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i < array1.length; i++) {\n            array3[i] = array1[i] / constant;\n        }\n    }\n    else {\n        for (let i = 0; i < array1.length; i++) {\n            array3[i] = array1[i] / array2[i];\n        }\n    }\n    return array3;\n}\n//# sourceMappingURL=xDivide.js.map","import { xCheck } from './xCheck';\n/**\n * Returns a copy of the data as Float64\n *\n * @param array - array of numbers\n */\nexport function xEnsureFloat64(array) {\n    xCheck(array);\n    if (array instanceof Float64Array) {\n        return array.slice(0);\n    }\n    return Float64Array.from(array);\n}\n//# sourceMappingURL=xEnsureFloat64.js.map","/**\n * Returns the closest index of a `target`\n *\n * @param array - array of numbers\n * @param target - target\n * @returns - closest index\n */\nexport function xFindClosestIndex(array, target, options = {}) {\n    const { sorted = true } = options;\n    if (sorted) {\n        let low = 0;\n        let high = array.length - 1;\n        let middle = 0;\n        while (high - low > 1) {\n            middle = low + ((high - low) >> 1);\n            if (array[middle] < target) {\n                low = middle;\n            }\n            else if (array[middle] > target) {\n                high = middle;\n            }\n            else {\n                return middle;\n            }\n        }\n        if (low < array.length - 1) {\n            if (Math.abs(target - array[low]) < Math.abs(array[low + 1] - target)) {\n                return low;\n            }\n            else {\n                return low + 1;\n            }\n        }\n        else {\n            return low;\n        }\n    }\n    else {\n        let index = 0;\n        let diff = Number.POSITIVE_INFINITY;\n        for (let i = 0; i < array.length; i++) {\n            const currentDiff = Math.abs(array[i] - target);\n            if (currentDiff < diff) {\n                diff = currentDiff;\n                index = i;\n            }\n        }\n        return index;\n    }\n}\n//# sourceMappingURL=xFindClosestIndex.js.map","import { xFindClosestIndex } from './xFindClosestIndex';\n/**\n * Returns an object with {fromIndex, toIndex} for a specific from / to\n *\n * @param x - array of numbers\n * @param options - Options\n */\nexport function xGetFromToIndex(x, options = {}) {\n    let { fromIndex, toIndex, from, to } = options;\n    if (fromIndex === undefined) {\n        if (from !== undefined) {\n            fromIndex = xFindClosestIndex(x, from);\n        }\n        else {\n            fromIndex = 0;\n        }\n    }\n    if (toIndex === undefined) {\n        if (to !== undefined) {\n            toIndex = xFindClosestIndex(x, to);\n        }\n        else {\n            toIndex = x.length - 1;\n        }\n    }\n    if (fromIndex < 0)\n        fromIndex = 0;\n    if (toIndex < 0)\n        toIndex = 0;\n    if (fromIndex >= x.length)\n        fromIndex = x.length - 1;\n    if (toIndex >= x.length)\n        toIndex = x.length - 1;\n    if (fromIndex > toIndex)\n        [fromIndex, toIndex] = [toIndex, fromIndex];\n    return { fromIndex, toIndex };\n}\n//# sourceMappingURL=xGetFromToIndex.js.map","import { xCheck } from './xCheck';\nimport { xGetFromToIndex } from './xGetFromToIndex';\n/**\n * Computes the maximal value of an array of values\n *\n * @param array - array of numbers\n * @param options - options\n */\nexport function xMaxValue(array, options = {}) {\n    xCheck(array);\n    const { fromIndex, toIndex } = xGetFromToIndex(array, options);\n    let maxValue = array[fromIndex];\n    for (let i = fromIndex + 1; i <= toIndex; i++) {\n        if (array[i] > maxValue) {\n            maxValue = array[i];\n        }\n    }\n    return maxValue;\n}\n//# sourceMappingURL=xMaxValue.js.map","import { xCheck } from './xCheck';\nimport { xGetFromToIndex } from './xGetFromToIndex';\n/**\n * Computes the minimal value of an array of values\n *\n * @param array - array of numbers\n * @param options - options\n */\nexport function xMinValue(array, options = {}) {\n    xCheck(array);\n    const { fromIndex, toIndex } = xGetFromToIndex(array, options);\n    let minValue = array[fromIndex];\n    for (let i = fromIndex + 1; i <= toIndex; i++) {\n        if (array[i] < minValue) {\n            minValue = array[i];\n        }\n    }\n    return minValue;\n}\n//# sourceMappingURL=xMinValue.js.map","/**\n * Check if the values are separated always by the same difference\n *\n * @param array - Monotone growing array of number\n */\nexport function xIsEquallySpaced(array, options = {}) {\n    if (array.length < 3)\n        return true;\n    const { tolerance = 0.05 } = options;\n    let maxDx = 0;\n    let minDx = Number.MAX_SAFE_INTEGER;\n    for (let i = 0; i < array.length - 1; ++i) {\n        let absoluteDifference = array[i + 1] - array[i];\n        if (absoluteDifference < minDx) {\n            minDx = absoluteDifference;\n        }\n        if (absoluteDifference > maxDx) {\n            maxDx = absoluteDifference;\n        }\n    }\n    return (maxDx - minDx) / maxDx < tolerance;\n}\n//# sourceMappingURL=xIsEquallySpaced.js.map","/**\n * Returns true if x is monotone\n *\n * @param array - array of numbers\n */\nexport function xIsMonotone(array) {\n    if (array.length <= 2) {\n        return true;\n    }\n    if (array[0] === array[1]) {\n        // maybe a constant series\n        for (let i = 1; i < array.length - 1; i++) {\n            if (array[i] !== array[i + 1])\n                return false;\n        }\n        return true;\n    }\n    if (array[0] < array[array.length - 1]) {\n        for (let i = 0; i < array.length - 1; i++) {\n            if (array[i] >= array[i + 1])\n                return false;\n        }\n    }\n    else {\n        for (let i = 0; i < array.length - 1; i++) {\n            if (array[i] <= array[i + 1])\n                return false;\n        }\n    }\n    return true;\n}\n//# sourceMappingURL=xIsMonotone.js.map","/**\n * Returns true if x is monotone\n *\n * @param array - array of numbers\n */\nexport function xIsMonotoneIncreasing(array) {\n    if (array.length < 2) {\n        return true;\n    }\n    for (let i = 0; i < array.length - 1; i++) {\n        if (array[i] >= array[i + 1])\n            return false;\n    }\n    return true;\n}\n//# sourceMappingURL=xIsMonotoneIncreasing.js.map","import { xCheck } from './xCheck';\nimport { xGetFromToIndex } from './xGetFromToIndex';\n/**\n * Computes the mean value of an array of values\n *\n * @param array - array of numbers\n * @param options - options\n */\nexport function xMean(array, options = {}) {\n    xCheck(array);\n    const { fromIndex, toIndex } = xGetFromToIndex(array, options);\n    let sumValue = array[fromIndex];\n    for (let i = fromIndex + 1; i <= toIndex; i++) {\n        sumValue += array[i];\n    }\n    return sumValue / (toIndex - fromIndex + 1);\n}\n//# sourceMappingURL=xMean.js.map","import { xCheck } from './xCheck';\n/**\n * Return min and max values of an array\n *\n * @param array - array of number\n * @returns - Object with 2 properties, min and max\n */\nexport function xMinMaxValues(array) {\n    xCheck(array);\n    let min = array[0];\n    let max = array[0];\n    for (let value of array) {\n        if (value < min)\n            min = value;\n        if (value > max)\n            max = value;\n    }\n    return { min, max };\n}\n//# sourceMappingURL=xMinMaxValues.js.map","import { xMedianAbsoluteDeviation } from '..';\n/**\n * Determine noise level using MAD https://en.wikipedia.org/wiki/Median_absolute_deviation\n * Constant to convert mad to sd calculated using https://www.wolframalpha.com/input?i=sqrt%282%29+inverse+erf%280.5%29\n * This assumes a gaussian distribution of the noise\n * @param array\n * @returns noise level corresponding to one standard deviation\n */\nexport function xNoiseStandardDeviation(array) {\n    const { mad, median } = xMedianAbsoluteDeviation(array);\n    return { sd: mad / 0.6744897501960817, mad, median };\n}\n//# sourceMappingURL=xNoiseStandardDeviation.js.map","import { xMedian } from './xMedian';\n/**\n * This function calculates the median absolute deviation (MAD)\n * https://en.wikipedia.org/wiki/Median_absolute_deviation\n * @param array\n */\nexport function xMedianAbsoluteDeviation(array) {\n    const median = xMedian(array);\n    const averageDeviations = new Float64Array(array.length);\n    for (let i = 0; i < array.length; i++) {\n        averageDeviations[i] = Math.abs(array[i] - median);\n    }\n    return {\n        median,\n        mad: xMedian(averageDeviations),\n    };\n}\n//# sourceMappingURL=xMedianAbsoluteDeviation.js.map","/**\n * This function calculate the norm of a vector\n *\n * @example xNorm([3, 4]) -> 5\n * @param array - array\n * @returns - calculated norm\n */\nexport function xNorm(array) {\n    let result = 0;\n    for (const element of array) {\n        result += element ** 2;\n    }\n    return Math.sqrt(result);\n}\n//# sourceMappingURL=xNorm.js.map","import { xCheck } from './xCheck';\nimport { xGetFromToIndex } from './xGetFromToIndex';\n/**\n * Calculate the sum of the values\n *\n * @param array - Object that contains property x (an ordered increasing array) and y (an array).\n * @param options - Options.\n * @returns XSum value on the specified range.\n */\nexport function xSum(array, options = {}) {\n    xCheck(array);\n    const { fromIndex, toIndex } = xGetFromToIndex(array, options);\n    let sumValue = array[fromIndex];\n    for (let i = fromIndex + 1; i <= toIndex; i++) {\n        sumValue += array[i];\n    }\n    return sumValue;\n}\n//# sourceMappingURL=xSum.js.map","import { getOutputArray } from './utils/getOutputArray';\nimport { xCheck } from './xCheck';\nimport { xMaxValue } from './xMaxValue';\nimport { xSum } from './xSum';\n/**\n * Divides the data with either the sum, the absolute sum or the maximum of the data\n * @param array - Array containing values\n * @param options - options\n * @returns - normalized data\n */\nexport function xNormed(input, options = {}) {\n    const { algorithm = 'absolute', value = 1 } = options;\n    xCheck(input);\n    const output = getOutputArray(options.output, input.length);\n    if (input.length === 0) {\n        throw new Error('input must not be empty');\n    }\n    switch (algorithm.toLowerCase()) {\n        case 'absolute': {\n            let absoluteSumValue = absoluteSum(input) / value;\n            if (absoluteSumValue === 0) {\n                throw new Error('xNormed: trying to divide by 0');\n            }\n            for (let i = 0; i < input.length; i++) {\n                output[i] = input[i] / absoluteSumValue;\n            }\n            return output;\n        }\n        case 'max': {\n            let currentMaxValue = xMaxValue(input);\n            if (currentMaxValue === 0) {\n                throw new Error('xNormed: trying to divide by 0');\n            }\n            const factor = value / currentMaxValue;\n            for (let i = 0; i < input.length; i++) {\n                output[i] = input[i] * factor;\n            }\n            return output;\n        }\n        case 'sum': {\n            let sumFactor = xSum(input) / value;\n            if (sumFactor === 0) {\n                throw new Error('xNormed: trying to divide by 0');\n            }\n            for (let i = 0; i < input.length; i++) {\n                output[i] = input[i] / sumFactor;\n            }\n            return output;\n        }\n        default:\n            throw new Error(`norm: unknown algorithm: ${algorithm}`);\n    }\n}\nfunction absoluteSum(input) {\n    let sumValue = 0;\n    for (let i = 0; i < input.length; i++) {\n        sumValue += Math.abs(input[i]);\n    }\n    return sumValue;\n}\n//# sourceMappingURL=xNormed.js.map","import { xCheck } from './xCheck';\n/**\n * This function pads an array\n *s\n * @param array - the array that will be padded\n * @param options - options\n */\nexport function xPadding(array, options = {}) {\n    const { size = 0, value = 0, algorithm = '' } = options;\n    xCheck(array);\n    if (!algorithm) {\n        if (array instanceof Float64Array) {\n            return array.slice();\n        }\n        else {\n            return Float64Array.from(array);\n        }\n    }\n    let result = new Float64Array(array.length + size * 2);\n    for (let i = 0; i < array.length; i++) {\n        result[i + size] = array[i];\n    }\n    let fromEnd = size + array.length;\n    let toEnd = 2 * size + array.length;\n    switch (algorithm.toLowerCase()) {\n        case 'value':\n            for (let i = 0; i < size; i++) {\n                result[i] = value;\n            }\n            for (let i = fromEnd; i < toEnd; i++) {\n                result[i] = value;\n            }\n            break;\n        case 'duplicate':\n            for (let i = 0; i < size; i++) {\n                result[i] = array[0];\n            }\n            for (let i = fromEnd; i < toEnd; i++) {\n                result[i] = array[array.length - 1];\n            }\n            break;\n        case 'circular':\n            for (let i = 0; i < size; i++) {\n                result[i] =\n                    array[(array.length - (size % array.length) + i) % array.length];\n            }\n            for (let i = 0; i < size; i++) {\n                result[i + fromEnd] = array[i % array.length];\n            }\n            break;\n        default:\n            throw new Error('xPadding: unknown algorithm');\n    }\n    return result;\n}\n//# sourceMappingURL=xPadding.js.map","import { isAnyArray } from 'is-any-array';\nimport { xMean } from './xMean';\n/** Finds the variance of the data\n *\n * @param values - the values of the array\n * @param options - options\n * @returns variance\n */\nexport function xVariance(values, options = {}) {\n    if (!isAnyArray(values)) {\n        throw new TypeError('input must be an array');\n    }\n    const { unbiased = true, mean = xMean(values) } = options;\n    let sqrError = 0;\n    for (let i = 0; i < values.length; i++) {\n        let x = values[i] - mean;\n        sqrError += x * x;\n    }\n    if (unbiased) {\n        return sqrError / (values.length - 1);\n    }\n    else {\n        return sqrError / values.length;\n    }\n}\n//# sourceMappingURL=xVariance.js.map","import { xVariance } from './xVariance';\n/** Finds the standard deviation for the data at hand\n *\n * @param values - values in the data\n * @param options - options\n * @returns standard deviation\n */\nexport function xStandardDeviation(values, options = {}) {\n    return Math.sqrt(xVariance(values, options));\n}\n//# sourceMappingURL=xStandardDeviation.js.map","import { xCheck } from './xCheck';\nimport { xStandardDeviation } from './xStandardDeviation';\n/**\n * Pareto scaling, which uses the square root of standard deviation as the scaling factor, circumvents the amplification of noise by retaining a small portion of magnitude information.\n * Noda, I. (2008). Scaling techniques to enhance two-dimensional correlation spectra. Journal of Molecular Structure, 883, 216-227.\n * DOI: 10.1016/j.molstruc.2007.12.026\n *\n * @param array - array of number\n */\nexport function xParetoNormalization(array) {\n    xCheck(array);\n    let result = [];\n    const sqrtSD = Math.sqrt(xStandardDeviation(array));\n    for (let item of array) {\n        result.push(item / sqrtSD);\n    }\n    return result;\n}\n//# sourceMappingURL=xParetoNormalization.js.map","import { xCheck } from '..';\nimport { getOutputArray } from './utils/getOutputArray';\nimport { xMaxValue } from './xMaxValue';\nimport { xMinValue } from './xMinValue';\n/** Function used to rescale data\n *\n * @param input - input for the rescale\n * @param options - options\n * @returns rescaled data\n */\nexport function xRescale(input, options = {}) {\n    xCheck(input);\n    const output = getOutputArray(options.output, input.length);\n    const currentMin = xMinValue(input);\n    const currentMax = xMaxValue(input);\n    if (currentMin === currentMax) {\n        throw new RangeError('minimum and maximum input values are equal. Cannot rescale a constant array');\n    }\n    const { min = 0, max = 1 } = options;\n    if (min >= max) {\n        throw new RangeError('min option must be smaller than max option');\n    }\n    const factor = (max - min) / (currentMax - currentMin);\n    for (let i = 0; i < input.length; i++) {\n        output[i] = (input[i] - currentMin) * factor + min;\n    }\n    return output;\n}\n//# sourceMappingURL=xRescale.js.map","import { xCheck } from './xCheck';\nimport { xPadding } from './xPadding';\n/**\n * This function calculates a rolling average\n *\n * @param array - array\n * @param fct - callback function that from an array returns a value\n * @param options - options\n */\nexport function xRolling(array, fct, options = {}) {\n    xCheck(array);\n    if (typeof fct !== 'function')\n        throw new Error('fct has to be a function');\n    const { window = 5, padding = {} } = options;\n    const { size = window - 1, algorithm, value } = padding;\n    array = xPadding(array, { size, algorithm, value }); // ensure we get a copy and it is float64\n    const newArray = [];\n    for (let i = 0; i < array.length - window + 1; i++) {\n        // we will send a view to the original buffer\n        newArray.push(fct(array.subarray(i, i + window)));\n    }\n    return newArray;\n}\n//# sourceMappingURL=xRolling.js.map","import { xMean } from './xMean';\nimport { xRolling } from './xRolling';\n/**\n * This function calculates a rolling average\n *\n * @param array - array\n * @param options - option\n */\nexport function xRollingAverage(array, options = {}) {\n    return xRolling(array, xMean, options);\n}\n//# sourceMappingURL=xRollingAverage.js.map","import { xMedian } from './xMedian';\nimport { xRolling } from './xRolling';\n/**\n * This function calculates a rolling average\n *\n * @param array - array\n * @param options - options\n */\nexport function xRollingMedian(array, options = {}) {\n    return xRolling(array, xMedian, options);\n}\n//# sourceMappingURL=xRollingMedian.js.map","/**\n * Will apply a function on each element of the array described as a string\n * By default we will use as variable 'x'\n * In front of sequence of lowercase we will add 'Math.'. This allows to write\n * `sin(x) + cos(x)` and it will be replace internally by (x) => (Math.sin(x) + Math.cos(x))\n * @param array\n * @param options\n * @returns\n */\nexport function xApplyFunctionStr(array, options = {}) {\n    const { variableLabel = 'x', fctString = variableLabel } = options;\n    const fct = new Function(variableLabel, `return Number(${fctString\n        .replace(/(?<before>^|\\W)(?<after>[\\da-z]{2,}\\()/g, '$<before>Math.$<after>')\n        .replace(/Math\\.Math/g, 'Math')})`);\n    const toReturn = Float64Array.from(array);\n    for (let i = 0; i < array.length; i++) {\n        toReturn[i] = fct(array[i]);\n        if (Number.isNaN(toReturn[i])) {\n            throw new Error(`The callback ${fctString} does not return a number: ${array[i]}`);\n        }\n    }\n    return toReturn;\n}\n//# sourceMappingURL=xApplyFunctionStr.js.map","import { isAnyArray } from 'is-any-array';\n/**\n * Throw an error in no an object of x,y arrays\n *\n * @param data - array of points {x,y,z}\n */\nexport function xyCheck(data, options = {}) {\n    const { minLength } = options;\n    if (typeof data !== 'object' || !isAnyArray(data.x) || !isAnyArray(data.y)) {\n        throw new Error('Data must be an object of x and y arrays');\n    }\n    if (data.x.length !== data.y.length) {\n        throw new Error('The x and y arrays must have the same length');\n    }\n    if (minLength && data.x.length < minLength) {\n        throw new Error(`data.x must have a length of at least ${minLength}`);\n    }\n}\n//# sourceMappingURL=xyCheck.js.map","import { xIsMonotoneIncreasing } from '../x/xIsMonotoneIncreasing';\nimport { xyCheck } from './xyCheck';\n/**\n * Filters x,y values to allow strictly growing values in x axis.\n *\n * @param data - Object that contains property x (an ordered increasing array) and y (an array).\n */\nexport function xyEnsureGrowingX(data) {\n    xyCheck(data);\n    if (xIsMonotoneIncreasing(data.x))\n        return data;\n    const x = Array.from(data.x);\n    const y = Array.from(data.y);\n    let prevX = Number.NEGATIVE_INFINITY;\n    let currentIndex = 0;\n    for (let index = 0; index < x.length; index++) {\n        if (prevX < x[index]) {\n            if (currentIndex < index) {\n                x[currentIndex] = x[index];\n                y[currentIndex] = y[index];\n            }\n            currentIndex++;\n            prevX = x[index];\n        }\n    }\n    x.length = currentIndex;\n    y.length = currentIndex;\n    return { x, y };\n}\n//# sourceMappingURL=xyEnsureGrowingX.js.map","/**\n * Normalize an array of zones:\n * - ensure than from < to\n * - merge overlapping zones\n * - deal with exclusions zones\n * - if no zones is specified add one between -Infinity and +Infinity\n * @param zones - array of zones\n * @param options - options\n * @returns array of zones\n */\nexport function zonesNormalize(zones = [], options = {}) {\n    let { from = Number.NEGATIVE_INFINITY, to = Number.POSITIVE_INFINITY, exclusions = [], } = options;\n    if (from > to)\n        [from, to] = [to, from];\n    zones = JSON.parse(JSON.stringify(zones)).map((zone) => zone.from > zone.to ? { from: zone.to, to: zone.from } : zone);\n    zones = zones.sort((a, b) => {\n        if (a.from !== b.from)\n            return a.from - b.from;\n        return a.to - b.to;\n    });\n    if (zones.length === 0) {\n        zones.push({ from, to });\n    }\n    for (const zone of zones) {\n        if (from > zone.from)\n            zone.from = from;\n        if (to < zone.to)\n            zone.to = to;\n    }\n    zones = zones.filter((zone) => zone.from <= zone.to);\n    if (zones.length === 0)\n        return [];\n    let currentZone = zones[0];\n    let beforeExclusionsZones = [currentZone];\n    for (let i = 1; i < zones.length; i++) {\n        let zone = zones[i];\n        if (zone.from <= currentZone.to) {\n            if (currentZone.to < zone.to) {\n                currentZone.to = zone.to;\n            }\n        }\n        else {\n            currentZone = zone;\n            beforeExclusionsZones.push(currentZone);\n        }\n    }\n    if (exclusions.length === 0)\n        return beforeExclusionsZones;\n    const normalizedExclusions = zonesNormalize(exclusions);\n    let currentExclusionIndex = 0;\n    const results = [];\n    let counter = 0;\n    for (let zoneIndex = 0; zoneIndex < beforeExclusionsZones.length; zoneIndex++) {\n        if (counter++ > 5)\n            break;\n        const zone = beforeExclusionsZones[zoneIndex];\n        if (currentExclusionIndex === normalizedExclusions.length) {\n            // we analysed all the exclusion zones\n            results.push(zone);\n            continue;\n        }\n        while (currentExclusionIndex < normalizedExclusions.length &&\n            normalizedExclusions[currentExclusionIndex].to <= zone.from) {\n            currentExclusionIndex++;\n        }\n        if (currentExclusionIndex === normalizedExclusions.length) {\n            // we analysed all the exclusion zones\n            results.push(zone);\n            continue;\n        }\n        if (zone.to < normalizedExclusions[currentExclusionIndex].from) {\n            // no problems, not yet in exclusion\n            results.push(zone);\n            continue;\n        }\n        if (normalizedExclusions[currentExclusionIndex].to >= zone.to) {\n            // could be totally excluded\n            if (normalizedExclusions[currentExclusionIndex].from <= zone.from) {\n                continue;\n            }\n            results.push({\n                from: normalizedExclusions[currentExclusionIndex].to,\n                to: zone.to,\n            });\n        }\n        // we cut in the middle, we need to create more zones, annoying !\n        if (normalizedExclusions[currentExclusionIndex].from > zone.from) {\n            results.push({\n                from: zone.from,\n                to: normalizedExclusions[currentExclusionIndex].from,\n            });\n        }\n        zone.from = normalizedExclusions[currentExclusionIndex].to;\n        zoneIndex--;\n    }\n    return results;\n}\n//# sourceMappingURL=zonesNormalize.js.map","import { zonesNormalize } from './zonesNormalize';\n/**\n * Add the number of points per zone to reach a specified total\n *\n * @param zones - array of zones\n * @param numberOfPoints - total number of points to distribute between zones\n * @param options - options\n * @returns array of zones with points\n */\nexport function zonesWithPoints(zones = [], \n/**\n * total number of points to distribute between zones\n * @default 10\n */\nnumberOfPoints = 10, options = {}) {\n    if (zones.length === 0)\n        return zones;\n    let returnZones = zonesNormalize(zones, options);\n    const totalSize = returnZones.reduce((previous, current) => {\n        return previous + (current.to - current.from);\n    }, 0);\n    let unitsPerPoint = totalSize / numberOfPoints;\n    let currentTotal = 0;\n    for (let i = 0; i < returnZones.length - 1; i++) {\n        let zone = returnZones[i];\n        zone.numberOfPoints = Math.min(Math.round((zone.to - zone.from) / unitsPerPoint), numberOfPoints - currentTotal);\n        currentTotal += zone.numberOfPoints;\n    }\n    let zone = returnZones[returnZones.length - 1];\n    zone.numberOfPoints = numberOfPoints - currentTotal;\n    return returnZones;\n}\n//# sourceMappingURL=zonesWithPoints.js.map","/**\n * Function that calculates the integral of the line between two\n * x-coordinates, given the slope and intercept of the line.\n * @param x0\n * @param x1\n * @param slope\n * @param intercept\n * @return integral value.\n */\nexport default function integral(\n/** first coordinate of point */\nx0, \n/** second coordinate of point */\nx1, \n/** slope of the line */\nslope, \n/** intercept of the line on the y axis */\nintercept) {\n    return (0.5 * slope * x1 * x1 +\n        intercept * x1 -\n        (0.5 * slope * x0 * x0 + intercept * x0));\n}\n//# sourceMappingURL=integral.js.map","import { createFromToArray } from '../utils/createFromToArray';\nimport { zonesNormalize } from '../zones/zonesNormalize';\nimport { zonesWithPoints } from '../zones/zonesWithPoints';\nimport equallySpacedSlot from './utils/equallySpacedSlot';\nimport equallySpacedSmooth from './utils/equallySpacedSmooth';\nimport { xyCheck } from './xyCheck';\n/**\n * Function that returns a Number array of equally spaced numberOfPoints\n * containing a representation of intensities of the spectra arguments x\n * and y.\n *\n * The options parameter contains an object in the following form:\n * from: starting point\n * to: last point\n * numberOfPoints: number of points between from and to\n * variant: \"slot\" or \"smooth\" - smooth is the default option\n *\n * The slot variant consist that each point in an array is calculated\n * averaging the existing points between the slot that belongs to the current\n * value. The smooth variant is the same but takes the integral of the range\n * of the slot and divide by the step size between two points in an array.\n *\n * If exclusions zone are present, zones are ignored !\n *\n * @param data - object containing 2 properties x and y\n * @param options - options\n * @return new object with x / y array with the equally spaced data.\n */\nexport function xyEquallySpaced(data, options = {}) {\n    let { x, y } = data;\n    let xLength = x.length;\n    const { from = x[0], to = x[xLength - 1], variant = 'smooth', numberOfPoints = 100, exclusions = [], zones = [{ from, to }], } = options;\n    if (from > to) {\n        throw new RangeError('from should be larger than to');\n    }\n    xyCheck(data);\n    if (numberOfPoints < 2) {\n        throw new RangeError(\"'numberOfPoints' option must be greater than 1\");\n    }\n    const normalizedZones = zonesNormalize(zones, { from, to, exclusions });\n    const zonesWithPointsRes = zonesWithPoints(normalizedZones, numberOfPoints, {\n        from,\n        to,\n    });\n    let xResult = [];\n    let yResult = [];\n    for (let zone of zonesWithPointsRes) {\n        if (!zone.numberOfPoints) {\n            zone.numberOfPoints = 0;\n        }\n        let zoneResult = processZone(Array.from(x), Array.from(y), zone.from, zone.to, zone.numberOfPoints, variant);\n        xResult = xResult.concat(zoneResult.x);\n        yResult = yResult.concat(zoneResult.y);\n    }\n    return { x: xResult, y: yResult };\n}\nfunction processZone(x, y, from, to, numberOfPoints, variant) {\n    if (numberOfPoints < 1) {\n        throw new RangeError('the number of points must be at least 1');\n    }\n    let output = variant === 'slot'\n        ? Array.from(equallySpacedSlot(x, y, from, to, numberOfPoints))\n        : Array.from(equallySpacedSmooth(x, y, from, to, numberOfPoints));\n    return {\n        x: Array.from(createFromToArray({\n            from,\n            to,\n            length: numberOfPoints,\n        })),\n        y: output,\n    };\n}\n//# sourceMappingURL=xyEquallySpaced.js.map","/**\n * function that retrieves the getEquallySpacedData with the variant \"slot\"\n *\n * @param x\n * @param y\n * @param from\n * @param to\n * @param numberOfPoints\n * @return Array of y's equally spaced with the variant \"slot\"\n */\nexport default function equallySpacedSlot(\n/** x coordinates */\nx, \n/** y coordinates */\ny, \n/** from value */\nfrom, \n/** to value */\nto, \n/** number of points */\nnumberOfPoints) {\n    let xLength = x.length;\n    let step = (to - from) / (numberOfPoints > 1 ? numberOfPoints - 1 : 1);\n    let halfStep = step / 2;\n    let lastStep = x[x.length - 1] - x[x.length - 2];\n    let start = from - halfStep;\n    // Changed Array to Float64Array\n    let output = new Float64Array(numberOfPoints);\n    // Init main variables\n    let min = start;\n    let max = start + step;\n    let previousX = -Number.MAX_VALUE;\n    let previousY = 0;\n    let nextX = x[0];\n    let nextY = y[0];\n    let frontOutsideSpectra = 0;\n    let backOutsideSpectra = true;\n    let currentValue = 0;\n    // for slot algorithm\n    let currentPoints = 0;\n    let i = 1; // index of input\n    let j = 0; // index of output\n    main: while (true) {\n        if (previousX >= nextX)\n            throw new Error('x must be a growing series');\n        while (previousX - max > 0) {\n            // no overlap with original point, just consume current value\n            if (backOutsideSpectra) {\n                currentPoints++;\n                backOutsideSpectra = false;\n            }\n            output[j] = currentPoints <= 0 ? 0 : currentValue / currentPoints;\n            j++;\n            if (j === numberOfPoints) {\n                break main;\n            }\n            min = max;\n            max += step;\n            currentValue = 0;\n            currentPoints = 0;\n        }\n        if (previousX > min) {\n            currentValue += previousY;\n            currentPoints++;\n        }\n        if (previousX === -Number.MAX_VALUE || frontOutsideSpectra > 1) {\n            currentPoints--;\n        }\n        previousX = nextX;\n        previousY = nextY;\n        if (i < xLength) {\n            nextX = x[i];\n            nextY = y[i];\n            i++;\n        }\n        else {\n            nextX += lastStep;\n            nextY = 0;\n            frontOutsideSpectra++;\n        }\n    }\n    return output;\n}\n//# sourceMappingURL=equallySpacedSlot.js.map","import integral from './integral';\n/**\n * function that retrieves the getEquallySpacedData with the variant \"smooth\"\n *\n * @param x\n * @param y\n * @param from\n * @param to\n * @param numberOfPoints\n * @return - Array of y's equally spaced with the variant \"smooth\"\n */\nexport default function equallySpacedSmooth(\n/** x coordinates */\nx, \n/** y coordinates */\ny, \n/** from value */\nfrom, \n/** to value */\nto, \n/** number of points */\nnumberOfPoints) {\n    let xLength = x.length;\n    let step = (to - from) / (numberOfPoints > 1 ? numberOfPoints - 1 : 1);\n    let halfStep = step / 2;\n    // Changed Array to Float64Array\n    let output = new Float64Array(numberOfPoints);\n    let initialOriginalStep = x[1] - x[0];\n    let lastOriginalStep = x[xLength - 1] - x[xLength - 2];\n    // Init main variables\n    let min = from - halfStep;\n    let max = from + halfStep;\n    let previousX = Number.MIN_SAFE_INTEGER;\n    let previousY = 0;\n    let nextX = x[0] - initialOriginalStep;\n    let nextY = 0;\n    let currentValue = 0;\n    let slope = 0;\n    let intercept = 0;\n    let sumAtMin = 0;\n    let sumAtMax = 0;\n    let i = 0; // index of input\n    let j = 0; // index of output\n    let add = 0;\n    main: while (true) {\n        if (previousX >= nextX)\n            throw new Error('x must be a growing series');\n        if (previousX <= min && min <= nextX) {\n            add = integral(0, min - previousX, slope, previousY);\n            sumAtMin = currentValue + add;\n        }\n        while (nextX - max >= 0) {\n            // no overlap with original point, just consume current value\n            add = integral(0, max - previousX, slope, previousY);\n            sumAtMax = currentValue + add;\n            output[j++] = (sumAtMax - sumAtMin) / step;\n            if (j === numberOfPoints) {\n                break main;\n            }\n            min = max;\n            max += step;\n            sumAtMin = sumAtMax;\n        }\n        currentValue += integral(previousX, nextX, slope, intercept);\n        previousX = nextX;\n        previousY = nextY;\n        if (i < xLength) {\n            nextX = x[i];\n            nextY = y[i];\n            i++;\n        }\n        else if (i === xLength) {\n            nextX += lastOriginalStep;\n            nextY = 0;\n        }\n        slope = getSlope(previousX, previousY, nextX, nextY);\n        intercept = -slope * previousX + previousY;\n    }\n    return output;\n}\nfunction getSlope(x0, y0, x1, y1) {\n    return (y1 - y0) / (x1 - x0);\n}\n//# sourceMappingURL=equallySpacedSmooth.js.map","import { zonesNormalize } from '../zones/zonesNormalize';\n/** Filter an array x/y based on various criteria x points are expected to be sorted\n *\n * @param data - object containing 2 properties x and y\n * @param options - options\n * @return filtered array\n */\nexport function xyFilterX(data, options = {}) {\n    const { x, y } = data;\n    const { from = x[0], to = x[x.length - 1], zones = [{ from, to }], exclusions = [], } = options;\n    let normalizedZones = zonesNormalize(zones, { from, to, exclusions });\n    let currentZoneIndex = 0;\n    let newX = [];\n    let newY = [];\n    let position = 0;\n    while (position < x.length) {\n        if (x[position] <= normalizedZones[currentZoneIndex].to &&\n            x[position] >= normalizedZones[currentZoneIndex].from) {\n            newX.push(x[position]);\n            newY.push(y[position]);\n        }\n        else if (x[position] > normalizedZones[currentZoneIndex].to) {\n            currentZoneIndex++;\n            if (!normalizedZones[currentZoneIndex])\n                break;\n        }\n        position++;\n    }\n    return {\n        x: newX,\n        y: newY,\n    };\n}\n//# sourceMappingURL=xyFilterX.js.map","import { xyCheck } from './xyCheck';\n/**\n * Filter out all the points for which x <= 0. Useful to display log scale data\n *\n * @param data - data\n * @returns - An object with the filtered data\n */\nexport function xyFilterXPositive(data) {\n    xyCheck(data);\n    const { x, y } = data;\n    const newX = [];\n    const newY = [];\n    if (x === undefined || y === undefined)\n        return { x: newX, y: newY };\n    for (let i = 0; i < x.length; i++) {\n        if (x[i] > 0) {\n            newX.push(x[i]);\n            newY.push(y[i]);\n        }\n    }\n    return { x: newX, y: newY };\n}\n//# sourceMappingURL=xyFilterXPositive.js.map","import { xFindClosestIndex } from '../x/xFindClosestIndex';\nimport { xyCheck } from './xyCheck';\n/**\n * Find the closest maximum going up hill\n *\n * @param data - Object that contains property x (an ordered increasing array) and y (an array)\n * @param options - options\n * @returns - An object with the x/y value\n */\nexport function xyMaxClosestYPoint(data, options = {}) {\n    xyCheck(data);\n    const { x, y } = data;\n    let { target, targetIndex } = options;\n    if (targetIndex === undefined) {\n        if (target !== undefined) {\n            targetIndex = xFindClosestIndex(x, target);\n        }\n        else {\n            targetIndex = 0;\n        }\n    }\n    let previousIndex = Number.MIN_SAFE_INTEGER;\n    let currentIndex = targetIndex;\n    let xyMaxY = y[targetIndex];\n    while (currentIndex !== previousIndex) {\n        previousIndex = currentIndex;\n        if (currentIndex > 0 && y[currentIndex - 1] > xyMaxY) {\n            currentIndex--;\n        }\n        else if (currentIndex < x.length - 1 && y[currentIndex + 1] > xyMaxY) {\n            currentIndex++;\n        }\n        xyMaxY = y[currentIndex];\n    }\n    return {\n        x: x[currentIndex],\n        y: y[currentIndex],\n        index: currentIndex,\n    };\n}\n//# sourceMappingURL=xyMaxClosestYPoint.js.map","import { xFindClosestIndex } from '../x/xFindClosestIndex';\nimport { xyCheck } from './xyCheck';\n/**\n * Find the closest minimum going down hill\n *\n * @param data - Object that contains property x (an ordered increasing array) and y (an array)\n * @param options - Options\n * @returns - An object with the x/y value\n */\nexport function xyMinClosestYPoint(data, options = {}) {\n    xyCheck(data);\n    const { x, y } = data;\n    let { target, targetIndex } = options;\n    if (targetIndex === undefined) {\n        if (target !== undefined) {\n            targetIndex = xFindClosestIndex(x, target);\n        }\n        else {\n            targetIndex = 0;\n        }\n    }\n    let previousIndex = Number.MIN_SAFE_INTEGER;\n    let currentIndex = targetIndex;\n    let minY = y[targetIndex];\n    while (currentIndex !== previousIndex) {\n        previousIndex = currentIndex;\n        if (currentIndex > 0 && y[currentIndex - 1] < minY) {\n            currentIndex--;\n        }\n        else if (currentIndex < x.length - 1 && y[currentIndex + 1] < minY) {\n            currentIndex++;\n        }\n        minY = y[currentIndex];\n    }\n    return {\n        x: x[currentIndex],\n        y: y[currentIndex],\n        index: currentIndex,\n    };\n}\n//# sourceMappingURL=xyMinClosestYPoint.js.map","import { matrixCheck } from './matrixCheck';\n/**\n * Get min and max Z\n *\n * @param matrix - matrix [rows][cols].\n */\nexport function matrixMinMaxZ(matrix) {\n    matrixCheck(matrix);\n    const nbRows = matrix.length;\n    const nbColumns = matrix[0].length;\n    let min = matrix[0][0];\n    let max = matrix[0][0];\n    for (let column = 0; column < nbColumns; column++) {\n        for (let row = 0; row < nbRows; row++) {\n            if (matrix[row][column] < min)\n                min = matrix[row][column];\n            if (matrix[row][column] > max)\n                max = matrix[row][column];\n        }\n    }\n    return { min, max };\n}\n//# sourceMappingURL=matrixMinMaxZ.js.map","export function matrixCheck(data) {\n    if (data.length === 0 || data[0].length === 0) {\n        throw new RangeError('matrix should contain data');\n    }\n    const firstLength = data[0].length;\n    for (let i = 1; i < data.length; i++) {\n        if (data[i].length !== firstLength) {\n            throw new RangeError('All rows should has the same length');\n        }\n    }\n}\n//# sourceMappingURL=matrixCheck.js.map","import { isAnyArray } from 'is-any-array';\n\nfunction max(input) {\n  var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {};\n\n  if (!isAnyArray(input)) {\n    throw new TypeError('input must be an array');\n  }\n\n  if (input.length === 0) {\n    throw new TypeError('input must not be empty');\n  }\n\n  var _options$fromIndex = options.fromIndex,\n      fromIndex = _options$fromIndex === void 0 ? 0 : _options$fromIndex,\n      _options$toIndex = options.toIndex,\n      toIndex = _options$toIndex === void 0 ? input.length : _options$toIndex;\n\n  if (fromIndex < 0 || fromIndex >= input.length || !Number.isInteger(fromIndex)) {\n    throw new Error('fromIndex must be a positive integer smaller than length');\n  }\n\n  if (toIndex <= fromIndex || toIndex > input.length || !Number.isInteger(toIndex)) {\n    throw new Error('toIndex must be an integer greater than fromIndex and at most equal to length');\n  }\n\n  var maxValue = input[fromIndex];\n\n  for (var i = fromIndex + 1; i < toIndex; i++) {\n    if (input[i] > maxValue) maxValue = input[i];\n  }\n\n  return maxValue;\n}\n\nexport { max as default };\n","import { isAnyArray } from 'is-any-array';\n\nfunction min(input) {\n  var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {};\n\n  if (!isAnyArray(input)) {\n    throw new TypeError('input must be an array');\n  }\n\n  if (input.length === 0) {\n    throw new TypeError('input must not be empty');\n  }\n\n  var _options$fromIndex = options.fromIndex,\n      fromIndex = _options$fromIndex === void 0 ? 0 : _options$fromIndex,\n      _options$toIndex = options.toIndex,\n      toIndex = _options$toIndex === void 0 ? input.length : _options$toIndex;\n\n  if (fromIndex < 0 || fromIndex >= input.length || !Number.isInteger(fromIndex)) {\n    throw new Error('fromIndex must be a positive integer smaller than length');\n  }\n\n  if (toIndex <= fromIndex || toIndex > input.length || !Number.isInteger(toIndex)) {\n    throw new Error('toIndex must be an integer greater than fromIndex and at most equal to length');\n  }\n\n  var minValue = input[fromIndex];\n\n  for (var i = fromIndex + 1; i < toIndex; i++) {\n    if (input[i] < minValue) minValue = input[i];\n  }\n\n  return minValue;\n}\n\nexport { min as default };\n","import { isAnyArray } from 'is-any-array';\nimport max from 'ml-array-max';\nimport min from 'ml-array-min';\n\nfunction rescale(input) {\n  var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {};\n\n  if (!isAnyArray(input)) {\n    throw new TypeError('input must be an array');\n  } else if (input.length === 0) {\n    throw new TypeError('input must not be empty');\n  }\n\n  var output;\n\n  if (options.output !== undefined) {\n    if (!isAnyArray(options.output)) {\n      throw new TypeError('output option must be an array if specified');\n    }\n\n    output = options.output;\n  } else {\n    output = new Array(input.length);\n  }\n\n  var currentMin = min(input);\n  var currentMax = max(input);\n\n  if (currentMin === currentMax) {\n    throw new RangeError('minimum and maximum input values are equal. Cannot rescale a constant array');\n  }\n\n  var _options$min = options.min,\n      minValue = _options$min === void 0 ? options.autoMinMax ? currentMin : 0 : _options$min,\n      _options$max = options.max,\n      maxValue = _options$max === void 0 ? options.autoMinMax ? currentMax : 1 : _options$max;\n\n  if (minValue >= maxValue) {\n    throw new RangeError('min option must be smaller than max option');\n  }\n\n  var factor = (maxValue - minValue) / (currentMax - currentMin);\n\n  for (var i = 0; i < input.length; i++) {\n    output[i] = (input[i] - currentMin) * factor + minValue;\n  }\n\n  return output;\n}\n\nexport { rescale as default };\n","const indent = ' '.repeat(2);\nconst indentData = ' '.repeat(4);\n\nexport function inspectMatrix() {\n  return inspectMatrixWithOptions(this);\n}\n\nexport function inspectMatrixWithOptions(matrix, options = {}) {\n  const {\n    maxRows = 15,\n    maxColumns = 10,\n    maxNumSize = 8,\n    padMinus = 'auto',\n  } = options;\n  return `${matrix.constructor.name} {\n${indent}[\n${indentData}${inspectData(matrix, maxRows, maxColumns, maxNumSize, padMinus)}\n${indent}]\n${indent}rows: ${matrix.rows}\n${indent}columns: ${matrix.columns}\n}`;\n}\n\nfunction inspectData(matrix, maxRows, maxColumns, maxNumSize, padMinus) {\n  const { rows, columns } = matrix;\n  const maxI = Math.min(rows, maxRows);\n  const maxJ = Math.min(columns, maxColumns);\n  const result = [];\n\n  if (padMinus === 'auto') {\n    padMinus = false;\n    loop: for (let i = 0; i < maxI; i++) {\n      for (let j = 0; j < maxJ; j++) {\n        if (matrix.get(i, j) < 0) {\n          padMinus = true;\n          break loop;\n        }\n      }\n    }\n  }\n\n  for (let i = 0; i < maxI; i++) {\n    let line = [];\n    for (let j = 0; j < maxJ; j++) {\n      line.push(formatNumber(matrix.get(i, j), maxNumSize, padMinus));\n    }\n    result.push(`${line.join(' ')}`);\n  }\n  if (maxJ !== columns) {\n    result[result.length - 1] += ` ... ${columns - maxColumns} more columns`;\n  }\n  if (maxI !== rows) {\n    result.push(`... ${rows - maxRows} more rows`);\n  }\n  return result.join(`\\n${indentData}`);\n}\n\nfunction formatNumber(num, maxNumSize, padMinus) {\n  return (\n    num >= 0 && padMinus\n      ? ` ${formatNumber2(num, maxNumSize - 1)}`\n      : formatNumber2(num, maxNumSize)\n  ).padEnd(maxNumSize);\n}\n\nfunction formatNumber2(num, len) {\n  // small.length numbers should be as is\n  let str = num.toString();\n  if (str.length <= len) return str;\n\n  // (7)'0.00123' is better then (7)'1.23e-2'\n  // (8)'0.000123' is worse then (7)'1.23e-3',\n  let fix = num.toFixed(len);\n  if (fix.length > len) {\n    fix = num.toFixed(Math.max(0, len - (fix.length - len)));\n  }\n  if (\n    fix.length <= len &&\n    !fix.startsWith('0.000') &&\n    !fix.startsWith('-0.000')\n  ) {\n    return fix;\n  }\n\n  // well, if it's still too long the user should've used longer numbers\n  let exp = num.toExponential(len);\n  if (exp.length > len) {\n    exp = num.toExponential(Math.max(0, len - (exp.length - len)));\n  }\n  return exp.slice(0);\n}\n","import { isAnyArray } from 'is-any-array';\n\n/**\n * @private\n * Check that a row index is not out of bounds\n * @param {Matrix} matrix\n * @param {number} index\n * @param {boolean} [outer]\n */\nexport function checkRowIndex(matrix, index, outer) {\n  let max = outer ? matrix.rows : matrix.rows - 1;\n  if (index < 0 || index > max) {\n    throw new RangeError('Row index out of range');\n  }\n}\n\n/**\n * @private\n * Check that a column index is not out of bounds\n * @param {Matrix} matrix\n * @param {number} index\n * @param {boolean} [outer]\n */\nexport function checkColumnIndex(matrix, index, outer) {\n  let max = outer ? matrix.columns : matrix.columns - 1;\n  if (index < 0 || index > max) {\n    throw new RangeError('Column index out of range');\n  }\n}\n\n/**\n * @private\n * Check that the provided vector is an array with the right length\n * @param {Matrix} matrix\n * @param {Array|Matrix} vector\n * @return {Array}\n * @throws {RangeError}\n */\nexport function checkRowVector(matrix, vector) {\n  if (vector.to1DArray) {\n    vector = vector.to1DArray();\n  }\n  if (vector.length !== matrix.columns) {\n    throw new RangeError(\n      'vector size must be the same as the number of columns',\n    );\n  }\n  return vector;\n}\n\n/**\n * @private\n * Check that the provided vector is an array with the right length\n * @param {Matrix} matrix\n * @param {Array|Matrix} vector\n * @return {Array}\n * @throws {RangeError}\n */\nexport function checkColumnVector(matrix, vector) {\n  if (vector.to1DArray) {\n    vector = vector.to1DArray();\n  }\n  if (vector.length !== matrix.rows) {\n    throw new RangeError('vector size must be the same as the number of rows');\n  }\n  return vector;\n}\n\nexport function checkRowIndices(matrix, rowIndices) {\n  if (!isAnyArray(rowIndices)) {\n    throw new TypeError('row indices must be an array');\n  }\n\n  for (let i = 0; i < rowIndices.length; i++) {\n    if (rowIndices[i] < 0 || rowIndices[i] >= matrix.rows) {\n      throw new RangeError('row indices are out of range');\n    }\n  }\n}\n\nexport function checkColumnIndices(matrix, columnIndices) {\n  if (!isAnyArray(columnIndices)) {\n    throw new TypeError('column indices must be an array');\n  }\n\n  for (let i = 0; i < columnIndices.length; i++) {\n    if (columnIndices[i] < 0 || columnIndices[i] >= matrix.columns) {\n      throw new RangeError('column indices are out of range');\n    }\n  }\n}\n\nexport function checkRange(matrix, startRow, endRow, startColumn, endColumn) {\n  if (arguments.length !== 5) {\n    throw new RangeError('expected 4 arguments');\n  }\n  checkNumber('startRow', startRow);\n  checkNumber('endRow', endRow);\n  checkNumber('startColumn', startColumn);\n  checkNumber('endColumn', endColumn);\n  if (\n    startRow > endRow ||\n    startColumn > endColumn ||\n    startRow < 0 ||\n    startRow >= matrix.rows ||\n    endRow < 0 ||\n    endRow >= matrix.rows ||\n    startColumn < 0 ||\n    startColumn >= matrix.columns ||\n    endColumn < 0 ||\n    endColumn >= matrix.columns\n  ) {\n    throw new RangeError('Submatrix indices are out of range');\n  }\n}\n\nexport function newArray(length, value = 0) {\n  let array = [];\n  for (let i = 0; i < length; i++) {\n    array.push(value);\n  }\n  return array;\n}\n\nfunction checkNumber(name, value) {\n  if (typeof value !== 'number') {\n    throw new TypeError(`${name} must be a number`);\n  }\n}\n\nexport function checkNonEmpty(matrix) {\n  if (matrix.isEmpty()) {\n    throw new Error('Empty matrix has no elements to index');\n  }\n}\n","import { isAnyArray } from 'is-any-array';\nimport rescale from 'ml-array-rescale';\n\nimport { inspectMatrix, inspectMatrixWithOptions } from './inspect';\nimport { installMathOperations } from './mathOperations';\nimport {\n  sumByRow,\n  sumByColumn,\n  sumAll,\n  productByRow,\n  productByColumn,\n  productAll,\n  varianceByRow,\n  varianceByColumn,\n  varianceAll,\n  centerByRow,\n  centerByColumn,\n  centerAll,\n  scaleByRow,\n  scaleByColumn,\n  scaleAll,\n  getScaleByRow,\n  getScaleByColumn,\n  getScaleAll,\n} from './stat';\nimport {\n  checkRowVector,\n  checkRowIndex,\n  checkColumnIndex,\n  checkColumnVector,\n  checkRange,\n  checkNonEmpty,\n  checkRowIndices,\n  checkColumnIndices,\n} from './util';\n\nexport class AbstractMatrix {\n  static from1DArray(newRows, newColumns, newData) {\n    let length = newRows * newColumns;\n    if (length !== newData.length) {\n      throw new RangeError('data length does not match given dimensions');\n    }\n    let newMatrix = new Matrix(newRows, newColumns);\n    for (let row = 0; row < newRows; row++) {\n      for (let column = 0; column < newColumns; column++) {\n        newMatrix.set(row, column, newData[row * newColumns + column]);\n      }\n    }\n    return newMatrix;\n  }\n\n  static rowVector(newData) {\n    let vector = new Matrix(1, newData.length);\n    for (let i = 0; i < newData.length; i++) {\n      vector.set(0, i, newData[i]);\n    }\n    return vector;\n  }\n\n  static columnVector(newData) {\n    let vector = new Matrix(newData.length, 1);\n    for (let i = 0; i < newData.length; i++) {\n      vector.set(i, 0, newData[i]);\n    }\n    return vector;\n  }\n\n  static zeros(rows, columns) {\n    return new Matrix(rows, columns);\n  }\n\n  static ones(rows, columns) {\n    return new Matrix(rows, columns).fill(1);\n  }\n\n  static rand(rows, columns, options = {}) {\n    if (typeof options !== 'object') {\n      throw new TypeError('options must be an object');\n    }\n    const { random = Math.random } = options;\n    let matrix = new Matrix(rows, columns);\n    for (let i = 0; i < rows; i++) {\n      for (let j = 0; j < columns; j++) {\n        matrix.set(i, j, random());\n      }\n    }\n    return matrix;\n  }\n\n  static randInt(rows, columns, options = {}) {\n    if (typeof options !== 'object') {\n      throw new TypeError('options must be an object');\n    }\n    const { min = 0, max = 1000, random = Math.random } = options;\n    if (!Number.isInteger(min)) throw new TypeError('min must be an integer');\n    if (!Number.isInteger(max)) throw new TypeError('max must be an integer');\n    if (min >= max) throw new RangeError('min must be smaller than max');\n    let interval = max - min;\n    let matrix = new Matrix(rows, columns);\n    for (let i = 0; i < rows; i++) {\n      for (let j = 0; j < columns; j++) {\n        let value = min + Math.round(random() * interval);\n        matrix.set(i, j, value);\n      }\n    }\n    return matrix;\n  }\n\n  static eye(rows, columns, value) {\n    if (columns === undefined) columns = rows;\n    if (value === undefined) value = 1;\n    let min = Math.min(rows, columns);\n    let matrix = this.zeros(rows, columns);\n    for (let i = 0; i < min; i++) {\n      matrix.set(i, i, value);\n    }\n    return matrix;\n  }\n\n  static diag(data, rows, columns) {\n    let l = data.length;\n    if (rows === undefined) rows = l;\n    if (columns === undefined) columns = rows;\n    let min = Math.min(l, rows, columns);\n    let matrix = this.zeros(rows, columns);\n    for (let i = 0; i < min; i++) {\n      matrix.set(i, i, data[i]);\n    }\n    return matrix;\n  }\n\n  static min(matrix1, matrix2) {\n    matrix1 = this.checkMatrix(matrix1);\n    matrix2 = this.checkMatrix(matrix2);\n    let rows = matrix1.rows;\n    let columns = matrix1.columns;\n    let result = new Matrix(rows, columns);\n    for (let i = 0; i < rows; i++) {\n      for (let j = 0; j < columns; j++) {\n        result.set(i, j, Math.min(matrix1.get(i, j), matrix2.get(i, j)));\n      }\n    }\n    return result;\n  }\n\n  static max(matrix1, matrix2) {\n    matrix1 = this.checkMatrix(matrix1);\n    matrix2 = this.checkMatrix(matrix2);\n    let rows = matrix1.rows;\n    let columns = matrix1.columns;\n    let result = new this(rows, columns);\n    for (let i = 0; i < rows; i++) {\n      for (let j = 0; j < columns; j++) {\n        result.set(i, j, Math.max(matrix1.get(i, j), matrix2.get(i, j)));\n      }\n    }\n    return result;\n  }\n\n  static checkMatrix(value) {\n    return AbstractMatrix.isMatrix(value) ? value : new Matrix(value);\n  }\n\n  static isMatrix(value) {\n    return value != null && value.klass === 'Matrix';\n  }\n\n  get size() {\n    return this.rows * this.columns;\n  }\n\n  apply(callback) {\n    if (typeof callback !== 'function') {\n      throw new TypeError('callback must be a function');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        callback.call(this, i, j);\n      }\n    }\n    return this;\n  }\n\n  to1DArray() {\n    let array = [];\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        array.push(this.get(i, j));\n      }\n    }\n    return array;\n  }\n\n  to2DArray() {\n    let copy = [];\n    for (let i = 0; i < this.rows; i++) {\n      copy.push([]);\n      for (let j = 0; j < this.columns; j++) {\n        copy[i].push(this.get(i, j));\n      }\n    }\n    return copy;\n  }\n\n  toJSON() {\n    return this.to2DArray();\n  }\n\n  isRowVector() {\n    return this.rows === 1;\n  }\n\n  isColumnVector() {\n    return this.columns === 1;\n  }\n\n  isVector() {\n    return this.rows === 1 || this.columns === 1;\n  }\n\n  isSquare() {\n    return this.rows === this.columns;\n  }\n\n  isEmpty() {\n    return this.rows === 0 || this.columns === 0;\n  }\n\n  isSymmetric() {\n    if (this.isSquare()) {\n      for (let i = 0; i < this.rows; i++) {\n        for (let j = 0; j <= i; j++) {\n          if (this.get(i, j) !== this.get(j, i)) {\n            return false;\n          }\n        }\n      }\n      return true;\n    }\n    return false;\n  }\n\n  isEchelonForm() {\n    let i = 0;\n    let j = 0;\n    let previousColumn = -1;\n    let isEchelonForm = true;\n    let checked = false;\n    while (i < this.rows && isEchelonForm) {\n      j = 0;\n      checked = false;\n      while (j < this.columns && checked === false) {\n        if (this.get(i, j) === 0) {\n          j++;\n        } else if (this.get(i, j) === 1 && j > previousColumn) {\n          checked = true;\n          previousColumn = j;\n        } else {\n          isEchelonForm = false;\n          checked = true;\n        }\n      }\n      i++;\n    }\n    return isEchelonForm;\n  }\n\n  isReducedEchelonForm() {\n    let i = 0;\n    let j = 0;\n    let previousColumn = -1;\n    let isReducedEchelonForm = true;\n    let checked = false;\n    while (i < this.rows && isReducedEchelonForm) {\n      j = 0;\n      checked = false;\n      while (j < this.columns && checked === false) {\n        if (this.get(i, j) === 0) {\n          j++;\n        } else if (this.get(i, j) === 1 && j > previousColumn) {\n          checked = true;\n          previousColumn = j;\n        } else {\n          isReducedEchelonForm = false;\n          checked = true;\n        }\n      }\n      for (let k = j + 1; k < this.rows; k++) {\n        if (this.get(i, k) !== 0) {\n          isReducedEchelonForm = false;\n        }\n      }\n      i++;\n    }\n    return isReducedEchelonForm;\n  }\n\n  echelonForm() {\n    let result = this.clone();\n    let h = 0;\n    let k = 0;\n    while (h < result.rows && k < result.columns) {\n      let iMax = h;\n      for (let i = h; i < result.rows; i++) {\n        if (result.get(i, k) > result.get(iMax, k)) {\n          iMax = i;\n        }\n      }\n      if (result.get(iMax, k) === 0) {\n        k++;\n      } else {\n        result.swapRows(h, iMax);\n        let tmp = result.get(h, k);\n        for (let j = k; j < result.columns; j++) {\n          result.set(h, j, result.get(h, j) / tmp);\n        }\n        for (let i = h + 1; i < result.rows; i++) {\n          let factor = result.get(i, k) / result.get(h, k);\n          result.set(i, k, 0);\n          for (let j = k + 1; j < result.columns; j++) {\n            result.set(i, j, result.get(i, j) - result.get(h, j) * factor);\n          }\n        }\n        h++;\n        k++;\n      }\n    }\n    return result;\n  }\n\n  reducedEchelonForm() {\n    let result = this.echelonForm();\n    let m = result.columns;\n    let n = result.rows;\n    let h = n - 1;\n    while (h >= 0) {\n      if (result.maxRow(h) === 0) {\n        h--;\n      } else {\n        let p = 0;\n        let pivot = false;\n        while (p < n && pivot === false) {\n          if (result.get(h, p) === 1) {\n            pivot = true;\n          } else {\n            p++;\n          }\n        }\n        for (let i = 0; i < h; i++) {\n          let factor = result.get(i, p);\n          for (let j = p; j < m; j++) {\n            let tmp = result.get(i, j) - factor * result.get(h, j);\n            result.set(i, j, tmp);\n          }\n        }\n        h--;\n      }\n    }\n    return result;\n  }\n\n  set() {\n    throw new Error('set method is unimplemented');\n  }\n\n  get() {\n    throw new Error('get method is unimplemented');\n  }\n\n  repeat(options = {}) {\n    if (typeof options !