/**
* Copyright 2012-2018, Plotly, Inc.
* All rights reserved.
*
* This source code is licensed under the MIT license found in the
* LICENSE file in the root directory of this source tree.
*/

'use strict';

var isArrayOrTypedArray = require('../../lib').isArrayOrTypedArray;

/*
 * Construct a 2D array of cheater values given a, b, and a slope.
 * If
 */
module.exports = function(a, b, cheaterslope) {
    var i, j, ascal, bscal, aval, bval;
    var data = [];

    var na = isArrayOrTypedArray(a) ? a.length : a;
    var nb = isArrayOrTypedArray(b) ? b.length : b;
    var adata = isArrayOrTypedArray(a) ? a : null;
    var bdata = isArrayOrTypedArray(b) ? b : null;

    // If we're using data, scale it so that for data that's just barely
    // not evenly spaced, the switch to value-based indexing is continuous.
    // This means evenly spaced data should look the same whether value
    // or index cheatertype.
    if(adata) {
        ascal = (adata.length - 1) / (adata[adata.length - 1] - adata[0]) / (na - 1);
    }

    if(bdata) {
        bscal = (bdata.length - 1) / (bdata[bdata.length - 1] - bdata[0]) / (nb - 1);
    }

    var xval;
    var xmin = Infinity;
    var xmax = -Infinity;
    for(j = 0; j < nb; j++) {
        data[j] = [];
        bval = bdata ? (bdata[j] - bdata[0]) * bscal : j / (nb - 1);
        for(i = 0; i < na; i++) {
            aval = adata ? (adata[i] - adata[0]) * ascal : i / (na - 1);
            xval = aval - bval * cheaterslope;
            xmin = Math.min(xval, xmin);
            xmax = Math.max(xval, xmax);
            data[j][i] = xval;
        }
    }

    // Normalize cheater values to the 0-1 range. This comes into play when you have
    // multiple cheater plots. After careful consideration, it seems better if cheater
    // values are normalized to a consistent range. Otherwise one cheater affects the
    // layout of other cheaters on the same axis.
    var slope = 1.0 / (xmax - xmin);
    var offset = -xmin * slope;
    for(j = 0; j < nb; j++) {
        for(i = 0; i < na; i++) {
            data[j][i] = slope * data[j][i] + offset;
        }
    }

    return data;
};
