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{"version":3,"file":"index.mjs","sources":["../../../../node_modules/lodash-es/_arrayAggregator.js","../../../../node_modules/lodash-es/_baseAggregator.js","../../../../node_modules/lodash-es/_createAggregator.js","../../../../node_modules/lodash-es/fromPairs.js","../../../../node_modules/lodash-es/groupBy.js","../../../../node_modules/d3-array/src/count.js","../../../../node_modules/d3-array/src/identity.js","../../../../node_modules/d3-array/src/sort.js","../../../../node_modules/d3-array/src/array.js","../../../../node_modules/d3-array/src/constant.js","../../../../node_modules/d3-array/src/nice.js","../../../../node_modules/d3-array/src/threshold/sturges.js","../../../../node_modules/d3-array/src/bin.js","../../../../node_modules/d3-array/src/quickselect.js","../../../../node_modules/d3-array/src/quantile.js","../../../../node_modules/d3/node_modules/d3-shape/src/offset/none.js","../../../../node_modules/d3/node_modules/d3-shape/src/order/none.js","../../../../node_modules/d3/node_modules/d3-shape/src/stack.js","../../../../node_modules/d3/node_modules/d3-shape/src/offset/diverging.js","../../src/model/model.ts","../../src/model/cartesian-charts.ts","../../src/model/alluvial.ts","../../src/model/boxplot.ts","../../src/model/bullet.ts","../../src/model/choropleth.ts","../../src/model/circle-pack.ts","../../src/model/pie.ts","../../src/model/gauge.ts","../../src/model/heatmap.ts","../../src/model/binned-charts.ts","../../src/model/meter.ts","../../src/model/radar.ts","../../src/model/tree.ts","../../src/model/treemap.ts","../../src/model/wordcloud.ts"],"sourcesContent":["/**\n * A specialized version of `baseAggregator` for arrays.\n *\n * @private\n * @param {Array} [array] The array to iterate over.\n * @param {Function} setter The function to set `accumulator` values.\n * @param {Function} iteratee The iteratee to transform keys.\n * @param {Object} accumulator The initial aggregated object.\n * @returns {Function} Returns `accumulator`.\n */\nfunction arrayAggregator(array, setter, iteratee, accumulator) {\n var index = -1,\n length = array == null ? 0 : array.length;\n\n while (++index < length) {\n var value = array[index];\n setter(accumulator, value, iteratee(value), array);\n }\n return accumulator;\n}\n\nexport default arrayAggregator;\n","import baseEach from './_baseEach.js';\n\n/**\n * Aggregates elements of `collection` on `accumulator` with keys transformed\n * by `iteratee` and values set by `setter`.\n *\n * @private\n * @param {Array|Object} collection The collection to iterate over.\n * @param {Function} setter The function to set `accumulator` values.\n * @param {Function} iteratee The iteratee to transform keys.\n * @param {Object} accumulator The initial aggregated object.\n * @returns {Function} Returns `accumulator`.\n */\nfunction baseAggregator(collection, setter, iteratee, accumulator) {\n baseEach(collection, function(value, key, collection) {\n setter(accumulator, value, iteratee(value), collection);\n });\n return accumulator;\n}\n\nexport default baseAggregator;\n","import arrayAggregator from './_arrayAggregator.js';\nimport baseAggregator from './_baseAggregator.js';\nimport baseIteratee from './_baseIteratee.js';\nimport isArray from './isArray.js';\n\n/**\n * Creates a function like `_.groupBy`.\n *\n * @private\n * @param {Function} setter The function to set accumulator values.\n * @param {Function} [initializer] The accumulator object initializer.\n * @returns {Function} Returns the new aggregator function.\n */\nfunction createAggregator(setter, initializer) {\n return function(collection, iteratee) {\n var func = isArray(collection) ? arrayAggregator : baseAggregator,\n accumulator = initializer ? initializer() : {};\n\n return func(collection, setter, baseIteratee(iteratee, 2), accumulator);\n };\n}\n\nexport default createAggregator;\n","/**\n * The inverse of `_.toPairs`; this method returns an object composed\n * from key-value `pairs`.\n *\n * @static\n * @memberOf _\n * @since 4.0.0\n * @category Array\n * @param {Array} pairs The key-value pairs.\n * @returns {Object} Returns the new object.\n * @example\n *\n * _.fromPairs([['a', 1], ['b', 2]]);\n * // => { 'a': 1, 'b': 2 }\n */\nfunction fromPairs(pairs) {\n var index = -1,\n length = pairs == null ? 0 : pairs.length,\n result = {};\n\n while (++index < length) {\n var pair = pairs[index];\n result[pair[0]] = pair[1];\n }\n return result;\n}\n\nexport default fromPairs;\n","import baseAssignValue from './_baseAssignValue.js';\nimport createAggregator from './_createAggregator.js';\n\n/** Used for built-in method references. */\nvar objectProto = Object.prototype;\n\n/** Used to check objects for own properties. */\nvar hasOwnProperty = objectProto.hasOwnProperty;\n\n/**\n * Creates an object composed of keys generated from the results of running\n * each element of `collection` thru `iteratee`. The order of grouped values\n * is determined by the order they occur in `collection`. The corresponding\n * value of each key is an array of elements responsible for generating the\n * key. The iteratee is invoked with one argument: (value).\n *\n * @static\n * @memberOf _\n * @since 0.1.0\n * @category Collection\n * @param {Array|Object} collection The collection to iterate over.\n * @param {Function} [iteratee=_.identity] The iteratee to transform keys.\n * @returns {Object} Returns the composed aggregate object.\n * @example\n *\n * _.groupBy([6.1, 4.2, 6.3], Math.floor);\n * // => { '4': [4.2], '6': [6.1, 6.3] }\n *\n * // The `_.property` iteratee shorthand.\n * _.groupBy(['one', 'two', 'three'], 'length');\n * // => { '3': ['one', 'two'], '5': ['three'] }\n */\nvar groupBy = createAggregator(function(result, value, key) {\n if (hasOwnProperty.call(result, key)) {\n result[key].push(value);\n } else {\n baseAssignValue(result, key, [value]);\n }\n});\n\nexport default groupBy;\n","export default function count(values, valueof) {\n let count = 0;\n if (valueof === undefined) {\n for (let value of values) {\n if (value != null && (value = +value) >= value) {\n ++count;\n }\n }\n } else {\n let index = -1;\n for (let value of values) {\n if ((value = valueof(value, ++index, values)) != null && (value = +value) >= value) {\n ++count;\n }\n }\n }\n return count;\n}\n","export default function identity(x) {\n return x;\n}\n","import ascending from \"./ascending.js\";\nimport permute from \"./permute.js\";\n\nexport default function sort(values, ...F) {\n if (typeof values[Symbol.iterator] !== \"function\") throw new TypeError(\"values is not iterable\");\n values = Array.from(values);\n let [f] = F;\n if ((f && f.length !== 2) || F.length > 1) {\n const index = Uint32Array.from(values, (d, i) => i);\n if (F.length > 1) {\n F = F.map(f => values.map(f));\n index.sort((i, j) => {\n for (const f of F) {\n const c = ascendingDefined(f[i], f[j]);\n if (c) return c;\n }\n });\n } else {\n f = values.map(f);\n index.sort((i, j) => ascendingDefined(f[i], f[j]));\n }\n return permute(values, index);\n }\n return values.sort(compareDefined(f));\n}\n\nexport function compareDefined(compare = ascending) {\n if (compare === ascending) return ascendingDefined;\n if (typeof compare !== \"function\") throw new TypeError(\"compare is not a function\");\n return (a, b) => {\n const x = compare(a, b);\n if (x || x === 0) return x;\n return (compare(b, b) === 0) - (compare(a, a) === 0);\n };\n}\n\nexport function ascendingDefined(a, b) {\n return (a == null || !(a >= a)) - (b == null || !(b >= b)) || (a < b ? -1 : a > b ? 