== 'object') {\n      throw new TypeError('options must be an object');\n    }\n    const { rows = 1, columns = 1 } = options;\n    if (!Number.isInteger(rows) || rows <= 0) {\n      throw new TypeError('rows must be a positive integer');\n    }\n    if (!Number.isInteger(columns) || columns <= 0) {\n      throw new TypeError('columns must be a positive integer');\n    }\n    let matrix = new Matrix(this.rows * rows, this.columns * columns);\n    for (let i = 0; i < rows; i++) {\n      for (let j = 0; j < columns; j++) {\n        matrix.setSubMatrix(this, this.rows * i, this.columns * j);\n      }\n    }\n    return matrix;\n  }\n\n  fill(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, value);\n      }\n    }\n    return this;\n  }\n\n  neg() {\n    return this.mulS(-1);\n  }\n\n  getRow(index) {\n    checkRowIndex(this, index);\n    let row = [];\n    for (let i = 0; i < this.columns; i++) {\n      row.push(this.get(index, i));\n    }\n    return row;\n  }\n\n  getRowVector(index) {\n    return Matrix.rowVector(this.getRow(index));\n  }\n\n  setRow(index, array) {\n    checkRowIndex(this, index);\n    array = checkRowVector(this, array);\n    for (let i = 0; i < this.columns; i++) {\n      this.set(index, i, array[i]);\n    }\n    return this;\n  }\n\n  swapRows(row1, row2) {\n    checkRowIndex(this, row1);\n    checkRowIndex(this, row2);\n    for (let i = 0; i < this.columns; i++) {\n      let temp = this.get(row1, i);\n      this.set(row1, i, this.get(row2, i));\n      this.set(row2, i, temp);\n    }\n    return this;\n  }\n\n  getColumn(index) {\n    checkColumnIndex(this, index);\n    let column = [];\n    for (let i = 0; i < this.rows; i++) {\n      column.push(this.get(i, index));\n    }\n    return column;\n  }\n\n  getColumnVector(index) {\n    return Matrix.columnVector(this.getColumn(index));\n  }\n\n  setColumn(index, array) {\n    checkColumnIndex(this, index);\n    array = checkColumnVector(this, array);\n    for (let i = 0; i < this.rows; i++) {\n      this.set(i, index, array[i]);\n    }\n    return this;\n  }\n\n  swapColumns(column1, column2) {\n    checkColumnIndex(this, column1);\n    checkColumnIndex(this, column2);\n    for (let i = 0; i < this.rows; i++) {\n      let temp = this.get(i, column1);\n      this.set(i, column1, this.get(i, column2));\n      this.set(i, column2, temp);\n    }\n    return this;\n  }\n\n  addRowVector(vector) {\n    vector = checkRowVector(this, vector);\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) + vector[j]);\n      }\n    }\n    return this;\n  }\n\n  subRowVector(vector) {\n    vector = checkRowVector(this, vector);\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) - vector[j]);\n      }\n    }\n    return this;\n  }\n\n  mulRowVector(vector) {\n    vector = checkRowVector(this, vector);\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) * vector[j]);\n      }\n    }\n    return this;\n  }\n\n  divRowVector(vector) {\n    vector = checkRowVector(this, vector);\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) / vector[j]);\n      }\n    }\n    return this;\n  }\n\n  addColumnVector(vector) {\n    vector = checkColumnVector(this, vector);\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) + vector[i]);\n      }\n    }\n    return this;\n  }\n\n  subColumnVector(vector) {\n    vector = checkColumnVector(this, vector);\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) - vector[i]);\n      }\n    }\n    return this;\n  }\n\n  mulColumnVector(vector) {\n    vector = checkColumnVector(this, vector);\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) * vector[i]);\n      }\n    }\n    return this;\n  }\n\n  divColumnVector(vector) {\n    vector = checkColumnVector(this, vector);\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) / vector[i]);\n      }\n    }\n    return this;\n  }\n\n  mulRow(index, value) {\n    checkRowIndex(this, index);\n    for (let i = 0; i < this.columns; i++) {\n      this.set(index, i, this.get(index, i) * value);\n    }\n    return this;\n  }\n\n  mulColumn(index, value) {\n    checkColumnIndex(this, index);\n    for (let i = 0; i < this.rows; i++) {\n      this.set(i, index, this.get(i, index) * value);\n    }\n    return this;\n  }\n\n  max(by) {\n    if (this.isEmpty()) {\n      return NaN;\n    }\n    switch (by) {\n      case 'row': {\n        const max = new Array(this.rows).fill(Number.NEGATIVE_INFINITY);\n        for (let row = 0; row < this.rows; row++) {\n          for (let column = 0; column < this.columns; column++) {\n            if (this.get(row, column) > max[row]) {\n              max[row] = this.get(row, column);\n            }\n          }\n        }\n        return max;\n      }\n      case 'column': {\n        const max = new Array(this.columns).fill(Number.NEGATIVE_INFINITY);\n        for (let row = 0; row < this.rows; row++) {\n          for (let column = 0; column < this.columns; column++) {\n            if (this.get(row, column) > max[column]) {\n              max[column] = this.get(row, column);\n            }\n          }\n        }\n        return max;\n      }\n      case undefined: {\n        let max = this.get(0, 0);\n        for (let row = 0; row < this.rows; row++) {\n          for (let column = 0; column < this.columns; column++) {\n            if (this.get(row, column) > max) {\n              max = this.get(row, column);\n            }\n          }\n        }\n        return max;\n      }\n      default:\n        throw new Error(`invalid option: ${by}`);\n    }\n  }\n\n  maxIndex() {\n    checkNonEmpty(this);\n    let v = this.get(0, 0);\n    let idx = [0, 0];\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        if (this.get(i, j) > v) {\n          v = this.get(i, j);\n          idx[0] = i;\n          idx[1] = j;\n        }\n      }\n    }\n    return idx;\n  }\n\n  min(by) {\n    if (this.isEmpty()) {\n      return NaN;\n    }\n\n    switch (by) {\n      case 'row': {\n        const min = new Array(this.rows).fill(Number.POSITIVE_INFINITY);\n        for (let row = 0; row < this.rows; row++) {\n          for (let column = 0; column < this.columns; column++) {\n            if (this.get(row, column) < min[row]) {\n              min[row] = this.get(row, column);\n            }\n          }\n        }\n        return min;\n      }\n      case 'column': {\n        const min = new Array(this.columns).fill(Number.POSITIVE_INFINITY);\n        for (let row = 0; row < this.rows; row++) {\n          for (let column = 0; column < this.columns; column++) {\n            if (this.get(row, column) < min[column]) {\n              min[column] = this.get(row, column);\n            }\n          }\n        }\n        return min;\n      }\n      case undefined: {\n        let min = this.get(0, 0);\n        for (let row = 0; row < this.rows; row++) {\n          for (let column = 0; column < this.columns; column++) {\n            if (this.get(row, column) < min) {\n              min = this.get(row, column);\n            }\n          }\n        }\n        return min;\n      }\n      default:\n        throw new Error(`invalid option: ${by}`);\n    }\n  }\n\n  minIndex() {\n    checkNonEmpty(this);\n    let v = this.get(0, 0);\n    let idx = [0, 0];\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        if (this.get(i, j) < v) {\n          v = this.get(i, j);\n          idx[0] = i;\n          idx[1] = j;\n        }\n      }\n    }\n    return idx;\n  }\n\n  maxRow(row) {\n    checkRowIndex(this, row);\n    if (this.isEmpty()) {\n      return NaN;\n    }\n    let v = this.get(row, 0);\n    for (let i = 1; i < this.columns; i++) {\n      if (this.get(row, i) > v) {\n        v = this.get(row, i);\n      }\n    }\n    return v;\n  }\n\n  maxRowIndex(row) {\n    checkRowIndex(this, row);\n    checkNonEmpty(this);\n    let v = this.get(row, 0);\n    let idx = [row, 0];\n    for (let i = 1; i < this.columns; i++) {\n      if (this.get(row, i) > v) {\n        v = this.get(row, i);\n        idx[1] = i;\n      }\n    }\n    return idx;\n  }\n\n  minRow(row) {\n    checkRowIndex(this, row);\n    if (this.isEmpty()) {\n      return NaN;\n    }\n    let v = this.get(row, 0);\n    for (let i = 1; i < this.columns; i++) {\n      if (this.get(row, i) < v) {\n        v = this.get(row, i);\n      }\n    }\n    return v;\n  }\n\n  minRowIndex(row) {\n    checkRowIndex(this, row);\n    checkNonEmpty(this);\n    let v = this.get(row, 0);\n    let idx = [row, 0];\n    for (let i = 1; i < this.columns; i++) {\n      if (this.get(row, i) < v) {\n        v = this.get(row, i);\n        idx[1] = i;\n      }\n    }\n    return idx;\n  }\n\n  maxColumn(column) {\n    checkColumnIndex(this, column);\n    if (this.isEmpty()) {\n      return NaN;\n    }\n    let v = this.get(0, column);\n    for (let i = 1; i < this.rows; i++) {\n      if (this.get(i, column) > v) {\n        v = this.get(i, column);\n      }\n    }\n    return v;\n  }\n\n  maxColumnIndex(column) {\n    checkColumnIndex(this, column);\n    checkNonEmpty(this);\n    let v = this.get(0, column);\n    let idx = [0, column];\n    for (let i = 1; i < this.rows; i++) {\n      if (this.get(i, column) > v) {\n        v = this.get(i, column);\n        idx[0] = i;\n      }\n    }\n    return idx;\n  }\n\n  minColumn(column) {\n    checkColumnIndex(this, column);\n    if (this.isEmpty()) {\n      return NaN;\n    }\n    let v = this.get(0, column);\n    for (let i = 1; i < this.rows; i++) {\n      if (this.get(i, column) < v) {\n        v = this.get(i, column);\n      }\n    }\n    return v;\n  }\n\n  minColumnIndex(column) {\n    checkColumnIndex(this, column);\n    checkNonEmpty(this);\n    let v = this.get(0, column);\n    let idx = [0, column];\n    for (let i = 1; i < this.rows; i++) {\n      if (this.get(i, column) < v) {\n        v = this.get(i, column);\n        idx[0] = i;\n      }\n    }\n    return idx;\n  }\n\n  diag() {\n    let min = Math.min(this.rows, this.columns);\n    let diag = [];\n    for (let i = 0; i < min; i++) {\n      diag.push(this.get(i, i));\n    }\n    return diag;\n  }\n\n  norm(type = 'frobenius') {\n    let result = 0;\n    if (type === 'max') {\n      return this.max();\n    } else if (type === 'frobenius') {\n      for (let i = 0; i < this.rows; i++) {\n        for (let j = 0; j < this.columns; j++) {\n          result = result + this.get(i, j) * this.get(i, j);\n        }\n      }\n      return Math.sqrt(result);\n    } else {\n      throw new RangeError(`unknown norm type: ${type}`);\n    }\n  }\n\n  cumulativeSum() {\n    let sum = 0;\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        sum += this.get(i, j);\n        this.set(i, j, sum);\n      }\n    }\n    return this;\n  }\n\n  dot(vector2) {\n    if (AbstractMatrix.isMatrix(vector2)) vector2 = vector2.to1DArray();\n    let vector1 = this.to1DArray();\n    if (vector1.length !== vector2.length) {\n      throw new RangeError('vectors do not have the same size');\n    }\n    let dot = 0;\n    for (let i = 0; i < vector1.length; i++) {\n      dot += vector1[i] * vector2[i];\n    }\n    return dot;\n  }\n\n  mmul(other) {\n    other = Matrix.checkMatrix(other);\n\n    let m = this.rows;\n    let n = this.columns;\n    let p = other.columns;\n\n    let result = new Matrix(m, p);\n\n    let Bcolj = new Float64Array(n);\n    for (let j = 0; j < p; j++) {\n      for (let k = 0; k < n; k++) {\n        Bcolj[k] = other.get(k, j);\n      }\n\n      for (let i = 0; i < m; i++) {\n        let s = 0;\n        for (let k = 0; k < n; k++) {\n          s += this.get(i, k) * Bcolj[k];\n        }\n\n        result.set(i, j, s);\n      }\n    }\n    return result;\n  }\n\n  strassen2x2(other) {\n    other = Matrix.checkMatrix(other);\n    let result = new Matrix(2, 2);\n    const a11 = this.get(0, 0);\n    const b11 = other.get(0, 0);\n    const a12 = this.get(0, 1);\n    const b12 = other.get(0, 1);\n    const a21 = this.get(1, 0);\n    const b21 = other.get(1, 0);\n    const a22 = this.get(1, 1);\n    const b22 = other.get(1, 1);\n\n    // Compute intermediate values.\n    const m1 = (a11 + a22) * (b11 + b22);\n    const m2 = (a21 + a22) * b11;\n    const m3 = a11 * (b12 - b22);\n    const m4 = a22 * (b21 - b11);\n    const m5 = (a11 + a12) * b22;\n    const m6 = (a21 - a11) * (b11 + b12);\n    const m7 = (a12 - a22) * (b21 + b22);\n\n    // Combine intermediate values into the output.\n    const c00 = m1 + m4 - m5 + m7;\n    const c01 = m3 + m5;\n    const c10 = m2 + m4;\n    const c11 = m1 - m2 + m3 + m6;\n\n    result.set(0, 0, c00);\n    result.set(0, 1, c01);\n    result.set(1, 0, c10);\n    result.set(1, 1, c11);\n    return result;\n  }\n\n  strassen3x3(other) {\n    other = Matrix.checkMatrix(other);\n    let result = new Matrix(3, 3);\n\n    const a00 = this.get(0, 0);\n    const a01 = this.get(0, 1);\n    const a02 = this.get(0, 2);\n    const a10 = this.get(1, 0);\n    const a11 = this.get(1, 1);\n    const a12 = this.get(1, 2);\n    const a20 = this.get(2, 0);\n    const a21 = this.get(2, 1);\n    const a22 = this.get(2, 2);\n\n    const b00 = other.get(0, 0);\n    const b01 = other.get(0, 1);\n    const b02 = other.get(0, 2);\n    const b10 = other.get(1, 0);\n    const b11 = other.get(1, 1);\n    const b12 = other.get(1, 2);\n    const b20 = other.get(2, 0);\n    const b21 = other.get(2, 1);\n    const b22 = other.get(2, 2);\n\n    const m1 = (a00 + a01 + a02 - a10 - a11 - a21 - a22) * b11;\n    const m2 = (a00 - a10) * (-b01 + b11);\n    const m3 = a11 * (-b00 + b01 + b10 - b11 - b12 - b20 + b22);\n    const m4 = (-a00 + a10 + a11) * (b00 - b01 + b11);\n    const m5 = (a10 + a11) * (-b00 + b01);\n    const m6 = a00 * b00;\n    const m7 = (-a00 + a20 + a21) * (b00 - b02 + b12);\n    const m8 = (-a00 + a20) * (b02 - b12);\n    const m9 = (a20 + a21) * (-b00 + b02);\n    const m10 = (a00 + a01 + a02 - a11 - a12 - a20 - a21) * b12;\n    const m11 = a21 * (-b00 + b02 + b10 - b11 - b12 - b20 + b21);\n    const m12 = (-a02 + a21 + a22) * (b11 + b20 - b21);\n    const m13 = (a02 - a22) * (b11 - b21);\n    const m14 = a02 * b20;\n    const m15 = (a21 + a22) * (-b20 + b21);\n    const m16 = (-a02 + a11 + a12) * (b12 + b20 - b22);\n    const m17 = (a02 - a12) * (b12 - b22);\n    const m18 = (a11 + a12) * (-b20 + b22);\n    const m19 = a01 * b10;\n    const m20 = a12 * b21;\n    const m21 = a10 * b02;\n    const m22 = a20 * b01;\n    const m23 = a22 * b22;\n\n    const c00 = m6 + m14 + m19;\n    const c01 = m1 + m4 + m5 + m6 + m12 + m14 + m15;\n    const c02 = m6 + m7 + m9 + m10 + m14 + m16 + m18;\n    const c10 = m2 + m3 + m4 + m6 + m14 + m16 + m17;\n    const c11 = m2 + m4 + m5 + m6 + m20;\n    const c12 = m14 + m16 + m17 + m18 + m21;\n    const c20 = m6 + m7 + m8 + m11 + m12 + m13 + m14;\n    const c21 = m12 + m13 + m14 + m15 + m22;\n    const c22 = m6 + m7 + m8 + m9 + m23;\n\n    result.set(0, 0, c00);\n    result.set(0, 1, c01);\n    result.set(0, 2, c02);\n    result.set(1, 0, c10);\n    result.set(1, 1, c11);\n    result.set(1, 2, c12);\n    result.set(2, 0, c20);\n    result.set(2, 1, c21);\n    result.set(2, 2, c22);\n    return result;\n  }\n\n  mmulStrassen(y) {\n    y = Matrix.checkMatrix(y);\n    let x = this.clone();\n    let r1 = x.rows;\n    let c1 = x.columns;\n    let r2 = y.rows;\n    let c2 = y.columns;\n    if (c1 !== r2) {\n      // eslint-disable-next-line no-console\n      console.warn(\n        `Multiplying ${r1} x ${c1} and ${r2} x ${c2} matrix: dimensions do not match.`,\n      );\n    }\n\n    // Put a matrix into the top left of a matrix of zeros.\n    // `rows` and `cols` are the dimensions of the output matrix.\n    function embed(mat, rows, cols) {\n      let r = mat.rows;\n      let c = mat.columns;\n      if (r === rows && c === cols) {\n        return mat;\n      } else {\n        let resultat = AbstractMatrix.zeros(rows, cols);\n        resultat = resultat.setSubMatrix(mat, 0, 0);\n        return resultat;\n      }\n    }\n\n    // Make sure both matrices are the same size.\n    // This is exclusively for simplicity:\n    // this algorithm can be implemented with matrices of different sizes.\n\n    let r = Math.max(r1, r2);\n    let c = Math.max(c1, c2);\n    x = embed(x, r, c);\n    y = embed(y, r, c);\n\n    // Our recursive multiplication function.\n    function blockMult(a, b, rows, cols) {\n      // For small matrices, resort to naive multiplication.\n      if (rows <= 512 || cols <= 512) {\n        return a.mmul(b); // a is equivalent to this\n      }\n\n      // Apply dynamic padding.\n      if (rows % 2 === 1 && cols % 2 === 1) {\n        a = embed(a, rows + 1, cols + 1);\n        b = embed(b, rows + 1, cols + 1);\n      } else if (rows % 2 === 1) {\n        a = embed(a, rows + 1, cols);\n        b = embed(b, rows + 1, cols);\n      } else if (cols % 2 === 1) {\n        a = embed(a, rows, cols + 1);\n        b = embed(b, rows, cols + 1);\n      }\n\n      let halfRows = parseInt(a.rows / 2, 10);\n      let halfCols = parseInt(a.columns / 2, 10);\n      // Subdivide input matrices.\n      let a11 = a.subMatrix(0, halfRows - 1, 0, halfCols - 1);\n      let b11 = b.subMatrix(0, halfRows - 1, 0, halfCols - 1);\n\n      let a12 = a.subMatrix(0, halfRows - 1, halfCols, a.columns - 1);\n      let b12 = b.subMatrix(0, halfRows - 1, halfCols, b.columns - 1);\n\n      let a21 = a.subMatrix(halfRows, a.rows - 1, 0, halfCols - 1);\n      let b21 = b.subMatrix(halfRows, b.rows - 1, 0, halfCols - 1);\n\n      let a22 = a.subMatrix(halfRows, a.rows - 1, halfCols, a.columns - 1);\n      let b22 = b.subMatrix(halfRows, b.rows - 1, halfCols, b.columns - 1);\n\n      // Compute intermediate values.\n      let m1 = blockMult(\n        AbstractMatrix.add(a11, a22),\n        AbstractMatrix.add(b11, b22),\n        halfRows,\n        halfCols,\n      );\n      let m2 = blockMult(AbstractMatrix.add(a21, a22), b11, halfRows, halfCols);\n      let m3 = blockMult(a11, AbstractMatrix.sub(b12, b22), halfRows, halfCols);\n      let m4 = blockMult(a22, AbstractMatrix.sub(b21, b11), halfRows, halfCols);\n      let m5 = blockMult(AbstractMatrix.add(a11, a12), b22, halfRows, halfCols);\n      let m6 = blockMult(\n        AbstractMatrix.sub(a21, a11),\n        AbstractMatrix.add(b11, b12),\n        halfRows,\n        halfCols,\n      );\n      let m7 = blockMult(\n        AbstractMatrix.sub(a12, a22),\n        AbstractMatrix.add(b21, b22),\n        halfRows,\n        halfCols,\n      );\n\n      // Combine intermediate values into the output.\n      let c11 = AbstractMatrix.add(m1, m4);\n      c11.sub(m5);\n      c11.add(m7);\n      let c12 = AbstractMatrix.add(m3, m5);\n      let c21 = AbstractMatrix.add(m2, m4);\n      let c22 = AbstractMatrix.sub(m1, m2);\n      c22.add(m3);\n      c22.add(m6);\n\n      // Crop output to the desired size (undo dynamic padding).\n      let resultat = AbstractMatrix.zeros(2 * c11.rows, 2 * c11.columns);\n      resultat = resultat.setSubMatrix(c11, 0, 0);\n      resultat = resultat.setSubMatrix(c12, c11.rows, 0);\n      resultat = resultat.setSubMatrix(c21, 0, c11.columns);\n      resultat = resultat.setSubMatrix(c22, c11.rows, c11.columns);\n      return resultat.subMatrix(0, rows - 1, 0, cols - 1);\n    }\n\n    return blockMult(x, y, r, c);\n  }\n\n  scaleRows(options = {}) {\n    if (typeof options !== 'object') {\n      throw new TypeError('options must be an object');\n    }\n    const { min = 0, max = 1 } = options;\n    if (!Number.isFinite(min)) throw new TypeError('min must be a number');\n    if (!Number.isFinite(max)) throw new TypeError('max must be a number');\n    if (min >= max) throw new RangeError('min must be smaller than max');\n    let newMatrix = new Matrix(this.rows, this.columns);\n    for (let i = 0; i < this.rows; i++) {\n      const row = this.getRow(i);\n      if (row.length > 0) {\n        rescale(row, { min, max, output: row });\n      }\n      newMatrix.setRow(i, row);\n    }\n    return newMatrix;\n  }\n\n  scaleColumns(options = {}) {\n    if (typeof options !== 'object') {\n      throw new TypeError('options must be an object');\n    }\n    const { min = 0, max = 1 } = options;\n    if (!Number.isFinite(min)) throw new TypeError('min must be a number');\n    if (!Number.isFinite(max)) throw new TypeError('max must be a number');\n    if (min >= max) throw new RangeError('min must be smaller than max');\n    let newMatrix = new Matrix(this.rows, this.columns);\n    for (let i = 0; i < this.columns; i++) {\n      const column = this.getColumn(i);\n      if (column.length) {\n        rescale(column, {\n          min: min,\n          max: max,\n          output: column,\n        });\n      }\n      newMatrix.setColumn(i, column);\n    }\n    return newMatrix;\n  }\n\n  flipRows() {\n    const middle = Math.ceil(this.columns / 2);\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < middle; j++) {\n        let first = this.get(i, j);\n        let last = this.get(i, this.columns - 1 - j);\n        this.set(i, j, last);\n        this.set(i, this.columns - 1 - j, first);\n      }\n    }\n    return this;\n  }\n\n  flipColumns() {\n    const middle = Math.ceil(this.rows / 2);\n    for (let j = 0; j < this.columns; j++) {\n      for (let i = 0; i < middle; i++) {\n        let first = this.get(i, j);\n        let last = this.get(this.rows - 1 - i, j);\n        this.set(i, j, last);\n        this.set(this.rows - 1 - i, j, first);\n      }\n    }\n    return this;\n  }\n\n  kroneckerProduct(other) {\n    other = Matrix.checkMatrix(other);\n\n    let m = this.rows;\n    let n = this.columns;\n    let p = other.rows;\n    let q = other.columns;\n\n    let result = new Matrix(m * p, n * q);\n    for (let i = 0; i < m; i++) {\n      for (let j = 0; j < n; j++) {\n        for (let k = 0; k < p; k++) {\n          for (let l = 0; l < q; l++) {\n            result.set(p * i + k, q * j + l, this.get(i, j) * other.get(k, l));\n          }\n        }\n      }\n    }\n    return result;\n  }\n\n  kroneckerSum(other) {\n    other = Matrix.checkMatrix(other);\n    if (!this.isSquare() || !other.isSquare()) {\n      throw new Error('Kronecker Sum needs two Square Matrices');\n    }\n    let m = this.rows;\n    let n = other.rows;\n    let AxI = this.kroneckerProduct(Matrix.eye(n, n));\n    let IxB = Matrix.eye(m, m).kroneckerProduct(other);\n    return AxI.add(IxB);\n  }\n\n  transpose() {\n    let result = new Matrix(this.columns, this.rows);\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        result.set(j, i, this.get(i, j));\n      }\n    }\n    return result;\n  }\n\n  sortRows(compareFunction = compareNumbers) {\n    for (let i = 0; i < this.rows; i++) {\n      this.setRow(i, this.getRow(i).sort(compareFunction));\n    }\n    return this;\n  }\n\n  sortColumns(compareFunction = compareNumbers) {\n    for (let i = 0; i < this.columns; i++) {\n      this.setColumn(i, this.getColumn(i).sort(compareFunction));\n    }\n    return this;\n  }\n\n  subMatrix(startRow, endRow, startColumn, endColumn) {\n    checkRange(this, startRow, endRow, startColumn, endColumn);\n    let newMatrix = new Matrix(\n      endRow - startRow + 1,\n      endColumn - startColumn + 1,\n    );\n    for (let i = startRow; i <= endRow; i++) {\n      for (let j = startColumn; j <= endColumn; j++) {\n        newMatrix.set(i - startRow, j - startColumn, this.get(i, j));\n      }\n    }\n    return newMatrix;\n  }\n\n  subMatrixRow(indices, startColumn, endColumn) {\n    if (startColumn === undefined) startColumn = 0;\n    if (endColumn === undefined) endColumn = this.columns - 1;\n    if (\n      startColumn > endColumn ||\n      startColumn < 0 ||\n      startColumn >= this.columns ||\n      endColumn < 0 ||\n      endColumn >= this.columns\n    ) {\n      throw new RangeError('Argument out of range');\n    }\n\n    let newMatrix = new Matrix(indices.length, endColumn - startColumn + 1);\n    for (let i = 0; i < indices.length; i++) {\n      for (let j = startColumn; j <= endColumn; j++) {\n        if (indices[i] < 0 || indices[i] >= this.rows) {\n          throw new RangeError(`Row index out of range: ${indices[i]}`);\n        }\n        newMatrix.set(i, j - startColumn, this.get(indices[i], j));\n      }\n    }\n    return newMatrix;\n  }\n\n  subMatrixColumn(indices, startRow, endRow) {\n    if (startRow === undefined) startRow = 0;\n    if (endRow === undefined) endRow = this.rows - 1;\n    if (\n      startRow > endRow ||\n      startRow < 0 ||\n      startRow >= this.rows ||\n      endRow < 0 ||\n      endRow >= this.rows\n    ) {\n      throw new RangeError('Argument out of range');\n    }\n\n    let newMatrix = new Matrix(endRow - startRow + 1, indices.length);\n    for (let i = 0; i < indices.length; i++) {\n      for (let j = startRow; j <= endRow; j++) {\n        if (indices[i] < 0 || indices[i] >= this.columns) {\n          throw new RangeError(`Column index out of range: ${indices[i]}`);\n        }\n        newMatrix.set(j - startRow, i, this.get(j, indices[i]));\n      }\n    }\n    return newMatrix;\n  }\n\n  setSubMatrix(matrix, startRow, startColumn) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (matrix.isEmpty()) {\n      return this;\n    }\n    let endRow = startRow + matrix.rows - 1;\n    let endColumn = startColumn + matrix.columns - 1;\n    checkRange(this, startRow, endRow, startColumn, endColumn);\n    for (let i = 0; i < matrix.rows; i++) {\n      for (let j = 0; j < matrix.columns; j++) {\n        this.set(startRow + i, startColumn + j, matrix.get(i, j));\n      }\n    }\n    return this;\n  }\n\n  selection(rowIndices, columnIndices) {\n    checkRowIndices(this, rowIndices);\n    checkColumnIndices(this, columnIndices);\n    let newMatrix = new Matrix(rowIndices.length, columnIndices.length);\n    for (let i = 0; i < rowIndices.length; i++) {\n      let rowIndex = rowIndices[i];\n      for (let j = 0; j < columnIndices.length; j++) {\n        let columnIndex = columnIndices[j];\n        newMatrix.set(i, j, this.get(rowIndex, columnIndex));\n      }\n    }\n    return newMatrix;\n  }\n\n  trace() {\n    let min = Math.min(this.rows, this.columns);\n    let trace = 0;\n    for (let i = 0; i < min; i++) {\n      trace += this.get(i, i);\n    }\n    return trace;\n  }\n\n  clone() {\n    let newMatrix = new Matrix(this.rows, this.columns);\n    for (let row = 0; row < this.rows; row++) {\n      for (let column = 0; column < this.columns; column++) {\n        newMatrix.set(row, column, this.get(row, column));\n      }\n    }\n    return newMatrix;\n  }\n\n  sum(by) {\n    switch (by) {\n      case 'row':\n        return sumByRow(this);\n      case 'column':\n        return sumByColumn(this);\n      case undefined:\n        return sumAll(this);\n      default:\n        throw new Error(`invalid option: ${by}`);\n    }\n  }\n\n  product(by) {\n    switch (by) {\n      case 'row':\n        return productByRow(this);\n      case 'column':\n        return productByColumn(this);\n      case undefined:\n        return productAll(this);\n      default:\n        throw new Error(`invalid option: ${by}`);\n    }\n  }\n\n  mean(by) {\n    const sum = this.sum(by);\n    switch (by) {\n      case 'row': {\n        for (let i = 0; i < this.rows; i++) {\n          sum[i] /= this.columns;\n        }\n        return sum;\n      }\n      case 'column': {\n        for (let i = 0; i < this.columns; i++) {\n          sum[i] /= this.rows;\n        }\n        return sum;\n      }\n      case undefined:\n        return sum / this.size;\n      default:\n        throw new Error(`invalid option: ${by}`);\n    }\n  }\n\n  variance(by, options = {}) {\n    if (typeof by === 'object') {\n      options = by;\n      by = undefined;\n    }\n    if (typeof options !== 'object') {\n      throw new TypeError('options must be an object');\n    }\n    const { unbiased = true, mean = this.mean(by) } = options;\n    if (typeof unbiased !== 'boolean') {\n      throw new TypeError('unbiased must be a boolean');\n    }\n    switch (by) {\n      case 'row': {\n        if (!isAnyArray(mean)) {\n          throw new TypeError('mean must be an array');\n        }\n        return varianceByRow(this, unbiased, mean);\n      }\n      case 'column': {\n        if (!isAnyArray(mean)) {\n          throw new TypeError('mean must be an array');\n        }\n        return varianceByColumn(this, unbiased, mean);\n      }\n      case undefined: {\n        if (typeof mean !== 'number') {\n          throw new TypeError('mean must be a number');\n        }\n        return varianceAll(this, unbiased, mean);\n      }\n      default:\n        throw new Error(`invalid option: ${by}`);\n    }\n  }\n\n  standardDeviation(by, options) {\n    if (typeof by === 'object') {\n      options = by;\n      by = undefined;\n    }\n    const variance = this.variance(by, options);\n    if (by === undefined) {\n      return Math.sqrt(variance);\n    } else {\n      for (let i = 0; i < variance.length; i++) {\n        variance[i] = Math.sqrt(variance[i]);\n      }\n      return variance;\n    }\n  }\n\n  center(by, options = {}) {\n    if (typeof by === 'object') {\n      options = by;\n      by = undefined;\n    }\n    if (typeof options !== 'object') {\n      throw new TypeError('options must be an object');\n    }\n    const { center = this.mean(by) } = options;\n    switch (by) {\n      case 'row': {\n        if (!isAnyArray(center)) {\n          throw new TypeError('center must be an array');\n        }\n        centerByRow(this, center);\n        return this;\n      }\n      case 'column': {\n        if (!isAnyArray(center)) {\n          throw new TypeError('center must be an array');\n        }\n        centerByColumn(this, center);\n        return this;\n      }\n      case undefined: {\n        if (typeof center !== 'number') {\n          throw new TypeError('center must be a number');\n        }\n        centerAll(this, center);\n        return this;\n      }\n      default:\n        throw new Error(`invalid option: ${by}`);\n    }\n  }\n\n  scale(by, options = {}) {\n    if (typeof by === 'object') {\n      options = by;\n      by = undefined;\n    }\n    if (typeof options !== 'object') {\n      throw new TypeError('options must be an object');\n    }\n    let scale = options.scale;\n    switch (by) {\n      case 'row': {\n        if (scale === undefined) {\n          scale = getScaleByRow(this);\n        } else if (!isAnyArray(scale)) {\n          throw new TypeError('scale must be an array');\n        }\n        scaleByRow(this, scale);\n        return this;\n      }\n      case 'column': {\n        if (scale === undefined) {\n          scale = getScaleByColumn(this);\n        } else if (!isAnyArray(scale)) {\n          throw new TypeError('scale must be an array');\n        }\n        scaleByColumn(this, scale);\n        return this;\n      }\n      case undefined: {\n        if (scale === undefined) {\n          scale = getScaleAll(this);\n        } else if (typeof scale !== 'number') {\n          throw new TypeError('scale must be a number');\n        }\n        scaleAll(this, scale);\n        return this;\n      }\n      default:\n        throw new Error(`invalid option: ${by}`);\n    }\n  }\n\n  toString(options) {\n    return inspectMatrixWithOptions(this, options);\n  }\n}\n\nAbstractMatrix.prototype.klass = 'Matrix';\nif (typeof Symbol !== 'undefined') {\n  AbstractMatrix.prototype[Symbol.for('nodejs.util.inspect.custom')] =\n    inspectMatrix;\n}\n\nfunction compareNumbers(a, b) {\n  return a - b;\n}\n\nfunction isArrayOfNumbers(array) {\n  return array.every((element) => {\n    return typeof element === 'number';\n  });\n}\n\n// Synonyms\nAbstractMatrix.random = AbstractMatrix.rand;\nAbstractMatrix.randomInt = AbstractMatrix.randInt;\nAbstractMatrix.diagonal = AbstractMatrix.diag;\nAbstractMatrix.prototype.diagonal = AbstractMatrix.prototype.diag;\nAbstractMatrix.identity = AbstractMatrix.eye;\nAbstractMatrix.prototype.negate = AbstractMatrix.prototype.neg;\nAbstractMatrix.prototype.tensorProduct =\n  AbstractMatrix.prototype.kroneckerProduct;\n\nexport default class Matrix extends AbstractMatrix {\n  constructor(nRows, nColumns) {\n    super();\n    if (Matrix.isMatrix(nRows)) {\n      // eslint-disable-next-line no-constructor-return\n      return nRows.clone();\n    } else if (Number.isInteger(nRows) && nRows >= 0) {\n      // Create an empty matrix\n      this.data = [];\n      if (Number.isInteger(nColumns) && nColumns >= 0) {\n        for (let i = 0; i < nRows; i++) {\n          this.data.push(new Float64Array(nColumns));\n        }\n      } else {\n        throw new TypeError('nColumns must be a positive integer');\n      }\n    } else if (isAnyArray(nRows)) {\n      // Copy the values from the 2D array\n      const arrayData = nRows;\n      nRows = arrayData.length;\n      nColumns = nRows ? arrayData[0].length : 0;\n      if (typeof nColumns !== 'number') {\n        throw new TypeError(\n          'Data must be a 2D array with at least one element',\n        );\n      }\n      this.data = [];\n      for (let i = 0; i < nRows; i++) {\n        if (arrayData[i].length !== nColumns) {\n          throw new RangeError('Inconsistent array dimensions');\n        }\n        if (!isArrayOfNumbers(arrayData[i])) {\n          throw new TypeError('Input data contains non-numeric values');\n        }\n        this.data.push(Float64Array.from(arrayData[i]));\n      }\n    } else {\n      throw new TypeError(\n        'First argument must be a positive number or an array',\n      );\n    }\n    this.rows = nRows;\n    this.columns = nColumns;\n  }\n\n  set(rowIndex, columnIndex, value) {\n    this.data[rowIndex][columnIndex] = value;\n    return this;\n  }\n\n  get(rowIndex, columnIndex) {\n    return this.data[rowIndex][columnIndex];\n  }\n\n  removeRow(index) {\n    checkRowIndex(this, index);\n    this.data.splice(index, 1);\n    this.rows -= 1;\n    return this;\n  }\n\n  addRow(index, array) {\n    if (array === undefined) {\n      array = index;\n      index = this.rows;\n    }\n    checkRowIndex(this, index, true);\n    array = Float64Array.from(checkRowVector(this, array));\n    this.data.splice(index, 0, array);\n    this.rows += 1;\n    return this;\n  }\n\n  removeColumn(index) {\n    checkColumnIndex(this, index);\n    for (let i = 0; i < this.rows; i++) {\n      const newRow = new Float64Array(this.columns - 1);\n      for (let j = 0; j < index; j++) {\n        newRow[j] = this.data[i][j];\n      }\n      for (let j = index + 1; j < this.columns; j++) {\n        newRow[j - 1] = this.data[i][j];\n      }\n      this.data[i] = newRow;\n    }\n    this.columns -= 1;\n    return this;\n  }\n\n  addColumn(index, array) {\n    if (typeof array === 'undefined') {\n      array = index;\n      index = this.columns;\n    }\n    checkColumnIndex(this, index, true);\n    array = checkColumnVector(this, array);\n    for (let i = 0; i < this.rows; i++) {\n      const newRow = new Float64Array(this.columns + 1);\n      let j = 0;\n      for (; j < index; j++) {\n        newRow[j] = this.data[i][j];\n      }\n      newRow[j++] = array[i];\n      for (; j < this.columns + 1; j++) {\n        newRow[j] = this.data[i][j - 1];\n      }\n      this.data[i] = newRow;\n    }\n    this.columns += 1;\n    return this;\n  }\n}\n\ninstallMathOperations(AbstractMatrix, Matrix);\n","import { newArray } from './util';\n\nexport function sumByRow(matrix) {\n  let sum = newArray(matrix.rows);\n  for (let i = 0; i < matrix.rows; ++i) {\n    for (let j = 0; j < matrix.columns; ++j) {\n      sum[i] += matrix.get(i, j);\n    }\n  }\n  return sum;\n}\n\nexport function sumByColumn(matrix) {\n  let sum = newArray(matrix.columns);\n  for (let i = 0; i < matrix.rows; ++i) {\n    for (let j = 0; j < matrix.columns; ++j) {\n      sum[j] += matrix.get(i, j);\n    }\n  }\n  return sum;\n}\n\nexport function sumAll(matrix) {\n  let v = 0;\n  for (let i = 0; i < matrix.rows; i++) {\n    for (let j = 0; j < matrix.columns; j++) {\n      v += matrix.get(i, j);\n    }\n  }\n  return v;\n}\n\nexport function productByRow(matrix) {\n  let sum = newArray(matrix.rows, 1);\n  for (let i = 0; i < matrix.rows; ++i) {\n    for (let j = 0; j < matrix.columns; ++j) {\n      sum[i] *= matrix.get(i, j);\n    }\n  }\n  return sum;\n}\n\nexport function productByColumn(matrix) {\n  let sum = newArray(matrix.columns, 1);\n  for (let i = 0; i < matrix.rows; ++i) {\n    for (let j = 0; j < matrix.columns; ++j) {\n      sum[j] *= matrix.get(i, j);\n    }\n  }\n  return sum;\n}\n\nexport function productAll(matrix) {\n  let v = 1;\n  for (let i = 0; i < matrix.rows; i++) {\n    for (let j = 0; j < matrix.columns; j++) {\n      v *= matrix.get(i, j);\n    }\n  }\n  return v;\n}\n\nexport function varianceByRow(matrix, unbiased, mean) {\n  const rows = matrix.rows;\n  const cols = matrix.columns;\n  const variance = [];\n\n  for (let i = 0; i < rows; i++) {\n    let sum1 = 0;\n    let sum2 = 0;\n    let x = 0;\n    for (let j = 0; j < cols; j++) {\n      x = matrix.get(i, j) - mean[i];\n      sum1 += x;\n      sum2 += x * x;\n    }\n    if (unbiased) {\n      variance.push((sum2 - (sum1 * sum1) / cols) / (cols - 1));\n    } else {\n      variance.push((sum2 - (sum1 * sum1) / cols) / cols);\n    }\n  }\n  return variance;\n}\n\nexport function varianceByColumn(matrix, unbiased, mean) {\n  const rows = matrix.rows;\n  const cols = matrix.columns;\n  const variance = [];\n\n  for (let j = 0; j < cols; j++) {\n    let sum1 = 0;\n    let sum2 = 0;\n    let x = 0;\n    for (let i = 0; i < rows; i++) {\n      x = matrix.get(i, j) - mean[j];\n      sum1 += x;\n      sum2 += x * x;\n    }\n    if (unbiased) {\n      variance.push((sum2 - (sum1 * sum1) / rows) / (rows - 1));\n    } else {\n      variance.push((sum2 - (sum1 * sum1) / rows) / rows);\n    }\n  }\n  return variance;\n}\n\nexport function varianceAll(matrix, unbiased, mean) {\n  const rows = matrix.rows;\n  const cols = matrix.columns;\n  const size = rows * cols;\n\n  let sum1 = 0;\n  let sum2 = 0;\n  let x = 0;\n  for (let i = 0; i < rows; i++) {\n    for (let j = 0; j < cols; j++) {\n      x = matrix.get(i, j) - mean;\n      sum1 += x;\n      sum2 += x * x;\n    }\n  }\n  if (unbiased) {\n    return (sum2 - (sum1 * sum1) / size) / (size - 1);\n  } else {\n    return (sum2 - (sum1 * sum1) / size) / size;\n  }\n}\n\nexport function centerByRow(matrix, mean) {\n  for (let i = 0; i < matrix.rows; i++) {\n    for (let j = 0; j < matrix.columns; j++) {\n      matrix.set(i, j, matrix.get(i, j) - mean[i]);\n    }\n  }\n}\n\nexport function centerByColumn(matrix, mean) {\n  for (let i = 0; i < matrix.rows; i++) {\n    for (let j = 0; j < matrix.columns; j++) {\n      matrix.set(i, j, matrix.get(i, j) - mean[j]);\n    }\n  }\n}\n\nexport function centerAll(matrix, mean) {\n  for (let i = 0; i < matrix.rows; i++) {\n    for (let j = 0; j < matrix.columns; j++) {\n      matrix.set(i, j, matrix.get(i, j) - mean);\n    }\n  }\n}\n\nexport function getScaleByRow(matrix) {\n  const scale = [];\n  for (let i = 0; i < matrix.rows; i++) {\n    let sum = 0;\n    for (let j = 0; j < matrix.columns; j++) {\n      sum += Math.pow(matrix.get(i, j), 2) / (matrix.columns - 1);\n    }\n    scale.push(Math.sqrt(sum));\n  }\n  return scale;\n}\n\nexport function scaleByRow(matrix, scale) {\n  for (let i = 0; i < matrix.rows; i++) {\n    for (let j = 0; j < matrix.columns; j++) {\n      matrix.set(i, j, matrix.get(i, j) / scale[i]);\n    }\n  }\n}\n\nexport function getScaleByColumn(matrix) {\n  const scale = [];\n  for (let j = 0; j < matrix.columns; j++) {\n    let sum = 0;\n    for (let i = 0; i < matrix.rows; i++) {\n      sum += Math.pow(matrix.get(i, j), 2) / (matrix.rows - 1);\n    }\n    scale.push(Math.sqrt(sum));\n  }\n  return scale;\n}\n\nexport function scaleByColumn(matrix, scale) {\n  for (let i = 0; i < matrix.rows; i++) {\n    for (let j = 0; j < matrix.columns; j++) {\n      matrix.set(i, j, matrix.get(i, j) / scale[j]);\n    }\n  }\n}\n\nexport function getScaleAll(matrix) {\n  const divider = matrix.size - 1;\n  let sum = 0;\n  for (let j = 0; j < matrix.columns; j++) {\n    for (let i = 0; i < matrix.rows; i++) {\n      sum += Math.pow(matrix.get(i, j), 2) / divider;\n    }\n  }\n  return Math.sqrt(sum);\n}\n\nexport function scaleAll(matrix, scale) {\n  for (let i = 0; i < matrix.rows; i++) {\n    for (let j = 0; j < matrix.columns; j++) {\n      matrix.set(i, j, matrix.get(i, j) / scale);\n    }\n  }\n}\n","export function installMathOperations(AbstractMatrix, Matrix) {\n  AbstractMatrix.prototype.add = function add(value) {\n    if (typeof value === 'number') return this.addS(value);\n    return this.addM(value);\n  };\n\n  AbstractMatrix.prototype.addS = function addS(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) + value);\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.prototype.addM = function addM(matrix) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n      this.columns !== matrix.columns) {\n      throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) + matrix.get(i, j));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.add = function add(matrix, value) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.add(value);\n  };\n\n  AbstractMatrix.prototype.sub = function sub(value) {\n    if (typeof value === 'number') return this.subS(value);\n    return this.subM(value);\n  };\n\n  AbstractMatrix.prototype.subS = function subS(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) - value);\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.prototype.subM = function subM(matrix) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n      this.columns !== matrix.columns) {\n      throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) - matrix.get(i, j));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.sub = function sub(matrix, value) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.sub(value);\n  };\n  AbstractMatrix.prototype.subtract = AbstractMatrix.prototype.sub;\n  AbstractMatrix.prototype.subtractS = AbstractMatrix.prototype.subS;\n  AbstractMatrix.prototype.subtractM = AbstractMatrix.prototype.subM;\n  AbstractMatrix.subtract = AbstractMatrix.sub;\n\n  AbstractMatrix.prototype.mul = function mul(value) {\n    if (typeof value === 'number') return this.mulS(value);\n    return this.mulM(value);\n  };\n\n  AbstractMatrix.prototype.mulS = function mulS(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) * value);\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.prototype.mulM = function mulM(matrix) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n      this.columns !== matrix.columns) {\n      throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) * matrix.get(i, j));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.mul = function mul(matrix, value) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.mul(value);\n  };\n  AbstractMatrix.prototype.multiply = AbstractMatrix.prototype.mul;\n  AbstractMatrix.prototype.multiplyS = AbstractMatrix.prototype.mulS;\n  AbstractMatrix.prototype.multiplyM = AbstractMatrix.prototype.mulM;\n  AbstractMatrix.multiply = AbstractMatrix.mul;\n\n  AbstractMatrix.prototype.div = function div(value) {\n    if (typeof value === 'number') return this.divS(value);\n    return this.divM(value);\n  };\n\n  AbstractMatrix.prototype.divS = function divS(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) / value);\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.prototype.divM = function divM(matrix) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n      this.columns !== matrix.columns) {\n      throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) / matrix.get(i, j));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.div = function div(matrix, value) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.div(value);\n  };\n  AbstractMatrix.prototype.divide = AbstractMatrix.prototype.div;\n  AbstractMatrix.prototype.divideS = AbstractMatrix.prototype.divS;\n  AbstractMatrix.prototype.divideM = AbstractMatrix.prototype.divM;\n  AbstractMatrix.divide = AbstractMatrix.div;\n\n  AbstractMatrix.prototype.mod = function mod(value) {\n    if (typeof value === 'number') return this.modS(value);\n    return this.modM(value);\n  };\n\n  AbstractMatrix.prototype.modS = function modS(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) % value);\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.prototype.modM = function modM(matrix) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n      this.columns !== matrix.columns) {\n      throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) % matrix.get(i, j));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.mod = function mod(matrix, value) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.mod(value);\n  };\n  AbstractMatrix.prototype.modulus = AbstractMatrix.prototype.mod;\n  AbstractMatrix.prototype.modulusS = AbstractMatrix.prototype.modS;\n  AbstractMatrix.prototype.modulusM = AbstractMatrix.prototype.modM;\n  AbstractMatrix.modulus = AbstractMatrix.mod;\n\n  AbstractMatrix.prototype.and = function and(value) {\n    if (typeof value === 'number') return this.andS(value);\n    return this.andM(value);\n  };\n\n  AbstractMatrix.prototype.andS = function andS(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) & value);\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.prototype.andM = function andM(matrix) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n      this.columns !== matrix.columns) {\n      throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) & matrix.get(i, j));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.and = function and(matrix, value) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.and(value);\n  };\n\n  AbstractMatrix.prototype.or = function or(value) {\n    if (typeof value === 'number') return this.orS(value);\n    return this.orM(value);\n  };\n\n  AbstractMatrix.prototype.orS = function orS(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) | value);\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.prototype.orM = function orM(matrix) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n      this.columns !== matrix.columns) {\n      throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) | matrix.get(i, j));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.or = function or(matrix, value) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.or(value);\n  };\n\n  AbstractMatrix.prototype.xor = function xor(value) {\n    if (typeof value === 'number') return this.xorS(value);\n    return this.xorM(value);\n  };\n\n  AbstractMatrix.prototype.xorS = function xorS(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) ^ value);\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.prototype.xorM = function xorM(matrix) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n      this.columns !== matrix.columns) {\n      throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) ^ matrix.get(i, j));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.xor = function xor(matrix, value) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.xor(value);\n  };\n\n  AbstractMatrix.prototype.leftShift = function leftShift(value) {\n    if (typeof value === 'number') return this.leftShiftS(value);\n    return this.leftShiftM(value);\n  };\n\n  AbstractMatrix.prototype.leftShiftS = function leftShiftS(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) << value);\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.prototype.leftShiftM = function leftShiftM(matrix) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n      this.columns !== matrix.columns) {\n      throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) << matrix.get(i, j));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.leftShift = function leftShift(matrix, value) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.leftShift(value);\n  };\n\n  AbstractMatrix.prototype.signPropagatingRightShift = function signPropagatingRightShift(value) {\n    if (typeof value === 'number') return this.signPropagatingRightShiftS(value);\n    return this.signPropagatingRightShiftM(value);\n  };\n\n  AbstractMatrix.prototype.signPropagatingRightShiftS = function signPropagatingRightShiftS(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) >> value);\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.prototype.signPropagatingRightShiftM = function signPropagatingRightShiftM(matrix) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n      this.columns !== matrix.columns) {\n      throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) >> matrix.get(i, j));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.signPropagatingRightShift = function signPropagatingRightShift(matrix, value) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.signPropagatingRightShift(value);\n  };\n\n  AbstractMatrix.prototype.rightShift = function rightShift(value) {\n    if (typeof value === 'number') return this.rightShiftS(value);\n    return this.rightShiftM(value);\n  };\n\n  AbstractMatrix.prototype.rightShiftS = function rightShiftS(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) >>> value);\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.prototype.rightShiftM = function rightShiftM(matrix) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n      this.columns !== matrix.columns) {\n      throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, this.get(i, j) >>> matrix.get(i, j));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.rightShift = function rightShift(matrix, value) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.rightShift(value);\n  };\n  AbstractMatrix.prototype.zeroFillRightShift = AbstractMatrix.prototype.rightShift;\n  AbstractMatrix.prototype.zeroFillRightShiftS = AbstractMatrix.prototype.rightShiftS;\n  AbstractMatrix.prototype.zeroFillRightShiftM = AbstractMatrix.prototype.rightShiftM;\n  AbstractMatrix.zeroFillRightShift = AbstractMatrix.rightShift;\n\n  AbstractMatrix.prototype.not = function not() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, ~(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.not = function not(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.not();\n  };\n\n  AbstractMatrix.prototype.abs = function abs() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.abs(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.abs = function abs(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.abs();\n  };\n\n  AbstractMatrix.prototype.acos = function acos() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.acos(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.acos = function acos(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.acos();\n  };\n\n  AbstractMatrix.prototype.acosh = function acosh() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.acosh(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.acosh = function acosh(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.acosh();\n  };\n\n  AbstractMatrix.prototype.asin = function asin() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.asin(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.asin = function asin(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.asin();\n  };\n\n  AbstractMatrix.prototype.asinh = function asinh() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.asinh(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.asinh = function asinh(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.asinh();\n  };\n\n  AbstractMatrix.prototype.atan = function atan() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.atan(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.atan = function atan(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.atan();\n  };\n\n  AbstractMatrix.prototype.atanh = function atanh() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.atanh(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.atanh = function atanh(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.atanh();\n  };\n\n  AbstractMatrix.prototype.cbrt = function cbrt() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.cbrt(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.cbrt = function cbrt(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.cbrt();\n  };\n\n  AbstractMatrix.prototype.ceil = function ceil() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.ceil(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.ceil = function ceil(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.ceil();\n  };\n\n  AbstractMatrix.prototype.clz32 = function clz32() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.clz32(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.clz32 = function clz32(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.clz32();\n  };\n\n  AbstractMatrix.prototype.cos = function cos() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.cos(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.cos = function cos(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.cos();\n  };\n\n  AbstractMatrix.prototype.cosh = function cosh() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.cosh(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.cosh = function cosh(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.cosh();\n  };\n\n  AbstractMatrix.prototype.exp = function exp() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.exp(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.exp = function exp(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.exp();\n  };\n\n  AbstractMatrix.prototype.expm1 = function expm1() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.expm1(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.expm1 = function expm1(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.expm1();\n  };\n\n  AbstractMatrix.prototype.floor = function floor() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.floor(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.floor = function floor(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.floor();\n  };\n\n  AbstractMatrix.prototype.fround = function fround() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.fround(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.fround = function fround(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.fround();\n  };\n\n  AbstractMatrix.prototype.log = function log() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.log(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.log = function log(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.log();\n  };\n\n  AbstractMatrix.prototype.log1p = function log1p() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.log1p(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.log1p = function log1p(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.log1p();\n  };\n\n  AbstractMatrix.prototype.log10 = function log10() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.log10(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.log10 = function log10(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.log10();\n  };\n\n  AbstractMatrix.prototype.log2 = function log2() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.log2(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.log2 = function log2(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.log2();\n  };\n\n  AbstractMatrix.prototype.round = function round() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.round(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.round = function round(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.round();\n  };\n\n  AbstractMatrix.prototype.sign = function sign() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.sign(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.sign = function sign(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.sign();\n  };\n\n  AbstractMatrix.prototype.sin = function sin() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.sin(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.sin = function sin(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.sin();\n  };\n\n  AbstractMatrix.prototype.sinh = function sinh() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.sinh(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.sinh = function sinh(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.sinh();\n  };\n\n  AbstractMatrix.prototype.sqrt = function sqrt() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.sqrt(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.sqrt = function sqrt(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.sqrt();\n  };\n\n  AbstractMatrix.prototype.tan = function tan() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.tan(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.tan = function tan(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.tan();\n  };\n\n  AbstractMatrix.prototype.tanh = function tanh() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.tanh(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.tanh = function tanh(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.tanh();\n  };\n\n  AbstractMatrix.prototype.trunc = function trunc() {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.trunc(this.get(i, j)));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.trunc = function trunc(matrix) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.trunc();\n  };\n\n  AbstractMatrix.pow = function pow(matrix, arg0) {\n    const newMatrix = new Matrix(matrix);\n    return newMatrix.pow(arg0);\n  };\n\n  AbstractMatrix.prototype.pow = function pow(value) {\n    if (typeof value === 'number') return this.powS(value);\n    return this.powM(value);\n  };\n\n  AbstractMatrix.prototype.powS = function powS(value) {\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.pow(this.get(i, j), value));\n      }\n    }\n    return this;\n  };\n\n  AbstractMatrix.prototype.powM = function powM(matrix) {\n    matrix = Matrix.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n      this.columns !== matrix.columns) {\n      throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (let i = 0; i < this.rows; i++) {\n      for (let j = 0; j < this.columns; j++) {\n        this.set(i, j, Math.pow(this.get(i, j), matrix.get(i, j)));\n      }\n    }\n    return this;\n  };\n}\n","import { AbstractMatrix } from '../matrix';\n\nexport default class BaseView extends AbstractMatrix {\n  constructor(matrix, rows, columns) {\n    super();\n    this.matrix = matrix;\n    this.rows = rows;\n    this.columns = columns;\n  }\n}\n","import BaseView from './base';\n\nexport default class MatrixTransposeView extends BaseView {\n  constructor(matrix) {\n    super(matrix, matrix.columns, matrix.rows);\n  }\n\n  set(rowIndex, columnIndex, value) {\n    this.matrix.set(columnIndex, rowIndex, value);\n    return this;\n  }\n\n  get(rowIndex, columnIndex) {\n    return this.matrix.get(columnIndex, rowIndex);\n  }\n}\n","import { AbstractMatrix } from '../matrix';\n\nexport default class WrapperMatrix2D extends AbstractMatrix {\n  constructor(data) {\n    super();\n    this.data = data;\n    this.rows = data.length;\n    this.columns = data[0].length;\n  }\n\n  set(rowIndex, columnIndex, value) {\n    this.data[rowIndex][columnIndex] = value;\n    return this;\n  }\n\n  get(rowIndex, columnIndex) {\n    return this.data[rowIndex][columnIndex];\n  }\n}\n","import Matrix from '../matrix';\nimport WrapperMatrix2D from '../wrap/WrapperMatrix2D';\n\nexport default class LuDecomposition {\n  constructor(matrix) {\n    matrix = WrapperMatrix2D.checkMatrix(matrix);\n\n    let lu = matrix.clone();\n    let rows = lu.rows;\n    let columns = lu.columns;\n    let pivotVector = new Float64Array(rows);\n    let pivotSign = 1;\n    let i, j, k, p, s, t, v;\n    let LUcolj, kmax;\n\n    for (i = 0; i < rows; i++) {\n      pivotVector[i] = i;\n    }\n\n    LUcolj = new Float64Array(rows);\n\n    for (j = 0; j < columns; j++) {\n      for (i = 0; i < rows; i++) {\n        LUcolj[i] = lu.get(i, j);\n      }\n\n      for (i = 0; i < rows; i++) {\n        kmax = Math.min(i, j);\n        s = 0;\n        for (k = 0; k < kmax; k++) {\n          s += lu.get(i, k) * LUcolj[k];\n        }\n        LUcolj[i] -= s;\n        lu.set(i, j, LUcolj[i]);\n      }\n\n      p = j;\n      for (i = j + 1; i < rows; i++) {\n        if (Math.abs(LUcolj[i]) > Math.abs(LUcolj[p])) {\n          p = i;\n        }\n      }\n\n      if (p !== j) {\n        for (k = 0; k < columns; k++) {\n          t = lu.get(p, k);\n          lu.set(p, k, lu.get(j, k));\n          lu.set(j, k, t);\n        }\n\n        v = pivotVector[p];\n        pivotVector[p] = pivotVector[j];\n        pivotVector[j] = v;\n\n        pivotSign = -pivotSign;\n      }\n\n      if (j < rows && lu.get(j, j) !== 0) {\n        for (i = j + 1; i < rows; i++) {\n          lu.set(i, j, lu.get(i, j) / lu.get(j, j));\n        }\n      }\n    }\n\n    this.LU = lu;\n    this.pivotVector = pivotVector;\n    this.pivotSign = pivotSign;\n  }\n\n  isSingular() {\n    let data = this.LU;\n    let col = data.columns;\n    for (let j = 0; j < col; j++) {\n      if (data.get(j, j) === 0) {\n        return true;\n      }\n    }\n    return false;\n  }\n\n  solve(value) {\n    value = Matrix.checkMatrix(value);\n\n    let lu = this.LU;\n    let rows = lu.rows;\n\n    if (rows !== value.rows) {\n      throw new Error('Invalid matrix dimensions');\n    }\n    if (this.isSingular()) {\n      throw new Error('LU matrix is singular');\n    }\n\n    let count = value.columns;\n    let X = value.subMatrixRow(this.pivotVector, 0, count - 1);\n    let columns = lu.columns;\n    let i, j, k;\n\n    for (k = 0; k < columns; k++) {\n      for (i = k + 1; i < columns; i++) {\n        for (j = 0; j < count; j++) {\n          X.set(i, j, X.get(i, j) - X.get(k, j) * lu.get(i, k));\n        }\n      }\n    }\n    for (k = columns - 1; k >= 0; k--) {\n      for (j = 0; j < count; j++) {\n        X.set(k, j, X.get(k, j) / lu.get(k, k));\n      }\n      for (i = 0; i < k; i++) {\n        for (j = 0; j < count; j++) {\n          X.set(i, j, X.get(i, j) - X.get(k, j) * lu.get(i, k));\n        }\n      }\n    }\n    return X;\n  }\n\n  get determinant() {\n    let data = this.LU;\n    if (!data.isSquare()) {\n      throw new Error('Matrix must be square');\n    }\n    let determinant = this.pivotSign;\n    let col = data.columns;\n    for (let j = 0; j < col; j++) {\n      determinant *= data.get(j, j);\n    }\n    return determinant;\n  }\n\n  get lowerTriangularMatrix() {\n    let data = this.LU;\n    let rows = data.rows;\n    let columns = data.columns;\n    let X = new Matrix(rows, columns);\n    for (let i = 0; i < rows; i++) {\n      for (let j = 0; j < columns; j++) {\n        if (i > j) {\n          X.set(i, j, data.get(i, j));\n        } else if (i === j) {\n          X.set(i, j, 1);\n        } else {\n          X.set(i, j, 0);\n        }\n      }\n    }\n    return X;\n  }\n\n  get upperTriangularMatrix() {\n    let data = this.LU;\n    let rows = data.rows;\n    let columns = data.columns;\n    let X = new Matrix(rows, columns);\n    for (let i = 0; i < rows; i++) {\n      for (let j = 0; j < columns; j++) {\n        if (i <= j) {\n          X.set(i, j, data.get(i, j));\n        } else {\n          X.set(i, j, 0);\n        }\n      }\n    }\n    return X;\n  }\n\n  get pivotPermutationVector() {\n    return Array.from(this.pivotVector);\n  }\n}\n","export function hypotenuse(a, b) {\n  let r = 0;\n  if (Math.abs(a) > Math.abs(b)) {\n    r = b / a;\n    return Math.abs(a) * Math.sqrt(1 + r * r);\n  }\n  if (b !