ck-ops/code/grafana/public/build/heatmapPlugin.023404025d5e6228a049.js.map

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{ auto } from 'angular';\nimport { indexOf } from 'lodash';\n\nexport class QueryCtrl<T = any> {\n  target!: T;\n  datasource!: any;\n  panelCtrl!: any;\n  panel: any;\n  hasRawMode!: boolean;\n  error?: string | null;\n  isLastQuery: boolean;\n\n  constructor(public $scope: any, public $injector: auto.IInjectorService) {\n    this.panelCtrl = this.panelCtrl ?? $scope.ctrl.panelCtrl;\n    this.target = this.target ?? $scope.ctrl.target;\n    this.datasource = this.datasource ?? $scope.ctrl.datasource;\n    this.panel = this.panelCtrl?.panel ?? $scope.ctrl.panelCtrl.panel;\n    this.isLastQuery = indexOf(this.panel.targets, this.target) === this.panel.targets.length - 1;\n  }\n\n  refresh() {\n    this.panelCtrl.refresh();\n  }\n}\n","import * as d3 from 'd3';\nimport * as d3ScaleChromatic from 'd3-scale-chromatic';\n\nexport function getColorScale(colorScheme: any, lightTheme: boolean, maxValue: number, minValue = 0): (d: any) => any {\n  //@ts-ignore\n  const colorInterpolator = d3ScaleChromatic[colorScheme.value];\n  const colorScaleInverted = colorScheme.invert === 'always' || colorScheme.invert === (lightTheme ? 'light' : 'dark');\n\n  const start = colorScaleInverted ? maxValue : minValue;\n  const end = colorScaleInverted ? minValue : maxValue;\n\n  return d3.scaleSequential(colorInterpolator).domain([start, end]);\n}\n\nexport function getOpacityScale(\n  options: { cardColor?: null; colorScale?: any; exponent?: any },\n  maxValue: number,\n  minValue = 0\n): any {\n  let legendOpacityScale;\n  if (options.colorScale === 'linear') {\n    legendOpacityScale = d3.scaleLinear().domain([minValue, maxValue]).range([0, 1]);\n  } else if (options.colorScale === 'sqrt') {\n    legendOpacityScale = d3.scalePow().exponent(options.exponent).domain([minValue, maxValue]).range([0, 1]);\n  }\n  return legendOpacityScale;\n}\n","import * as d3 from 'd3';\nimport $ from 'jquery';\nimport { find, isEmpty, isNil, sortBy, uniq } from 'lodash';\n\nimport { PanelEvents } from '@grafana/data';\nimport coreModule from 'app/angular/core_module';\nimport { config } from 'app/core/config';\nimport { contextSrv } from 'app/core/core';\nimport { tickStep } from 'app/core/utils/ticks';\n\nimport { getColorScale, getOpacityScale } from './color_scale';\n\nconst LEGEND_HEIGHT_PX = 6;\nconst LEGEND_WIDTH_PX = 100;\nconst LEGEND_TICK_SIZE = 0;\nconst LEGEND_VALUE_MARGIN = 0;\nconst LEGEND_PADDING_LEFT = 10;\nconst LEGEND_SEGMENT_WIDTH = 10;\n\n/**\n * Color legend for heatmap editor.\n */\ncoreModule.directive('colorLegend', () => {\n  return {\n    restrict: 'E',\n    template: '<div class=\"heatmap-color-legend\"><svg width=\"16.5rem\" height=\"24px\"></svg></div>',\n    link: (scope: any, elem, attrs) => {\n      const ctrl = scope.ctrl;\n      const panel = scope.ctrl.panel;\n\n      render();\n\n      ctrl.events.on(PanelEvents.render, () => {\n        render();\n      });\n\n      function render() {\n        const legendElem = $(elem).find('svg');\n        const legendWidth = Math.floor(legendElem.outerWidth() ?? 10);\n\n        if (panel.color.mode === 'spectrum') {\n          const colorScheme: any = find(ctrl.colorSchemes, {\n            value: panel.color.colorScheme,\n          });\n          const colorScale = getColorScale(colorScheme, contextSrv.user.lightTheme, legendWidth);\n          drawSimpleColorLegend(elem, colorScale);\n        } else if (panel.color.mode === 'opacity') {\n          const colorOptions = panel.color;\n          drawSimpleOpacityLegend(elem, colorOptions);\n        }\n      }\n    },\n  };\n});\n\n/**\n * Heatmap legend with scale values.\n */\ncoreModule.directive('heatmapLegend', () => {\n  return {\n    restrict: 'E',\n    template: `<div class=\"heatmap-color-legend\"><svg width=\"${LEGEND_WIDTH_PX}px\" height=\"${LEGEND_HEIGHT_PX}px\"></svg></div>`,\n    link: (scope: any, elem, attrs) => {\n      const ctrl = scope.ctrl;\n      const panel = scope.ctrl.panel;\n\n      render();\n      ctrl.events.on(PanelEvents.render, () => {\n        render();\n      });\n\n      function render() {\n        clearLegend(elem);\n        if (!isEmpty(ctrl.data) && !isEmpty(ctrl.data.cards)) {\n          const cardStats = ctrl.data.cardStats;\n          const rangeFrom = isNil(panel.color.min) ? Math.max(cardStats.min, 0) : panel.color.min;\n          const rangeTo = isNil(panel.color.max) ? cardStats.max : panel.color.max;\n          const maxValue = cardStats.max;\n          const minValue = cardStats.min;\n\n          if (panel.color.mode === 'spectrum') {\n            const colorScheme: any = find(ctrl.colorSchemes, {\n              value: panel.color.colorScheme,\n            });\n            drawColorLegend(elem, colorScheme, rangeFrom, rangeTo, maxValue, minValue);\n          } else if (panel.color.mode === 'opacity') {\n            const colorOptions = panel.color;\n            drawOpacityLegend(elem, colorOptions, rangeFrom, rangeTo, maxValue, minValue);\n          }\n        }\n      }\n    },\n  };\n});\n\nfunction drawColorLegend(\n  elem: JQuery,\n  colorScheme: any,\n  rangeFrom: number,\n  rangeTo: number,\n  maxValue: number,\n  minValue: number\n) {\n  const legendElem = $(elem).find('svg');\n  const legendDomElement = legendElem.get(0);\n  if (legendDomElement) {\n    const legend = d3.select(legendDomElement);\n    clearLegend(elem);\n\n    const legendWidth = Math.floor(legendElem.outerWidth() ?? 10) - 30;\n    const legendHeight = legendElem.attr('height') as any;\n\n    const rangeStep = ((rangeTo - rangeFrom) / legendWidth) * LEGEND_SEGMENT_WIDTH;\n    const widthFactor = legendWidth / (rangeTo - rangeFrom);\n    const valuesRange = d3.range(rangeFrom, rangeTo, rangeStep);\n\n    const colorScale = getColorScale(colorScheme, contextSrv.user.lightTheme, rangeTo, rangeFrom);\n    legend\n      .append('g')\n      .attr('class', 'legend-color-bar')\n      .attr('transform', 'translate(' + LEGEND_PADDING_LEFT + ',0)')\n      .selectAll('.heatmap-color-legend-rect')\n      .data(valuesRange)\n      .enter()\n      .append('rect')\n      .attr('x', (d) => Math.round((d - rangeFrom) * widthFactor))\n      .attr('y', 0)\n      .attr('width', Math.round(rangeStep * widthFactor + 1)) // Overlap rectangles to prevent gaps\n      .attr('height', legendHeight)\n      .attr('stroke-width', 0)\n      .attr('fill', (d) => colorScale(d));\n\n    drawLegendValues(elem, rangeFrom, rangeTo, maxValue, minValue, legendWidth, valuesRange);\n  }\n}\n\nfunction drawOpacityLegend(\n  elem: JQuery,\n  options: { cardColor: null },\n  rangeFrom: number,\n  rangeTo: number,\n  maxValue: any,\n  minValue: number\n) {\n  const legendElem = $(elem).find('svg');\n  const legendDomElement = legendElem.get(0);\n  if (legendDomElement) {\n    const legend = d3.select(legendDomElement);\n    clearLegend(elem);\n\n    const legendWidth = Math.floor(legendElem.outerWidth() ?? 