @template {InputType} T
   * @param {T} X
   * @param {Partial<ParametersSAMMON<AvailableInit>>} [parameters]
   * @returns {T}
   */
  static transform<T_1 extends InputType>(
    X: T_1,
    parameters?: Partial<ParametersSAMMON<AvailableInit>>,
  ): T_1;
  /**
   * @template {InputType} T
   * @param {T} X
   * @param {Partial<ParametersSAMMON<AvailableInit>>} [parameters]
   * @returns {Generator<T, T, void>}
   */
  static generator<T_1 extends InputType>(
    X: T_1,
    parameters?: Partial<ParametersSAMMON<AvailableInit>>,
  ): Generator<T_1, T_1, void>;
  /**
   * @template {InputType} T
   * @param {T} X
   * @param {Partial<ParametersSAMMON<AvailableInit>>} [parameters]
   * @returns {Promise<T>}
   */
  static transform_async<T_1 extends InputType>(
    X: T_1,
    parameters?: Partial<ParametersSAMMON<AvailableInit>>,
  ): Promise<T_1>;
  /**
   * SAMMON's Mapping
   *
   * @param {T} X - The high-dimensional data.
   * @param {Partial<ParametersSAMMON<AvailableInit>>} [parameters] - Object containing parameterization of the DR
   *   method.
   * @see {@link https://arxiv.org/pdf/2009.01512.pdf}
   */
  constructor(X: T, parameters?: Partial<ParametersSAMMON<AvailableInit>>);
  /** @type {Matrix | undefined} */
  distance_matrix: Matrix | undefined;
  /**
   * Initializes the projection.
   *
   * @param {Matrix | undefined} D
   * @returns {asserts D is Matrix}
   */
  init(D: Matrix | undefined): asserts D is Matrix;
  /**
   * Transforms the inputdata `X` to dimensionality 2.
   *
   * @param {number} [max_iter=200] - Maximum number of iteration steps. Default is `200`
   * @returns {T} The projection of `X`.
   */
  transform(max_iter?: number): T;
  /**
   * Transforms the inputdata `X` to dimenionality 2.
   *
   * @param {number} [max_iter=200] - Maximum number of iteration steps. Default is `200`
   * @returns {Generator<T, T, void>} A generator yielding the intermediate steps of the projection of
   *   `X`.
   */
  generator(max_iter?: number): Generator<T, T, void>;
  _step(): Matrix;
}
export type AvailableInit = "PCA" | "MDS" | "random";
export type ChooseDR = {
  PCA: ParametersPCA;
  MDS: ParametersMDS;
  random: {};
};
import type { InputType } from "../index.js";
import type { ParametersSAMMON } from "./index.js";
import { DR } from "./DR.js";
import { Matrix } from "../matrix/index.js";
import type { ParametersPCA } from "./index.js";
import type { ParametersMDS } from "./index.js";
//# sourceMappingURL=SAMMON.d.ts.map