{"version":3,"file":"histogram.cjs","sources":["../../../../src/transformations/transformers/histogram.ts"],"sourcesContent":["import { map } from 'rxjs/operators';\n\nimport { outerJoinDataFrames } from '../..';\nimport { getDisplayProcessor } from '../../field/displayProcessor';\nimport { createTheme } from '../../themes/createTheme';\nimport { GrafanaTheme2 } from '../../themes/types';\nimport { DataFrame, Field, FieldConfig, FieldType } from '../../types/dataFrame';\nimport { DataFrameType } from '../../types/dataFrameTypes';\nimport { DataTransformContext, SynchronousDataTransformerInfo } from '../../types/transformations';\nimport { roundDecimals } from '../../utils/numbers';\n\nimport { DataTransformerID } from './ids';\nimport { AlignedData, join } from './joinDataFrames';\nimport { nullToValueField } from './nulls/nullToValue';\n\n/**\n * @internal\n */\n/* eslint-disable */\n// prettier-ignore\nexport const histogramBucketSizes = [\n 1e-9, 2e-9, 2.5e-9, 4e-9, 5e-9,\n 1e-8, 2e-8, 2.5e-8, 4e-8, 5e-8,\n 1e-7, 2e-7, 2.5e-7, 4e-7, 5e-7,\n 1e-6, 2e-6, 2.5e-6, 4e-6, 5e-6,\n 1e-5, 2e-5, 2.5e-5, 4e-5, 5e-5,\n 1e-4, 2e-4, 2.5e-4, 4e-4, 5e-4,\n 1e-3, 2e-3, 2.5e-3, 4e-3, 5e-3,\n 1e-2, 2e-2, 2.5e-2, 4e-2, 5e-2,\n 1e-1, 2e-1, 2.5e-1, 4e-1, 5e-1,\n 1, 2, 4, 5,\n 1e+1, 2e+1, 2.5e+1, 4e+1, 5e+1,\n 1e+2, 2e+2, 2.5e+2, 4e+2, 5e+2,\n 1e+3, 2e+3, 2.5e+3, 4e+3, 5e+3,\n 1e+4, 2e+4, 2.5e+4, 4e+4, 5e+4,\n 1e+5, 2e+5, 2.5e+5, 4e+5, 5e+5,\n 1e+6, 2e+6, 2.5e+6, 4e+6, 5e+6,\n 1e+7, 2e+7, 2.5e+7, 4e+7, 5e+7,\n 1e+8, 2e+8, 2.5e+8, 4e+8, 5e+8,\n 1e+9, 2e+9, 2.5e+9, 4e+9, 5e+9,\n];\n/* eslint-enable */\n\nconst DEFAULT_BUCKET_COUNT = 30;\n\nconst histFilter: number[] = [];\nconst histSort = (a: number, b: number) => a - b;\n\nexport interface HistogramTransformerInputs {\n bucketCount?: number;\n bucketSize?: string | number;\n bucketOffset?: string | number;\n combine?: boolean;\n}\n\n/**\n * @alpha\n */\nexport interface HistogramTransformerOptions {\n bucketCount?: number;\n bucketSize?: number; // 0 is auto\n bucketOffset?: number;\n // xMin?: number;\n // xMax?: number;\n combine?: boolean; // if multiple series are input, join them into one\n}\n\n/**\n * This is a helper class to use the same text in both a panel and transformer UI\n *\n * @internal\n */\nexport const histogramFieldInfo = {\n bucketCount: {\n name: 'Bucket count',\n description: 'approx bucket count',\n },\n bucketSize: {\n name: 'Bucket size',\n description: undefined,\n },\n bucketOffset: {\n name: 'Bucket offset',\n description: 'for non-zero-based buckets',\n },\n combine: {\n name: 'Combine series',\n description: 'combine all series into a single histogram',\n },\n};\n\n/**\n * @alpha\n */\nexport const histogramTransformer: SynchronousDataTransformerInfo = {\n id: DataTransformerID.histogram,\n name: 'Histogram',\n description: 'Calculate a histogram from input data.',\n defaultOptions: {\n fields: {},\n },\n\n operator: (options, ctx) => (source) =>\n source.pipe(map((data) => histogramTransformer.transformer(options, ctx)(data))),\n\n transformer: (options: HistogramTransformerInputs, ctx: DataTransformContext) => (data: DataFrame[]) => {\n if (!Array.isArray(data) || data.length === 0) {\n return data;\n }\n\n let bucketSize,\n bucketOffset: number | undefined = undefined;\n\n if (options.bucketSize) {\n