1 : 0);\n}\n","var array = Array.prototype;\n\nexport var slice = array.slice;\nexport var map = array.map;\n","export default function constant(x) {\n return () => x;\n}\n","import {tickIncrement} from \"./ticks.js\";\n\nexport default function nice(start, stop, count) {\n let prestep;\n while (true) {\n const step = tickIncrement(start, stop, count);\n if (step === prestep || step === 0 || !isFinite(step)) {\n return [start, stop];\n } else if (step > 0) {\n start = Math.floor(start / step) * step;\n stop = Math.ceil(stop / step) * step;\n } else if (step < 0) {\n start = Math.ceil(start * step) / step;\n stop = Math.floor(stop * step) / step;\n }\n prestep = step;\n }\n}\n","import count from \"../count.js\";\n\nexport default function thresholdSturges(values) {\n return Math.max(1, Math.ceil(Math.log(count(values)) / Math.LN2) + 1);\n}\n","import {slice} from \"./array.js\";\nimport bisect from \"./bisect.js\";\nimport constant from \"./constant.js\";\nimport extent from \"./extent.js\";\nimport identity from \"./identity.js\";\nimport nice from \"./nice.js\";\nimport ticks, {tickIncrement} from \"./ticks.js\";\nimport sturges from \"./threshold/sturges.js\";\n\nexport default function bin() {\n var value = identity,\n domain = extent,\n threshold = sturges;\n\n function histogram(data) {\n if (!Array.isArray(data)) data = Array.from(data);\n\n var i,\n n = data.length,\n x,\n step,\n values = new Array(n);\n\n for (i = 0; i < n; ++i) {\n values[i] = value(data[i], i, data);\n }\n\n var xz = domain(values),\n x0 = xz[0],\n x1 = xz[1],\n tz = threshold(values, x0, x1);\n\n // Convert number of thresholds into uniform thresholds, and nice the\n // default domain accordingly.\n if (!Array.isArray(tz)) {\n const max = x1, tn = +tz;\n if (domain === extent) [x0, x1] = nice(x0, x1, tn);\n tz = ticks(x0, x1, tn);\n\n // If the domain is aligned with the first tick (which it will by\n // default), then we can use quantization rather than bisection to bin\n // values, which is substantially faster.\n if (tz[0] <= x0) step = tickIncrement(x0, x1, tn);\n\n // If the last threshold is coincident with the domain’s upper bound, the\n // last bin will be zero-width. If the default domain is used, and this\n // last threshold is coincident with the maximum input value, we can\n // extend the niced upper bound by one tick to ensure uniform bin widths;\n // otherwise, we simply remove the last threshold. Note that we don’t\n // coerce values or the domain to numbers, and thus must be careful to\n // compare order (>=) rather than strict equality (===)!\n if (tz[tz.length - 1] >= x1) {\n if (max >= x1 && domain === extent) {\n const step = tickIncrement(x0, x1, tn);\n if (isFinite(step)) {\n if (step > 0) {\n x1 = (Math.floor(x1 / step) + 1) * step;\n } else if (step < 0) {\n x1 = (Math.ceil(x1 * -step) + 1) / -step;\n }\n }\n } else {\n tz.pop();\n }\n }\n }\n\n // Remove any thresholds outside the domain.\n // Be careful not to mutate an array owned by the user!\n var m = tz.length, a = 0, b = m;\n while (tz[a] <= x0) ++a;\n while (tz[b - 1] > x1) --b;\n if (a || b < m) tz = tz.slice(a, b), m = b - a;\n\n var bins = new Array(m + 1),\n bin;\n\n // Initialize bins.\n for (i = 0; i <= m; ++i) {\n bin = bins[i] = [];\n bin.x0 = i > 0 ? tz[i - 1] : x0;\n bin.x1 = i < m ? tz[i] : x1;\n }\n\n // Assign data to bins by value, ignoring any outside the domain.\n if (isFinite(step)) {\n if (step > 0) {\n for (i = 0; i < n; ++i) {\n if ((x = values[i]) != null && x0 <= x && x <= x1) {\n bins[Math.min(m, Math.floor((x - x0) / step))].push(data[i]);\n }\n }\n } else if (step < 0) {\n for (i = 0; i < n; ++i) {\n if ((x = values[i]) != null && x0 <= x && x <= x1) {\n const j = Math.floor((x0 - x) * step);\n bins[Math.min(m, j + (tz[j] <= x))].push(data[i]); // handle off-by-one due to rounding\n }\n }\n }\n } else {\n for (i = 0; i < n; ++i) {\n if ((x = values[i]) != null && x0 <= x && x <= x1) {\n bins[bisect(tz, x, 0, m)].push(data[i]);\n }\n }\n }\n\n return bins;\n }\n\n histogram.value = function(_) {\n return arguments.length ? (value = typeof _ === \"function\" ? _ : constant(_), histogram) : value;\n };\n\n histogram.domain = function(_) {\n return arguments.length ? (domain = typeof _ === \"function\" ? _ : constant([_[0], _[1]]), histogram) : domain;\n };\n\n histogram.thresholds = function(_) {\n return arguments.length ? (threshold = typeof _ === \"function\" ? _ : constant(Array.isArray(_) ? slice.call(_) : _), histogram) : threshold;\n };\n\n return histogram;\n}\n","import {ascendingDefined, compareDefined} from \"./sort.js\";\n\n// Based on https://github.com/mourner/quickselect\n// ISC license, Copyright 2018 Vladimir Agafonkin.\nexport default function quickselect(array, k, left = 0, right = Infinity, compare) {\n k = Math.floor(k);\n left = Math.floor(Math.max(0, left));\n right = Math.floor(Math.min(array.length - 1, right));\n\n if (!(left <= k && k <= right)) return array;\n\n compare = compare === undefined ? ascendingDefined : compareDefined(compare);\n\n while (right > left) {\n if (right - left > 600) {\n const n = right - left + 1;\n const m = k - left + 1;\n const z = Math.log(n);\n const s = 0.5 * Math.exp(2 * z / 3);\n const sd = 0.5 * Math.sqrt(z * s * (n - s) / n) * (m - n / 2 < 0 ? -1 : 1);\n const newLeft = Math.max(left, Math.floor(k - m * s / n + sd));\n const newRight = Math.min(right, Math.floor(k + (n - m) * s / n + sd));\n quickselect(array, k, newLeft, newRight, compare);\n }\n\n const t = array[k];\n let i = left;\n let j = right;\n\n swap(array, left, k);\n if (compare(array[right], t) > 0) swap(array, left, right);\n\n while (i < j) {\n swap(array, i, j), ++i, --j;\n while (compare(array[i], t) < 0) ++i;\n while (compare(array[j], t) > 0) --j;\n }\n\n if (compare(array[left], t) === 0) swap(array, left, j);\n else ++j, swap(array, j, right);\n\n if (j <= k) left = j + 1;\n if (k <= j) right = j - 1;\n }\n\n return array;\n}\n\nfunction swap(array, i, j) {\n const t = array[i];\n array[i] = array[j];\n array[j] = t;\n}\n","import max from \"./max.js\";\nimport maxIndex from \"./maxIndex.js\";\nimport min from \"./min.js\";\nimport minIndex from \"./minIndex.js\";\nimport quickselect from \"./quickselect.js\";\nimport number, {numbers} from \"./number.js\";\nimport {ascendingDefined} from \"./sort.js\";\nimport greatest from \"./greatest.js\";\n\nexport default function quantile(values, p, valueof) {\n values = Float64Array.from(numbers(values, valueof));\n if (!(n = values.length) || isNaN(p = +p)) return;\n if (p <= 0 || n < 2) return min(values);\n if (p >= 1) return max(values);\n var n,\n i = (n - 1) * p,\n i0 = Math.floor(i),\n value0 = max(quickselect(values, i0).subarray(0, i0 + 1)),\n value1 = min(values.subarray(i0 + 1));\n return value0 + (value1 - value0) * (i - i0);\n}\n\nexport function quantileSorted(values, p, valueof = number) {\n if (!(n = values.length) || isNaN(p = +p)) return;\n if (p <= 0 || n < 2) return +valueof(values[0], 0, values);\n if (p >= 1) return +valueof(values[n - 1], n - 1, values);\n var n,\n i = (n - 1) * p,\n i0 = Math.floor(i),\n value0 = +valueof(values[i0], i0, values),\n value1 = +valueof(values[i0 + 1], i0 + 1, values);\n return value0 + (value1 - value0) * (i - i0);\n}\n\nexport function quantileIndex(values, p, valueof = number) {\n if (isNaN(p = +p)) return;\n numbers = Float64Array.from(values, (_, i) => number(valueof(values[i], i, values)));\n if (p <= 0) return minIndex(numbers);\n if (p >= 1) return maxIndex(numbers);\n var numbers,\n index = Uint32Array.from(values, (_, i) => i),\n j = numbers.length - 1,\n i = Math.floor(j * p);\n quickselect(index, i, 0, j, (i, j) => ascendingDefined(numbers[i], numbers[j]));\n i = greatest(index.subarray(0, i + 1), (i) => numbers[i]);\n return i >= 0 ? i : -1;\n}\n","export default function(series, order) {\n if (!