== 0) {\n    r = a / b;\n    return Math.abs(b) * Math.sqrt(1 + r * r);\n  }\n  return 0;\n}\n","import Matrix from '../matrix';\nimport WrapperMatrix2D from '../wrap/WrapperMatrix2D';\n\nimport { hypotenuse } from './util';\n\nexport default class QrDecomposition {\n  constructor(value) {\n    value = WrapperMatrix2D.checkMatrix(value);\n\n    let qr = value.clone();\n    let m = value.rows;\n    let n = value.columns;\n    let rdiag = new Float64Array(n);\n    let i, j, k, s;\n\n    for (k = 0; k < n; k++) {\n      let nrm = 0;\n      for (i = k; i < m; i++) {\n        nrm = hypotenuse(nrm, qr.get(i, k));\n      }\n      if (nrm !== 0) {\n        if (qr.get(k, k) < 0) {\n          nrm = -nrm;\n        }\n        for (i = k; i < m; i++) {\n          qr.set(i, k, qr.get(i, k) / nrm);\n        }\n        qr.set(k, k, qr.get(k, k) + 1);\n        for (j = k + 1; j < n; j++) {\n          s = 0;\n          for (i = k; i < m; i++) {\n            s += qr.get(i, k) * qr.get(i, j);\n          }\n          s = -s / qr.get(k, k);\n          for (i = k; i < m; i++) {\n            qr.set(i, j, qr.get(i, j) + s * qr.get(i, k));\n          }\n        }\n      }\n      rdiag[k] = -nrm;\n    }\n\n    this.QR = qr;\n    this.Rdiag = rdiag;\n  }\n\n  solve(value) {\n    value = Matrix.checkMatrix(value);\n\n    let qr = this.QR;\n    let m = qr.rows;\n\n    if (value.rows !== m) {\n      throw new Error('Matrix row dimensions must agree');\n    }\n    if (!this.isFullRank()) {\n      throw new Error('Matrix is rank deficient');\n    }\n\n    let count = value.columns;\n    let X = value.clone();\n    let n = qr.columns;\n    let i, j, k, s;\n\n    for (k = 0; k < n; k++) {\n      for (j = 0; j < count; j++) {\n        s = 0;\n        for (i = k; i < m; i++) {\n          s += qr.get(i, k) * X.get(i, j);\n        }\n        s = -s / qr.get(k, k);\n        for (i = k; i < m; i++) {\n          X.set(i, j, X.get(i, j) + s * qr.get(i, k));\n        }\n      }\n    }\n    for (k = n - 1; k >= 0; k--) {\n      for (j = 0; j < count; j++) {\n        X.set(k, j, X.get(k, j) / this.Rdiag[k]);\n      }\n      for (i = 0; i < k; i++) {\n        for (j = 0; j < count; j++) {\n          X.set(i, j, X.get(i, j) - X.get(k, j) * qr.get(i, k));\n        }\n      }\n    }\n\n    return X.subMatrix(0, n - 1, 0, count - 1);\n  }\n\n  isFullRank() {\n    let columns = this.QR.columns;\n    for (let i = 0; i < columns; i++) {\n      if (this.Rdiag[i] === 0) {\n        return false;\n      }\n    }\n    return true;\n  }\n\n  get upperTriangularMatrix() {\n    let qr = this.QR;\n    let n = qr.columns;\n    let X = new Matrix(n, n);\n    let i, j;\n    for (i = 0; i < n; i++) {\n      for (j = 0; j < n; j++) {\n        if (i < j) {\n          X.set(i, j, qr.get(i, j));\n        } else if (i === j) {\n          X.set(i, j, this.Rdiag[i]);\n        } else {\n          X.set(i, j, 0);\n        }\n      }\n    }\n    return X;\n  }\n\n  get orthogonalMatrix() {\n    let qr = this.QR;\n    let rows = qr.rows;\n    let columns = qr.columns;\n    let X = new Matrix(rows, columns);\n    let i, j, k, s;\n\n    for (k = columns - 1; k >= 0; k--) {\n      for (i = 0; i < rows; i++) {\n        X.set(i, k, 0);\n      }\n      X.set(k, k, 1);\n      for (j = k; j < columns; j++) {\n        if (qr.get(k, k) !== 0) {\n          s = 0;\n          for (i = k; i < rows; i++) {\n            s += qr.get(i, k) * X.get(i, j);\n          }\n\n          s = -s / qr.get(k, k);\n\n          for (i = k; i < rows; i++) {\n            X.set(i, j, X.get(i, j) + s * qr.get(i, k));\n          }\n        }\n      }\n    }\n    return X;\n  }\n}\n","import Matrix from '../matrix';\nimport WrapperMatrix2D from '../wrap/WrapperMatrix2D';\n\nimport { hypotenuse } from './util';\n\nexport default class SingularValueDecomposition {\n  constructor(value, options = {}) {\n    value = WrapperMatrix2D.checkMatrix(value);\n\n    if (value.isEmpty()) {\n      throw new Error('Matrix must be non-empty');\n    }\n\n    let m = value.rows;\n    let n = value.columns;\n\n    const {\n      computeLeftSingularVectors = true,\n      computeRightSingularVectors = true,\n      autoTranspose = false,\n    } = options;\n\n    let wantu = Boolean(computeLeftSingularVectors);\n    let wantv = Boolean(computeRightSingularVectors);\n\n    let swapped = false;\n    let a;\n    if (m < n) {\n      if (!autoTranspose) {\n        a = value.clone();\n        // eslint-disable-next-line no-console\n        console.warn(\n          'Computing SVD on a matrix with more columns than rows. Consider enabling autoTranspose',\n        );\n      } else {\n        a = value.transpose();\n        m = a.rows;\n        n = a.columns;\n        swapped = true;\n        let aux = wantu;\n        wantu = wantv;\n        wantv = aux;\n      }\n    } else {\n      a = value.clone();\n    }\n\n    let nu = Math.min(m, n);\n    let ni = Math.min(m + 1, n);\n    let s = new Float64Array(ni);\n    let U = new Matrix(m, nu);\n    let V = new Matrix(n, n);\n\n    let e = new Float64Array(n);\n    let work = new Float64Array(m);\n\n    let si = new Float64Array(ni);\n    for (let i = 0; i < ni; i++) si[i] = i;\n\n    let nct = Math.min(m - 1, n);\n    let nrt = Math.max(0, Math.min(n - 2, m));\n    let mrc = Math.max(nct, nrt);\n\n    for (let k = 0; k < mrc; k++) {\n      if (k < nct) {\n        s[k] = 0;\n        for (let i = k; i < m; i++) {\n          s[k] = hypotenuse(s[k], a.get(i, k));\n        }\n        if (s[k] !== 0) {\n          if (a.get(k, k) < 0) {\n            s[k] = -s[k];\n          }\n          for (let i = k; i < m; i++) {\n            a.set(i, k, a.get(i, k) / s[k]);\n          }\n          a.set(k, k, a.get(k, k) + 1);\n        }\n        s[k] = -s[k];\n      }\n\n      for (let j = k + 1; j < n; j++) {\n        if (k < nct && s[k] !== 0) {\n          let t = 0;\n          for (let i = k; i < m; i++) {\n            t += a.get(i, k) * a.get(i, j);\n          }\n          t = -t / a.get(k, k);\n          for (let i = k; i < m; i++) {\n            a.set(i, j, a.get(i, j) + t * a.get(i, k));\n          }\n        }\n        e[j] = a.get(k, j);\n      }\n\n      if (wantu && k < nct) {\n        for (let i = k; i < m; i++) {\n          U.set(i, k, a.get(i, k));\n        }\n      }\n\n      if (k < nrt) {\n        e[k] = 0;\n        for (let i = k + 1; i < n; i++) {\n          e[k] = hypotenuse(e[k], e[i]);\n        }\n        if (e[k] !== 0) {\n          if (e[k + 1] < 0) {\n            e[k] = 0 - e[k];\n          }\n          for (let i = k + 1; i < n; i++) {\n            e[i] /= e[k];\n          }\n          e[k + 1] += 1;\n        }\n        e[k] = -e[k];\n        if (k + 1 < m && e[k] !== 0) {\n          for (let i = k + 1; i < m; i++) {\n            work[i] = 0;\n          }\n          for (let i = k + 1; i < m; i++) {\n            for (let j = k + 1; j < n; j++) {\n              work[i] += e[j] * a.get(i, j);\n            }\n          }\n          for (let j = k + 1; j < n; j++) {\n            let t = -e[j] / e[k + 1];\n            for (let i = k + 1; i < m; i++) {\n              a.set(i, j, a.get(i, j) + t * work[i]);\n            }\n          }\n        }\n        if (wantv) {\n          for (let i = k + 1; i < n; i++) {\n            V.set(i, k, e[i]);\n          }\n        }\n      }\n    }\n\n    let p = Math.min(n, m + 1);\n    if (nct < n) {\n      s[nct] = a.get(nct, nct);\n    }\n    if (m < p) {\n      s[p - 1] = 0;\n    }\n    if (nrt + 1 < p) {\n      e[nrt] = a.get(nrt, p - 1);\n    }\n    e[p - 1] = 0;\n\n    if (wantu) {\n      for (let j = nct; j < nu; j++) {\n        for (let i = 0; i < m; i++) {\n          U.set(i, j, 0);\n        }\n        U.set(j, j, 1);\n      }\n      for (let k = nct - 1; k >= 0; k--) {\n        if (s[k] !== 0) {\n          for (let j = k + 1; j < nu; j++) {\n            let t = 0;\n            for (let i = k; i < m; i++) {\n              t += U.get(i, k) * U.get(i, j);\n            }\n            t = -t / U.get(k, k);\n            for (let i = k; i < m; i++) {\n              U.set(i, j, U.get(i, j) + t * U.get(i, k));\n            }\n          }\n          for (let i = k; i < m; i++) {\n            U.set(i, k, -U.get(i, k));\n          }\n          U.set(k, k, 1 + U.get(k, k));\n          for (let i = 0; i < k - 1; i++) {\n            U.set(i, k, 0);\n          }\n        } else {\n          for (let i = 0; i < m; i++) {\n            U.set(i, k, 0);\n          }\n          U.set(k, k, 1);\n        }\n      }\n    }\n\n    if (wantv) {\n      for (let k = n - 1; k >= 0; k--) {\n        if (k < nrt && e[k] !== 0) {\n          for (let j = k + 1; j < n; j++) {\n            let t = 0;\n            for (let i = k + 1; i < n; i++) {\n              t += V.get(i, k) * V.get(i, j);\n            }\n            t = -t / V.get(k + 1, k);\n            for (let i = k + 1; i < n; i++) {\n              V.set(i, j, V.get(i, j) + t * V.get(i, k));\n            }\n          }\n        }\n        for (let i = 0; i < n; i++) {\n          V.set(i, k, 0);\n        }\n        V.set(k, k, 1);\n      }\n    }\n\n    let pp = p - 1;\n    let iter = 0;\n    let eps = Number.EPSILON;\n    while (p > 0) {\n      let k, kase;\n      for (k = p - 2; k >= -1; k--) {\n        if (k === -1) {\n          break;\n        }\n        const alpha =\n          Number.MIN_VALUE + eps * Math.abs(s[k] + Math.abs(s[k + 1]));\n        if (Math.abs(e[k]) <= alpha || Number.isNaN(e[k])) {\n          e[k] = 0;\n          break;\n        }\n      }\n      if (k === p - 2) {\n        kase = 4;\n      } else {\n        let ks;\n        for (ks = p - 1; ks >= k; ks--) {\n          if (ks === k) {\n            break;\n          }\n          let t =\n            (ks !== p ? Math.abs(e[ks]) : 0) +\n            (ks !== k + 1 ? Math.abs(e[ks - 1]) : 0);\n          if (Math.abs(s[ks]) <= eps * t) {\n            s[ks] = 0;\n            break;\n          }\n        }\n        if (ks === k) {\n          kase = 3;\n        } else if (ks === p - 1) {\n          kase = 1;\n        } else {\n          kase = 2;\n          k = ks;\n        }\n      }\n\n      k++;\n\n      switch (kase) {\n        case 1: {\n          let f = e[p - 2];\n          e[p - 2] = 0;\n          for (let j = p - 2; j >= k; j--) {\n            let t = hypotenuse(s[j], f);\n            let cs = s[j] / t;\n            let sn = f / t;\n            s[j] = t;\n            if (j !== k) {\n              f = -sn * e[j - 1];\n              e[j - 1] = cs * e[j - 1];\n            }\n            if (wantv) {\n              for (let i = 0; i < n; i++) {\n                t = cs * V.get(i, j) + sn * V.get(i, p - 1);\n                V.set(i, p - 1, -sn * V.get(i, j) + cs * V.get(i, p - 1));\n                V.set(i, j, t);\n              }\n            }\n          }\n          break;\n        }\n        case 2: {\n          let f = e[k - 1];\n          e[k - 1] = 0;\n          for (let j = k; j < p; j++) {\n            let t = hypotenuse(s[j], f);\n            let cs = s[j] / t;\n            let sn = f / t;\n            s[j] = t;\n            f = -sn * e[j];\n            e[j] = cs * e[j];\n            if (wantu) {\n              for (let i = 0; i < m; i++) {\n                t = cs * U.get(i, j) + sn * U.get(i, k - 1);\n                U.set(i, k - 1, -sn * U.get(i, j) + cs * U.get(i, k - 1));\n                U.set(i, j, t);\n              }\n            }\n          }\n          break;\n        }\n        case 3: {\n          const scale = Math.max(\n            Math.abs(s[p - 1]),\n            Math.abs(s[p - 2]),\n            Math.abs(e[p - 2]),\n            Math.abs(s[k]),\n            Math.abs(e[k]),\n          );\n          const sp = s[p - 1] / scale;\n          const spm1 = s[p - 2] / scale;\n          const epm1 = e[p - 2] / scale;\n          const sk = s[k] / scale;\n          const ek = e[k] / scale;\n          const b = ((spm1 + sp) * (spm1 - sp) + epm1 * epm1) / 2;\n          const c = sp * epm1 * (sp * epm1);\n          let shift = 0;\n          if (b !== 0 || c !== 0) {\n            if (b < 0) {\n              shift = 0 - Math.sqrt(b * b + c);\n            } else {\n              shift = Math.sqrt(b * b + c);\n            }\n            shift = c / (b + shift);\n          }\n          let f = (sk + sp) * (sk - sp) + shift;\n          let g = sk * ek;\n          for (let j = k; j < p - 1; j++) {\n            let t = hypotenuse(f, g);\n            if (t === 0) t = Number.MIN_VALUE;\n            let cs = f / t;\n            let sn = g / t;\n            if (j !== k) {\n              e[j - 1] = t;\n            }\n            f = cs * s[j] + sn * e[j];\n            e[j] = cs * e[j] - sn * s[j];\n            g = sn * s[j + 1];\n            s[j + 1] = cs * s[j + 1];\n            if (wantv) {\n              for (let i = 0; i < n; i++) {\n                t = cs * V.get(i, j) + sn * V.get(i, j + 1);\n                V.set(i, j + 1, -sn * V.get(i, j) + cs * V.get(i, j + 1));\n                V.set(i, j, t);\n              }\n            }\n            t = hypotenuse(f, g);\n            if (t === 0) t = Number.MIN_VALUE;\n            cs = f / t;\n            sn = g / t;\n            s[j] = t;\n            f = cs * e[j] + sn * s[j + 1];\n            s[j + 1] = -sn * e[j] + cs * s[j + 1];\n            g = sn * e[j + 1];\n            e[j + 1] = cs * e[j + 1];\n            if (wantu && j < m - 1) {\n              for (let i = 0; i < m; i++) {\n                t = cs * U.get(i, j) + sn * U.get(i, j + 1);\n                U.set(i, j + 1, -sn * U.get(i, j) + cs * U.get(i, j + 1));\n                U.set(i, j, t);\n              }\n            }\n          }\n          e[p - 2] = f;\n          iter = iter + 1;\n          break;\n        }\n        case 4: {\n          if (s[k] <= 0) {\n            s[k] = s[k] < 0 ? -s[k] : 0;\n            if (wantv) {\n              for (let i = 0; i <= pp; i++) {\n                V.set(i, k, -V.get(i, k));\n              }\n            }\n          }\n          while (k < pp) {\n            if (s[k] >= s[k + 1]) {\n              break;\n            }\n            let t = s[k];\n            s[k] = s[k + 1];\n            s[k + 1] = t;\n            if (wantv && k < n - 1) {\n              for (let i = 0; i < n; i++) {\n                t = V.get(i, k + 1);\n                V.set(i, k + 1, V.get(i, k));\n                V.set(i, k, t);\n              }\n            }\n            if (wantu && k < m - 1) {\n              for (let i = 0; i < m; i++) {\n                t = U.get(i, k + 1);\n                U.set(i, k + 1, U.get(i, k));\n                U.set(i, k, t);\n              }\n            }\n            k++;\n          }\n          iter = 0;\n          p--;\n          break;\n        }\n        // no default\n      }\n    }\n\n    if (swapped) {\n      let tmp = V;\n      V = U;\n      U = tmp;\n    }\n\n    this.m = m;\n    this.n = n;\n    this.s = s;\n    this.U = U;\n    this.V = V;\n  }\n\n  solve(value) {\n    let Y = value;\n    let e = this.threshold;\n    let scols = this.s.length;\n    let Ls = Matrix.zeros(scols, scols);\n\n    for (let i = 0; i < scols; i++) {\n      if (Math.abs(this.s[i]) <= e) {\n        Ls.set(i, i, 0);\n      } else {\n        Ls.set(i, i, 1 / this.s[i]);\n      }\n    }\n\n    let U = this.U;\n    let V = this.rightSingularVectors;\n\n    let VL = V.mmul(Ls);\n    let vrows = V.rows;\n    let urows = U.rows;\n    let VLU = Matrix.zeros(vrows, urows);\n\n    for (let i = 0; i < vrows; i++) {\n      for (let j = 0; j < urows; j++) {\n        let sum = 0;\n        for (let k = 0; k < scols; k++) {\n          sum += VL.get(i, k) * U.get(j, k);\n        }\n        VLU.set(i, j, sum);\n      }\n    }\n\n    return VLU.mmul(Y);\n  }\n\n  solveForDiagonal(value) {\n    return this.solve(Matrix.diag(value));\n  }\n\n  inverse() {\n    let V = this.V;\n    let e = this.threshold;\n    let vrows = V.rows;\n    let vcols = V.columns;\n    let X = new Matrix(vrows, this.s.length);\n\n    for (let i = 0; i < vrows; i++) {\n      for (let j = 0; j < vcols; j++) {\n        if (Math.abs(this.s[j]) > e) {\n          X.set(i, j, V.get(i, j) / this.s[j]);\n        }\n      }\n    }\n\n    let U = this.U;\n\n    let urows = U.rows;\n    let ucols = U.columns;\n    let Y = new Matrix(vrows, urows);\n\n    for (let i = 0; i < vrows; i++) {\n      for (let j = 0; j < urows; j++) {\n        let sum = 0;\n        for (let k = 0; k < ucols; k++) {\n          sum += X.get(i, k) * U.get(j, k);\n        }\n        Y.set(i, j, sum);\n      }\n    }\n\n    return Y;\n  }\n\n  get condition() {\n    return this.s[0] / this.s[Math.min(this.m, this.n) - 1];\n  }\n\n  get norm2() {\n    return this.s[0];\n  }\n\n  get rank() {\n    let tol = Math.max(this.m, this.n) * this.s[0] * Number.EPSILON;\n    let r = 0;\n    let s = this.s;\n    for (let i = 0, ii = s.length; i < ii; i++) {\n      if (s[i] > tol) {\n        r++;\n      }\n    }\n    return r;\n  }\n\n  get diagonal() {\n    return Array.from(this.s);\n  }\n\n  get threshold() {\n    return (Number.EPSILON / 2) * Math.max(this.m, this.n) * this.s[0];\n  }\n\n  get leftSingularVectors() {\n    return this.U;\n  }\n\n  get rightSingularVectors() {\n    return this.V;\n  }\n\n  get diagonalMatrix() {\n    return Matrix.diag(this.s);\n  }\n}\n","import LuDecomposition from './dc/lu';\nimport QrDecomposition from './dc/qr';\nimport SingularValueDecomposition from './dc/svd';\nimport Matrix from './matrix';\nimport WrapperMatrix2D from './wrap/WrapperMatrix2D';\n\nexport function inverse(matrix, useSVD = false) {\n  matrix = WrapperMatrix2D.checkMatrix(matrix);\n  if (useSVD) {\n    return new SingularValueDecomposition(matrix).inverse();\n  } else {\n    return solve(matrix, Matrix.eye(matrix.rows));\n  }\n}\n\nexport function solve(leftHandSide, rightHandSide, useSVD = false) {\n  leftHandSide = WrapperMatrix2D.checkMatrix(leftHandSide);\n  rightHandSide = WrapperMatrix2D.checkMatrix(rightHandSide);\n  if (useSVD) {\n    return new SingularValueDecomposition(leftHandSide).solve(rightHandSide);\n  } else {\n    return leftHandSide.isSquare()\n      ? new LuDecomposition(leftHandSide).solve(rightHandSide)\n      : new QrDecomposition(leftHandSide).solve(rightHandSide);\n  }\n}\n","export function addStyle(serie, spectrum, options = {}) {\n    let { color = '#A9A9A9', opacity = 1, lineWidth = 1 } = options;\n    // eslint-disable-next-line @typescript-eslint/prefer-regexp-exec\n    if (color.match(/#[0-9A-F]{6}$/i)) {\n        color = (color + ((opacity * 255) >> 0).toString(16)).toUpperCase();\n    }\n    else {\n        color = color.replace(/rgb ?\\((.*)\\)/, `rgba($1,${opacity})`);\n    }\n    serie.style = [\n        {\n            name: 'unselected',\n            style: {\n                line: {\n                    color,\n                    width: lineWidth,\n                    dash: 1,\n                },\n            },\n        },\n        {\n            name: 'selected',\n            style: {\n                line: {\n                    color,\n                    width: lineWidth + 2,\n                    dash: 1,\n                },\n            },\n        },\n    ];\n    serie.name = spectrum.label || spectrum.id;\n}\n//# sourceMappingURL=data:application/json;base64,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","export const COLORS = [\n    '#FFB300',\n    '#803E75',\n    '#FF6800',\n    '#A6BDD7',\n    '#C10020',\n    '#CEA262',\n    '#817066',\n    '#007D34',\n    '#F6768E',\n    '#00538A',\n    '#FF7A5C',\n    '#53377A',\n    '#FF8E00',\n    '#B32851',\n    '#F4C800',\n    '#7F180D',\n    '#93AA00',\n    '#593315',\n    '#F13A13',\n    '#232C16',\n];\n//# sourceMappingURL=data:application/json;base64,eyJ2ZXJzaW9uIjozLCJmaWxlIjoiY29sb3JzLmpzIiwic291cmNlUm9vdCI6IiIsInNvdXJjZXMiOlsiLi4vLi4vc3JjL2pzZ3JhcGgvY29sb3JzLnRzIl0sIm5hbWVzIjpbXSwibWFwcGluZ3MiOiJBQUFBLE1BQU0sQ0FBQyxNQUFNLE1BQU0sR0FBRztJQUNwQixTQUFTO0lBQ1QsU0FBUztJQUNULFNBQVM7SUFDVCxTQUFTO0lBQ1QsU0FBUztJQUNULFNBQVM7SUFDVCxTQUFTO0lBQ1QsU0FBUztJQUNULFNBQVM7SUFDVCxTQUFTO0lBQ1QsU0FBUztJQUNULFNBQVM7SUFDVCxTQUFTO0lBQ1QsU0FBUztJQUNULFNBQVM7SUFDVCxTQUFTO0lBQ1QsU0FBUztJQUNULFNBQVM7SUFDVCxTQUFTO0lBQ1QsU0FBUztDQUNWLENBQUMifQ==","export function appendDistinctParameter(values, key, value) {\n    if (!values[key]) {\n        values[key] = {\n            key,\n            values: [],\n            count: 0,\n        };\n    }\n    if (!values[key].values.includes(value)) {\n        values[key].values.push(value);\n    }\n    values[key].count++;\n}\n//# sourceMappingURL=data:application/json;base64,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","export function appendDistinctValue(values, key) {\n    if (!values[key]) {\n        values[key] = {\n            key,\n            count: 0,\n        };\n    }\n    values[key].count++;\n}\n//# sourceMappingURL=data:application/json;base64,eyJ2ZXJzaW9uIjozLCJmaWxlIjoiYXBwZW5kRGlzdGluY3RWYWx1ZS5qcyIsInNvdXJjZVJvb3QiOiIiLCJzb3VyY2VzIjpbIi4uLy4uL3NyYy91dGlsL2FwcGVuZERpc3RpbmN0VmFsdWUudHMiXSwibmFtZXMiOltdLCJtYXBwaW5ncyI6IkFBRUEsTUFBTSxVQUFVLG1CQUFtQixDQUNqQyxNQUFtQyxFQUNuQyxHQUFXO0lBRVgsSUFBSSxDQUFDLE1BQU0sQ0FBQyxHQUFHLENBQUMsRUFBRTtRQUNoQixNQUFNLENBQUMsR0FBRyxDQUFDLEdBQUc7WUFDWixHQUFHO1lBQ0gsS0FBSyxFQUFFLENBQUM7U0FDVCxDQUFDO0tBQ0g7SUFDRCxNQUFNLENBQUMsR0FBRyxDQUFDLENBQUMsS0FBSyxFQUFFLENBQUM7QUFDdEIsQ0FBQyJ9","import { appendDistinctParameter } from './util/appendDistinctParameter';\nimport { appendDistinctValue } from './util/appendDistinctValue';\nexport class AnalysesManager {\n    constructor() {\n        this.analyses = [];\n    }\n    addAnalysis(analysis) {\n        let index = this.getAnalysisIndex(analysis.id);\n        if (index === undefined) {\n            this.analyses.push(analysis);\n        }\n        else {\n            this.analyses[index] = analysis;\n        }\n    }\n    getAnalyses(options = {}) {\n        const { ids } = options;\n        let analyses = [];\n        for (const analysis of this.analyses) {\n            if (!ids || ids.includes(analysis.id)) {\n                analyses.push(analysis);\n            }\n        }\n        return analyses;\n    }\n    getSpectra() {\n        const spectra = [];\n        for (const analysis of this.analyses) {\n            spectra.push(...analysis.spectra);\n        }\n        return spectra;\n    }\n    getAnalysisBySpectrumId(id) {\n        for (const analysis of this.analyses) {\n            for (const spectrum of analysis.spectra) {\n                if (spectrum.id === id)\n                    return analysis;\n            }\n        }\n        return undefined;\n    }\n    getSpectrumById(id) {\n        for (const analysis of this.analyses) {\n            for (const spectrum of analysis.spectra) {\n                if (spectrum.id === id)\n                    return spectrum;\n            }\n        }\n        return undefined;\n    }\n    /**\n     * Get an array of objects (key + count) of all the titles\n     */\n    getDistinctTitles() {\n        let values = {};\n        for (let spectrum of this.getSpectra()) {\n            if (spectrum.title) {\n                appendDistinctValue(values, spectrum.title);\n            }\n        }\n        return Object.keys(values).map((key) => values[key]);\n    }\n    /**\n     * Get an array of objects (key + count) of all the units\n     */\n    getDistinctUnits() {\n        let values = {};\n        for (let spectrum of this.getSpectra()) {\n            if (spectrum.variables) {\n                for (let [, variable] of Object.entries(spectrum.variables)) {\n                    if (variable.units) {\n                        appendDistinctValue(values, variable.units);\n                    }\n                }\n            }\n        }\n        return Object.keys(values).map((key) => values[key]);\n    }\n    /**\n     * Get an array of objects (key + unit + label + count) of all the units\n     */\n    getDistinctLabelUnits() {\n        let values = {};\n        for (let spectrum of this.getSpectra()) {\n            if (spectrum.variables) {\n                for (let [, variable] of Object.entries(spectrum.variables)) {\n                    const { label, units } = normalizeLabelUnits(variable.label, variable.units);\n                    const key = label + (units ? ` (${units})` : '');\n                    if (key) {\n                        if (!values[key]) {\n                            values[key] = { key, units, label, count: 0 };\n                        }\n                        values[key].count++;\n                    }\n                }\n            }\n        }\n        return Object.keys(values).map((key) => values[key]);\n    }\n    /**\n     * Get an array of objects (key + count) of all the labels\n     */\n    getDistinctLabels() {\n        let values = {};\n        for (let spectrum of this.getSpectra()) {\n            if (spectrum.variables) {\n                for (let [, variable] of Object.entries(spectrum.variables)) {\n                    appendDistinctValue(values, variable.label.replace(/\\s+[[(].*$/, ''));\n                }\n            }\n        }\n        return Object.keys(values).map((key) => values[key]);\n    }\n    /**\n     * Get an array of objects (key + count) of all the dataTypes\n     */\n    getDistinctDataTypes() {\n        let values = {};\n        for (let spectrum of this.getSpectra()) {\n            if (spectrum.dataType) {\n                appendDistinctValue(values, spectrum.dataType);\n            }\n        }\n        return Object.keys(values).map((key) => values[key]);\n    }\n    /**\n     * Get an array of objects (key + count) of all the meta\n     */\n    getDistinctMeta() {\n        let values = {};\n        for (let spectrum of this.getSpectra()) {\n            if (spectrum.meta) {\n                for (let key in spectrum.meta) {\n                    appendDistinctParameter(values, key, spectrum.meta[key]);\n                }\n            }\n        }\n        return Object.keys(values).map((key) => values[key]);\n    }\n    removeAllAnalyses() {\n        this.analyses.splice(0);\n    }\n    /**\n     * Remove the analysis from the AnalysesManager for the specified id\n     */\n    removeAnalysis(id) {\n        let index = this.getAnalysisIndex(id);\n        if (index === undefined)\n            return undefined;\n        return this.analyses.splice(index, 1);\n    }\n    /**\n     * Returns the index of the analysis in the analyses array\n     */\n    getAnalysisIndex(id) {\n        if (!id)\n            return undefined;\n        for (let i = 0; i < this.analyses.length; i++) {\n            let analysis = this.analyses[i];\n            if (analysis.id === id)\n                return i;\n        }\n        return undefined;\n    }\n    /**\n     * Checks if the ID of an analysis exists in the AnalysesManager\n     */\n    includes(id) {\n        const index = this.getAnalysisIndex(id);\n        return index === undefined ? false : !isNaN(index);\n    }\n}\nfunction normalizeLabelUnits(originalLabel, originalUnits) {\n    if (!originalLabel) {\n        return { units: '', label: '' };\n    }\n    if (originalLabel.search(/[[(]]/) >= 0) {\n        const [units, label] = originalLabel.split(/\\s*[[(]/);\n        return { units: originalUnits || units, label };\n    }\n    return { label: originalLabel, units: originalUnits };\n}\n//# 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Based on https://github.com/scijs/cholesky-solve\r\n\r\n/*\r\nThe MIT License (MIT)\r\n\r\nCopyright (c) 2013 Eric Arnebäck\r\n\r\nPermission is hereby granted, free of charge, to any person obtaining a copy\r\nof this software and associated documentation files (the \"Software\"), to deal\r\nin the Software without restriction, including without limitation the rights\r\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\r\ncopies of the Software, and to permit persons to whom the Software is\r\nfurnished to do so, subject to the following conditions:\r\n\r\nThe above copyright notice and this permission notice shall be included in\r\nall copies or substantial portions of the Software.\r\n\r\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\r\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\r\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\r\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\r\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\r\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\r\nTHE SOFTWARE.\r\n*/\r\n\r\nfunction ldlSymbolic(\r\n  n /* A and L are n-by-n, where n >= 0 */,\r\n  Ap /* input of size n + 1, not modified */,\r\n  Ai /* input of size nz=Ap[n], not modified */,\r\n  Lp /* output of size n + 1, not defined on input */,\r\n  Parent /* output of size n, not defined on input */,\r\n  Lnz /* output of size n, not defined on input */,\r\n  Flag /* workspace of size n, not defn. on input or output */,\r\n) {\r\n  let i, k, p, kk, p2;\r\n\r\n  for (k = 0; k < n; k++) {\r\n    /* L(k,:) pattern: all nodes reachable in etree from nz in A(0:k-1,k) */\r\n    Parent[k] = -1; /* parent of k is not yet known */\r\n    Flag[k] = k; /* mark node k as visited */\r\n    Lnz[k] = 0; /* count of nonzeros in column k of L */\r\n    kk = k; /* kth original, or permuted, column */\r\n    p2 = Ap[kk + 1];\r\n    for (p = Ap[kk]; p < p2; p++) {\r\n      /* A (i,k) is nonzero (original or permuted A) */\r\n      i = Ai[p];\r\n\r\n      if (i < k) {\r\n        /* follow path from i to root of etree, stop at flagged node */\r\n        for (; Flag[i] !== k; i = Parent[i]) {\r\n          /* find parent of i if not yet determined */\r\n          if (Parent[i] === -1) Parent[i] = k;\r\n          Lnz[i]++; /* L (k,i) is nonzero */\r\n          Flag[i] = k; /* mark i as visited */\r\n        }\r\n      }\r\n    }\r\n  }\r\n  /* construct Lp index array from Lnz column counts */\r\n  Lp[0] = 0;\r\n  for (k = 0; k < n; k++) {\r\n    Lp[k + 1] = Lp[k] + Lnz[k];\r\n  }\r\n}\r\n\r\nfunction ldlNumeric(\r\n  n /* A and L are n-by-n, where n >= 0 */,\r\n  Ap /* input of size n+1, not modified */,\r\n  Ai /* input of size nz=Ap[n], not modified */,\r\n  Ax /* input of size nz=Ap[n], not modified */,\r\n  Lp /* input of size n+1, not modified */,\r\n  Parent /* input of size n, not modified */,\r\n  Lnz /* output of size n, not defn. on input */,\r\n  Li /* output of size lnz=Lp[n], not defined on input */,\r\n  Lx /* output of size lnz=Lp[n], not defined on input */,\r\n  D /* output of size n, not defined on input */,\r\n  Y /* workspace of size n, not defn. on input or output */,\r\n  Pattern /* workspace of size n, not defn. on input or output */,\r\n  Flag /* workspace of size n, not defn. on input or output */,\r\n) {\r\n  let yi, lKi;\r\n  let i, k, p, kk, p2, len, top;\r\n  for (k = 0; k < n; k++) {\r\n    /* compute nonzero Pattern of kth row of L, in topological order */\r\n    Y[k] = 0.0; /* Y(0:k) is now all zero */\r\n    top = n; /* stack for pattern is empty */\r\n    Flag[k] = k; /* mark node k as visited */\r\n    Lnz[k] = 0; /* count of nonzeros in column k of L */\r\n    kk = k; /* kth original, or permuted, column */\r\n    p2 = Ap[kk + 1];\r\n    for (p = Ap[kk]; p < p2; p++) {\r\n      i = Ai[p]; /* get A(i,k) */\r\n      if (i <= k) {\r\n        Y[i] += Ax[p]; /* scatter A(i,k) into Y (sum duplicates) */\r\n        for (len = 0; Flag[i] !== k; i = Parent[i]) {\r\n          Pattern[len++] = i; /* L(k,i) is nonzero */\r\n          Flag[i] = k; /* mark i as visited */\r\n        }\r\n        while (len > 0) Pattern[--top] = Pattern[--len];\r\n      }\r\n    }\r\n    /* compute numerical values kth row of L (a sparse triangular solve) */\r\n    D[k] = Y[k]; /* get D(k,k) and clear Y(k) */\r\n    Y[k] = 0.0;\r\n    for (; top < n; top++) {\r\n      i = Pattern[top]; /* Pattern[top:n-1] is pattern of L(:,k) */\r\n      yi = Y[i]; /* get and clear Y(i) */\r\n      Y[i] = 0.0;\r\n      p2 = Lp[i] + Lnz[i];\r\n      for (p = Lp[i]; p < p2; p++) {\r\n        Y[Li[p]] -= Lx[p] * yi;\r\n      }\r\n      lKi = yi / D[i]; /* the nonzero entry L(k,i) */\r\n      D[k] -= lKi * yi;\r\n      Li[p] = k; /* store L(k,i) in column form of L */\r\n      Lx[p] = lKi;\r\n      Lnz[i]++; /* increment count of nonzeros in col i */\r\n    }\r\n\r\n    if (D[k] === 0.0) return k; /* failure, D(k,k) is zero */\r\n  }\r\n\r\n  return n; /* success, diagonal of D is all nonzero */\r\n}\r\n\r\nfunction ldlLsolve(\r\n  n /* L is n-by-n, where n >= 0 */,\r\n  X /* size n. right-hand-side on input, soln. on output */,\r\n  Lp /* input of size n+1, not modified */,\r\n  Li /* input of size lnz=Lp[n], not modified */,\r\n  Lx /* input of size lnz=Lp[n], not modified */,\r\n) {\r\n  let j, p, p2;\r\n  for (j = 0; j < n; j++) {\r\n    p2 = Lp[j + 1];\r\n    for (p = Lp[j]; p < p2; p++) {\r\n      X[Li[p]] -= Lx[p] * X[j];\r\n    }\r\n  }\r\n}\r\nfunction ldlDsolve(\r\n  n /* D is n-by-n, where n >= 0 */,\r\n  X /* size n. right-hand-side on input, soln. on output */,\r\n  D /* input of size n, not modified */,\r\n) {\r\n  let j;\r\n  for (j = 0; j < n; j++) {\r\n    X[j] /= D[j];\r\n  }\r\n}\r\nfunction ldlLTsolve(\r\n  n /* L is n-by-n, where n >= 0 */,\r\n  X /* size n. right-hand-side on input, soln. on output */,\r\n  Lp /* input of size n+1, not modified */,\r\n  Li /* input of size lnz=Lp[n], not modified */,\r\n  Lx /* input of size lnz=Lp[n], not modified */,\r\n) {\r\n  let j, p, p2;\r\n  for (j = n - 1; j >= 0; j--) {\r\n    p2 = Lp[j + 1];\r\n    for (p = Lp[j]; p < p2; p++) {\r\n      X[j] -= Lx[p] * X[Li[p]];\r\n    }\r\n  }\r\n}\r\n\r\nfunction ldlPerm(\r\n  n /* size of X, B, and P */,\r\n  X /* output of size n. */,\r\n  B /* input of size n. */,\r\n  P /* input permutation array of size n. */,\r\n) {\r\n  let j;\r\n  for (j = 0; j < n; j++) {\r\n    X[j] = B[P[j]];\r\n  }\r\n}\r\n\r\nfunction ldlPermt(\r\n  n /* size of X, B, and P */,\r\n  X /* output of size n. */,\r\n  B /* input of size n. */,\r\n  P /* input permutation array of size n. */,\r\n) {\r\n  let j;\r\n  for (j = 0; j < n; j++) {\r\n    X[P[j]] = B[j];\r\n  }\r\n}\r\n\r\nfunction prepare(M, n, P) {\r\n  // if a permutation was specified, apply it.\r\n  if (P) {\r\n    let Pinv = new Array(n);\r\n\r\n    for (let k = 0; k < n; k++) {\r\n      Pinv[P[k]] = k;\r\n    }\r\n\r\n    let Mt = []; // scratch memory\r\n    // Apply permutation. We make M into P*M*P^T\r\n    for (let a = 0; a < M.length; ++a) {\r\n      let ar = Pinv[M[a][0]];\r\n      let ac = Pinv[M[a][1]];\r\n\r\n      // we only store the upper-diagonal elements(since we assume matrix is symmetric, we only need to store these)\r\n      // if permuted element is below diagonal, we simply transpose it.\r\n      if (ac < ar) {\r\n        let t = ac;\r\n        ac = ar;\r\n        ar = t;\r\n      }\r\n\r\n      Mt[a] = [];\r\n      Mt[a][0] = ar;\r\n      Mt[a][1] = ac;\r\n      Mt[a][2] = M[a][2];\r\n    }\r\n\r\n    M = Mt; // copy scratch memory.\r\n  } else {\r\n    // if P argument is null, we just use an identity permutation.\r\n    P = [];\r\n    for (let i = 0; i < n; ++i) {\r\n      P[i] = i;\r\n    }\r\n  }\r\n\r\n  // The sparse matrix we are decomposing is A.\r\n  // Now we shall create A from M.\r\n  let Ap = new Array(n + 1);\r\n  let Ai = new Array(M.length);\r\n  let Ax = new Array(M.length);\r\n\r\n  // count number of non-zero elements in columns.\r\n  let LNZ = [];\r\n  for (let i = 0; i < n; ++i) {\r\n    LNZ[i] = 0;\r\n  }\r\n  for (let a = 0; a < M.length; ++a) {\r\n    LNZ[M[a][1]]++;\r\n  }\r\n\r\n  Ap[0] = 0;\r\n  for (let i = 0; i < n; ++i) {\r\n    Ap[i + 1] = Ap[i] + LNZ[i];\r\n  }\r\n\r\n  let coloffset = [];\r\n  for (let a = 0; a < n; ++a) {\r\n    coloffset[a] = 0;\r\n  }\r\n\r\n  // go through all elements in M, and add them to sparse matrix A.\r\n  for (let i = 0; i < M.length; ++i) {\r\n    let e = M[i];\r\n    let col = e[1];\r\n\r\n    let adr = Ap[col] + coloffset[col];\r\n    Ai[adr] = e[0];\r\n    Ax[adr] = e[2];\r\n\r\n    coloffset[col]++;\r\n  }\r\n\r\n  let D = new Array(n);\r\n  let Y = new Array(n);\r\n  let Lp = new Array(n + 1);\r\n  let Parent = new Array(n);\r\n  let Lnz = new Array(n);\r\n  let Flag = new Array(n);\r\n  let Pattern = new Array(n);\r\n  let bp1 = new Array(n);\r\n  let x = new Array(n);\r\n  let d;\r\n\r\n  ldlSymbolic(n, Ap, Ai, Lp, Parent, Lnz, Flag);\r\n\r\n  let Lx = new Array(Lp[n]);\r\n  let Li = new Array(Lp[n]);\r\n\r\n  d = ldlNumeric(n, Ap, Ai, Ax, Lp, Parent, Lnz, Li, Lx, D, Y, Pattern, Flag);\r\n\r\n  if (d === n) {\r\n    return function (b) {\r\n      ldlPerm(n, bp1, b, P);\r\n      ldlLsolve(n, bp1, Lp, Li, Lx);\r\n      ldlDsolve(n, bp1, D);\r\n      ldlLTsolve(n, bp1, Lp, Li, Lx);\r\n      ldlPermt(n, x, bp1, P);\r\n\r\n      return x;\r\n    };\r\n  } else {\r\n    return null;\r\n  }\r\n}\r\n\r\nexport { prepare as default };\r\n","'use strict'\n\nmodule.exports = cuthillMckee\n\nfunction compareNum(a, b) { return a - b }\n\nfunction cuthillMckee(list, n) {\n  var adj = new Array(n)\n  var visited = new Array(n)\n  for(var i=0; i<n; ++i) {\n    adj[i]     = []\n    visited[i] = false\n  }\n\n  for(var i=0; i<list.length; ++i) {\n    var l = list[i]\n    adj[l[0]].push(l[1])\n  }\n\n  var toVisit = new Array(n)\n  var eol = 0\n  var ptr = 0\n  for(var i=0; i<n; ++i) {\n    if(visited[i]) {\n      continue\n    }\n    toVisit[eol++] = i\n    visited[i] = true\n    while(ptr < eol) {\n      var v = toVisit[ptr++]\n      var nbhd = adj[v]\n      nbhd.sort(compareNum)\n      for(var j=0; j<nbhd.length; ++j) {\n        var u = nbhd[j]\n        if(visited[u]) {\n          continue\n        }\n        visited[u] = true\n        toVisit[eol++] = u\n      }\n    }\n  }\n\n  var result = new Array(n)\n  for(var i=0; i<n; ++i) {\n    result[toVisit[i]] = i\n  }\n\n  return result\n}\n","import cuthillMckee from 'cuthill-mckee';\r\n\r\nconst getClosestNumber = (array = [], goal = 0) => {\r\n  const closest = array.reduce((prev, curr) => {\r\n    return Math.abs(curr - goal) < Math.abs(prev - goal) ? curr : prev;\r\n  });\r\n  return closest;\r\n};\r\n\r\nconst getCloseIndex = (array = [], goal = 0) => {\r\n  const closest = getClosestNumber(array, goal);\r\n  return array.indexOf(closest);\r\n};\r\n\r\nconst updateSystem = (matrix, y, weights) => {\r\n  let nbPoints = y.length;\r\n  let l = nbPoints - 1;\r\n  let newMatrix = new Array(matrix.length);\r\n  let newVector = new Float64Array(nbPoints);\r\n  for (let i = 0; i < l; i++) {\r\n    let w = weights[i];\r\n    let diag = i * 2;\r\n    let next = diag + 1;\r\n    newMatrix[diag] = matrix[diag].slice();\r\n    newMatrix[next] = matrix[next].slice();\r\n    if (w === 0) {\r\n      newVector[i] = 0;\r\n    } else {\r\n      newVector[i] = y[i] * w;\r\n      newMatrix[diag][2] += w;\r\n    }\r\n  }\r\n  newVector[l] = y[l] * weights[l];\r\n  newMatrix[l * 2] = matrix[l * 2].slice();\r\n  newMatrix[l * 2][2] += weights[l];\r\n\r\n  return [newMatrix, newVector];\r\n};\r\n\r\nconst getDeltaMatrix = (nbPoints, lambda) => {\r\n  let matrix = [];\r\n  let last = nbPoints - 1;\r\n  for (let i = 0; i < last; i++) {\r\n    matrix.push([i, i, lambda * 2]);\r\n    matrix.push([i + 1, i, -1 * lambda]);\r\n  }\r\n  matrix[0][2] = lambda;\r\n  matrix.push([last, last, lambda]);\r\n  return {\r\n    lowerTriangularNonZeros: matrix,\r\n    permutationEncodedArray: cuthillMckee(matrix, nbPoints),\r\n  };\r\n};\r\n\r\nexport { updateSystem, getDeltaMatrix, getCloseIndex, getClosestNumber };\r\n","import Cholesky from './choleskySolver';\r\nimport { updateSystem, getDeltaMatrix, getCloseIndex } from './utils';\r\n\r\n/**\r\n * Fit the baseline drift by iteratively changing weights of sum square error between the fitted baseline and original signals,\r\n * for further information about the parameters you can get the [paper of airPLS](https://github.com/zmzhang/airPLS/blob/master/airPLS_manuscript.pdf)\r\n * @param {Array<number>} x - x axis data useful when control points or zones are submitted\r\n * @param {Array<number>} y - Original data\r\n * @param {object} [options={}] - Options object\r\n * @param {number} [options.maxIterations = 100] - Maximal number of iterations if the method does not reach the stop criterion\r\n * @param {number} [options.factorCriterion = 0.001] - Factor of the sum of absolute value of original data, to compute stop criterion\r\n * @param {Array<number>} [options.weights = [1,1,...]] - Initial weights vector, default each point has the same weight\r\n * @param {number} [options.lambda = 100] - Factor of weights matrix in -> [I + lambda D'D]z = x\r\n * @param {Array<number>} [options.controlPoints = []] - Array of x axis values to force that baseline cross those points.\r\n * @param {Array<number>} [options.baseLineZones = []] - Array of x axis values (as from - to), to force that baseline cross those zones.\r\n * @returns {{corrected: Array<number>, error: number, iteration: number, baseline: Array<number>}}\r\n */\r\nfunction airPLS(x, y, options = {}) {\r\n  let {\r\n    maxIterations = 100,\r\n    lambda = 100,\r\n    factorCriterion = 0.001,\r\n    weights = new Array(y.length).fill(1),\r\n    controlPoints = [],\r\n    baseLineZones = [],\r\n  } = options;\r\n\r\n  if (controlPoints.length > 0) {\r\n    controlPoints.forEach((e, i, arr) => (arr[i] = getCloseIndex(x, e)));\r\n  }\r\n  if (baseLineZones.length > 0) {\r\n    baseLineZones.forEach((range) => {\r\n      let indexFrom = getCloseIndex(x, range.from);\r\n      let indexTo = getCloseIndex(x, range.to);\r\n      if (indexFrom > indexTo) [indexFrom, indexTo] = [indexTo, indexFrom];\r\n      for (let i = indexFrom; i < indexTo; i++) {\r\n        controlPoints.push(i);\r\n      }\r\n    });\r\n  }\r\n\r\n  let baseline, iteration;\r\n  let nbPoints = y.length;\r\n  let l = nbPoints - 1;\r\n  let sumNegDifferences = Number.MAX_SAFE_INTEGER;\r\n  let stopCriterion =\r\n    factorCriterion * y.reduce((sum, e) => Math.abs(e) + sum, 0);\r\n\r\n  let { lowerTriangularNonZeros, permutationEncodedArray } = getDeltaMatrix(\r\n    nbPoints,\r\n    lambda,\r\n  );\r\n\r\n  for (\r\n    iteration = 0;\r\n    iteration < maxIterations && Math.abs(sumNegDifferences) > stopCriterion;\r\n    iteration++\r\n  ) {\r\n    let [leftHandSide, rightHandSide] = updateSystem(\r\n      lowerTriangularNonZeros,\r\n      y,\r\n      weights,\r\n    );\r\n\r\n    let cho = Cholesky(leftHandSide, nbPoints, permutationEncodedArray);\r\n\r\n    baseline = cho(rightHandSide);\r\n\r\n    sumNegDifferences = 0;\r\n\r\n    let difference = y.map(calculateError);\r\n\r\n    let maxNegativeDiff = -1 * Number.MAX_SAFE_INTEGER;\r\n    for (let i = 1; i < l; i++) {\r\n      let diff = difference[i];\r\n      if (diff >= 0) {\r\n        weights[i] = 0;\r\n      } else {\r\n        weights[i] = Math.exp((iteration * diff) / sumNegDifferences);\r\n        if (maxNegativeDiff < diff) maxNegativeDiff = diff;\r\n      }\r\n    }\r\n\r\n    let value = Math.exp((iteration * maxNegativeDiff) / sumNegDifferences);\r\n    weights[0] = value;\r\n    weights[l] = value;\r\n    controlPoints.forEach((i) => (weights[i] = value));\r\n  }\r\n\r\n  return {\r\n    corrected: y.map((e, i) => e - baseline[i]),\r\n    baseline,\r\n    iteration,\r\n    error: sumNegDifferences,\r\n  };\r\n\r\n  function calculateError(e, i) {\r\n    let diff = e - baseline[i];\r\n    if (diff < 0) sumNegDifferences += diff;\r\n    return diff;\r\n  }\r\n}\r\n\r\nexport { airPLS as default };\r\n","import { isAnyArray } from 'is-any-array';\n\nfunction _typeof(obj) {\n  \"@babel/helpers - typeof\";\n\n  if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") {\n    _typeof = function (obj) {\n      return typeof obj;\n    };\n  } else {\n    _typeof = function (obj) {\n      return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj;\n    };\n  }\n\n  return _typeof(obj);\n}\n\n/**\n * Fill an array with sequential numbers\n * @param {Array<number>} [input] - optional destination array (if not provided a new array will be created)\n * @param {object} [options={}]\n * @param {number} [options.from=0] - first value in the array\n * @param {number} [options.to=10] - last value in the array\n * @param {number} [options.size=input.length] - size of the array (if not provided calculated from step)\n * @param {number} [options.step] - if not provided calculated from size\n * @return {Array<number>}\n */\n\nfunction sequentialFill() {\n  var input = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : [];\n  var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {};\n\n  if (_typeof(input) === 'object' && !isAnyArray(input)) {\n    options = input;\n    input = [];\n  }\n\n  if (!isAnyArray(input)) {\n    throw new TypeError('input must be an array');\n  }\n\n  var _options = options,\n      _options$from = _options.from,\n      from = _options$from === void 0 ? 0 : _options$from,\n      _options$to = _options.to,\n      to = _options$to === void 0 ? 10 : _options$to,\n      _options$size = _options.size,\n      size = _options$size === void 0 ? input.length : _options$size,\n      step = _options.step;\n\n  if (size !== 0 && step) {\n    throw new Error('step is defined by the array size');\n  }\n\n  if (!size) {\n    if (step) {\n      size = Math.floor((to - from) / step) + 1;\n    } else {\n      size = to - from + 1;\n    }\n  }\n\n  if (!step && size) {\n    step = (to - from) / (size - 1);\n  }\n\n  if (Array.isArray(input)) {\n    // only works with normal array\n    input.length = 0;\n\n    for (var i = 0; i < size; i++) {\n      input.push(from);\n      from += step;\n    }\n  } else {\n    if (input.length !== size) {\n      throw new Error('sequentialFill typed array must have the correct length');\n    }\n\n    for (var _i = 0; _i < size; _i++) {\n      input[_i] = from;\n      from += step;\n    }\n  }\n\n  return input;\n}\n\nexport { sequentialFill as default };\n","export default function maybeToPrecision(value, digits) {\n  if (value < 0) {\n    value = 0 - value;\n    if (typeof digits === 'number') {\n      return `- ${value.toPrecision(digits)}`;\n    } else {\n      return `- ${value.toString()}`;\n    }\n  } else {\n    if (typeof digits === 'number') {\n      return value.toPrecision(digits);\n    } else {\n      return value.toString();\n    }\n  }\n}\n","import { isAnyArray } from 'is-any-array';\n\nexport { default as maybeToPrecision } from './maybeToPrecision';\nexport { default as checkArrayLength } from './checkArrayLength';\n\nexport default class BaseRegression {\n  constructor() {\n    if (new.target === BaseRegression) {\n      throw new Error('BaseRegression must be subclassed');\n    }\n  }\n\n  predict(x) {\n    if (typeof x === 'number') {\n      return this._predict(x);\n    } else if (isAnyArray(x)) {\n      const y = [];\n      for (let i = 0; i < x.length; i++) {\n        y.push(this._predict(x[i]));\n      }\n      return y;\n    } else {\n      throw new TypeError('x must be a number or array');\n    }\n  }\n\n  _predict() {\n    throw new Error('_predict must be implemented');\n  }\n\n  train() {\n    // Do nothing for this package\n  }\n\n  toString() {\n    return '';\n  }\n\n  toLaTeX() {\n    return '';\n  }\n\n  /**\n   * Return the correlation coefficient of determination (r) and chi-square.\n   * @param {Array<number>} x\n   * @param {Array<number>} y\n   * @return {object}\n   */\n  score(x, y) {\n    if (!isAnyArray(x) || !isAnyArray(y) || x.length !== y.length) {\n      throw new Error('x and y must be arrays of the same length');\n    }\n\n    const n = x.length;\n    const y2 = new Array(n);\n    for (let i = 0; i < n; i++) {\n      y2[i] = this._predict(x[i]);\n    }\n\n    let xSum = 0;\n    let ySum = 0;\n    let chi2 = 0;\n    let rmsd = 0;\n    let xSquared = 0;\n    let ySquared = 0;\n    let xY = 0;\n    for (let i = 0; i < n; i++) {\n      xSum += y2[i];\n      ySum += y[i];\n      xSquared += y2[i] * y2[i];\n      ySquared += y[i] * y[i];\n      xY += y2[i] * y[i];\n      if (y[i] !== 0) {\n        chi2 += ((y[i] - y2[i]) * (y[i] - y2[i])) / y[i];\n      }\n      rmsd += (y[i] - y2[i]) * (y[i] - y2[i]);\n    }\n\n    const r =\n      (n * xY - xSum * ySum) /\n      Math.sqrt((n * xSquared - xSum * xSum) * (n * ySquared - ySum * ySum));\n\n    return {\n      r: r,\n      r2: r * r,\n      chi2: chi2,\n      rmsd: Math.sqrt(rmsd / n),\n    };\n  }\n}\n","import { Matrix, MatrixTransposeView, solve } from 'ml-matrix';\nimport BaseRegression, {\n  checkArrayLength,\n  maybeToPrecision,\n} from 'ml-regression-base';\n\nexport default class PolynomialRegression extends BaseRegression {\n  constructor(x, y, degree) {\n    super();\n    if (x === true) {\n      this.degree = y.degree;\n      this.powers = y.powers;\n      this.coefficients = y.coefficients;\n    } else {\n      checkArrayLength(x, y);\n      regress(this, x, y, degree);\n    }\n  }\n\n  _predict(x) {\n    let y = 0;\n    for (let k = 0; k < this.powers.length; k++) {\n      y += this.coefficients[k] * Math.pow(x, this.powers[k]);\n    }\n    return y;\n  }\n\n  toJSON() {\n    return {\n      name: 'polynomialRegression',\n      degree: this.degree,\n      powers: this.powers,\n      coefficients: this.coefficients,\n    };\n  }\n\n  toString(precision) {\n    return this._toFormula(precision, false);\n  }\n\n  toLaTeX(precision) {\n    return this._toFormula(precision, true);\n  }\n\n  _toFormula(precision, isLaTeX) {\n    let sup = '^';\n    let closeSup = '';\n    let times = ' * ';\n    if (isLaTeX) {\n      sup = '^{';\n      closeSup = '}';\n      times = '';\n    }\n\n    let fn = '';\n    let str = '';\n    for (let k = 0; k < this.coefficients.length; k++) {\n      str = '';\n      if (this.coefficients[k] !== 0) {\n        if (this.powers[k] === 0) {\n          str = maybeToPrecision(this.coefficients[k], precision);\n        } else {\n          if (this.powers[k] === 1) {\n            str = `${maybeToPrecision(this.coefficients[k], precision) +\n              times}x`;\n          } else {\n            str = `${maybeToPrecision(this.coefficients[k], precision) +\n              times}x${sup}${this.powers[k]}${closeSup}`;\n          }\n        }\n\n        if (this.coefficients[k] > 0 && k !== this.coefficients.length - 1) {\n          str = ` + ${str}`;\n        } else if (k !== this.coefficients.length - 1) {\n          str = ` ${str}`;\n        }\n      }\n      fn = str + fn;\n    }\n    if (fn.charAt(0) === '+') {\n      fn = fn.slice(1);\n    }\n\n    return `f(x) = ${fn}`;\n  }\n\n  static load(json) {\n    if (json.name !== 'polynomialRegression') {\n      throw new TypeError('not a polynomial regression model');\n    }\n    return new PolynomialRegression(true, json);\n  }\n}\n\nfunction regress(pr, x, y, degree) {\n  const n = x.length;\n  let powers;\n  if (Array.isArray(degree)) {\n    powers = degree;\n    degree = powers.length;\n  } else {\n    degree++;\n    powers = new Array(degree);\n    for (let k = 0; k < degree; k++) {\n      powers[k] = k;\n    }\n  }\n  const F = new Matrix(n, degree);\n  const Y = new Matrix([y]);\n  for (let k = 0; k < degree; k++) {\n    for (let i = 0; i < n; i++) {\n      if (powers[k] === 0) {\n        F.set(i, k, 1);\n      } else {\n        F.set(i, k, Math.pow(x[i], powers[k]));\n      }\n    }\n  }\n\n  const FT = new MatrixTransposeView(F);\n  const A = FT.mmul(F);\n  const B = FT.mmul(new MatrixTransposeView(Y));\n\n  pr.degree = degree - 1;\n  pr.powers = powers;\n  pr.coefficients = solve(A, B).to1DArray();\n}\n","import { isAnyArray } from 'is-any-array';\n\nexport default function checkArraySize(x, y) {\n  if (!isAnyArray(x) || !isAnyArray(y)) {\n    throw new TypeError('x and y must be arrays');\n  }\n  if (x.length !== y.length) {\n    throw new RangeError('x and y arrays must have the same length');\n  }\n}\n","import PolynomialRegression from 'ml-regression-polynomial';\r\n\r\n/**\r\n * Iterative regression-based baseline correction\r\n * @param {Array<number>} x - Independent axis variable\r\n * @param {Array<number>} y - Dependent axis variable\r\n * @param {object} [options] - Options object\r\n * @param {number} [options.maxIterations = 100] - Maximum number of allowed iterations\r\n * @param {function} [options.Regression = PolynomialRegression] - Regression class with a predict method\r\n * @param {*} [options.regressionOptions] - Options for regressionFunction\r\n * @param {number} [options.tolerance = 0.001] - Convergence error tolerance\r\n * @return {{corrected: Array<number>, delta: number, iteration: number, baseline: Array<number>}}\r\n */\r\nexport default function baselineCorrectionRegression(x, y, options = {}) {\r\n  let {\r\n    maxIterations = 100,\r\n    Regression = PolynomialRegression,\r\n    regressionOptions,\r\n    tolerance = 0.001,\r\n  } = options;\r\n\r\n  if (!regressionOptions && Regression === PolynomialRegression) {\r\n    regressionOptions = 3;\r\n  }\r\n\r\n  let baseline = y.slice();\r\n  let fitting = y.slice();\r\n  let oldFitting = y;\r\n  let iteration = 0;\r\n  let delta;\r\n  let regression;\r\n  while (iteration < maxIterations) {\r\n    // Calculate the fitting result\r\n    regression = new Regression(x, baseline, regressionOptions);\r\n\r\n    delta = 0;\r\n    for (let i = 0; i < baseline.length; i++) {\r\n      fitting[i] = regression.predict(x[i]);\r\n      if (baseline[i] > fitting[i]) {\r\n        baseline[i] = fitting[i];\r\n      }\r\n\r\n      delta += Math.abs((fitting[i] - oldFitting[i]) / oldFitting[i]);\r\n    }\r\n\r\n    // Stop criterion\r\n    if (delta < tolerance) {\r\n      break;\r\n    } else {\r\n      oldFitting = fitting.slice();\r\n      iteration++;\r\n    }\r\n  }\r\n\r\n  // removes baseline\r\n  let corrected = new Array(baseline.length);\r\n  for (let j = 0; j < baseline.length; j++) {\r\n    corrected[j] = y[j] - baseline[j];\r\n  }\r\n\r\n  return {\r\n    corrected,\r\n    delta,\r\n    iteration,\r\n    baseline,\r\n    regression: regression,\r\n  };\r\n}\r\n","import { isAnyArray } from 'is-any-array';\nimport { xMean, xMaxValue, xMinValue } from 'ml-spectra-processing';\n\n/**\n * Rolling ball baseline correction algorithm.\n * From the abstract of (1):\n * \"This algorithm behaves equivalently to traditional polynomial backgrounds in simple spectra,\n * [...] and is considerably more robust for multiple overlapping peaks, rapidly varying background [...]\n *\n * The baseline is the trace one gets by rolling a ball below a spectrum. Algorithm has three steps:\n * Finding the minima in each window, find maxima among minima and then smooth over them by averaging.\n *\n * Reference:\n * (1) Kneen, M. A.; Annegarn, H. J.\n *     Algorithm for Fitting XRF, SEM and PIXE X-Ray Spectra Backgrounds.\n *     Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 1996, 109–110, 209–213.\n *     https://doi.org/10.1016/0168-583X(95)00908-6.\n * (2) Kristian Hovde Liland, Bjørn-Helge Mevik, Roberto Canteri: baseline.\n *     https://cran.r-project.org/web/packages/baseline/index.html\n * @export\n * @param {Array} spectrum\n * @param {Object} [options={}]\n * @param {Number} [options.windowM] - width of local window for minimization/maximization, defaults to 4% of the spectrum length\n * @param {Number} [options.windowS] - width of local window for smoothing, defaults to 8% of the spectrum length\n */\nexport function rollingBall(spectrum, options = {}) {\n  if (!isAnyArray(spectrum)) {\n    throw new Error('Spectrum must be an array');\n  }\n\n  if (spectrum.length === 0) {\n    throw new TypeError('Spectrum must not be empty');\n  }\n\n  const numberPoints = spectrum.length;\n  const maxima = new Float64Array(numberPoints);\n  const minima = new Float64Array(numberPoints);\n  const baseline = new Float64Array(numberPoints);\n\n  // windowM 4 percent of spectrum length\n  // windowS 8 percent of spectrum length\n  const {\n    windowM = Math.round(numberPoints * 0.04),\n    windowS = Math.round(numberPoints * 0.08),\n  } = options;\n\n  // fi(1) in original paper\n  for (let i = 0; i < spectrum.length; i++) {\n    let windowLeft = Math.max(0, i - windowM);\n    let windowRight = Math.min(i + windowM + 1, spectrum.length);\n\n    minima[i] = xMinValue(spectrum, {\n      fromIndex: windowLeft,\n      toIndex: windowRight,\n    });\n  }\n\n  // fi in original paper\n  for (let i = 0; i < minima.length; i++) {\n    let windowLeft = Math.max(0, i - windowM);\n    let windowRight = Math.min(i + windowM + 1, minima.length);\n    maxima[i] = xMaxValue(minima, {\n      fromIndex: windowLeft,\n      toIndex: windowRight,\n    });\n  }\n\n  for (let i = 0; i < minima.length; i++) {\n    let windowLeft = Math.max(0, i - windowS);\n    let windowRight = Math.min(i + windowS + 1, maxima.length);\n    baseline[i] = xMean(maxima.subarray(windowLeft, windowRight));\n  }\n\n  return baseline;\n}\n","import { isAnyArray } from 'is-any-array';\n/**\n * Apply Savitzky Golay algorithm\n * @param [ys] Array of y values\n * @param [xs] Array of X or deltaX\n * @return  Array containing the new ys (same length)\n */\nexport function sgg(ys, xs, options = {}) {\n    let { windowSize = 9, derivative = 0, polynomial = 3 } = options;\n    if (windowSize % 2 === 0 || windowSize < 5 || !Number.isInteger(windowSize)) {\n        throw new RangeError('Invalid window size (should be odd and at least 5 integer number)');\n    }\n    if (!isAnyArray(ys)) {\n        throw new TypeError('Y values must be an array');\n    }\n    if (typeof xs === 'undefined') {\n        throw new TypeError('X must be defined');\n    }\n    if (windowSize > ys.length) {\n        throw new RangeError(`Window size is higher than the data length ${windowSize}>${ys.length}`);\n    }\n    if (derivative < 0 || !Number.isInteger(derivative)) {\n        throw new RangeError('Derivative should be a positive integer');\n    }\n    if (polynomial < 1 || !Number.isInteger(polynomial)) {\n        throw new RangeError('Polynomial should be a positive integer');\n    }\n    if (polynomial >= 6) {\n        // eslint-disable-next-line no-console\n        console.warn('You should not use polynomial grade higher than 5 if you are' +\n            ' not sure that your data arises from such a model. Possible polynomial oscillation problems');\n    }\n    let half = Math.floor(windowSize / 2);\n    let np = ys.length;\n    let ans = new Float64Array(np);\n    let weights = fullWeights(windowSize, polynomial, derivative);\n    let hs = 0;\n    let constantH = true;\n    if (isAnyArray(xs)) {\n        constantH = false;\n    }\n    else {\n        hs = Math.pow(xs, derivative);\n    }\n    //For the borders\n    for (let i = 0; i < half; i++) {\n        let wg1 = weights[half - i - 1];\n        let wg2 = weights[half + i + 1];\n        let d1 = 0;\n        let d2 = 0;\n        for (let l = 0; l < windowSize; l++) {\n            d1 += wg1[l] * ys[l];\n            d2 += wg2[l] * ys[np - windowSize + l];\n        }\n        if (constantH) {\n            ans[half - i - 1] = d1 / hs;\n            ans[np - half + i] = d2 / hs;\n        }\n        else {\n            hs = getHs(xs, half - i - 1, half, derivative);\n            ans[half - i - 1] = d1 / hs;\n            hs = getHs(xs, np - half + i, half, derivative);\n            ans[np - half + i] = d2 / hs;\n        }\n    }\n    //For the internal points\n    let wg = weights[half];\n    for (let i = windowSize; i <= np; i++) {\n        let d = 0;\n        for (let l = 0; l < windowSize; l++)\n            d += wg[l] * ys[l + i - windowSize];\n        if (!constantH) {\n            hs = getHs(xs, i - half - 1, half, derivative);\n        }\n        ans[i - half - 1] = d / hs;\n    }\n    return ans;\n}\nfunction getHs(h, center, half, derivative) {\n    let hs = 0;\n    let count = 0;\n    for (let i = center - half; i < center + half; i++) {\n        if (i >= 0 && i < h.length - 1) {\n            hs += h[i + 1] - h[i];\n            count++;\n        }\n    }\n    return Math.pow(hs / count, derivative);\n}\nfunction gramPoly(i, m, k, s) {\n    let Grampoly = 0;\n    if (k > 0) {\n        Grampoly =\n            ((4 * k - 2) / (k * (2 * m - k + 1))) *\n                (i * gramPoly(i, m, k - 1, s) + s * gramPoly(i, m, k - 1, s - 1)) -\n                (((k - 1) * (2 * m + k)) / (k * (2 * m - k + 1))) *\n                    gramPoly(i, m, k - 2, s);\n    }\n    else {\n        if (k === 0 && s === 0) {\n            Grampoly = 1;\n        }\n        else {\n            Grampoly = 0;\n        }\n    }\n    return Grampoly;\n}\nfunction genFact(a, b) {\n    let gf = 1;\n    if (a >= b) {\n        for (let j = a - b + 1; j <= a; j++) {\n            gf *= j;\n        }\n    }\n    return gf;\n}\nfunction weight(i, t, m, n, s) {\n    let sum = 0;\n    for (let k = 0; k <= n; k++) {\n        sum +=\n            (2 * k + 1) *\n                (genFact(2 * m, k) / genFact(2 * m + k + 1, k + 1)) *\n                gramPoly(i, m, k, 0) *\n                gramPoly(t, m, k, s);\n    }\n    return sum;\n}\n/**\n * @private\n * @param m  Number of points\n * @param n  Polynomial grade\n * @param s  Derivative\n */\nfunction fullWeights(m, n, s) {\n    let weights = new Array(m);\n    let np = Math.floor(m / 2);\n    for (let t = -np; t <= np; t++) {\n        weights[t + np] = new Float64Array(m);\n        for (let j = -np; j <= np; j++) {\n            weights[t + np][j + np] = weight(j, t, np, n, s);\n        }\n    }\n    return weights;\n}\n//# sourceMappingURL=index.js.map","export const GAUSSIAN_EXP_FACTOR = -4 * Math.LN2;\nexport const ROOT_PI_OVER_LN2 = Math.sqrt(Math.PI / Math.LN2);\nexport const ROOT_THREE = Math.sqrt(3);\nexport const ROOT_2LN2 = Math.sqrt(2 * Math.LN2);\nexport const ROOT_2LN2_MINUS_ONE = Math.sqrt(2 * Math.LN2) - 1;\n//# sourceMappingURL=constants.js.map","// https://en.wikipedia.org/wiki/Error_function#Inverse_functions\n// This code yields to a good approximation\n// If needed a better implementation using polynomial can be found on https://en.wikipedia.org/wiki/Error_function#Inverse_functions\nexport default function erfinv(x) {\n    let a = 0.147;\n    if (x === 0)\n        return 0;\n    let ln1MinusXSqrd = Math.log(1 - x * x);\n    let lnEtcBy2Plus2 = ln1MinusXSqrd / 2 + 2 / (Math.PI * a);\n    let firstSqrt = Math.sqrt(lnEtcBy2Plus2 ** 2 - ln1MinusXSqrd / a);\n    let secondSqrt = Math.sqrt(firstSqrt - lnEtcBy2Plus2);\n    return secondSqrt * (x > 0 ? 