30) - 30;\n    const legendHeight = legendElem.attr('height') as any;\n\n    const rangeStep = ((rangeTo - rangeFrom) / legendWidth) * LEGEND_SEGMENT_WIDTH;\n    const widthFactor = legendWidth / (rangeTo - rangeFrom);\n    const valuesRange = d3.range(rangeFrom, rangeTo, rangeStep);\n\n    const opacityScale = getOpacityScale(options, rangeTo, rangeFrom);\n    legend\n      .append('g')\n      .attr('class', 'legend-color-bar')\n      .attr('transform', 'translate(' + LEGEND_PADDING_LEFT + ',0)')\n      .selectAll('.heatmap-opacity-legend-rect')\n      .data(valuesRange)\n      .enter()\n      .append('rect')\n      .attr('x', (d) => Math.round((d - rangeFrom) * widthFactor))\n      .attr('y', 0)\n      .attr('width', Math.round(rangeStep * widthFactor))\n      .attr('height', legendHeight)\n      .attr('stroke-width', 0)\n      .attr('fill', options.cardColor)\n      .style('opacity', (d) => opacityScale(d));\n\n    drawLegendValues(elem, rangeFrom, rangeTo, maxValue, minValue, legendWidth, valuesRange);\n  }\n}\n\nfunction drawLegendValues(\n  elem: JQuery,\n  rangeFrom: number,\n  rangeTo: number,\n  maxValue: any,\n  minValue: any,\n  legendWidth: number,\n  valuesRange: number[]\n) {\n  const legendElem = $(elem).find('svg');\n  const legendDomElement = legendElem.get(0);\n  if (legendDomElement) {\n    const legend = d3.select(legendDomElement);\n\n    if (legendWidth <= 0 || legendDomElement.childNodes.length === 0) {\n      return;\n    }\n\n    const legendValueScale = d3.scaleLinear().domain([rangeFrom, rangeTo]).range([0, legendWidth]);\n\n    const ticks = buildLegendTicks(rangeFrom, rangeTo, maxValue, minValue);\n    const xAxis = d3.axisBottom(legendValueScale).tickValues(ticks).tickSize(LEGEND_TICK_SIZE);\n\n    const colorRect = legendElem.find(':first-child');\n    const posY = getSvgElemHeight(legendElem) + LEGEND_VALUE_MARGIN;\n    const posX = getSvgElemX(colorRect) + LEGEND_PADDING_LEFT;\n\n    d3.select(legendDomElement)\n      .append('g')\n      .attr('class', 'axis')\n      .attr('transform', 'translate(' + posX + ',' + posY + ')')\n      .call(xAxis);\n\n    legend.select('.axis').select('.domain').remove();\n  }\n}\n\nfunction drawSimpleColorLegend(elem: JQuery, colorScale: any) {\n  const legendElem = $(elem).find('svg');\n  clearLegend(elem);\n\n  const legendWidth = Math.floor(legendElem.outerWidth() ?? 30);\n  const legendHeight = legendElem.attr('height') as any;\n\n  if (legendWidth) {\n    const valuesNumber = Math.floor(legendWidth / 2);\n    const rangeStep = Math.floor(legendWidth / valuesNumber);\n    const valuesRange = d3.range(0, legendWidth, rangeStep);\n\n    const legendDomElement = legendElem.get(0);\n    if (legendDomElement) {\n      const legend = d3.select(legendDomElement);\n      const legendRects = legend.selectAll('.heatmap-color-legend-rect').data(valuesRange);\n\n      legendRects\n        .enter()\n        .append('rect')\n        .attr('x', (d) => d)\n        .attr('y', 0)\n        .attr('width', rangeStep + 1) // Overlap rectangles to prevent gaps\n        .attr('height', legendHeight)\n        .attr('stroke-width', 0)\n        .attr('fill', (d) => colorScale(d));\n    }\n  }\n}\n\nfunction drawSimpleOpacityLegend(elem: JQuery, options: { colorScale: string; exponent: number; cardColor: string }) {\n  const legendElem = $(elem).find('svg');\n  const legendDomElement = legendElem.get(0);\n  if (legendDomElement) {\n    clearLegend(elem);\n\n    const legend = d3.select(legendDomElement);\n    const legendWidth = Math.floor(legendElem.outerWidth() ?? 30);\n    const legendHeight = legendElem.attr('height') as any;\n\n    if (legendWidth) {\n      let legendOpacityScale: any;\n      if (options.colorScale === 'linear') {\n        legendOpacityScale = d3.scaleLinear().domain([0, legendWidth]).range([0, 1]);\n      } else if (options.colorScale === 'sqrt') {\n        legendOpacityScale = d3.scalePow().exponent(options.exponent).domain([0, legendWidth]).range([0, 1]);\n      }\n\n      const rangeStep = 10;\n      const valuesRange = d3.range(0, legendWidth, rangeStep);\n      const legendRects = legend.selectAll('.heatmap-opacity-legend-rect').data(valuesRange);\n\n      legendRects\n        .enter()\n        .append('rect')\n        .attr('x', (d) => d)\n        .attr('y', 0)\n        .attr('width', rangeStep)\n        .attr('height', legendHeight)\n        .attr('stroke-width', 0)\n        .attr('fill', config.theme.visualization.getColorByName(options.cardColor))\n        .style('opacity', (d) => legendOpacityScale(d));\n    }\n  }\n}\n\nfunction clearLegend(elem: JQuery) {\n  const legendElem = $(elem).find('svg');\n  legendElem.empty();\n}\n\nfunction getSvgElemX(elem: JQuery) {\n  const svgElem: any = elem.get(0) as any;\n  if (svgElem && svgElem.x && svgElem.x.baseVal) {\n    return svgElem.x.baseVal.value;\n  } else {\n    return 0;\n  }\n}\n\nfunction getSvgElemHeight(elem: JQuery<any>) {\n  const svgElem: any = elem.get(0);\n  if (svgElem && svgElem.height && svgElem.height.baseVal) {\n    return svgElem.height.baseVal.value;\n  } else {\n    return 0;\n  }\n}\n\nfunction buildLegendTicks(rangeFrom: number, rangeTo: number, maxValue: number, minValue: number) {\n  const range = rangeTo - rangeFrom;\n  const tickStepSize = tickStep(rangeFrom, rangeTo, 3);\n  const ticksNum = Math.ceil(range / tickStepSize);\n  const firstTick = getFirstCloseTick(rangeFrom, tickStepSize);\n  let ticks = [];\n\n  for (let i = 0; i < ticksNum; i++) {\n    const current = firstTick + tickStepSize * i;\n    // Add user-defined min and max if it had been set\n    if (isValueCloseTo(minValue, current, tickStepSize)) {\n      ticks.push(minValue);\n      continue;\n    } else if (minValue < current) {\n      ticks.push(minValue);\n    }\n    if (isValueCloseTo(maxValue, current, tickStepSize)) {\n      ticks.push(maxValue);\n      continue;\n    } else if (maxValue < current) {\n      ticks.push(maxValue);\n    }\n    ticks.push(current);\n  }\n  if (!isValueCloseTo(maxValue, rangeTo, tickStepSize)) {\n    ticks.push(maxValue);\n  }\n  ticks.push(rangeTo);\n  ticks = sortBy(uniq(ticks));\n  return ticks;\n}\n\nfunction isValueCloseTo(val: number, valueTo: number, step: number) {\n  const diff = Math.abs(val - valueTo);\n  return diff < step * 0.3;\n}\n\nfunction getFirstCloseTick(minValue: number, step: number) {\n  if (minValue < 0) {\n    return Math.floor(minValue / step) * step;\n  }\n  return 0;\n}\n","export class AxesEditorCtrl {\n  panel: any;\n  panelCtrl: any;\n  logScales: any;\n  dataFormats: any;\n  yBucketBoundModes: any;\n\n  /** @ngInject */\n  constructor($scope: any, uiSegmentSrv: any) {\n    $scope.editor = this;\n    this.panelCtrl = $scope.ctrl;\n    this.panel = this.panelCtrl.panel;\n\n    this.logScales = {\n      linear: 1,\n      'log (base 2)': 2,\n      'log (base 10)': 10,\n      'log (base 32)': 32,\n      'log (base 1024)': 1024,\n    };\n\n    this.dataFormats = {\n      'Time series': 'timeseries',\n      'Time series buckets': 'tsbuckets',\n    };\n\n    this.yBucketBoundModes = {\n      Auto: 'auto',\n      Upper: 'upper',\n      Lower: 'lower',\n      Middle: 'middle',\n    };\n  }\n\n  setUnitFormat = (unit: string) => {\n    this.panel.yAxis.format = unit;\n    this.panelCtrl.render();\n  };\n}\n\n/** @ngInject */\nexport function axesEditor() {\n  'use strict';\n  return {\n    restrict: 'E',\n    scope: true,\n    templateUrl: 'public/app/plugins/panel/heatmap/partials/axes_editor.html',\n    controller: AxesEditorCtrl,\n  };\n}\n","export class HeatmapDisplayEditorCtrl {\n  panel: any;\n  panelCtrl: any;\n\n  /** @ngInject */\n  constructor($scope: any) {\n    $scope.editor = this;\n    this.panelCtrl = $scope.ctrl;\n    this.panel = this.panelCtrl.panel;\n  }\n}\n\n/** @ngInject */\nexport function heatmapDisplayEditor() {\n  'use strict';\n  return {\n    restrict: 'E',\n    scope: true,\n    templateUrl: 'public/app/plugins/panel/heatmap/partials/display_editor.html',\n    controller: HeatmapDisplayEditorCtrl,\n  };\n}\n","import { concat, forEach, isEmpty, isEqual, isNumber, sortBy } from 'lodash';\n\nimport { TimeSeries } from 'app/core/core';\n\nimport { Bucket, HeatmapCard, HeatmapCardStats, YBucket, XBucket } from './types';\n\nconst VALUE_INDEX = 0;\nconst TIME_INDEX = 1;\n\n/**\n * Convert histogram represented by the list of series to heatmap object.\n * @param seriesList List of time series\n */\nfunction histogramToHeatmap(seriesList: TimeSeries[]) {\n  const heatmap: any = {};\n\n  for (let i = 0; i < seriesList.length; i++) {\n    const series = seriesList[i];\n    const bound = i;\n    if (isNaN(bound)) {\n      return heatmap;\n    }\n\n    for (const point of series.datapoints) {\n      const count = point[VALUE_INDEX];\n      const time = point[TIME_INDEX];\n\n      if (!isNumber(count)) {\n        continue;\n      }\n\n      let bucket = heatmap[time];\n      if (!bucket) {\n        bucket = heatmap[time] = { x: time, buckets: {} };\n      }\n\n      bucket.buckets[bound] = {\n        y: bound,\n        count: count,\n        bounds: {\n          top: null,\n          bottom: bound,\n        },\n        values: [],\n        points: [],\n      };\n    }\n  }\n\n  return heatmap;\n}\n\n/**\n * Sort series representing histogram by label value.