@astermind/astermind-elm/dist/core/Matrix.d.ts

JavaScript Extreme Learning Machine (ELM) library for browser and Node.js.

export declare class DimError extends Error {
    constructor(msg: string);
}
/**
 * Coerce any 2D array-like into a strict rectangular number[][]
 * - If width is not provided, infer from the first row's length
 * - Pads/truncates to width
 * - Non-finite values become 0
 */
export declare function ensureRectNumber2D(M: any, width?: number, name?: string): number[][];
/**
 * Relaxed rectangularity check:
 * - Accepts any array-like rows (typed arrays included)
 * - Verifies consistent width and finite numbers
 */
export declare function assertRect(A: any, name?: string): void;
export declare class Matrix {
    static shape(A: any): [number, number];
    static clone(A: any): number[][];
    static zeros(rows: number, cols: number): number[][];
    static identity(n: number): number[][];
    static transpose(A: any): number[][];
    static add(A: any, B: any): number[][];
    /** Adds lambda to the diagonal (ridge regularization) */
    static addRegularization(A: any, lambda?: number): number[][];
    static multiply(A: any, B: any): number[][];
    static multiplyVec(A: any, v: any): number[];
    static cholesky(A: any, jitter?: number): number[][];
    static solveCholesky(A: any, B: any, jitter?: number): number[][];
    static inverse(A: any): number[][];
    static inverseSPDOrFallback(A: any): number[][];
    private static assertSquare;
    static eigSym(A: any, maxIter?: number, tol?: number): {
        values: number[];
        vectors: number[][];
    };
    static invSqrtSym(A: any, eps?: number): number[][];
}