type DType = "i1" | "u1" | "i2" | "u2" | "i4" | "u4" | "i8" | "u8" | "f2" | "f4" | "f8" | "b1" | "c8" | "c16" | `U${number}`;
type TypedArray = Int8Array | Int16Array | Int32Array | BigInt64Array | Uint8Array | Uint8ClampedArray | Uint16Array | Uint32Array | BigUint64Array | Float32Array | Float64Array;
interface NpyArray<T extends ArrayBufferView = ArrayBufferView> {
    data: T;
    shape: number[];
    dtype: DType;
    fortranOrder: boolean;
}
interface Options {
    /** Convert float16 to float32. Default true. */
    convertFloat16?: boolean;
}
interface DumpOptions {
    /**
     * Specify the dtype for the output. Required for complex types (c8, c16)
     * since they cannot be inferred from a plain number array.
     */
    dtype?: DType;
}
declare function load(source: string | ArrayBuffer | ArrayBufferView | Blob, opts?: Options): Promise<NpyArray>;
declare function float16ToFloat32(u16: number): number;
declare function arrayToTypedArray(dtype: DType, array: ArrayLike<number | string>): TypedArray;
declare function inferDtypeFromArray(array: Array<number | number[] | string | string[]>): DType;
declare function dump(array: TypedArray | Array<number | string>, shape?: number[], options?: DumpOptions): ArrayBuffer;
declare class N {
    private opts;
    constructor(opts?: Options);
    load(source: string | ArrayBuffer | ArrayBufferView): Promise<NpyArray<ArrayBufferView<ArrayBufferLike>>>;
    static float16ToFloat32(u16: number): number;
    dump(array: TypedArray | Array<number | string>, shape?: number[], options?: DumpOptions): ArrayBuffer;
}

export { type DType, type DumpOptions, type NpyArray, type Options, type TypedArray, arrayToTypedArray, N as default, dump, float16ToFloat32, inferDtypeFromArray, load };