\n */\nfunction sortSeriesByLabel(s1: { label: string }, s2: { label: string }) {\n  let label1, label2;\n\n  try {\n    // fail if not integer. might happen with bad queries\n    label1 = parseHistogramLabel(s1.label);\n    label2 = parseHistogramLabel(s2.label);\n  } catch (err) {\n    console.error(err.message || err);\n    return 0;\n  }\n\n  if (label1 > label2) {\n    return 1;\n  }\n\n  if (label1 < label2) {\n    return -1;\n  }\n\n  return 0;\n}\n\nfunction parseHistogramLabel(label: string): number {\n  if (label === '+Inf' || label === 'inf') {\n    return +Infinity;\n  }\n  const value = Number(label);\n  if (isNaN(value)) {\n    throw new Error(`Error parsing histogram label: ${label} is not a number`);\n  }\n  return value;\n}\n\n/**\n * Convert buckets into linear array of \"cards\" - objects, represented heatmap elements.\n * @param  {Object} buckets\n * @returns {Object}          Array of \"card\" objects and stats\n */\nfunction convertToCards(buckets: any, hideZero = false): { cards: HeatmapCard[]; cardStats: HeatmapCardStats } {\n  let min = 0,\n    max = 0;\n  const cards: HeatmapCard[] = [];\n  forEach(buckets, (xBucket) => {\n    forEach(xBucket.buckets, (yBucket) => {\n      const card: HeatmapCard = {\n        x: xBucket.x,\n        y: yBucket.y,\n        yBounds: yBucket.bounds,\n        values: yBucket.values,\n        count: yBucket.count,\n      };\n      if (!hideZero || card.count !== 0) {\n        cards.push(card);\n      }\n\n      if (cards.length === 1) {\n        min = yBucket.count;\n        max = yBucket.count;\n      }\n\n      min = yBucket.count < min ? yBucket.count : min;\n      max = yBucket.count > max ? yBucket.count : max;\n    });\n  });\n\n  const cardStats = { min, max };\n  return { cards, cardStats };\n}\n\n/**\n * Special method for log scales. When series converted into buckets with log scale,\n * for simplification, 0 values are converted into 0, not into -Infinity. On the other hand, we mean\n * that all values less than series minimum, is 0 values, and we create special \"minimum\" bucket for\n * that values (actually, there're no values less than minimum, so this bucket is empty).\n *  8-16|    | ** |    |  * |  **|\n *   4-8|  * |*  *|*   |** *| *  |\n *   2-4| * *|    | ***|    |*   |\n *   1-2|*   |    |    |    |    | This bucket contains minimum series value\n * 0.5-1|____|____|____|____|____| This bucket should be displayed as 0 on graph\n *     0|____|____|____|____|____| This bucket is for 0 values (should actually be -Infinity)\n * So we should merge two bottom buckets into one (0-value bucket).\n *\n * @param  {Object} buckets  Heatmap buckets\n * @param  {Number} minValue Minimum series value\n * @returns {Object}          Transformed buckets\n */\nfunction mergeZeroBuckets(buckets: any, minValue: number) {\n  forEach(buckets, (xBucket) => {\n    const yBuckets = xBucket.buckets;\n\n    const emptyBucket: any = {\n      bounds: { bottom: 0, top: 0 },\n      values: [],\n      points: [],\n      count: 0,\n    };\n\n    const nullBucket = yBuckets[0] || emptyBucket;\n    const minBucket = yBuckets[minValue] || emptyBucket;\n\n    const newBucket: any = {\n      y: 0,\n      bounds: { bottom: minValue, top: minBucket.bounds.top || minValue },\n      values: [],\n      points: [],\n      count: 0,\n    };\n\n    newBucket.points = nullBucket.points.concat(minBucket.points);\n    newBucket.values = nullBucket.values.concat(minBucket.values);\n    newBucket.count = newBucket.values.length;\n\n    if (newBucket.count === 0) {\n      return;\n    }\n\n    delete yBuckets[minValue];\n    yBuckets[0] = newBucket;\n  });\n\n  return buckets;\n}\n\n/**\n * Convert set of time series into heatmap buckets\n * @returns {Object}    Heatmap object:\n * {\n *   xBucketBound_1: {\n *     x: xBucketBound_1,\n *     buckets: {\n *       yBucketBound_1: {\n *         y: yBucketBound_1,\n *         bounds: {bottom, top}\n *         values: [val_1, val_2, ..., val_K],\n *         points: [[val_Y, val_X, series_name], ..., [...]],\n *         seriesStat: {seriesName_1: val_1, seriesName_2: val_2}\n *       },\n *       ...\n *       yBucketBound_M: {}\n *     },\n *     values: [val_1, val_2, ..., val_K],\n *     points: [\n *       [val_Y, val_X, series_name], (point_1)\n *       ...\n *       [...] (point_K)\n *     ]\n *   },\n *   xBucketBound_2: {},\n *   ...\n *   xBucketBound_N: {}\n * }\n */\nfunction convertToHeatMap(seriesList: TimeSeries[], yBucketSize: number, xBucketSize: number, logBase = 1) {\n  const heatmap = {};\n\n  for (const series of seriesList) {\n    const datapoints = series.datapoints;\n    const seriesName = series.label;\n\n    // Slice series into X axis buckets\n    // |    | ** |    |  * |  **|\n    // |  * |*  *|*   |** *| *  |\n    // |** *|    | ***|    |*   |\n    // |____|____|____|____|____|_\n    //\n    forEach(datapoints, (point) => {\n      const bucketBound = getBucketBound(point[TIME_INDEX], xBucketSize);\n      pushToXBuckets(heatmap, point, bucketBound, seriesName);\n    });\n  }\n\n  // Slice X axis buckets into Y (value) buckets\n  // |  **|     |2|,\n  // | *  | --\\ |1|,\n  // |*   | --/ |1|,\n  // |____|     |0|\n  //\n  forEach(heatmap, (xBucket: any) => {\n    if (logBase !== 1) {\n      xBucket.buckets = convertToLogScaleValueBuckets(xBucket, yBucketSize, logBase);\n    } else {\n      xBucket.buckets = convertToValueBuckets(xBucket, yBucketSize);\n    }\n  });\n\n  return heatmap;\n}\n\nfunction pushToXBuckets(buckets: any, point: any[], bucketNum: number, seriesName: string) {\n  const value = point[VALUE_INDEX];\n  if (value === null || value === undefined || isNaN(value)) {\n    return;\n  }\n\n  // Add series name to point for future identification\n  const pointExt = concat(point, seriesName);\n\n  if (buckets[bucketNum] && buckets[bucketNum].values) {\n    buckets[bucketNum].values.push(value);\n    buckets[bucketNum].points.push(pointExt);\n  } else {\n    buckets[bucketNum] = {\n      x: bucketNum,\n      values: [value],\n      points: [pointExt],\n    };\n  }\n}\n\nfunction pushToYBuckets(\n  buckets: Bucket,\n  bucketNum: number,\n  value: any,\n  point: string[],\n  bounds: { bottom: number; top: number }\n) {\n  let count = 1;\n  // Use the 3rd argument as scale/count\n  if (point.length > 3) {\n    count = parseInt(point[2], 10);\n  }\n  if (buckets[bucketNum]) {\n    buckets[bucketNum].values.push(value);\n    buckets[bucketNum].points?.push(point);\n    buckets[bucketNum].count += count;\n  } else {\n    buckets[bucketNum] = {\n      y: bucketNum,\n      bounds: bounds,\n      values: [value],\n      points: [point],\n      count: count,\n    };\n  }\n}\n\nfunction getValueBucketBound(value: any, yBucketSize: number, logBase: number) {\n  if (logBase === 1) {\n    return getBucketBound(value, yBucketSize);\n  } else {\n    return getLogScaleBucketBound(value, yBucketSize, logBase);\n  }\n}\n\n/**\n * Find bucket for given value (for linear scale)\n */\nfunction getBucketBounds(value: number, bucketSize: number) {\n  let bottom, top;\n  bottom = Math.floor(value / bucketSize) * bucketSize;\n  top = (Math.floor(value / bucketSize) + 1) * bucketSize;\n\n  return { bottom, top };\n}\n\nfunction getBucketBound(value: number, bucketSize: number) {\n  const bounds = getBucketBounds(value, bucketSize);\n  return bounds.bottom;\n}\n\nfunction convertToValueBuckets(xBucket: { values: any; points: any }, bucketSize: number) {\n  const values = xBucket.values;\n  const points = xBucket.points;\n  const buckets = {};\n\n  forEach(values, (val, index) => {\n    const bounds = getBucketBounds(val, bucketSize);\n    const bucketNum = bounds.bottom;\n    pushToYBuckets(buckets, bucketNum, val, points[index], bounds);\n  });\n\n  return buckets;\n}\n\n/**\n * Find bucket for given value (for log scales)\n */\nfunction getLogScaleBucketBounds(value: number, yBucketSplitFactor: number, logBase: number) {\n  let top, bottom;\n  if (value === 0) {\n    return { bottom: 0, top: 0 };\n  }\n\n  const valueLog = logp(value, logBase);\n  let pow, powTop;\n  if (yBucketSplitFactor === 1 || !yBucketSplitFactor) {\n    pow = Math.floor(valueLog);\n    powTop = pow + 1;\n  } else {\n    const additionalBucketSize = 1 / yBucketSplitFactor;\n    let additionalLog = valueLog - Math.floor(valueLog);\n    additionalLog = Math.floor(additionalLog / additionalBucketSize) * additionalBucketSize;\n    pow = Math.floor(valueLog) + additionalLog;\n    powTop = pow + additionalBucketSize;\n  }\n  bottom = Math.pow(logBase, pow);\n  top = Math.pow(logBase, powTop);\n\n  return { bottom, top };\n}\n\nfunction getLogScaleBucketBound(value: number, yBucketSplitFactor: number, logBase: number) {\n  const bounds = getLogScaleBucketBounds(value, yBucketSplitFactor, logBase);\n  return bounds.bottom;\n}\n\nfunction convertToLogScaleValueBuckets(\n  xBucket: { values: any; points: any },\n  yBucketSplitFactor: number,\n  logBase: number\n) {\n  const values = xBucket.values;\n  const points = xBucket.points;\n\n  const buckets = {};\n  forEach(values, (val, index) => {\n    const bounds = getLogScaleBucketBounds(val, yBucketSplitFactor, logBase);\n    const bucketNum = bounds.bottom;\n    pushToYBuckets(buckets, bucketNum, val, points[index], bounds);\n  });\n\n  return buckets;\n}\n\n/**\n * Logarithm for custom base\n * @param value\n * @param base logarithm base\n */\nfunction logp(value: number, base: number) {\n  return Math.log(value) / Math.log(base);\n}\n\n/**\n * Calculate size of Y bucket from given buckets bounds.\n * @param bounds Array of Y buckets bounds\n * @param logBase Logarithm base\n */\nfunction calculateBucketSize(bounds: number[], logBase = 1): number {\n  let bucketSize = Infinity;\n\n  if (bounds.length === 0) {\n    return 0;\n  } else if (bounds.length === 1) {\n    return bounds[0];\n  } else {\n    bounds = sortBy(bounds);\n    for (let i = 1; i < bounds.length; i++) {\n      const distance = getDistance(bounds[i], bounds[i - 1], logBase);\n      bucketSize = distance < bucketSize ? distance : bucketSize;\n    }\n  }\n\n  return bucketSize;\n}\n\n/**\n * Calculate distance between two numbers in given scale (linear or logarithmic).\n * @param a\n * @param b\n * @param logBase\n */\nfunction getDistance(a: number, b: number, logBase = 1): number {\n  if (logBase === 1) {\n    // Linear distance\n    return Math.abs(b - a);\n  } else {\n    // logarithmic distance\n    const ratio = Math.max(a, b) / Math.min(a, b);\n    return logp(ratio, logBase);\n  }\n}\n\n/**\n * Compare two heatmap data objects\n * @param objA\n * @param objB\n */\nfunction isHeatmapDataEqual(objA: any, objB: any): boolean {\n  let isEql = !emptyXOR(objA, objB);\n\n  forEach(objA, (xBucket: XBucket, x) => {\n    if (objB[x]) {\n      if (emptyXOR(xBucket.buckets, objB[x].buckets)) {\n        isEql = false;\n        return false;\n      }\n\n      forEach(xBucket.buckets, (yBucket: YBucket, y) => {\n        if (objB[x].buckets && objB[x].buckets[y]) {\n          if (objB[x].buckets[y].values) {\n            isEql = isEqual(sortBy(yBucket.values), sortBy(objB[x].buckets[y].values));\n            if (!isEql) {\n              return false;\n            } else {\n              return true;\n            }\n          } else {\n            isEql = false;\n            return false;\n          }\n        } else {\n          isEql = false;\n          return false;\n        }\n      });\n\n      if (!isEql) {\n        return false;\n      } else {\n        return true;\n      }\n    } else {\n      isEql = false;\n      return false;\n    }\n  });\n\n  return isEql;\n}\n\nfunction emptyXOR(foo: any, bar: any): boolean {\n  return (isEmpty(foo) || isEmpty(bar)) && !(isEmpty(foo) && isEmpty(bar));\n}\n\nexport {\n  convertToHeatMap,\n  histogramToHeatmap,\n  convertToCards,\n  mergeZeroBuckets,\n  getValueBucketBound,\n  isHeatmapDataEqual,\n  calculateBucketSize,\n  sortSeriesByLabel,\n};\n","import * as d3 from 'd3';\nimport $ from 'jquery';\nimport { filter, find, isNumber, map, reduce } from 'lodash';\n\nimport { getValueFormat, formattedValueToString } from '@grafana/data';\n\nimport { getValueBucketBound } from './heatmap_data_converter';\n\nconst TOOLTIP_PADDING_X = 30;\nconst TOOLTIP_PADDING_Y = 5;\nconst HISTOGRAM_WIDTH = 160;\nconst HISTOGRAM_HEIGHT = 40;\n\nexport class HeatmapTooltip {\n  tooltip: any;\n  scope: any;\n  dashboard: any;\n  panelCtrl: any;\n  panel: any;\n  heatmapPanel: any;\n  mouseOverBucket: boolean;\n  originalFillColor: any;\n\n  constructor(elem: JQuery, scope: any) {\n    this.scope = scope;\n    this.dashboard = scope.ctrl.dashboard;\n    this.panelCtrl = scope.ctrl;\n    this.panel = scope.ctrl.panel;\n    this.heatmapPanel = elem;\n    this.mouseOverBucket = false;\n    this.originalFillColor = null;\n\n    elem.on('mouseleave', this.onMouseLeave.bind(this));\n  }\n\n  onMouseLeave() {\n    this.destroy();\n  }\n\n  onMouseMove(e: any) {\n    if (!this.panel.tooltip.show) {\n      return;\n    }\n\n    this.move(e);\n  }\n\n  add() {\n    this.tooltip = d3.select('body').append('div').attr('class', 'heatmap-tooltip graph-tooltip grafana-tooltip');\n  }\n\n  destroy() {\n    if (this.tooltip) {\n      this.tooltip.remove();\n    }\n\n    this.tooltip = null;\n  }\n\n  show(pos: { panelRelY: any }, data: any) {\n    if (!this.panel.tooltip.show || !data) {\n      return;\n    }\n    // shared tooltip mode\n    if (pos.panelRelY) {\n      return;\n    }\n\n    const { xBucketIndex, yBucketIndex } = this.getBucketIndexes(pos, data);\n\n    if (!data.buckets[xBucketIndex]) {\n      this.destroy();\n      return;\n    }\n\n    if (!this.tooltip) {\n      this.add();\n    }\n\n    let boundBottom, boundTop, valuesNumber;\n    const xData = data.buckets[xBucketIndex];\n    // Search in special 'zero' bucket also\n    const yData: any = find(xData.buckets, (bucket, bucketIndex) => {\n      return bucket.bounds.bottom === yBucketIndex || bucketIndex === yBucketIndex.toString();\n    });\n\n    const tooltipTimeFormat = 'YYYY-MM-DD HH:mm:ss';\n    const time = this.dashboard.formatDate(xData.x, tooltipTimeFormat);\n\n    // Decimals override. Code from panel/graph/graph.ts\n    let countValueFormatter, bucketBoundFormatter;\n    if (isNumber(this.panel.tooltipDecimals)) {\n      countValueFormatter = this.countValueFormatter(this.panel.tooltipDecimals, null);\n      bucketBoundFormatter = this.panelCtrl.tickValueFormatter(this.panelCtrl.decimals, null);\n    } else {\n      // auto decimals\n      // legend and tooltip gets one more decimal precision\n      // than graph legend ticks\n      const decimals = (this.panelCtrl.decimals || -1) + 1;\n      countValueFormatter = this.countValueFormatter(decimals, this.panelCtrl.scaledDecimals + 2);\n      bucketBoundFormatter = this.panelCtrl.tickValueFormatter(decimals, this.panelCtrl.scaledDecimals + 2);\n    }\n\n    let tooltipHtml = `<div class=\"graph-tooltip-time\">${time}</div>\n      <div class=\"heatmap-histogram\"></div>`;\n\n    if (yData) {\n      if (yData.bounds) {\n        if (data.tsBuckets) {\n          // Use Y-axis labels\n          const tickFormatter = (valIndex: string | number) => {\n            return data.tsBucketsFormatted ? data.tsBucketsFormatted[valIndex] : data.tsBuckets[valIndex];\n          };\n\n          boundBottom = tickFormatter(yBucketIndex);\n          if (this.panel.yBucketBound !