/*!
 * Copyright (c) Microsoft. All rights reserved.
 * Licensed under the MIT license. See LICENSE file in the project.
 */
/**
 * The Bin holds an array of values that match the bounding criteria,
 * along with an additional pair of properties indicating that bounding.
 */
export interface Bin extends Array<number> {
    /**
     * Minimum _computed_ value for the bin
     */
    x0: number;
    /**
     * Maximum _computed_ value for the bin
     */
    x1: number;
}
/**
 * A Histogram is just an array of Bins.
 * This follows the d3 format, so these outputs can be used as drop-ins to
 * any code that expects a d3-style histogram.
 */
export type Histogram = Array<Bin>;
/**
 * Creates a histogram from an array of objects.
 * The histogram will be populated with numeric values.
 * If your input data is not numeric, supply an accessor function.
 * By default, a standard equal-interval histogram will be created.
 * If the quantize parameter is set, it will instead use quantiles (i.e., equal-length bins).
 * If you are quantizing, you can also set a smooth parameter to indicate that breaks in the data should try to minimize variance.
 *
 * Note on quantiles: the bin count and length are ideals, but not guaranteed.
 * The way the quantiles are calculated, a precise number of bins can't be guaranteed unless you will accept empty bins.
 * For example, if your dataset is [1,1,1,1,1,2,2], you will always only get back two bins.
 * Depending on the data distribution, we also may not be able to assure each bin is the same length as the others.
 * Using the same example dataset, here we would have one bin with 5 items, and the other with 2.
 * We _could_ split them evenly and put some of the 1s in the 2 bin, but that seems less preferable.
 *
 */
export declare const histogram: (data: any[], bins: number, accessor?: (d: any) => any, quantize?: boolean, smooth?: boolean) => Histogram;