((n = series.length) > 1)) return;\n for (var i = 1, j, s0, s1 = series[order[0]], n, m = s1.length; i < n; ++i) {\n s0 = s1, s1 = series[order[i]];\n for (j = 0; j < m; ++j) {\n s1[j][1] += s1[j][0] = isNaN(s0[j][1]) ? s0[j][0] : s0[j][1];\n }\n }\n}\n","export default function(series) {\n var n = series.length, o = new Array(n);\n while (--n >= 0) o[n] = n;\n return o;\n}\n","import array from \"./array.js\";\nimport constant from \"./constant.js\";\nimport offsetNone from \"./offset/none.js\";\nimport orderNone from \"./order/none.js\";\n\nfunction stackValue(d, key) {\n return d[key];\n}\n\nfunction stackSeries(key) {\n const series = [];\n series.key = key;\n return series;\n}\n\nexport default function() {\n var keys = constant([]),\n order = orderNone,\n offset = offsetNone,\n value = stackValue;\n\n function stack(data) {\n var sz = Array.from(keys.apply(this, arguments), stackSeries),\n i, n = sz.length, j = -1,\n oz;\n\n for (const d of data) {\n for (i = 0, ++j; i < n; ++i) {\n (sz[i][j] = [0, +value(d, sz[i].key, j, data)]).data = d;\n }\n }\n\n for (i = 0, oz = array(order(sz)); i < n; ++i) {\n sz[oz[i]].index = i;\n }\n\n offset(sz, oz);\n return sz;\n }\n\n stack.keys = function(_) {\n return arguments.length ? (keys = typeof _ === \"function\" ? _ : constant(Array.from(_)), stack) : keys;\n };\n\n stack.value = function(_) {\n return arguments.length ? (value = typeof _ === \"function\" ? _ : constant(+_), stack) : value;\n };\n\n stack.order = function(_) {\n return arguments.length ? (order = _ == null ? orderNone : typeof _ === \"function\" ? _ : constant(Array.from(_)), stack) : order;\n };\n\n stack.offset = function(_) {\n return arguments.length ? (offset = _ == null ? offsetNone : _, stack) : offset;\n };\n\n return stack;\n}\n","export default function(series, order) {\n if (!((n = series.length) > 0)) return;\n for (var i, j = 0, d, dy, yp, yn, n, m = series[order[0]].length; j < m; ++j) {\n for (yp = yn = 0, i = 0; i < n; ++i) {\n if ((dy = (d = series[order[i]][j])[1] - d[0]) > 0) {\n d[0] = yp, d[1] = yp += dy;\n } else if (dy < 0) {\n d[1] = yn, d[0] = yn += dy;\n } else {\n d[0] = 0, d[1] = dy;\n }\n }\n }\n}\n","import { bin as d3Bin, scaleOrdinal, stack, stackOffsetDiverging } from 'd3'\nimport { cloneDeep, fromPairs, groupBy, merge, uniq } from 'lodash-es'\nimport { getProperty, updateLegendAdditionalItems } from '@/tools'\nimport { color as colorConfigs, legend as legendConfigs } from '@/configuration'\nimport { histogram as histogramConfigs } from '@/configuration-non-customizable'\nimport { Events, ScaleTypes, ColorClassNameTypes } from '@/interfaces/enums'\nimport { formatDateTillMilliSeconds } from '@/services/time-series'\nimport type { ChartTabularData } from '@/interfaces/model'\n\nexport type StackKeysParams = {\n\tbins?: any\n\tgroups?: any\n\tpercentage?: any\n\tdivergent?: any\n}\n\nfunction _sanitizeCsvCell(cellContent: string): string {\n\tconst _trimmedCell = cellContent.trim()\n\tif (['=', '+', '-', '@', '\\t', '\\r'].includes(_trimmedCell.charAt(0))) {\n\t\treturn `\\xA0${_trimmedCell}`\n\t}\n\n\t// Only add quotes if cell contains commas, newlines, or quotes\n\tif (/[,\\\"\\n]/.test(_trimmedCell)) {\n\t\treturn `\"${_trimmedCell}\"`\n\t}\n\n\treturn _trimmedCell\n}\n\n/** The charting model layer which includes mainly the chart data and options,\n * as well as some misc. information to be shared among components */\nexport class ChartModel {\n\tprotected services: any\n\n\t// Internal Model state\n\tprotected state: any = {\n\t\toptions: {}\n\t}\n\n\t// Data labels\n\t/**\n\t * A list of all the data groups that have existed within the lifetime of the chart\n\t * @type string[]\n\t */\n\tprotected allDataGroups: string[]\n\n\t// Fill scales & fill related objects\n\tprotected colorScale: any = {}\n\n\tprotected colorClassNames: any = {}\n\n\tconstructor(services: any) {\n\t\tthis.services = services\n\t}\n\n\tformatTable({ headers, cells }) {\n\t\tconst options = this.getOptions()\n\t\tconst {\n\t\t\tcode: localeCode,\n\t\t\tdate: dateFormatter,\n\t\t\tnumber: numberFormatter\n\t\t} = getProperty(options, 'locale')\n\t\tconst tableHeadingFormatter = getProperty(options, 'tabularRepModal', 'tableHeadingFormatter')\n\t\tconst tableCellFormatter = getProperty(options, 'tabularRepModal', 'tableCellFormatter')\n\t\tconst { cartesianScales } = this.services\n\t\tconst domainScaleType = cartesianScales?.getDomainAxisScaleType()\n\t\tlet domainValueFormatter: any\n\n\t\tif (domainScaleType === ScaleTypes.TIME) {\n\t\t\tdomainValueFormatter = (d: any) =>\n\t\t\t\tdateFormatter(d, localeCode, { month: 'short', day: 'numeric', year: 'numeric' })\n\t\t}\n\n\t\tconst result = [\n\t\t\ttypeof tableHeadingFormatter === 'function' ? tableHeadingFormatter(headers) : headers,\n\t\t\t...(typeof tableCellFormatter === 'function'\n\t\t\t\t? tableCellFormatter(cells)\n\t\t\t\t: cells.map((data: (string | number)[]) => {\n\t\t\t\t\t\tif (domainValueFormatter) {\n\t\t\t\t\t\t\tdata[1] = domainValueFormatter(data[1]) as string\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor (const i in data) {\n\t\t\t\t\t\t\tconst val = data[i]\n\t\t\t\t\t\t\tif (typeof val === 'number') {\n\t\t\t\t\t\t\t\tdata[i] = numberFormatter(val, localeCode)\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t\treturn data\n\t\t\t\t\t}))\n\t\t]\n\t\treturn result\n\t}\n\n\tgetAllDataFromDomain(groups?: any) {\n\t\tif (!this.getData()) {\n\t\t\treturn null\n\t\t}\n\t\tconst options = this.getOptions()\n\t\t// Remove datasets that have been disabled\n\t\tlet allData = this.getData()\n\t\tconst dataGroups = this.getDataGroups()\n\t\tconst { groupMapsTo } = getProperty(options, 'data')\n\t\tconst axesOptions = getProperty(options, 'axes')\n\n\t\t// filter out the groups that are irrelevant to the component\n\t\tif (groups) {\n\t\t\tallData = allData.filter((item: any) => groups.includes(item[groupMapsTo]))\n\t\t}\n\n\t\tif (axesOptions) {\n\t\t\tObject.keys(axesOptions).forEach(axis => {\n\t\t\t\tconst mapsTo = axesOptions[axis].mapsTo\n\t\t\t\tconst scaleType = axesOptions[axis].scaleType\n\t\t\t\t// make sure linear/log values are numbers\n\t\t\t\tif (scaleType === ScaleTypes.LINEAR || scaleType === ScaleTypes.LOG) {\n\t\t\t\t\tallData = allData.map((datum: any) => {\n\t\t\t\t\t\treturn {\n\t\t\t\t\t\t\t...datum,\n\t\t\t\t\t\t\t[mapsTo]: datum[mapsTo] === null ? datum[mapsTo] : Number(datum[mapsTo])\n\t\t\t\t\t\t}\n\t\t\t\t\t})\n\t\t\t\t}\n\n\t\t\t\t// Check for custom domain\n\t\t\t\tif (mapsTo && axesOptions[axis].domain) {\n\t\t\t\t\tif (scaleType === ScaleTypes.LABELS) {\n\t\t\t\t\t\tallData = allData.filter((datum: any) =>\n\t\t\t\t\t\t\taxesOptions[axis].domain.includes(datum[mapsTo])\n\t\t\t\t\t\t)\n\t\t\t\t\t} else {\n\t\t\t\t\t\tconst [start, end] = axesOptions[axis].domain\n\t\t\t\t\t\t// Filter out data outside domain if that datapoint is using that axis (has mapsTo property)\n\t\t\t\t\t\tallData = allData.filter(\n\t\t\t\t\t\t\t(datum: any) => !(mapsTo in datum) || (datum[mapsTo] >= start && datum[mapsTo] <= end)\n\t\t\t\t\t\t)\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t})\n\t\t}\n\n\t\treturn allData.filter((datum: any) => {\n\t\t\treturn dataGroups.find((group: any) => group.name === datum[groupMapsTo])\n\t\t})\n\t}\n\n\t/**\n\t * Charts that have group configs passed into them, only want to retrieve the display data relevant to that chart\n\t * @param groups the included datasets for the particular chart\n\t */\n\tgetDisplayData(groups?: any) {\n\t\tif (!this.get('data')) {\n\t\t\treturn null\n\t\t}\n\n\t\tconst { ACTIVE } = legendConfigs.items.status\n\t\tconst dataGroups = this.getDataGroups(groups)\n\t\tconst { groupMapsTo } = this.getOptions().data\n\t\tconst allDataFromDomain = this.getAllDataFromDomain(groups)\n\n\t\treturn allDataFromDomain.filter((datum: any) => {\n\t\t\treturn dataGroups.find(\n\t\t\t\t(dataGroup: any) => dataGroup.name === datum[groupMapsTo] && dataGroup.status === ACTIVE\n\t\t\t)\n\t\t})\n\t}\n\n\tgetData() {\n\t\treturn this.get('data')\n\t}\n\n\tisDataEmpty() {\n\t\treturn !this.getData().length\n\t}\n\n\t/**\n\t * Sets the data for the current instance.