1 : -1);\n}\n//# sourceMappingURL=erfinv.js.map","import { ROOT_2LN2, GAUSSIAN_EXP_FACTOR, ROOT_PI_OVER_LN2, } from '../../../util/constants';\nimport erfinv from '../../../util/erfinv';\nexport class Gaussian {\n    constructor(options = {}) {\n        const { fwhm = 500, sd } = options;\n        this.fwhm = sd ? gaussianWidthToFWHM(2 * sd) : fwhm;\n    }\n    fwhmToWidth(fwhm = this.fwhm) {\n        return gaussianFwhmToWidth(fwhm);\n    }\n    widthToFWHM(width) {\n        return gaussianWidthToFWHM(width);\n    }\n    fct(x) {\n        return gaussianFct(x, this.fwhm);\n    }\n    getArea(height = calculateGaussianHeight({ fwhm: this.fwhm })) {\n        return getGaussianArea({ fwhm: this.fwhm, height });\n    }\n    getFactor(area) {\n        return getGaussianFactor(area);\n    }\n    getData(options = {}) {\n        return getGaussianData(this, options);\n    }\n    calculateHeight(area = 1) {\n        return calculateGaussianHeight({ fwhm: this.fwhm, area });\n    }\n    getParameters() {\n        return ['fwhm'];\n    }\n}\nexport function calculateGaussianHeight(options) {\n    let { fwhm = 500, area = 1, sd } = options;\n    if (sd)\n        fwhm = gaussianWidthToFWHM(2 * sd);\n    return (2 * area) / ROOT_PI_OVER_LN2 / fwhm;\n}\n/**\n * Calculate the height of the gaussian function of a specific width (fwhm) at a speicifc\n * x position (the gaussian is centered on x=0)\n * @param x\n * @param fwhm\n * @returns y\n */\nexport function gaussianFct(x, fwhm) {\n    return Math.exp(GAUSSIAN_EXP_FACTOR * Math.pow(x / fwhm, 2));\n}\nexport function gaussianWidthToFWHM(width) {\n    return width * ROOT_2LN2;\n}\nexport function gaussianFwhmToWidth(fwhm) {\n    return fwhm / ROOT_2LN2;\n}\nexport function getGaussianArea(options) {\n    let { fwhm = 500, sd, height = 1 } = options;\n    if (sd)\n        fwhm = gaussianWidthToFWHM(2 * sd);\n    return (height * ROOT_PI_OVER_LN2 * fwhm) / 2;\n}\nexport function getGaussianFactor(area = 0.9999) {\n    return Math.sqrt(2) * erfinv(area);\n}\nexport function getGaussianData(shape = {}, options = {}) {\n    let { fwhm = 500, sd } = shape;\n    if (sd)\n        fwhm = gaussianWidthToFWHM(2 * sd);\n    let { length, factor = getGaussianFactor(), height = calculateGaussianHeight({ fwhm }), } = options;\n    if (!length) {\n        length = Math.min(Math.ceil(fwhm * factor), Math.pow(2, 25) - 1);\n        if (length % 2 === 0)\n            length++;\n    }\n    const center = (length - 1) / 2;\n    const data = new Float64Array(length);\n    for (let i = 0; i <= center; i++) {\n        data[i] = gaussianFct(i - center, fwhm) * height;\n        data[length - 1 - i] = data[i];\n    }\n    return data;\n}\n//# sourceMappingURL=Gaussian.js.map","import { ROOT_THREE } from '../../../util/constants';\nexport class Lorentzian {\n    constructor(options = {}) {\n        const { fwhm = 500 } = options;\n        this.fwhm = fwhm;\n    }\n    fwhmToWidth(fwhm = this.fwhm) {\n        return lorentzianFwhmToWidth(fwhm);\n    }\n    widthToFWHM(width) {\n        return lorentzianWidthToFWHM(width);\n    }\n    fct(x) {\n        return lorentzianFct(x, this.fwhm);\n    }\n    getArea(height = 1) {\n        return getLorentzianArea({ fwhm: this.fwhm, height });\n    }\n    getFactor(area) {\n        return getLorentzianFactor(area);\n    }\n    getData(options = {}) {\n        return getLorentzianData(this, options);\n    }\n    calculateHeight(area = 1) {\n        return calculateLorentzianHeight({ fwhm: this.fwhm, area });\n    }\n    getParameters() {\n        return ['fwhm'];\n    }\n}\nexport const calculateLorentzianHeight = ({ fwhm = 1, area = 1 }) => {\n    return (2 * area) / Math.PI / fwhm;\n};\nexport const getLorentzianArea = (options) => {\n    const { fwhm = 500, height = 1 } = options;\n    return (height * Math.PI * fwhm) / 2;\n};\nexport const lorentzianFct = (x, fwhm) => {\n    return fwhm ** 2 / (4 * x ** 2 + fwhm ** 2);\n};\nexport const lorentzianWidthToFWHM = (width) => {\n    return width * ROOT_THREE;\n};\nexport const lorentzianFwhmToWidth = (fwhm) => {\n    return fwhm / ROOT_THREE;\n};\nexport const getLorentzianFactor = (area = 0.9999) => {\n    if (area >= 1) {\n        throw new Error('area should be (0 - 1)');\n    }\n    const halfResidual = (1 - area) * 0.5;\n    const quantileFunction = (p) => Math.tan(Math.PI * (p - 0.5));\n    return ((quantileFunction(1 - halfResidual) - quantileFunction(halfResidual)) / 2);\n};\nexport const getLorentzianData = (shape = {}, options = {}) => {\n    let { fwhm = 500 } = shape;\n    let { length, factor = getLorentzianFactor(), height = calculateLorentzianHeight({ fwhm, area: 1 }), } = options;\n    if (!length) {\n        length = Math.min(Math.ceil(fwhm * factor), Math.pow(2, 25) - 1);\n        if (length % 2 === 0)\n            length++;\n    }\n    const center = (length - 1) / 2;\n    const data = new Float64Array(length);\n    for (let i = 0; i <= center; i++) {\n        data[i] = lorentzianFct(i - center, fwhm) * height;\n        data[length - 1 - i] = data[i];\n    }\n    return data;\n};\n//# sourceMappingURL=Lorentzian.js.map","import { GAUSSIAN_EXP_FACTOR, ROOT_2LN2_MINUS_ONE, ROOT_PI_OVER_LN2, } from '../../../util/constants';\nimport { gaussianFct, getGaussianFactor } from '../gaussian/Gaussian';\nimport { lorentzianFct, getLorentzianFactor } from '../lorentzian/Lorentzian';\nexport class PseudoVoigt {\n    constructor(options = {}) {\n        const { fwhm = 500, mu = 0.5 } = options;\n        this.mu = mu;\n        this.fwhm = fwhm;\n    }\n    fwhmToWidth(fwhm = this.fwhm, mu = this.mu) {\n        return pseudoVoigtFwhmToWidth(fwhm, mu);\n    }\n    widthToFWHM(width, mu = this.mu) {\n        return pseudoVoigtWidthToFWHM(width, mu);\n    }\n    fct(x) {\n        return pseudoVoigtFct(x, this.fwhm, this.mu);\n    }\n    getArea(height = 1) {\n        return getPseudoVoigtArea({ fwhm: this.fwhm, height, mu: this.mu });\n    }\n    getFactor(area) {\n        return getPseudoVoigtFactor(area);\n    }\n    getData(options = {}) {\n        const { length, factor, height = calculatePseudoVoigtHeight({\n            fwhm: this.fwhm,\n            mu: this.mu,\n            area: 1,\n        }), } = options;\n        return getPseudoVoigtData(this, { factor, length, height });\n    }\n    calculateHeight(area = 1) {\n        return calculatePseudoVoigtHeight({ fwhm: this.fwhm, mu: this.mu, area });\n    }\n    getParameters() {\n        return ['fwhm', 'mu'];\n    }\n}\nexport const calculatePseudoVoigtHeight = (options = {}) => {\n    let { fwhm = 1, mu = 0.5, area = 1 } = options;\n    return (2 * area) / (fwhm * (mu * ROOT_PI_OVER_LN2 + (1 - mu) * Math.PI));\n};\nexport const pseudoVoigtFct = (x, fwhm, mu) => {\n    return (1 - mu) * lorentzianFct(x, fwhm) + mu * gaussianFct(x, fwhm);\n};\nexport const pseudoVoigtWidthToFWHM = (width, mu = 0.5) => {\n    return width * (mu * ROOT_2LN2_MINUS_ONE + 1);\n};\nexport const pseudoVoigtFwhmToWidth = (fwhm, mu = 0.5) => {\n    return fwhm / (mu * ROOT_2LN2_MINUS_ONE + 1);\n};\nexport const getPseudoVoigtArea = (options) => {\n    const { fwhm = 500, height = 1, mu = 0.5 } = options;\n    return (fwhm * height * (mu * ROOT_PI_OVER_LN2 + (1 - mu) * Math.PI)) / 2;\n};\nexport const getPseudoVoigtFactor = (area = 0.9999, mu = 0.5) => {\n    return mu < 1 ? getLorentzianFactor(area) : getGaussianFactor(area);\n};\nexport const getPseudoVoigtData = (shape = {}, options = {}) => {\n    let { fwhm = 500, mu = 0.5 } = shape;\n    let { length, factor = getPseudoVoigtFactor(0.999, mu), height = calculatePseudoVoigtHeight({ fwhm, mu, area: 1 }), } = options;\n    if (!height) {\n        height =\n            1 /\n                ((mu / Math.sqrt(-GAUSSIAN_EXP_FACTOR / Math.PI)) * fwhm +\n                    ((1 - mu) * fwhm * Math.PI) / 2);\n    }\n    if (!length) {\n        length = Math.min(Math.ceil(fwhm * factor), Math.pow(2, 25) - 1);\n        if (length % 2 === 0)\n            length++;\n    }\n    const center = (length - 1) / 2;\n    const data = new Float64Array(length);\n    for (let i = 0; i <= center; i++) {\n        data[i] = pseudoVoigtFct(i - center, fwhm, mu) * height;\n        data[length - 1 - i] = data[i];\n    }\n    return data;\n};\n//# sourceMappingURL=PseudoVoigt.js.map","import { Gaussian } from './gaussian/Gaussian';\nimport { Lorentzian } from './lorentzian/Lorentzian';\nimport { PseudoVoigt } from './pseudoVoigt/PseudoVoigt';\n/**\n * Generate a instance of a specific kind of shape.\n */\nexport function getShape1D(shape) {\n    const { kind } = shape;\n    switch (kind) {\n        case 'gaussian':\n            return new Gaussian(shape);\n        case 'lorentzian':\n            return new Lorentzian(shape);\n        case 'pseudoVoigt':\n            return new PseudoVoigt(shape);\n        default: {\n            throw Error(`Unknown distribution ${kind}`);\n        }\n    }\n}\n//# sourceMappingURL=getShape1D.js.map","import { getShape1D } from 'ml-peak-shape-generator';\n/**\n * Append 2 properties to the peaks, shape and fwhm\n */\nexport function appendShapeAndFWHM(peaks, options = {}) {\n    let { shape = { kind: 'gaussian' } } = options;\n    let shapeInstance = getShape1D(shape);\n    return peaks.map((peak) => ({\n        ...peak,\n        shape: { fwhm: shapeInstance.widthToFWHM(peak.width), ...shape },\n    }));\n}\n//# sourceMappingURL=appendShapeAndFWHM.js.map","/**\n * Correction of the x and y coordinates using a quadratic optimizations with the peak and its 3 closest neighbors to determine the true x,y values of the peak.\n * This process is done in place and is very fast.\n * @param data\n * @param peaks\n */\nexport function optimizeTop(data, peaks) {\n    const { x, y } = data;\n    for (const peak of peaks) {\n        let currentIndex = peak.index;\n        // The detected peak could be moved 1 or 2 units to left or right.\n        if (y[currentIndex - 1] >= y[currentIndex - 2] &&\n            y[currentIndex - 1] >= y[currentIndex]) {\n            currentIndex--;\n        }\n        else {\n            if (y[currentIndex + 1] >= y[currentIndex] &&\n                y[currentIndex + 1] >= y[currentIndex + 2]) {\n                currentIndex++;\n            }\n            else {\n                if (y[currentIndex - 2] >= y[currentIndex - 3] &&\n                    y[currentIndex - 2] >= y[currentIndex - 1]) {\n                    currentIndex -= 2;\n                }\n                else {\n                    if (y[currentIndex + 2] >= y[currentIndex + 1] &&\n                        y[currentIndex + 2] >= y[currentIndex + 3]) {\n                        currentIndex += 2;\n                    }\n                }\n            }\n        }\n        // interpolation to a sin() function\n        if (y[currentIndex - 1] > 0 &&\n            y[currentIndex + 1] > 0 &&\n            y[currentIndex] >= y[currentIndex - 1] &&\n            y[currentIndex] >= y[currentIndex + 1] &&\n            (y[currentIndex] !== y[currentIndex - 1] ||\n                y[currentIndex] !== y[currentIndex + 1])) {\n            let alpha = 20 * Math.log10(y[currentIndex - 1]);\n            let beta = 20 * Math.log10(y[currentIndex]);\n            let gamma = 20 * Math.log10(y[currentIndex + 1]);\n            let p = (0.5 * (alpha - gamma)) / (alpha - 2 * beta + gamma);\n            peak.x = x[currentIndex] + (x[currentIndex] - x[currentIndex - 1]) * p;\n            peak.y =\n                y[currentIndex] -\n                    0.25 * (y[currentIndex - 1] - y[currentIndex + 1]) * p;\n        }\n    }\n}\n//# sourceMappingURL=optimizeTop.js.map","import { sgg } from 'ml-savitzky-golay-generalized';\nimport { xIsEquallySpaced, xIsMonotoneIncreasing, xMinValue, xMaxValue, xNoiseStandardDeviation, } from 'ml-spectra-processing';\nimport { appendShapeAndFWHM } from './utils/appendShapeAndFWHM';\nimport { optimizeTop } from './utils/optimizeTop';\n/**\n * Global spectra deconvolution\n * @param  data - Object data with x and y arrays. Values in x has to be growing\n * @param {number} [options.broadRatio = 0.00] - If `broadRatio` is higher than 0, then all the peaks which second derivative\n * smaller than `broadRatio * maxAbsSecondDerivative` will be marked with the soft mask equal to true.\n\n */\nexport function gsd(data, options = {}) {\n    let { sgOptions = {\n        windowSize: 9,\n        polynomial: 3,\n    }, shape, noiseLevel, smoothY = false, maxCriteria = true, minMaxRatio = 0.00025, realTopDetection = false, } = options;\n    let { x, y } = data;\n    if (!xIsMonotoneIncreasing(x)) {\n        throw new Error('GSD only accepts monotone increasing x values');\n    }\n    //rescale;\n    y = y.slice();\n    // If the max difference between delta x is less than 5%, then,\n    // we can assume it to be equally spaced variable\n    let equallySpaced = xIsEquallySpaced(x);\n    if (noiseLevel === undefined) {\n        if (equallySpaced) {\n            const noiseInfo = xNoiseStandardDeviation(y);\n            if (maxCriteria) {\n                noiseLevel = noiseInfo.median + 1.5 * noiseInfo.sd;\n            }\n            else {\n                noiseLevel = -noiseInfo.median + 1.5 * noiseInfo.sd;\n            }\n        }\n        else {\n            noiseLevel = 0;\n        }\n    }\n    else {\n        if (maxCriteria === false) {\n            noiseLevel *= -1;\n        }\n    }\n    if (maxCriteria === false) {\n        for (let i = 0; i < y.length; i++) {\n            y[i] *= -1;\n        }\n    }\n    if (noiseLevel !== undefined) {\n        for (let i = 0; i < y.length; i++) {\n            if (y[i] < noiseLevel) {\n                y[i] = noiseLevel;\n            }\n        }\n    }\n    let yData = y;\n    let dY, ddY;\n    const { windowSize, polynomial } = sgOptions;\n    if (equallySpaced) {\n        if (smoothY) {\n            yData = sgg(y, x[1] - x[0], {\n                windowSize,\n                polynomial,\n                derivative: 0,\n            });\n        }\n        dY = sgg(y, x[1] - x[0], {\n            windowSize,\n            polynomial,\n            derivative: 1,\n        });\n        ddY = sgg(y, x[1] - x[0], {\n            windowSize,\n            polynomial,\n            derivative: 2,\n        });\n    }\n    else {\n        if (smoothY) {\n            yData = sgg(y, x, {\n                windowSize,\n                polynomial,\n                derivative: 0,\n            });\n        }\n        dY = sgg(y, x, {\n            windowSize,\n            polynomial,\n            derivative: 1,\n        });\n        ddY = sgg(y, x, {\n            windowSize,\n            polynomial,\n            derivative: 2,\n        });\n    }\n    const minY = xMinValue(yData);\n    const maxY = xMaxValue(yData);\n    if (minY > maxY || minY === maxY)\n        return [];\n    const yThreshold = minY + (maxY - minY) * minMaxRatio;\n    const dX = x[1] - x[0];\n    let lastMax = null;\n    let lastMin = null;\n    let minddY = [];\n    let intervalL = [];\n    let intervalR = [];\n    // By the intermediate value theorem We cannot find 2 consecutive maximum or minimum\n    for (let i = 1; i < yData.length - 1; ++i) {\n        if ((dY[i] < dY[i - 1] && dY[i] <= dY[i + 1]) ||\n            (dY[i] <= dY[i - 1] && dY[i] < dY[i + 1])) {\n            lastMin = {\n                x: x[i],\n                index: i,\n            };\n            if (dX > 0 && lastMax !== null) {\n                intervalL.push(lastMax);\n                intervalR.push(lastMin);\n            }\n        }\n        // Maximum in first derivative\n        if ((dY[i] >= dY[i - 1] && dY[i] > dY[i + 1]) ||\n            (dY[i] > dY[i - 1] && dY[i] >= dY[i + 1])) {\n            lastMax = {\n                x: x[i],\n                index: i,\n            };\n            if (dX < 0 && lastMin !== null) {\n                intervalL.push(lastMax);\n                intervalR.push(lastMin);\n            }\n        }\n        // Minimum in second derivative\n        if (ddY[i] < ddY[i - 1] && ddY[i] < ddY[i + 1]) {\n            minddY.push(i);\n        }\n    }\n    let lastK = -1;\n    const peaks = [];\n    for (const minddYIndex of minddY) {\n        let deltaX = x[minddYIndex];\n        let possible = -1;\n        let k = lastK + 1;\n        let minDistance = Number.POSITIVE_INFINITY;\n        let currentDistance = 0;\n        while (possible === -1 && k < intervalL.length) {\n            currentDistance = Math.abs(deltaX - (intervalL[k].x + intervalR[k].x) / 2);\n            if (currentDistance < (intervalR[k].x - intervalL[k].x) / 2) {\n                possible = k;\n                lastK = k;\n            }\n            ++k;\n            // Not getting closer?\n            if (currentDistance >= minDistance) {\n                break;\n            }\n            minDistance = currentDistance;\n        }\n        if (possible !== -1) {\n            if (yData[minddYIndex] > yThreshold) {\n                let width = Math.abs(intervalR[possible].x - intervalL[possible].x);\n                peaks.push({\n                    x: deltaX,\n                    y: yData[minddYIndex],\n                    width,\n                    index: minddYIndex,\n                    ddY: ddY[minddYIndex],\n                    inflectionPoints: {\n                        from: intervalL[possible],\n                        to: intervalR[possible],\n                    },\n                });\n            }\n        }\n    }\n    if (realTopDetection) {\n        optimizeTop({ x, y: yData }, peaks);\n    }\n    peaks.forEach((peak) => {\n        if (!maxCriteria) {\n            peak.y *= -1;\n            peak.ddY = peak.ddY * -1;\n        }\n    });\n    peaks.sort((a, b) => {\n        return a.x - b.x;\n    });\n    return appendShapeAndFWHM(peaks, { shape });\n}\n//# sourceMappingURL=gsd.js.map","import { isAnyArray } from 'is-any-array';\nexport default function checkOptions(data, parameterizedFunction, options) {\n    let { timeout, minValues, maxValues, initialValues, weights = 1, damping = 1e-2, dampingStepUp = 11, dampingStepDown = 9, maxIterations = 100, errorTolerance = 1e-7, centralDifference = false, gradientDifference = 10e-2, improvementThreshold = 1e-3, } = options;\n    if (damping <= 0) {\n        throw new Error('The damping option must be a positive number');\n    }\n    else if (!data.x || !data.y) {\n        throw new Error('The data parameter must have x and y elements');\n    }\n    else if (!isAnyArray(data.x) ||\n        data.x.length < 2 ||\n        !isAnyArray(data.y) ||\n        data.y.length < 2) {\n        throw new Error('The data parameter elements must be an array with more than 2 points');\n    }\n    else if (data.x.length !== data.y.length) {\n        throw new Error('The data parameter elements must have the same size');\n    }\n    let parameters = initialValues || new Array(parameterizedFunction.length).fill(1);\n    let nbPoints = data.y.length;\n    let parLen = parameters.length;\n    maxValues = maxValues || new Array(parLen).fill(Number.MAX_SAFE_INTEGER);\n    minValues = minValues || new Array(parLen).fill(Number.MIN_SAFE_INTEGER);\n    if (maxValues.length !== minValues.length) {\n        throw new Error('minValues and maxValues must be the same size');\n    }\n    if (!isAnyArray(parameters)) {\n        throw new Error('initialValues must be an array');\n    }\n    if (typeof gradientDifference === 'number') {\n        gradientDifference = new Array(parameters.length).fill(gradientDifference);\n    }\n    else if (isAnyArray(gradientDifference)) {\n        if (gradientDifference.length !== parLen) {\n            gradientDifference = new Array(parLen).fill(gradientDifference[0]);\n        }\n    }\n    else {\n        throw new Error('gradientDifference should be a number or array with length equal to the number of parameters');\n    }\n    let filler;\n    if (typeof weights === 'number') {\n        let value = 1 / weights ** 2;\n        filler = () => value;\n    }\n    else if (isAnyArray(weights)) {\n        if (weights.length < data.x.length) {\n            let value = 1 / weights[0] ** 2;\n            filler = () => value;\n        }\n        else {\n            filler = (i) => 1 / weights[i] ** 2;\n        }\n    }\n    else {\n        throw new Error('weights should be a number or array with length equal to the number of data points');\n    }\n    let checkTimeout;\n    if (timeout !== undefined) {\n        if (typeof timeout !== 'number') {\n            throw new Error('timeout should be a number');\n        }\n        let endTime = Date.now() + timeout * 1000;\n        checkTimeout = () => Date.now() > endTime;\n    }\n    else {\n        checkTimeout = () => false;\n    }\n    let weightSquare = new Array(data.x.length);\n    for (let i = 0; i < nbPoints; i++) {\n        weightSquare[i] = filler(i);\n    }\n    return {\n        checkTimeout,\n        minValues,\n        maxValues,\n        parameters,\n        weightSquare,\n        damping,\n        dampingStepUp,\n        dampingStepDown,\n        maxIterations,\n        errorTolerance,\n        centralDifference,\n        gradientDifference,\n        improvementThreshold,\n    };\n}\n//# sourceMappingURL=checkOptions.js.map","/**\n * the sum of the weighted squares of the errors (or weighted residuals) between the data.y\n * and the curve-fit function.\n * @ignore\n * @param {{x:ArrayLike<number>, y:ArrayLike<number>}} data - Array of points to fit in the format [x1, x2, ... ], [y1, y2, ... ]\n * @param {ArrayLike<number>} parameters - Array of current parameter values\n * @param {function} parameterizedFunction - The parameters and returns a function with the independent variable as a parameter\n * @param {ArrayLike<number>} weightSquare - Square of weights\n * @return {number}\n */\nexport default function errorCalculation(data, parameters, parameterizedFunction, weightSquare) {\n    let error = 0;\n    const func = parameterizedFunction(parameters);\n    for (let i = 0; i < data.x.length; i++) {\n        error += Math.pow(data.y[i] - func(data.x[i]), 2) / weightSquare[i];\n    }\n    return error;\n}\n//# sourceMappingURL=errorCalculation.js.map","import { inverse, Matrix } from 'ml-matrix';\nimport gradientFunction from './gradientFunction';\n/**\n * Matrix function over the samples\n * @ignore\n * @param {{x:ArrayLike<number>, y:ArrayLike<number>}} data - Array of points to fit in the format [x1, x2, ... ], [y1, y2, ... ]\n * @param {ArrayLike<number>} evaluatedData - Array of previous evaluated function values\n * @return {Matrix}\n */\nfunction matrixFunction(data, evaluatedData) {\n    const m = data.x.length;\n    let ans = new Matrix(m, 1);\n    for (let point = 0; point < m; point++) {\n        ans.set(point, 0, data.y[point] - evaluatedData[point]);\n    }\n    return ans;\n}\n/**\n * Iteration for Levenberg-Marquardt\n * @ignore\n * @param {{x:ArrayLike<number>, y:ArrayLike<number>}} data - Array of points to fit in the format [x1, x2, ... ], [y1, y2, ... ]\n * @param {Array<number>} params - Array of previous parameter values\n * @param {number} damping - Levenberg-Marquardt parameter\n * @param {number|array} gradientDifference - The step size to approximate the jacobian matrix\n * @param {boolean} centralDifference - If true the jacobian matrix is approximated by central differences otherwise by forward differences\n * @param {function} parameterizedFunction - The parameters and returns a function with the independent variable as a parameter\n */\nexport default function step(data, params, damping, gradientDifference, parameterizedFunction, centralDifference, weights) {\n    let value = damping;\n    let identity = Matrix.eye(params.length, params.length, value);\n    const func = parameterizedFunction(params);\n    let evaluatedData = new Float64Array(data.x.length);\n    for (let i = 0; i < data.x.length; i++) {\n        evaluatedData[i] = func(data.x[i]);\n    }\n    let gradientFunc = gradientFunction(data, evaluatedData, params, gradientDifference, parameterizedFunction, centralDifference);\n    let residualError = matrixFunction(data, evaluatedData);\n    let inverseMatrix = inverse(identity.add(gradientFunc.mmul(gradientFunc.transpose().scale('row', { scale: weights }))));\n    let jacobianWeightResidualError = gradientFunc.mmul(residualError.scale('row', { scale: weights }));\n    let perturbations = inverseMatrix.mmul(jacobianWeightResidualError);\n    return {\n        perturbations,\n        jacobianWeightResidualError,\n    };\n}\n//# sourceMappingURL=step.js.map","import { Matrix } from 'ml-matrix';\n/**\n * Difference of the matrix function over the parameters\n * @ignore\n * @param {{x:ArrayLike<number>, y:ArrayLike<number>}} data - Array of points to fit in the format [x1, x2, ... ], [y1, y2, ... ]\n * @param {ArrayLike<number>} evaluatedData - Array of previous evaluated function values\n * @param {Array<number>} params - Array of previous parameter values\n * @param {number|array} gradientDifference - The step size to approximate the jacobian matrix\n * @param {boolean} centralDifference - If true the jacobian matrix is approximated by central differences otherwise by forward differences\n * @param {function} paramFunction - The parameters and returns a function with the independent variable as a parameter\n * @return {Matrix}\n */\nexport default function gradientFunction(data, evaluatedData, params, gradientDifference, paramFunction, centralDifference) {\n    const nbParams = params.length;\n    const nbPoints = data.x.length;\n    let ans = Matrix.zeros(nbParams, nbPoints);\n    let rowIndex = 0;\n    for (let param = 0; param < nbParams; param++) {\n        if (gradientDifference[param] === 0)\n            continue;\n        let delta = gradientDifference[param];\n        let auxParams = params.slice();\n        auxParams[param] += delta;\n        let funcParam = paramFunction(auxParams);\n        if (!centralDifference) {\n            for (let point = 0; point < nbPoints; point++) {\n                ans.set(rowIndex, point, (evaluatedData[point] - funcParam(data.x[point])) / delta);\n            }\n        }\n        else {\n            auxParams = params.slice();\n            auxParams[param] -= delta;\n            delta *= 2;\n            let funcParam2 = paramFunction(auxParams);\n            for (let point = 0; point < nbPoints; point++) {\n                ans.set(rowIndex, point, (funcParam2(data.x[point]) - funcParam(data.x[point])) / delta);\n            }\n        }\n        rowIndex++;\n    }\n    return ans;\n}\n//# sourceMappingURL=gradientFunction.js.map","import checkOptions from './checkOptions';\nimport errorCalculation from './errorCalculation';\nimport step from './step';\n/**\n * Curve fitting algorithm\n * @param {{x:ArrayLike<number>, y:ArrayLike<number>}} data - Array of points to fit in the format [x1, x2, ... ], [y1, y2, ... ]\n * @param {function} parameterizedFunction - The parameters and returns a function with the independent variable as a parameter\n * @param {object} [options] - Options object\n * @param {number|ArrayLike<number>} [options.weights = 1] - weighting vector, if the length does not match with the number of data points, the vector is reconstructed with first value.\n * @param {number} [options.damping = 1e-2] - Levenberg-Marquardt parameter, small values of the damping parameter λ result in a Gauss-Newton update and large\nvalues of λ result in a gradient descent update\n * @param {number} [options.dampingStepDown = 9] - factor to reduce the damping (Levenberg-Marquardt parameter) when there is not an improvement when updating parameters.\n * @param {number} [options.dampingStepUp = 11] - factor to increase the damping (Levenberg-Marquardt parameter) when there is an improvement when updating parameters.\n * @param {number} [options.improvementThreshold = 1e-3] - the threshold to define an improvement through an update of parameters\n * @param {number|ArrayLike<number>} [options.gradientDifference = 10e-2] - The step size to approximate the jacobian matrix\n * @param {boolean} [options.centralDifference = false] - If true the jacobian matrix is approximated by central differences otherwise by forward differences\n * @param {ArrayLike<number>} [options.minValues] - Minimum allowed values for parameters\n * @param {ArrayLike<number>} [options.maxValues] - Maximum allowed values for parameters\n * @param {ArrayLike<number>} [options.initialValues] - Array of initial parameter values\n * @param {number} [options.maxIterations = 100] - Maximum of allowed iterations\n * @param {number} [options.errorTolerance = 10e-3] - Minimum uncertainty allowed for each point.\n * @param {number} [options.timeout] - maximum time running before throw in seconds.\n * @return {{parameterValues: Array<number>, parameterError: number, iterations: number}}\n */\nexport function levenbergMarquardt(data, parameterizedFunction, options = {}) {\n    let { checkTimeout, minValues, maxValues, parameters, weightSquare, damping, dampingStepUp, dampingStepDown, maxIterations, errorTolerance, centralDifference, gradientDifference, improvementThreshold, } = checkOptions(data, parameterizedFunction, options);\n    let error = errorCalculation(data, parameters, parameterizedFunction, weightSquare);\n    let optimalError = error;\n    let optimalParameters = parameters.slice();\n    let converged = error <= errorTolerance;\n    let iteration = 0;\n    for (; iteration < maxIterations && !converged; iteration++) {\n        let previousError = error;\n        let { perturbations, jacobianWeightResidualError } = step(data, parameters, damping, gradientDifference, parameterizedFunction, centralDifference, weightSquare);\n        for (let k = 0; k < parameters.length; k++) {\n            parameters[k] = Math.min(Math.max(minValues[k], parameters[k] - perturbations.get(k, 0)), maxValues[k]);\n        }\n        error = errorCalculation(data, parameters, parameterizedFunction, weightSquare);\n        if (isNaN(error))\n            break;\n        if (error < optimalError - errorTolerance) {\n            optimalError = error;\n            optimalParameters = parameters.slice();\n        }\n        let improvementMetric = (previousError - error) /\n            perturbations\n                .transpose()\n                .mmul(perturbations.mul(damping).add(jacobianWeightResidualError))\n                .get(0, 0);\n        if (improvementMetric > improvementThreshold) {\n            damping = Math.max(damping / dampingStepDown, 1e-7);\n        }\n        else {\n            damping = Math.min(damping * dampingStepUp, 1e7);\n        }\n        if (checkTimeout()) {\n            throw new Error(`The execution time is over to ${options.timeout} seconds`);\n        }\n        converged = error <= errorTolerance;\n    }\n    return {\n        parameterValues: optimalParameters,\n        parameterError: optimalError,\n        iterations: iteration,\n    };\n}\n//# sourceMappingURL=index.js.map","import { xMean } from 'ml-spectra-processing';\n/**\n * Center the mean\n * @param data\n */\nexport function centerMean(data) {\n    const { y } = data;\n    const mean = xMean(y);\n    for (let i = 0; i < y.length; i++) {\n        y[i] -= mean;\n    }\n    return { data };\n}\n//# sourceMappingURL=centerMean.js.map","import { xMedian } from 'ml-spectra-processing';\n/**\n * Center the median\n * @param data\n */\nexport function centerMedian(data) {\n    const { y } = data;\n    const median = xMedian(y);\n    for (let i = 0; i < y.length; i++) {\n        y[i] -= median;\n    }\n    return { data };\n}\n//# sourceMappingURL=centerMedian.js.map","import { xGetFromToIndex } from 'ml-spectra-processing';\n/**\n * Filter that allows to\n * @param data\n * @param options\n */\nexport function fromTo(data, options = {}) {\n    const { fromIndex, toIndex } = xGetFromToIndex(data.x, options);\n    return {\n        data: {\n            x: data.x.subarray(fromIndex, toIndex + 1),\n            y: data.y.subarray(fromIndex, toIndex + 1),\n        },\n    };\n}\n//# sourceMappingURL=fromTo.js.map","import { xNormed } from 'ml-spectra-processing';\n/**\n * Norm the Y values\n * @param data\n */\nexport function normed(data, options = {}) {\n    xNormed(data.y, { ...options, output: data.y });\n    return { data };\n}\n//# sourceMappingURL=normed.js.map","import { xStandardDeviation } from 'ml-spectra-processing';\n/**\n * Center the mean\n * @param data\n */\nexport function divideBySD(data) {\n    const { y } = data;\n    const sd = xStandardDeviation(y);\n    for (let i = 0; i < y.length; i++) {\n        y[i] /= sd;\n    }\n    return { data };\n}\n//# sourceMappingURL=divideBySD.js.map","import { xRescale } from 'ml-spectra-processing';\n/**\n * Center the mean\n * @param data\n */\nexport function rescale(data, options = {}) {\n    xRescale(data.y, { ...options, output: data.y });\n    return { data };\n}\n//# sourceMappingURL=rescale.js.map","import { xParetoNormalization } from 'ml-spectra-processing';\n/**\n * Filter that allows to\n * @param data\n */\nexport function paretoNormalization(data) {\n    return {\n        data: {\n            x: data.x,\n            y: xParetoNormalization(data.y),\n        },\n    };\n}\n//# sourceMappingURL=paretoNormalization.js.map","//@ts-expect-error no type definition for baselines\nimport { airPLSBaseline as baselineFct } from 'baselines';\n/**\n * @param data\n */\nexport function airPLSBaseline(data) {\n    data.y = baselineFct(data.y).correctedSpectrum;\n    return { data };\n}\n//# sourceMappingURL=airPLSBaseline.js.map","import airpls from 'ml-airpls';\nimport sequentialFill from 'ml-array-sequential-fill';\n/**\n * Adaptive iteratively reweighted penalized least squares [1]\n *\n * This function calls ml-airpls\n *\n * References:\n * [1] Zhang, Z.-M.; Chen, S.; Liang, Y.-Z.\n * Baseline Correction Using Adaptive Iteratively Reweighted Penalized Least Squares.\n * Analyst 2010, 135 (5), 1138–1146. https://doi.org/10.1039/B922045C.\n * @export\n * @param {Array<number>} ys\n * @param {object} [options] - Options object\n * @param {Array<number>} [options.x] Optional, Independent axis variable. If not specified, we use a linear grid\n * @param {object} [options.regression] - Options for the regression\n * @param {number} [options.regression.maxIterations = 100] - Maximum number of allowed iterations\n * @param {function} [options.regression.§Regression = PolynomialRegression] - Regression class with a predict method\n * @param {*} [options.regression.regressionOptions] - Options for regressionFunction\n * @param {number} [options.regression.tolerance = 0.001] - Convergence error tolerance\n * @returns {BaselineOutput}\n */\nexport function airPLSBaseline(ys, options = {}) {\n  const numberPoints = ys.length;\n  let { x, regressionOptions } = options;\n  if (!x) {\n    x = sequentialFill({ from: 0, to: numberPoints - 1, size: numberPoints });\n  }\n  let output = airpls(x, ys, regressionOptions);\n\n  return { baseline: output.baseline, correctedSpectrum: output.corrected };\n}\n","//@ts-expect-error no type definition for baselines\nimport { iterativePolynomialBaseline as baselineFct } from 'baselines';\n/**\n * @param data\n */\nexport function iterativePolynomialBaseline(data) {\n    data.y = baselineFct(data.y).correctedSpectrum;\n    return { data };\n}\n//# sourceMappingURL=iterativePolynomialBaseline.js.map","import sequentialFill from 'ml-array-sequential-fill';\nimport baselineCorrection from 'ml-baseline-correction-regression';\n\n/**\n * Iterative polynomial fitting [1]\n *\n * Implementation based on ml-baseline-correction-regression\n *\n * References:\n * [1] Gan, F.; Ruan, G.; Mo, J.\n * Baseline Correction by Improved Iterative Polynomial Fitting with Automatic Threshold.\n *  Chemometrics and Intelligent Laboratory Systems 2006, 82 (1), 59–65.\n * https://doi.org/10.1016/j.chemolab.2005.08.009.\n * @export\n * @param {Array<number>} ys\n * @param {object} [options] - Options object\n * @param {Array<number>} [options.x] Optional, Independent axis variable. If not specified, we use a linear grid\n * @param {Object} [options.regression]\n * @param {number} [options.regression.maxIterations = 100] - Maximum number of allowed iterations\n * @param {Object} [options.regression]\n * @param {function} [options.regression.Regression = PolynomialRegression] - Regression class with a predict method\n * @param {Object} [options.regression.regressionOptions] - Options for regressionFunction\n * @param {number} [options.regression.tolerance = 0.001] - Convergence error tolerance\n * @returns {BaselineOutput}\n */\nexport function iterativePolynomialBaseline(ys, options = {}) {\n  const numberPoints = ys.length;\n  let { x, regressionOptions } = options;\n  if (!x) {\n    x = sequentialFill({ from: 0, to: numberPoints - 1, size: numberPoints });\n  }\n\n  let output = baselineCorrection(x, ys, regressionOptions);\n\n  return { baseline: output.baseline, correctedSpectrum: output.corrected };\n}\n","//@ts-expect-error no type definition for baselines\nimport { rollingAverageBaseline as baselineFct } from 'baselines';\n/**\n * @param data\n */\nexport function rollingAverageBaseline(data) {\n    data.y = baselineFct(data.y).correctedSpectrum;\n    return { data };\n}\n//# sourceMappingURL=rollingAverageBaseline.js.map","import { xRollingAverage } from 'ml-spectra-processing';\n\n/**\n\n *\n * @export\n * @param {Array<number>} ys\n * @param {Object} [options={}]\n * @param {number} [options.window] rolling window size, defaults to 10% of the length of the spectrum\n * @param {string} [options.padding.size=window-1] none, value, circular, duplicate\n * @param {string} [options.padding.algorithm='duplicate'] none, value, circular, duplicate\n * @param {number} [options.padding.value=0] value to use for padding (if algorithm='value')\n * @returns {BaselineOutput}\n */\nexport function rollingAverageBaseline(ys, options = {}) {\n  let window = Math.max(Math.round(ys.length * 0.1), 2);\n  let defaults = {\n    window,\n    padding: {\n      size: window - 1,\n      algorithm: 'duplicate',\n      value: 0,\n    },\n  };\n  let actualOptions = { ...defaults, ...options };\n  let baseline = xRollingAverage(ys, actualOptions);\n  let corrected = new Float64Array(ys.length);\n  for (let i = 0; i < corrected.length; i++) {\n    corrected[i] = ys[i] - baseline[i];\n  }\n\n  return { baseline, correctedSpectrum: corrected };\n}\n","//@ts-expect-error no type definition for baselines\nimport { rollingBallBaseline as baselineFct } from 'baselines';\n/**\n * @param data\n */\nexport function rollingBallBaseline(data) {\n    data.y = baselineFct(data.y).correctedSpectrum;\n    return { data };\n}\n//# sourceMappingURL=rollingBallBaseline.js.map","import { rollingBall } from 'ml-rolling-ball-baseline';\n\n/**\n * Rolling ball baseline correction algorithm.\n * From the abstract of (1):\n * \"This algorithm behaves equivalently to traditional polynomial backgrounds in simple spectra,\n * [...] and is considerably more robust for multiple overlapping peaks, rapidly varying background [...]\n *\n * The baseline is the trace one gets by rolling a ball below a spectrum. Algorithm has three steps:\n * Finding the minima in each window, find maxima among minima and then smooth over them by averaging.\n *\n * Algorithm described in (1), but in the implementation here the window width does not change.\n *\n * Reference:\n * (1) Kneen, M. A.; Annegarn, H. J.\n *     Algorithm for Fitting XRF, SEM and PIXE X-Ray Spectra Backgrounds.\n *     Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 1996, 109–110, 209–213.\n *     https://doi.org/10.1016/0168-583X(95)00908-6.\n * (2) Kristian Hovde Liland, Bjørn-Helge Mevik, Roberto Canteri: baseline.\n *     https://cran.r-project.org/web/packages/baseline/index.html\n *\n * @export\n * @param {Array<number>} ys\n * @param {Object} [options={}]\n * @param {Number} [options.windowM] - width of local window for minimization/maximization, defaults to 4% of the spectrum length\n * @param {Number} [options.windowS] - width of local window for smoothing, defaults to 8% of the specturm length\n * @returns {BaselineOutput}\n */\nexport function rollingBallBaseline(ys, options = {}) {\n  const baseline = rollingBall(ys, options);\n  let corrected = new Float64Array(ys.length);\n  for (let i = 0; i < corrected.length; i++) {\n    corrected[i] = ys[i] - baseline[i];\n  }\n\n  return { baseline, correctedSpectrum: corrected };\n}\n","//@ts-expect-error no type definition for baselines\nimport { rollingMedianBaseline as baselineFct } from 'baselines';\n/**\n * @param data\n */\nexport function rollingMedianBaseline(data) {\n    data.y = baselineFct(data.y).correctedSpectrum;\n    return { data };\n}\n//# sourceMappingURL=rollingMedianBaseline.js.map","import { xRollingMedian } from 'ml-spectra-processing';\n\n/**\n\n *\n * @export\n * @param {Array<number>} ys\n * @param {Object} [options={}]\n * @param {number} [options.window] rolling window size, defaults to 10% of the length of the spectrum\n * @param {string} [options.padding.size=window-1] none, value, circular, duplicate\n * @param {string} [options.padding.algorithm='duplicate'] none, value, circular, duplicate\n * @param {number} [options.padding.value=0] value to use for padding (if algorithm='value')\n * @returns {BaselineOutput}\n */\nexport function rollingMedianBaseline(ys, options = {}) {\n  let window = Math.max(Math.round(ys.length * 0.1), 2);\n  let defaults = {\n    window,\n    padding: {\n      size: window - 1,\n      algorithm: 'duplicate',\n      value: 0,\n    },\n  };\n  let actualOptions = { ...defaults, ...options };\n  let baseline = xRollingMedian(ys, actualOptions);\n  let corrected = new Float64Array(ys.length);\n  for (let i = 0; i < corrected.length; i++) {\n    corrected[i] = ys[i] - baseline[i];\n  }\n\n  return { baseline, correctedSpectrum: corrected };\n}\n","import { sgg } from 'ml-savitzky-golay-generalized';\n/**\n * Calculate the first derivative using Savitzky–Golay filter.\n * @param data\n */\nexport function firstDerivative(data, options = {}) {\n    const { x, y } = data;\n    return { data: { x, y: sgg(y, x, { ...options, derivative: 1 }) } };\n}\n//# sourceMappingURL=firstDerivative.js.map","import { sgg } from 'ml-savitzky-golay-generalized';\n/**\n * Calculate the second derivative using Savitzky–Golay filter.\n * @param data\n */\nexport function secondDerivative(data, options = {}) {\n    const { x, y } = data;\n    return { data: { x, y: sgg(y, x, { ...options, derivative: 2 }) } };\n}\n//# sourceMappingURL=secondDerivative.js.map","import { sgg } from 'ml-savitzky-golay-generalized';\n/**\n * Calculate the third derivative using Savitzky–Golay filter.\n * @param data\n */\nexport function thirdDerivative(data, options = {}) {\n    const { x, y } = data;\n    return { data: { x, y: sgg(y, x, { ...options, derivative: 3 }) } };\n}\n//# sourceMappingURL=thirdDerivative.js.map","import { sgg } from 'ml-savitzky-golay-generalized';\n/**\n * Apply the Savitzky Golay Generalized Filter\n * @param data\n */\nexport function savitzkyGolay(data, options = {}) {\n    const { x, y } = data;\n    return { data: { x, y: sgg(y, x, options) } };\n}\n//# sourceMappingURL=savitzkyGolay.js.map","import { xyEnsureGrowingX } from 'ml-spectra-processing';\n/**\n * Ensure X values are strictly monotonic increasing\n * http://www-groups.mcs.st-andrews.ac.uk/~john/analysis/Lectures/L8.html\n * @param data\n */\nexport function ensureGrowing(data) {\n    return { data: xyEnsureGrowingX(data) };\n}\n//# sourceMappingURL=ensureGrowing.js.map","import { xyEquallySpaced } from 'ml-spectra-processing';\n/**\n * Filter that allows to\n * @param data\n * @param options\n */\nexport function equallySpaced(data, options = {}) {\n    return { data: xyEquallySpaced(data, options) };\n}\n//# sourceMappingURL=equallySpaced.js.map","import { xyFilterX } from 'ml-spectra-processing';\n/**\n * Filter that allows to\n * @param data\n * @param options\n */\nexport function filterX(data, options = {}) {\n    return {\n        data: xyFilterX(data, options),\n    };\n}\n//# sourceMappingURL=filterX.js.map","import { gsd } from 'ml-gsd';\nimport { xFindClosestIndex, xMean, xAdd } from 'ml-spectra-processing';\n/**\n * Filter that allows to calibrateX the x axis based on the presence of peaks\n */\nexport function calibrateX(data, options = {}) {\n    const { targetX = 0, nbPeaks = 1, from = data.x[0], to = data.x[data.x.length - 1], gsd: gsdOptions = {\n        minMaxRatio: 0.1,\n        realTopDetection: true,\n        smoothY: true,\n        sgOptions: {\n            windowSize: 7,\n            polynomial: 3,\n        },\n    }, } = options;\n    const fromIndex = xFindClosestIndex(data.x, from);\n    const toIndex = xFindClosestIndex(data.x, to);\n    let peaks = gsd({\n        x: data.x.subarray(fromIndex, toIndex),\n        y: data.y.subarray(fromIndex, toIndex),\n    }, gsdOptions)\n        .sort((a, b) => b.y - a.y)\n        .slice(0, nbPeaks);\n    if (peaks.length === 0)\n        return { data };\n    const middle = xMean(peaks.map((peak) => peak.x));\n    return { data: { x: xAdd(data.x, targetX - middle), y: data.y } };\n}\n//# sourceMappingURL=calibrateX.js.map","import { xApplyFunctionStr } from 'ml-spectra-processing';\n/**\n * Filter that allows to\n * @param data\n * @param options\n */\nexport function xFunction(data, options = {}) {\n    return {\n        data: {\n            x: xApplyFunctionStr(data.x, {\n                variableLabel: 'x',\n                fctString: options.function,\n            }),\n            y: data.y,\n        },\n    };\n}\n//# sourceMappingURL=xFunction.js.map","import { xApplyFunctionStr } from 'ml-spectra-processing';\n/**\n * Filter that allows to\n * @param data\n * @param options\n */\nexport function yFunction(data, options = {}) {\n    return {\n        data: {\n            x: data.x,\n            y: xApplyFunctionStr(data.y, {\n                variableLabel: 'y',\n                fctString: options.function,\n            }),\n        },\n    };\n}\n//# sourceMappingURL=yFunction.js.map","import { xEnsureFloat64 } from 'ml-spectra-processing';\nimport * as Filters from './filters/filters';\n/**\n * Apply filters on {x:[], y:[]}\n * @returns A very important number\n */\nexport function filterXY(data, filters) {\n    let result = {\n        data: { x: xEnsureFloat64(data.x), y: xEnsureFloat64(data.y) },\n    };\n    const logs = [];\n    for (let filter of filters) {\n        const start = Date.now();\n        // eslint-disable-next-line import/namespace\n        const filterFct = Filters[filter.name];\n        if (!filterFct) {\n            throw new Error(`Unknown filter: ${filter.name}`);\n        }\n        // @ts-expect-error some method have options and some other ones don't have any options\n        result = filterFct(result.data, filter.options);\n        logs.push({\n            name: filter.name,\n            time: Date.now() - start,\n        });\n    }\n    return { logs, data: result.data };\n}\n//# sourceMappingURL=filterXY.js.map","import { filterXY } from 'ml-signal-processing';\nimport { xIsMonotone, xMinValue, xMaxValue } from 'ml-spectra-processing';\nexport function getNormalizedSpectrum(spectrum, options = {}) {\n    var _a;\n    let data = {\n        x: spectrum.variables.x.data,\n        y: spectrum.variables.y.data,\n    };\n    let newSpectrum = {\n        variables: {\n            x: {\n                data: spectrum.variables.x.data,\n                units: spectrum.variables.x.units,\n                label: spectrum.variables.x.label,\n            },\n            y: {\n                data: spectrum.variables.y.data,\n                units: spectrum.variables.y.units,\n                label: spectrum.variables.y.label,\n            },\n        },\n    };\n    if (spectrum.title)\n        newSpectrum.title = spectrum.title;\n    if (spectrum.dataType)\n        newSpectrum.dataType = spectrum.dataType;\n    if (spectrum.meta)\n        newSpectrum.meta = spectrum.meta;\n    if (spectrum.id)\n        newSpectrum.id = spectrum.id;\n    let { from = spectrum.variables.x.min, to = spectrum.variables.x.max, numberOfPoints, filters = [], exclusions = [], zones = [], } = options;\n    filters = JSON.parse(JSON.stringify(filters));\n    if (numberOfPoints) {\n        filters.push({\n            name: 'equallySpaced',\n            options: { from, to, exclusions, zones, numberOfPoints },\n        });\n    }\n    else {\n        filters.push({\n            name: 'filterX',\n            options: { from, to, exclusions, zones },\n        });\n    }\n    let { x, y } = filterXY(data, filters).data;\n    // filters change the y axis, we get rid of the units\n    // TODO we should deal correctly with this problem\n    if (filters.length > 1) {\n        newSpectrum.variables.y.units = '';\n        newSpectrum.variables.y.label = (_a = newSpectrum.variables.y.label) === null || _a === void 0 ? void 0 : _a.replace(/\\s*\\[.*\\]/, '');\n    }\n    newSpectrum.variables.x.data = x;\n    newSpectrum.variables.x.min = xMinValue(x);\n    newSpectrum.variables.x.max = xMaxValue(x);\n    newSpectrum.variables.x.isMonotone = xIsMonotone(x);\n    newSpectrum.variables.y.data = y;\n    newSpectrum.variables.y.min = xMinValue(y);\n    newSpectrum.variables.y.max = xMaxValue(y);\n    newSpectrum.variables.y.isMonotone = xIsMonotone(y);\n    return newSpectrum;\n}\n//# 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MIT License (MIT)\nCopyright © 2006-2007 Kevin C. Olbrich\nCopyright © 2010-2016 LIM SAS (http://lim.eu) - Julien Sanchez\n\nPermission is hereby granted, free of charge, to any person obtaining a copy of\nthis software and associated documentation files (the \"Software\"), to deal in\nthe Software without restriction, including without limitation the rights to\nuse, copy, modify, merge, publish, distribute, sublicense, and/or sell copies\nof the Software, and to permit persons to whom the Software is furnished to do\nso, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n*/\n(function (global, factory) {\n  typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() :\n  typeof define === 'function' && define.amd ? define(factory) :\n  (global = typeof globalThis !== 'undefined' ? globalThis : global || self, global.Qty = factory());\n}(this, (function () { 'use strict';\n\n  /**\n   * Tests if a value is a string\n   *\n   * @param {*} value - Value to test\n   *\n   * @returns {boolean} true if value is a string, false otherwise\n   */\n  function isString(value) {\n    return typeof value === \"string\" || value instanceof String;\n  }\n\n  /*\n   * Prefer stricter Number.isFinite if currently supported.\n   * To be dropped when ES6 is finalized. Obsolete browsers will\n   * have to use ES6 polyfills.\n   */\n  var isFiniteImpl = Number.isFinite || window.isFinite;\n  /**\n   * Tests if a value is a number\n   *\n   * @param {*} value - Value to test\n   *\n   * @returns {boolean} true if value is a number, false otherwise\n   */\n  function isNumber(value) {\n    // Number.isFinite allows not to consider NaN or '1' as numbers\n    return isFiniteImpl(value);\n  }\n\n  /*\n   * Identity function\n   */\n  function identity(value) {\n    return value;\n  }\n\n  /**\n   * Returns unique strings from list\n   *\n   * @param {string[]} strings - array of strings\n   *\n   *\n   * @returns {string[]} a new array of strings without duplicates\n   */\n  function uniq(strings) {\n    var seen = {};\n    return strings.filter(function(item) {\n      return seen.hasOwnProperty(item) ? false : (seen[item] = true);\n    });\n  }\n\n  function compareArray(array1, array2) {\n    if (array2.length !== array1.length) {\n      return false;\n    }\n    for (var i = 0; i < array1.length; i++) {\n      if (array2[i].compareArray) {\n        if (!array2[i].compareArray(array1[i])) {\n          return false;\n        }\n      }\n      if (array2[i] !== array1[i]) {\n        return false;\n      }\n    }\n    return true;\n  }\n\n  function assign(target, properties) {\n    Object.keys(properties).forEach(function(key) {\n      target[key] = properties[key];\n    });\n  }\n\n  /**\n   * Safely multiplies numbers while avoiding floating errors\n   * like 0.1 * 0.1 => 0.010000000000000002\n   *\n   * @param {...number} numbers - numbers to multiply\n   *\n   * @returns {number} result\n   */\n  function mulSafe() {\n    var result = 1, decimals = 0;\n    for (var i = 0; i < arguments.length; i++) {\n      var arg = arguments[i];\n      decimals = decimals + getFractional(arg);\n      result *= arg;\n    }\n\n    return decimals !== 0 ? round(result, decimals) : result;\n  }\n\n  /**\n   * Safely divides two numbers while avoiding floating errors\n   * like 0.3 / 0.05 => 5.999999999999999\n   *\n   * @returns {number} result\n   * @param {number} num Numerator\n   * @param {number} den Denominator\n   */\n  function divSafe(num, den) {\n    if (den === 0) {\n      throw new Error(\"Divide by zero\");\n    }\n\n    var factor = Math.pow(10, getFractional(den));\n    var invDen = factor / (factor * den);\n\n    return mulSafe(num, invDen);\n  }\n\n  /**\n   * Rounds value at the specified number of decimals\n   *\n   * @param {number} val - value to round\n   * @param {number} decimals - number of decimals\n   *\n   * @returns {number} rounded number\n   */\n  function round(val, decimals) {\n    return Math.round(val * Math.pow(10, decimals)) / Math.pow(10, decimals);\n  }\n\n  function getFractional(num) {\n    // Check for NaNs or Infinities\n    if (!isFinite(num)) {\n      return 0;\n    }\n\n    // Faster than parsing strings\n    // http://jsperf.com/count-decimals/2\n    var count = 0;\n    while (num % 1 !