== 'middle') {\n            boundTop = yBucketIndex < data.tsBuckets.length - 1 ? tickFormatter(yBucketIndex + 1) : '';\n          }\n        } else {\n          // Display 0 if bucket is a special 'zero' bucket\n          const bottom = yData.y ? yData.bounds.bottom : 0;\n          boundBottom = bucketBoundFormatter(bottom);\n          boundTop = bucketBoundFormatter(yData.bounds.top);\n        }\n        valuesNumber = countValueFormatter(yData.count);\n        const boundStr = boundTop && boundBottom ? `${boundBottom} - ${boundTop}` : boundBottom || boundTop;\n        tooltipHtml += `<div>\n          bucket: <b>${boundStr}</b> <br>\n          count: <b>${valuesNumber}</b> <br>\n        </div>`;\n      } else {\n        // currently no bounds for pre bucketed data\n        tooltipHtml += `<div>count: <b>${yData.count}</b><br></div>`;\n      }\n    } else {\n      if (!this.panel.tooltip.showHistogram) {\n        this.destroy();\n        return;\n      }\n      boundBottom = yBucketIndex;\n      boundTop = '';\n      valuesNumber = 0;\n    }\n\n    this.tooltip.html(tooltipHtml);\n\n    if (this.panel.tooltip.showHistogram) {\n      this.addHistogram(xData);\n    }\n\n    this.move(pos);\n  }\n\n  getBucketIndexes(pos: { panelRelY?: any; x?: any; y?: any }, data: any) {\n    const xBucketIndex = this.getXBucketIndex(pos.x, data);\n    const yBucketIndex = this.getYBucketIndex(pos.y, data);\n    return { xBucketIndex, yBucketIndex };\n  }\n\n  getXBucketIndex(x: number, data: { buckets: any; xBucketSize: number }) {\n    // First try to find X bucket by checking x pos is in the\n    // [bucket.x, bucket.x + xBucketSize] interval\n    const xBucket: any = find(data.buckets, (bucket) => {\n      return x > bucket.x && x - bucket.x <= data.xBucketSize;\n    });\n    return xBucket ? xBucket.x : getValueBucketBound(x, data.xBucketSize, 1);\n  }\n\n  getYBucketIndex(y: number, data: { tsBuckets: any; yBucketSize: number }) {\n    if (data.tsBuckets) {\n      return Math.floor(y);\n    }\n    const yBucketIndex = getValueBucketBound(y, data.yBucketSize, this.panel.yAxis.logBase);\n    return yBucketIndex;\n  }\n\n  getSharedTooltipPos(pos: { pageX: any; x: any; pageY: any; panelRelY: number }) {\n    // get pageX from position on x axis and pageY from relative position in original panel\n    pos.pageX = this.heatmapPanel.offset().left + this.scope.xScale(pos.x);\n    pos.pageY = this.heatmapPanel.offset().top + this.scope.chartHeight * pos.panelRelY;\n    return pos;\n  }\n\n  addHistogram(data: { x: string | number }) {\n    const xBucket = this.scope.ctrl.data.buckets[data.x];\n    const yBucketSize = this.scope.ctrl.data.yBucketSize;\n    let min: number, max: number, ticks: number;\n    if (this.scope.ctrl.data.tsBuckets) {\n      min = 0;\n      max = this.scope.ctrl.data.tsBuckets.length - 1;\n      ticks = this.scope.ctrl.data.tsBuckets.length;\n    } else {\n      min = this.scope.ctrl.data.yAxis.min;\n      max = this.scope.ctrl.data.yAxis.max;\n      ticks = this.scope.ctrl.data.yAxis.ticks;\n    }\n    let histogramData = map(xBucket.buckets, (bucket) => {\n      const count = bucket.count !== undefined ? bucket.count : bucket.values.length;\n      return [bucket.bounds.bottom, count];\n    });\n    histogramData = filter(histogramData, (d) => {\n      return d[0] >= min && d[0] <= max;\n    });\n\n    const scale = this.scope.yScale.copy();\n    const histXScale = scale.domain([min, max]).range([0, HISTOGRAM_WIDTH]);\n\n    let barWidth: number;\n    if (this.panel.yAxis.logBase === 1) {\n      barWidth = Math.floor((HISTOGRAM_WIDTH / (max - min)) * yBucketSize * 0.9);\n    } else {\n      const barNumberFactor = yBucketSize ? yBucketSize : 1;\n      barWidth = Math.floor((HISTOGRAM_WIDTH / ticks / barNumberFactor) * 0.9);\n    }\n    barWidth = Math.max(barWidth, 1);\n\n    // Normalize histogram Y axis\n    const histogramDomain = reduce(\n      map(histogramData, (d) => d[1]),\n      (sum, val) => sum + val,\n      0\n    );\n    const histYScale = d3.scaleLinear().domain([0, histogramDomain]).range([0, HISTOGRAM_HEIGHT]);\n\n    const histogram = this.tooltip\n      .select('.heatmap-histogram')\n      .append('svg')\n      .attr('width', HISTOGRAM_WIDTH)\n      .attr('height', HISTOGRAM_HEIGHT);\n\n    histogram\n      .selectAll('.bar')\n      .data(histogramData)\n      .enter()\n      .append('rect')\n      .attr('x', (d: any[]) => {\n        return histXScale(d[0]);\n      })\n      .attr('width', barWidth)\n      .attr('y', (d: any[]) => {\n        return HISTOGRAM_HEIGHT - histYScale(d[1]);\n      })\n      .attr('height', (d: any[]) => {\n        return histYScale(d[1]);\n      });\n  }\n\n  move(pos: { panelRelY?: any; pageX?: any; pageY?: any }) {\n    if (!this.tooltip) {\n      return;\n    }\n\n    const elem = $(this.tooltip.node())[0];\n    const tooltipWidth = elem.clientWidth;\n    const tooltipHeight = elem.clientHeight;\n\n    let left = pos.pageX + TOOLTIP_PADDING_X;\n    let top = pos.pageY + TOOLTIP_PADDING_Y;\n\n    if (pos.pageX + tooltipWidth + 40 > window.innerWidth) {\n      left = pos.pageX - tooltipWidth - TOOLTIP_PADDING_X;\n    }\n\n    if (pos.pageY - window.pageYOffset + tooltipHeight + 20 > window.innerHeight) {\n      top = pos.pageY - tooltipHeight - TOOLTIP_PADDING_Y;\n    }\n\n    return this.tooltip.style('left', left + 'px').style('top', top + 'px');\n  }\n\n  countValueFormatter(decimals: number, scaledDecimals: any = null) {\n    const fmt = getValueFormat('short');\n    return (value: number) => {\n      return formattedValueToString(fmt(value, decimals, scaledDecimals));\n    };\n  }\n}\n","import * as d3 from 'd3';\nimport $ from 'jquery';\nimport { find, isEmpty, isNaN, isNil, isString, map, max, min, toNumber } from 'lodash';\n\nimport {\n  dateTimeFormat,\n  formattedValueToString,\n  getValueFormat,\n  LegacyGraphHoverClearEvent,\n  LegacyGraphHoverEvent,\n  PanelEvents,\n  toUtc,\n} from '@grafana/data';\nimport { graphTimeFormat } from '@grafana/ui';\nimport { config } from 'app/core/config';\nimport { contextSrv } from 'app/core/core';\nimport * as ticksUtils from 'app/core/utils/ticks';\n\nimport { getColorScale, getOpacityScale } from './color_scale';\nimport { mergeZeroBuckets } from './heatmap_data_converter';\nimport { HeatmapTooltip } from './heatmap_tooltip';\n\nconst MIN_CARD_SIZE = 1,\n  CARD_PADDING = 1,\n  CARD_ROUND = 0,\n  DATA_RANGE_WIDING_FACTOR = 1.2,\n  DEFAULT_X_TICK_SIZE_PX = 100,\n  DEFAULT_Y_TICK_SIZE_PX = 22.5,\n  X_AXIS_TICK_PADDING = 10,\n  Y_AXIS_TICK_PADDING = 5,\n  MIN_SELECTION_WIDTH = 2;\n\nexport default function rendering(scope: any, elem: any, attrs: any, ctrl: any) {\n  return new HeatmapRenderer(scope, elem, attrs, ctrl);\n}\nexport class HeatmapRenderer {\n  width = 200;\n  height = 200;\n  yScale: any;\n  xScale: any;\n  chartWidth = 0;\n  chartHeight = 0;\n  chartTop = 0;\n  chartBottom = 0;\n  yAxisWidth = 0;\n  xAxisHeight = 0;\n  cardPadding = 0;\n  cardRound = 0;\n  cardWidth = 0;\n  cardHeight = 0;\n  colorScale: any;\n  opacityScale: any;\n  mouseUpHandler: any;\n  data: any;\n  panel: any;\n  $heatmap: any;\n  tooltip: HeatmapTooltip;\n  heatmap: any;\n  timeRange: any;\n\n  selection: any;\n  padding: any;\n  margin: any;\n  dataRangeWidingFactor: number;\n\n  hoverEvent: LegacyGraphHoverEvent;\n\n  constructor(private scope: any, private elem: any, attrs: any, private ctrl: any) {\n    // $heatmap is JQuery object, but heatmap is D3\n    this.$heatmap = this.elem.find('.heatmap-panel');\n    this.tooltip = new HeatmapTooltip(this.$heatmap, this.scope);\n\n    this.selection = {\n      active: false,\n      x1: -1,\n      x2: -1,\n    };\n\n    this.padding = { left: 0, right: 0, top: 0, bottom: 0 };\n    this.margin = { left: 25, right: 15, top: 10, bottom: 20 };\n    this.dataRangeWidingFactor = DATA_RANGE_WIDING_FACTOR;\n    this.ctrl.events.on(PanelEvents.render, this.onRender.bind(this));\n    this.ctrl.tickValueFormatter = this.tickValueFormatter.bind(this);\n\n    /////////////////////////////\n    // Selection and crosshair //\n    /////////////////////////////\n\n    // Shared crosshair and tooltip\n    this.ctrl.dashboard.events.on(LegacyGraphHoverEvent.type, this.onGraphHover.bind(this), this.scope);\n    this.ctrl.dashboard.events.on(LegacyGraphHoverClearEvent.type, this.onGraphHoverClear.bind(this), this.scope);\n\n    // Register selection listeners\n    this.