if (typeof options.bucketSize === 'string') {\n bucketSize = parseFloat(options.bucketSize);\n } else {\n bucketSize = options.bucketSize;\n }\n\n if (isNaN(bucketSize)) {\n bucketSize = undefined;\n }\n }\n\n if (options.bucketOffset) {\n if (typeof options.bucketOffset === 'string') {\n bucketOffset = parseFloat(options.bucketOffset);\n } else {\n bucketOffset = options.bucketOffset;\n }\n\n if (isNaN(bucketOffset)) {\n bucketOffset = undefined;\n }\n }\n\n const interpolatedOptions: HistogramTransformerOptions = {\n bucketSize: bucketSize,\n bucketOffset: bucketOffset,\n combine: options.combine,\n };\n\n const hist = buildHistogram(data, interpolatedOptions);\n if (hist == null) {\n return [];\n }\n return [histogramFieldsToFrame(hist)];\n },\n};\n\n/**\n * @internal\n */\nexport const histogramFrameBucketMinFieldName = 'xMin';\n\n/**\n * @internal\n */\nexport function isHistogramFrameBucketMinFieldName(v: string) {\n return v === histogramFrameBucketMinFieldName || v === 'BucketMin'; // REMOVE 'BuckentMin/Max'\n}\n\n/**\n * @internal\n */\nexport const histogramFrameBucketMaxFieldName = 'xMax';\n\n/**\n * @internal\n */\nexport function isHistogramFrameBucketMaxFieldName(v: string) {\n return v === histogramFrameBucketMaxFieldName || v === 'BucketMax'; // REMOVE 'BuckentMin/Max'\n}\n\n/**\n * @alpha\n */\nexport interface HistogramFields {\n xMin: Field;\n xMax: Field;\n counts: Field[]; // frequency\n}\n\n/**\n * Given a frame, find the explicit histogram fields\n *\n * @alpha\n */\nexport function getHistogramFields(frame: DataFrame): HistogramFields | undefined {\n // we ignore xMax (time field) and sum all counts together for each found bucket\n if (frame.meta?.type === DataFrameType.HeatmapCells) {\n // we assume uniform bucket size for now\n // we assume xMax, yMin, yMax fields\n let yMinField = frame.fields.find((f) => f.name === 'yMin')!;\n let yMaxField = frame.fields.find((f) => f.name === 'yMax')!;\n let countField = frame.fields.find((f) => f.name === 'count')!;\n\n let uniqueMaxs = [...new Set(yMaxField.values)].sort((a, b) => a - b);\n let uniqueMins = [...new Set(yMinField.values)].sort((a, b) => a - b);\n\n // useLogScale is assumed for native histograms, we get the multiplier from first bucket's min/max bounds\n let bucketFactor = uniqueMaxs[0] / uniqueMins[0];\n\n // NOTES:\n // native histograms default bucket growth factor is 8th root of 2 (schema 3) -> (2 ** (2 ** -3)) = 1.0905077326652577\n // the by-division inference from data results in 1.090507732665258\n\n // densify the buckets using 0 counts (consumers of this fn assume a dense structure)\n let denseMins: number[] = [];\n let denseMaxs: number[] = [];\n\n const MAX_DENSIFIED_BUCKETS = 1000;\n\n for (let i = 0; i < uniqueMaxs.length; i++) {\n let curMax = uniqueMaxs[i];\n let curMin = uniqueMins[i];\n\n denseMaxs.push(curMax);\n denseMins.push(curMin);\n\n let nextMax = uniqueMaxs[i + 1];\n\n if (nextMax != null) {\n curMax = curMax * bucketFactor;\n curMin = curMin * bucketFactor;\n\n while (curMax < nextMax * 0.999999 && denseMaxs.length < MAX_DENSIFIED_BUCKETS) {\n denseMaxs.push(curMax);\n denseMins.push(curMin);\n\n curMax = curMax * bucketFactor;\n curMin = curMin * bucketFactor;\n }\n\n if (denseMaxs.length >= MAX_DENSIFIED_BUCKETS) {\n break;\n }\n }\n }\n\n let countsByMax = new Map();\n denseMaxs.forEach((max) => countsByMax.set(max, 0));\n\n for (let i = 0; i < yMaxField.values.length; i++) {\n let max = yMaxField.values[i];\n let currentCount = countsByMax.get(max);\n if (currentCount !