== 0) {\n      num *= 10;\n      count++;\n    }\n    return count;\n  }\n\n  /**\n   * Custom error type definition\n   * @constructor\n   */\n  function QtyError() {\n    var err;\n    if (!this) { // Allows to instantiate QtyError without new()\n      err = Object.create(QtyError.prototype);\n      QtyError.apply(err, arguments);\n      return err;\n    }\n    err = Error.apply(this, arguments);\n    this.name = \"QtyError\";\n    this.message = err.message;\n    this.stack = err.stack;\n  }\n  QtyError.prototype = Object.create(Error.prototype, {constructor: { value: QtyError }});\n\n  /*\n   * Throws incompatible units error\n   * @param {string} left - units\n   * @param {string} right - units incompatible with first argument\n   * @throws \"Incompatible units\" error\n   */\n  function throwIncompatibleUnits(left, right) {\n    throw new QtyError(\"Incompatible units: \" + left + \" and \" + right);\n  }\n\n  var UNITS = {\n    /* prefixes */\n    \"<googol>\" : [[\"googol\"], 1e100, \"prefix\"],\n    \"<kibi>\"  :  [[\"Ki\",\"Kibi\",\"kibi\"], Math.pow(2,10), \"prefix\"],\n    \"<mebi>\"  :  [[\"Mi\",\"Mebi\",\"mebi\"], Math.pow(2,20), \"prefix\"],\n    \"<gibi>\"  :  [[\"Gi\",\"Gibi\",\"gibi\"], Math.pow(2,30), \"prefix\"],\n    \"<tebi>\"  :  [[\"Ti\",\"Tebi\",\"tebi\"], Math.pow(2,40), \"prefix\"],\n    \"<pebi>\"  :  [[\"Pi\",\"Pebi\",\"pebi\"], Math.pow(2,50), \"prefix\"],\n    \"<exi>\"   :  [[\"Ei\",\"Exi\",\"exi\"], Math.pow(2,60), \"prefix\"],\n    \"<zebi>\"  :  [[\"Zi\",\"Zebi\",\"zebi\"], Math.pow(2,70), \"prefix\"],\n    \"<yebi>\"  :  [[\"Yi\",\"Yebi\",\"yebi\"], Math.pow(2,80), \"prefix\"],\n    \"<yotta>\" :  [[\"Y\",\"Yotta\",\"yotta\"], 1e24, \"prefix\"],\n    \"<zetta>\" :  [[\"Z\",\"Zetta\",\"zetta\"], 1e21, \"prefix\"],\n    \"<exa>\"   :  [[\"E\",\"Exa\",\"exa\"], 1e18, \"prefix\"],\n    \"<peta>\"  :  [[\"P\",\"Peta\",\"peta\"], 1e15, \"prefix\"],\n    \"<tera>\"  :  [[\"T\",\"Tera\",\"tera\"], 1e12, \"prefix\"],\n    \"<giga>\"  :  [[\"G\",\"Giga\",\"giga\"], 1e9, \"prefix\"],\n    \"<mega>\"  :  [[\"M\",\"Mega\",\"mega\"], 1e6, \"prefix\"],\n    \"<kilo>\"  :  [[\"k\",\"kilo\"], 1e3, \"prefix\"],\n    \"<hecto>\" :  [[\"h\",\"Hecto\",\"hecto\"], 1e2, \"prefix\"],\n    \"<deca>\"  :  [[\"da\",\"Deca\",\"deca\",\"deka\"], 1e1, \"prefix\"],\n    \"<deci>\"  :  [[\"d\",\"Deci\",\"deci\"], 1e-1, \"prefix\"],\n    \"<centi>\"  : [[\"c\",\"Centi\",\"centi\"], 1e-2, \"prefix\"],\n    \"<milli>\" :  [[\"m\",\"Milli\",\"milli\"], 1e-3, \"prefix\"],\n    \"<micro>\"  : [\n      [\"u\",\"\\u03BC\"/*µ as greek letter*/,\"\\u00B5\"/*µ as micro sign*/,\"Micro\",\"mc\",\"micro\"],\n      1e-6,\n      \"prefix\"\n    ],\n    \"<nano>\"  :  [[\"n\",\"Nano\",\"nano\"], 1e-9, \"prefix\"],\n    \"<pico>\"  :  [[\"p\",\"Pico\",\"pico\"], 1e-12, \"prefix\"],\n    \"<femto>\" :  [[\"f\",\"Femto\",\"femto\"], 1e-15, \"prefix\"],\n    \"<atto>\"  :  [[\"a\",\"Atto\",\"atto\"], 1e-18, \"prefix\"],\n    \"<zepto>\" :  [[\"z\",\"Zepto\",\"zepto\"], 1e-21, \"prefix\"],\n    \"<yocto>\" :  [[\"y\",\"Yocto\",\"yocto\"], 1e-24, \"prefix\"],\n\n    \"<1>\"     :  [[\"1\", \"<1>\"], 1, \"\"],\n    /* length units */\n    \"<meter>\" :  [[\"m\",\"meter\",\"meters\",\"metre\",\"metres\"], 1.0, \"length\", [\"<meter>\"] ],\n    \"<inch>\"  :  [[\"in\",\"inch\",\"inches\",\"\\\"\"], 0.0254, \"length\", [\"<meter>\"]],\n    \"<foot>\"  :  [[\"ft\",\"foot\",\"feet\",\"'\"], 0.3048, \"length\", [\"<meter>\"]],\n    \"<yard>\"  :  [[\"yd\",\"yard\",\"yards\"], 0.9144, \"length\", [\"<meter>\"]],\n    \"<mile>\"  :  [[\"mi\",\"mile\",\"miles\"], 1609.344, \"length\", [\"<meter>\"]],\n    \"<naut-mile>\" : [[\"nmi\",\"naut-mile\"], 1852, \"length\", [\"<meter>\"]],\n    \"<league>\":  [[\"league\",\"leagues\"], 4828, \"length\", [\"<meter>\"]],\n    \"<furlong>\": [[\"furlong\",\"furlongs\"], 201.2, \"length\", [\"<meter>\"]],\n    \"<rod>\"   :  [[\"rd\",\"rod\",\"rods\"], 5.029, \"length\", [\"<meter>\"]],\n    \"<mil>\"   :  [[\"mil\",\"mils\"], 0.0000254, \"length\", [\"<meter>\"]],\n    \"<angstrom>\"  :[[\"ang\",\"angstrom\",\"angstroms\"], 1e-10, \"length\", [\"<meter>\"]],\n    \"<fathom>\" : [[\"fathom\",\"fathoms\"], 1.829, \"length\", [\"<meter>\"]],\n    \"<pica>\"  : [[\"pica\",\"picas\"], 0.00423333333, \"length\", [\"<meter>\"]],\n    \"<point>\" : [[\"pt\",\"point\",\"points\"], 0.000352777778, \"length\", [\"<meter>\"]],\n    \"<redshift>\" : [[\"z\",\"red-shift\", \"redshift\"], 1.302773e26, \"length\", [\"<meter>\"]],\n    \"<AU>\"    : [[\"AU\",\"astronomical-unit\"], 149597900000, \"length\", [\"<meter>\"]],\n    \"<light-second>\":[[\"ls\",\"light-second\"], 299792500, \"length\", [\"<meter>\"]],\n    \"<light-minute>\":[[\"lmin\",\"light-minute\"], 17987550000, \"length\", [\"<meter>\"]],\n    \"<light-year>\" : [[\"ly\",\"light-year\"], 9460528000000000, \"length\", [\"<meter>\"]],\n    \"<parsec>\"  : [[\"pc\",\"parsec\",\"parsecs\"], 30856780000000000, \"length\", [\"<meter>\"]],\n    \"<datamile>\"  :  [[\"DM\",\"datamile\"], 1828.8, \"length\", [\"<meter>\"]],\n\n    /* mass */\n    \"<kilogram>\" : [[\"kg\",\"kilogram\",\"kilograms\"], 1.0, \"mass\", [\"<kilogram>\"]],\n    \"<AMU>\" : [[\"u\",\"AMU\",\"amu\"], 1.660538921e-27, \"mass\", [\"<kilogram>\"]],\n    \"<dalton>\" : [[\"Da\",\"Dalton\",\"Daltons\",\"dalton\",\"daltons\"], 1.660538921e-27, \"mass\", [\"<kilogram>\"]],\n    \"<slug>\" : [[\"slug\",\"slugs\"], 14.5939029, \"mass\", [\"<kilogram>\"]],\n    \"<short-ton>\" : [[\"tn\",\"ton\",\"short-ton\"], 907.18474, \"mass\", [\"<kilogram>\"]],\n    \"<metric-ton>\":[[\"tonne\",\"metric-ton\"], 1000, \"mass\", [\"<kilogram>\"]],\n    \"<carat>\" : [[\"ct\",\"carat\",\"carats\"], 0.0002, \"mass\", [\"<kilogram>\"]],\n    \"<pound>\" : [[\"lbs\",\"lb\",\"pound\",\"pounds\",\"#\"], 0.45359237, \"mass\", [\"<kilogram>\"]],\n    \"<ounce>\" : [[\"oz\",\"ounce\",\"ounces\"], 0.0283495231, \"mass\", [\"<kilogram>\"]],\n    \"<gram>\"    :  [[\"g\",\"gram\",\"grams\",\"gramme\",\"grammes\"], 1e-3, \"mass\", [\"<kilogram>\"]],\n    \"<grain>\" : [[\"grain\",\"grains\",\"gr\"], 6.479891e-5, \"mass\", [\"<kilogram>\"]],\n    \"<dram>\"  : [[\"dram\",\"drams\",\"dr\"], 0.0017718452, \"mass\",[\"<kilogram>\"]],\n    \"<stone>\" : [[\"stone\",\"stones\",\"st\"],6.35029318, \"mass\",[\"<kilogram>\"]],\n\n    /* area */\n    \"<hectare>\":[[\"hectare\"], 10000, \"area\", [\"<meter>\",\"<meter>\"]],\n    \"<acre>\":[[\"acre\",\"acres\"], 4046.85642, \"area\", [\"<meter>\",\"<meter>\"]],\n    \"<sqft>\":[[\"sqft\"], 1, \"area\", [\"<foot>\",\"<foot>\"]],\n\n    /* volume */\n    \"<liter>\" : [[\"l\",\"L\",\"liter\",\"liters\",\"litre\",\"litres\"], 0.001, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<gallon>\":  [[\"gal\",\"gallon\",\"gallons\"], 0.0037854118, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<gallon-imp>\":  [[\"galimp\",\"gallon-imp\",\"gallons-imp\"], 0.0045460900, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<quart>\":  [[\"qt\",\"quart\",\"quarts\"], 0.00094635295, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<pint>\":  [[\"pt\",\"pint\",\"pints\"], 0.000473176475, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<pint-imp>\":  [[\"ptimp\",\"pint-imp\",\"pints-imp\"], 5.6826125e-4, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<cup>\":  [[\"cu\",\"cup\",\"cups\"], 0.000236588238, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<fluid-ounce>\":  [[\"floz\",\"fluid-ounce\",\"fluid-ounces\"], 2.95735297e-5, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<fluid-ounce-imp>\":  [[\"flozimp\", \"floz-imp\",\"fluid-ounce-imp\",\"fluid-ounces-imp\"], 2.84130625e-5, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<tablespoon>\":  [[\"tb\",\"tbsp\",\"tbs\",\"tablespoon\",\"tablespoons\"], 1.47867648e-5, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<teaspoon>\":  [[\"tsp\",\"teaspoon\",\"teaspoons\"], 4.92892161e-6, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<bushel>\":  [[\"bu\",\"bsh\",\"bushel\",\"bushels\"], 0.035239072, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<oilbarrel>\":  [[\"bbl\",\"oilbarrel\", \"oilbarrels\", \"oil-barrel\",\"oil-barrels\"], 0.158987294928, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<beerbarrel>\":  [[\"bl\",\"bl-us\",\"beerbarrel\", \"beerbarrels\", \"beer-barrel\",\"beer-barrels\"], 0.1173477658, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<beerbarrel-imp>\":  [[\"blimp\",\"bl-imp\",\"beerbarrel-imp\", \"beerbarrels-imp\", \"beer-barrel-imp\",\"beer-barrels-imp\"], 0.16365924, \"volume\", [\"<meter>\",\"<meter>\",\"<meter>\"]],\n\n    /* speed */\n    \"<kph>\" : [[\"kph\"], 0.277777778, \"speed\", [\"<meter>\"], [\"<second>\"]],\n    \"<mph>\" : [[\"mph\"], 0.44704, \"speed\", [\"<meter>\"], [\"<second>\"]],\n    \"<knot>\" : [[\"kt\",\"kn\",\"kts\",\"knot\",\"knots\"], 0.514444444, \"speed\", [\"<meter>\"], [\"<second>\"]],\n    \"<fps>\"  : [[\"fps\"], 0.3048, \"speed\", [\"<meter>\"], [\"<second>\"]],\n\n    /* acceleration */\n    \"<gee>\" : [[\"gee\"], 9.80665, \"acceleration\", [\"<meter>\"], [\"<second>\",\"<second>\"]],\n    \"<Gal>\" : [[\"Gal\"], 1e-2, \"acceleration\", [\"<meter>\"], [\"<second>\",\"<second>\"]],\n\n    /* temperature_difference */\n    \"<kelvin>\" : [[\"degK\",\"kelvin\"], 1.0, \"temperature\", [\"<kelvin>\"]],\n    \"<celsius>\" : [[\"degC\",\"celsius\",\"celsius\",\"centigrade\"], 1.0, \"temperature\", [\"<kelvin>\"]],\n    \"<fahrenheit>\" : [[\"degF\",\"fahrenheit\"], 5 / 9, \"temperature\", [\"<kelvin>\"]],\n    \"<rankine>\" : [[\"degR\",\"rankine\"], 5 / 9, \"temperature\", [\"<kelvin>\"]],\n    \"<temp-K>\"  : [[\"tempK\",\"temp-K\"], 1.0, \"temperature\", [\"<temp-K>\"]],\n    \"<temp-C>\"  : [[\"tempC\",\"temp-C\"], 1.0, \"temperature\", [\"<temp-K>\"]],\n    \"<temp-F>\"  : [[\"tempF\",\"temp-F\"], 5 / 9, \"temperature\", [\"<temp-K>\"]],\n    \"<temp-R>\"  : [[\"tempR\",\"temp-R\"], 5 / 9, \"temperature\", [\"<temp-K>\"]],\n\n    /* time */\n    \"<second>\":  [[\"s\",\"sec\",\"secs\",\"second\",\"seconds\"], 1.0, \"time\", [\"<second>\"]],\n    \"<minute>\":  [[\"min\",\"mins\",\"minute\",\"minutes\"], 60.0, \"time\", [\"<second>\"]],\n    \"<hour>\":  [[\"h\",\"hr\",\"hrs\",\"hour\",\"hours\"], 3600.0, \"time\", [\"<second>\"]],\n    \"<day>\":  [[\"d\",\"day\",\"days\"], 3600 * 24, \"time\", [\"<second>\"]],\n    \"<week>\":  [[\"wk\",\"week\",\"weeks\"], 7 * 3600 * 24, \"time\", [\"<second>\"]],\n    \"<fortnight>\": [[\"fortnight\",\"fortnights\"], 1209600, \"time\", [\"<second>\"]],\n    \"<year>\":  [[\"y\",\"yr\",\"year\",\"years\",\"annum\"], 31556926, \"time\", [\"<second>\"]],\n    \"<decade>\":[[\"decade\",\"decades\"], 315569260, \"time\", [\"<second>\"]],\n    \"<century>\":[[\"century\",\"centuries\"], 3155692600, \"time\", [\"<second>\"]],\n\n    /* pressure */\n    \"<pascal>\" : [[\"Pa\",\"pascal\",\"Pascal\"], 1.0, \"pressure\", [\"<kilogram>\"],[\"<meter>\",\"<second>\",\"<second>\"]],\n    \"<bar>\" : [[\"bar\",\"bars\"], 100000, \"pressure\", [\"<kilogram>\"],[\"<meter>\",\"<second>\",\"<second>\"]],\n    \"<mmHg>\" : [[\"mmHg\"], 133.322368, \"pressure\", [\"<kilogram>\"],[\"<meter>\",\"<second>\",\"<second>\"]],\n    \"<inHg>\" : [[\"inHg\"], 3386.3881472, \"pressure\", [\"<kilogram>\"],[\"<meter>\",\"<second>\",\"<second>\"]],\n    \"<torr>\" : [[\"torr\"], 133.322368, \"pressure\", [\"<kilogram>\"],[\"<meter>\",\"<second>\",\"<second>\"]],\n    \"<atm>\" : [[\"atm\",\"ATM\",\"atmosphere\",\"atmospheres\"], 101325, \"pressure\", [\"<kilogram>\"],[\"<meter>\",\"<second>\",\"<second>\"]],\n    \"<psi>\" : [[\"psi\"], 6894.76, \"pressure\", [\"<kilogram>\"],[\"<meter>\",\"<second>\",\"<second>\"]],\n    \"<cmh2o>\" : [[\"cmH2O\",\"cmh2o\"], 98.0638, \"pressure\", [\"<kilogram>\"],[\"<meter>\",\"<second>\",\"<second>\"]],\n    \"<inh2o>\" : [[\"inH2O\",\"inh2o\"], 249.082052, \"pressure\", [\"<kilogram>\"],[\"<meter>\",\"<second>\",\"<second>\"]],\n\n    /* viscosity */\n    \"<poise>\"  : [[\"P\",\"poise\"], 0.1, \"viscosity\", [\"<kilogram>\"],[\"<meter>\",\"<second>\"] ],\n    \"<stokes>\" : [[\"St\",\"stokes\"], 1e-4, \"viscosity\", [\"<meter>\",\"<meter>\"], [\"<second>\"]],\n\n    /* substance */\n    \"<mole>\"  :  [[\"mol\",\"mole\"], 1.0, \"substance\", [\"<mole>\"]],\n\n    /* concentration */\n    \"<molar>\" : [[\"M\",\"molar\"], 1000, \"concentration\", [\"<mole>\"], [\"<meter>\",\"<meter>\",\"<meter>\"]],\n    \"<wtpercent>\"  : [[\"wt%\",\"wtpercent\"], 10, \"concentration\", [\"<kilogram>\"], [\"<meter>\",\"<meter>\",\"<meter>\"]],\n\n    /* activity */\n    \"<katal>\" :  [[\"kat\",\"katal\",\"Katal\"], 1.0, \"activity\", [\"<mole>\"], [\"<second>\"]],\n    \"<unit>\"  :  [[\"U\",\"enzUnit\",\"unit\"], 16.667e-16, \"activity\", [\"<mole>\"], [\"<second>\"]],\n\n    /* capacitance */\n    \"<farad>\" :  [[\"F\",\"farad\",\"Farad\"], 1.0, \"capacitance\", [\"<second>\",\"<second>\",\"<second>\",\"<second>\",\"<ampere>\",\"<ampere>\"], [\"<meter>\", \"<meter>\", \"<kilogram>\"]],\n\n    /* charge */\n    \"<coulomb>\" :  [[\"C\",\"coulomb\",\"Coulomb\"], 1.0, \"charge\", [\"<ampere>\",\"<second>\"]],\n    \"<Ah>\" :  [[\"Ah\"], 3600, \"charge\", [\"<ampere>\",\"<second>\"]],\n\n    /* current */\n    \"<ampere>\"  :  [[\"A\",\"Ampere\",\"ampere\",\"amp\",\"amps\"], 1.0, \"current\", [\"<ampere>\"]],\n\n    /* conductance */\n    \"<siemens>\" : [[\"S\",\"Siemens\",\"siemens\"], 1.0, \"conductance\", [\"<second>\",\"<second>\",\"<second>\",\"<ampere>\",\"<ampere>\"], [\"<kilogram>\",\"<meter>\",\"<meter>\"]],\n\n    /* inductance */\n    \"<henry>\" :  [[\"H\",\"Henry\",\"henry\"], 1.0, \"inductance\", [\"<meter>\",\"<meter>\",\"<kilogram>\"], [\"<second>\",\"<second>\",\"<ampere>\",\"<ampere>\"]],\n\n    /* potential */\n    \"<volt>\"  :  [[\"V\",\"Volt\",\"volt\",\"volts\"], 1.0, \"potential\", [\"<meter>\",\"<meter>\",\"<kilogram>\"], [\"<second>\",\"<second>\",\"<second>\",\"<ampere>\"]],\n\n    /* resistance */\n    \"<ohm>\" :  [\n      [\"Ohm\",\"ohm\",\"\\u03A9\"/*Ω as greek letter*/,\"\\u2126\"/*Ω as ohm sign*/],\n      1.0,\n      \"resistance\",\n      [\"<meter>\",\"<meter>\",\"<kilogram>\"],[\"<second>\",\"<second>\",\"<second>\",\"<ampere>\",\"<ampere>\"]\n    ],\n    /* magnetism */\n    \"<weber>\" : [[\"Wb\",\"weber\",\"webers\"], 1.0, \"magnetism\", [\"<meter>\",\"<meter>\",\"<kilogram>\"], [\"<second>\",\"<second>\",\"<ampere>\"]],\n    \"<tesla>\"  : [[\"T\",\"tesla\",\"teslas\"], 1.0, \"magnetism\", [\"<kilogram>\"], [\"<second>\",\"<second>\",\"<ampere>\"]],\n    \"<gauss>\" : [[\"G\",\"gauss\"], 1e-4, \"magnetism\",  [\"<kilogram>\"], [\"<second>\",\"<second>\",\"<ampere>\"]],\n    \"<maxwell>\" : [[\"Mx\",\"maxwell\",\"maxwells\"], 1e-8, \"magnetism\", [\"<meter>\",\"<meter>\",\"<kilogram>\"], [\"<second>\",\"<second>\",\"<ampere>\"]],\n    \"<oersted>\"  : [[\"Oe\",\"oersted\",\"oersteds\"], 250.0 / Math.PI, \"magnetism\", [\"<ampere>\"], [\"<meter>\"]],\n\n    /* energy */\n    \"<joule>\" :  [[\"J\",\"joule\",\"Joule\",\"joules\"], 1.0, \"energy\", [\"<meter>\",\"<meter>\",\"<kilogram>\"], [\"<second>\",\"<second>\"]],\n    \"<erg>\"   :  [[\"erg\",\"ergs\"], 1e-7, \"energy\", [\"<meter>\",\"<meter>\",\"<kilogram>\"], [\"<second>\",\"<second>\"]],\n    \"<btu>\"   :  [[\"BTU\",\"btu\",\"BTUs\"], 1055.056, \"energy\", [\"<meter>\",\"<meter>\",\"<kilogram>\"], [\"<second>\",\"<second>\"]],\n    \"<calorie>\" :  [[\"cal\",\"calorie\",\"calories\"], 4.18400, \"energy\",[\"<meter>\",\"<meter>\",\"<kilogram>\"], [\"<second>\",\"<second>\"]],\n    \"<Calorie>\" :  [[\"Cal\",\"Calorie\",\"Calories\"], 4184.00, \"energy\",[\"<meter>\",\"<meter>\",\"<kilogram>\"], [\"<second>\",\"<second>\"]],\n    \"<therm-US>\" : [[\"th\",\"therm\",\"therms\",\"Therm\",\"therm-US\"], 105480400, \"energy\",[\"<meter>\",\"<meter>\",\"<kilogram>\"], [\"<second>\",\"<second>\"]],\n    \"<Wh>\" : [[\"Wh\"], 3600, \"energy\",[\"<meter>\",\"<meter>\",\"<kilogram>\"], [\"<second>\",\"<second>\"]],\n\n    /* force */\n    \"<newton>\"  : [[\"N\",\"Newton\",\"newton\"], 1.0, \"force\", [\"<kilogram>\",\"<meter>\"], [\"<second>\",\"<second>\"]],\n    \"<dyne>\"  : [[\"dyn\",\"dyne\"], 1e-5, \"force\", [\"<kilogram>\",\"<meter>\"], [\"<second>\",\"<second>\"]],\n    \"<pound-force>\"  : [[\"lbf\",\"pound-force\"], 4.448222, \"force\", [\"<kilogram>\",\"<meter>\"], [\"<second>\",\"<second>\"]],\n\n    /* frequency */\n    \"<hertz>\" : [[\"Hz\",\"hertz\",\"Hertz\"], 1.0, \"frequency\", [\"<1>\"], [\"<second>\"]],\n\n    /* angle */\n    \"<radian>\" :[[\"rad\",\"radian\",\"radians\"], 1.0, \"angle\", [\"<radian>\"]],\n    \"<degree>\" :[[\"deg\",\"degree\",\"degrees\"], Math.PI / 180.0, \"angle\", [\"<radian>\"]],\n    \"<gradian>\"   :[[\"gon\",\"grad\",\"gradian\",\"grads\"], Math.PI / 200.0, \"angle\", [\"<radian>\"]],\n    \"<steradian>\"  : [[\"sr\",\"steradian\",\"steradians\"], 1.0, \"solid_angle\", [\"<steradian>\"]],\n\n    /* rotation */\n    \"<rotation>\" : [[\"rotation\"], 2.0 * Math.PI, \"angle\", [\"<radian>\"]],\n    \"<rpm>\"   :[[\"rpm\"], 2.0 * Math.PI / 60.0, \"angular_velocity\", [\"<radian>\"], [\"<second>\"]],\n\n    /* information */\n    \"<byte>\"  :[[\"B\",\"byte\",\"bytes\"], 1.0, \"information\", [\"<byte>\"]],\n    \"<bit>\"  :[[\"b\",\"bit\",\"bits\"], 0.125, \"information\", [\"<byte>\"]],\n\n    /* information rate */\n    \"<Bps>\" : [[\"Bps\"], 1.0, \"information_rate\", [\"<byte>\"], [\"<second>\"]],\n    \"<bps>\" : [[\"bps\"], 0.125, \"information_rate\", [\"<byte>\"], [\"<second>\"]],\n\n    /* currency */\n    \"<dollar>\":[[\"USD\",\"dollar\"], 1.0, \"currency\", [\"<dollar>\"]],\n    \"<cents>\" :[[\"cents\"], 0.01, \"currency\", [\"<dollar>\"]],\n\n    /* luminosity */\n    \"<candela>\" : [[\"cd\",\"candela\"], 1.0, \"luminosity\", [\"<candela>\"]],\n    \"<lumen>\" : [[\"lm\",\"lumen\"], 1.0, \"luminous_power\", [\"<candela>\",\"<steradian>\"]],\n    \"<lux>\" :[[\"lux\"], 1.0, \"illuminance\", [\"<candela>\",\"<steradian>\"], [\"<meter>\",\"<meter>\"]],\n\n    /* power */\n    \"<watt>\"  : [[\"W\",\"watt\",\"watts\"], 1.0, \"power\", [\"<kilogram>\",\"<meter>\",\"<meter>\"], [\"<second>\",\"<second>\",\"<second>\"]],\n    \"<volt-ampere>\"  : [[\"VA\",\"volt-ampere\"], 1.0, \"power\", [\"<kilogram>\",\"<meter>\",\"<meter>\"], [\"<second>\",\"<second>\",\"<second>\"]],\n    \"<volt-ampere-reactive>\"  : [[\"var\",\"Var\",\"VAr\",\"VAR\",\"volt-ampere-reactive\"], 1.0, \"power\", [\"<kilogram>\",\"<meter>\",\"<meter>\"], [\"<second>\",\"<second>\",\"<second>\"]],\n    \"<horsepower>\"  :  [[\"hp\",\"horsepower\"], 745.699872, \"power\", [\"<kilogram>\",\"<meter>\",\"<meter>\"], [\"<second>\",\"<second>\",\"<second>\"]],\n\n    /* radiation */\n    \"<gray>\" : [[\"Gy\",\"gray\",\"grays\"], 1.0, \"radiation\", [\"<meter>\",\"<meter>\"], [\"<second>\",\"<second>\"]],\n    \"<roentgen>\" : [[\"R\",\"roentgen\"], 0.009330, \"radiation\", [\"<meter>\",\"<meter>\"], [\"<second>\",\"<second>\"]],\n    \"<sievert>\" : [[\"Sv\",\"sievert\",\"sieverts\"], 1.0, \"radiation\", [\"<meter>\",\"<meter>\"], [\"<second>\",\"<second>\"]],\n    \"<becquerel>\" : [[\"Bq\",\"becquerel\",\"becquerels\"], 1.0, \"radiation\", [\"<1>\"],[\"<second>\"]],\n    \"<curie>\" : [[\"Ci\",\"curie\",\"curies\"], 3.7e10, \"radiation\", [\"<1>\"],[\"<second>\"]],\n\n    /* rate */\n    \"<cpm>\" : [[\"cpm\"], 1.0 / 60.0, \"rate\", [\"<count>\"],[\"<second>\"]],\n    \"<dpm>\" : [[\"dpm\"], 1.0 / 60.0, \"rate\", [\"<count>\"],[\"<second>\"]],\n    \"<bpm>\" : [[\"bpm\"], 1.0 / 60.0, \"rate\", [\"<count>\"],[\"<second>\"]],\n\n    /* resolution / typography */\n    \"<dot>\" : [[\"dot\",\"dots\"], 1, \"resolution\", [\"<each>\"]],\n    \"<pixel>\" : [[\"pixel\",\"px\"], 1, \"resolution\", [\"<each>\"]],\n    \"<ppi>\" : [[\"ppi\"], 1, \"resolution\", [\"<pixel>\"], [\"<inch>\"]],\n    \"<dpi>\" : [[\"dpi\"], 1, \"typography\", [\"<dot>\"], [\"<inch>\"]],\n\n    /* other */\n    \"<cell>\" : [[\"cells\",\"cell\"], 1, \"counting\", [\"<each>\"]],\n    \"<each>\" : [[\"each\"], 1.0, \"counting\", [\"<each>\"]],\n    \"<count>\" : [[\"count\"], 1.0, \"counting\", [\"<each>\"]],\n    \"<base-pair>\"  : [[\"bp\",\"base-pair\"], 1.0, \"counting\", [\"<each>\"]],\n    \"<nucleotide>\" : [[\"nt\",\"nucleotide\"], 1.0, \"counting\", [\"<each>\"]],\n    \"<molecule>\" : [[\"molecule\",\"molecules\"], 1.0, \"counting\", [\"<1>\"]],\n    \"<dozen>\" :  [[\"doz\",\"dz\",\"dozen\"],12.0,\"prefix_only\", [\"<each>\"]],\n    \"<percent>\": [[\"%\",\"percent\"], 0.01, \"prefix_only\", [\"<1>\"]],\n    \"<ppm>\" :  [[\"ppm\"],1e-6, \"prefix_only\", [\"<1>\"]],\n    \"<ppt>\" :  [[\"ppt\"],1e-9, \"prefix_only\", [\"<1>\"]],\n    \"<gross>\" :  [[\"gr\",\"gross\"],144.0, \"prefix_only\", [\"<dozen>\",\"<dozen>\"]],\n    \"<decibel>\"  : [[\"dB\",\"decibel\",\"decibels\"], 1.0, \"logarithmic\", [\"<decibel>\"]]\n  };\n\n  var BASE_UNITS = [\"<meter>\",\"<kilogram>\",\"<second>\",\"<mole>\", \"<ampere>\",\"<radian>\",\"<kelvin>\",\"<temp-K>\",\"<byte>\",\"<dollar>\",\"<candela>\",\"<each>\",\"<steradian>\",\"<decibel>\"];\n\n  var UNITY = \"<1>\";\n  var UNITY_ARRAY = [UNITY];\n\n  // Setup\n\n  /**\n   * Asserts unit definition is valid\n   *\n   * @param {string} unitDef - Name of unit to test\n   * @param {Object} definition - Definition of unit to test\n   *\n   * @returns {void}\n   * @throws {QtyError} if unit definition is not valid\n   */\n  function validateUnitDefinition(unitDef, definition) {\n    var scalar = definition[1];\n    var numerator = definition[3] || [];\n    var denominator = definition[4] || [];\n    if (!isNumber(scalar)) {\n      throw new QtyError(unitDef + \": Invalid unit definition. \" +\n                         \"'scalar' must be a number\");\n    }\n\n    numerator.forEach(function(unit) {\n      if (UNITS[unit] === undefined) {\n        throw new QtyError(unitDef + \": Invalid unit definition. \" +\n                           \"Unit \" + unit + \" in 'numerator' is not recognized\");\n      }\n    });\n\n    denominator.forEach(function(unit) {\n      if (UNITS[unit] === undefined) {\n        throw new QtyError(unitDef + \": Invalid unit definition. \" +\n                           \"Unit \" + unit + \" in 'denominator' is not recognized\");\n      }\n    });\n  }\n\n  var PREFIX_VALUES = {};\n  var PREFIX_MAP = {};\n  var UNIT_VALUES = {};\n  var UNIT_MAP = {};\n  var OUTPUT_MAP = {};\n  for (var unitDef in UNITS) {\n    if (UNITS.hasOwnProperty(unitDef)) {\n      var definition = UNITS[unitDef];\n      if (definition[2] === \"prefix\") {\n        PREFIX_VALUES[unitDef] = definition[1];\n        for (var i = 0; i < definition[0].length; i++) {\n          PREFIX_MAP[definition[0][i]] = unitDef;\n        }\n      }\n      else {\n        validateUnitDefinition(unitDef, definition);\n        UNIT_VALUES[unitDef] = {\n          scalar: definition[1],\n          numerator: definition[3],\n          denominator: definition[4]\n        };\n        for (var j = 0; j < definition[0].length; j++) {\n          UNIT_MAP[definition[0][j]] = unitDef;\n        }\n      }\n      OUTPUT_MAP[unitDef] = definition[0][0];\n    }\n  }\n\n  /**\n   * Returns a list of available units of kind\n   *\n   * @param {string} [kind] - kind of units\n   * @returns {array} names of units\n   * @throws {QtyError} if kind is unknown\n   */\n  function getUnits(kind) {\n    var i;\n    var units = [];\n    var unitKeys = Object.keys(UNITS);\n    if (typeof kind === \"undefined\") {\n      for (i = 0; i < unitKeys.length; i++) {\n        if ([\"\", \"prefix\"].indexOf(UNITS[unitKeys[i]][2]) === -1) {\n          units.push(unitKeys[i].substr(1, unitKeys[i].length - 2));\n        }\n      }\n    }\n    else if (this.getKinds().indexOf(kind) === -1) {\n      throw new QtyError(\"Kind not recognized\");\n    }\n    else {\n      for (i = 0; i < unitKeys.length; i++) {\n        if (UNITS[unitKeys[i]][2] === kind) {\n          units.push(unitKeys[i].substr(1, unitKeys[i].length - 2));\n        }\n      }\n    }\n\n    return units.sort(function(a, b) {\n      if (a.toLowerCase() < b.toLowerCase()) {\n        return -1;\n      }\n      if (a.toLowerCase() > b.toLowerCase()) {\n        return 1;\n      }\n      return 0;\n    });\n  }\n\n  /**\n   * Returns a list of alternative names for a unit\n   *\n   * @param {string} unitName - name of unit\n   * @returns {string[]} aliases for unit\n   * @throws {QtyError} if unit is unknown\n   */\n  function getAliases(unitName) {\n    if (!UNIT_MAP[unitName]) {\n      throw new QtyError(\"Unit not recognized\");\n    }\n    return UNITS[UNIT_MAP[unitName]][0];\n  }\n\n  var SIGNATURE_VECTOR = [\"length\", \"time\", \"temperature\", \"mass\", \"current\", \"substance\", \"luminosity\", \"currency\", \"information\", \"angle\"];\n\n  /*\n  calculates the unit signature id for use in comparing compatible units and simplification\n  the signature is based on a simple classification of units and is based on the following publication\n\n  Novak, G.S., Jr. \"Conversion of units of measurement\", IEEE Transactions on Software Engineering,\n  21(8), Aug 1995, pp.651-661\n  doi://10.1109/32.403789\n  http://ieeexplore.ieee.org/Xplore/login.jsp?url=/iel1/32/9079/00403789.pdf?isnumber=9079&prod=JNL&arnumber=403789&arSt=651&ared=661&arAuthor=Novak%2C+G.S.%2C+Jr.\n  */\n  function unitSignature() {\n    if (this.signature) {\n      return this.signature;\n    }\n    var vector = unitSignatureVector.call(this);\n    for (var i = 0; i < vector.length; i++) {\n      vector[i] *= Math.pow(20, i);\n    }\n\n    return vector.reduce(\n      function(previous, current) {\n        return previous + current;\n      },\n      0\n    );\n  }\n\n  // calculates the unit signature vector used by unit_signature\n  function unitSignatureVector() {\n    if (!this.isBase()) {\n      return unitSignatureVector.call(this.toBase());\n    }\n\n    var vector = new Array(SIGNATURE_VECTOR.length);\n    for (var i = 0; i < vector.length; i++) {\n      vector[i] = 0;\n    }\n    var r, n;\n    for (var j = 0; j < this.numerator.length; j++) {\n      if ((r = UNITS[this.numerator[j]])) {\n        n = SIGNATURE_VECTOR.indexOf(r[2]);\n        if (n >= 0) {\n          vector[n] = vector[n] + 1;\n        }\n      }\n    }\n\n    for (var k = 0; k < this.denominator.length; k++) {\n      if ((r = UNITS[this.denominator[k]])) {\n        n = SIGNATURE_VECTOR.indexOf(r[2]);\n        if (n >= 0) {\n          vector[n] = vector[n] - 1;\n        }\n      }\n    }\n    return vector;\n  }\n\n  var SIGN = \"[+-]\";\n  var INTEGER = \"\\\\d+\";\n  var SIGNED_INTEGER = SIGN + \"?\" + INTEGER;\n  var FRACTION = \"\\\\.\" + INTEGER;\n  var FLOAT = \"(?:\" + INTEGER + \"(?:\" + FRACTION + \")?\" + \")\" +\n              \"|\" +\n              \"(?:\" + FRACTION + \")\";\n  var EXPONENT = \"[Ee]\" + SIGNED_INTEGER;\n  var SCI_NUMBER = \"(?:\" + FLOAT + \")(?:\" + EXPONENT + \")?\";\n  var SIGNED_NUMBER = SIGN + \"?\\\\s*\" + SCI_NUMBER;\n  var QTY_STRING = \"(\" + SIGNED_NUMBER + \")?\" + \"\\\\s*([^/]*)(?:\\/(.+))?\";\n  var QTY_STRING_REGEX = new RegExp(\"^\" + QTY_STRING + \"$\");\n\n  var POWER_OP = \"\\\\^|\\\\*{2}\";\n  // Allow unit powers representing scalar, length, area, volume; 4 is for some\n  // special case representations in SI base units.\n  var SAFE_POWER = \"[01234]\";\n  var TOP_REGEX = new RegExp (\"([^ \\\\*\\\\d]+?)(?:\" + POWER_OP + \")?(-?\" + SAFE_POWER + \"(?![a-zA-Z]))\");\n  var BOTTOM_REGEX = new RegExp(\"([^ \\\\*\\\\d]+?)(?:\" + POWER_OP + \")?(\" + SAFE_POWER + \"(?![a-zA-Z]))\");\n\n  /* parse a string into a unit object.\n   * Typical formats like :\n   * \"5.6 kg*m/s^2\"\n   * \"5.6 kg*m*s^-2\"\n   * \"5.6 kilogram*meter*second^-2\"\n   * \"2.2 kPa\"\n   * \"37 degC\"\n   * \"1\"  -- creates a unitless constant with value 1\n   * \"GPa\"  -- creates a unit with scalar 1 with units 'GPa'\n   * 6'4\"  -- recognized as 6 feet + 4 inches\n   * 8 lbs 8 oz -- recognized as 8 lbs + 8 ounces\n   */\n  function parse(val) {\n    if (!isString(val)) {\n      val = val.toString();\n    }\n    val = val.trim();\n\n    var result = QTY_STRING_REGEX.exec(val);\n    if (!result) {\n      throw new QtyError(val + \": Quantity not recognized\");\n    }\n\n    var scalarMatch = result[1];\n    if (scalarMatch) {\n      // Allow whitespaces between sign and scalar for loose parsing\n      scalarMatch = scalarMatch.replace(/\\s/g, \"\");\n      this.scalar = parseFloat(scalarMatch);\n    }\n    else {\n      this.scalar = 1;\n    }\n    var top = result[2];\n    var bottom = result[3];\n\n    var n, x, nx;\n    // TODO DRY me\n    while ((result = TOP_REGEX.exec(top))) {\n      n = parseFloat(result[2]);\n      if (isNaN(n)) {\n        // Prevents infinite loops\n        throw new QtyError(\"Unit exponent is not a number\");\n      }\n      // Disallow unrecognized unit even if exponent is 0\n      if (n === 0 && !UNIT_TEST_REGEX.test(result[1])) {\n        throw new QtyError(\"Unit not recognized\");\n      }\n      x = result[1] + \" \";\n      nx = \"\";\n      for (var i = 0; i < Math.abs(n) ; i++) {\n        nx += x;\n      }\n      if (n >= 0) {\n        top = top.replace(result[0], nx);\n      }\n      else {\n        bottom = bottom ? bottom + nx : nx;\n        top = top.replace(result[0], \"\");\n      }\n    }\n\n    while ((result = BOTTOM_REGEX.exec(bottom))) {\n      n = parseFloat(result[2]);\n      if (isNaN(n)) {\n        // Prevents infinite loops\n        throw new QtyError(\"Unit exponent is not a number\");\n      }\n      // Disallow unrecognized unit even if exponent is 0\n      if (n === 0 && !UNIT_TEST_REGEX.test(result[1])) {\n        throw new QtyError(\"Unit not recognized\");\n      }\n      x = result[1] + \" \";\n      nx = \"\";\n      for (var j = 0; j < n ; j++) {\n        nx += x;\n      }\n\n      bottom = bottom.replace(result[0], nx);\n    }\n\n    if (top) {\n      this.numerator = parseUnits(top.trim());\n    }\n    if (bottom) {\n      this.denominator = parseUnits(bottom.trim());\n    }\n  }\n\n  var PREFIX_REGEX = Object.keys(PREFIX_MAP).sort(function(a, b) {\n    return b.length - a.length;\n  }).join(\"|\");\n  var UNIT_REGEX = Object.keys(UNIT_MAP).sort(function(a, b) {\n    return b.length - a.length;\n  }).join(\"|\");\n  /*\n   * Minimal boundary regex to support units with Unicode characters\n   * \\b only works for ASCII\n   */\n  var BOUNDARY_REGEX = \"\\\\b|$\";\n  var UNIT_MATCH = \"(\" + PREFIX_REGEX + \")??(\" +\n                   UNIT_REGEX +\n                   \")(?:\" + BOUNDARY_REGEX + \")\";\n  var UNIT_TEST_REGEX = new RegExp(\"^\\\\s*(\" + UNIT_MATCH + \"[\\\\s\\\\*]*)+$\");\n  var UNIT_MATCH_REGEX = new RegExp(UNIT_MATCH, \"g\"); // g flag for multiple occurences\n  var parsedUnitsCache = {};\n  /**\n   * Parses and converts units string to normalized unit array.\n   * Result is cached to speed up next calls.\n   *\n   * @param {string} units Units string\n   * @returns {string[]} Array of normalized units\n   *\n   * @example\n   * // Returns [\"<second>\", \"<meter>\", \"<second>\"]\n   * parseUnits(\"s m s\");\n   *\n   */\n  function parseUnits(units) {\n    var cached = parsedUnitsCache[units];\n    if (cached) {\n      return cached;\n    }\n\n    var unitMatch, normalizedUnits = [];\n\n    // Scan\n    if (!UNIT_TEST_REGEX.test(units)) {\n      throw new QtyError(\"Unit not recognized\");\n    }\n\n    while ((unitMatch = UNIT_MATCH_REGEX.exec(units))) {\n      normalizedUnits.push(unitMatch.slice(1));\n    }\n\n    normalizedUnits = normalizedUnits.map(function(item) {\n      return PREFIX_MAP[item[0]] ? [PREFIX_MAP[item[0]], UNIT_MAP[item[1]]] : [UNIT_MAP[item[1]]];\n    });\n\n    // Flatten and remove null elements\n    normalizedUnits = normalizedUnits.reduce(function(a,b) {\n      return a.concat(b);\n    }, []);\n    normalizedUnits = normalizedUnits.filter(function(item) {\n      return item;\n    });\n\n    parsedUnitsCache[units] = normalizedUnits;\n\n    return normalizedUnits;\n  }\n\n  /**\n   * Parses a string as a quantity\n   * @param {string} value - quantity as text\n   * @throws if value is not a string\n   * @returns {Qty|null} Parsed quantity or null if unrecognized\n   */\n  function globalParse(value) {\n    if (!isString(value)) {\n      throw new QtyError(\"Argument should be a string\");\n    }\n\n    try {\n      return this(value);\n    }\n    catch (e) {\n      return null;\n    }\n  }\n\n  /**\n   * Tests if a value is a Qty instance\n   *\n   * @param {*} value - Value to test\n   *\n   * @returns {boolean} true if value is a Qty instance, false otherwise\n   */\n  function isQty(value) {\n    return value instanceof Qty;\n  }\n\n  function Qty(initValue, initUnits) {\n    assertValidConstructorArgs.apply(null, arguments);\n\n    if (!(isQty(this))) {\n      return new Qty(initValue, initUnits);\n    }\n\n    this.scalar = null;\n    this.baseScalar = null;\n    this.signature = null;\n    this._conversionCache = {};\n    this.numerator = UNITY_ARRAY;\n    this.denominator = UNITY_ARRAY;\n\n    if (isDefinitionObject(initValue)) {\n      this.scalar = initValue.scalar;\n      this.numerator = (initValue.numerator && initValue.numerator.length !== 0) ? initValue.numerator : UNITY_ARRAY;\n      this.denominator = (initValue.denominator && initValue.denominator.length !== 0) ? initValue.denominator : UNITY_ARRAY;\n    }\n    else if (initUnits) {\n      parse.call(this, initUnits);\n      this.scalar = initValue;\n    }\n    else {\n      parse.call(this, initValue);\n    }\n\n    // math with temperatures is very limited\n    if (this.denominator.join(\"*\").indexOf(\"temp\") >= 0) {\n      throw new QtyError(\"Cannot divide with temperatures\");\n    }\n    if (this.numerator.join(\"*\").indexOf(\"temp\") >= 0) {\n      if (this.numerator.length > 1) {\n        throw new QtyError(\"Cannot multiply by temperatures\");\n      }\n      if (!compareArray(this.denominator, UNITY_ARRAY)) {\n        throw new QtyError(\"Cannot divide with temperatures\");\n      }\n    }\n\n    this.initValue = initValue;\n    updateBaseScalar.call(this);\n\n    if (this.isTemperature() && this.baseScalar < 0) {\n      throw new QtyError(\"Temperatures must not be less than absolute zero\");\n    }\n  }\n\n  Qty.prototype = {\n    // Properly set up constructor\n    constructor: Qty,\n  };\n\n  /**\n   * Asserts constructor arguments are valid\n   *\n   * @param {*} value - Value to test\n   * @param {string} [units] - Optional units when value is passed as a number\n   *\n   * @returns {void}\n   * @throws {QtyError} if constructor arguments are invalid\n   */\n  function assertValidConstructorArgs(value, units) {\n    if (units) {\n      if (!(isNumber(value) && isString(units))) {\n        throw new QtyError(\"Only number accepted as initialization value \" +\n                           \"when units are explicitly provided\");\n      }\n    }\n    else {\n      if (!(isString(value) ||\n            isNumber(value) ||\n            isQty(value)    ||\n            isDefinitionObject(value))) {\n        throw new QtyError(\"Only string, number or quantity accepted as \" +\n                           \"single initialization value\");\n      }\n    }\n  }\n\n  /**\n   * Tests if a value is a Qty definition object\n   *\n   * @param {*} value - Value to test\n   *\n   * @returns {boolean} true if value is a definition object, false otherwise\n   */\n  function isDefinitionObject(value) {\n    return value && typeof value === \"object\" && value.hasOwnProperty(\"scalar\");\n  }\n\n  function updateBaseScalar() {\n    if (this.baseScalar) {\n      return this.baseScalar;\n    }\n    if (this.isBase()) {\n      this.baseScalar = this.scalar;\n      this.signature = unitSignature.call(this);\n    }\n    else {\n      var base = this.toBase();\n      this.baseScalar = base.scalar;\n      this.signature = base.signature;\n    }\n  }\n\n  var KINDS = {\n    \"-312078\": \"elastance\",\n    \"-312058\": \"resistance\",\n    \"-312038\": \"inductance\",\n    \"-152058\": \"potential\",\n    \"-152040\": \"magnetism\",\n    \"-152038\": \"magnetism\",\n    \"-7997\": \"specific_volume\",\n    \"-79\": \"snap\",\n    \"-59\": \"jolt\",\n    \"-39\": \"acceleration\",\n    \"-38\": \"radiation\",\n    \"-20\": \"frequency\",\n    \"-19\": \"speed\",\n    \"-18\": \"viscosity\",\n    \"-17\": \"volumetric_flow\",\n    \"-1\": \"wavenumber\",\n    \"0\": \"unitless\",\n    \"1\": \"length\",\n    \"2\": \"area\",\n    \"3\": \"volume\",\n    \"20\": \"time\",\n    \"400\": \"temperature\",\n    \"7941\": \"yank\",\n    \"7942\": \"power\",\n    \"7959\": \"pressure\",\n    \"7961\": \"force\",\n    \"7962\": \"energy\",\n    \"7979\": \"viscosity\",\n    \"7981\": \"momentum\",\n    \"7982\": \"angular_momentum\",\n    \"7997\": \"density\",\n    \"7998\": \"area_density\",\n    \"8000\": \"mass\",\n    \"152020\": \"radiation_exposure\",\n    \"159999\": \"magnetism\",\n    \"160000\": \"current\",\n    \"160020\": \"charge\",\n    \"312058\": \"conductance\",\n    \"312078\": \"capacitance\",\n    \"3199980\": \"activity\",\n    \"3199997\": \"molar_concentration\",\n    \"3200000\": \"substance\",\n    \"63999998\": \"illuminance\",\n    \"64000000\": \"luminous_power\",\n    \"1280000000\": \"currency\",\n    \"25599999980\": \"information_rate\",\n    \"25600000000\": \"information\",\n    \"511999999980\": \"angular_velocity\",\n    \"512000000000\": \"angle\"\n  };\n\n  /**\n   * Returns the list of available well-known kinds of units, e.g.\n   * \"radiation\" or \"length\".\n   *\n   * @returns {string[]} names of kinds of units\n   */\n  function getKinds() {\n    return uniq(Object.keys(KINDS).map(function(knownSignature) {\n      return KINDS[knownSignature];\n    }));\n  }\n\n  Qty.prototype.kind = function() {\n    return KINDS[this.signature.toString()];\n  };\n\n  assign(Qty.prototype, {\n    isDegrees: function() {\n      // signature may not have been calculated yet\n      return (this.signature === null || this.signature === 400) &&\n        this.numerator.length === 1 &&\n        compareArray(this.denominator, UNITY_ARRAY) &&\n        (this.numerator[0].match(/<temp-[CFRK]>/) || this.numerator[0].match(/<(kelvin|celsius|rankine|fahrenheit)>/));\n    },\n\n    isTemperature: function() {\n      return this.isDegrees() && this.numerator[0].match(/<temp-[CFRK]>/);\n    }\n  });\n\n  function subtractTemperatures(lhs,rhs) {\n    var lhsUnits = lhs.units();\n    var rhsConverted = rhs.to(lhsUnits);\n    var dstDegrees = Qty(getDegreeUnits(lhsUnits));\n    return Qty({\"scalar\": lhs.scalar - rhsConverted.scalar, \"numerator\": dstDegrees.numerator, \"denominator\": dstDegrees.denominator});\n  }\n\n  function subtractTempDegrees(temp,deg) {\n    var tempDegrees = deg.to(getDegreeUnits(temp.units()));\n    return Qty({\"scalar\": temp.scalar - tempDegrees.scalar, \"numerator\": temp.numerator, \"denominator\": temp.denominator});\n  }\n\n  function addTempDegrees(temp,deg) {\n    var tempDegrees = deg.to(getDegreeUnits(temp.units()));\n    return Qty({\"scalar\": temp.scalar + tempDegrees.scalar, \"numerator\": temp.numerator, \"denominator\": temp.denominator});\n  }\n\n  function getDegreeUnits(units) {\n    if (units === \"tempK\") {\n      return \"degK\";\n    }\n    else if (units === \"tempC\") {\n      return \"degC\";\n    }\n    else if (units === \"tempF\") {\n      return \"degF\";\n    }\n    else if (units === \"tempR\") {\n      return \"degR\";\n    }\n    else {\n      throw new QtyError(\"Unknown type for temp conversion from: \" + units);\n    }\n  }\n\n  function toDegrees(src,dst) {\n    var srcDegK = toDegK(src);\n    var dstUnits = dst.units();\n    var dstScalar;\n\n    if (dstUnits === \"degK\") {\n      dstScalar = srcDegK.scalar;\n    }\n    else if (dstUnits === \"degC\") {\n      dstScalar = srcDegK.scalar ;\n    }\n    else if (dstUnits === \"degF\") {\n      dstScalar = srcDegK.scalar * 9 / 5;\n    }\n    else if (dstUnits === \"degR\") {\n      dstScalar = srcDegK.scalar * 9 / 5;\n    }\n    else {\n      throw new QtyError(\"Unknown type for degree conversion to: \" + dstUnits);\n    }\n\n    return Qty({\"scalar\": dstScalar, \"numerator\": dst.numerator, \"denominator\": dst.denominator});\n  }\n\n  function toDegK(qty) {\n    var units = qty.units();\n    var q;\n    if (units.match(/(deg)[CFRK]/)) {\n      q = qty.baseScalar;\n    }\n    else if (units === \"tempK\") {\n      q = qty.scalar;\n    }\n    else if (units === \"tempC\") {\n      q = qty.scalar;\n    }\n    else if (units === \"tempF\") {\n      q = qty.scalar * 5 / 9;\n    }\n    else if (units === \"tempR\") {\n      q = qty.scalar * 5 / 9;\n    }\n    else {\n      throw new QtyError(\"Unknown type for temp conversion from: \" + units);\n    }\n\n    return Qty({\"scalar\": q, \"numerator\": [\"<kelvin>\"], \"denominator\": UNITY_ARRAY});\n  }\n\n  function toTemp(src,dst) {\n    var dstUnits = dst.units();\n    var dstScalar;\n\n    if (dstUnits === \"tempK\") {\n      dstScalar = src.baseScalar;\n    }\n    else if (dstUnits === \"tempC\") {\n      dstScalar = src.baseScalar - 273.15;\n    }\n    else if (dstUnits === \"tempF\") {\n      dstScalar = (src.baseScalar * 9 / 5) - 459.67;\n    }\n    else if (dstUnits === \"tempR\") {\n      dstScalar = src.baseScalar * 9 / 5;\n    }\n    else {\n      throw new QtyError(\"Unknown type for temp conversion to: \" + dstUnits);\n    }\n\n    return Qty({\"scalar\": dstScalar, \"numerator\": dst.numerator, \"denominator\": dst.denominator});\n  }\n\n  function toTempK(qty) {\n    var units = qty.units();\n    var q;\n    if (units.match(/(deg)[CFRK]/)) {\n      q = qty.baseScalar;\n    }\n    else if (units === \"tempK\") {\n      q = qty.scalar;\n    }\n    else if (units === \"tempC\") {\n      q = qty.scalar + 273.15;\n    }\n    else if (units === \"tempF\") {\n      q = (qty.scalar + 459.67) * 5 / 9;\n    }\n    else if (units === \"tempR\") {\n      q = qty.scalar * 5 / 9;\n    }\n    else {\n      throw new QtyError(\"Unknown type for temp conversion from: \" + units);\n    }\n\n    return Qty({\"scalar\": q, \"numerator\": [\"<temp-K>\"], \"denominator\": UNITY_ARRAY});\n  }\n\n  assign(Qty.prototype, {\n    /**\n     * Converts to other compatible units.\n     * Instance's converted quantities are cached for faster subsequent calls.\n     *\n     * @param {(string|Qty)} other - Target units as string or retrieved from\n     *                               other Qty instance (scalar is ignored)\n     *\n     * @returns {Qty} New converted Qty instance with target units\n     *\n     * @throws {QtyError} if target units are incompatible\n     *\n     * @example\n     * var weight = Qty(\"25 kg\");\n     * weight.to(\"lb\"); // => Qty(\"55.11556554621939 lbs\");\n     * weight.to(Qty(\"3 g\")); // => Qty(\"25000 g\"); // scalar of passed Qty is ignored\n     */\n    to: function(other) {\n      var cached, target;\n\n      if (other === undefined || other === null) {\n        return this;\n      }\n\n      if (!isString(other)) {\n        return this.to(other.units());\n      }\n\n      cached = this._conversionCache[other];\n      if (cached) {\n        return cached;\n      }\n\n      // Instantiating target to normalize units\n      target = Qty(other);\n      if (target.units() === this.units()) {\n        return this;\n      }\n\n      if (!this.isCompatible(target)) {\n        if (this.isInverse(target)) {\n          target = this.inverse().to(other);\n        }\n        else {\n          throwIncompatibleUnits(this.units(), target.units());\n        }\n      }\n      else {\n        if (target.isTemperature()) {\n          target = toTemp(this,target);\n        }\n        else if (target.isDegrees()) {\n          target = toDegrees(this,target);\n        }\n        else {\n          var q = divSafe(this.baseScalar, target.baseScalar);\n          target = Qty({\"scalar\": q, \"numerator\": target.numerator, \"denominator\": target.denominator});\n        }\n      }\n\n      this._conversionCache[other] = target;\n      return target;\n    },\n\n    // convert to base SI units\n    // results of the conversion are cached so subsequent calls to this will be fast\n    toBase: function() {\n      if (this.isBase()) {\n        return this;\n      }\n\n      if (this.isTemperature()) {\n        return toTempK(this);\n      }\n\n      var cached = baseUnitCache[this.units()];\n      if (!cached) {\n        cached = toBaseUnits(this.numerator,this.denominator);\n        baseUnitCache[this.units()] = cached;\n      }\n      return cached.mul(this.scalar);\n    },\n\n    // Converts the unit back to a float if it is unitless.  Otherwise raises an exception\n    toFloat: function() {\n      if (this.isUnitless()) {\n        return this.scalar;\n      }\n      throw new QtyError(\"Can't convert to Float unless unitless.  Use Unit#scalar\");\n    },\n\n    /**\n     * Returns the nearest multiple of quantity passed as\n     * precision\n     *\n     * @param {(Qty|string|number)} precQuantity - Quantity, string formated\n     *   quantity or number as expected precision\n     *\n     * @returns {Qty} Nearest multiple of precQuantity\n     *\n     * @example\n     * Qty('5.5 ft').toPrec('2 ft'); // returns 6 ft\n     * Qty('0.8 cu').toPrec('0.25 cu'); // returns 0.75 cu\n     * Qty('6.3782 m').toPrec('cm'); // returns 6.38 m\n     * Qty('1.146 MPa').toPrec('0.1 bar'); // returns 1.15 MPa\n     *\n     */\n    toPrec: function(precQuantity) {\n      if (isString(precQuantity)) {\n        precQuantity = Qty(precQuantity);\n      }\n      if (isNumber(precQuantity)) {\n        precQuantity = Qty(precQuantity + \" \" + this.units());\n      }\n\n      if (!this.isUnitless()) {\n        precQuantity = precQuantity.to(this.units());\n      }\n      else if (!precQuantity.isUnitless()) {\n        throwIncompatibleUnits(this.units(), precQuantity.units());\n      }\n\n      if (precQuantity.scalar === 0) {\n        throw new QtyError(\"Divide by zero\");\n      }\n\n      var precRoundedResult = mulSafe(\n        Math.round(this.scalar / precQuantity.scalar),\n        precQuantity.scalar\n      );\n\n      return Qty(precRoundedResult + this.units());\n    }\n  });\n\n  /**\n   * Configures and returns a fast function to convert\n   * Number values from units to others.\n   * Useful to efficiently convert large array of values\n   * with same units into others with iterative methods.\n   * Does not take care of rounding issues.\n   *\n   * @param {string} srcUnits Units of values to convert\n   * @param {string} dstUnits Units to convert to\n   *\n   * @returns {Function} Converting function accepting Number value\n   *   and returning converted value\n   *\n   * @throws \"Incompatible units\" if units are incompatible\n   *\n   * @example\n   * // Converting large array of numbers with the same units\n   * // into other units\n   * var converter = Qty.swiftConverter(\"m/h\", \"ft/s\");\n   * var convertedSerie = largeSerie.map(converter);\n   *\n   */\n  function swiftConverter(srcUnits, dstUnits) {\n    var srcQty = Qty(srcUnits);\n    var dstQty = Qty(dstUnits);\n\n    if (srcQty.eq(dstQty)) {\n      return identity;\n    }\n\n    var convert;\n    if (!srcQty.isTemperature()) {\n      convert = function(value) {\n        return value * srcQty.baseScalar / dstQty.baseScalar;\n      };\n    }\n    else {\n      convert = function(value) {\n        // TODO Not optimized\n        return srcQty.mul(value).to(dstQty).scalar;\n      };\n    }\n\n    return function converter(value) {\n      var i, length, result;\n      if (!Array.isArray(value)) {\n        return convert(value);\n      }\n      else {\n        length = value.length;\n        result = [];\n        for (i = 0; i < length; i++) {\n          result.push(convert(value[i]));\n        }\n        return result;\n      }\n    };\n  }\n\n  var baseUnitCache = {};\n\n  function toBaseUnits(numerator,denominator) {\n    var num = [];\n    var den = [];\n    var q = 1;\n    var unit;\n    for (var i = 0; i < numerator.length; i++) {\n      unit = numerator[i];\n      if (PREFIX_VALUES[unit]) {\n        // workaround to fix\n        // 0.1 * 0.1 => 0.010000000000000002\n        q = mulSafe(q, PREFIX_VALUES[unit]);\n      }\n      else {\n        if (UNIT_VALUES[unit]) {\n          q *= UNIT_VALUES[unit].scalar;\n\n          if (UNIT_VALUES[unit].numerator) {\n            num.push(UNIT_VALUES[unit].numerator);\n          }\n          if (UNIT_VALUES[unit].denominator) {\n            den.push(UNIT_VALUES[unit].denominator);\n          }\n        }\n      }\n    }\n    for (var j = 0; j < denominator.length; j++) {\n      unit = denominator[j];\n      if (PREFIX_VALUES[unit]) {\n        q /= PREFIX_VALUES[unit];\n      }\n      else {\n        if (UNIT_VALUES[unit]) {\n          q /= UNIT_VALUES[unit].scalar;\n\n          if (UNIT_VALUES[unit].numerator) {\n            den.push(UNIT_VALUES[unit].numerator);\n          }\n          if (UNIT_VALUES[unit].denominator) {\n            num.push(UNIT_VALUES[unit].denominator);\n          }\n        }\n      }\n    }\n\n    // Flatten\n    num = num.reduce(function(a,b) {\n      return a.concat(b);\n    }, []);\n    den = den.reduce(function(a,b) {\n      return a.concat(b);\n    }, []);\n\n    return Qty({\"scalar\": q, \"numerator\": num, \"denominator\": den});\n  }\n\n  Qty.parse = globalParse;\n\n  Qty.getUnits = getUnits;\n  Qty.getAliases = getAliases;\n\n  Qty.mulSafe = mulSafe;\n  Qty.divSafe = divSafe;\n\n  Qty.getKinds = getKinds;\n\n  Qty.swiftConverter = swiftConverter;\n\n  Qty.Error = QtyError;\n\n  assign(Qty.prototype, {\n    // Returns new instance with units of this\n    add: function(other) {\n      if (isString(other)) {\n        other = Qty(other);\n      }\n\n      if (!this.isCompatible(other)) {\n        throwIncompatibleUnits(this.units(), other.units());\n      }\n\n      if (this.isTemperature() && other.isTemperature()) {\n        throw new QtyError(\"Cannot add two temperatures\");\n      }\n      else if (this.isTemperature()) {\n        return addTempDegrees(this, other);\n      }\n      else if (other.isTemperature()) {\n        return addTempDegrees(other, this);\n      }\n\n      return Qty({\"scalar\": this.scalar + other.to(this).scalar, \"numerator\": this.numerator, \"denominator\": this.denominator});\n    },\n\n    sub: function(other) {\n      if (isString(other)) {\n        other = Qty(other);\n      }\n\n      if (!this.isCompatible(other)) {\n        throwIncompatibleUnits(this.units(), other.units());\n      }\n\n      if (this.isTemperature() && other.isTemperature()) {\n        return subtractTemperatures(this,other);\n      }\n      else if (this.isTemperature()) {\n        return subtractTempDegrees(this,other);\n      }\n      else if (other.isTemperature()) {\n        throw new QtyError(\"Cannot subtract a temperature from a differential degree unit\");\n      }\n\n      return Qty({\"scalar\": this.scalar - other.to(this).scalar, \"numerator\": this.numerator, \"denominator\": this.denominator});\n    },\n\n    mul: function(other) {\n      if (isNumber(other)) {\n        return Qty({\"scalar\": mulSafe(this.scalar, other), \"numerator\": this.numerator, \"denominator\": this.denominator});\n      }\n      else if (isString(other)) {\n        other = Qty(other);\n      }\n\n      if ((this.isTemperature() || other.isTemperature()) && !(this.isUnitless() || other.isUnitless())) {\n        throw new QtyError(\"Cannot multiply by temperatures\");\n      }\n\n      // Quantities should be multiplied with same units if compatible, with base units else\n      var op1 = this;\n      var op2 = other;\n\n      // so as not to confuse results, multiplication and division between temperature degrees will maintain original unit info in num/den\n      // multiplication and division between deg[CFRK] can never factor each other out, only themselves: \"degK*degC/degC^2\" == \"degK/degC\"\n      if (op1.isCompatible(op2) && op1.signature !== 400) {\n        op2 = op2.to(op1);\n      }\n      var numdenscale = cleanTerms(op1.numerator, op1.denominator, op2.numerator, op2.denominator);\n\n      return Qty({\"scalar\": mulSafe(op1.scalar, op2.scalar, numdenscale[2]), \"numerator\": numdenscale[0], \"denominator\": numdenscale[1]});\n    },\n\n    div: function(other) {\n      if (isNumber(other)) {\n        if (other === 0) {\n          throw new QtyError(\"Divide by zero\");\n        }\n        return Qty({\"scalar\": this.scalar / other, \"numerator\": this.numerator, \"denominator\": this.denominator});\n      }\n      else if (isString(other)) {\n        other = Qty(other);\n      }\n\n      if (other.scalar === 0) {\n        throw new QtyError(\"Divide by zero\");\n      }\n\n      if (other.isTemperature()) {\n        throw new QtyError(\"Cannot divide with temperatures\");\n      }\n      else if (this.isTemperature() && !other.isUnitless()) {\n        throw new QtyError(\"Cannot divide with temperatures\");\n      }\n\n      // Quantities should be multiplied with same units if compatible, with base units else\n      var op1 = this;\n      var op2 = other;\n\n      // so as not to confuse results, multiplication and division between temperature degrees will maintain original unit info in num/den\n      // multiplication and division between deg[CFRK] can never factor each other out, only themselves: \"degK*degC/degC^2\" == \"degK/degC\"\n      if (op1.isCompatible(op2) && op1.signature !== 400) {\n        op2 = op2.to(op1);\n      }\n      var numdenscale = cleanTerms(op1.numerator, op1.denominator, op2.denominator, op2.numerator);\n\n      return Qty({\"scalar\": mulSafe(op1.scalar, numdenscale[2]) / op2.scalar, \"numerator\": numdenscale[0], \"denominator\": numdenscale[1]});\n    },\n\n    // Returns a Qty that is the inverse of this Qty,\n    inverse: function() {\n      if (this.isTemperature()) {\n        throw new QtyError(\"Cannot divide with temperatures\");\n      }\n      if (this.scalar === 0) {\n        throw new QtyError(\"Divide by zero\");\n      }\n      return Qty({\"scalar\": 1 / this.scalar, \"numerator\": this.denominator, \"denominator\": this.numerator});\n    }\n  });\n\n  function cleanTerms(num1, den1, num2, den2) {\n    function notUnity(val) {\n      return val !== UNITY;\n    }\n\n    num1 = num1.filter(notUnity);\n    num2 = num2.filter(notUnity);\n    den1 = den1.filter(notUnity);\n    den2 = den2.filter(notUnity);\n\n    var combined = {};\n\n    function combineTerms(terms, direction) {\n      var k;\n      var prefix;\n      var prefixValue;\n      for (var i = 0; i < terms.length; i++) {\n        if (PREFIX_VALUES[terms[i]]) {\n          k = terms[i + 1];\n          prefix = terms[i];\n          prefixValue = PREFIX_VALUES[prefix];\n          i++;\n        }\n        else {\n          k = terms[i];\n          prefix = null;\n          prefixValue = 1;\n        }\n        if (k && k !== UNITY) {\n          if (combined[k]) {\n            combined[k][0] += direction;\n            var combinedPrefixValue = combined[k][2] ? PREFIX_VALUES[combined[k][2]] : 1;\n            combined[k][direction === 1 ? 3 : 4] *= divSafe(prefixValue, combinedPrefixValue);\n          }\n          else {\n            combined[k] = [direction, k, prefix, 1, 1];\n          }\n        }\n      }\n    }\n\n    combineTerms(num1, 1);\n    combineTerms(den1, -1);\n    combineTerms(num2, 1);\n    combineTerms(den2, -1);\n\n    var num = [];\n    var den = [];\n    var scale = 1;\n\n    for (var prop in combined) {\n      if (combined.hasOwnProperty(prop)) {\n        var item = combined[prop];\n        var n;\n        if (item[0] > 0) {\n          for (n = 0; n < item[0]; n++) {\n            num.push(item[2] === null ? item[1] : [item[2], item[1]]);\n          }\n        }\n        else if (item[0] < 0) {\n          for (n = 0; n < -item[0]; n++) {\n            den.push(item[2] === null ? item[1] : [item[2], item[1]]);\n          }\n        }\n        scale *= divSafe(item[3], item[4]);\n      }\n    }\n\n    if (num.length === 0) {\n      num = UNITY_ARRAY;\n    }\n    if (den.length === 0) {\n      den = UNITY_ARRAY;\n    }\n\n    // Flatten\n    num = num.reduce(function(a,b) {\n      return a.concat(b);\n    }, []);\n    den = den.reduce(function(a,b) {\n      return a.concat(b);\n    }, []);\n\n    return [num, den, scale];\n  }\n\n  assign(Qty.prototype, {\n    eq: function(other) {\n      return this.compareTo(other) === 0;\n    },\n\n    lt: function(other) {\n      return this.compareTo(other) === -1;\n    },\n\n    lte: function(other) {\n      return this.eq(other) || this.lt(other);\n    },\n\n    gt: function(other) {\n      return this.compareTo(other) === 1;\n    },\n\n    gte: function(other) {\n      return this.eq(other) || this.gt(other);\n    },\n\n    // Compare two Qty objects. Throws an exception if they are not of compatible types.\n    // Comparisons are done based on the value of the quantity in base SI units.\n    //\n    // NOTE: We cannot compare inverses as that breaks the general compareTo contract:\n    //   if a.compareTo(b) < 0 then b.compareTo(a) > 0\n    //   if a.compareTo(b) == 0 then b.compareTo(a) == 0\n    //\n    //   Since \"10S\" == \".1ohm\" (10 > .1) and \"10ohm\" == \".1S\" (10 > .1)\n    //     Qty(\"10S\").inverse().compareTo(\"10ohm\") == -1\n    //     Qty(\"10ohm\").inverse().compareTo(\"10S\") == -1\n    //\n    //   If including inverses in the sort is needed, I suggest writing: Qty.sort(qtyArray,units)\n    compareTo: function(other) {\n      if (isString(other)) {\n        return this.compareTo(Qty(other));\n      }\n      if (!this.isCompatible(other)) {\n        throwIncompatibleUnits(this.units(), other.units());\n      }\n      if (this.baseScalar < other.baseScalar) {\n        return -1;\n      }\n      else if (this.baseScalar === other.baseScalar) {\n        return 0;\n      }\n      else if (this.baseScalar > other.baseScalar) {\n        return 1;\n      }\n    },\n\n    // Return true if quantities and units match\n    // Unit(\"100 cm\").same(Unit(\"100 cm\"))  # => true\n    // Unit(\"100 cm\").same(Unit(\"1 m\"))     # => false\n    same: function(other) {\n      return (this.scalar === other.scalar) && (this.units() === other.units());\n    }\n  });\n\n  assign(Qty.prototype, {\n    // returns true if no associated units\n    // false, even if the units are \"unitless\" like 'radians, each, etc'\n    isUnitless: function() {\n      return [this.numerator, this.denominator].every(function(item) {\n        return compareArray(item, UNITY_ARRAY);\n      });\n    },\n\n    /*\n    check to see if units are compatible, but not the scalar part\n    this check is done by comparing signatures for performance reasons\n    if passed a string, it will create a unit object with the string and then do the comparison\n    this permits a syntax like:\n    unit =~ \"mm\"\n    if you want to do a regexp on the unit string do this ...\n    unit.units =~ /regexp/\n    */\n    isCompatible: function(other) {\n      if (isString(other)) {\n        return this.isCompatible(Qty(other));\n      }\n\n      if (!(isQty(other))) {\n        return false;\n      }\n\n      if (other.signature !== undefined) {\n        return this.signature === other.signature;\n      }\n      else {\n        return false;\n      }\n    },\n\n    /*\n    check to see if units are inverse of each other, but not the scalar part\n    this check is done by comparing signatures for performance reasons\n    if passed a string, it will create a unit object with the string and then do the comparison\n    this permits a syntax like:\n    unit =~ \"mm\"\n    if you want to do a regexp on the unit string do this ...\n    unit.units =~ /regexp/\n    */\n    isInverse: function(other) {\n      return this.inverse().isCompatible(other);\n    },\n\n    // Returns 'true' if the Unit is represented in base units\n    isBase: function() {\n      if (this._isBase !== undefined) {\n        return this._isBase;\n      }\n      if (this.isDegrees() && this.numerator[0].match(/<(kelvin|temp-K)>/)) {\n        this._isBase = true;\n        return this._isBase;\n      }\n\n      this.numerator.concat(this.denominator).forEach(function(item) {\n        if (item !== UNITY && BASE_UNITS.indexOf(item) === -1 ) {\n          this._isBase = false;\n        }\n      }, this);\n      if (this._isBase === false) {\n        return this._isBase;\n      }\n      this._isBase = true;\n      return this._isBase;\n    }\n  });\n\n  function NestedMap() {}\n\n  NestedMap.prototype.get = function(keys) {\n\n    // Allows to pass key1, key2, ... instead of [key1, key2, ...]\n    if (arguments.length > 1) {\n      // Slower with Firefox but faster with Chrome than\n      // Array.prototype.slice.call(arguments)\n      // See http://jsperf.com/array-apply-versus-array-prototype-slice-call\n      keys = Array.apply(null, arguments);\n    }\n\n    return keys.reduce(function(map, key, index) {\n      if (map) {\n\n        var childMap = map[key];\n\n        if (index === keys.length - 1) {\n          return childMap ? childMap.data : undefined;\n        }\n        else {\n          return childMap;\n        }\n      }\n    },\n    this);\n  };\n\n  NestedMap.prototype.set = function(keys, value) {\n\n    if (arguments.length > 2) {\n      keys = Array.prototype.slice.call(arguments, 0, -1);\n      value = arguments[arguments.length - 1];\n    }\n\n    return keys.reduce(function(map, key, index) {\n\n      var childMap = map[key];\n      if (childMap === undefined) {\n        childMap = map[key] = {};\n      }\n\n      if (index === keys.length - 1) {\n        childMap.data = value;\n        return value;\n      }\n      else {\n        return childMap;\n      }\n    }, this);\n  };\n\n  /**\n   * Default formatter\n   *\n   * @param {number} scalar - scalar value\n   * @param {string} units - units as string\n   *\n   * @returns {string} formatted result\n   */\n  function defaultFormatter(scalar, units) {\n    return (scalar + \" \" + units).trim();\n  }\n\n  /**\n   *\n   * Configurable Qty default formatter\n   *\n   * @type {function}\n   *\n   * @param {number} scalar\n   * @param {string} units\n   *\n   * @returns {string} formatted result\n   */\n  Qty.formatter = defaultFormatter;\n\n  assign(Qty.prototype, {\n\n    // returns the 'unit' part of the Unit object without the scalar\n    units: function() {\n      if (this._units !== undefined) {\n        return this._units;\n      }\n\n      var numIsUnity = compareArray(this.numerator, UNITY_ARRAY);\n      var denIsUnity = compareArray(this.denominator, UNITY_ARRAY);\n      if (numIsUnity && denIsUnity) {\n        this._units = \"\";\n        return this._units;\n      }\n\n      var numUnits = stringifyUnits(this.numerator);\n      var denUnits = stringifyUnits(this.denominator);\n      this._units = numUnits + (denIsUnity ? \"\" : (\"/\" + denUnits));\n      return this._units;\n    },\n\n    /**\n     * Stringifies the quantity\n     * Deprecation notice: only units parameter is supported.\n     *\n     * @param {(number|string|Qty)} targetUnitsOrMaxDecimalsOrPrec -\n     *                              target units if string,\n     *                              max number of decimals if number,\n     *                              passed to #toPrec before converting if Qty\n     *\n     * @param {number=} maxDecimals - Maximum number of decimals of\n     *                                formatted output\n     *\n     * @returns {string} reparseable quantity as string\n     */\n    toString: function(targetUnitsOrMaxDecimalsOrPrec, maxDecimals) {\n      var targetUnits;\n      if (isNumber(targetUnitsOrMaxDecimalsOrPrec)) {\n        targetUnits = this.units();\n        maxDecimals = targetUnitsOrMaxDecimalsOrPrec;\n      }\n      else if (isString(targetUnitsOrMaxDecimalsOrPrec)) {\n        targetUnits = targetUnitsOrMaxDecimalsOrPrec;\n      }\n      else if (isQty(targetUnitsOrMaxDecimalsOrPrec)) {\n        return this.toPrec(targetUnitsOrMaxDecimalsOrPrec).toString(maxDecimals);\n      }\n\n      var out = this.to(targetUnits);\n\n      var outScalar = maxDecimals !== undefined ? round(out.scalar, maxDecimals) : out.scalar;\n      out = (outScalar + \" \" + out.units()).trim();\n      return out;\n    },\n\n    /**\n     * Format the quantity according to optional passed target units\n     * and formatter\n     *\n     * @param {string} [targetUnits=current units] -\n     *                 optional units to convert to before formatting\n     *\n     * @param {function} [formatter=Qty.formatter] -\n     *                   delegates formatting to formatter callback.\n     *                   formatter is called back with two parameters (scalar, units)\n     *                   and should return formatted result.\n     *                   If unspecified, formatting is delegated to default formatter\n     *                   set to Qty.formatter\n     *\n     * @example\n     * var roundingAndLocalizingFormatter = function(scalar, units) {\n     *   // localize or limit scalar to n max decimals for instance\n     *   // return formatted result\n     * };\n     * var qty = Qty('1.1234 m');\n     * qty.format(); // same units, default formatter => \"1.234 m\"\n     * qty.format(\"cm\"); // converted to \"cm\", default formatter => \"123.45 cm\"\n     * qty.format(roundingAndLocalizingFormatter); // same units, custom formatter => \"1,2 m\"\n     * qty.format(\"cm\", roundingAndLocalizingFormatter); // convert to \"cm\", custom formatter => \"123,4 cm\"\n     *\n     * @returns {string} quantity as string\n     */\n    format: function(targetUnits, formatter) {\n      if (arguments.length === 1) {\n        if (typeof targetUnits === \"function\") {\n          formatter = targetUnits;\n          targetUnits = undefined;\n        }\n      }\n\n      formatter = formatter || Qty.formatter;\n      var targetQty = this.to(targetUnits);\n      return formatter.call(this, targetQty.scalar, targetQty.units());\n    }\n  });\n\n  var stringifiedUnitsCache = new NestedMap();\n  /**\n   * Returns a string representing a normalized unit array\n   *\n   * @param {string[]} units Normalized unit array\n   * @returns {string} String representing passed normalized unit array and\n   *   suitable for output\n   *\n   */\n  function stringifyUnits(units) {\n\n    var stringified = stringifiedUnitsCache.get(units);\n    if (stringified) {\n      return stringified;\n    }\n\n    var isUnity = compareArray(units, UNITY_ARRAY);\n    if (isUnity) {\n      stringified = \"1\";\n    }\n    else {\n      stringified = simplify(getOutputNames(units)).join(\"*\");\n    }\n\n    // Cache result\n    stringifiedUnitsCache.set(units, stringified);\n\n    return stringified;\n  }\n\n  function getOutputNames(units) {\n    var unitNames = [], token, tokenNext;\n    for (var i = 0; i < units.length; i++) {\n      token = units[i];\n      tokenNext = units[i + 1];\n      if (PREFIX_VALUES[token]) {\n        unitNames.push(OUTPUT_MAP[token] + OUTPUT_MAP[tokenNext]);\n        i++;\n      }\n      else {\n        unitNames.push(OUTPUT_MAP[token]);\n      }\n    }\n    return unitNames;\n  }\n\n  function simplify(units) {\n    // this turns ['s','m','s'] into ['s2','m']\n\n    var unitCounts = units.reduce(function(acc, unit) {\n      var unitCounter = acc[unit];\n      if (!unitCounter) {\n        acc.push(unitCounter = acc[unit] = [unit, 0]);\n      }\n\n      unitCounter[1]++;\n\n      return acc;\n    }, []);\n\n    return unitCounts.map(function(unitCount) {\n      return unitCount[0] + (unitCount[1] > 1 ? unitCount[1] : \"\");\n    });\n  }\n\n  Qty.version = \"1.7.6\";\n\n  return Qty;\n\n})));\n","import Qty from 'js-quantities';\nexport function convertUnit(array, fromUnit, toUnit) {\n    fromUnit = normalize(fromUnit);\n    toUnit = normalize(toUnit);\n    if (fromUnit === toUnit)\n        return array;\n    const convert = Qty.swiftConverter(fromUnit, toUnit); // Configures converter\n    //@ts-expect-error convert does not allowed typed array but it works\n    return convert(array);\n}\nfunction normalize(unit) {\n    unit = unit.replace(/°C/g, 'tempC');\n    unit = unit.replace(/°F/g, 'tempF');\n    unit = unit.replace(/(^|\\W)K(\\W|$)/g, '$1tempK$2');\n    return unit;\n}\n//# sourceMappingURL=data:application/json;base64,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","const testRegExp = /^\\/((?:\\\\\\/|[^/])+)\\/([migyu]{0,5})?