\n\t *\n\t * This method sanitizes the provided data, generates data groups,\n\t * and updates the instance's state with the sanitized data and data groups.\n\t *\n\t * @param {any} newData - The new data to be set. This data will be cloned and sanitized.\n\t * @returns {any} - The sanitized version of the provided data.\n\t */\n\tsetData(newData: any) {\n\t\tconst sanitizedData = this.sanitize(cloneDeep(newData))\n\t\tconst dataGroups = this.generateDataGroups(sanitizedData)\n\n\t\tthis.set({\n\t\t\tdata: sanitizedData,\n\t\t\tdataGroups\n\t\t})\n\n\t\treturn sanitizedData\n\t}\n\n\tgetDataGroups(groups?: any) {\n\t\tconst isDataLoading = getProperty(this.getOptions(), 'data', 'loading')\n\n\t\t// No data should be displayed while data is still loading\n\t\tif (isDataLoading) {\n\t\t\treturn []\n\t\t}\n\n\t\t// if its a combo chart, the specific chart will pass the model the groups it needs\n\t\tif (groups) {\n\t\t\treturn this.get('dataGroups').filter((dataGroup: any) => groups.includes(dataGroup.name))\n\t\t}\n\t\treturn this.get('dataGroups')\n\t}\n\n\tgetActiveDataGroups(groups?: any) {\n\t\tconst { ACTIVE } = legendConfigs.items.status\n\n\t\treturn this.getDataGroups(groups).filter((dataGroup: any) => dataGroup.status === ACTIVE)\n\t}\n\n\tgetDataGroupNames(groups?: any) {\n\t\tconst dataGroups = this.getDataGroups(groups)\n\t\treturn dataGroups.map((dataGroup: any) => dataGroup.name)\n\t}\n\n\tgetActiveDataGroupNames(groups?: any) {\n\t\tconst activeDataGroups = this.getActiveDataGroups(groups)\n\t\treturn activeDataGroups.map((dataGroup: any) => dataGroup.name)\n\t}\n\n\tprivate aggregateBinDataByGroup(bin: any) {\n\t\treturn groupBy(bin, 'group')\n\t}\n\n\tgetBinConfigurations() {\n\t\t// Manipulate data and options for Histogram\n\t\tconst data = this.getDisplayData()\n\t\tconst options = this.getOptions()\n\n\t\tconst mainXPos = this.services.cartesianScales.getMainXAxisPosition()\n\t\tconst domainIdentifier = this.services.cartesianScales.getDomainIdentifier()\n\n\t\tconst axisOptions = options.axes[mainXPos]\n\t\tconst { groupMapsTo } = options.data\n\t\tconst { bins: axisBins = histogramConfigs.defaultBins } = axisOptions\n\t\tconst areBinsDefined = Array.isArray(axisBins)\n\n\t\t// Get Histogram bins\n\t\tconst bins = d3Bin()\n\t\t\t.value((d: any) => d[domainIdentifier])\n\t\t\t.thresholds(axisBins)(data)\n\n\t\tif (!areBinsDefined) {\n\t\t\t// If bins are not defined by user\n\t\t\tconst binsWidth = bins[0].x1 - bins[0].x0\n\t\t\t// Set last bin width as the others\n\t\t\tbins[bins.length - 1].x1 = +bins[bins.length - 1].x0 + binsWidth\n\t\t} else {\n\t\t\t// Set last bin end as the last user defined one\n\t\t\tbins[bins.length - 1].x1 = axisBins[axisBins.length - 1]\n\t\t}\n\n\t\tconst binsDomain = areBinsDefined\n\t\t\t? [axisBins[0], axisBins[axisBins.length - 1]]\n\t\t\t: [bins[0].x0, bins[bins.length - 1].x1]\n\n\t\t// Get all groups\n\t\tconst groupsKeys = Array.from(new Set(data.map((d: any) => d[groupMapsTo])))\n\n\t\tconst histogramData = []\n\n\t\t// Group data by bin\n\t\tbins.forEach(bin => {\n\t\t\tconst key = `${bin.x0}-${bin.x1}`\n\t\t\tconst aggregateDataByGroup = this.aggregateBinDataByGroup(bin)\n\n\t\t\tgroupsKeys.forEach((group: string) => {\n\t\t\t\t// For each dataset put a bin with value 0 if not exist\n\t\t\t\t// (Scale X won't change when changing showed datasets)\n\t\t\t\thistogramData.push({\n\t\t\t\t\tgroup,\n\t\t\t\t\tkey,\n\t\t\t\t\tvalue: aggregateDataByGroup[group] || 0,\n\t\t\t\t\tbin: bin.x0\n\t\t\t\t})\n\t\t\t})\n\t\t})\n\n\t\treturn {\n\t\t\tbins,\n\t\t\tbinsDomain\n\t\t}\n\t}\n\n\tgetBinnedStackedData() {\n\t\tconst options = this.getOptions()\n\t\tconst { groupMapsTo } = options.data\n\n\t\tconst dataGroupNames = this.getActiveDataGroupNames()\n\n\t\tconst { bins } = this.getBinConfigurations()\n\t\tconst dataValuesGroupedByKeys = this.getDataValuesGroupedByKeys({\n\t\t\tbins\n\t\t})\n\n\t\treturn stack()\n\t\t\t.keys(dataGroupNames)(dataValuesGroupedByKeys)\n\t\t\t.map((series, i) => {\n\t\t\t\t// Add data group names to each series\n\t\t\t\treturn Object.keys(series)\n\t\t\t\t\t.filter((key: any) => !isNaN(key))\n\t\t\t\t\t.map((key: any) => {\n\t\t\t\t\t\tconst element = series[key]\n\t\t\t\t\t\telement[groupMapsTo] = dataGroupNames[i]\n\n\t\t\t\t\t\treturn element\n\t\t\t\t\t})\n\t\t\t})\n\t}\n\n\tgetGroupedData(groups?: any) {\n\t\tconst displayData = this.getDisplayData(groups)\n\t\tconst groupedData: any = {}\n\t\tconst { groupMapsTo } = this.getOptions().data\n\n\t\tdisplayData.map((datum: any) => {\n\t\t\tconst group = datum[groupMapsTo]\n\t\t\tif (groupedData[group] !== null && groupedData[group] !== undefined) {\n\t\t\t\tgroupedData[group].push(datum)\n\t\t\t} else {\n\t\t\t\tgroupedData[group] = [datum]\n\t\t\t}\n\t\t})\n\n\t\treturn Object.keys(groupedData).map(groupName => ({\n\t\t\tname: groupName,\n\t\t\tdata: groupedData[groupName]\n\t\t}))\n\t}\n\n\tgetStackKeys({ bins = null, groups = null }: StackKeysParams = { bins: null, groups: null }) {\n\t\tconst options = this.getOptions()\n\n\t\tconst displayData = this.getDisplayData(groups)\n\n\t\tlet stackKeys: any\n\t\tif (bins) {\n\t\t\tstackKeys = bins.map((bin: any) => `${bin.x0}:${bin.x1}`)\n\t\t} else {\n\t\t\tstackKeys = uniq(\n\t\t\t\tdisplayData.map((datum: any) => {\n\t\t\t\t\tconst domainIdentifier = this.services.cartesianScales.getDomainIdentifier(datum)\n\n\t\t\t\t\t// Use time value as key for Date object to avoid multiple data in the same second\n\t\t\t\t\tif (datum[domainIdentifier] instanceof Date) {\n\t\t\t\t\t\treturn formatDateTillMilliSeconds(datum[domainIdentifier])\n\t\t\t\t\t}\n\n\t\t\t\t\treturn datum[domainIdentifier] && typeof datum[domainIdentifier].toString === 'function'\n\t\t\t\t\t\t? datum[domainIdentifier].toString()\n\t\t\t\t\t\t: datum[domainIdentifier]\n\t\t\t\t})\n\t\t\t)\n\t\t}\n\n\t\tconst axisPosition = this.services.cartesianScales.domainAxisPosition\n\t\tconst scaleType = options.axes[axisPosition].scaleType\n\n\t\t// Sort keys\n\t\tif (scaleType === ScaleTypes.TIME) {\n\t\t\tstackKeys.sort((a: any, b: any) => {\n\t\t\t\tconst dateA: any = new Date(a)\n\t\t\t\tconst dateB: any = new Date(b)\n\n\t\t\t\treturn dateA - dateB\n\t\t\t})\n\t\t} else if (scaleType === ScaleTypes.LOG || scaleType === ScaleTypes.LINEAR) {\n\t\t\tstackKeys.sort((a: any, b: any) => a - b)\n\t\t}\n\n\t\treturn stackKeys\n\t}\n\n\tgetDataValuesGroupedByKeys({ bins = null, groups = null }: StackKeysParams) {\n\t\tconst options = this.getOptions()\n\t\tconst { groupMapsTo } = options.data\n\t\tconst displayData = this.getDisplayData(groups)\n\n\t\tconst dataGroupNames = this.getDataGroupNames()\n\n\t\tconst stackKeys = this.getStackKeys({ bins, groups })\n\t\tif (bins) {\n\t\t\treturn stackKeys.map((key: any) => {\n\t\t\t\tconst [binStart, binEnd] = key.split(':')\n\n\t\t\t\tconst correspondingValues: any = { x0: binStart, x1: binEnd }\n\t\t\t\tconst correspondingBin = bins.find((bin: any) => bin.x0.toString() === binStart.toString())\n\t\t\t\tdataGroupNames.forEach((dataGroupName: any) => {\n\t\t\t\t\tcorrespondingValues[dataGroupName] = correspondingBin.filter(\n\t\t\t\t\t\t(binItem: any) => binItem[groupMapsTo] === dataGroupName\n\t\t\t\t\t).length\n\t\t\t\t})\n\n\t\t\t\treturn correspondingValues\n\t\t\t}) as any\n\t\t}\n\n\t\treturn stackKeys.map((key: any) => {\n\t\t\tconst correspondingValues: any = { sharedStackKey: key }\n\t\t\tdataGroupNames.forEach((dataGroupName: any) => {\n\t\t\t\tconst correspondingDatum = displayData.find((datum: any) => {\n\t\t\t\t\tconst domainIdentifier = this.services.cartesianScales.getDomainIdentifier(datum)\n\n\t\t\t\t\treturn (\n\t\t\t\t\t\tdatum[groupMapsTo] === dataGroupName &&\n\t\t\t\t\t\tObject.prototype.hasOwnProperty.call(datum, domainIdentifier) &&\n\t\t\t\t\t\t(datum[domainIdentifier] instanceof