== undefined) {\n countsByMax.set(max, currentCount + countField.values[i]);\n }\n }\n\n let fields = {\n xMin: {\n ...yMinField,\n name: 'xMin',\n values: denseMins,\n },\n xMax: {\n ...yMaxField,\n name: 'xMax',\n values: denseMaxs,\n },\n counts: [\n {\n ...countField,\n values: [...countsByMax.values()],\n },\n ],\n };\n\n return fields;\n } else if (frame.meta?.type === DataFrameType.HeatmapRows) {\n // assumes le\n\n // tick label strings (will be ordinal-ized)\n let minVals: string[] = [];\n let maxVals: string[] = [];\n\n // sums of all timstamps per bucket\n let countVals: number[] = [];\n\n let minVal = '0';\n frame.fields.forEach((f) => {\n if (f.type === FieldType.number) {\n let countsSum = f.values.reduce((acc, v) => acc + v, 0);\n countVals.push(countsSum);\n minVals.push(minVal);\n maxVals.push((minVal = f.name));\n }\n });\n\n // fake extra value for +Inf (for x scale ranging since bars are right-aligned)\n countVals.push(0);\n minVals.push(minVal);\n maxVals.push(minVal);\n\n let fields = {\n xMin: {\n ...frame.fields[1],\n name: 'xMin',\n type: FieldType.string,\n values: minVals,\n },\n xMax: {\n ...frame.fields[1],\n name: 'xMax',\n type: FieldType.string,\n values: maxVals,\n },\n counts: [\n {\n ...frame.fields[1],\n name: 'count',\n type: FieldType.number,\n values: countVals,\n },\n ],\n };\n\n return fields;\n }\n\n let xMin: Field | undefined = undefined;\n let xMax: Field | undefined = undefined;\n const counts: Field[] = [];\n for (const field of frame.fields) {\n if (isHistogramFrameBucketMinFieldName(field.name)) {\n xMin = field;\n } else if (isHistogramFrameBucketMaxFieldName(field.name)) {\n xMax = field;\n } else if (field.type === FieldType.number) {\n counts.push(field);\n }\n }\n\n // guess bucket size from single explicit bucket field\n if (!xMax && xMin && xMin.values.length > 1) {\n let vals = xMin.values;\n let bucketSize = roundDecimals(vals[1] - vals[0], 6);\n\n xMax = {\n ...xMin,\n name: histogramFrameBucketMaxFieldName,\n values: vals.map((v) => v + bucketSize),\n };\n }\n\n if (!xMin && xMax && xMax?.values.length > 1) {\n let vals = xMax.values;\n let bucketSize = roundDecimals(vals[1] - vals[0], 6);\n\n xMin = {\n ...xMax,\n name: histogramFrameBucketMinFieldName,\n values: vals.map((v) => v - bucketSize),\n };\n }\n\n if (xMin && xMax && counts.length) {\n return {\n xMin,\n xMax,\n counts,\n };\n }\n return undefined;\n}\n\n/**\n * @alpha\n */\nexport function buildHistogram(\n frames: DataFrame[],\n options?: HistogramTransformerOptions,\n theme?: GrafanaTheme2\n): HistogramFields | null {\n let bucketSize = options?.bucketSize;\n let bucketCount = options?.bucketCount ?? DEFAULT_BUCKET_COUNT;\n let bucketOffset = options?.bucketOffset ?? 0;\n\n // replace or filter nulls from numeric fields\n frames = frames.map((frame) => {\n return {\n ...frame,\n fields: frame.fields.map((field) => {\n if (field.type === FieldType.number) {\n const noValue = Number(field.config.noValue);\n\n if (!Number.isNaN(noValue)) {\n field = nullToValueField(field, noValue);\n } else {\n field = { ...field, values: field.values.filter((v) => v != null) };\n }\n }\n\n return field;\n }),\n };\n });\n\n // if bucket size is auto, try to calc from all numeric fields\n if (!bucketSize || bucketSize < 0) {\n let allValues: number[] = [];\n\n // TODO: include field configs!