$/;\nexport function ensureRegexp(string) {\n    if (typeof string !== 'string')\n        return string;\n    const parts = testRegExp.exec(string);\n    if (parts) {\n        try {\n            return new RegExp(parts[1], parts[2]);\n        }\n        catch (err) {\n            return stringToRegexp(string);\n        }\n    }\n    else {\n        return stringToRegexp(string);\n    }\n}\nfunction stringToRegexp(string, flags = 'i') {\n    return new RegExp(string.replace(/[[\\]\\\\{}()+*?.$^|]/g, (match) => `\\\\${match}`), flags);\n}\n//# 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{ xIsMonotone, xMinValue, xMaxValue } from 'ml-spectra-processing';\nimport { convertUnit } from './convertUnit';\nexport function getConvertedVariable(variable, newUnits) {\n    const data = variable.units !== undefined && variable.units !== newUnits // would be nice if convertUnit would allow typedArray\n        ? convertUnit(Array.from(variable.data), variable.units, newUnits)\n        : variable.data;\n    return {\n        units: newUnits,\n        label: variable.label.replace(`[${variable.units || ''}]`, `[${newUnits}]`),\n        data: data || [],\n        min: data ? xMinValue(data) : undefined,\n        max: data ? xMaxValue(data) : undefined,\n        isMonotone: xIsMonotone(data),\n    };\n}\n//# 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eslint-disable @typescript-eslint/no-dynamic-delete */\nimport { convertUnit } from './convertUnit';\nimport { ensureRegexp } from './ensureRegexp';\nimport { getConvertedVariable } from './getConvertedVariable';\n/**\n * Retrieve the spectrum with only X/Y data that match all the selectors\n * If more than one variable match the selector the 'x' or 'y' variable will be\n * taken\n */\nexport function getXYSpectra(spectra = [], selector = {}) {\n    const selectedSpectra = [];\n    if (spectra.length < 1)\n        return selectedSpectra;\n    let { dataType, title, xUnits, yUnits, variables, xVariable = 'x', yVariable = 'y', units, labels, xLabel, yLabel, meta, index, } = selector;\n    if (index !== undefined) {\n        return [spectra[index]];\n    }\n    if (dataType) {\n        dataType = ensureRegexp(dataType);\n    }\n    if (title) {\n        title = ensureRegexp(title);\n    }\n    if (units && !xUnits && !yUnits)\n        [yUnits, xUnits] = units.split(/\\s*vs\\s*/);\n    if (labels && !xLabel && !yLabel) {\n        [yLabel, xLabel] = labels.split(/\\s*vs\\s*/);\n    }\n    if (variables) {\n        const parts = variables.split(/\\s*vs\\s*/);\n        if (parts.length === 2) {\n            xVariable = parts[1];\n            yVariable = parts[0];\n        }\n    }\n    if (xLabel)\n        xLabel = ensureRegexp(xLabel);\n    if (yLabel)\n        yLabel = ensureRegexp(yLabel);\n    for (let spectrum of spectra) {\n        let variableNames = Object.keys(spectrum.variables);\n        if (!(variableNames.length > 1))\n            continue;\n        // we filter on general spectrum information\n        if (dataType) {\n            if (!spectrum.dataType || !dataType.exec(spectrum.dataType)) {\n                continue;\n            }\n        }\n        if (title) {\n            if (!spectrum.title || !title.exec(spectrum.title)) {\n                continue;\n            }\n        }\n        if (meta && typeof meta === 'object') {\n            if (!spectrum.meta)\n                continue;\n            for (let key in spectrum.meta) {\n                if (!spectrum.meta[key])\n                    continue;\n                let value = ensureRegexp(spectrum.meta[key]);\n                if (!value.exec(spectrum.meta[key]))\n                    continue;\n            }\n        }\n        let x = getPossibleVariable(spectrum.variables, {\n            units: xUnits,\n            label: xLabel,\n            variableName: xVariable,\n        });\n        let y = getPossibleVariable(spectrum.variables, {\n            units: yUnits,\n            label: yLabel,\n            variableName: yVariable,\n        });\n        if (x && y) {\n            selectedSpectra.push({\n                title: spectrum.title,\n                dataType: spectrum.dataType,\n                meta: spectrum.meta,\n                variables: { x, y },\n                id: spectrum.id,\n            });\n        }\n    }\n    return selectedSpectra;\n}\nfunction getPossibleVariable(variables, selector = {}) {\n    var _a, _b;\n    const { units, label, variableName } = selector;\n    let possible = { ...variables };\n    let key;\n    if (units !== undefined) {\n        for (key in possible) {\n            const variable = variables[key];\n            let convertibleUnits = true;\n            try {\n                convertUnit(1, (variable === null || variable === void 0 ? void 0 : variable.units) || '', units);\n            }\n            catch (e) {\n                convertibleUnits = false;\n            }\n            if (convertibleUnits && variable) {\n                possible[key] = getConvertedVariable(variable, units);\n            }\n            else {\n                delete possible[key];\n            }\n        }\n    }\n    if (label !== undefined) {\n        const regexpLabel = ensureRegexp(label);\n        for (key in possible) {\n            if (!regexpLabel.exec((_b = (_a = variables[key]) === null || _a === void 0 ? void 0 : _a.label) !== null && _b !== void 0 ? _b : '')) {\n                delete possible[key];\n            }\n        }\n    }\n    if (variableName !== undefined) {\n        if (possible[variableName])\n            return possible[variableName];\n        const upper = variableName.toUpperCase();\n        if (Object.prototype.hasOwnProperty.call(possible, upper)) {\n            return possible[upper];\n        }\n        const lower = variableName.toLowerCase();\n        if (Object.prototype.hasOwnProperty.call(possible, lower)) {\n            return possible[lower];\n        }\n    }\n    const possibleFiltered = Object.values(possible).filter((val) => val !== undefined);\n    if (possibleFiltered.length > 0) {\n        return possibleFiltered[0];\n    }\n}\n//# 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{ isAnyArray } from 'is-any-array';\nimport { xIsMonotone, xMinValue, xMaxValue } from 'ml-spectra-processing';\nimport { getNormalizedSpectrum } from './util/getNormalizedSpectrum';\nimport { getXYSpectra } from './util/getXYSpectra';\nimport { getXYSpectrum } from './util/getXYSpectrum';\n/**\n * Class allowing to store and manipulate an analysis.\n * An analysis may contain one or more spectra that can be selected\n * based on their units\n */\nexport class Analysis {\n    constructor(options = {}) {\n        this.id = options.id || Math.random().toString(36).substring(2, 10);\n        this.label = options.label || this.id;\n        this.spectrumCallback = options.spectrumCallback;\n        this.spectra = [];\n        this.cache = { spectrum: {}, spectra: {} };\n    }\n    /**\n     * Add a spectrum in the internal spectra variable\n     */\n    pushSpectrum(variables, options = {}) {\n        this.spectra.push(standardizeData(variables, options, {\n            spectrumCallback: this.spectrumCallback,\n        }));\n        this.cache = { spectrum: {}, spectra: {} };\n    }\n    /**\n     * Retrieve a Spectrum based on x/y units\n     */\n    getXYSpectrum(selector = {}) {\n        let id = JSON.stringify(selector);\n        if (!this.cache.spectrum[id]) {\n            this.cache.spectrum[id] = getXYSpectrum(this.spectra, selector);\n        }\n        return this.cache.spectrum[id];\n    }\n    /**\n     * Retrieve spectra matching selector\n     */\n    getXYSpectra(selector = {}) {\n        let id = JSON.stringify(selector);\n        if (!this.cache.spectra[id]) {\n            this.cache.spectra[id] = getXYSpectra(this.spectra, selector);\n        }\n        return this.cache.spectra[id];\n    }\n    /**\n     * Retrieve a xy object\n     * @param selector.units Units separated by vs like for example \"g vs °C\"\n     * @param selector.xUnits if undefined takes the first variable\n     * @param selector.yUnits if undefined takes the second variable\n     */\n    getXY(selector = {}) {\n        let spectrum = this.getXYSpectrum(selector);\n        if (!spectrum)\n            return undefined;\n        return {\n            x: spectrum.variables.x.data,\n            y: spectrum.variables.y.data,\n        };\n    }\n    /**\n     * Return the data object for specific x/y units with possibly some\n     * normalization options\n     * @param options.selector.xUnits // if undefined takes the first variable\n     * @param options.selector.yUnits // if undefined takes the second variable\n     */\n    getNormalizedSpectrum(options = {}) {\n        const { normalization, selector } = options;\n        const spectrum = this.getXYSpectrum(selector);\n        if (!spectrum)\n            return undefined;\n        return getNormalizedSpectrum(spectrum, normalization);\n    }\n    /**\n     */\n    getNormalizedSpectra(options = {}) {\n        const { normalization, selector } = options;\n        const spectra = this.getXYSpectra(selector);\n        if (spectra.length === 0)\n            return [];\n        const normalizedSpectra = [];\n        for (const spectrum of spectra) {\n            normalizedSpectra.push(getNormalizedSpectrum(spectrum, normalization));\n        }\n        return normalizedSpectra;\n    }\n    /**\n     * Returns the first spectrum. This method could be improved in the future\n     * @returns\n     */\n    getSpectrum() {\n        return this.spectra[0];\n    }\n    /**\n     * Returns the xLabel\n     * @param selector.xUnits // if undefined takes the first variable\n     * @param selector.yUnits // if undefined takes the second variable\n     */\n    getXLabel(selector) {\n        var _a;\n        return (_a = this.getXYSpectrum(selector)) === null || _a === void 0 ? void 0 : _a.variables.x.label;\n    }\n    /**\n     * Returns the yLabel\n     * @param selector.xUnits // if undefined takes the first variable\n     * @param selector.yUnits // if undefined takes the second variable\n     */\n    getYLabel(selector) {\n        var _a;\n        return (_a = this.getXYSpectrum(selector)) === null || _a === void 0 ? void 0 : _a.variables.y.label;\n    }\n}\n/**\n * Internal function that ensure the order of x / y array\n */\nfunction standardizeData(variables, options, analysisOptions) {\n    let { meta = {}, dataType = '', title = '' } = options;\n    const { spectrumCallback } = analysisOptions;\n    if (spectrumCallback) {\n        spectrumCallback(variables);\n    }\n    let xVariable = variables.x;\n    let yVariable = variables.y;\n    if (!xVariable || !yVariable) {\n        throw Error('A spectrum must contain at least x and y variables');\n    }\n    if (!isAnyArray(xVariable.data) || !isAnyArray(yVariable.data)) {\n        throw Error('x and y variables must contain an array data');\n    }\n    let x = xVariable.data;\n    let reverse = x && x.length > 1 && x[0] > x[x.length - 1];\n    for (let [key, variable] of Object.entries(variables)) {\n        if (reverse)\n            variable.data = variable.data.slice().reverse();\n        variable.label = variable.label || key;\n        if (variable.label.match(/^.*[([](?<units>.*)[)\\]].*$/)) {\n            const units = variable.label.replace(/^.*[([](?<units>.*)[)\\]].*$/, '$<units>');\n            if (!variable.units || variable.units === units) {\n                variable.units = units;\n                variable.label = variable.label.replace(/[([].*[)\\]]/, '').trim();\n            }\n        }\n        variable.min = xMinValue(variable.data);\n        variable.max = xMaxValue(variable.data);\n        variable.isMonotone = xIsMonotone(variable.data);\n    }\n    return {\n        variables,\n        title,\n        dataType,\n        meta,\n        id: Math.random().toString(36).replace('0.', ''),\n    };\n}\n//# 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","import { getXYSpectra } from './getXYSpectra';\n/**\n * Retrieve the spectrum with only X/Y data that match all the selectors\n * If more than one variable match the selector the 'x' or 'y' variable will be\n * taken\n */\nexport function getXYSpectrum(spectra = [], selector = {}) {\n    const selectedSpectra = getXYSpectra(spectra, selector);\n    if (selectedSpectra.length === 0)\n        return undefined;\n    return selectedSpectra[0];\n}\n//# sourceMappingURL=data:application/json;base64,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","import isutf8 from 'isutf8';\n/**\n * Ensure that the data is string. If it is an ArrayBuffer it will be converted to string using TextDecoder.\n * @param blob\n * @param options\n * @returns\n */\nexport function ensureString(blob, options = {}) {\n    if (typeof blob === 'string') {\n        return blob;\n    }\n    if (ArrayBuffer.isView(blob) || blob instanceof ArrayBuffer) {\n        const { encoding = guessEncoding(blob) } = options;\n        const decoder = new TextDecoder(encoding);\n        return decoder.decode(blob);\n    }\n    throw new TypeError(`blob must be a string, ArrayBuffer or ArrayBufferView`);\n}\nfunction guessEncoding(blob) {\n    const uint8 = ArrayBuffer.isView(blob)\n        ? new Uint8Array(blob.buffer, blob.byteOffset, blob.byteLength)\n        : new Uint8Array(blob);\n    if (uint8.length >= 2) {\n        if (uint8[0] === 0xfe && uint8[1] === 0xff) {\n            return 'utf-16be';\n        }\n        if (uint8[0] === 0xff && uint8[1] === 0xfe) {\n            return 'utf-16le';\n        }\n    }\n    //@ts-expect-error an ArrayBuffer is also ok\n    if (!isutf8(blob))\n        return 'latin1';\n    return 'utf-8';\n}\n//# sourceMappingURL=index.js.map","/*\n    https://tools.ietf.org/html/rfc3629\n\n    UTF8-char = UTF8-1 / UTF8-2 / UTF8-3 / UTF8-4\n\n    UTF8-1    = %x00-7F\n\n    UTF8-2    = %xC2-DF UTF8-tail\n\n    UTF8-3    = %xE0 %xA0-BF UTF8-tail\n                %xE1-EC 2( UTF8-tail )\n                %xED %x80-9F UTF8-tail\n                %xEE-EF 2( UTF8-tail )\n\n    UTF8-4    = %xF0 %x90-BF 2( UTF8-tail )\n                %xF1-F3 3( UTF8-tail )\n                %xF4 %x80-8F 2( UTF8-tail )\n\n    UTF8-tail = %x80-BF\n*/\n/**\n * Check if a Node.js Buffer or Uint8Array is UTF-8.\n */\nfunction isUtf8(buf) {\n    if (!buf) {\n        return false;\n    }\n    var i = 0;\n    var len = buf.length;\n    while (i < len) {\n        // UTF8-1 = %x00-7F\n        if (buf[i] <= 0x7F) {\n            i++;\n            continue;\n        }\n        // UTF8-2 = %xC2-DF UTF8-tail\n        if (buf[i] >= 0xC2 && buf[i] <= 0xDF) {\n            // if(buf[i + 1] >= 0x80 && buf[i + 1] <= 0xBF) {\n            if (buf[i + 1] >> 6 === 2) {\n                i += 2;\n                continue;\n            }\n            else {\n                return false;\n            }\n        }\n        // UTF8-3 = %xE0 %xA0-BF UTF8-tail\n        // UTF8-3 = %xED %x80-9F UTF8-tail\n        if (((buf[i] === 0xE0 && buf[i + 1] >= 0xA0 && buf[i + 1] <= 0xBF) ||\n            (buf[i] === 0xED && buf[i + 1] >= 0x80 && buf[i + 1] <= 0x9F)) && buf[i + 2] >> 6 === 2) {\n            i += 3;\n            continue;\n        }\n        // UTF8-3 = %xE1-EC 2( UTF8-tail )\n        // UTF8-3 = %xEE-EF 2( UTF8-tail )\n        if (((buf[i] >= 0xE1 && buf[i] <= 0xEC) ||\n            (buf[i] >= 0xEE && buf[i] <= 0xEF)) &&\n            buf[i + 1] >> 6 === 2 &&\n            buf[i + 2] >> 6 === 2) {\n            i += 3;\n            continue;\n        }\n        // UTF8-4 = %xF0 %x90-BF 2( UTF8-tail )\n        //          %xF1-F3 3( UTF8-tail )\n        //          %xF4 %x80-8F 2( UTF8-tail )\n        if (((buf[i] === 0xF0 && buf[i + 1] >= 0x90 && buf[i + 1] <= 0xBF) ||\n            (buf[i] >= 0xF1 && buf[i] <= 0xF3 && buf[i + 1] >> 6 === 2) ||\n            (buf[i] === 0xF4 && buf[i + 1] >= 0x80 && buf[i + 1] <= 0x8F)) &&\n            buf[i + 2] >> 6 === 2 &&\n            buf[i + 3] >> 6 === 2) {\n            i += 4;\n            continue;\n        }\n        return false;\n    }\n    return true;\n}\n\nexport { isUtf8 as default };\n","/**\n * Dynamically type a string\n * @param {string} value String to dynamically type\n * @returns {boolean|string|number}\n */\nexport function parseString(value) {\n  if (value.length === 4 || value.length === 5) {\n    let lowercase = value.toLowerCase();\n\n    if (lowercase === 'true') return true;\n    if (lowercase === 'false') return false;\n  }\n  let number = Number(value);\n  if (number === 0 && !value.includes('0')) {\n    return value;\n  }\n  if (!Number.isNaN(number)) return number;\n  return value;\n}\n","const GC_MS_FIELDS = ['TIC', '.RIC', 'SCANNUMBER'];\nexport function complexChromatogram(result) {\n    let spectra = result.spectra;\n    let length = spectra.length;\n    let chromatogram = {\n        times: new Array(length),\n        series: {\n            ms: {\n                dimension: 2,\n                data: new Array(length),\n            },\n        },\n    };\n    let existingGCMSFields = [];\n    for (let i = 0; i < GC_MS_FIELDS.length; i++) {\n        let label = convertMSFieldToLabel(GC_MS_FIELDS[i]);\n        if (spectra[0][label]) {\n            existingGCMSFields.push(label);\n            chromatogram.series[label] = {\n                dimension: 1,\n                data: new Array(length),\n            };\n        }\n    }\n    for (let i = 0; i < length; i++) {\n        let spectrum = spectra[i];\n        chromatogram.times[i] = spectrum.pageValue;\n        for (let j = 0; j < existingGCMSFields.length; j++) {\n            chromatogram.series[existingGCMSFields[j]].data[i] = Number(spectrum[existingGCMSFields[j]]);\n        }\n        if (spectrum.data) {\n            chromatogram.series.ms.data[i] = [spectrum.data.x, spectrum.data.y];\n        }\n    }\n    result.chromatogram = chromatogram;\n}\nexport function isMSField(canonicDataLabel) {\n    return GC_MS_FIELDS.indexOf(canonicDataLabel) !== -1;\n}\nexport function convertMSFieldToLabel(value) {\n    return value.toLowerCase().replace(/[^a-z0-9]/g, '');\n}\n//# sourceMappingURL=complexChromatogram.js.map","export default function convertToFloatArray(stringArray) {\n    let floatArray = [];\n    for (let i = 0; i < stringArray.length; i++) {\n        floatArray.push(Number(stringArray[i]));\n    }\n    return floatArray;\n}\n//# sourceMappingURL=convertToFloatArray.js.map","export default function fastParseXYData(spectrum, value) {\n    // TODO need to deal with result\n    //  console.log(value);\n    // we check if deltaX is defined otherwise we calculate it\n    let yFactor = spectrum.yFactor;\n    let deltaX = spectrum.deltaX;\n    spectrum.isXYdata = true;\n    let currentData = { x: [], y: [] };\n    spectrum.data = currentData;\n    let currentX = spectrum.firstX;\n    let currentY = spectrum.firstY;\n    // we skip the first line\n    //\n    let endLine = false;\n    let ascii;\n    let i = 0;\n    for (; i < value.length; i++) {\n        ascii = value.charCodeAt(i);\n        if (ascii === 13 || ascii === 10) {\n            endLine = true;\n        }\n        else if (endLine) {\n            break;\n        }\n    }\n    // we proceed taking the i after the first line\n    let newLine = true;\n    let isDifference = false;\n    let isLastDifference = false;\n    let lastDifference = 0;\n    let isDuplicate = false;\n    let inComment = false;\n    let currentValue = 0; // can be a difference or a duplicate\n    let lastValue = 0; // must be the real last value\n    let isNegative = false;\n    let inValue = false;\n    let skipFirstValue = false;\n    let decimalPosition = 0;\n    for (; i <= value.length; i++) {\n        if (i === value.length)\n            ascii = 13;\n        else\n            ascii = value.charCodeAt(i);\n        if (inComment) {\n            // we should ignore the text if we are after $$\n            if (ascii === 13 || ascii === 10) {\n                newLine = true;\n                inComment = false;\n            }\n        }\n        else {\n            // when is it a new value ?\n            // when it is not a digit, . or comma\n            // it is a number that is either new or we continue\n            // eslint-disable-next-line no-lonely-if\n            if (ascii <= 57 && ascii >= 48) {\n                // a number\n                inValue = true;\n                if (decimalPosition > 0) {\n                    currentValue += (ascii - 48) / Math.pow(10, decimalPosition++);\n                }\n                else {\n                    currentValue *= 10;\n                    currentValue += ascii - 48;\n                }\n            }\n            else if (ascii === 44 || ascii === 46) {\n                // a \",\" or \".\"\n                inValue = true;\n                decimalPosition++;\n            }\n            else {\n                if (inValue) {\n                    // need to process the previous value\n                    if (newLine) {\n                        newLine = false; // we don't check the X value\n                        // console.log(\"NEW LINE\",isDifference, lastDifference);\n                        // if new line and lastDifference, the first value is just a check !\n                        // that we don't check ...\n                        if (isLastDifference)\n                            skipFirstValue = true;\n                    }\n                    else {\n                        // need to deal with duplicate and differences\n                        // eslint-disable-next-line no-lonely-if\n                        if (skipFirstValue) {\n                            skipFirstValue = false;\n                        }\n                        else {\n                            if (isDifference) {\n                                lastDifference = isNegative ? 0 - currentValue : currentValue;\n                                isLastDifference = true;\n                                isDifference = false;\n                            }\n                            else if (!isDuplicate) {\n                                lastValue = isNegative ? 0 - currentValue : currentValue;\n                            }\n                            let duplicate = isDuplicate ? currentValue - 1 : 1;\n                            for (let j = 0; j < duplicate; j++) {\n                                if (isLastDifference) {\n                                    currentY += lastDifference;\n                                }\n                                else {\n                                    currentY = lastValue;\n                                }\n                                currentData.x.push(currentX);\n                                currentData.y.push(currentY * yFactor);\n                                currentX += deltaX;\n                            }\n                        }\n                    }\n                    isNegative = false;\n                    currentValue = 0;\n                    decimalPosition = 0;\n                    inValue = false;\n                    isDuplicate = false;\n                }\n                // positive SQZ digits @ A B C D E F G H I (ascii 64-73)\n                if (ascii < 74 && ascii > 63) {\n                    inValue = true;\n                    isLastDifference = false;\n                    currentValue = ascii - 64;\n                }\n                else if (ascii > 96 && ascii < 106) {\n                    // negative SQZ digits a b c d e f g h i (ascii 97-105)\n                    inValue = true;\n                    isLastDifference = false;\n                    currentValue = ascii - 96;\n                    isNegative = true;\n                }\n                else if (ascii === 115) {\n                    // DUP digits S T U V W X Y Z s (ascii 83-90, 115)\n                    inValue = true;\n                    isDuplicate = true;\n                    currentValue = 9;\n                }\n                else if (ascii > 82 && ascii < 91) {\n                    inValue = true;\n                    isDuplicate = true;\n                    currentValue = ascii - 82;\n                }\n                else if (ascii > 73 && ascii < 83) {\n                    // positive DIF digits % J K L M N O P Q R (ascii 37, 74-82)\n                    inValue = true;\n                    isDifference = true;\n                    currentValue = ascii - 73;\n                }\n                else if (ascii > 105 && ascii < 115) {\n                    // negative DIF digits j k l m n o p q r (ascii 106-114)\n                    inValue = true;\n                    isDifference = true;\n                    currentValue = ascii - 105;\n                    isNegative = true;\n                }\n                else if (ascii === 36 && value.charCodeAt(i + 1) === 36) {\n                    // $ sign, we need to check the next one\n                    inValue = true;\n                    inComment = true;\n                }\n                else if (ascii === 37) {\n                    // positive DIF digits % J K L M N O P Q R (ascii 37, 74-82)\n                    inValue = true;\n                    isDifference = true;\n                    currentValue = 0;\n                    isNegative = false;\n                }\n                else if (ascii === 45) {\n                    // a \"-\"\n                    // check if after there is a number, decimal or comma\n                    let ascii2 = value.charCodeAt(i + 1);\n                    if ((ascii2 >= 48 && ascii2 <= 57) ||\n                        ascii2 === 44 ||\n                        ascii2 === 46) {\n                        inValue = true;\n                        if (!newLine)\n                            isLastDifference = false;\n                        isNegative = true;\n                    }\n                }\n                else if (ascii === 13 || ascii === 10) {\n                    newLine = true;\n                    inComment = false;\n                }\n                // and now analyse the details ... space or tabulation\n                // if \"+\" we just don't care\n            }\n        }\n    }\n}\n//# sourceMappingURL=fastParseXYData.js.map","const removeCommentRegExp = /\\$\\$.*/;\nconst peakTableSplitRegExp = /[,\\t ]+/;\nexport default function parsePeakTable(spectrum, value, result) {\n    spectrum.isPeaktable = true;\n    if (!spectrum.variables || Object.keys(spectrum.variables) === 2) {\n        parseXY(spectrum, value, result);\n    }\n    else {\n        parseXYZ(spectrum, value, result);\n    }\n    // we will add the data in the variables\n    if (spectrum.variables) {\n        for (let key in spectrum.variables) {\n            spectrum.variables[key].data = spectrum.data[key];\n        }\n    }\n}\nfunction parseXY(spectrum, value, result) {\n    let currentData = { x: [], y: [] };\n    spectrum.data = currentData;\n    // counts for around 20% of the time\n    let lines = value.split(/,? *,?[;\\r\\n]+ */);\n    for (let i = 1; i < lines.length; i++) {\n        let values = lines[i]\n            .trim()\n            .replace(removeCommentRegExp, '')\n            .split(peakTableSplitRegExp);\n        if (values.length % 2 === 0) {\n            for (let j = 0; j < values.length; j = j + 2) {\n                // takes around 40% of the time to add and parse the 2 values nearly exclusively because of Number\n                currentData.x.push(Number(values[j]) * spectrum.xFactor);\n                currentData.y.push(Number(values[j + 1]) * spectrum.yFactor);\n            }\n        }\n        else {\n            result.logs.push(`Format error: ${values}`);\n        }\n    }\n}\nfunction parseXYZ(spectrum, value, result) {\n    let currentData = {};\n    let variables = Object.keys(spectrum.variables);\n    let numberOfVariables = variables.length;\n    variables.forEach((variable) => (currentData[variable] = []));\n    spectrum.data = currentData;\n    // counts for around 20% of the time\n    let lines = value.split(/,? *,?[;\\r\\n]+ */);\n    for (let i = 1; i < lines.length; i++) {\n        let values = lines[i]\n            .trim()\n            .replace(removeCommentRegExp, '')\n            .split(peakTableSplitRegExp);\n        if (values.length % numberOfVariables === 0) {\n            for (let j = 0; j < values.length; j++) {\n                // todo should try to find a xFactor (y, ...)\n                currentData[variables[j % numberOfVariables]].push(Number(values[j]));\n            }\n        }\n        else {\n            result.logs.push(`Format error: ${values}`);\n        }\n    }\n}\n//# sourceMappingURL=parsePeakTable.js.map","/*\n(5.4.4) ##РЕАК ASSIGNMENTS= (STRING). List\nof peak assignments for components or functional groups\nin the forms ##РЕАК ASSIGNMENTS= (ХУА),\n(XYW А), (ХУМА), (XYMW А). Each entry is surrounded Ьу parentheses and starts а new line. У, W (peak\nwidth), and М (multiplicity) values are optional. The\nsymbol А stands for а string detailing the assignment\nand must Ье enclosed Ьу angle brackets. If the peak width\nvalue is included, then the function used to calculate the\npeak width must Ье detailed in а $$ comment on the\nline(s) below ##PEAKASSIGNMENTS=. Priority OPTIONAL. N.B.: ##РЕАК ASSIGNMENTS= is the preferred method of transmitting peak information when\nthe assignments are known.\n */\nexport default function parseXYA(spectrum, value) {\n    spectrum.isXYAdata = true;\n    const currentData = {};\n    spectrum.data = currentData;\n    let lines = value.split(/\\r?\\n/);\n    const variables = lines[0]\n        .replace(/^.*?([A-Z]+).*$/, '$1')\n        .split('')\n        .map((variable) => variable.toLowerCase());\n    for (let i = 1; i < lines.length; i++) {\n        const fields = lines[i].replace(/^\\((.*)\\)$/, '$1').split(/ *, */);\n        for (let j = 0; j < variables.length; j++) {\n            let value = fields[j];\n            switch (variables[j]) {\n                case 'x':\n                case 'y':\n                case 'w':\n                    value = Number.parseFloat(value);\n                    break;\n                case 'a':\n                    value = value.replace(/^<(.*)>$/, '$1');\n                    break;\n                case 'm':\n                    break;\n                default:\n                    continue;\n            }\n            if (!currentData[variables[j]]) {\n                currentData[variables[j]] = [];\n            }\n            currentData[variables[j]].push(value);\n        }\n    }\n}\n//# sourceMappingURL=parseXYA.js.map","(function(){function a(d){for(var e=0,f=d.length-1,g=void 0,h=void 0,i=void 0,j=c(e,f);!0;){if(f<=e)return d[j];if(f==e+1)return d[e]>d[f]&&b(d,e,f),d[j];for(g=c(e,f),d[g]>d[f]&&b(d,g,f),d[e]>d[f]&&b(d,e,f),d[g]>d[e]&&b(d,g,e),b(d,g,e+1),h=e+1,i=f;!0;){do h++;while(d[e]>d[h]);do i--;while(d[i]>d[e]);if(i<h)break;b(d,h,i)}b(d,e,i),i<=j&&(e=h),i>=j&&(f=i-1)}}var b=function b(d,e,f){var _ref;return _ref=[d[f],d[e]],d[e]=_ref[0],d[f]=_ref[1],_ref},c=function c(d,e){return~~((d+e)/2)};'undefined'!=typeof module&&module.exports?module.exports=a:window.median=a})();\n","import { isAnyArray } from 'is-any-array';\nimport quickSelectMedian from 'median-quickselect';\n\nfunction median(input) {\n  if (!isAnyArray(input)) {\n    throw new TypeError('input must be an array');\n  }\n\n  if (input.length === 0) {\n    throw new TypeError('input must not be empty');\n  }\n\n  return quickSelectMedian(input.slice());\n}\n\nexport { median as default };\n","import convertTo3DZ from './convertTo3DZ';\nimport generateContourLines from './generateContourLines';\nexport default function add2D(result, options) {\n    let zData = convertTo3DZ(result.spectra);\n    if (!options.noContour) {\n        result.contourLines = generateContourLines(zData, options);\n        delete zData.z;\n    }\n    result.minMax = zData;\n}\n//# sourceMappingURL=add2D.js.map","import getMedian from 'ml-array-median';\nexport default function convertTo3DZ(spectra) {\n    let minZ = spectra[0].data.y[0];\n    let maxZ = minZ;\n    let ySize = spectra.length;\n    let xSize = spectra[0].data.x.length;\n    let z = new Array(ySize);\n    for (let i = 0; i < ySize; i++) {\n        z[i] = spectra[i].data.y;\n        for (let j = 0; j < xSize; j++) {\n            let value = z[i][j];\n            if (value < minZ)\n                minZ = value;\n            if (value > maxZ)\n                maxZ = value;\n        }\n    }\n    const firstX = spectra[0].data.x[0];\n    const lastX = spectra[0].data.x[spectra[0].data.x.length - 1]; // has to be -2 because it is a 1D array [x,y,x,y,...]\n    const firstY = spectra[0].pageValue;\n    const lastY = spectra[ySize - 1].pageValue;\n    // Because the min / max value are the only information about the matrix if we invert\n    // min and max we need to invert the array\n    if (firstX > lastX) {\n        for (let spectrum of z) {\n            spectrum.reverse();\n        }\n    }\n    if (firstY > lastY) {\n        z.reverse();\n    }\n    const medians = [];\n    for (let i = 0; i < z.length; i++) {\n        const row = Float64Array.from(z[i]);\n        for (let i = 0; i < row.length; i++) {\n            if (row[i] < 0)\n                row[i] = -row[i];\n        }\n        medians.push(getMedian(row));\n    }\n    const median = getMedian(medians);\n    return {\n        z,\n        minX: Math.min(firstX, lastX),\n        maxX: Math.max(firstX, lastX),\n        minY: Math.min(firstY, lastY),\n        maxY: Math.max(firstY, lastY),\n        minZ,\n        maxZ,\n        noise: median,\n    };\n}\n//# sourceMappingURL=convertTo3DZ.js.map","export default function generateContourLines(zData, options) {\n    let noise = zData.noise;\n    let z = zData.z;\n    let povarHeight0, povarHeight1, povarHeight2, povarHeight3;\n    let isOver0, isOver1, isOver2, isOver3;\n    let nbSubSpectra = z.length;\n    let nbPovars = z[0].length;\n    let pAx, pAy, pBx, pBy;\n    let x0 = zData.minX;\n    let xN = zData.maxX;\n    let dx = (xN - x0) / (nbPovars - 1);\n    let y0 = zData.minY;\n    let yN = zData.maxY;\n    let dy = (yN - y0) / (nbSubSpectra - 1);\n    let minZ = zData.minZ;\n    let maxZ = zData.maxZ;\n    // System.out.prvarln('y0 '+y0+' yN '+yN);\n    // -------------------------\n    // Povars attribution\n    //\n    // 0----1\n    // |  / |\n    // | /  |\n    // 2----3\n    //\n    // ---------------------d------\n    let iter = options.nbContourLevels * 2;\n    let contourLevels = new Array(iter);\n    let lineZValue;\n    for (let level = 0; level < iter; level++) {\n        // multiply by 2 for positif and negatif\n        let contourLevel = {};\n        contourLevels[level] = contourLevel;\n        let side = level % 2;\n        let factor = (maxZ - options.noiseMultiplier * noise) *\n            Math.exp((level >> 1) - options.nbContourLevels);\n        if (side === 0) {\n            lineZValue = factor + options.noiseMultiplier * noise;\n        }\n        else {\n            lineZValue = 0 - factor - options.noiseMultiplier * noise;\n        }\n        let lines = [];\n        contourLevel.zValue = lineZValue;\n        contourLevel.lines = lines;\n        if (lineZValue <= minZ || lineZValue >= maxZ)\n            continue;\n        for (let iSubSpectra = 0; iSubSpectra < nbSubSpectra - 1; iSubSpectra++) {\n            let subSpectra = z[iSubSpectra];\n            let subSpectraAfter = z[iSubSpectra + 1];\n            for (let povar = 0; povar < nbPovars - 1; povar++) {\n                povarHeight0 = subSpectra[povar];\n                povarHeight1 = subSpectra[povar + 1];\n                povarHeight2 = subSpectraAfter[povar];\n                povarHeight3 = subSpectraAfter[povar + 1];\n                isOver0 = povarHeight0 > lineZValue;\n                isOver1 = povarHeight1 > lineZValue;\n                isOver2 = povarHeight2 > lineZValue;\n                isOver3 = povarHeight3 > lineZValue;\n                // Example povar0 is over the plane and povar1 and\n                // povar2 are below, we find the varersections and add\n                // the segment\n                if (isOver0 !== isOver1 && isOver0 !== isOver2) {\n                    pAx =\n                        povar + (lineZValue - povarHeight0) / (povarHeight1 - povarHeight0);\n                    pAy = iSubSpectra;\n                    pBx = povar;\n                    pBy =\n                        iSubSpectra +\n                            (lineZValue - povarHeight0) / (povarHeight2 - povarHeight0);\n                    lines.push(pAx * dx + x0);\n                    lines.push(pAy * dy + y0);\n                    lines.push(pBx * dx + x0);\n                    lines.push(pBy * dy + y0);\n                }\n                // remove push does not help !!!!\n                if (isOver3 !== isOver1 && isOver3 !== isOver2) {\n                    pAx = povar + 1;\n                    pAy =\n                        iSubSpectra +\n                            1 -\n                            (lineZValue - povarHeight3) / (povarHeight1 - povarHeight3);\n                    pBx =\n                        povar +\n                            1 -\n                            (lineZValue - povarHeight3) / (povarHeight2 - povarHeight3);\n                    pBy = iSubSpectra + 1;\n                    lines.push(pAx * dx + x0);\n                    lines.push(pAy * dy + y0);\n                    lines.push(pBx * dx + x0);\n                    lines.push(pBy * dy + y0);\n                }\n                // test around the diagonal\n                if (isOver1 !== isOver2) {\n                    pAx =\n                        (povar +\n                            1 -\n                            (lineZValue - povarHeight1) / (povarHeight2 - povarHeight1)) *\n                            dx +\n                            x0;\n                    pAy =\n                        (iSubSpectra +\n                            (lineZValue - povarHeight1) / (povarHeight2 - povarHeight1)) *\n                            dy +\n                            y0;\n                    if (isOver1 !== isOver0) {\n                        pBx =\n                            povar +\n                                1 -\n                                (lineZValue - povarHeight1) / (povarHeight0 - povarHeight1);\n                        pBy = iSubSpectra;\n                        lines.push(pAx);\n                        lines.push(pAy);\n                        lines.push(pBx * dx + x0);\n                        lines.push(pBy * dy + y0);\n                    }\n                    if (isOver2 !== isOver0) {\n                        pBx = povar;\n                        pBy =\n                            iSubSpectra +\n                                1 -\n                                (lineZValue - povarHeight2) / (povarHeight0 - povarHeight2);\n                        lines.push(pAx);\n                        lines.push(pAy);\n                        lines.push(pBx * dx + x0);\n                        lines.push(pBy * dy + y0);\n                    }\n                    if (isOver1 !== isOver3) {\n                        pBx = povar + 1;\n                        pBy =\n                            iSubSpectra +\n                                (lineZValue - povarHeight1) / (povarHeight3 - povarHeight1);\n                        lines.push(pAx);\n                        lines.push(pAy);\n                        lines.push(pBx * dx + x0);\n                        lines.push(pBy * dy + y0);\n                    }\n                    if (isOver2 !== isOver3) {\n                        pBx =\n                            povar +\n                                (lineZValue - povarHeight2) / (povarHeight3 - povarHeight2);\n                        pBy = iSubSpectra + 1;\n                        lines.push(pAx);\n                        lines.push(pAy);\n                        lines.push(pBx * dx + x0);\n                        lines.push(pBy * dy + y0);\n                    }\n                }\n            }\n        }\n    }\n    return {\n        minX: zData.minX,\n        maxX: zData.maxX,\n        minY: zData.minY,\n        maxY: zData.maxY,\n        segments: contourLevels,\n    };\n}\n//# sourceMappingURL=generateContourLines.js.map","export const gyromagneticRatio = {\n    '1H': 267.52218744e6,\n    '2H': 41.065e6,\n    '3H': 285.3508e6,\n    '3He': -203.789e6,\n    '7Li': 103.962e6,\n    '13C': 67.28284e6,\n    '14N': 19.331e6,\n    '15N': -27.116e6,\n    '17O': -36.264e6,\n    '19F': 251.662e6,\n    '23Na': 70.761e6,\n    '27Al': 69.763e6,\n    '29Si': -53.19e6,\n    '31P': 108.291e6,\n    '57Fe': 8.681e6,\n    '63Cu': 71.118e6,\n    '67Zn': 16.767e6,\n    '129Xe': -73.997e6,\n};\n//# sourceMappingURL=index.js.map","export default function profiling(result, action, options) {\n    if (result.profiling) {\n        result.profiling.push({\n            action,\n            time: Date.now() - options.start,\n        });\n    }\n}\n//# sourceMappingURL=profiling.js.map","export default function simpleChromatogram(result) {\n    let data = result.spectra[0].data;\n    result.chromatogram = {\n        times: data.x.slice(),\n        series: {\n            intensity: {\n                dimension: 1,\n                data: data.y.slice(),\n            },\n        },\n    };\n}\n//# sourceMappingURL=simpleChromatogram.js.map","import add2D from './2d/add2D';\nimport { complexChromatogram } from './complexChromatogram';\nimport postProcessingNMR from './postProcessingNMR';\nimport profiling from './profiling';\nimport simpleChromatogram from './simpleChromatogram';\nexport default function postProcessing(entriesFlat, result, options) {\n    // converting Hz to ppm\n    postProcessingNMR(entriesFlat);\n    for (let entry of entriesFlat) {\n        if (Object.keys(entry.ntuples).length > 0) {\n            let newNtuples = [];\n            let keys = Object.keys(entry.ntuples);\n            for (let i = 0; i < keys.length; i++) {\n                let key = keys[i];\n                let values = entry.ntuples[key];\n                for (let j = 0; j < values.length; j++) {\n                    if (!newNtuples[j])\n                        newNtuples[j] = {};\n                    newNtuples[j][key] = values[j];\n                }\n            }\n            entry.ntuples = newNtuples;\n        }\n        if (entry.twoD && options.wantXY) {\n            add2D(entry, options);\n            profiling(result, 'Finished countour plot calculation', options);\n            if (!options.keepSpectra) {\n                delete entry.spectra;\n            }\n        }\n        // maybe it is a GC (HPLC) / MS. In this case we add a new format\n        if (options.chromatogram) {\n            if (entry.spectra.length > 1) {\n                complexChromatogram(entry);\n            }\n            else {\n                simpleChromatogram(entry);\n            }\n            profiling(result, 'Finished chromatogram calculation', options);\n        }\n        delete entry.tmp;\n    }\n}\n//# sourceMappingURL=postProcessing.js.map","import { gyromagneticRatio } from 'gyromagnetic-ratio';\nexport default function postProcessingNMR(entriesFlat) {\n    // specific NMR functions\n    for (let entry of entriesFlat) {\n        let observeFrequency = 0;\n        let shiftOffsetVal = 0;\n        for (let spectrum of entry.spectra) {\n            if (entry.ntuples && entry.ntuples.symbol) {\n                if (!observeFrequency && spectrum.observeFrequency) {\n                    observeFrequency = spectrum.observeFrequency;\n                }\n                if (!shiftOffsetVal && spectrum.shiftOffsetVal) {\n                    shiftOffsetVal = spectrum.shiftOffsetVal;\n                }\n            }\n            else {\n                observeFrequency = spectrum.observeFrequency;\n                shiftOffsetVal = spectrum.shiftOffsetVal;\n            }\n            if (observeFrequency) {\n                if (spectrum.xUnits && spectrum.xUnits.toUpperCase().includes('HZ')) {\n                    spectrum.xUnits = 'PPM';\n                    spectrum.xFactor = spectrum.xFactor / observeFrequency;\n                    spectrum.firstX = spectrum.firstX / observeFrequency;\n                    spectrum.lastX = spectrum.lastX / observeFrequency;\n                    spectrum.deltaX = spectrum.deltaX / observeFrequency;\n                    for (let i = 0; i < spectrum.data.x.length; i++) {\n                        spectrum.data.x[i] /= observeFrequency;\n                    }\n                }\n            }\n            if (shiftOffsetVal && spectrum.xUnits.toLowerCase().includes('ppm')) {\n                let shift = spectrum.firstX - shiftOffsetVal;\n                spectrum.firstX = spectrum.firstX - shift;\n                spectrum.lastX = spectrum.lastX - shift;\n                for (let i = 0; i < spectrum.data.x.length; i++) {\n                    spectrum.data.x[i] -= shift;\n                }\n            }\n            // we will check if some nucleus are missing ...\n            if (entry.ntuples && entry.ntuples.nucleus && entry.ntuples.symbol) {\n                for (let i = 0; i < entry.ntuples.nucleus.length; i++) {\n                    let symbol = entry.ntuples.symbol[i];\n                    let nucleus = entry.ntuples.nucleus[i];\n                    if (symbol.startsWith('F') && !nucleus) {\n                        if (symbol === 'F1') {\n                            // if F1 is defined we will use F2\n                            if (entry.tmp.$NUC2) {\n                                entry.ntuples.nucleus[i] = entry.tmp.$NUC2;\n                            }\n                            else {\n                                let f2index = entry.ntuples.symbol.indexOf('F2');\n                                if (f2index && entry.ntuples.nucleus[f2index]) {\n                                    entry.ntuples.nucleus[i] = entry.ntuples.nucleus[f2index];\n                                }\n                            }\n                        }\n                        if (symbol === 'F2')\n                            entry.ntuples.nucleus[i] = entry.tmp.$NUC1;\n                    }\n                    if (symbol === 'F2') {\n                        entry.yType = entry.ntuples.nucleus[0];\n                    }\n                }\n            }\n            if (observeFrequency &&\n                entry.ntuples &&\n                entry.ntuples.symbol &&\n                entry.ntuples.nucleus) {\n                let unit = '';\n                let pageSymbolIndex = entry.ntuples.symbol.indexOf(spectrum.pageSymbol);\n                if (entry.ntuples.units && entry.ntuples.units[pageSymbolIndex]) {\n                    unit = entry.ntuples.units[pageSymbolIndex];\n                }\n                if (unit !== 'PPM') {\n                    if (pageSymbolIndex !== 0) {\n                        throw Error('Not sure about this ntuples format');\n                    }\n                    let ratio0 = gyromagneticRatio[entry.ntuples.nucleus[0]];\n                    let ratio1 = gyromagneticRatio[entry.ntuples.nucleus[1]];\n                    if (!ratio0 || !ratio1) {\n                        throw Error('Problem with determination of gyromagnetic ratio');\n                    }\n                    let ratio = (ratio0 / ratio1) * observeFrequency;\n                    spectrum.pageValue /= ratio;\n                }\n            }\n        }\n    }\n}\n//# sourceMappingURL=postProcessingNMR.js.map","export default function prepareNtuplesDatatable(currentEntry, spectrum, kind) {\n    let xIndex = -1;\n    let yIndex = -1;\n    let firstVariable = '';\n    let secondVariable = '';\n    if (kind.indexOf('++') > 0) {\n        firstVariable = kind.replace(/.*\\(([a-zA-Z0-9]+)\\+\\+.*/, '$1');\n        secondVariable = kind.replace(/.*\\.\\.([a-zA-Z0-9]+).*/, '$1');\n    }\n    else {\n        kind = kind.replace(/[^a-zA-Z]/g, '');\n        firstVariable = kind.charAt(0);\n        secondVariable = kind.charAt(1);\n        spectrum.variables = {};\n        for (let symbol of kind) {\n            let lowerCaseSymbol = symbol.toLowerCase();\n            let index = currentEntry.ntuples.symbol.indexOf(symbol);\n            if (index === -1)\n                throw Error(`Symbol undefined: ${symbol}`);\n            spectrum.variables[lowerCaseSymbol] = {};\n            for (let key in currentEntry.ntuples) {\n                if (currentEntry.ntuples[key][index]) {\n                    spectrum.variables[lowerCaseSymbol][key.replace(/^var/, '')] =\n                        currentEntry.ntuples[key][index];\n                }\n            }\n        }\n    }\n    xIndex = currentEntry.ntuples.symbol.indexOf(firstVariable);\n    yIndex = currentEntry.ntuples.symbol.indexOf(secondVariable);\n    if (xIndex === -1)\n        xIndex = 0;\n    if (yIndex === -1)\n        yIndex = 0;\n    if (currentEntry.ntuples.first) {\n        if (currentEntry.ntuples.first.length > xIndex) {\n            spectrum.firstX = currentEntry.ntuples.first[xIndex];\n        }\n        if (currentEntry.ntuples.first.length > yIndex) {\n            spectrum.firstY = currentEntry.ntuples.first[yIndex];\n        }\n    }\n    if (currentEntry.ntuples.last) {\n        if (currentEntry.ntuples.last.length > xIndex) {\n            spectrum.lastX = currentEntry.ntuples.last[xIndex];\n        }\n        if (currentEntry.ntuples.last.length > yIndex) {\n            spectrum.lastY = currentEntry.ntuples.last[yIndex];\n        }\n    }\n    if (currentEntry.ntuples.vardim &&\n        currentEntry.ntuples.vardim.length > xIndex) {\n        spectrum.nbPoints = currentEntry.ntuples.vardim[xIndex];\n    }\n    if (currentEntry.ntuples.factor) {\n        if (currentEntry.ntuples.factor.length > xIndex) {\n            spectrum.xFactor = currentEntry.ntuples.factor[xIndex];\n        }\n        if (currentEntry.ntuples.factor.length > yIndex) {\n            spectrum.yFactor = currentEntry.ntuples.factor[yIndex];\n        }\n    }\n    if (currentEntry.ntuples.units) {\n        if (currentEntry.ntuples.units.length > xIndex) {\n            if (currentEntry.ntuples.varname &&\n                currentEntry.ntuples.varname[xIndex]) {\n                spectrum.xUnits = `${currentEntry.ntuples.varname[xIndex]} [${currentEntry.ntuples.units[xIndex]}]`;\n            }\n            else {\n                spectrum.xUnits = currentEntry.ntuples.units[xIndex];\n            }\n        }\n        if (currentEntry.ntuples.units.length > yIndex) {\n            if (currentEntry.ntuples.varname &&\n                currentEntry.ntuples.varname[yIndex]) {\n                spectrum.yUnits = `${currentEntry.ntuples.varname[yIndex]} [${currentEntry.ntuples.units[yIndex]}]`;\n            }\n            else {\n                spectrum.yUnits = currentEntry.ntuples.units[yIndex];\n            }\n        }\n    }\n}\n//# sourceMappingURL=prepareNtuplesDatatable.js.map","export default function prepareSpectrum(spectrum) {\n    if (!spectrum.xFactor)\n        spectrum.xFactor = 1;\n    if (!spectrum.yFactor)\n        spectrum.yFactor = 1;\n}\n//# sourceMappingURL=prepareSpectrum.js.map","import { parseString } from 'dynamic-typing';\nimport { ensureString } from 'ensure-string';\nimport { isMSField, convertMSFieldToLabel } from './complexChromatogram';\nimport convertToFloatArray from './convertToFloatArray';\nimport fastParseXYData from './parse/fastParseXYData';\nimport parsePeakTable from './parse/parsePeakTable';\nimport parseXYA from './parse/parseXYA';\nimport postProcessing from './postProcessing';\nimport prepareNtuplesDatatable from './prepareNtuplesDatatable';\nimport prepareSpectrum from './prepareSpectrum';\nimport profiling from './profiling';\n// the following RegExp can only be used for XYdata, some peakTables have values with a \"E-5\" ...\nconst ntuplesSeparatorRegExp = /[ \\t]*,[ \\t]*/;\nconst defaultOptions = {\n    keepRecordsRegExp: /^$/,\n    canonicDataLabels: true,\n    canonicMetadataLabels: false,\n    dynamicTyping: true,\n    withoutXY: false,\n    chromatogram: false,\n    keepSpectra: false,\n    noContour: false,\n    nbContourLevels: 7,\n    noiseMultiplier: 5,\n    profiling: false,\n};\n/**\n * Conversion options\n * @typedef {object} ConvertOptions\n * @property {RegExp} [keepRecordsRegExp=/^$/] - By default we don't keep meta information.\n * @property {boolean} [canonicDataLabels=true] - Canonize the Labels (uppercase without symbol).\n * @property {boolean} [canonicMetadataLabels=false] - Canonize the metadata Labels (uppercase without symbol).\n * @property {boolean} [dynamicTyping=false] - Convert numbers to Number.\n * @property {boolean} [withoutXY=false] - Remove the XY data.\n * @property {boolean} [chromatogram=false] - Special post-processing for GC / HPLC / MS.\n * @property {boolean} [keepSpectra=false] - Force to keep the spectra in case of 2D.\n * @property {boolean} [noContour=false] - Don't calculate countour in case of 2D.\n * @property {number} [nbContourLevels=7] - Number of positive / negative contour levels to calculate.\n * @property {number} [noiseMultiplier=5] - Define for 2D the level as 5 times the median as default.\n * @property {boolean} [profiling=false] - Add profiling information.\n */\n/**\n *\n * @typedef {object} Ntuples\n * @property {string[]} [varname]\n * @property {string[]} [symbol]\n * @property {string[]} [vartype]\n * @property {string[]} [varform]\n * @property {number[]} [vardim]\n * @property {string[]} [units]\n * @property {number[]} [factor]\n * @property {number[]} [first]\n * @property {number[]} [last]\n * @property {number[]} [min]\n * @property {number[]} [max]\n * @property {string[]} [nucleus]\n */\n/**\n * @typedef { Record<string, any> } Spectrum\n * @property {Record<string, number[]>} [data]\n * @property {number} [firstX] - first X value\n * @property {number} [lastX] - last X value\n * @property {number} [deltaX] - distance between 2 consecutive x axis values\n * @property {number} [yFactor] - y axis scaling factor\n * @property {number} [xFactor] - x axis scaling factor\n * @property {number} [nbPoints] - Number of points\n */\n/**\n *\n * @typedef {object} Entry\n * @property {Spectrum[]} spectra\n * @property {Ntuples} ntuples\n * @property {object} meta\n * @property {object} info\n * @property {object} tmp\n * @property {string} [title]\n * @property {string} [dataType]\n * @property {string} [dataClass]\n * @property {boolean} [twoD]\n */\n/**\n *\n * @typedef { object } ConvertResult\n * @property { object[] | boolean } profiling\n * @property { string[] } logs\n * @property { object[] } entries\n * @property { Entry[] } flatten\n */\n/**\n * Parse a jcamp.\n * The data can be provide as a string or array buffer. In this later case\n * we will convert it first to a string before parsing.\n * @param {string|ArrayBuffer|Uint8Array} jcamp\n * @param {ConvertOptions} [options]\n * @returns {ConvertResult}\n */\nexport function convert(jcamp, options = {}) {\n    jcamp = ensureString(jcamp);\n    options = { ...defaultOptions, ...options };\n    options.wantXY = !options.withoutXY;\n    options.start = Date.now();\n    let entriesFlat = [];\n    let result = {\n        profiling: options.profiling ? [] : false,\n        logs: [],\n        entries: [],\n    };\n    let tmpResult = { children: [] };\n    let currentEntry = tmpResult;\n    let parentsStack = [];\n    let spectrum = {};\n    if (typeof jcamp !== 'string') {\n        throw new TypeError('the JCAMP should be a string');\n    }\n    profiling(result, 'Before split to LDRS', options);\n    let ldrs = jcamp.replace(/[\\r\\n]+##/g, '\\n##').split('\\n##');\n    profiling(result, 'Split to LDRS', options);\n    if (ldrs[0])\n        ldrs[0] = ldrs[0].replace(/^[\\r\\n ]*##/, '');\n    for (let ldr of ldrs) {\n        // This is a new LDR\n        let position = ldr.indexOf('=');\n        let dataLabel = position > 0 ? ldr.substring(0, position) : ldr;\n        let dataValue = position > 0 ? ldr.substring(position + 1).trim() : '';\n        let canonicDataLabel = dataLabel.replace(/[_ -]/g, '').toUpperCase();\n        if (canonicDataLabel === 'DATATABLE') {\n            let endLine = dataValue.indexOf('\\n');\n            if (endLine === -1)\n                endLine = dataValue.indexOf('\\r');\n            if (endLine > 0) {\n                // ##DATA TABLE= (X++(I..I)), XYDATA\n                // We need to find the variables\n                let infos = dataValue.substring(0, endLine).split(/[ ,;\\t]+/);\n                prepareNtuplesDatatable(currentEntry, spectrum, infos[0]);\n                spectrum.datatable = infos[0];\n                if (infos[1] && infos[1].indexOf('PEAKS') > -1) {\n                    canonicDataLabel = 'PEAKTABLE';\n                }\n                else if (infos[1] &&\n                    (infos[1].indexOf('XYDATA') || infos[0].indexOf('++') > 0)) {\n                    canonicDataLabel = 'XYDATA';\n                    if (spectrum.nbPoints) {\n                        spectrum.deltaX =\n                            (spectrum.lastX - spectrum.firstX) / (spectrum.nbPoints - 1);\n                    }\n                }\n            }\n        }\n        if (canonicDataLabel === 'XYDATA') {\n            if (options.wantXY) {\n                prepareSpectrum(spectrum);\n                // well apparently we should still consider it is a PEAK TABLE if there are no '++' after\n                if (dataValue.match(/.*\\+\\+.*/)) {\n                    // ex: (X++(Y..Y))\n                    if (spectrum.nbPoints) {\n                        spectrum.deltaX =\n                            (spectrum.lastX - spectrum.firstX) / (spectrum.nbPoints - 1);\n                    }\n                    fastParseXYData(spectrum, dataValue, result);\n                }\n                else {\n                    parsePeakTable(spectrum, dataValue, result);\n                }\n                currentEntry.spectra.push(spectrum);\n                spectrum = {};\n            }\n            continue;\n        }\n        else if (canonicDataLabel === 'PEAKTABLE') {\n            if (options.wantXY) {\n                prepareSpectrum(spectrum);\n                parsePeakTable(spectrum, dataValue, result);\n                currentEntry.spectra.push(spectrum);\n                spectrum = {};\n            }\n            continue;\n        }\n        if (canonicDataLabel === 'PEAKASSIGNMENTS') {\n            if (options.wantXY) {\n                if (dataValue.match(/.*([^A-Z]*).