$heatmap.on('mousedown', this.onMouseDown.bind(this));\n    this.$heatmap.on('mousemove', this.onMouseMove.bind(this));\n    this.$heatmap.on('mouseleave', this.onMouseLeave.bind(this));\n\n    this.hoverEvent = new LegacyGraphHoverEvent({ pos: {}, point: {}, panel: this.panel });\n  }\n\n  onGraphHoverClear() {\n    this.clearCrosshair();\n  }\n\n  onGraphHover(event: { pos: any }) {\n    this.drawSharedCrosshair(event.pos);\n  }\n\n  onRender() {\n    this.render();\n    this.ctrl.renderingCompleted();\n  }\n\n  setElementHeight() {\n    try {\n      let height = this.ctrl.height || this.panel.height || this.ctrl.row.height;\n      if (isString(height)) {\n        height = parseInt(height.replace('px', ''), 10);\n      }\n\n      height -= this.panel.legend.show ? 28 : 11; // bottom padding and space for legend\n\n      this.$heatmap.css('height', height + 'px');\n\n      return true;\n    } catch (e) {\n      // IE throws errors sometimes\n      return false;\n    }\n  }\n\n  getYAxisWidth(elem: any) {\n    const panelYAxisWidth = this.getPanelYAxisWidth();\n    if (panelYAxisWidth !== null) {\n      return panelYAxisWidth + Y_AXIS_TICK_PADDING;\n    }\n\n    const axisText = elem.selectAll('.axis-y text').nodes();\n    const maxTextWidth = max(\n      map(axisText, (text) => {\n        // Use SVG getBBox method\n        return text.getBBox().width;\n      })\n    );\n\n    return maxTextWidth;\n  }\n\n  getXAxisHeight(elem: any) {\n    const axisLine = elem.select('.axis-x line');\n    if (!axisLine.empty()) {\n      const axisLinePosition = parseFloat(elem.select('.axis-x line').attr('y2'));\n      const canvasWidth = parseFloat(elem.attr('height'));\n      return canvasWidth - axisLinePosition;\n    } else {\n      // Default height\n      return 30;\n    }\n  }\n\n  addXAxis() {\n    this.scope.xScale = this.xScale = d3\n      .scaleTime()\n      .domain([this.timeRange.from, this.timeRange.to])\n      .range([0, this.chartWidth]);\n\n    const ticks = this.chartWidth / DEFAULT_X_TICK_SIZE_PX;\n    const format = graphTimeFormat(ticks, this.timeRange.from.valueOf(), this.timeRange.to.valueOf());\n    const timeZone = this.ctrl.dashboard.getTimezone();\n    const formatter = (date: d3.AxisDomain) =>\n      dateTimeFormat(date.valueOf(), {\n        format: format,\n        timeZone: timeZone,\n      });\n\n    const xAxis = d3\n      .axisBottom(this.xScale)\n      .ticks(ticks)\n      .tickFormat(formatter)\n      .tickPadding(X_AXIS_TICK_PADDING)\n      .tickSize(this.chartHeight);\n\n    const posY = this.margin.top;\n    const posX = this.yAxisWidth;\n    this.heatmap\n      .append('g')\n      .attr('class', 'axis axis-x')\n      .attr('transform', 'translate(' + posX + ',' + posY + ')')\n      .call(xAxis);\n\n    // Remove horizontal line in the top of axis labels (called domain in d3)\n    this.heatmap.select('.axis-x').select('.domain').remove();\n  }\n\n  addYAxis() {\n    let ticks = Math.ceil(this.chartHeight / DEFAULT_Y_TICK_SIZE_PX);\n    let tickInterval = ticksUtils.tickStep(this.data.heatmapStats.min, this.data.heatmapStats.max, ticks);\n    let { yMin, yMax } = this.wideYAxisRange(this.data.heatmapStats.min, this.data.heatmapStats.max, tickInterval);\n\n    // Rewrite min and max if it have been set explicitly\n    yMin = this.panel.yAxis.min !== null ? this.panel.yAxis.min : yMin;\n    yMax = this.panel.yAxis.max !== null ? this.panel.yAxis.max : yMax;\n\n    // Adjust ticks after Y range widening\n    tickInterval = ticksUtils.tickStep(yMin, yMax, ticks);\n    ticks = Math.ceil((yMax - yMin) / tickInterval);\n\n    const decimalsAuto = ticksUtils.getPrecision(tickInterval);\n    let decimals = this.panel.yAxis.decimals === null ? decimalsAuto : this.panel.yAxis.decimals;\n    // Calculate scaledDecimals for log scales using tick size (as in jquery.flot.js)\n    const flotTickSize = ticksUtils.getFlotTickSize(yMin, yMax, ticks, decimalsAuto);\n    const scaledDecimals = ticksUtils.getScaledDecimals(decimals, flotTickSize);\n    this.ctrl.decimals = decimals;\n    this.ctrl.scaledDecimals = scaledDecimals;\n\n    // Set default Y min and max if no data\n    if (isEmpty(this.data.buckets)) {\n      yMax = 1;\n      yMin = -1;\n      ticks = 3;\n      decimals = 1;\n    }\n\n    this.data.yAxis = {\n      min: yMin,\n      max: yMax,\n      ticks: ticks,\n    };\n\n    this.scope.yScale = this.yScale = d3.scaleLinear().domain([yMin, yMax]).range([this.chartHeight, 0]);\n\n    const yAxis = d3\n      .axisLeft(this.yScale)\n      .ticks(ticks)\n      .tickFormat(this.tickValueFormatter(decimals, scaledDecimals))\n      .tickSizeInner(0 - this.width)\n      .tickSizeOuter(0)\n      .tickPadding(Y_AXIS_TICK_PADDING);\n\n    this.heatmap.append('g').attr('class', 'axis axis-y').call(yAxis);\n\n    // Calculate Y axis width first, then move axis into visible area\n    const posY = this.margin.top;\n    const posX = this.getYAxisWidth(this.heatmap) + Y_AXIS_TICK_PADDING;\n    this.heatmap.select('.axis-y').attr('transform', 'translate(' + posX + ',' + posY + ')');\n\n    // Remove vertical line in the right of axis labels (called domain in d3)\n    this.heatmap.select('.axis-y').select('.domain').remove();\n  }\n\n  // Wide Y values range and anjust to bucket size\n  wideYAxisRange(min: number, max: number, tickInterval: number) {\n    const yWiding = (max * (this.dataRangeWidingFactor - 1) - min * (this.dataRangeWidingFactor - 1)) / 2;\n    let yMin, yMax;\n\n    if (tickInterval === 0) {\n      yMax = max * this.dataRangeWidingFactor;\n      yMin = min - min * (this.dataRangeWidingFactor - 1);\n    } else {\n      yMax = Math.ceil((max + yWiding) / tickInterval) * tickInterval;\n      yMin = Math.floor((min - yWiding) / tickInterval) * tickInterval;\n    }\n\n    // Don't wide axis below 0 if all values are positive\n    if (min >= 0 && yMin < 0) {\n      yMin = 0;\n    }\n\n    return { yMin, yMax };\n  }\n\n  addLogYAxis() {\n    const logBase = this.panel.yAxis.logBase;\n    let { yMin, yMax } = this.adjustLogRange(this.data.heatmapStats.minLog, this.data.heatmapStats.max, logBase);\n\n    yMin =\n      this.panel.yAxis.min && this.panel.yAxis.min !== '0' ? this.adjustLogMin(this.panel.yAxis.min, logBase) : yMin;\n    yMax = this.panel.yAxis.max !== null ? this.adjustLogMax(this.panel.yAxis.max, logBase) : yMax;\n\n    // Set default Y min and max if no data\n    if (isEmpty(this.data.buckets)) {\n      yMax = Math.pow(logBase, 2);\n      yMin = 1;\n    }\n\n    this.scope.yScale = this.yScale = d3\n      .scaleLog()\n      .base(this.panel.yAxis.logBase)\n      .domain([yMin, yMax])\n      .range([this.chartHeight, 0]);\n\n    const domain = this.yScale.domain();\n    const tickValues = this.logScaleTickValues(domain, logBase);\n\n    const decimalsAuto = ticksUtils.getPrecision(yMin);\n    const decimals = this.panel.yAxis.decimals || decimalsAuto;\n\n    // Calculate scaledDecimals for log scales using tick size (as in jquery.flot.js)\n    const flotTickSize = ticksUtils.getFlotTickSize(yMin, yMax, tickValues.length, decimalsAuto);\n    const scaledDecimals = ticksUtils.getScaledDecimals(decimals, flotTickSize);\n    this.ctrl.decimals = decimals;\n    this.ctrl.scaledDecimals = scaledDecimals;\n\n    this.data.yAxis = {\n      min: yMin,\n      max: yMax,\n      ticks: tickValues.length,\n    };\n\n    const yAxis = d3\n      .axisLeft(this.yScale)\n      .tickValues(tickValues)\n      .tickFormat(this.tickValueFormatter(decimals, scaledDecimals))\n      .tickSizeInner(0 - this.width)\n      .tickSizeOuter(0)\n      .tickPadding(Y_AXIS_TICK_PADDING);\n\n    this.heatmap.append('g').attr('class', 'axis axis-y').call(yAxis);\n\n    // Calculate Y axis width first, then move axis into visible area\n    const posY = this.margin.top;\n    const posX = this.getYAxisWidth(this.heatmap) + Y_AXIS_TICK_PADDING;\n    this.heatmap.select('.axis-y').attr('transform', 'translate(' + posX + ',' + posY + ')');\n\n    // Set first tick as pseudo 0\n    if (yMin < 1) {\n      this.heatmap.select('.axis-y').select('.tick text').text('0');\n    }\n\n    // Remove vertical line in the right of axis labels (called domain in d3)\n    this.heatmap.select('.axis-y').select('.domain').remove();\n  }\n\n  addYAxisFromBuckets() {\n    const tsBuckets = this.data.tsBuckets;\n    let ticks = Math.ceil(this.chartHeight / DEFAULT_Y_TICK_SIZE_PX);\n\n    this.scope.yScale = this.yScale = d3\n      .scaleLinear()\n      .domain([0, tsBuckets.length - 1])\n      .range([this.chartHeight, 0]);\n\n    const tickValues = map(tsBuckets, (b, i) => i);\n    const decimalsAuto = max(map(tsBuckets, ticksUtils.getStringPrecision));\n    const decimals = this.panel.yAxis.decimals === null ? decimalsAuto : this.panel.yAxis.decimals;\n    this.ctrl.decimals = decimals;\n\n    const tickValueFormatter = this.tickValueFormatter.bind(this);\n    function tickFormatter(yAxisWidth: number | null) {\n      return function (valIndex: d3.AxisDomain) {\n        let valueFormatted = tsBuckets[valIndex.valueOf()];\n        if (!isNaN(toNumber(valueFormatted)) && valueFormatted !