\n for (const frame of frames) {\n for (const field of frame.fields) {\n if (field.type === FieldType.number) {\n allValues = allValues.concat(field.values);\n }\n }\n }\n\n allValues.sort((a, b) => a - b);\n\n let smallestDelta = Infinity;\n\n // TODO: case of 1 value needs work\n if (allValues.length === 1) {\n smallestDelta = 1;\n } else {\n for (let i = 1; i < allValues.length; i++) {\n let delta = allValues[i] - allValues[i - 1];\n\n if (delta !== 0) {\n smallestDelta = Math.min(smallestDelta, delta);\n }\n }\n }\n\n let min = allValues[0];\n let max = allValues[allValues.length - 1];\n\n let range = max - min;\n\n const targetSize = range / bucketCount;\n\n // choose bucket\n for (let i = 0; i < histogramBucketSizes.length; i++) {\n let _bucketSize = histogramBucketSizes[i];\n\n if (targetSize < _bucketSize && _bucketSize >= smallestDelta) {\n bucketSize = _bucketSize;\n break;\n }\n }\n }\n\n const getBucket = (v: number) => roundDecimals(incrRoundDn(v - bucketOffset, bucketSize!) + bucketOffset, 9);\n\n // guess number of decimals\n let bucketDecimals = (('' + bucketSize).match(/\\.\\d+$/) ?? ['.'])[0].length - 1;\n\n let histograms: AlignedData[] = [];\n let counts: Field[] = [];\n let config: FieldConfig | undefined = undefined;\n\n for (const frame of frames) {\n for (const field of frame.fields) {\n if (field.type === FieldType.number) {\n let fieldHist = histogram(field.values, getBucket, histFilter, histSort);\n histograms.push(fieldHist);\n\n const count = {\n ...field,\n config: {\n ...field.config,\n unit: field.config.unit === 'short' ? 'short' : undefined,\n },\n };\n\n count.display = getDisplayProcessor({\n field: count,\n theme: theme ?? createTheme(),\n });\n counts.push(count);\n if (!config && field.config.unit) {\n config = field.config;\n }\n }\n }\n }\n\n // Quit early for empty a\n if (!counts.length) {\n return null;\n }\n\n // align histograms\n let joinedHists = join(histograms);\n\n // zero-fill all undefined values (missing buckets -> 0 counts)\n for (let histIdx = 1; histIdx < joinedHists.length; histIdx++) {\n let hist = joinedHists[histIdx];\n\n for (let bucketIdx = 0; bucketIdx < hist.length; bucketIdx++) {\n if (hist[bucketIdx] == null) {\n hist[bucketIdx] = 0;\n }\n }\n }\n\n const xMin: Field = {\n name: histogramFrameBucketMinFieldName,\n values: joinedHists[0],\n type: FieldType.number,\n state: undefined,\n config:\n bucketDecimals === 0\n ? (config ?? {})\n : {\n ...config,\n decimals: bucketDecimals,\n },\n };\n const xMax = {\n ...xMin,\n name: histogramFrameBucketMaxFieldName,\n values: joinedHists[0].map((v) => v + bucketSize!),\n };\n\n if (options?.combine) {\n const vals = new Array(joinedHists[0].length).fill(0);\n for (let i = 1; i < joinedHists.length; i++) {\n for (let j = 0; j < vals.length; j++) {\n vals[j] += joinedHists[i][j];\n }\n }\n counts = [\n {\n ...counts[0],\n name: 'count',\n values: vals,\n type: FieldType.number,\n state: {\n ...counts[0].state,\n displayName: 'Count',\n multipleFrames: false,\n origin: { frameIndex: 0, fieldIndex: 2 },\n },\n },\n ];\n } else {\n counts.forEach((field, i) => {\n field.values = joinedHists[i + 1];\n });\n }\n\n return {\n xMin,\n xMax,\n counts,\n };\n}\n\n/**\n * @internal\n */\nexport function incrRound(num: number, incr: number) {\n return Math.round(num / incr) * incr;\n}\n\n/**\n * @internal\n */\nexport function incrRoundUp(num: number, incr: number) {\n return Math.ceil(num / incr) * incr;\n}\n\n/**\n * @internal\n */\nexport function incrRoundDn(num: number, incr: number) {\n return Math.floor(num / incr) * incr;\n}\n\nfunction histogram(\n vals: number[],\n getBucket: (v: number) => number,\n filterOut?: number[],\n sort?: ((a: number, b: number) => number) | null\n): AlignedData {\n let hist = new Map();\n\n for (let i = 0; i < vals.length; i++) {\n let v = vals[i];\n\n if (v != null) {\n v = getBucket(v);\n }\n\n let entry = hist.get(v);\n\n if (entry) {\n entry.count++;\n } else {\n hist.set(v, { value: v, count: 1 });\n }\n }\n\n filterOut && filterOut.forEach((v) => hist.delete(v));\n\n let bins = [...hist.values()];\n\n sort && bins.sort((a, b) => sort(a.value, b.value));\n\n let values = Array(bins.length);\n let counts = Array(bins.length);\n\n for (let i = 0; i < bins.length; i++) {\n values[i] = bins[i].value;\n counts[i] = bins[i].count;\n }\n\n return [values, counts];\n}\n\n/**\n * @internal\n */\nexport function histogramFieldsToFrame(info: HistogramFields, theme?: GrafanaTheme2): DataFrame {\n if (!info.xMin.display) {\n const display = getDisplayProcessor({\n field: info.xMin,\n theme: theme ?? createTheme(),\n });\n info.xMin.display = display;\n info.xMax.display = display;\n }\n\n return {\n length: info.xMin.values.length,\n meta: {\n type: DataFrameType.Histogram,\n },\n fields: [info.xMin, info.xMax, ...info.counts],\n refId: `${DataTransformerID.histogram}`,\n };\n}\n\n/**\n *\n * Join multiple histograms into a histogram with multiple counts.\n * Useful eg if you want to overlay them for comparison.\n *\n * This is needed because histogram results from database\n * will have buckets omitted for 0 counts, but when joining multiple histograms\n * we need to fill in the 0 values for missing buckets.\n *\n * Returns field configs of the first provided histogram.\n * @alpha\n */\n\nexport function joinHistograms(histograms: HistogramFields[]): HistogramFields {\n if (histograms.length === 1) {\n return histograms[0];\n }\n\n let joined = outerJoinDataFrames({\n frames: histograms.map((h) => ({\n length: h.xMax.values.length,\n fields: [h.xMax, h.xMin, ...h.counts],\n })),\n joinBy: (field) => field.name === 'xMax',\n })!;\n\n let xMaxField: Field | null = null;\n let xMinField: Field | null = null;\n let countFields: Field[] = [];\n\n // merge all xMin fields into first xMin field\n // and default all count fields to 0\n joined.fields.forEach((f) => {\n if (f.name === 'xMax') {\n xMaxField = f;\n } else if (f.name === 'xMin') {\n if (xMinField == null) {\n xMinField = f;\n } else {\n for (let i = 0; i < f.values.length; i++) {\n xMinField.values[i] ??= f.values[i];\n }\n }\n } else {\n countFields.push({\n ...f,\n values: f.values.map((v) => v ?? 0),\n });\n }\n });\n\n const result: HistogramFields = {\n xMin: xMinField!,\n xMax: xMaxField!,\n counts: countFields,\n };\n\n return 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