*/)) {\n                    // ex: (XYA)\n                    parseXYA(spectrum, dataValue);\n                }\n                currentEntry.spectra.push(spectrum);\n                spectrum = {};\n            }\n            continue;\n        }\n        if (canonicDataLabel === 'TITLE') {\n            let parentEntry = currentEntry;\n            if (!parentEntry.children) {\n                parentEntry.children = [];\n            }\n            currentEntry = {\n                spectra: [],\n                ntuples: {},\n                info: {},\n                meta: {},\n                tmp: {}, // tmp information we need to keep for postprocessing\n            };\n            parentEntry.children.push(currentEntry);\n            parentsStack.push(parentEntry);\n            entriesFlat.push(currentEntry);\n            currentEntry.title = dataValue;\n        }\n        else if (canonicDataLabel === 'DATATYPE') {\n            currentEntry.dataType = dataValue;\n            if (dataValue.match(/(^nd|\\snd\\s)/i)) {\n                currentEntry.twoD = true;\n            }\n        }\n        else if (canonicDataLabel === 'NTUPLES') {\n            if (dataValue.match(/(^nd|\\snd\\s)/i)) {\n                currentEntry.twoD = true;\n            }\n        }\n        else if (canonicDataLabel === 'DATACLASS') {\n            currentEntry.dataClass = dataValue;\n        }\n        else if (canonicDataLabel === 'XUNITS') {\n            spectrum.xUnits = dataValue;\n        }\n        else if (canonicDataLabel === 'YUNITS') {\n            spectrum.yUnits = dataValue;\n        }\n        else if (canonicDataLabel === 'FIRSTX') {\n            spectrum.firstX = Number(dataValue);\n        }\n        else if (canonicDataLabel === 'LASTX') {\n            spectrum.lastX = Number(dataValue);\n        }\n        else if (canonicDataLabel === 'FIRSTY') {\n            spectrum.firstY = Number(dataValue);\n        }\n        else if (canonicDataLabel === 'LASTY') {\n            spectrum.lastY = Number(dataValue);\n        }\n        else if (canonicDataLabel === 'NPOINTS') {\n            spectrum.nbPoints = Number(dataValue);\n        }\n        else if (canonicDataLabel === 'XFACTOR') {\n            spectrum.xFactor = Number(dataValue);\n        }\n        else if (canonicDataLabel === 'YFACTOR') {\n            spectrum.yFactor = Number(dataValue);\n        }\n        else if (canonicDataLabel === 'MAXX') {\n            spectrum.maxX = Number(dataValue);\n        }\n        else if (canonicDataLabel === 'MINX') {\n            spectrum.minX = Number(dataValue);\n        }\n        else if (canonicDataLabel === 'MAXY') {\n            spectrum.maxY = Number(dataValue);\n        }\n        else if (canonicDataLabel === 'MINY') {\n            spectrum.minY = Number(dataValue);\n        }\n        else if (canonicDataLabel === 'DELTAX') {\n            spectrum.deltaX = Number(dataValue);\n        }\n        else if (canonicDataLabel === '.OBSERVEFREQUENCY' ||\n            canonicDataLabel === '$SFO1') {\n            if (!spectrum.observeFrequency) {\n                spectrum.observeFrequency = Number(dataValue);\n            }\n        }\n        else if (canonicDataLabel === '.OBSERVENUCLEUS') {\n            if (!spectrum.xType) {\n                currentEntry.xType = dataValue.replace(/[^a-zA-Z0-9]/g, '');\n            }\n        }\n        else if (canonicDataLabel === '$OFFSET') {\n            // OFFSET for Bruker spectra\n            currentEntry.shiftOffsetNum = 0;\n            if (!spectrum.shiftOffsetVal) {\n                spectrum.shiftOffsetVal = Number(dataValue);\n            }\n        }\n        else if (canonicDataLabel === '$REFERENCEPOINT') {\n            // OFFSET for Varian spectra\n            // if we activate this part it does not work for ACD specmanager\n            //         } else if (canonicDataLabel=='.SHIFTREFERENCE') {   // OFFSET FOR Bruker Spectra\n            //                 var parts = dataValue.split(/ *, */);\n            //                 currentEntry.shiftOffsetNum = parseInt(parts[2].trim());\n            //                 spectrum.shiftOffsetVal = Number(parts[3].trim());\n        }\n        else if (canonicDataLabel === 'VARNAME') {\n            currentEntry.ntuples.varname = dataValue.split(ntuplesSeparatorRegExp);\n        }\n        else if (canonicDataLabel === 'SYMBOL') {\n            currentEntry.ntuples.symbol = dataValue.split(ntuplesSeparatorRegExp);\n        }\n        else if (canonicDataLabel === 'VARTYPE') {\n            currentEntry.ntuples.vartype = dataValue.split(ntuplesSeparatorRegExp);\n        }\n        else if (canonicDataLabel === 'VARFORM') {\n            currentEntry.ntuples.varform = dataValue.split(ntuplesSeparatorRegExp);\n        }\n        else if (canonicDataLabel === 'VARDIM') {\n            currentEntry.ntuples.vardim = convertToFloatArray(dataValue.split(ntuplesSeparatorRegExp));\n        }\n        else if (canonicDataLabel === 'UNITS') {\n            currentEntry.ntuples.units = dataValue.split(ntuplesSeparatorRegExp);\n        }\n        else if (canonicDataLabel === 'FACTOR') {\n            currentEntry.ntuples.factor = convertToFloatArray(dataValue.split(ntuplesSeparatorRegExp));\n        }\n        else if (canonicDataLabel === 'FIRST') {\n            currentEntry.ntuples.first = convertToFloatArray(dataValue.split(ntuplesSeparatorRegExp));\n        }\n        else if (canonicDataLabel === 'LAST') {\n            currentEntry.ntuples.last = convertToFloatArray(dataValue.split(ntuplesSeparatorRegExp));\n        }\n        else if (canonicDataLabel === 'MIN') {\n            currentEntry.ntuples.min = convertToFloatArray(dataValue.split(ntuplesSeparatorRegExp));\n        }\n        else if (canonicDataLabel === 'MAX') {\n            currentEntry.ntuples.max = convertToFloatArray(dataValue.split(ntuplesSeparatorRegExp));\n        }\n        else if (canonicDataLabel === '.NUCLEUS') {\n            if (currentEntry.ntuples) {\n                currentEntry.ntuples.nucleus = dataValue.split(ntuplesSeparatorRegExp);\n            }\n        }\n        else if (canonicDataLabel === 'PAGE') {\n            spectrum.page = dataValue.trim();\n            spectrum.pageValue = Number(dataValue.replace(/^.*=/, ''));\n            spectrum.pageSymbol = spectrum.page.replace(/[=].*/, '');\n        }\n        else if (canonicDataLabel === 'RETENTIONTIME') {\n            spectrum.pageValue = Number(dataValue);\n        }\n        else if (isMSField(canonicDataLabel)) {\n            spectrum[convertMSFieldToLabel(canonicDataLabel)] = dataValue;\n        }\n        else if (canonicDataLabel === 'SAMPLEDESCRIPTION') {\n            spectrum.sampleDescription = dataValue;\n        }\n        else if (canonicDataLabel.startsWith('$NUC')) {\n            if (!currentEntry.tmp[canonicDataLabel] && !dataValue.includes('off')) {\n                currentEntry.tmp[canonicDataLabel] = dataValue.replace(/[<>]/g, '');\n            }\n        }\n        else if (canonicDataLabel === 'END') {\n            currentEntry = parentsStack.pop();\n        }\n        if (currentEntry &&\n            currentEntry.info &&\n            currentEntry.meta &&\n            canonicDataLabel.match(options.keepRecordsRegExp)) {\n            let value = dataValue.trim();\n            let target, label;\n            if (dataLabel.startsWith('$')) {\n                label = options.canonicMetadataLabels\n                    ? canonicDataLabel.substring(1)\n                    : dataLabel.substring(1);\n                target = currentEntry.meta;\n            }\n            else {\n                label = options.canonicDataLabels ? canonicDataLabel : dataLabel;\n                target = currentEntry.info;\n            }\n            if (options.dynamicTyping) {\n                value = parseString(value);\n            }\n            if (target[label]) {\n                if (!Array.isArray(target[label])) {\n                    target[label] = [target[label]];\n                }\n                target[label].push(value);\n            }\n            else {\n                target[label] = value;\n            }\n        }\n    }\n    profiling(result, 'Finished parsing', options);\n    postProcessing(entriesFlat, result, options);\n    profiling(result, 'Total time', options);\n    /*\n    if (result.children && result.children.length>0) {\n      result = { ...result, ...result.children[0] };\n    }\n    */\n    result.entries = tmpResult.children;\n    result.flatten = entriesFlat;\n    return result;\n}\n//# sourceMappingURL=convert.js.map","import { convert } from 'jcampconverter';\nimport { Analysis } from '../Analysis';\n/**\n * Creates a new Analysis from a JCAMP string\n * @param {string} jcamp - String containing the JCAMP data\n * @param {object} [options={}]\n * @param {object} [options.id=Math.random()]\n * @param {string} [options.label=options.id] human redeable label\n * @param {string} [options.spectrumCallback] a callback to apply on variables when creating spectrum\n * @return {Analysis} - New class element with the given data\n */\nexport function fromJcamp(jcamp, options = {}) {\n    let analysis = new Analysis(options);\n    addJcamp(analysis, jcamp);\n    return analysis;\n}\nfunction addJcamp(analysis, jcamp) {\n    let converted = convert(jcamp, {\n        keepRecordsRegExp: /.*/,\n    });\n    for (let entry of converted.flatten) {\n        if (!entry.spectra || !entry.spectra[0])\n            continue;\n        let currentSpectrum = entry.spectra[0];\n        // we ensure variables\n        if (!currentSpectrum.variables) {\n            const variables = {};\n            currentSpectrum.variables = variables;\n            variables.x = {\n                label: currentSpectrum.xUnits,\n                symbol: 'X',\n                data: currentSpectrum.data.x || currentSpectrum.data.X,\n            };\n            variables.y = {\n                label: currentSpectrum.yUnits,\n                symbol: 'Y',\n                data: currentSpectrum.data.y || currentSpectrum.data.Y,\n            };\n        }\n        else {\n            for (let key in currentSpectrum.variables) {\n                const variable = currentSpectrum.variables[key];\n                if (variable.label)\n                    continue;\n                variable.label = variable.name || variable.symbol || key;\n                if (variable.units && !variable.label.includes(variable.units)) {\n                    variable.label += ` [${variable.units}]`;\n                }\n            }\n        }\n        analysis.pushSpectrum(currentSpectrum.variables, {\n            dataType: entry.dataType,\n            title: entry.title,\n            meta: entry.meta,\n        });\n    }\n}\n//# sourceMappingURL=data:application/json;base64,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","export const addInfoData = (data, keys = Object.keys(data), prefix = '##$') => {\n    let header = '';\n    for (const key of keys) {\n        header +=\n            typeof data[key] === 'object'\n                ? `${prefix}${key}=${JSON.stringify(data[key])}\\n`\n                : `${prefix}${key}=${data[key]}\\n`;\n    }\n    return header;\n};\n//# sourceMappingURL=addInfoData.js.map","import { isAnyArray } from 'is-any-array';\nexport function checkNumberOrArray(data) {\n    if (!isAnyArray(data) || isAnyArray(data[0])) {\n        throw new Error(`x and y data should be an array of numbers`);\n    }\n}\n//# sourceMappingURL=checkNumberOrArray.js.map","import { isAnyArray } from 'is-any-array';\nimport { matrixMinMaxZ, xMinMaxValues, } from 'ml-spectra-processing';\nimport { checkMatrix } from './checkMatrix';\nimport { checkNumberOrArray } from './checkNumberOrArray';\nexport function getExtremeValues(data) {\n    if (isAnyArray(data[0])) {\n        checkMatrix(data);\n        const firstRow = data[0];\n        return {\n            firstLast: {\n                first: firstRow[0],\n                last: data[data.length - 1][data[0].length - 1],\n            },\n            minMax: matrixMinMaxZ(data),\n        };\n    }\n    checkNumberOrArray(data);\n    return {\n        firstLast: {\n            first: data[0],\n            last: data[data.length - 1],\n        },\n        minMax: xMinMaxValues(data),\n    };\n}\n//# sourceMappingURL=getExtremeValues.js.map","import { isAnyArray } from 'is-any-array';\nexport function checkMatrix(data) {\n    if (!isAnyArray(data) || !isAnyArray(data[0])) {\n        throw new Error(`2D data should be a matrix`);\n    }\n}\n//# sourceMappingURL=checkMatrix.js.map","import { addInfoData } from './utils/addInfoData';\nimport { getExtremeValues } from './utils/getExtremeValues';\n/**\n * Parse from a xyxy data array\n * @param variables - Variables to convert to jcamp\n * @param [options={}] - options that allows to add meta data in the jcamp\n * @return JCAMP-DX text file corresponding to the variables\n */\nexport default function creatorNtuples(variables, options) {\n    const { meta = {}, info = {} } = options;\n    const { title = '', owner = '', origin = '', dataType = '' } = info;\n    const symbol = [];\n    const varName = [];\n    const varType = [];\n    const varDim = [];\n    const units = [];\n    const first = [];\n    const last = [];\n    const min = [];\n    const max = [];\n    const keys = Object.keys(variables);\n    for (let i = 0; i < keys.length; i++) {\n        const key = keys[i];\n        let variable = variables[key];\n        if (!variable)\n            continue;\n        let name = variable?.label.replace(/ *\\[.*/, '');\n        let unit = variable?.label.replace(/.*\\[(?<units>.*)\\].*/, '$<units>');\n        const { firstLast, minMax } = getExtremeValues(variable.data);\n        symbol.push(variable.symbol || key);\n        varName.push(name || key);\n        varDim.push(variable.data.length);\n        first.push(firstLast.first);\n        last.push(firstLast.last);\n        max.push(minMax.max);\n        min.push(minMax.min);\n        if (variable.isDependent !== undefined) {\n            varType.push(variable.isDependent ? 'DEPENDENT' : 'INDEPENDENT');\n        }\n        else {\n            varType.push(variable.isDependent !== undefined\n                ? !variable.isDependent\n                : i === 0\n                    ? 'INDEPENDENT'\n                    : 'DEPENDENT');\n        }\n        units.push(variable.units || unit || '');\n    }\n    let header = `##TITLE=${title}\n##JCAMP-DX=6.00\n##DATA TYPE=${dataType}\n##DATA CLASS= NTUPLES\n##ORIGIN=${origin}\n##OWNER=${owner}\\n`;\n    const infoKeys = Object.keys(info).filter((e) => !['title', 'owner', 'origin', 'datatype'].includes(e.toLocaleLowerCase()));\n    header += addInfoData(info, infoKeys, '##');\n    header += addInfoData(meta);\n    header += `##NTUPLES= ${dataType}\n##VAR_NAME=  ${varName.join()}\n##SYMBOL=    ${symbol.join()}\n##VAR_TYPE=  ${varType.join()}\n##VAR_DIM=   ${varDim.join()}\n##UNITS=     ${units.join()}\n##FIRST=     ${first.join()}\n##LAST=      ${last.join()}\n##MIN=       ${min.join()}\n##MAX=       ${max.join()}\n##PAGE= N=1\\n`;\n    header += `##DATA TABLE= (${symbol.join('')}..${symbol.join('')}), PEAKS\\n`;\n    for (let i = 0; i < variables.x.data.length; i++) {\n        let point = [];\n        for (let key of keys) {\n            let variable = variables[key];\n            if (!variable)\n                continue;\n            point.push(variable.data[i]);\n        }\n        header += `${point.join('\\t')}\\n`;\n    }\n    header += `##END NTUPLES= ${dataType}\\n`;\n    header += '##END=\\n##END=';\n    return header;\n}\n//# sourceMappingURL=creatorNtuples.js.map","export function getFactorNumber(minMax, maxValue = 2 ** 31 - 1) {\n    let factor;\n    if (minMax.min < 0) {\n        if (minMax.max > 0) {\n            factor = Math.max(-minMax.min, minMax.max) / maxValue;\n        }\n        else {\n            factor = -minMax.min / maxValue;\n        }\n    }\n    else {\n        factor = minMax.max / maxValue;\n    }\n    return factor;\n}\n//# sourceMappingURL=getFactorNumber.js.map","import { xMinMaxValues } from 'ml-spectra-processing';\nimport { getFactorNumber } from './getFactorNumber';\nexport function getBestFactor(array, options = {}) {\n    const { maxValue, factor, minMax } = options;\n    if (factor !== undefined) {\n        return factor;\n    }\n    // is there non integer number ?\n    let onlyInteger = true;\n    for (let y of array) {\n        if (Math.round(y) !== y) {\n            onlyInteger = false;\n            break;\n        }\n    }\n    if (onlyInteger) {\n        return 1;\n    }\n    // we need to rescale the values\n    // need to find the max and min values\n    const extremeValues = minMax || xMinMaxValues(array);\n    return getFactorNumber(extremeValues, maxValue);\n}\n//# sourceMappingURL=getBestFactor.js.map","/**\n * Reconvert number to original value\n * @param number Number used for computation\n * @param factor Multiplying factor\n * @returns Original value\n */\nexport function getNumber(number, factor) {\n    if (factor !== 1)\n        number /= factor;\n    const rounded = Math.round(number);\n    if (rounded !== number && Math.abs(rounded - number) <= Number.EPSILON) {\n        return rounded;\n    }\n    return number;\n}\n//# sourceMappingURL=getNumber.js.map","import { getNumber } from './getNumber';\nexport function peakTableCreator(data, options = {}) {\n    const { xFactor = 1, yFactor = 1 } = options.info || {};\n    let firstX = Number.POSITIVE_INFINITY;\n    let lastX = Number.NEGATIVE_INFINITY;\n    let firstY = Number.POSITIVE_INFINITY;\n    let lastY = Number.NEGATIVE_INFINITY;\n    let lines = [];\n    for (let i = 0; i < data.x.length; i++) {\n        let x = data.x[i];\n        let y = data.y[i];\n        if (firstX > x) {\n            firstX = x;\n        }\n        if (lastX < x) {\n            lastX = x;\n        }\n        if (firstY > y) {\n            firstY = y;\n        }\n        if (lastY < y) {\n            lastY = y;\n        }\n    }\n    lines.push(`##FIRSTX=${firstX}`);\n    lines.push(`##LASTX=${lastX}`);\n    lines.push(`##FIRSTY=${firstY}`);\n    lines.push(`##LASTY=${lastY}`);\n    lines.push(`##XFACTOR=${xFactor}`);\n    lines.push(`##YFACTOR=${yFactor}`);\n    lines.push('##PEAK TABLE=(XY..XY)');\n    for (let i = 0; i < data.x.length; i++) {\n        lines.push(`${getNumber(data.x[i], xFactor)} ${getNumber(data.y[i], yFactor)}`);\n    }\n    return lines;\n}\n//# sourceMappingURL=peakTableCreator.js.map","import { xDivide } from 'ml-spectra-processing';\nexport function rescaleAndEnsureInteger(data, factor = 1) {\n    if (factor === 1)\n        return data.map((value) => Math.round(value));\n    return xDivide(data, factor);\n}\n//# sourceMappingURL=rescaleAndEnsureInteger.js.map","/**\n * class encodes a integer vector as a String in order to store it in a text file.\n * The algorithms used to encode the data are describe in:\n *            http://www.iupac.org/publications/pac/pdf/2001/pdf/7311x1765.pdf\n */\nconst newLine = '\\n';\nconst pseudoDigits = [\n    ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'],\n    ['@', 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I'],\n    ['@', 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i'],\n    ['%', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R'],\n    ['%', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r'],\n    [' ', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', 's'],\n];\nconst SQZ_P = 1;\nconst SQZ_N = 2;\nconst DIF_P = 3;\nconst DIF_N = 4;\nconst DUP = 5;\nconst maxLinelength = 100;\n/**\n * This function encodes the given vector. The xyEncoding format is specified by the\n * xyEncoding option\n * @param xyEncoding: ('FIX','SQZ','DIF','DIFDUP','CVS','PAC') Default 'DIFDUP'\n * @return {string}\n */\nexport function vectorEncoder(data, firstX, intervalX, xyEncoding) {\n    switch (xyEncoding) {\n        case 'FIX':\n            return fixEncoding(data, firstX, intervalX);\n        case 'SQZ':\n            return squeezedEncoding(data, firstX, intervalX);\n        case 'DIF':\n            return differenceEncoding(data, firstX, intervalX);\n        case 'DIFDUP':\n            return differenceDuplicateEncoding(data, firstX, intervalX);\n        case 'CSV':\n            return commaSeparatedValuesEncoding(data, firstX, intervalX);\n        case 'PAC':\n            return packedEncoding(data, firstX, intervalX);\n        default:\n            return differenceEncoding(data, firstX, intervalX);\n    }\n}\n/**\n * @private\n * No data compression used. The data is separated by a comma(',').\n */\nexport function commaSeparatedValuesEncoding(data, firstX, intervalX) {\n    return fixEncoding(data, firstX, intervalX, ',');\n}\n/**\n * @private\n * No data compression used. The data is separated by the specified separator.\n */\nexport function fixEncoding(data, firstX, intervalX, separator = ' ') {\n    let outputData = '';\n    let j = 0;\n    let dataLength = data.length;\n    while (j < dataLength - 7) {\n        outputData += Math.ceil(firstX + j * intervalX);\n        for (let i = 0; i < 8; i++) {\n            outputData += `${separator}${data[j++]}`;\n        }\n        outputData += newLine;\n    }\n    if (j < dataLength) {\n        // We add last numbers\n        outputData += Math.ceil(firstX + j * intervalX);\n        for (let i = j; i < dataLength; i++) {\n            outputData += `${separator}${data[i]}`;\n        }\n    }\n    return outputData;\n}\n/**\n * @private\n * No data compression used. The data is separated by the sign of the number.\n */\nexport function packedEncoding(data, firstX, intervalX) {\n    let outputData = '';\n    let j = 0;\n    let dataLength = data.length;\n    while (j < dataLength - 7) {\n        outputData += Math.ceil(firstX + j * intervalX);\n        for (let i = 0; i < 8; i++) {\n            outputData += data[j] < 0 ? data[j++] : `+${data[j++]}`;\n        }\n        outputData += newLine;\n    }\n    if (j < dataLength) {\n        // We add last numbers\n        outputData += Math.ceil(firstX + j * intervalX);\n        for (let i = j; i < dataLength; i++) {\n            outputData += data[i] < 0 ? data[i] : `+${data[i]}`;\n        }\n    }\n    return outputData;\n}\n/**\n * @private\n * Data compression is possible using the squeezed form (SQZ) in which the delimiter, the leading digit,\n * and sign are replaced by a pseudo-digit from Table 1. For example, the Y-values 30, 32 would be\n * represented as C0C2.\n */\nexport function squeezedEncoding(data, firstX, intervalX) {\n    let outputData = '';\n    // String outputData = new String();\n    let j = 0;\n    let dataLength = data.length;\n    while (j < dataLength - 10) {\n        outputData += Math.ceil(firstX + j * intervalX);\n        for (let i = 0; i < 10; i++) {\n            outputData += squeezedDigit(data[j++].toString());\n        }\n        outputData += newLine;\n    }\n    if (j < dataLength) {\n        // We add last numbers\n        outputData += Math.ceil(firstX + j * intervalX);\n        for (let i = j; i < dataLength; i++) {\n            outputData += squeezedDigit(data[i].toString());\n        }\n    }\n    return outputData;\n}\n/**\n * @private\n * Duplicate suppression xyEncoding\n */\nexport function differenceDuplicateEncoding(data, firstX, intervalX) {\n    let mult = 0;\n    let index = 0;\n    let charCount = 0;\n    // We built a string where we store the encoded data.\n    let encodedData = '';\n    let encodedNumber = '';\n    let temp = '';\n    // We calculate the differences vector\n    let diffData = new Array(data.length - 1);\n    for (let i = 0; i < diffData.length; i++) {\n        diffData[i] = data[i + 1] - data[i];\n    }\n    // We simulate a line carry\n    let numDiff = diffData.length;\n    while (index < numDiff) {\n        if (charCount === 0) {\n            // Start line\n            encodedNumber = `${Math.ceil(firstX + index * intervalX)}${squeezedDigit(data[index].toString())}${differenceDigit(diffData[index].toString())}`;\n            encodedData += encodedNumber;\n            charCount += encodedNumber.length;\n        }\n        else if (diffData[index - 1] === diffData[index]) {\n            // Try to insert next difference\n            mult++;\n        }\n        else if (mult > 0) {\n            // Now we know that it can be in line\n            mult++;\n            encodedNumber = duplicateDigit(mult.toString());\n            encodedData += encodedNumber;\n            charCount += encodedNumber.length;\n            mult = 0;\n            index--;\n        }\n        else {\n            // Check if it fits, otherwise start a new line\n            encodedNumber = differenceDigit(diffData[index].toString());\n            if (encodedNumber.length + charCount < maxLinelength) {\n                encodedData += encodedNumber;\n                charCount += encodedNumber.length;\n            }\n            else {\n                // start a new line\n                encodedData += newLine;\n                temp = `${Math.ceil(firstX + index * intervalX)}${squeezedDigit(data[index].toString())}${encodedNumber}`;\n                encodedData += temp; // Each line start with first index number.\n                charCount = temp.length;\n            }\n        }\n        index++;\n    }\n    if (mult > 0) {\n        encodedData += duplicateDigit((mult + 1).toString());\n    }\n    // We insert the last data from fid. It is done to control of data\n    // The last line start with the number of datas in the fid.\n    encodedData += `${newLine}${Math.ceil(firstX + index * intervalX)}${squeezedDigit(data[index].toString())}`;\n    return encodedData;\n}\n/**\n * @private\n * Differential xyEncoding\n */\nexport function differenceEncoding(data, firstX, intervalX) {\n    let index = 0;\n    let charCount = 0;\n    let i;\n    let encodedData = '';\n    let encodedNumber = '';\n    let temp = '';\n    // We calculate the differences vector\n    let diffData = new Array(data.length - 1);\n    for (i = 0; i < diffData.length; i++) {\n        diffData[i] = data[i + 1] - data[i];\n    }\n    let numDiff = diffData.length;\n    while (index < numDiff) {\n        if (charCount === 0) {\n            // We convert the first number.\n            encodedNumber = `${Math.ceil(firstX + index * intervalX)}${squeezedDigit(data[index].toString())}${differenceDigit(diffData[index].toString())}`;\n            encodedData += encodedNumber;\n            charCount += encodedNumber.length;\n        }\n        else {\n            encodedNumber = differenceDigit(diffData[index].toString());\n            if (encodedNumber.length + charCount < maxLinelength) {\n                encodedData += encodedNumber;\n                charCount += encodedNumber.length;\n            }\n            else {\n                encodedData += newLine;\n                temp = `${Math.ceil(firstX + index * intervalX)}${squeezedDigit(data[index].toString())}${encodedNumber}`;\n                encodedData += temp; // Each line start with first index number.\n                charCount = temp.length;\n            }\n        }\n        index++;\n    }\n    // We insert the last number from data. It is done to control of data\n    encodedData += `${newLine}${Math.ceil(firstX + index * intervalX)}${squeezedDigit(data[index].toString())}`;\n    return encodedData;\n}\n/**\n * @private\n * Convert number to the ZQZ format, using pseudo digits.\n */\nfunction squeezedDigit(num) {\n    let sqzDigits = '';\n    if (num.startsWith('-')) {\n        sqzDigits += pseudoDigits[SQZ_N][num.charCodeAt(1) - 48];\n        if (num.length > 2) {\n            sqzDigits += num.substring(2);\n        }\n    }\n    else {\n        sqzDigits += pseudoDigits[SQZ_P][num.charCodeAt(0) - 48];\n        if (num.length > 1) {\n            sqzDigits += num.substring(1);\n        }\n    }\n    return sqzDigits;\n}\n/**\n * Convert number to the DIF format, using pseudo digits.\n */\nfunction differenceDigit(num) {\n    let diffDigits = '';\n    if (num.startsWith('-')) {\n        diffDigits += pseudoDigits[DIF_N][num.charCodeAt(1) - 48];\n        if (num.length > 2) {\n            diffDigits += num.substring(2);\n        }\n    }\n    else {\n        diffDigits += pseudoDigits[DIF_P][num.charCodeAt(0) - 48];\n        if (num.length > 1) {\n            diffDigits += num.substring(1);\n        }\n    }\n    return diffDigits;\n}\n/**\n * Convert number to the DUP format, using pseudo digits.\n */\nfunction duplicateDigit(num) {\n    let dupDigits = '';\n    dupDigits += pseudoDigits[DUP][num.charCodeAt(0) - 48];\n    if (num.length > 1) {\n        dupDigits += num.substring(1);\n    }\n    return dupDigits;\n}\n//# sourceMappingURL=vectorEncoder.js.map","import { rescaleAndEnsureInteger } from './rescaleAndEnsureInteger';\nimport { vectorEncoder } from './vectorEncoder';\nexport function xyDataCreator(data, options = {}) {\n    const { xyEncoding = 'DIF' } = options;\n    const { xFactor = 1, yFactor = 1 } = options.info || {};\n    let firstX = data.x[0];\n    let lastX = data.x[data.x.length - 1];\n    let firstY = data.y[0];\n    let lastY = data.y[data.y.length - 1];\n    let nbPoints = data.x.length;\n    let deltaX = (lastX - firstX) / (nbPoints - 1);\n    let lines = [];\n    lines.push(`##FIRSTX=${firstX}`);\n    lines.push(`##LASTX=${lastX}`);\n    lines.push(`##FIRSTY=${firstY}`);\n    lines.push(`##LASTY=${lastY}`);\n    lines.push(`##DELTAX=${deltaX}`);\n    lines.push(`##XFACTOR=${xFactor}`);\n    lines.push(`##YFACTOR=${yFactor}`);\n    lines.push('##XYDATA=(X++(Y..Y))');\n    let line = vectorEncoder(rescaleAndEnsureInteger(data.y, yFactor), firstX / xFactor, deltaX / xFactor, xyEncoding);\n    if (line)\n        lines.push(line);\n    return lines;\n}\n//# sourceMappingURL=xyDataCreator.js.map","import { addInfoData } from './utils/addInfoData';\nimport { getBestFactor } from './utils/getBestFactor';\nimport { peakTableCreator } from './utils/peakTableCreator';\nimport { xyDataCreator } from './utils/xyDataCreator';\nconst infoDefaultKeys = [\n    'title',\n    'owner',\n    'origin',\n    'dataType',\n    'xUnits',\n    'yUnits',\n    'xFactor',\n    'yFactor',\n];\n/**\n * Create a jcamp\n * @param data object of array\n * @param [options={meta:{},info:{}} - metadata object\n * @returns JCAMP of the input\n */\nexport function fromJSON(data, options = {}) {\n    const { meta = {}, info = {}, xyEncoding } = options;\n    let { title = '', owner = '', origin = '', dataType = '', xUnits = '', yUnits = '', xFactor, yFactor, } = info;\n    data = { x: data.x, y: data.y };\n    let header = `##TITLE=${title}\n##JCAMP-DX=4.24\n##DATA TYPE=${dataType}\n##ORIGIN=${origin}\n##OWNER=${owner}\n##XUNITS=${xUnits}\n##YUNITS=${yUnits}\\n`;\n    const infoKeys = Object.keys(info).filter((keys) => !infoDefaultKeys.includes(keys));\n    header += addInfoData(info, infoKeys, '##');\n    header += addInfoData(meta);\n    // we leave the header and utf8 fonts ${header.replace(/[^\\t\\n\\x20-\\x7F]/g, '')\n    if (xyEncoding) {\n        xFactor = getBestFactor(data.x, { factor: xFactor });\n        yFactor = getBestFactor(data.y, { factor: yFactor });\n        return `${header}##NPOINTS=${data.x.length}\n${xyDataCreator(data, { info: { xFactor, yFactor }, xyEncoding }).join('\\n')}\n##END=`;\n    }\n    else {\n        if (xFactor === undefined)\n            xFactor = 1;\n        if (yFactor === undefined)\n            yFactor = 1;\n        if (xFactor !== 1) {\n            //@ts-expect-error xFactor is always defined\n            data.x = data.x.map((value) => value / xFactor);\n        }\n        if (yFactor !== 1) {\n            //@ts-expect-error yFactor is always defined\n            data.y = data.y.map((value) => value / yFactor);\n        }\n        return `${header}##NPOINTS=${data.x.length}\n${peakTableCreator(data, { info: { xFactor, yFactor } }).join('\\n')}\n##END=`;\n    }\n}\n//# sourceMappingURL=fromJSON.js.map","import { fromVariables } from 'convert-to-jcamp';\nexport function toJcamps(analysis, options = {}) {\n    let jcamps = [];\n    for (let spectrum of analysis.spectra) {\n        jcamps.push(getJcamp(spectrum, options));\n    }\n    return jcamps;\n}\nfunction getJcamp(spectrum, options) {\n    const { info = {}, meta = {} } = options;\n    let jcampOptions = {\n        options: {},\n        info: {\n            title: spectrum.title,\n            dataType: spectrum.dataType,\n            ...info,\n        },\n        meta: { ...spectrum.meta, ...meta },\n    };\n    return fromVariables(spectrum.variables, jcampOptions);\n}\n//# sourceMappingURL=data:application/json;base64,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","import creatorNtuples from './creatorNtuples';\nimport { fromJSON } from './fromJSON';\nimport { checkNumberOrArray } from './utils/checkNumberOrArray';\n/**\n * Create a jcamp from variables\n */\nexport function fromVariables(\n/** object of variables */\nvariables, options = {}) {\n    const { info = {}, meta = {}, forceNtuples = false } = options;\n    let jcampOptions = {\n        info,\n        meta,\n    };\n    let keys = Object.keys(variables).map((key) => key.toLowerCase());\n    if (!forceNtuples && keys.length === 2) {\n        let x = variables.x;\n        let xLabel = x.label || 'x';\n        if (variables.x.units) {\n            if (xLabel.includes(variables.x.units)) {\n                jcampOptions.info.xUnits = xLabel;\n            }\n            else {\n                jcampOptions.info.xUnits = `${xLabel} (${variables.x.units})`;\n            }\n        }\n        else {\n            jcampOptions.info.xUnits = xLabel;\n        }\n        let y = variables.y;\n        let yLabel = y.label || 'y';\n        if (variables.y.units) {\n            if (yLabel.includes(variables.y.units)) {\n                jcampOptions.info.xUnits = yLabel;\n            }\n            else {\n                jcampOptions.info.yUnits = `${yLabel} (${variables.y.units})`;\n            }\n        }\n        else {\n            jcampOptions.info.yUnits = yLabel;\n        }\n        const xData = variables.x.data;\n        const yData = variables.y.data;\n        checkNumberOrArray(xData);\n        checkNumberOrArray(yData);\n        return fromJSON({ x: xData, y: yData }, jcampOptions);\n    }\n    else {\n        return creatorNtuples(variables, options);\n    }\n}\n//# sourceMappingURL=fromVariables.js.map","/**\n * This function returns the sumOfShapes function\n * This function gives sumOfShapes access to the peak list and the associated data\n * @param parameters - parameters\n */\nexport function getSumOfShapes(internalPeaks) {\n    return function sumOfShapes(parameters) {\n        return (x) => {\n            let totalY = 0;\n            for (const peak of internalPeaks) {\n                const peakX = parameters[peak.fromIndex];\n                const y = parameters[peak.fromIndex + 1];\n                for (let i = 2; i < parameters.length; i++) {\n                    //@ts-expect-error Not simply to solve the issue\n                    peak.shapeFct[peak.parameters[i]] = parameters[peak.fromIndex + i];\n                }\n                totalY += y * peak.shapeFct.fct(x - peakX);\n            }\n            return totalY;\n        };\n    };\n}\n//# sourceMappingURL=getSumOfShapes.js.map","/**\n * Asserts that value is truthy.\n *\n * @param value - Value to check.\n * @param message - Optional error message to throw.\n */\nexport function assert(value, message) {\n    if (!value) {\n        throw new Error(message ? message : 'unreachable');\n    }\n}\n//# sourceMappingURL=assert.js.map","export const DefaultParameters = {\n    x: {\n        init: (peak) => peak.x,\n        min: (peak, peakShape) => peak.x - peakShape.fwhm * 2,\n        max: (peak, peakShape) => peak.x + peakShape.fwhm * 2,\n        gradientDifference: (peak, peakShape) => peakShape.fwhm * 2e-3,\n    },\n    y: {\n        init: (peak) => peak.y,\n        min: (peak) => (peak.y < 0 ? -1.1 : 0),\n        max: (peak) => (peak.y < 0 ? 0 : 1.1),\n        gradientDifference: () => 1e-3,\n    },\n    fwhm: {\n        init: (peak, peakShape) => peakShape.fwhm,\n        min: (peak, peakShape) => peakShape.fwhm * 0.25,\n        max: (peak, peakShape) => peakShape.fwhm * 4,\n        gradientDifference: (peak, peakShape) => peakShape.fwhm * 2e-3,\n    },\n    mu: {\n        init: (peak, peakShape) => peakShape.mu,\n        min: () => 0,\n        max: () => 1,\n        gradientDifference: () => 0.01,\n    },\n};\n//# sourceMappingURL=DefaultParameters.js.map","import { getShape1D } from 'ml-peak-shape-generator';\nimport { assert } from '../assert';\nimport { DefaultParameters } from './DefaultParameters';\nconst properties = ['init', 'min', 'max', 'gradientDifference'];\n/**\n * Return an array of internalPeaks that contains the exact init, min, max values based on the options\n * @param peaks\n * @param options\n * @returns\n */\nexport function getInternalPeaks(peaks, minMaxY, options = {}) {\n    let index = 0;\n    let internalPeaks = [];\n    const { baseline: shiftValue = minMaxY.min } = options;\n    const normalizedPeaks = peaks.map((peak) => {\n        return {\n            ...peak,\n            y: (peak.y - shiftValue) / minMaxY.range,\n        };\n    });\n    for (const peak of normalizedPeaks) {\n        const { id, shape = options.shape ? options.shape : { kind: 'gaussian' } } = peak;\n        const shapeFct = getShape1D(shape);\n        const parameters = ['x', 'y', ...shapeFct.getParameters()];\n        const propertiesValues = {\n            min: [],\n            max: [],\n            init: [],\n            gradientDifference: [],\n        };\n        for (let parameter of parameters) {\n            for (let property of properties) {\n                // check if the property is specified in the peak\n                let propertyValue = peak?.parameters?.[parameter]?.[property];\n                if (propertyValue) {\n                    propertyValue = getNormalizedValue(propertyValue, parameter, property, minMaxY, options.baseline);\n                    propertiesValues[property].push(propertyValue);\n                    continue;\n                }\n                // check if there are some global option, it could be a number or a callback\n                let generalParameterValue = options?.parameters?.[parameter]?.[property];\n                if (generalParameterValue) {\n                    if (typeof generalParameterValue === 'number') {\n                        generalParameterValue = getNormalizedValue(generalParameterValue, parameter, property, minMaxY, options.baseline);\n                        propertiesValues[property].push(generalParameterValue);\n                        continue;\n                    }\n                    else {\n                        let value = generalParameterValue(peak);\n                        value = getNormalizedValue(value, parameter, property, minMaxY, options.baseline);\n                        propertiesValues[property].push(value);\n                        continue;\n                    }\n                }\n                // we just need to take the default parameters\n                assert(DefaultParameters[parameter], `No default parameter for ${parameter}`);\n                const defaultParameterValues = DefaultParameters[parameter][property];\n                //@ts-expect-error should never happen\n                propertiesValues[property].push(defaultParameterValues(peak, shapeFct));\n            }\n        }\n        const fromIndex = index;\n        const toIndex = fromIndex + parameters.length - 1;\n        index += toIndex - fromIndex + 1;\n        internalPeaks.push({\n            id,\n            shape,\n            shapeFct,\n            parameters,\n            propertiesValues,\n            fromIndex,\n            toIndex,\n        });\n    }\n    return internalPeaks;\n}\nfunction getNormalizedValue(value, parameter, property, minMaxY, baseline) {\n    if (parameter === 'y') {\n        if (property === 'gradientDifference') {\n            return value;\n        }\n        else {\n            return baseline !== undefined\n                ? (value - baseline) / minMaxY.range\n                : (value - minMaxY.min) / minMaxY.range;\n        }\n    }\n    return value;\n}\n//# sourceMappingURL=getInternalPeaks.js.map","/**\n * Preparata, F. P., & Shamos, M. I. (2012). Computational geometry: an introduction. Springer Science & Business Media.\n * @param {Array} x - The array with x coordinates of the points.\n * @param {Array} y - The array with y coordinates of the points.\n * @return {Array} The indices of the points of anticlockwise lower convex hull\n * @private\n */\nexport default function antiLowerConvexHull(x, y) {\n  if (x.length !== y.length) {\n    throw new RangeError('X and Y vectors has different dimensions');\n  }\n\n  const nbPoints = x.length - 1;\n  if (nbPoints === 0) return [0];\n  if (nbPoints === 1) return [0, 1];\n\n  let currentPoint = 0;\n  let result = new Array(x.length).fill(true);\n  while (true) {\n    const a = currentPoint;\n    const b = moveOn(currentPoint, nbPoints, result);\n    const c = moveOn(moveOn(currentPoint, nbPoints, result), nbPoints, result);\n\n    const det =\n      x[c] * (y[a] - y[b]) + x[a] * (y[b] - y[c]) + x[b] * (y[c] - y[a]);\n\n    const leftTurn = det >= 0;\n\n    if (leftTurn) {\n      currentPoint = b;\n    } else {\n      result[b] = false;\n      currentPoint = moveBack(currentPoint, nbPoints, result);\n    }\n    if (c === nbPoints) break;\n  }\n\n  return result\n    .map((item, index) => (item === false ? false : index))\n    .filter((item) => item !== false);\n}\n\n/**\n * @param {number} currentPoint - The index of the current point to make the move\n * @param {number} nbPoints - The total number of points in the array\n * @param {Array} vector - The array with the points\n * @return {number} the index of the point after the move\n * @private\n */\n\nfunction moveBack(currentPoint, nbPoints, vector) {\n  let counter = currentPoint - 1;\n  while (vector[counter] === false) counter--;\n  return currentPoint === 0 ? nbPoints : counter;\n}\n\nfunction moveOn(currentPoint, nbPoints, vector) {\n  let counter = currentPoint + 1;\n  while (vector[counter] === false) counter++;\n  return currentPoint === nbPoints ? 0 : counter;\n}\n","import { xNorm, xMaxValue, xMinValue } from 'ml-spectra-processing';\n\nimport antiLowerConvexHull from './util/antiLowerConvexHull';\n\n/**\n * Performs a global optimization of required parameters\n * It will return an object containing:\n * - `minFunctionValue`: The minimum value found for the objetive function\n * - `optima`: Array of Array of values for all the variables where the function reach its minimum value\n * - `iterations`: Number of iterations performed in the process\n * - `finalState`: Internal state allowing to continue optimization (initialState)\n * @param {function} objectiveFunction Function to evaluate. It should accept an array of variables\n * @param {Array} lowerBoundaries Array containing for each variable the lower boundary\n * @param {Array} upperBoundaries Array containing for each variable the higher boundary\n * @param {Object} [options={}]\n * @param {number} [options.iterations] - Number of iterations.\n * @param {number} [options.epsilon] - Tolerance to choose best current value.\n * @param {number} [options.tolerance] - Minimum tollerance of the function.\n * @param {number} [options.tolerance2] - Minimum tollerance of the function.\n * @param {Object} [options.initialState={}}] - finalState of previous optimization.\n * @return {Object} {finalState, iterations, minFunctionValue}\n * */\n\nexport default function direct(\n  objectiveFunction,\n  lowerBoundaries,\n  upperBoundaries,\n  options = {},\n) {\n  const {\n    iterations = 50,\n    epsilon = 1e-4,\n    tolerance = 1e-16,\n    tolerance2 = 1e-12,\n    initialState = {},\n  } = options;\n\n  if (\n    objectiveFunction === undefined ||\n    lowerBoundaries === undefined ||\n    upperBoundaries === undefined\n  ) {\n    throw new RangeError('There is something undefined');\n  }\n\n  lowerBoundaries = new Float64Array(lowerBoundaries);\n  upperBoundaries = new Float64Array(upperBoundaries);\n\n  if (lowerBoundaries.length !== upperBoundaries.length) {\n    throw new Error(\n      'Lower bounds and Upper bounds for x are not of the same length',\n    );\n  }\n\n  //-------------------------------------------------------------------------\n  //                        STEP 1. Initialization\n  //-------------------------------------------------------------------------\n  let n = lowerBoundaries.length;\n  let diffBorders = upperBoundaries.map((x, i) => x - lowerBoundaries[i]);\n\n  let {\n    numberOfRectangles = 0,\n    totalIterations = 0,\n    unitaryCoordinates = [new Float64Array(n).fill(0.5)],\n    middlePoint = new Float64Array(n).map((value, index) => {\n      return (\n        lowerBoundaries[index] +\n        unitaryCoordinates[0][index] * diffBorders[index]\n      );\n    }),\n    bestCurrentValue = objectiveFunction(middlePoint),\n    fCalls = 1,\n    smallerDistance = 0,\n    edgeSizes = [new Float64Array(n).fill(0.5)],\n    diagonalDistances = [Math.sqrt(n * Math.pow(0.5, 2))],\n    functionValues = [bestCurrentValue],\n    differentDistances = diagonalDistances,\n    smallerValuesByDistance = [bestCurrentValue],\n    choiceLimit = undefined,\n  } = initialState;\n  if (\n    initialState.originalCoordinates &&\n    initialState.originalCoordinates.length > 0\n  ) {\n    bestCurrentValue = xMinValue(functionValues);\n    choiceLimit =\n      epsilon * Math.abs(bestCurrentValue) > 1e-8\n        ? epsilon * Math.abs(bestCurrentValue)\n        : 1e-8;\n\n    smallerDistance = getMinIndex(\n      functionValues,\n      diagonalDistances,\n      choiceLimit,\n      bestCurrentValue,\n    );\n\n    unitaryCoordinates = initialState.originalCoordinates.slice();\n    for (let j = 0; j < unitaryCoordinates.length; j++) {\n      for (let i = 0; i < lowerBoundaries.length; i++) {\n        unitaryCoordinates[j][i] =\n          (unitaryCoordinates[j][i] - lowerBoundaries[i]) / diffBorders[i];\n      }\n    }\n  }\n\n  let iteration = 0;\n  //-------------------------------------------------------------------------\n  //                          Iteration loop\n  //-------------------------------------------------------------------------\n\n  while (iteration < iterations) {\n    //----------------------------------------------------------------------\n    //  STEP 2. Identify the set S of all potentially optimal rectangles\n    //----------------------------------------------------------------------\n\n    let S1 = [];\n    let idx = differentDistances.findIndex(\n      // eslint-disable-next-line no-loop-func\n      (e) => e === diagonalDistances[smallerDistance],\n    );\n    let counter = 0;\n    for (let i = idx; i < differentDistances.length; i++) {\n      for (let f = 0; f < functionValues.length; f++) {\n        if (\n          (functionValues[f] === smallerValuesByDistance[i]) &\n          (diagonalDistances[f] === differentDistances[i])\n        ) {\n          S1[counter++] = f;\n        }\n      }\n    }\n\n    let optimumValuesIndex, S3;\n    if (differentDistances.length - idx > 1) {\n      let a1 = diagonalDistances[smallerDistance];\n      let b1 = functionValues[smallerDistance];\n      let a2 = differentDistances[differentDistances.length - 1];\n      let b2 = smallerValuesByDistance[differentDistances.length - 1];\n      let slope = (b2 - b1) / (a2 - a1);\n      let constant = b1 - slope * a1;\n      let S2 = new Uint32Array(counter);\n      counter = 0;\n      for (let i = 0; i < S2.length; i++) {\n        let j = S1[i];\n        if (\n          functionValues[j] <=\n          slope * diagonalDistances[j] + constant + tolerance2\n        ) {\n          S2[counter++] = j;\n        }\n      }\n\n      let xHull = [];\n      let yHull = [];\n      for (let i = 0; i < counter; i++) {\n        xHull.push(diagonalDistances[S2[i]]);\n        yHull.push(functionValues[S2[i]]);\n      }\n\n      let lowerIndexHull = antiLowerConvexHull(xHull, yHull);\n\n      S3 = [];\n      for (let i = 0; i < lowerIndexHull.length; i++) {\n        S3.push(S2[lowerIndexHull[i]]);\n      }\n    } else {\n      S3 = S1.slice(0, counter);\n    }\n    optimumValuesIndex = S3;\n    //--------------------------------------------------------------\n    // STEPS 3,5: Select any rectangle j in S\n    //--------------------------------------------------------------\n    for (let k = 0; k < optimumValuesIndex.length; k++) {\n      let j = optimumValuesIndex[k];\n      let largerSide = xMaxValue(edgeSizes[j]);\n      let largeSidesIndex = new Uint32Array(edgeSizes[j].length);\n      counter = 0;\n      for (let i = 0; i < edgeSizes[j].length; i++) {\n        if (Math.abs(edgeSizes[j][i] - largerSide) < tolerance) {\n          largeSidesIndex[counter++] = i;\n        }\n      }\n      let delta = (2 * largerSide) / 3;\n      let bestFunctionValues = [];\n      for (let r = 0; r < counter; r++) {\n        let i = largeSidesIndex[r];\n        let firstMiddleCenter = unitaryCoordinates[j].slice();\n        let secondMiddleCenter = unitaryCoordinates[j].slice();\n        firstMiddleCenter[i] += delta;\n        secondMiddleCenter[i] -= delta;\n        let firstMiddleValue = new Float64Array(firstMiddleCenter.length);\n        let secondMiddleValue = new Float64Array(secondMiddleCenter.length);\n        for (let i = 0; i < firstMiddleCenter.length; i++) {\n          firstMiddleValue[i] =\n            lowerBoundaries[i] + firstMiddleCenter[i] * diffBorders[i];\n          secondMiddleValue[i] =\n            lowerBoundaries[i] + secondMiddleCenter[i] * diffBorders[i];\n        }\n        let firstMinValue = objectiveFunction(firstMiddleValue);\n        let secondMinValue = objectiveFunction(secondMiddleValue);\n        fCalls += 2;\n        bestFunctionValues.push({\n          minValue: Math.min(firstMinValue, secondMinValue),\n          index: r,\n        });\n        // [Math.min(firstMinValue, secondMinValue), r];\n        unitaryCoordinates.push(firstMiddleCenter, secondMiddleCenter);\n        functionValues.push(firstMinValue, secondMinValue);\n      }\n\n      let b = bestFunctionValues.sort((a, b) => a.minValue - b.minValue);\n      for (let r = 0; r < counter; r++) {\n        let u = largeSidesIndex[b[r].index];\n        let ix1 = numberOfRectangles + 2 * (b[r].index + 1) - 1;\n        let ix2 = numberOfRectangles + 2 * (b[r].index + 1);\n        edgeSizes[j][u] = delta / 2;\n        edgeSizes[ix1] = edgeSizes[j].slice();\n        edgeSizes[ix2] = edgeSizes[j].slice();\n        diagonalDistances[j] = xNorm(edgeSizes[j]);\n        diagonalDistances[ix1] = diagonalDistances[j];\n        diagonalDistances[ix2] = diagonalDistances[j];\n      }\n      numberOfRectangles += 2 * counter;\n    }\n\n    //--------------------------------------------------------------\n    //                  Update\n    //--------------------------------------------------------------\n\n    bestCurrentValue = xMinValue(functionValues);\n\n    choiceLimit =\n      epsilon * Math.abs(bestCurrentValue) > 1e-8\n        ? epsilon * Math.abs(bestCurrentValue)\n        : 1e-8;\n\n    smallerDistance = getMinIndex(\n      functionValues,\n      diagonalDistances,\n      choiceLimit,\n      bestCurrentValue,\n      iteration,\n    );\n\n    differentDistances = Array.from(new Set(diagonalDistances));\n    differentDistances = differentDistances.sort((a, b) => a - b);\n\n    smallerValuesByDistance = [];\n    for (let i = 0; i < differentDistances.length; i++) {\n      let minIndex;\n      let minValue = Number.POSITIVE_INFINITY;\n      for (let k = 0; k < diagonalDistances.length; k++) {\n        if (diagonalDistances[k] === differentDistances[i]) {\n          if (functionValues[k] < minValue) {\n            minValue = functionValues[k];\n            minIndex = k;\n          }\n        }\n      }\n      smallerValuesByDistance.push(functionValues[minIndex]);\n    }\n\n    let currentMin = [];\n    for (let j = 0; j < functionValues.length; j++) {\n      if (functionValues[j] === bestCurrentValue) {\n        let temp = [];\n        for (let i = 0; i < lowerBoundaries.length; i++) {\n          temp.push(\n            lowerBoundaries[i] + unitaryCoordinates[j][i] * diffBorders[i],\n          );\n        }\n        currentMin.push(temp);\n      }\n    }\n    iteration += 1;\n  }\n  //--------------------------------------------------------------\n  //                  Saving results\n  //--------------------------------------------------------------\n\n  let result = {};\n  result.minFunctionValue = bestCurrentValue;\n  result.iterations = iteration;\n  let originalCoordinates = [];\n  for (let j = 0; j < numberOfRectangles + 1; j++) {\n    let pair = [];\n    for (let i = 0; i < lowerBoundaries.length; i++) {\n      pair.push(lowerBoundaries[i] + unitaryCoordinates[j][i] * diffBorders[i]);\n    }\n    originalCoordinates.push(pair);\n  }\n\n  result.finalState = {\n    numberOfRectangles,\n    totalIterations: (totalIterations += iterations),\n    originalCoordinates,\n    middlePoint,\n    fCalls,\n    smallerDistance,\n    edgeSizes,\n    diagonalDistances,\n    functionValues,\n    differentDistances,\n    smallerValuesByDistance,\n    choiceLimit,\n  };\n\n  let minimizer = [];\n  for (let i = 0; i < functionValues.length; i++) {\n    if (functionValues[i] === bestCurrentValue) {\n      minimizer.push(originalCoordinates[i]);\n    }\n  }\n\n  result.optima = minimizer;\n  return result;\n}\n\nfunction getMinIndex(\n  functionValues,\n  diagonalDistances,\n  choiceLimit,\n  bestCurrentValue,\n) {\n  let item = [];\n  for (let i = 0; i < functionValues.length; i++) {\n    item[i] =\n      Math.abs(functionValues[i] - (bestCurrentValue + choiceLimit)) /\n      diagonalDistances[i];\n  }\n  const min = xMinValue(item);\n  let result = item.findIndex((x) => x === min);\n  return result;\n}\n","import direct from 'ml-direct';\nexport function directOptimization(data, sumOfShapes, options) {\n    const { minValues, maxValues, maxIterations, epsilon, tolerance, tolerance2, initialState, } = options;\n    const objectiveFunction = getObjectiveFunction(data, sumOfShapes);\n    const result = direct(objectiveFunction, minValues, maxValues, {\n        iterations: maxIterations,\n        epsilon,\n        tolerance,\n        tolerance2,\n        initialState,\n    });\n    const { optima } = result;\n    return {\n        parameterError: result.minFunctionValue,\n        iterations: result.iterations,\n        parameterValues: optima[0],\n    };\n}\nfunction getObjectiveFunction(data, sumOfShapes) {\n    const { x, y } = data;\n    const nbPoints = x.length;\n    return (parameters) => {\n        const fct = sumOfShapes(parameters);\n        let error = 0;\n        for (let i = 0; i < nbPoints; i++) {\n            error += Math.pow(y[i] - fct(x[i]), 2);\n        }\n        return error;\n    };\n}\n//# sourceMappingURL=directOptimization.js.map","import { levenbergMarquardt } from 'ml-levenberg-marquardt';\nimport { directOptimization } from './wrappers/directOptimization';\n/** Algorithm to select the method.\n * @param optimizationOptions - Optimization options\n * @returns - The algorithm and optimization options\n */\nexport function selectMethod(optimizationOptions = {}) {\n    let { kind = 'lm', options } = optimizationOptions;\n    switch (kind) {\n        case 'lm':\n        case 'levenbergMarquardt':\n            return {\n                algorithm: levenbergMarquardt,\n                optimizationOptions: {\n                    damping: 1.5,\n                    maxIterations: 100,\n                    errorTolerance: 1e-8,\n                    ...options,\n                },\n            };\n        case 'direct': {\n            return {\n                algorithm: directOptimization,\n                optimizationOptions: {\n                    iterations: 20,\n                    epsilon: 1e-4,\n                    tolerance: 1e-16,\n                    tolerance2: 1e-12,\n                    initialState: {},\n                    ...options,\n                },\n            };\n        }\n        default:\n            throw new Error(`Unknown fitting algorithm`);\n    }\n}\n//# sourceMappingURL=selectMethod.js.map","import { xMinMaxValues } from 'ml-spectra-processing';\nimport { getSumOfShapes } from './shapes/getSumOfShapes';\nimport { getInternalPeaks } from './util/internalPeaks/getInternalPeaks';\nimport { selectMethod } from './util/selectMethod';\n/**\n * Fits a set of points to the sum of a set of bell functions.\n *\n * @param data - An object containing the x and y data to be fitted.\n * @param peaks - A list of initial parameters to be optimized. e.g. coming from a peak picking [{x, y, width}].\n * @param options - Options for optimize\n * @returns - An object with fitting error and the list of optimized parameters { parameters: [ {x, y, width} ], error } if the kind of shape is pseudoVoigt mu parameter is optimized.\n */\nexport function optimize(data, peaks, options = {}) {\n    // rescale data\n    let temp = xMinMaxValues(data.y);\n    const minMaxY = { ...temp, range: temp.max - temp.min };\n    const internalPeaks = getInternalPeaks(peaks, minMaxY, options);\n    // need to rescale what is related to Y\n    const { baseline: shiftValue = minMaxY.min } = options;\n    let normalizedY = new Float64Array(data.y.length);\n    for (let i = 0; i < data.y.length; i++) {\n        normalizedY[i] = (data.y[i] - shiftValue) / minMaxY.range;\n    }\n    const nbParams = internalPeaks[internalPeaks.length - 1].toIndex + 1;\n    const minValues = new Float64Array(nbParams);\n    const maxValues = new Float64Array(nbParams);\n    const initialValues = new Float64Array(nbParams);\n    const gradientDifferences = new Float64Array(nbParams);\n    let index = 0;\n    for (const peak of internalPeaks) {\n        for (let i = 0; i < peak.parameters.length; i++) {\n            minValues[index] = peak.propertiesValues.min[i];\n            maxValues[index] = peak.propertiesValues.max[i];\n            initialValues[index] = peak.propertiesValues.init[i];\n            gradientDifferences[index] = peak.propertiesValues.gradientDifference[i];\n            index++;\n        }\n    }\n    let { algorithm, optimizationOptions } = selectMethod(options.optimization);\n    let sumOfShapes = getSumOfShapes(internalPeaks);\n    let fitted = algorithm({ x: data.x, y: normalizedY }, sumOfShapes, {\n        minValues,\n        maxValues,\n        initialValues,\n        gradientDifference: gradientDifferences,\n        ...optimizationOptions,\n    });\n    const fittedValues = fitted.parameterValues;\n    let newPeaks = [];\n    for (let peak of internalPeaks) {\n        const { id, shape, parameters, fromIndex } = peak;\n        let newPeak = { x: 0, y: 0, shape };\n        if (id) {\n            newPeak = { ...newPeak, id };\n        }\n        newPeak.x = fittedValues[fromIndex];\n        newPeak.y = fittedValues[fromIndex + 1] * minMaxY.range + shiftValue;\n        for (let i = 2; i < parameters.length; i++) {\n            //@ts-expect-error should be fixed once\n            newPeak.shape[parameters[i]] = fittedValues[fromIndex + i];\n        }\n        newPeaks.push(newPeak);\n    }\n    return {\n        error: fitted.parameterError,\n        iterations: fitted.iterations,\n        peaks: newPeaks,\n    };\n}\n//# sourceMappingURL=index.js.map","import { getShape1D } from 'ml-peak-shape-generator';\n/**\n * Append 2 properties to the peaks, shape and fwhm\n */\nexport function appendShapeAndFWHM(peaks, options = {}) {\n    let { shape = { kind: 'gaussian' } } = options;\n    let shapeInstance = getShape1D(shape);\n    return peaks.map((peak) => ({\n        ...peak,\n        shape: { fwhm: shapeInstance.widthToFWHM(peak.width), ...shape },\n    }));\n}\n//# sourceMappingURL=appendShapeAndFWHM.js.map","/**\n * Correction of the x and y coordinates using a quadratic optimizations with the peak and its 3 closest neighbors to determine the true x,y values of the peak.\n * This process is done in place and is very fast.\n * @param data\n * @param peaks\n */\nexport function optimizeTop(data, peaks) {\n    const { x, y } = data;\n    for (const peak of peaks) {\n        let currentIndex = peak.index;\n        // The detected peak could be moved 1 or 2 units to left or right.\n        if (y[currentIndex - 1] >= y[currentIndex - 2] &&\n            y[currentIndex - 1] >= y[currentIndex]) {\n            currentIndex--;\n        }\n        else {\n            if (y[currentIndex + 1] >= y[currentIndex] &&\n                y[currentIndex + 1] >= y[currentIndex + 2]) {\n                currentIndex++;\n            }\n            else {\n                if (y[currentIndex - 2] >= y[currentIndex - 3] &&\n                    y[currentIndex - 2] >= y[currentIndex - 1]) {\n                    currentIndex -= 2;\n                }\n                else {\n                    if (y[currentIndex + 2] >= y[currentIndex + 1] &&\n                        y[currentIndex + 2] >= y[currentIndex + 3]) {\n                        currentIndex += 2;\n                    }\n                }\n            }\n        }\n        // interpolation to a sin() function\n        if (y[currentIndex - 1] > 0 &&\n            y[currentIndex + 1] > 0 &&\n            y[currentIndex] >= y[currentIndex - 1] &&\n            y[currentIndex] >= y[currentIndex + 1] &&\n            (y[currentIndex] !== y[currentIndex - 1] ||\n                y[currentIndex] !== y[currentIndex + 1])) {\n            let alpha = 20 * Math.log10(y[currentIndex - 1]);\n            let beta = 20 * Math.log10(y[currentIndex]);\n            let gamma = 20 * Math.log10(y[currentIndex + 1]);\n            let p = (0.5 * (alpha - gamma)) / (alpha - 2 * beta + gamma);\n            peak.x = x[currentIndex] + (x[currentIndex] - x[currentIndex - 1]) * p;\n            peak.y =\n                y[currentIndex] -\n                    0.25 * (y[currentIndex - 1] - y[currentIndex + 1]) * p;\n        }\n    }\n}\n//# sourceMappingURL=optimizeTop.js.map","import { sgg } from 'ml-savitzky-golay-generalized';\nimport { xIsEquallySpaced, xIsMonotoneIncreasing, xMinValue, xMaxValue, xNoiseStandardDeviation, } from 'ml-spectra-processing';\nimport { appendShapeAndFWHM } from './utils/appendShapeAndFWHM';\nimport { optimizeTop } from './utils/optimizeTop';\n/**\n * Global spectra deconvolution\n * @param  data - Object data with x and y arrays. Values in x has to be growing\n * @param {number} [options.broadRatio = 0.00] - If `broadRatio` is higher than 0, then all the peaks which second derivative\n * smaller than `broadRatio * maxAbsSecondDerivative` will be marked with the soft mask equal to true.\n\n */\nexport function gsd(data, options = {}) {\n    let { sgOptions = {\n        windowSize: 9,\n        polynomial: 3,\n    }, shape, noiseLevel, smoothY = false, maxCriteria = true, minMaxRatio = 0.00025, realTopDetection = false, } = options;\n    let { x, y } = data;\n    if (!xIsMonotoneIncreasing(x)) {\n        throw new Error('GSD only accepts monotone increasing x values');\n    }\n    //rescale;\n    y = y.slice();\n    // If the max difference between delta x is less than 5%, then,\n    // we can assume it to be equally spaced variable\n    let equallySpaced = xIsEquallySpaced(x);\n    if (noiseLevel === undefined) {\n        if (equallySpaced) {\n            const noiseInfo = xNoiseStandardDeviation(y);\n            if (maxCriteria) {\n                noiseLevel = noiseInfo.median + 1.5 * noiseInfo.sd;\n            }\n            else {\n                noiseLevel = -noiseInfo.median + 1.5 * noiseInfo.sd;\n            }\n        }\n        else {\n            noiseLevel = 0;\n        }\n    }\n    else {\n        if (maxCriteria === false) {\n            noiseLevel *= -1;\n        }\n    }\n    if (maxCriteria === false) {\n        for (let i = 0; i < y.length; i++) {\n            y[i] *= -1;\n        }\n    }\n    if (noiseLevel !