Date\n\t\t\t\t\t\t\t? formatDateTillMilliSeconds(datum[domainIdentifier]) === key\n\t\t\t\t\t\t\t: datum[domainIdentifier].toString() === key)\n\t\t\t\t\t)\n\t\t\t\t})\n\n\t\t\t\tconst rangeIdentifier =\n\t\t\t\t\tthis.services.cartesianScales.getRangeIdentifier(correspondingValues)\n\t\t\t\tcorrespondingValues[dataGroupName] = correspondingDatum\n\t\t\t\t\t? correspondingDatum[rangeIdentifier]\n\t\t\t\t\t: null\n\t\t\t})\n\n\t\t\treturn correspondingValues\n\t\t}) as any\n\t}\n\n\tgetStackedData({ percentage = false, groups = null, divergent = false }: StackKeysParams) {\n\t\tconst options = this.getOptions()\n\t\tconst { groupMapsTo } = options.data\n\n\t\t// Get only active data groups so non-active data groups are not rendered\n\t\t// on legend item click\n\t\tconst dataGroupNames = this.getActiveDataGroupNames(groups)\n\t\tconst dataValuesGroupedByKeys = this.getDataValuesGroupedByKeys({\n\t\t\tgroups\n\t\t})\n\n\t\tif (percentage) {\n\t\t\tconst maxByKey = fromPairs(dataValuesGroupedByKeys.map((d: any) => [d.sharedStackKey, 0]))\n\n\t\t\tdataValuesGroupedByKeys.forEach((d: any) => {\n\t\t\t\tdataGroupNames.forEach((name: any) => {\n\t\t\t\t\tmaxByKey[d.sharedStackKey] += d[name]\n\t\t\t\t})\n\t\t\t})\n\n\t\t\t// cycle through data values to get percentage\n\t\t\tdataValuesGroupedByKeys.forEach((d: any) => {\n\t\t\t\tdataGroupNames.forEach((name: any) => {\n\t\t\t\t\tconst denominator: number = maxByKey[d.sharedStackKey] as number\n\t\t\t\t\tif (maxByKey[d.sharedStackKey]) {\n\t\t\t\t\t\td[name] = (d[name] / denominator) * 100\n\t\t\t\t\t} else {\n\t\t\t\t\t\td[name] = 0\n\t\t\t\t\t}\n\t\t\t\t})\n\t\t\t})\n\t\t}\n\n\t\tconst stackToUse = divergent ? stack().offset(stackOffsetDiverging) : stack()\n\n\t\treturn stackToUse\n\t\t\t.keys(dataGroupNames)(dataValuesGroupedByKeys)\n\t\t\t.map((series: any, i: number) => {\n\t\t\t\t// Add data group names to each series\n\t\t\t\treturn Object.keys(series)\n\t\t\t\t\t.filter((key: any) => !isNaN(key))\n\t\t\t\t\t.map((key: any) => {\n\t\t\t\t\t\tconst element = series[key]\n\t\t\t\t\t\telement[groupMapsTo] = dataGroupNames[i]\n\n\t\t\t\t\t\treturn element\n\t\t\t\t\t})\n\t\t\t})\n\t}\n\n\t/**\n\t * Retrieves the current options from the instance's state.\n\t *\n\t * @returns {any} - The current options stored in the instance's state.\n\t */\n\tgetOptions() {\n\t\treturn this.state.options\n\t}\n\n\tset(newState: any, configs?: any) {\n\t\tthis.state = Object.assign({}, this.state, newState)\n\t\tconst newConfig = Object.assign(\n\t\t\t{ skipUpdate: false, animate: true }, // default configs\n\t\t\tconfigs\n\t\t)\n\t\tif (!newConfig.skipUpdate) {\n\t\t\tthis.update(newConfig.animate)\n\t\t}\n\t}\n\n\tget(property?: string) {\n\t\tif (property) {\n\t\t\treturn this.state[property]\n\t\t} else {\n\t\t\treturn this.state\n\t\t}\n\t}\n\n\t/**\n\t * Updates the current options for the instance.\n\t *\n\t * This method retrieves the existing options, updates the legend additional items,\n\t * and merges the new options with the existing ones. The instance's state is then updated\n\t * with the merged options.\n\t *\n\t * @param {any} newOptions - The new options to be set. These options will be merged with the existing options.\n\t */\n\tsetOptions(newOptions: any) {\n\t\tconst options = this.getOptions()\n\t\tupdateLegendAdditionalItems(options, newOptions)\n\n\t\tthis.set({\n\t\t\toptions: merge(options, newOptions)\n\t\t})\n\t}\n\n\t/**\n\t *\n\t * Updates miscellanous information within the model\n\t * such as the color scales, or the legend data labels\n\t */\n\tupdate(animate = true) {\n\t\tif (!this.getDisplayData()) {\n\t\t\treturn\n\t\t}\n\n\t\tthis.updateAllDataGroups()\n\n\t\tthis.setCustomColorScale()\n\t\tthis.setColorClassNames()\n\t\tthis.services.events.dispatchEvent(Events.Model.UPDATE, { animate })\n\t}\n\n\t/*\n\t * Data labels\n\t */\n\ttoggleDataLabel(changedLabel: string) {\n\t\tconst { ACTIVE, DISABLED } = legendConfigs.items.status\n\t\tconst dataGroups = this.getDataGroups()\n\n\t\tconst hasDeactivatedItems = dataGroups.some((group: any) => group.status === DISABLED)\n\t\tconst activeItems = dataGroups.filter((group: any) => group.status === ACTIVE)\n\n\t\t// If there are deactivated items, toggle \"changedLabel\"\n\t\tif (hasDeactivatedItems) {\n\t\t\t// If the only active item is being toggled\n\t\t\t// Activate all items\n\t\t\tif (activeItems.length === 1 && activeItems[0].name === changedLabel) {\n\t\t\t\t// If every item is active, then enable \"changedLabel\" and disable all other items\n\t\t\t\tdataGroups.forEach((_: any, i: number) => {\n\t\t\t\t\tdataGroups[i].status = ACTIVE\n\t\t\t\t})\n\t\t\t} else {\n\t\t\t\tconst indexToChange = dataGroups.findIndex((group: any) => group.name === changedLabel)\n\t\t\t\tdataGroups[indexToChange].status =\n\t\t\t\t\tdataGroups[indexToChange].status === DISABLED ? ACTIVE : DISABLED\n\t\t\t}\n\t\t} else {\n\t\t\t// If every item is active, then enable \"changedLabel\" and disable all other items\n\t\t\tdataGroups.forEach((group: any, i: number) => {\n\t\t\t\tdataGroups[i].status = group.name === changedLabel ? ACTIVE : DISABLED\n\t\t\t})\n\t\t}\n\n\t\t// Updates selected groups\n\t\tconst updatedActiveItems = dataGroups.filter((group: any) => group.status === ACTIVE)\n\t\tconst options = this.getOptions()\n\n\t\tconst hasUpdatedDeactivatedItems = dataGroups.some((group: any) => group.status === DISABLED)\n\n\t\t// If there are deactivated items, map the item name into selected groups\n\t\tif (hasUpdatedDeactivatedItems) {\n\t\t\toptions.data.selectedGroups = updatedActiveItems.map((activeItem: any) => activeItem.name)\n\t\t} else {\n\t\t\t// If every item is active, clear array\n\t\t\toptions.data.selectedGroups = []\n\t\t}\n\n\t\t// dispatch legend filtering event with the status of all the dataLabels\n\t\tthis.services.events.dispatchEvent(Events.Legend.ITEMS_UPDATE, {\n\t\t\tdataGroups\n\t\t})\n\n\t\t// Update model\n\t\tthis.set({\n\t\t\tdataGroups\n\t\t})\n\t}\n\n\t/**\n\t * Should the data point be filled?\n\t * @param group\n\t * @param key\n\t * @param data\n\t * @param defaultFilled the default for this chart\n\t */\n\tgetIsFilled(group: any, key?: any, data?: any, defaultFilled?: boolean) {\n\t\tconst options = this.getOptions()\n\t\tif (options.getIsFilled) {\n\t\t\treturn options.getIsFilled(group, key, data, defaultFilled)\n\t\t} else {\n\t\t\treturn defaultFilled\n\t\t}\n\t}\n\n\tgetFillColor(group: any, key?: any, data?: any) {\n\t\tconst options = this.getOptions()\n\t\tconst defaultFillColor = getProperty(this.colorScale, group)\n\n\t\tif (options.getFillColor) {\n\t\t\treturn options.getFillColor(group, key, data, defaultFillColor)\n\t\t} else {\n\t\t\treturn defaultFillColor\n\t\t}\n\t}\n\n\tgetStrokeColor(group: any, key?: any, data?: any) {\n\t\tconst options = this.getOptions()\n\t\tconst defaultStrokeColor = getProperty(this.colorScale, group)\n\n\t\tif (options.getStrokeColor) {\n\t\t\treturn options.getStrokeColor(group, key, data, defaultStrokeColor)\n\t\t} else {\n\t\t\treturn defaultStrokeColor\n\t\t}\n\t}\n\n\tisUserProvidedColorScaleValid() {\n\t\tconst userProvidedScale = getProperty(this.getOptions(), 'color', 'scale')\n\t\tconst dataGroups = this.getDataGroups()\n\n\t\tif (userProvidedScale == null || Object.keys(userProvidedScale).length == 0) {\n\t\t\treturn false\n\t\t}\n\n\t\treturn dataGroups.some((dataGroup: any) =>\n\t\t\tObject.keys(userProvidedScale).includes(dataGroup.name)\n\t\t)\n\t}\n\n\tgetColorClassName(configs: {\n\t\tclassNameTypes?: ColorClassNameTypes[] // heatmaps do not pass this value\n\t\tdataGroupName?: string | number\n\t\toriginalClassName?: string\n\t\tvalue?: number // required for heatmap override\n\t}) {\n\t\tconst colorPairingTag = this.colorClassNames(configs.dataGroupName)\n\t\tlet className = configs.originalClassName\n\t\tconfigs.classNameTypes.forEach(\n\t\t\ttype =>\n\t\t\t\t(className = configs.originalClassName\n\t\t\t\t\t? `${className} ${type}-${colorPairingTag}`\n\t\t\t\t\t: `${type}-${colorPairingTag}`)\n\t\t)\n\n\t\treturn className || ''\n\t}\n\n\t/**\n\t * For charts that might hold an associated status for their dataset\n\t */\n\tgetStatus(): any {\n\t\treturn null\n\t}\n\n\tgetAllDataGroupsNames() {\n\t\treturn this.allDataGroups\n\t}\n\n\t/**\n\t * Converts data provided in the older format to tabular\n\t *\n\t */\n\tprotected transformToTabularData(data: any) {\n\t\tconsole.warn(\n\t\t\t\"We've updated the charting data format to be tabular by default. The current format you're using is deprecated and will be removed in v1.0, read more here https://charts.carbondesignsystem.com/\"\n\t\t)\n\t\tconst tabularData: ChartTabularData = []\n\t\tconst { datasets, labels } = data\n\n\t\t// Loop through all datasets\n\t\tdatasets.forEach((dataset: any) => {\n\t\t\t// Update each data point to the new format\n\t\t\tdataset.data.forEach((datum: any, i: number) => {\n\t\t\t\tlet group\n\n\t\t\t\tconst datasetLabel = getProperty(dataset, 'label')\n\t\t\t\tif (datasetLabel === null) {\n\t\t\t\t\tconst correspondingLabel = getProperty(labels, i)\n\t\t\t\t\tif (correspondingLabel) {\n\t\t\t\t\t\tgroup = correspondingLabel\n\t\t\t\t\t} else {\n\t\t\t\t\t\tgroup = 'Ungrouped'\n\t\t\t\t\t}\n\t\t\t\t} else {\n\t\t\t\t\tgroup = datasetLabel\n\t\t\t\t}\n\n\t\t\t\tconst updatedDatum: any = {\n\t\t\t\t\tgroup,\n\t\t\t\t\tkey: labels[i]\n\t\t\t\t}\n\n\t\t\t\tif (isNaN(datum)) {\n\t\t\t\t\tupdatedDatum['value'] = datum.value\n\t\t\t\t\tupdatedDatum['date'] = datum.date\n\t\t\t\t} else {\n\t\t\t\t\tupdatedDatum['value'] = datum\n\t\t\t\t}\n\n\t\t\t\ttabularData.push(updatedDatum)\n\t\t\t})\n\t\t})\n\n\t\treturn tabularData\n\t}\n\n\tgetTabularDataArray(): ChartTabularData {\n\t\t//apply tableFormatter\n\t\treturn []\n\t}\n\n\texportToCSV() {\n\t\tconst data = this.getTabularDataArray().map(row =>\n\t\t\trow.map((column: any) => {\n\t\t\t\tconst columnValue = column === '–' ? '–' : column\n\n\t\t\t\t// Split by separators and quotes, then sanitize each part individually\n\t\t\t\tconst sanitizedParts = columnValue.split(/[,;'\"`]/).map(part => _sanitizeCsvCell(part))\n\t\t\t\treturn `\"${sanitizedParts.join('')}\"`\n\t\t\t})\n\t\t)\n\n\t\tconst csvString = data.map(row => row.join(',')).join('\\n')\n\n\t\tconst options = this.getOptions()\n\n\t\tlet fileName = 'myChart'\n\t\tconst customFilename = getProperty(options, 'fileDownload', 'fileName')\n\n\t\tif (typeof customFilename === 'function') {\n\t\t\tfileName = customFilename('csv')\n\t\t} else if (typeof customFilename === 'string') {\n\t\t\tfileName = customFilename\n\t\t}\n\n\t\tthis.services.files.downloadCSV(csvString, `${fileName}.csv`)\n\t}\n\n\tprotected getTabularData(data: any) {\n\t\t// if data is not an array\n\t\tif (!Array.isArray(data)) {\n\t\t\treturn this.transformToTabularData(data)\n\t\t}\n\n\t\treturn data\n\t}\n\n\tprotected sanitize(data: any) {\n\t\tdata = this.getTabularData(data)\n\n\t\treturn data\n\t}\n\n\t/*\n\t * Data groups\n\t */\n\tprotected updateAllDataGroups() {\n\t\t// allDataGroups is used to generate a color scale that applies\n\t\t// to all the groups. Now when the data updates, you might remove a group,\n\t\t// and then bring it back in a newer data update, therefore\n\t\t// the order of the groups in allDataGroups matters so that you'd never\n\t\t// have an incorrect color assigned to a group.\n\n\t\t// Also, a new group should only be added to allDataGroups if\n\t\t// it doesn't currently exist\n\n\t\tif (!this.allDataGroups) {\n\t\t\tthis.allDataGroups = this.getDataGroupNames()\n\t\t} else {\n\t\t\t// Loop through current data groups\n\t\t\tthis.getDataGroupNames().forEach((dataGroupName: any) => {\n\t\t\t\t// If group name hasn't been stored yet, store it\n\t\t\t\tif (this.allDataGroups.indexOf(dataGroupName) === -1) {\n\t\t\t\t\tthis.allDataGroups.push(dataGroupName)\n\t\t\t\t}\n\t\t\t})\n\t\t}\n\t}\n\n\tprotected generateDataGroups(data: any) {\n\t\tconst { groupMapsTo } = this.getOptions().data\n\t\tconst { ACTIVE, DISABLED } = legendConfigs.items.status\n\t\tconst options = this.getOptions()\n\n\t\tconst uniqueDataGroups = uniq(data.map((datum: any) => datum[groupMapsTo]))\n\n\t\t// check if selectedGroups can be applied to chart with current data groups\n\t\tif (options.data.selectedGroups.length) {\n\t\t\tconst hasAllSelectedGroups = options.data.selectedGroups.every((groupName: any) =>\n\t\t\t\tuniqueDataGroups.includes(groupName)\n\t\t\t)\n\t\t\tif (!hasAllSelectedGroups) {\n\t\t\t\toptions.data.selectedGroups = []\n\t\t\t}\n\t\t}\n\n\t\t// Get group status based on items in selected groups\n\t\tconst getStatus = (groupName: any) =>\n\t\t\t!options.data.selectedGroups.length || options.data.selectedGroups.includes(groupName)\n\t\t\t\t? ACTIVE\n\t\t\t\t: DISABLED\n\n\t\treturn uniqueDataGroups.map(groupName => ({\n\t\t\tname: groupName,\n\t\t\tstatus: getStatus(groupName)\n\t\t}))\n\t}\n\n\t/*\n\t * Fill scales\n\t */\n\tprotected setCustomColorScale() {\n\t\tif (!this.isUserProvidedColorScaleValid()) {\n\t\t\treturn\n\t\t}\n\n\t\tconst options = this.getOptions()\n\t\tconst userProvidedScale = getProperty(options, 'color', 'scale')\n\n\t\tObject.keys(userProvidedScale).forEach(dataGroup => {\n\t\t\tif (!this.allDataGroups.includes(dataGroup)) {\n\t\t\t\tconsole.warn(`\"${dataGroup}\" does not exist in data groups.`)\n\t\t\t}\n\t\t})\n\n\t\t/**\n\t\t * Go through allDataGroups. If a data group has a color value provided\n\t\t * by the user, add that to the color range\n\t\t */\n\t\tconst providedDataGroups = this.allDataGroups.filter(dataGroup => userProvidedScale[dataGroup])\n\n\t\tprovidedDataGroups.forEach(\n\t\t\tdataGroup => (this.colorScale[dataGroup] = userProvidedScale[dataGroup])\n\t\t)\n\t}\n\n\t/*\n\t * Color palette\n\t */\n\tprotected setColorClassNames() {\n\t\tconst colorPairingOptions = getProperty(this.getOptions(), 'color', 'pairing')\n\n\t\t// Check if user has defined numberOfVariants (differ from given data)\n\t\tlet numberOfVariants = getProperty(colorPairingOptions, 'numberOfVariants')\n\t\tif (!numberOfVariants || numberOfVariants < this.allDataGroups.length) {\n\t\t\tnumberOfVariants = this.allDataGroups.length\n\t\t}\n\n\t\tlet pairingOption = getProperty(colorPairingOptions, 'option')\n\t\tconst colorPairingCounts = colorConfigs.pairingOptions\n\n\t\t// If number of dataGroups is greater than 5, user 14-color palette\n\t\tconst numberOfColors = numberOfVariants > 5 ? 14 : numberOfVariants\n\n\t\t// Use default palette if user choice is not in range\n\t\tconst key = `${numberOfColors}-color` as keyof typeof colorPairingCounts\n\t\tpairingOption = pairingOption <= colorPairingCounts[key] ? pairingOption : 1\n\n\t\t// Create color classes for graph, tooltip and stroke use\n\t\tconst colorPairing = this.allDataGroups.map(\n\t\t\t(_, index) => `${numberOfColors}-${pairingOption}-${(index % 14) + 1}`\n\t\t)\n\n\t\t// Create default color classnames\n\t\tthis.colorClassNames = scaleOrdinal().range(colorPairing).domain(this.allDataGroups)\n\t}\n}\n","import { cloneDeep, uniq } from 'lodash-es'\nimport { getProperty } from '@/tools'\nimport { ChartModel } from './model'\nimport { ScaleTypes, AxisPositions, AxisFlavor } from '@/interfaces/enums'\n\n/**\n * This supports adding X and Y Cartesian[2D] zoom data to a ChartModel\n * */\nexport class ChartModelCartesian extends ChartModel {\n\taxisFlavor = AxisFlavor.DEFAULT // can't be protected as it's used by two-dimensional-axes.ts\n\n\tconstructor(services: any) {\n\t\tsuper(services)\n\t}\n\n\t// get the scales information\n\t// needed for getTabularArray()\n\tprotected assignRangeAndDomains() {\n\t\tconst { cartesianScales } = this.services\n\t\tconst options = this.getOptions()\n\t\tconst