== '') {\n          // Try to format numeric tick labels\n          valueFormatted = tickValueFormatter(decimals)(toNumber(valueFormatted));\n        } else if (valueFormatted && typeof valueFormatted === 'string' && valueFormatted !== '') {\n          if (yAxisWidth) {\n            const scale = 0.15; // how to have a better calculation for this\n            const trimmed = valueFormatted.substring(0, Math.floor(yAxisWidth * scale));\n            const postfix = trimmed.length < valueFormatted.length ? '...' : '';\n            valueFormatted = `${trimmed}${postfix}`;\n          }\n        }\n        return valueFormatted;\n      };\n    }\n    const tsBucketsFormatted = map(tsBuckets, (v, i) => tickFormatter(null)(i));\n    this.data.tsBucketsFormatted = tsBucketsFormatted;\n\n    const yAxis = d3\n      .axisLeft(this.yScale)\n      .tickFormat(tickFormatter(this.getPanelYAxisWidth()))\n      .tickSizeInner(0 - this.width)\n      .tickSizeOuter(0)\n      .tickPadding(Y_AXIS_TICK_PADDING);\n    if (tickValues && tickValues.length <= ticks) {\n      yAxis.tickValues(tickValues);\n    } else {\n      yAxis.ticks(ticks);\n    }\n\n    this.heatmap.append('g').attr('class', 'axis axis-y').call(yAxis);\n\n    // Calculate Y axis width first, then move axis into visible area\n    const posY = this.margin.top;\n    const posX = this.getYAxisWidth(this.heatmap) + Y_AXIS_TICK_PADDING;\n    this.heatmap.select('.axis-y').attr('transform', 'translate(' + posX + ',' + posY + ')');\n\n    if (this.panel.yBucketBound === 'middle' && tickValues && tickValues.length) {\n      // Shift Y axis labels to the middle of bucket\n      const tickShift = 0 - this.chartHeight / (tickValues.length - 1) / 2;\n      this.heatmap.selectAll('.axis-y text').attr('transform', 'translate(' + 0 + ',' + tickShift + ')');\n    }\n\n    // Remove vertical line in the right of axis labels (called domain in d3)\n    this.heatmap.select('.axis-y').select('.domain').remove();\n  }\n\n  // Adjust data range to log base\n  adjustLogRange(min: number, max: number, logBase: number) {\n    let yMin = this.data.heatmapStats.minLog;\n    if (this.data.heatmapStats.minLog > 1 || !this.data.heatmapStats.minLog) {\n      yMin = 1;\n    } else {\n      yMin = this.adjustLogMin(this.data.heatmapStats.minLog, logBase);\n    }\n\n    // Adjust max Y value to log base\n    const yMax = this.adjustLogMax(this.data.heatmapStats.max, logBase);\n\n    return { yMin, yMax };\n  }\n\n  adjustLogMax(max: number, base: number) {\n    return Math.pow(base, Math.ceil(ticksUtils.logp(max, base)));\n  }\n\n  adjustLogMin(min: number, base: number) {\n    return Math.pow(base, Math.floor(ticksUtils.logp(min, base)));\n  }\n\n  logScaleTickValues(domain: any[], base: number) {\n    const domainMin = domain[0];\n    const domainMax = domain[1];\n    const tickValues = [];\n\n    if (domainMin < 1) {\n      const underOneTicks = Math.floor(ticksUtils.logp(domainMin, base));\n      for (let i = underOneTicks; i < 0; i++) {\n        const tickValue = Math.pow(base, i);\n        tickValues.push(tickValue);\n      }\n    }\n\n    const ticks = Math.ceil(ticksUtils.logp(domainMax, base));\n    for (let i = 0; i <= ticks; i++) {\n      const tickValue = Math.pow(base, i);\n      tickValues.push(tickValue);\n    }\n\n    return tickValues;\n  }\n\n  tickValueFormatter(decimals: number, scaledDecimals: any = null) {\n    const format = this.panel.yAxis.format;\n    return (value: any) => {\n      try {\n        if (format !== 'none') {\n          const v = getValueFormat(format)(value, decimals, scaledDecimals);\n          return formattedValueToString(v);\n        }\n      } catch (err) {\n        console.error(err.message || err);\n      }\n      return value;\n    };\n  }\n\n  fixYAxisTickSize() {\n    this.heatmap.select('.axis-y').selectAll('.tick line').attr('x2', this.chartWidth);\n  }\n\n  addAxes() {\n    this.chartHeight = this.height - this.margin.top - this.margin.bottom;\n    this.chartTop = this.margin.top;\n    this.chartBottom = this.chartTop + this.chartHeight;\n    if (this.panel.dataFormat === 'tsbuckets') {\n      this.addYAxisFromBuckets();\n    } else {\n      if (this.panel.yAxis.logBase === 1) {\n        this.addYAxis();\n      } else {\n        this.addLogYAxis();\n      }\n    }\n\n    this.yAxisWidth = this.getYAxisWidth(this.heatmap) + Y_AXIS_TICK_PADDING;\n    this.chartWidth = this.width - this.yAxisWidth - this.margin.right;\n    this.fixYAxisTickSize();\n\n    this.addXAxis();\n    this.xAxisHeight = this.getXAxisHeight(this.heatmap);\n\n    if (!this.panel.yAxis.show) {\n      this.heatmap.select('.axis-y').selectAll('line').style('opacity', 0);\n    }\n\n    if (!this.panel.xAxis.show) {\n      this.heatmap.select('.axis-x').selectAll('line').style('opacity', 0);\n    }\n  }\n\n  addHeatmapCanvas() {\n    const heatmapElem = this.$heatmap[0];\n\n    this.width = Math.floor(this.$heatmap.width()) - this.padding.right;\n    this.height = Math.floor(this.$heatmap.height()) - this.padding.bottom;\n\n    this.cardPadding = this.panel.cards.cardPadding !== null ? this.panel.cards.cardPadding : CARD_PADDING;\n    this.cardRound = this.panel.cards.cardRound !== null ? this.panel.cards.cardRound : CARD_ROUND;\n\n    if (this.heatmap) {\n      this.heatmap.remove();\n    }\n\n    this.heatmap = d3.select(heatmapElem).append('svg').attr('width', this.width).attr('height', this.height);\n  }\n\n  addHeatmap() {\n    this.addHeatmapCanvas();\n    this.addAxes();\n\n    if (this.panel.yAxis.logBase !== 1 && this.panel.dataFormat !== 'tsbuckets') {\n      const logBase = this.panel.yAxis.logBase;\n      const domain = this.yScale.domain();\n      const tickValues = this.logScaleTickValues(domain, logBase);\n      this.data.buckets = mergeZeroBuckets(this.data.buckets, min(tickValues)!);\n    }\n\n    const cardsData = this.data.cards;\n    const cardStats = this.data.cardStats;\n    const maxValueAuto = cardStats.max;\n    const minValueAuto = Math.max(cardStats.min, 0);\n    const maxValue = isNil(this.panel.color.max) ? maxValueAuto : this.panel.color.max;\n    const minValue = isNil(this.panel.color.min) ? minValueAuto : this.panel.color.min;\n    const colorScheme: any = find(this.ctrl.colorSchemes, {\n      value: this.panel.color.colorScheme,\n    });\n    this.colorScale = getColorScale(colorScheme, contextSrv.user.lightTheme, maxValue, minValue);\n    this.opacityScale = getOpacityScale(this.panel.color, maxValue, minValue);\n    this.setCardSize();\n\n    let cards = this.heatmap.selectAll('.heatmap-card').data(cardsData);\n    cards.append('title');\n    cards = cards\n      .enter()\n      .append('rect')\n      .attr('x', this.getCardX.bind(this))\n      .attr('width', this.getCardWidth.bind(this))\n      .attr('y', this.getCardY.bind(this))\n      .attr('height', this.getCardHeight.bind(this))\n      .attr('rx', this.cardRound)\n      .attr('ry', this.cardRound)\n      .attr('class', 'bordered heatmap-card')\n      .style('fill', this.getCardColor.bind(this))\n      .style('stroke', this.getCardColor.bind(this))\n      .style('stroke-width', 0)\n      .style('opacity', this.getCardOpacity.bind(this));\n\n    const $cards = this.