== undefined) {\n        for (let i = 0; i < y.length; i++) {\n            if (y[i] < noiseLevel) {\n                y[i] = noiseLevel;\n            }\n        }\n    }\n    let yData = y;\n    let dY, ddY;\n    const { windowSize, polynomial } = sgOptions;\n    if (equallySpaced) {\n        if (smoothY) {\n            yData = sgg(y, x[1] - x[0], {\n                windowSize,\n                polynomial,\n                derivative: 0,\n            });\n        }\n        dY = sgg(y, x[1] - x[0], {\n            windowSize,\n            polynomial,\n            derivative: 1,\n        });\n        ddY = sgg(y, x[1] - x[0], {\n            windowSize,\n            polynomial,\n            derivative: 2,\n        });\n    }\n    else {\n        if (smoothY) {\n            yData = sgg(y, x, {\n                windowSize,\n                polynomial,\n                derivative: 0,\n            });\n        }\n        dY = sgg(y, x, {\n            windowSize,\n            polynomial,\n            derivative: 1,\n        });\n        ddY = sgg(y, x, {\n            windowSize,\n            polynomial,\n            derivative: 2,\n        });\n    }\n    const minY = xMinValue(yData);\n    const maxY = xMaxValue(yData);\n    if (minY > maxY || minY === maxY)\n        return [];\n    const yThreshold = minY + (maxY - minY) * minMaxRatio;\n    const dX = x[1] - x[0];\n    let lastMax = null;\n    let lastMin = null;\n    let minddY = [];\n    let intervalL = [];\n    let intervalR = [];\n    // By the intermediate value theorem We cannot find 2 consecutive maximum or minimum\n    for (let i = 1; i < yData.length - 1; ++i) {\n        if ((dY[i] < dY[i - 1] && dY[i] <= dY[i + 1]) ||\n            (dY[i] <= dY[i - 1] && dY[i] < dY[i + 1])) {\n            lastMin = {\n                x: x[i],\n                index: i,\n            };\n            if (dX > 0 && lastMax !== null) {\n                intervalL.push(lastMax);\n                intervalR.push(lastMin);\n            }\n        }\n        // Maximum in first derivative\n        if ((dY[i] >= dY[i - 1] && dY[i] > dY[i + 1]) ||\n            (dY[i] > dY[i - 1] && dY[i] >= dY[i + 1])) {\n            lastMax = {\n                x: x[i],\n                index: i,\n            };\n            if (dX < 0 && lastMin !== null) {\n                intervalL.push(lastMax);\n                intervalR.push(lastMin);\n            }\n        }\n        // Minimum in second derivative\n        if (ddY[i] < ddY[i - 1] && ddY[i] < ddY[i + 1]) {\n            minddY.push(i);\n        }\n    }\n    let lastK = -1;\n    const peaks = [];\n    for (const minddYIndex of minddY) {\n        let deltaX = x[minddYIndex];\n        let possible = -1;\n        let k = lastK + 1;\n        let minDistance = Number.POSITIVE_INFINITY;\n        let currentDistance = 0;\n        while (possible === -1 && k < intervalL.length) {\n            currentDistance = Math.abs(deltaX - (intervalL[k].x + intervalR[k].x) / 2);\n            if (currentDistance < (intervalR[k].x - intervalL[k].x) / 2) {\n                possible = k;\n                lastK = k;\n            }\n            ++k;\n            // Not getting closer?\n            if (currentDistance >= minDistance) {\n                break;\n            }\n            minDistance = currentDistance;\n        }\n        if (possible !== -1) {\n            if (yData[minddYIndex] > yThreshold) {\n                let width = Math.abs(intervalR[possible].x - intervalL[possible].x);\n                peaks.push({\n                    x: deltaX,\n                    y: yData[minddYIndex],\n                    width,\n                    index: minddYIndex,\n                    ddY: ddY[minddYIndex],\n                    inflectionPoints: {\n                        from: intervalL[possible],\n                        to: intervalR[possible],\n                    },\n                });\n            }\n        }\n    }\n    if (realTopDetection) {\n        optimizeTop({ x, y: yData }, peaks);\n    }\n    peaks.forEach((peak) => {\n        if (!maxCriteria) {\n            peak.y *= -1;\n            peak.ddY = peak.ddY * -1;\n        }\n    });\n    peaks.sort((a, b) => {\n        return a.x - b.x;\n    });\n    return appendShapeAndFWHM(peaks, { shape });\n}\n//# sourceMappingURL=gsd.js.map","import { getJSGraph } from './jsgraph/getJSGraph';\nimport { getNormalizationAnnotations } from './jsgraph/getNormalizationAnnotations';\nexport * from './AnalysesManager';\nexport * from './Analysis';\nexport * from './from/fromJcamp';\nexport * from './from/fromText';\nexport * from './to/toJcamp';\nexport * from './to/toJcamps';\nexport * from './to/toText';\nexport * from './util/getNormalizedSpectrum';\nexport * from './util/peakPicking';\nexport * from './util/autoPeakPicking';\nexport * from './types/types';\nexport * from './types/AutoPeakPickingOptions';\nexport * from './types/NormalizedSpectrumOptions';\nexport * from './types/PlotObject';\nexport * from './types/SpectrumSelector';\nexport { getReactPlotJSON } from './reactPlot/getReactPlotJSON';\nexport const JSGraph = {\n    getJSGraph,\n    getNormalizationAnnotations,\n};\n//# sourceMappingURL=data:application/json;base64,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","import { xyFilterXPositive } from 'ml-spectra-processing';\nimport { addStyle } from './addStyle';\nimport { COLORS } from './colors';\n/**\n * Generate a jsgraph chart format from an array of Analysis\n */\nexport function getJSGraph(analyses, options = {}) {\n    const { colors = COLORS, opacities = [1], linesWidth = [1], selector = {}, normalization, xAxis = {}, yAxis = {}, } = options;\n    let series = [];\n    let xLabel = xAxis.label;\n    let yLabel = yAxis.label;\n    let xUnits = xAxis.units;\n    let yUnits = yAxis.units;\n    for (let i = 0; i < analyses.length; i++) {\n        const analysis = analyses[i];\n        let spectra = analysis.getNormalizedSpectra({\n            selector,\n            normalization,\n        });\n        if (spectra.length === 0)\n            continue;\n        const firstSpectrum = spectra[0];\n        // todo: if many spectra are available and not xUnits / yUnits are specified we should ensure that all the3 spectra are compatible\n        if (!xLabel)\n            xLabel = firstSpectrum.variables.x.label;\n        if (!yLabel)\n            yLabel = firstSpectrum.variables.y.label;\n        if (!xUnits)\n            xUnits = firstSpectrum.variables.x.units;\n        if (!yUnits)\n            yUnits = firstSpectrum.variables.y.units;\n        for (const spectrum of spectra) {\n            let serie = {};\n            addStyle(serie, analysis, {\n                color: colors[i % colors.length],\n                opacity: opacities[i % opacities.length],\n                lineWidth: linesWidth[i % linesWidth.length],\n            });\n            serie.data = {\n                x: spectrum.variables.x.data,\n                y: spectrum.variables.y.data,\n            };\n            serie.id = spectrum.id;\n            if (xAxis.logScale) {\n                serie.data = xyFilterXPositive(serie.data);\n            }\n            series.push(serie);\n        }\n    }\n    return {\n        axes: {\n            x: {\n                label: xLabel,\n                unit: xUnits,\n                unitWrapperBefore: '(',\n                unitWrapperAfter: ')',\n                flipped: false,\n                display: true,\n                ...xAxis,\n            },\n            y: {\n                label: yLabel,\n                unit: yUnits,\n                unitWrapperBefore: '(',\n                unitWrapperAfter: ')',\n                flipped: false,\n                display: true,\n                ...yAxis,\n            },\n        },\n        series,\n    };\n}\n//# sourceMappingURL=data:application/json;base64,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","export function getNormalizationAnnotations(filter = {}, boundary = { y: { min: '0px', max: '2000px' } }) {\n    let { exclusions = [] } = filter;\n    let annotations = [];\n    exclusions = exclusions.filter((exclusion) => !exclusion.ignore);\n    annotations = exclusions.map((exclusion) => {\n        let annotation = {\n            type: 'rect',\n            position: [\n                { x: exclusion.from, y: boundary.y.min },\n                { x: exclusion.to, y: boundary.y.max },\n            ],\n            strokeWidth: 0,\n            fillColor: 'rgba(255,255,224,1)',\n        };\n        return annotation;\n    });\n    if (filter.from !== undefined) {\n        annotations.push({\n            type: 'rect',\n            position: [\n                { x: Number.MIN_SAFE_INTEGER, y: boundary.y.min },\n                { x: filter.from, y: boundary.y.max },\n            ],\n            strokeWidth: 0,\n            fillColor: 'rgba(255,255,224,1)',\n        });\n    }\n    if (filter.to !== undefined) {\n        annotations.push({\n            type: 'rect',\n            position: [\n                { x: filter.to, y: boundary.y.min },\n                { x: Number.MAX_SAFE_INTEGER, y: boundary.y.max },\n            ],\n            strokeWidth: 0,\n            fillColor: 'rgba(255,255,224,1)',\n        });\n    }\n    return annotations;\n}\n//# sourceMappingURL=data:application/json;base64,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","/**\n * @typedef {Object} Peak\n * @property {number} wavenumber\n * @property {number} transmittance\n * @property {number} absorbance\n * @property {number} kind\n * @property {number} assignment\n */\n\n/**\n * Creates annotations for jsgraph that allows to display the result of peak picking\n * @param {array<Peak>} peaks\n * @param {object} [options={}]\n * @param {string} [options.fillColor='green']\n * @param {string} [options.strokeColor='red']\n * @param {string} [options.showKind=true] Display the kind, 'm', 'w', 'S'\n * @param {string} [options.showAssignment=true] Display the assignment\n * @param {function} [options.createFct] (annotation, peak) => {}: callback allowing to add properties\n * @param {string} [options.mode='t100'] 't100'=transmittance in %, 't'=transmittance, 'a'=absorbance\n * @returns array\n */\n\nexport function getAnnotations(peaks, options = {}) {\n  const {\n    fillColor = 'green',\n    strokeColor = 'red',\n    creationFct,\n    mode = 't100',\n  } = options;\n  let annotations = peaks.map((peak) => {\n    let annotation = {\n      line: 1,\n      type: 'rect',\n      strokeColor,\n      strokeWidth: 0,\n      fillColor,\n    };\n    if (creationFct) {\n      creationFct(annotation, peak);\n    }\n    switch (mode) {\n      case 'a':\n        annotationAbsorbance(annotation, peak, options);\n        break;\n      case 't':\n        annotationTransmittance(annotation, peak, 1, options);\n        break;\n      case 't100':\n        annotationTransmittance(annotation, peak, 100, options);\n        break;\n      default:\n    }\n    return annotation;\n  });\n  return annotations;\n}\n\nfunction annotationTransmittance(annotation, peak, factor = 1, options = {}) {\n  const { showKind = true, showAssignment = true } = options;\n  let labels = [];\n  let line = 0;\n\n  if (showKind) {\n    labels.push({\n      text: peak.kind,\n      size: '18px',\n      anchor: 'middle',\n      color: 'red',\n      position: {\n        x: peak.wavenumber,\n        y: peak.transmittance * factor,\n        dy: `${23 + line * 14}px`,\n      },\n    });\n    line++;\n  }\n\n  if (showAssignment) {\n    labels.push({\n      text: peak.assignment,\n      size: '18px',\n      anchor: 'middle',\n      color: 'darkred',\n      position: {\n        x: peak.wavenumber,\n        y: peak.transmittance * factor,\n        dy: `${23 + line * 14}px`,\n      },\n    });\n    line++;\n  }\n\n  annotation.labels = labels;\n  annotation.position = [\n    {\n      x: peak.wavenumber,\n      y: peak.transmittance * factor,\n      dy: '10px',\n      dx: '-1px',\n    },\n    {\n      x: peak.wavenumber,\n      y: peak.transmittance * factor,\n      dy: '5px',\n      dx: '1px',\n    },\n  ];\n}\n\nfunction annotationAbsorbance(annotation, peak, options = {}) {\n  const {\n    showKind = true,\n    showAssignment = true,\n    assignmentAngle = -45,\n  } = options;\n  let labels = [];\n  let line = 0;\n\n  if (showKind) {\n    labels.push({\n      text: peak.kind,\n      size: '18px',\n      anchor: 'middle',\n      color: 'red',\n      position: {\n        x: peak.wavenumber,\n        y: peak.absorbance,\n        dy: `${-15 - line * 14}px`,\n      },\n    });\n    line++;\n  }\n\n  if (showAssignment) {\n    labels.push({\n      text: peak.assignment,\n      size: '18px',\n      angle: assignmentAngle,\n      anchor: 'left',\n      color: 'darkred',\n      position: {\n        x: peak.wavenumber,\n        y: peak.absorbance,\n        dy: `${-15 - line * 14}px`,\n      },\n    });\n    line++;\n  }\n\n  annotation.labels = labels;\n\n  annotation.position = [\n    {\n      x: peak.wavenumber,\n      y: peak.absorbance,\n      dy: '-10px',\n      dx: '-1px',\n    },\n    {\n      x: peak.wavenumber,\n      y: peak.absorbance,\n      dy: '-5px',\n      dx: '1px',\n    },\n  ];\n}\n","export function spectrumCallback(variables) {\n  // we add missing absorbance / transmittance\n  // variable a = absorbance\n  // variable t = transmittance\n  let yVariable = variables.y;\n  let absorbance = true;\n  if (yVariable.label.toLowerCase().includes('trans')) {\n    absorbance = false;\n  }\n  if (absorbance) {\n    variables.a = { ...yVariable, symbol: 'a', data: yVariable.data.slice() };\n    variables.t = {\n      data: yVariable.data.map((absorbance) => 10 ** -absorbance * 100),\n      label: 'Transmittance (%)',\n      symbol: 't',\n      units: '',\n    };\n  } else {\n    const factor =\n      yVariable.label.includes('%') ||\n      yVariable.label.toLowerCase().includes('percent')\n        ? 100\n        : 1;\n\n    variables.a = {\n      data: yVariable.data.map(\n        (transmittance) => -Math.log10(transmittance / factor),\n      ),\n      symbol: 'a',\n      label: 'Absorbance',\n      units: '',\n    };\n    if (factor === 100) {\n      variables.t = { ...yVariable, symbol: 't' };\n      variables.t.data = variables.t.data.slice();\n    } else {\n      variables.t = {\n        units: '',\n        label: 'Transmittance (%)',\n        symbol: 't',\n        data: yVariable.data.map((transmittance) => transmittance * 100),\n      };\n    }\n  }\n}\n","/**\n * Gives meaning to type codes.\n * @param  xzwType x, z or w type code.\n * @return  String corresponding to the code.\n */\nexport function xzwTypes(xzwType) {\n    switch (xzwType) {\n        case 1:\n            return 'Wavenumber (cm-1)';\n        case 2:\n            return 'Micrometers (um)';\n        case 3:\n            return 'Nanometers (nm)';\n        case 4:\n            return 'Seconds';\n        case 5:\n            return 'Minutes';\n        case 6:\n            return 'Hertz (Hz)';\n        case 7:\n            return 'Kilohertz (KHz)';\n        case 8:\n            return 'Megahertz (MHz)';\n        case 9:\n            return 'Mass (M/z)';\n        case 10:\n            return 'Parts per million (PPM)';\n        case 11:\n            return 'Days';\n        case 12:\n            return 'Years';\n        case 13:\n            return 'Raman Shift (cm-1)';\n        case 14:\n            return 'eV';\n        case 15:\n            return 0;\n        case 16:\n            return 'Diode Number';\n        case 17:\n            return 'Channel ';\n        case 18:\n            return 'Degrees';\n        case 19:\n            return 'Temperature (F)';\n        case 20:\n            return 'Temperature (C)';\n        case 21:\n            return 'Temperature (K)';\n        case 22:\n            return 'Data Points';\n        case 23:\n            return 'Milliseconds (mSec)';\n        case 24:\n            return 'Microseconds (uSec)';\n        case 25:\n            return 'Nanoseconds (nSec)';\n        case 26:\n            return 'Gigahertz (GHz)';\n        case 27:\n            return 'Centimeters (cm)';\n        case 28:\n            return 'Meters (m)';\n        case 29:\n            return 'Millimeters (mm)';\n        case 30:\n            return 'Hours';\n        case 255:\n            return 'Double interferogram';\n        default:\n            return 'Arbitrary';\n    }\n}\n/**\n * Gives meaning to y type codes\n * @param  yType y type code\n * @return  String corresponding to the code\n */\nexport function yTypes(yType) {\n    switch (yType) {\n        case 0:\n            return 'Arbitrary Intensity';\n        case 1:\n            return 'Interferogram';\n        case 2:\n            return 'Absorbance';\n        case 3:\n            return 'Kubelka-Monk';\n        case 4:\n            return 'Counts';\n        case 5:\n            return 'Volts';\n        case 6:\n            return 'Degrees';\n        case 7:\n            return 'Milliamps';\n        case 8:\n            return 'Millimeters';\n        case 9:\n            return 'Millivolts';\n        case 10:\n            return 'Log(1/R)';\n        case 11:\n            return 'Percent';\n        case 12:\n            return 'Intensity';\n        case 13:\n            return 'Relative Intensity';\n        case 14:\n            return 'Energy';\n        case 16:\n            return 'Decibel';\n        case 19:\n            return 'Temperature (F)';\n        case 20:\n            return 'Temperature (C)';\n        case 21:\n            return 'Temperature (K)';\n        case 22:\n            return 'Index of Refraction [N]';\n        case 23:\n            return 'Extinction Coeff. [K]';\n        case 24:\n            return 'Real';\n        case 25:\n            return 'Imaginary';\n        case 26:\n            return 'Complex';\n        case 128:\n            return 'Transmission';\n        case 129:\n            return 'Reflectance';\n        case 130:\n            return 'Arbitrary or Single Beam with Valley Peaks';\n        case 131:\n            return 'Emission';\n        default:\n            return 'Reference Arbitrary Energy';\n    }\n}\n/**\n * Convert code to experiment type\n * @param code\n * @returns type of experiment carried out.\n */\nexport function experimentSettings(code) {\n    switch (code) {\n        case 1:\n            return 'Gas Chromatogram';\n        case 2:\n            return 'General Chromatogram (same as SPCGEN with TCGRAM)';\n        case 3:\n            return 'HPLC Chromatogram';\n        case 4:\n            return 'FT-IR, FT-NIR, FT-Raman Spectrum or Igram (Can also be used for scanning IR.)';\n        case 5:\n            return 'NIR Spectrum (Usually multi-spectral data sets for calibration.)';\n        case 7:\n            return 'UV-VIS Spectrum (Can be used for single scanning UV-VIS-NIR.)';\n        case 8:\n            return 'X-ray Diffraction Spectrum';\n        case 9:\n            return 'Mass Spectrum  (Can be single, GC-MS, Continuum, Centroid or TOF.)';\n        case 10:\n            return 'NMR Spectrum or FID';\n        case 11:\n            return 'Raman Spectrum (Usually Diode Array, CCD, etc. use SPCFTIR for FT-Raman.)';\n        case 12:\n            return 'Fluorescence Spectrum';\n        case 13:\n            return 'Atomic Spectrum';\n        case 14:\n            return 'Chromatography Diode Array Spectra';\n        default:\n            return 'General SPC (could be anything)';\n    }\n}\n//# sourceMappingURL=types.js.map","/**\n * Gets the parameter in each bit of the flag\n *\n * @param  flag First byte of the main header.\n * @returns  The parameters.\n */\nexport class FlagParameters {\n    constructor(flag) {\n        this.y16BitPrecision = (flag & 1) !== 0; //Y values are 16 bits instead of 32\n        this.useExperimentExtension = (flag & 2) !== 0; //Enable experiment mode\n        this.multiFile = (flag & 4) !== 0; //Multiple spectra (multifile)\n        this.zValuesRandom = (flag & 8) !== 0; //Z values in random order if multiFile\n        this.zValuesUneven = (flag & 16) !== 0; //Z values ordered but unevenly spaced if multi\n        this.customAxisLabels = (flag & 32) !== 0; //Custom labels\n        this.xyxy = (flag & 64) !== 0; //One X array per subfile, for discontinuous curves\n        this.xy = (flag & 128) !== 0; // Non-evenly spaced X, X before Y\n    }\n}\n/**\n * Gets the date encoded in binary in a long number.\n * @param  long Binary date.\n * @return  Date formatted to ISO 8601:2019 convention.\n */\nexport function longToDate(long) {\n    if (long === 0) {\n        return '0000-00-00T00:00:00.00Z';\n    }\n    const date = new Date();\n    date.setUTCFullYear(long >> 20);\n    date.setUTCMonth(((long >> 16) & 0x0f) - 1);\n    date.setUTCDate((long >> 11) & 0x1f);\n    date.setUTCHours((long >> 6) & 0x1f);\n    date.setUTCMinutes(long & 0x3f);\n    date.setUTCSeconds(0);\n    date.setUTCMilliseconds(0);\n    return date.toISOString();\n}\n//# sourceMappingURL=headerUtils.js.map","import { xzwTypes, yTypes, experimentSettings } from './types';\nimport { FlagParameters, longToDate } from './utility/headerUtils';\n/**\n * Old-format File-header parsing.\n * @param buffer spc buffer.\n * @param  prev `{parameters,fileversion}`\n * @return  file metadata\n */\nexport class TheOldHeader {\n    constructor(buffer, prev) {\n        this.fileVersion = prev.fileVersion; //Each bit contains a parameter\n        this.parameters = prev.parameters; //4B => New format; 4D => LabCalc format\n        this.exponentY = buffer.readInt16(); //Word (16 bits) instead of byte\n        this.numberPoints = buffer.readFloat32();\n        this.startingX = buffer.readFloat32();\n        this.endingX = buffer.readFloat32();\n        this.xUnitsType = xzwTypes(buffer.readUint8());\n        this.yUnitsType = yTypes(buffer.readUint8());\n        const date = new Date();\n        const zTypeYear = buffer.readUint16(); //Unrelated to Z axis\n        date.setUTCFullYear(zTypeYear % 4096); // TODO: might be wrong\n        date.setUTCMonth(Math.max(buffer.readUint8() - 1, 0));\n        date.setUTCDate(buffer.readUint8());\n        date.setUTCHours(buffer.readUint8());\n        date.setUTCMinutes(buffer.readUint8());\n        this.date = date.toISOString();\n        this.resolutionDescription = buffer\n            .readChars(8)\n            .replace(/\\x00/g, '')\n            .trim();\n        this.peakPointNumber = buffer.readUint16();\n        this.scans = buffer.readUint16();\n        this.spare = [];\n        for (let i = 0; i < 7; i++) {\n            this.spare.push(buffer.readFloat32());\n        }\n        this.memo = buffer.readChars(130).replace(/\\x00/g, '').trim();\n        this.xyzLabels = buffer.readChars(30).replace(/\\x00/g, '').trim();\n    }\n}\n/**\n * New format file-header parsing.\n * @param buffer spc buffer.\n * @param  prev `{parameters,fileversion}`\n * @return  file metadata\n */\nexport class TheNewHeader {\n    constructor(buffer, prev) {\n        this.fileVersion = prev.fileVersion; //Each bit contains a parameter\n        this.parameters = prev.parameters; //4B => New format; 4D => LabCalc format\n        this.experimentType = experimentSettings(buffer.readUint8()); //Experiment type code (See SPC.h)\n        this.exponentY = buffer.readInt8(); //Exponent for Y values (80h = floating point): FloatY = (2^Exp)*IntY/(2^32) 32-bit; FloatY = (2^Exp)*IntY/(2^16) 32-bit\n        this.numberPoints = buffer.readUint32(); //Number of points (if not XYXY)\n        this.startingX = buffer.readFloat64(); //First X coordinate\n        this.endingX = buffer.readFloat64(); //Last X coordinate\n        this.spectra = buffer.readUint32(); //Number of spectrums\n        this.xUnitsType = xzwTypes(buffer.readUint8()); //X Units type code (See types.js)\n        this.yUnitsType = yTypes(buffer.readUint8()); //Y \"\"\n        this.zUnitsType = xzwTypes(buffer.readUint8()); //Z \"\"\n        this.postingDisposition = buffer.readUint8(); //Posting disposition (See GRAMSDDE.H)\n        this.date = longToDate(buffer.readUint32()); //Date: minutes = first 6 bits, hours = 5 next bits, days = 5 next, months = 4 next, years = 12 last\n        this.resolutionDescription = buffer\n            .readChars(9)\n            .replace(/\\x00/g, '')\n            .trim(); //Resolution description text\n        this.sourceInstrumentDescription = buffer\n            .readChars(9)\n            .replace(/\\x00/g, '')\n            .trim(); // Source Instrument description text\n        this.peakPointNumber = buffer.readUint16(); //Peak point number for interferograms\n        this.spare = [];\n        for (let i = 0; i < 8; i++) {\n            this.spare.push(buffer.readFloat32());\n        }\n        if (this.fileVersion === 0x4c) {\n            //Untested case because no test files\n            this.spare.reverse();\n        }\n        this.memo = buffer.readChars(130).replace(/\\x00/g, '').trim();\n        this.xyzLabels = buffer.readChars(30).replace(/\\x00/g, '').trim();\n        this.logOffset = buffer.readUint32(); //Byte offset to Log Block\n        this.modifiedFlag = buffer.readUint32(); //File modification flag (See values in SPC.H)\n        this.processingCode = buffer.readUint8(); //Processing code (See GRAMSDDE.H)\n        this.calibrationLevel = buffer.readUint8(); //Calibration level + 1\n        this.subMethodSampleInjectionNumber = buffer.readUint16(); //Sub-method sample injection number\n        this.concentrationFactor = buffer.readFloat32(); //Floating data multiplier concentration factor\n        this.methodFile = buffer.readChars(48).replace(/\\x00/g, '').trim(); //Method file\n        this.zSubIncrement = buffer.readFloat32(); //Z subfile increment for even Z Multifiles\n        this.wPlanes = buffer.readUint32();\n        this.wPlaneIncrement = buffer.readFloat32();\n        this.wAxisUnits = xzwTypes(buffer.readUint8()); //W axis units code\n        this.reserved = buffer.readChars(187).replace(/\\x00/g, '').trim(); //Reserved space (Must be zero)\n        if (this.xUnitsType === 0) {\n            this.xUnitsType = this.xyzLabels.substring(0, 10);\n        }\n        if (this.zUnitsType === 0) {\n            this.zUnitsType = this.xyzLabels.substring(20, 30);\n        }\n    }\n}\n/**\n * File-header parsing - First 512/256 bytes (new/old format).\n * @param buffer SPC buffer.\n * @return File-header object\n */\nexport function fileHeader(buffer) {\n    const parameters = new FlagParameters(buffer.readUint8()); //Each bit contains a parameter\n    const fileVersion = buffer.readUint8(); //4B => New format; 4D => LabCalc format\n    const headerOpts = { parameters, fileVersion };\n    switch (fileVersion) {\n        case 0x4b: // new format\n            break;\n        case 0x4c:\n            buffer.setBigEndian();\n            break;\n        case 0x4d: {\n            // old LabCalc format\n            return new TheOldHeader(buffer, headerOpts);\n        }\n        default:\n            throw new Error('Unrecognized file format: byte 01 must be either 4B, 4C or 4D');\n    }\n    return new TheNewHeader(buffer, headerOpts);\n}\n//# sourceMappingURL=fileHeader.js.map","// eslint-disable-next-line import/no-unassigned-import\nimport './text-encoding-polyfill';\nexport function decode(bytes, encoding = 'utf8') {\n    const decoder = new TextDecoder(encoding);\n    return decoder.decode(bytes);\n}\nconst encoder = new TextEncoder();\nexport function encode(str) {\n    return encoder.encode(str);\n}\n//# sourceMappingURL=text.browser.js.map","import { decode, encode } from './text';\nconst defaultByteLength = 1024 * 8;\nconst hostBigEndian = (() => {\n    const array = new Uint8Array(4);\n    const view = new Uint32Array(array.buffer);\n    return !((view[0] = 1) & array[0]);\n})();\nconst typedArrays = {\n    int8: globalThis.Int8Array,\n    uint8: globalThis.Uint8Array,\n    int16: globalThis.Int16Array,\n    uint16: globalThis.Uint16Array,\n    int32: globalThis.Int32Array,\n    uint32: globalThis.Uint32Array,\n    uint64: globalThis.BigUint64Array,\n    int64: globalThis.BigInt64Array,\n    float32: globalThis.Float32Array,\n    float64: globalThis.Float64Array,\n};\nexport class IOBuffer {\n    /**\n     * @param data - The data to construct the IOBuffer with.\n     * If data is a number, it will be the new buffer's length<br>\n     * If data is `undefined`, the buffer will be initialized with a default length of 8Kb<br>\n     * If data is an ArrayBuffer, SharedArrayBuffer, an ArrayBufferView (Typed Array), an IOBuffer instance,\n     * or a Node.js Buffer, a view will be created over the underlying ArrayBuffer.\n     * @param options\n     */\n    constructor(data = defaultByteLength, options = {}) {\n        let dataIsGiven = false;\n        if (typeof data === 'number') {\n            data = new ArrayBuffer(data);\n        }\n        else {\n            dataIsGiven = true;\n            this.lastWrittenByte = data.byteLength;\n        }\n        const offset = options.offset ? options.offset >>> 0 : 0;\n        const byteLength = data.byteLength - offset;\n        let dvOffset = offset;\n        if (ArrayBuffer.isView(data) || data instanceof IOBuffer) {\n            if (data.byteLength !== data.buffer.byteLength) {\n                dvOffset = data.byteOffset + offset;\n            }\n            data = data.buffer;\n        }\n        if (dataIsGiven) {\n            this.lastWrittenByte = byteLength;\n        }\n        else {\n            this.lastWrittenByte = 0;\n        }\n        this.buffer = data;\n        this.length = byteLength;\n        this.byteLength = byteLength;\n        this.byteOffset = dvOffset;\n        this.offset = 0;\n        this.littleEndian = true;\n        this._data = new DataView(this.buffer, dvOffset, byteLength);\n        this._mark = 0;\n        this._marks = [];\n    }\n    /**\n     * Checks if the memory allocated to the buffer is sufficient to store more\n     * bytes after the offset.\n     * @param byteLength - The needed memory in bytes.\n     * @returns `true` if there is sufficient space and `false` otherwise.\n     */\n    available(byteLength = 1) {\n        return this.offset + byteLength <= this.length;\n    }\n    /**\n     * Check if little-endian mode is used for reading and writing multi-byte\n     * values.\n     * @returns `true` if little-endian mode is used, `false` otherwise.\n     */\n    isLittleEndian() {\n        return this.littleEndian;\n    }\n    /**\n     * Set little-endian mode for reading and writing multi-byte values.\n     */\n    setLittleEndian() {\n        this.littleEndian = true;\n        return this;\n    }\n    /**\n     * Check if big-endian mode is used for reading and writing multi-byte values.\n     * @returns `true` if big-endian mode is used, `false` otherwise.\n     */\n    isBigEndian() {\n        return !this.littleEndian;\n    }\n    /**\n     * Switches to big-endian mode for reading and writing multi-byte values.\n     */\n    setBigEndian() {\n        this.littleEndian = false;\n        return this;\n    }\n    /**\n     * Move the pointer n bytes forward.\n     * @param n - Number of bytes to skip.\n     */\n    skip(n = 1) {\n        this.offset += n;\n        return this;\n    }\n    /**\n     * Move the pointer n bytes backward.\n     * @param n - Number of bytes to move back.\n     */\n    back(n = 1) {\n        this.offset -= n;\n        return this;\n    }\n    /**\n     * Move the pointer to the given offset.\n     * @param offset\n     */\n    seek(offset) {\n        this.offset = offset;\n        return this;\n    }\n    /**\n     * Store the current pointer offset.\n     * @see {@link IOBuffer#reset}\n     */\n    mark() {\n        this._mark = this.offset;\n        return this;\n    }\n    /**\n     * Move the pointer back to the last pointer offset set by mark.\n     * @see {@link IOBuffer#mark}\n     */\n    reset() {\n        this.offset = this._mark;\n        return this;\n    }\n    /**\n     * Push the current pointer offset to the mark stack.\n     * @see {@link IOBuffer#popMark}\n     */\n    pushMark() {\n        this._marks.push(this.offset);\n        return this;\n    }\n    /**\n     * Pop the last pointer offset from the mark stack, and set the current\n     * pointer offset to the popped value.\n     * @see {@link IOBuffer#pushMark}\n     */\n    popMark() {\n        const offset = this._marks.pop();\n        if (offset === undefined) {\n            throw new Error('Mark stack empty');\n        }\n        this.seek(offset);\n        return this;\n    }\n    /**\n     * Move the pointer offset back to 0.\n     */\n    rewind() {\n        this.offset = 0;\n        return this;\n    }\n    /**\n     * Make sure the buffer has sufficient memory to write a given byteLength at\n     * the current pointer offset.\n     * If the buffer's memory is insufficient, this method will create a new\n     * buffer (a copy) with a length that is twice (byteLength + current offset).\n     * @param byteLength\n     */\n    ensureAvailable(byteLength = 1) {\n        if (!this.available(byteLength)) {\n            const lengthNeeded = this.offset + byteLength;\n            const newLength = lengthNeeded * 2;\n            const newArray = new Uint8Array(newLength);\n            newArray.set(new Uint8Array(this.buffer));\n            this.buffer = newArray.buffer;\n            this.length = this.byteLength = newLength;\n            this._data = new DataView(this.buffer);\n        }\n        return this;\n    }\n    /**\n     * Read a byte and return false if the byte's value is 0, or true otherwise.\n     * Moves pointer forward by one byte.\n     */\n    readBoolean() {\n        return this.readUint8() !== 0;\n    }\n    /**\n     * Read a signed 8-bit integer and move pointer forward by 1 byte.\n     */\n    readInt8() {\n        return this._data.getInt8(this.offset++);\n    }\n    /**\n     * Read an unsigned 8-bit integer and move pointer forward by 1 byte.\n     */\n    readUint8() {\n        return this._data.getUint8(this.offset++);\n    }\n    /**\n     * Alias for {@link IOBuffer#readUint8}.\n     */\n    readByte() {\n        return this.readUint8();\n    }\n    /**\n     * Read `n` bytes and move pointer forward by `n` bytes.\n     */\n    readBytes(n = 1) {\n        return this.readArray(n, 'uint8');\n    }\n    /**\n     * Creates an array of corresponding to the type `type` and size `size`.\n     * For example type `uint8` will create a `Uint8Array`.\n     * @param size - size of the resulting array\n     * @param type - number type of elements to read\n     */\n    readArray(size, type) {\n        const bytes = typedArrays[type].BYTES_PER_ELEMENT * size;\n        const offset = this.byteOffset + this.offset;\n        const slice = this.buffer.slice(offset, offset + bytes);\n        if (this.littleEndian === hostBigEndian &&\n            type !== 'uint8' &&\n            type !== 'int8') {\n            const slice = new Uint8Array(this.buffer.slice(offset, offset + bytes));\n            slice.reverse();\n            const returnArray = new typedArrays[type](slice.buffer);\n            this.offset += bytes;\n            returnArray.reverse();\n            return returnArray;\n        }\n        const returnArray = new typedArrays[type](slice);\n        this.offset += bytes;\n        return returnArray;\n    }\n    /**\n     * Read a 16-bit signed integer and move pointer forward by 2 bytes.\n     */\n    readInt16() {\n        const value = this._data.getInt16(this.offset, this.littleEndian);\n        this.offset += 2;\n        return value;\n    }\n    /**\n     * Read a 16-bit unsigned integer and move pointer forward by 2 bytes.\n     */\n    readUint16() {\n        const value = this._data.getUint16(this.offset, this.littleEndian);\n        this.offset += 2;\n        return value;\n    }\n    /**\n     * Read a 32-bit signed integer and move pointer forward by 4 bytes.\n     */\n    readInt32() {\n        const value = this._data.getInt32(this.offset, this.littleEndian);\n        this.offset += 4;\n        return value;\n    }\n    /**\n     * Read a 32-bit unsigned integer and move pointer forward by 4 bytes.\n     */\n    readUint32() {\n        const value = this._data.getUint32(this.offset, this.littleEndian);\n        this.offset += 4;\n        return value;\n    }\n    /**\n     * Read a 32-bit floating number and move pointer forward by 4 bytes.\n     */\n    readFloat32() {\n        const value = this._data.getFloat32(this.offset, this.littleEndian);\n        this.offset += 4;\n        return value;\n    }\n    /**\n     * Read a 64-bit floating number and move pointer forward by 8 bytes.\n     */\n    readFloat64() {\n        const value = this._data.getFloat64(this.offset, this.littleEndian);\n        this.offset += 8;\n        return value;\n    }\n    /**\n     * Read a 64-bit signed integer number and move pointer forward by 8 bytes.\n     */\n    readBigInt64() {\n        const value = this._data.getBigInt64(this.offset, this.littleEndian);\n        this.offset += 8;\n        return value;\n    }\n    /**\n     * Read a 64-bit unsigned integer number and move pointer forward by 8 bytes.\n     */\n    readBigUint64() {\n        const value = this._data.getBigUint64(this.offset, this.littleEndian);\n        this.offset += 8;\n        return value;\n    }\n    /**\n     * Read a 1-byte ASCII character and move pointer forward by 1 byte.\n     */\n    readChar() {\n        return String.fromCharCode(this.readInt8());\n    }\n    /**\n     * Read `n` 1-byte ASCII characters and move pointer forward by `n` bytes.\n     */\n    readChars(n = 1) {\n        let result = '';\n        for (let i = 0; i < n; i++) {\n            result += this.readChar();\n        }\n        return result;\n    }\n    /**\n     * Read the next `n` bytes, return a UTF-8 decoded string and move pointer\n     * forward by `n` bytes.\n     */\n    readUtf8(n = 1) {\n        return decode(this.readBytes(n));\n    }\n    /**\n     * Read the next `n` bytes, return a string decoded with `encoding` and move pointer\n     * forward by `n` bytes.\n     * If no encoding is passed, the function is equivalent to @see {@link IOBuffer#readUtf8}\n     */\n    decodeText(n = 1, encoding = 'utf-8') {\n        return decode(this.readBytes(n), encoding);\n    }\n    /**\n     * Write 0xff if the passed value is truthy, 0x00 otherwise and move pointer\n     * forward by 1 byte.\n     */\n    writeBoolean(value) {\n        this.writeUint8(value ? 0xff : 0x00);\n        return this;\n    }\n    /**\n     * Write `value` as an 8-bit signed integer and move pointer forward by 1 byte.\n     */\n    writeInt8(value) {\n        this.ensureAvailable(1);\n        this._data.setInt8(this.offset++, value);\n        this._updateLastWrittenByte();\n        return this;\n    }\n    /**\n     * Write `value` as an 8-bit unsigned integer and move pointer forward by 1\n     * byte.\n     */\n    writeUint8(value) {\n        this.ensureAvailable(1);\n        this._data.setUint8(this.offset++, value);\n        this._updateLastWrittenByte();\n        return this;\n    }\n    /**\n     * An alias for {@link IOBuffer#writeUint8}.\n     */\n    writeByte(value) {\n        return this.writeUint8(value);\n    }\n    /**\n     * Write all elements of `bytes` as uint8 values and move pointer forward by\n     * `bytes.length` bytes.\n     */\n    writeBytes(bytes) {\n        this.ensureAvailable(bytes.length);\n        for (let i = 0; i < bytes.length; i++) {\n            this._data.setUint8(this.offset++, bytes[i]);\n        }\n        this._updateLastWrittenByte();\n        return this;\n    }\n    /**\n     * Write `value` as a 16-bit signed integer and move pointer forward by 2\n     * bytes.\n     */\n    writeInt16(value) {\n        this.ensureAvailable(2);\n        this._data.setInt16(this.offset, value, this.littleEndian);\n        this.offset += 2;\n        this._updateLastWrittenByte();\n        return this;\n    }\n    /**\n     * Write `value` as a 16-bit unsigned integer and move pointer forward by 2\n     * bytes.\n     */\n    writeUint16(value) {\n        this.ensureAvailable(2);\n        this._data.setUint16(this.offset, value, this.littleEndian);\n        this.offset += 2;\n        this._updateLastWrittenByte();\n        return this;\n    }\n    /**\n     * Write `value` as a 32-bit signed integer and move pointer forward by 4\n     * bytes.\n     */\n    writeInt32(value) {\n        this.ensureAvailable(4);\n        this._data.setInt32(this.offset, value, this.littleEndian);\n        this.offset += 4;\n        this._updateLastWrittenByte();\n        return this;\n    }\n    /**\n     * Write `value` as a 32-bit unsigned integer and move pointer forward by 4\n     * bytes.\n     */\n    writeUint32(value) {\n        this.ensureAvailable(4);\n        this._data.setUint32(this.offset, value, this.littleEndian);\n        this.offset += 4;\n        this._updateLastWrittenByte();\n        return this;\n    }\n    /**\n     * Write `value` as a 32-bit floating number and move pointer forward by 4\n     * bytes.\n     */\n    writeFloat32(value) {\n        this.ensureAvailable(4);\n        this._data.setFloat32(this.offset, value, this.littleEndian);\n        this.offset += 4;\n        this._updateLastWrittenByte();\n        return this;\n    }\n    /**\n     * Write `value` as a 64-bit floating number and move pointer forward by 8\n     * bytes.\n     */\n    writeFloat64(value) {\n        this.ensureAvailable(8);\n        this._data.setFloat64(this.offset, value, this.littleEndian);\n        this.offset += 8;\n        this._updateLastWrittenByte();\n        return this;\n    }\n    /**\n     * Write `value` as a 64-bit signed bigint and move pointer forward by 8\n     * bytes.\n     */\n    writeBigInt64(value) {\n        this.ensureAvailable(8);\n        this._data.setBigInt64(this.offset, value, this.littleEndian);\n        this.offset += 8;\n        this._updateLastWrittenByte();\n        return this;\n    }\n    /**\n     * Write `value` as a 64-bit unsigned bigint and move pointer forward by 8\n     * bytes.\n     */\n    writeBigUint64(value) {\n        this.ensureAvailable(8);\n        this._data.setBigUint64(this.offset, value, this.littleEndian);\n        this.offset += 8;\n        this._updateLastWrittenByte();\n        return this;\n    }\n    /**\n     * Write the charCode of `str`'s first character as an 8-bit unsigned integer\n     * and move pointer forward by 1 byte.\n     */\n    writeChar(str) {\n        return this.writeUint8(str.charCodeAt(0));\n    }\n    /**\n     * Write the charCodes of all `str`'s characters as 8-bit unsigned integers\n     * and move pointer forward by `str.length` bytes.\n     */\n    writeChars(str) {\n        for (let i = 0; i < str.length; i++) {\n            this.writeUint8(str.charCodeAt(i));\n        }\n        return this;\n    }\n    /**\n     * UTF-8 encode and write `str` to the current pointer offset and move pointer\n     * forward according to the encoded length.\n     */\n    writeUtf8(str) {\n        return this.writeBytes(encode(str));\n    }\n    /**\n     * Export a Uint8Array view of the internal buffer.\n     * The view starts at the byte offset and its length\n     * is calculated to stop at the last written byte or the original length.\n     */\n    toArray() {\n        return new Uint8Array(this.buffer, this.byteOffset, this.lastWrittenByte);\n    }\n    /**\n     * Update the last written byte offset\n     * @private\n     */\n    _updateLastWrittenByte() {\n        if (this.offset > this.lastWrittenByte) {\n            this.lastWrittenByte = this.offset;\n        }\n    }\n}\n//# sourceMappingURL=IOBuffer.js.map","import { ensureIncreasingXValues } from './utility/ensureIncreasingXValues';\n/**\n * Gets the Subfile flags.\n *\n * @param  flag First byte of the subheader.\n * @return The parameters.\n */\nexport class SubFlagParameters {\n    constructor(flag) {\n        this.changed = (flag & 1) !== 0;\n        this.noPeakTable = (flag & 8) !== 0;\n        this.modifiedArithmetic = (flag & 128) !== 0;\n    }\n}\n/**\n * Parses the subheader (header of the subfile)\n *\n * @param buffer SPC buffer.\n * @return subheader object\n */\nexport class SubHeader {\n    constructor(buffer) {\n        this.parameters = new SubFlagParameters(buffer.readUint8());\n        this.exponentY = buffer.readInt8();\n        this.indexNumber = buffer.readUint16();\n        this.startingZ = buffer.readFloat32();\n        this.endingZ = buffer.readFloat32();\n        this.noiseValue = buffer.readFloat32();\n        this.numberPoints = buffer.readUint32();\n        this.numberCoAddedScans = buffer.readUint32();\n        this.wAxisValue = buffer.readFloat32();\n        this.reserved = buffer.readChars(4).replace(/\\x00/g, '').trim();\n    }\n}\n/**\n * Set the X and Y axis (object with labels, values etc.)\n * @param x\n * @param y\n * @param fileHeader\n * @return object with x and y as axis.\n */\nexport function setXYAxis(x, y, fileHeader) {\n    var _a, _b, _c, _d;\n    const xAxis = /(?<label>.*?) ?[([](?<units>.*)[)\\]]/.exec(fileHeader.xUnitsType);\n    const yAxis = /(?<label>.*?) ?[([](?<units>.*)[)\\]]/.exec(fileHeader.yUnitsType);\n    const [oX, oY] = ensureIncreasingXValues(x, y);\n    const variables = {\n        x: {\n            symbol: 'x',\n            label: ((_a = xAxis === null || xAxis === void 0 ? void 0 : xAxis.groups) === null || _a === void 0 ? void 0 : _a.label) || fileHeader.xUnitsType,\n            units: ((_b = xAxis === null || xAxis === void 0 ? void 0 : xAxis.groups) === null || _b === void 0 ? void 0 : _b.units) || '',\n            data: oX,\n            isDependent: false,\n        },\n        y: {\n            symbol: 'y',\n            label: ((_c = yAxis === null || yAxis === void 0 ? void 0 : yAxis.groups) === null || _c === void 0 ? void 0 : _c.label) || fileHeader.yUnitsType,\n            units: ((_d = yAxis === null || yAxis === void 0 ? void 0 : yAxis.groups) === null || _d === void 0 ? void 0 : _d.units) || '',\n            data: oY,\n            isDependent: true,\n        },\n    };\n    return variables;\n}\n//# sourceMappingURL=shared.js.map","/** Ensures x-values are increasing in magnitude. It reverses y if x was reversed.\n *\n * * Does not mutate arrays\n * * Assumes that X is either increasing or decreasing, not any random order.\n * * Expects x and y to be the same length\n * @param x - array of x values\n * @param y - array of y values\n * @returns [x,y] tuple\n */\nexport function ensureIncreasingXValues(x, y) {\n    const xL = x.length;\n    if (xL !== 0) {\n        if (y.length !== xL) {\n            //wouldn't really make sense for x and y to be !==\n            throw new RangeError('x and y length must be the same');\n        }\n        const firstX = x[0];\n        const lastX = x[x.length - 1];\n        if (firstX > lastX) {\n            //apparently slice(0) faster than slice()\n            return [x.slice(0).reverse(), y.slice(0).reverse()];\n        }\n    }\n    return [x, y];\n}\n//# sourceMappingURL=ensureIncreasingXValues.js.map","import { createFromToArray } from 'ml-spectra-processing';\nimport { getDataShape } from '../utility/getDataShape';\nimport { SubHeader, setXYAxis } from './shared';\n/**\n * Reads the data block of the SPC file.\n *\n * @param buffer spc buffer.\n * @param fileHeader main header.\n * @return Array containing the spectra.\n */\nexport function newDataBlock(buffer, fileHeader) {\n    let x;\n    let spectra = [];\n    const dataShape = getDataShape(fileHeader.parameters);\n    if (dataShape === 'XY' || dataShape === 'XYY') {\n        //for these ones, X axis comes before subheader !!\n        x = new Float64Array(fileHeader.numberPoints);\n        for (let i = 0; i < fileHeader.numberPoints; i++) {\n            x[i] = buffer.readFloat32();\n        }\n    }\n    else if (dataShape === 'YY' || dataShape === 'Y') {\n        //for these ones, no X axis, we create it as we have all parameters\n        x = createFromToArray({\n            from: fileHeader.startingX,\n            to: fileHeader.endingX,\n            length: fileHeader.numberPoints,\n        });\n    }\n    for (let i = 0; i < fileHeader.spectra; i++) {\n        // here Y is set (runs only once for a single spectra.)\n        const subFileHeader = new SubHeader(buffer);\n        // set X for the remaining cases if neccesary\n        if (dataShape === 'XYXY' || dataShape === 'exception') {\n            x = new Float64Array(subFileHeader.numberPoints);\n            for (let j = 0; j < x.length; j++) {\n                x[j] = buffer.readFloat32();\n            }\n        }\n        const y = getNewY(new Float64Array(x.length), subFileHeader, fileHeader, buffer);\n        const variables = setXYAxis(x, y, fileHeader);\n        spectra.push({ meta: subFileHeader, variables });\n    }\n    return spectra;\n}\nexport function getNewY(y, subHeader, fileHeader, buffer) {\n    const { exponentY, parameters: { y16BitPrecision }, } = fileHeader;\n    if (subHeader.exponentY === 0) {\n        subHeader.exponentY = exponentY;\n    }\n    const yFactor = Math.pow(2, subHeader.exponentY - (y16BitPrecision ? 16 : 32));\n    if (y16BitPrecision) {\n        for (let j = 0; j < y.length; j++) {\n            y[j] = buffer.readInt16() * yFactor;\n        }\n    }\n    else {\n        for (let j = 0; j < y.length; j++) {\n            if (subHeader.exponentY !== -128) {\n                y[j] = buffer.readInt32() * yFactor;\n            }\n            else {\n                y[j] = buffer.readFloat32();\n            }\n        }\n    }\n    return y;\n}\n//# sourceMappingURL=newDataBlock.js.map","import { createFromToArray } from 'ml-spectra-processing';\nimport { SubHeader, setXYAxis } from './shared';\n/**\n * Reads a file's data block (old SPC format)\n *\n * @param buffer spc buffer.\n * @param fileHeader header.\n * @return Array containing the spectra.\n */\nexport function oldDataBlock(buffer, fileHeader) {\n    // either Y or YY fall on the for loop\n    let spectra = [];\n    // old format uses always equidistant arrays\n    const x = createFromToArray({\n        from: fileHeader.startingX,\n        to: fileHeader.endingX,\n        length: fileHeader.numberPoints,\n    });\n    for (let i = 0; buffer.offset + fileHeader.numberPoints < buffer.length; i++) {\n        const subFileHeader = new SubHeader(buffer);\n        const y = getOldY(new Float64Array(x.length), subFileHeader, fileHeader, buffer);\n        const variables = setXYAxis(x, y, fileHeader);\n        spectra.push({ meta: subFileHeader, variables });\n    }\n    return spectra;\n}\n/**\n *\n *\n * @export\n * @param {Float64Array} y\n * @param {SubHeader} subHeader\n * @param {TheOldHeader} fileHeader\n * @param {IOBuffer} buffer\n * @return {*}\n */\nexport function getOldY(y, subHeader, fileHeader, buffer) {\n    const { fileVersion, exponentY, parameters: { y16BitPrecision }, } = fileHeader;\n    if (subHeader.exponentY === 0) {\n        subHeader.exponentY = exponentY;\n    }\n    const yFactor = Math.pow(2, subHeader.exponentY - (y16BitPrecision ? 16 : 32));\n    if (y16BitPrecision) {\n        for (let j = 0; j < y.length; j++) {\n            y[j] = buffer.readInt16() * yFactor;\n        }\n    }\n    else {\n        for (let j = 0; j < y.length; j++) {\n            if (fileVersion === 0x4d) {\n                y[j] =\n                    ((buffer.readUint8() << 16) +\n                        (buffer.readInt8() << 24) +\n                        (buffer.readUint8() << 0) +\n                        (buffer.readUint8() << 8)) *\n                        yFactor;\n            }\n        }\n    }\n    return y;\n}\n//# sourceMappingURL=oldDataBlock.js.map","import { IOBuffer } from 'iobuffer';\nimport { newDataBlock } from './dataBlock/newDataBlock';\nimport { oldDataBlock } from './dataBlock/oldDataBlock';\nimport { fileHeader, TheNewHeader } from './fileHeader';\nimport { readLogBlock } from './logBlock';\n/**\n * Parses an SPC file.\n *\n * @param  buffer SPC file buffer.\n * @return JSON-like object with information contained in the SPC file.\n */\nexport function parse(buffer) {\n    const ioBuffer = new IOBuffer(buffer);\n    const meta = fileHeader(ioBuffer);\n    if (meta instanceof TheNewHeader) {\n        //new format\n        const spectra = newDataBlock(ioBuffer, meta);\n        const logs = meta.logOffset !== 0 ? readLogBlock(ioBuffer, meta.logOffset) : null;\n        return { meta, spectra, logs };\n    }\n    else {\n        //old format\n        return {\n            meta,\n            spectra: oldDataBlock(ioBuffer, meta),\n        };\n    }\n}\n//# sourceMappingURL=parse.js.map","/** Get how the data was stored\n * @param multiFile - whether there are multiple spectra (subfiles) or not.\n * @param xy - uneven x values\n * @param xyxy - multifile with separate x axis\n * @return the shape of the data as a string\n */\nexport function getDataShape({ multiFile, xy, xyxy, }) {\n    /* single file */\n    if (!multiFile) {\n        // Y or XY,\n        return !xy ? 'Y' : xyxy ? 'exception' : 'XY';\n    }\n    /* then multifile */\n    if (!xy) {\n        /* even X - equidistant */\n        return 'YY';\n    }\n    else {\n        // uneven x\n        return !xyxy ? 'XYY' : 'XYXY';\n    }\n}\n//# sourceMappingURL=getDataShape.js.map","/**\n *\n * @param  buffer SPC buffer.\n * @param  logOffset Offset of the log (from mainHeader).\n * @return  Object containing log meta, data and text.\n */\nexport function readLogBlock(buffer, logOffset) {\n    let logHeader = {\n        size: buffer.readUint32(),\n        memorySize: buffer.readUint32(),\n        textOffset: buffer.readUint32(),\n        binarySize: buffer.readUint32(),\n        diskArea: buffer.readUint32(),\n        reserved: buffer.readChars(44).trim().replace(/\\x00/g, ''), //Reserved space\n    };\n    const logData = buffer.readChars(logHeader.binarySize);\n    buffer.offset = logOffset + logHeader.textOffset;\n    const logASCII = buffer\n        .readChars(logHeader.size - logHeader.textOffset)\n        .trim()\n        .replace(/\\x00/g, '');\n    return { meta: logHeader, data: logData, text: logASCII };\n}\n//# sourceMappingURL=logBlock.js.map","import { JSGraph as OriginalJSGraph } from 'common-spectrum';\n\nimport { getAnnotations } from './jsgraph/getAnnotations';\n\nexport {\n  Analysis,\n  AnalysesManager,\n  toJcamp,\n  peakPicking,\n  autoPeakPicking,\n} from 'common-spectrum';\n\nexport { fromJcamp } from './from/fromJcamp';\nexport { fromSPC } from './from/fromSPC';\n\nexport const JSGraph = { ...OriginalJSGraph, getAnnotations };\n","import { gsd } from 'ml-gsd';\nimport { xyMaxClosestYPoint, xyMinClosestYPoint } from 'ml-spectra-processing';\nimport { getNormalizedSpectrum } from './getNormalizedSpectrum';\n/** Based on a x value we will return a peak*/\nexport function autoPeakPicking(spectrum, options = {}) {\n    var _a, _b;\n    const { xVariable = 'x', yVariable = 'y', normalizationOptions, minPeakWidth, } = options;\n    let x = (_a = spectrum.variables[xVariable]) === null || _a === void 0 ? void 0 : _a.data;\n    let y = (_b = spectrum.variables[yVariable]) === null || _b === void 0 ? void 0 : _b.data;\n    if (!x || !y)\n        return [];\n    if (normalizationOptions) {\n        const tempSpectrum = {\n            variables: {\n                x: { data: x, label: '' },\n                y: { data: y, label: '' },\n            },\n        };\n        const normalizedSpectrum = getNormalizedSpectrum(tempSpectrum, normalizationOptions);\n        x = normalizedSpectrum.variables.x.data;\n        y = normalizedSpectrum.variables.y.data;\n    }\n    if (!x || !y)\n        return;\n    let { from, to } = options;\n    let peaks = gsd({ x, y }, options);\n    if (normalizationOptions) {\n        // we need to recalculate the real count\n        const xyClosestYPoint = options.maxCriteria === undefined || options.maxCriteria\n            ? xyMaxClosestYPoint\n            : xyMinClosestYPoint;\n        for (let peak of peaks) {\n            const closest = xyClosestYPoint({ x: spectrum.variables.x.data, y: spectrum.variables.y.data }, { target: peak.x });\n            peak.x = closest.x;\n            peak.y = closest.y;\n        }\n    }\n    if (from !== undefined) {\n        peaks = peaks.filter((peak) => peak.x >= from);\n    }\n    if (to !== undefined) {\n        peaks = peaks.filter((peak) => peak.x <= to);\n    }\n    if (minPeakWidth) {\n        peaks = peaks.filter((peak) => peak.width >= minPeakWidth);\n    }\n    return peaks.map((peak) => {\n        const result = {};\n        for (const [key, variable] of Object.entries(spectrum.variables)) {\n            result[key] = variable.data[peak.index];\n        }\n        result.width = peak.width;\n        return result;\n    });\n}\n//# 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{ fromJcamp as commonFromJcamp } from 'common-spectrum';\n\nimport { spectrumCallback } from './utils/spectrumCallback';\n\n/**\n * Creates a new Analysis from a SPC buffer\n * @param {ArrayBuffer|string} jcamp\n * @param {object} [options={}]\n * @param {string|number} [options.id=Math.random()]\n * @param {string} [options.label=options.id] human redeable label\n * @param {string} [options.spectrumCallback] a callback to apply on variables when creating spectrum. Default will add a and t\n * @return {Analysis} - New class element with the given data\n */\nexport function fromJcamp(jcamp, options = {}) {\n  return commonFromJcamp(jcamp, { ...options, spectrumCallback });\n}\n","import { Analysis } from 'common-spectrum';\nimport { parse } from 'spc-parser';\n\nimport { spectrumCallback } from './utils/spectrumCallback';\n\n/**\n * Creates a new Analysis from a SPC buffer\n * @param {ArrayBuffer} buffer\n * @param {object} [options={}]\n * @param {object} [options.id=Math.random()]\n * @param {string} [options.label=options.id] human redeable label\n * @param {string} [options.spectrumCallback] a callback to apply on variables when creating spectrum. Default will add a and t\n * @return {Analysis} - New class element with the given data\n */\n\nexport function fromSPC(buffer, options = {}) {\n  let analysis = new Analysis({ ...options, spectrumCallback });\n  let result = parse(buffer);\n\n  if (result.meta) delete result.meta.parameters;\n\n  for (let spectrum of result.spectra) {\n    if (spectrum.meta) delete spectrum.meta.parameters;\n    analysis.pushSpectrum(spectrum.variables, {\n      dataType: 'IR SPECTRUM',\n      title: '',\n      meta: { ...result.meta, ...spectrum.meta },\n    });\n  }\n  return analysis;\n}\n","import { optimize as optimizePeak } from 'ml-spectra-fitting';\nimport { xFindClosestIndex, xMaxValue } from 'ml-spectra-processing';\n/** Based on a x value we will return a peak\n * if you set optimize=True the returned positions will be\n * the closest actual datapoints to the fitted peak location.\n * the x/y of the fitted peak will be in xOptimized and yOptimized\n */\nexport function peakPicking(spectrum, \n/** value to search (on x axis) */\ntarget, options = {}) {\n    var _a, _b, _c;\n    const { xVariable = 'x', yVariable = 'y', optimize = false, max: isMax = true, shape = { kind: 'gaussian', fwhm: 1 }, } = options;\n    const x = (_a = spectrum.variables[xVariable]) === null || _a === void 0 ? void 0 : _a.data;\n    let y;\n    if (!isMax) {\n        y = (_b = spectrum.variables[yVariable]) === null || _b === void 0 ? void 0 : _b.data.slice(); // do deep copy as we maybe need to flip sign\n    }\n    else {\n        y = (_c = spectrum.variables[yVariable]) === null || _c === void 0 ? void 0 : _c.data;\n    }\n    if (!x || !y)\n        return;\n    let targetIndex;\n    targetIndex = xFindClosestIndex(x, target);\n    let optimizedPeak;\n    let optimizedIndex;\n    const result = {};\n    if (optimize) {\n        if (!isMax) {\n            let maximumY = xMaxValue(y);\n            for (let i = 0; i < y.length; i++) {\n                y[i] *= -1;\n                y[i] += maximumY; // This makes it somewhat more robust\n            }\n        }\n        optimizedPeak = optimizePeak({ x, y }, [{ x: x[targetIndex], y: y[targetIndex] }], { shape });\n        optimizedIndex = xFindClosestIndex(x, optimizedPeak.peaks[0].x);\n        for (let [key, variable] of Object.entries(spectrum.variables)) {\n            result[key] = variable.data[optimizedIndex];\n        }\n        result.optimized = optimizedPeak.peaks[0];\n    }\n    else {\n        for (let [key, variable] of Object.entries(spectrum.variables)) {\n            result[key] = variable.data[targetIndex];\n        }\n    }\n    return result;\n}\n//# 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