isDualAxes = cartesianScales.isDualAxes()\n\n\t\tconst scales = {\n\t\t\tprimaryDomain: cartesianScales.domainAxisPosition,\n\t\t\tprimaryRange: cartesianScales.rangeAxisPosition,\n\t\t\tsecondaryDomain: null as any,\n\t\t\tsecondaryRange: null as any\n\t\t}\n\t\tif (isDualAxes) {\n\t\t\tscales.secondaryDomain = cartesianScales.secondaryDomainAxisPosition\n\t\t\tscales.secondaryRange = cartesianScales.secondaryRangeAxisPosition\n\t\t}\n\n\t\tObject.keys(scales).forEach(\n\t\t\t(scale: 'primaryDomain' | 'primaryRange' | 'secondaryDomain' | 'secondaryRange') => {\n\t\t\t\tconst position = scales[scale]\n\t\t\t\tif (cartesianScales.scales[position]) {\n\t\t\t\t\tscales[scale] = {\n\t\t\t\t\t\tposition: position,\n\t\t\t\t\t\tlabel: cartesianScales.getScaleLabel(position),\n\t\t\t\t\t\tidentifier: getProperty(options, 'axes', position, 'mapsTo')\n\t\t\t\t\t}\n\t\t\t\t} else {\n\t\t\t\t\tscales[scale] = null\n\t\t\t\t}\n\t\t\t}\n\t\t)\n\n\t\treturn scales\n\t}\n\n\tgetTabularDataArray() {\n\t\tconst displayData = this.getDisplayData()\n\t\tconst options = this.getOptions()\n\t\tconst { groupMapsTo } = options.data\n\t\tconst { primaryDomain, primaryRange, secondaryDomain, secondaryRange } =\n\t\t\tthis.assignRangeAndDomains()\n\t\tconst { number: numberFormatter, code: localeCode } = getProperty(this.getOptions(), 'locale')\n\n\t\tconst headers = [\n\t\t\t'Group',\n\t\t\tprimaryDomain.label,\n\t\t\tprimaryRange.label,\n\t\t\t...(secondaryDomain ? [secondaryDomain.label] : []),\n\t\t\t...(secondaryRange ? [secondaryRange.label] : [])\n\t\t]\n\t\tconst cells = displayData.map((datum: any) => [\n\t\t\tdatum[groupMapsTo],\n\t\t\tdatum[primaryDomain.identifier] === null ? '–' : datum[primaryDomain.identifier],\n\t\t\tdatum[primaryRange.identifier] === null || isNaN(datum[primaryRange.identifier])\n\t\t\t\t? '–'\n\t\t\t\t: numberFormatter(datum[primaryRange.identifier], localeCode),\n\t\t\t...(secondaryDomain\n\t\t\t\t? [\n\t\t\t\t\t\tdatum[secondaryDomain.identifier] === null\n\t\t\t\t\t\t\t? '–'\n\t\t\t\t\t\t\t: datum[secondaryDomain.identifier]\n\t\t\t\t\t]\n\t\t\t\t: []),\n\t\t\t...(secondaryRange\n\t\t\t\t? [\n\t\t\t\t\t\tdatum[secondaryRange.identifier] === null || isNaN(datum[secondaryRange.identifier])\n\t\t\t\t\t\t\t? '–'\n\t\t\t\t\t\t\t: datum[secondaryRange.identifier]\n\t\t\t\t\t]\n\t\t\t\t: [])\n\t\t])\n\n\t\treturn super.formatTable({ headers, cells })\n\t}\n\n\tsetData(newData: any) {\n\t\tlet data: any\n\t\tif (newData) {\n\t\t\tdata = super.setData(newData)\n\t\t\tif (getProperty(this.getOptions(), 'zoomBar', AxisPositions.TOP, 'enabled')) {\n\t\t\t\t// get pre-defined zoom bar data\n\t\t\t\tconst definedZoomBarData = getProperty(\n\t\t\t\t\tthis.getOptions(),\n\t\t\t\t\t'zoomBar',\n\t\t\t\t\tAxisPositions.TOP,\n\t\t\t\t\t'data'\n\t\t\t\t)\n\t\t\t\t// if we have zoom bar data we need to update it as well\n\t\t\t\t// with pre-defined zoom bar data\n\t\t\t\tthis.setZoomBarData(definedZoomBarData)\n\t\t\t}\n\t\t}\n\n\t\treturn data\n\t}\n\n\t/**\n\t * Sets the zoom bar data for the current instance.\n\t *\n\t * This method sanitizes the provided zoom bar data or uses the display data if no explicit\n\t * zoom data is provided. It normalizes the zoom bar data by aggregating values based on unique\n\t * dates and updates the instance's state with the normalized data.\n\t *\n\t * @param {any} [newZoomBarData] - The new zoom bar data to be set. If not provided, the display data will be used.\n\t */\n\tsetZoomBarData(newZoomBarData?: any) {\n\t\tconst sanitizedData = newZoomBarData\n\t\t\t? this.sanitize(cloneDeep(newZoomBarData))\n\t\t\t: this.getDisplayData() // if we're not passed explicit zoom data use the model\n\n\t\tlet zoomBarNormalizedValues = sanitizedData\n\n\t\tconst { cartesianScales } = this.services\n\t\tif (sanitizedData && cartesianScales.domainAxisPosition && cartesianScales.rangeAxisPosition) {\n\t\t\tconst domainIdentifier = cartesianScales.getDomainIdentifier()\n\t\t\tconst rangeIdentifier = cartesianScales.getRangeIdentifier()\n\t\t\t// get all dates (Number) in displayData\n\t\t\tlet allDates = sanitizedData.map((datum: any) => datum[domainIdentifier].getTime())\n\t\t\tallDates = uniq(allDates).sort()\n\n\t\t\t// Go through all date values\n\t\t\t// And get corresponding data from each dataset\n\t\t\tzoomBarNormalizedValues = allDates.map((date: Date) => {\n\t\t\t\tlet sum = 0\n\t\t\t\tconst datum: any = {}\n\n\t\t\t\tsanitizedData.forEach((data: any) => {\n\t\t\t\t\tif (data[domainIdentifier].getTime() === date) {\n\t\t\t\t\t\tsum += data[rangeIdentifier]\n\t\t\t\t\t}\n\t\t\t\t})\n\t\t\t\tdatum[domainIdentifier] = new Date(date)\n\t\t\t\tdatum[rangeIdentifier] = sum\n\n\t\t\t\treturn datum\n\t\t\t})\n\t\t}\n\n\t\tthis.set({ zoomBarData: zoomBarNormalizedValues })\n\t}\n\n\tgetZoomBarData() {\n\t\treturn this.get('zoomBarData')\n\t}\n\n\tprotected sanitizeDateValues(data: any) {\n\t\tconst options = this.getOptions()\n\n\t\tif (!options.axes) {\n\t\t\treturn data\n\t\t}\n\n\t\tconst keysToCheck: any[] = []\n\t\tObject.keys(AxisPositions).forEach((axisPositionKey: keyof typeof AxisPositions) => {\n\t\t\tconst axisPosition = AxisPositions[axisPositionKey]\n\t\t\tconst axisOptions = options.axes[axisPosition]\n\n\t\t\tif (axisOptions && axisOptions.scaleType === ScaleTypes.TIME) {\n\t\t\t\tconst axisMapsTo = axisOptions.mapsTo\n\n\t\t\t\tif (axisMapsTo !== null || axisMapsTo !== undefined) {\n\t\t\t\t\tkeysToCheck.push(axisMapsTo)\n\t\t\t\t}\n\t\t\t}\n\t\t})\n\n\t\tif (keysToCheck.length > 0) {\n\t\t\t// Check all datapoints and sanitize dates\n\t\t\tdata.forEach((datum: any) => {\n\t\t\t\tkeysToCheck.forEach((key: any) => {\n\t\t\t\t\tif (getProperty(datum, key, 'getTime') === null) {\n\t\t\t\t\t\tdatum[key] = new Date(datum[key])\n\t\t\t\t\t}\n\t\t\t\t})\n\t\t\t})\n\t\t}\n\n\t\treturn data\n\t}\n\n\tprotected sanitize(data: any) {\n\t\tdata = super.sanitize(data)\n\t\tdata = this.sanitizeDateValues(data)\n\n\t\treturn data\n\t}\n}\n","// Internal Imports\nimport { ChartModelCartesian } from './cartesian-charts'\nimport { getProperty } from '@/tools'\n/**\n * Alluvial chart model layer\n */\nexport class AlluvialChartModel extends ChartModelCartesian {\n\tconstructor(services: any) {\n\t\tsuper(services)\n\t}\n\n\tgetTabularDataArray() {\n\t\tconst displayData = this.getDisplayData()\n\t\tconst { number: numberFormatter, code: localeCode } = getProperty(this.getOptions(), 'locale')\n\n\t\t// Sort array by source to get a close depiction of the alluvial chart\n\t\tdisplayData.sort((a: any, b: any) => a['source'].localeCompare(b['source']))\n\t\tconst headers = ['Source', 'Target', 'Value']\n\t\tconst cells = [\n\t\t\t...displayData.map((datum: any) => [\n\t\t\t\tdatum['source'],\n\t\t\t\tdatum['target'],\n\t\t\t\tdatum['value'] === null ? '–' : numberFormatter(datum['value'], localeCode)\n\t\t\t])\n\t\t]\n\n\t\treturn super.formatTable({ headers, cells })\n\t}\n}\n","import { ascending, min, max, quantile, scaleOrdinal } from 'd3'\nimport { getProperty } from '@/tools'\nimport { color as colorConfigs } from '@/configuration'\nimport { ChartModelCartesian } from './cartesian-charts'\n\n/** The charting model layer which includes mainly the chart data and options,\n * as well as some misc. information to be shared among components */\nexport class BoxplotChartModel extends ChartModelCartesian {\n\tconstructor(services: any) {\n\t\tsuper(services)\n\t}\n\n\tgetBoxQuartiles(d: any) {\n\t\treturn {\n\t\t\tq_25: quantile(d, 0.25),\n\t\t\tq_50: quantile(d, 0.5),\n\t\t\tq_75: quantile(d, 0.75)\n\t\t}\n\t}\n\n\tgetBoxplotData() {\n\t\tconst options = this.getOptions()\n\t\tconst { groupMapsTo } = options.data\n\n\t\tconst groupedData = this.getGroupedData()\n\n\t\t// Prepare the data for the box plots\n\t\tconst boxplotData = []\n\t\tfor (const { name: group, data } of groupedData) {\n\t\t\tconst