ts-scikit/lib/dsp/sampling.d.ts

A scientific toolkit written in Typescript

export declare class Sampling {
    private static readonly DEFAULT_TOLERANCE;
    private readonly _n;
    private readonly _d;
    private readonly _f;
    private readonly _t;
    private readonly _td;
    constructor(n: number, d?: number, f?: number, t?: number);
    /**
     * This sampling's count.
     */
    get count(): number;
    /**
     * This sampling's delta.
     */
    get delta(): number;
    /**
     * The first value of this sampling.
     */
    get first(): number;
    /**
     * The last value of this sampling.
     */
    get last(): number;
    /**
     * Gets the value v[i] of this sampling at a given index.
     * @param i the index.
     * @returns the value at index i.
     */
    valueAt(i: number): number;
    /**
     * Gets this sampling represented as an array of values.
     * @returns this sampling as an array.
     */
    values(): number[];
    /**
     * Returns the index of the sample with the specified value.
     * If this sampling has a sample value that equals (to within the sampling
     * tolerance) the specified value, then this method returns the
     * index of that sample. Otherwise, this method returns -1.
     * @param x the value.
     * @returns the index of the matching sample; -1, if none.
     */
    indexOf(x: number): number;
    /**
     * Returns the index of the sample nearest to the specified value.
     * @param x the value.
     * @returns the index of the nearest sample.
     */
    indexOfNearest(x: number): number;
    /**
     * Returns the value of the sample nearest to the specified value.
     * @param x the value.
     * @returns the value of the nearest sample.
     */
    valueOfNearest(x: number): number;
    /**
     * Determines whether the specified index is in the bounds of this sampling.
     * An index is in bounds if in the range [0, count - 1] of the first and last
     * sample indices.
     * @param i the index.
     * @returns true, if in bounds; false, otherwise.
     */
    isInBounds(i: number): boolean;
    /**
     * Determines whether the specified value is in the bounds of this samplineg.
     * A value is in bounds if in the range [first, last] defined by the first and
     * last sample values.
     * @param x the value.
     * @returns true, if in bounds; false, otherwise.
     */
    valueIsInBounds(x: number): boolean;
    /**
     * Shifts this sampling.
     * This method returns a new sampling; it does not modify this sampling.
     * @param s the value (shift) to add to this sampling's values.
     * @returns the new sampling.
     */
    shift(s: number): Sampling;
    /**
     * Prepends samples to this sampling.
     * <p>
     * This method returns a new sampling; it does not modify this sampling.
     * @param m the number of new samples
     * @returns the new sampling.
     */
    prepend(m: number): Sampling;
    /**
     * Appends samples to this sampling.
     * <p>
     * This method returns a new sampling; it does not modify this sampling.
     * @param m the number of new samples
     * @returns the new sampling.
     */
    append(m: number): Sampling;
    /**
     * Decimates this sampling.
     * Beginning with the first sample, keeps only every m'th sample, while
     * discarding the others in this sampling. If this sampling has n-values,
     * the new sampling with have 1 + (n - 1) / m values.
     * <p>
     * This method returns a new sampling; it does not modify this sampling.
     * @param m the factor by which to decimate; must be a positive integer.
     * @returns the new sampling.
     */
    decimate(m: number): Sampling;
    /**
     * Interpolates this sampling.
     * Inserts m - 1 evenly-spaced samples between each of the samples in this
     * sampling. If this sampling has n-values, the new sampling will have
     * 1 + (n - 1) * m values.
     * <p>
     * This method returns a new sampling; it does not modify this sampling.
     * @param m the factory by which to interpolate, must be a positive integer.
     * @returns the new sampling.
     */
    interpolate(m: number): Sampling;
}