rangeIdentifier = this.services.cartesianScales.getRangeIdentifier()\n\t\t\tconst values = data.map((d: any) => d[rangeIdentifier]).sort(ascending)\n\n\t\t\tconst record = {\n\t\t\t\t[groupMapsTo]: group,\n\t\t\t\tcounts: values,\n\t\t\t\tquartiles: this.getBoxQuartiles(values),\n\t\t\t\toutliers: null as any,\n\t\t\t\twhiskers: null as any\n\t\t\t}\n\n\t\t\tconst q1 = record.quartiles.q_25\n\t\t\tconst q3 = record.quartiles.q_75\n\n\t\t\tconst iqr = (q3 - q1) * 1.5\n\t\t\tconst irq1 = q1 - iqr\n\t\t\tconst irq3 = q3 + iqr\n\n\t\t\tconst outliers = []\n\t\t\tconst normalValues = []\n\n\t\t\tfor (const value of values) {\n\t\t\t\tif (value < irq1) {\n\t\t\t\t\toutliers.push(value)\n\t\t\t\t} else if (value > irq3) {\n\t\t\t\t\toutliers.push(value)\n\t\t\t\t} else {\n\t\t\t\t\tnormalValues.push(value)\n\t\t\t\t}\n\t\t\t}\n\n\t\t\trecord.outliers = outliers\n\n\t\t\tconst minNormalValue = min(normalValues)\n\t\t\tconst maxNormalValue = max(normalValues)\n\t\t\trecord.whiskers = {\n\t\t\t\tmin: minNormalValue\n\t\t\t\t\t? minNormalValue\n\t\t\t\t\t: min([record.quartiles.q_25, record.quartiles.q_50, record.quartiles.q_75]),\n\t\t\t\tmax: maxNormalValue\n\t\t\t\t\t? maxNormalValue\n\t\t\t\t\t: max([record.quartiles.q_25, record.quartiles.q_50, record.quartiles.q_75])\n\t\t\t}\n\n\t\t\tboxplotData.push(record)\n\t\t}\n\n\t\treturn boxplotData\n\t}\n\n\tgetTabularDataArray() {\n\t\tconst options = this.getOptions()\n\t\tconst { groupMapsTo } = options.data\n\t\tconst boxplotData = this.getBoxplotData()\n\t\tconst { number: numberFormatter, code: localeCode } = getProperty(options, 'locale')\n\n\t\tconst headers = ['Group', 'Minimum', 'Q1', 'Median', 'Q3', 'Maximum', 'IQR', 'Outlier(s)']\n\t\tconst cells = [\n\t\t\t...boxplotData.map(datum => {\n\t\t\t\tlet outliers = getProperty(datum, 'outliers')\n\t\t\t\tif (outliers === null || outliers.length === 0) {\n\t\t\t\t\toutliers = ['–']\n\t\t\t\t}\n\t\t\t\treturn [\n\t\t\t\t\tdatum[groupMapsTo],\n\t\t\t\t\tgetProperty(datum, 'whiskers', 'min') !== null\n\t\t\t\t\t\t? numberFormatter(getProperty(datum, 'whiskers', 'min'), localeCode)\n\t\t\t\t\t\t: '–',\n\t\t\t\t\tgetProperty(datum, 'quartiles', 'q_25') !== null\n\t\t\t\t\t\t? numberFormatter(getProperty(datum, 'quartiles', 'q_25'), localeCode)\n\t\t\t\t\t\t: '–',\n\t\t\t\t\tgetProperty(datum, 'quartiles', 'q_50') !== null\n\t\t\t\t\t\t? numberFormatter(getProperty(datum, 'quartiles', 'q_50'), localeCode)\n\t\t\t\t\t\t: '–',\n\t\t\t\t\tgetProperty(datum, 'quartiles', 'q_75') !== null\n\t\t\t\t\t\t? numberFormatter(getProperty(datum, 'quartiles', 'q_75'), localeCode)\n\t\t\t\t\t\t: '–',\n\t\t\t\t\tgetProperty(datum, 'whiskers', 'max') !== null\n\t\t\t\t\t\t? numberFormatter(getProperty(datum, 'whiskers', 'max'), localeCode)\n\t\t\t\t\t\t: '–',\n\t\t\t\t\tgetProperty(datum, 'quartiles', 'q_75') !== null &&\n\t\t\t\t\tgetProperty(datum, 'quartiles', 'q_25') !== null\n\t\t\t\t\t\t? (numberFormatter(\n\t\t\t\t\t\t\t\tgetProperty(datum, 'quartiles', 'q_75') - getProperty(datum, 'quartiles', 'q_25')\n\t\t\t\t\t\t\t),\n\t\t\t\t\t\t\tlocaleCode)\n\t\t\t\t\t\t: '–',\n\t\t\t\t\toutliers.map((d: any) => numberFormatter(d, localeCode)).join(',')\n\t\t\t\t]\n\t\t\t})\n\t\t]\n\n\t\treturn super.formatTable({ headers, cells })\n\t}\n\n\tprotected setColorClassNames() {\n\t\t// monochrome\n\t\tconst numberOfColors = 1\n\n\t\tconst colorPairingOptions = getProperty(this.getOptions(), 'color', 'pairing')\n\t\tlet pairingOption = getProperty(colorPairingOptions, 'option')\n\t\tconst colorPairingCounts = colorConfigs.pairingOptions\n\n\t\t// Use default palette if user choice is not in range\n\t\tpairingOption =\n\t\t\tpairingOption <= colorPairingCounts[`${numberOfColors}-color`] ? pairingOption : 1\n\n\t\t// Create color classes for graph, tooltip and stroke use\n\t\tconst colorPairing = this.allDataGroups.map(() => `${numberOfColors}-${pairingOption}-1`)\n\n\t\t// Create default color classnames\n\t\tthis.colorClassNames = scaleOrdinal().range(colorPairing).domain(this.allDataGroups)\n\t}\n}\n","import { getProperty } from '@/tools'\nimport { ChartModelCartesian } from './cartesian-charts'\n\n/**\n * Bullet chart model layer\n */\nexport class BulletChartModel extends ChartModelCartesian {\n\tconstructor(services: any) {\n\t\tsuper(services)\n\t}\n\n\t/**\n\t * Determines the index of the performance area titles to use\n\t * @param datum\n\t * @returns number\n\t */\n\tgetMatchingRangeIndexForDatapoint(datum: any) {\n\t\tlet matchingRangeIndex\n\t\tfor (let i = datum.ranges.length - 1; i > 0; i--) {\n\t\t\tconst range = datum.ranges[i]\n\t\t\tif (datum.value >= range) {\n\t\t\t\tmatchingRangeIndex = i\n\n\t\t\t\treturn matchingRangeIndex\n\t\t\t}\n\t\t}\n\n\t\treturn 0\n\t}\n\n\tgetTabularDataArray() {\n\t\tconst displayData = this.getDisplayData()\n\t\tconst options = this.getOptions()\n\t\tconst { groupMapsTo } = options.data\n\t\tconst rangeIdentifier = this.services.cartesianScales.getRangeIdentifier()\n\t\tconst { number: numberFormatter, code: localeCode } = getProperty(options, 'locale')\n\n\t\tconst performanceAreaTitles = getProperty(options, 'bullet', 'performanceAreaTitles')\n\t\tconst headers = ['Title', 'Group', 'Value', 'Target', 'Percentage', 'Performance']\n\t\tconst cells = [\n\t\t\t...displayData.map((datum: any) => [\n\t\t\t\tdatum['title'],\n\t\t\t\tdatum[groupMapsTo],\n\t\t\t\tdatum['value'] === null ? '–' : numberFormatter(datum['value'], localeCode),\n\t\t\t\tgetProperty(datum, 'marker') === null\n\t\t\t\t\t? '–'\n\t\t\t\t\t: numberFormatter(datum['marker'], localeCode),\n\t\t\t\tgetProperty(datum, 'marker') === null\n\t\t\t\t\t? '–'\n\t\t\t\t\t: `${numberFormatter(Math.floor((datum[rangeIdentifier] / datum.marker) * 100), localeCode)}%`,\n\t\t\t\tperformanceAreaTitles[this.getMatchingRangeIndexForDatapoint(datum)]\n\t\t\t])\n\t\t]\n\n\t\treturn super.formatTable({ headers, cells })\n\t}\n}\n","// External Imports\nimport { isEmpty } from 'lodash-es'\n\n// Internal Imports\nimport { ChartModel } from './model'\nimport { getProperty } from '@/tools'\nimport { getColorScale } from '@/services/color-scale-utils'\n\n/**\n * Base thematic maps chart model layer\n */\nexport class ChoroplethModel extends ChartModel {\n\tprivate _colorScale: any = undefined\n\n\t// Holds a mapping of geometry objects to data objects\n\t// Allows us to access data faster\n\tprivate _matrix = {}\n\n\tconstructor(services: any) {\n\t\tsuper(services)\n\t}\n\n\t/**\n\t * @override\n\t * @param value\n\t * @returns string\n\t */\n\tgetFillColor(value: number) {\n\t\treturn this._colorScale(value)\n\t}\n\n\t/**\n\t * Helper function that will generate a dictionary\n\t */\n\tgetCombinedData() {\n\t\tif (isEmpty(this._matrix)) {\n\t\t\tconst options = this.getOptions()\n\t\t\tconst data = this.getDisplayData()\n\t\t\tif (!isEmpty(data) && !isEmpty(options.geoData.objects.countries)) {\n\t\t\t\t/**\n\t\t\t\t * @todo\n\t\t\t\t * We can either use name or id by default to generate this dictionary\n\t\t\t\t * Curently id & name are standard in geoJSON. Unfortunately, topojson does not have any standard\n\t\t\t\t * so feature objects can have any key. We suggest that they include name or id at the very least\n\t\t\t\t *\n\t\t\t\t * May need to provide users with the option to pass in keys to create dictionary with\n\t\t\t\t */\n\t\t\t\toptions.geoData.objects.countries.geometries.forEach(country => {\n\t\t\t\t\tthis._matrix[country.properties.NAME] = country\n\t\t\t\t})\n\n\t\t\t\tdata.forEach(value => {\n\t\t\t\t\tif (this._matrix[value.name]) {\n\t\t\t\t\t\tthis._matrix[value.name]['value'] = value.value || null\n\t\t\t\t\t} else {\n\t\t\t\t\t\tconsole.warn(`Data point ${value} is missing geographical data.`)\n\t\t\t\t\t}\n\t\t\t\t})\n\t\t\t}\n\t\t}\n\n\t\treturn this._matrix\n\t}\n\n\t/**\n\t * Generate tabular data from display data\n\t * @returns Array