$heatmap.find('.heatmap-card');\n    $cards\n      .on('mouseenter', (event: any) => {\n        this.tooltip.mouseOverBucket = true;\n        this.highlightCard(event);\n      })\n      .on('mouseleave', (event: any) => {\n        this.tooltip.mouseOverBucket = false;\n        this.resetCardHighLight(event);\n      });\n  }\n\n  highlightCard(event: any) {\n    const color = d3.select(event.target).style('fill');\n    const highlightColor = d3.color(color)!.darker(2);\n    const strokeColor = d3.color(color)!.brighter(4);\n    const currentCard = d3.select(event.target);\n    this.tooltip.originalFillColor = color;\n    currentCard\n      .style('fill', highlightColor.toString())\n      .style('stroke', strokeColor.toString())\n      .style('stroke-width', 1);\n  }\n\n  resetCardHighLight(event: any) {\n    d3.select(event.target)\n      .style('fill', this.tooltip.originalFillColor)\n      .style('stroke', this.tooltip.originalFillColor)\n      .style('stroke-width', 0);\n  }\n\n  setCardSize() {\n    const xGridSize = Math.floor(this.xScale(this.data.xBucketSize) - this.xScale(0));\n    let yGridSize = Math.floor(this.yScale(this.yScale.invert(0) - this.data.yBucketSize));\n\n    if (this.panel.yAxis.logBase !== 1) {\n      const base = this.panel.yAxis.logBase;\n      const splitFactor = this.data.yBucketSize || 1;\n      yGridSize = Math.floor((this.yScale(1) - this.yScale(base)) / splitFactor);\n    }\n\n    const cardWidth = xGridSize - this.cardPadding * 2;\n    this.cardWidth = Math.max(cardWidth, MIN_CARD_SIZE);\n    this.cardHeight = yGridSize ? yGridSize - this.cardPadding * 2 : 0;\n  }\n\n  getCardX(d: { x: any }) {\n    let x;\n    if (this.xScale(d.x) < 0) {\n      // Cut card left to prevent overlay\n      x = this.yAxisWidth + this.cardPadding;\n    } else {\n      x = this.xScale(d.x) + this.yAxisWidth + this.cardPadding;\n    }\n\n    return x;\n  }\n\n  getCardWidth(d: { x: any }) {\n    let w = this.cardWidth;\n    if (this.xScale(d.x) < 0) {\n      // Cut card left to prevent overlay\n      w = this.xScale(d.x) + this.cardWidth;\n    } else if (this.xScale(d.x) + this.cardWidth > this.chartWidth) {\n      // Cut card right to prevent overlay\n      w = this.chartWidth - this.xScale(d.x) - this.cardPadding;\n    }\n\n    // Card width should be MIN_CARD_SIZE at least, but cut cards shouldn't be displayed\n    w = w > 0 ? Math.max(w, MIN_CARD_SIZE) : 0;\n    return w;\n  }\n\n  getCardY(d: { y: number }) {\n    let y = this.yScale(d.y) + this.chartTop - this.cardHeight - this.cardPadding;\n    if (this.panel.yAxis.logBase !== 1 && d.y === 0) {\n      y = this.chartBottom - this.cardHeight - this.cardPadding;\n    } else {\n      if (y < this.chartTop) {\n        y = this.chartTop;\n      }\n    }\n\n    return y;\n  }\n\n  getCardHeight(d: { y: number }) {\n    const y = this.yScale(d.y) + this.chartTop - this.cardHeight - this.cardPadding;\n    let h = this.cardHeight;\n\n    if (this.panel.yAxis.logBase !== 1 && d.y === 0) {\n      return this.cardHeight;\n    }\n\n    // Cut card height to prevent overlay\n    if (y < this.chartTop) {\n      h = this.yScale(d.y) - this.cardPadding;\n    } else if (this.yScale(d.y) > this.chartBottom) {\n      h = this.chartBottom - y;\n    } else if (y + this.cardHeight > this.chartBottom) {\n      h = this.chartBottom - y;\n    }\n\n    // Height can't be more than chart height\n    h = Math.min(h, this.chartHeight);\n    // Card height should be MIN_CARD_SIZE at least\n    h = Math.max(h, MIN_CARD_SIZE);\n\n    return h;\n  }\n\n  getCardColor(d: { count: any }) {\n    if (this.panel.color.mode === 'opacity') {\n      return config.theme.visualization.getColorByName(this.panel.color.cardColor);\n    } else {\n      return this.colorScale(d.count);\n    }\n  }\n\n  getCardOpacity(d: { count: any }) {\n    if (this.panel.color.mode === 'opacity') {\n      return this.opacityScale(d.count);\n    } else {\n      return 1;\n    }\n  }\n\n  getEventOffset(event: any) {\n    const elemOffset = this.$heatmap.offset();\n    const x = Math.floor(event.clientX - elemOffset.left);\n    const y = Math.floor(event.clientY - elemOffset.top);\n    return { x, y };\n  }\n\n  onMouseDown(event: any) {\n    const offset = this.getEventOffset(event);\n    this.selection.active = true;\n    this.selection.x1 = offset.x;\n\n    this.mouseUpHandler = () => {\n      this.onMouseUp();\n    };\n\n    $(document).one('mouseup', this.mouseUpHandler.bind(this));\n  }\n\n  onMouseUp() {\n    $(document).unbind('mouseup', this.mouseUpHandler.bind(this));\n    this.mouseUpHandler = null;\n    this.selection.active = false;\n\n    const selectionRange = Math.abs(this.selection.x2 - this.selection.x1);\n    if (this.selection.x2 >= 0 && selectionRange > MIN_SELECTION_WIDTH) {\n      const timeFrom = this.xScale.invert(Math.min(this.selection.x1, this.selection.x2) - this.yAxisWidth);\n      const timeTo = this.xScale.invert(Math.max(this.selection.x1, this.selection.x2) - this.yAxisWidth);\n\n      this.ctrl.timeSrv.setTime({\n        from: toUtc(timeFrom),\n        to: toUtc(timeTo),\n      });\n    }\n\n    this.clearSelection();\n  }\n\n  onMouseLeave() {\n    this.ctrl.dashboard.events.publish(new LegacyGraphHoverClearEvent());\n    this.clearCrosshair();\n  }\n\n  onMouseMove(event: any) {\n    if (!this.heatmap) {\n      return;\n    }\n\n    const offset = this.getEventOffset(event);\n    if (this.selection.active) {\n      // Clear crosshair and tooltip\n      this.clearCrosshair();\n      this.tooltip.destroy();\n\n      this.selection.x2 = this.limitSelection(offset.x);\n      this.drawSelection(this.selection.x1, this.selection.x2);\n    } else {\n      const pos = this.getEventPos(event, offset);\n      this.drawCrosshair(offset.x);\n      this.tooltip.show(pos, this.data);\n      this.emitGraphHoverEvent(pos);\n    }\n  }\n\n  getEventPos(event: { pageX: any; pageY: any }, offset: { x: any; y: any }) {\n    const x = this.xScale.invert(offset.x - this.yAxisWidth).valueOf();\n    const y = this.yScale.invert(offset.y - this.chartTop);\n    const pos: any = {\n      pageX: event.pageX,\n      pageY: event.pageY,\n      x: x,\n      x1: x,\n      y: y,\n      y1: y,\n      panelRelY: null,\n      offset,\n    };\n\n    return pos;\n  }\n\n  emitGraphHoverEvent(pos: { panelRelY: number; offset: { y: number } }) {\n    // Set minimum offset to prevent showing legend from another panel\n    pos.panelRelY = Math.max(pos.offset.y / this.height, 0.001);\n    // broadcast to other graph panels that we are hovering\n    this.hoverEvent.payload.pos = pos;\n    this.hoverEvent.payload.panel = this.panel;\n    this.hoverEvent.payload.point['time'] = (pos as any).x;\n    this.ctrl.dashboard.events.publish(this.hoverEvent);\n  }\n\n  limitSelection(x2: number) {\n    x2 = Math.max(x2, this.yAxisWidth);\n    x2 = Math.min(x2, this.chartWidth + this.yAxisWidth);\n    return x2;\n  }\n\n  drawSelection(posX1: number, posX2: number) {\n    if (this.heatmap) {\n      this.heatmap.selectAll('.heatmap-selection').remove();\n      const selectionX = Math.min(posX1, posX2);\n      const selectionWidth = Math.abs(posX1 - posX2);\n\n      if (selectionWidth > MIN_SELECTION_WIDTH) {\n        this.heatmap\n          .append('rect')\n          .attr('class', 'heatmap-selection')\n          .attr('x', selectionX)\n          .attr('width', selectionWidth)\n          .attr('y', this.chartTop)\n          .attr('height', this.chartHeight);\n      }\n    }\n  }\n\n  clearSelection() {\n    this.selection.x1 = -1;\n    this.selection.x2 = -1;\n\n    if (this.heatmap) {\n      this.heatmap.selectAll('.heatmap-selection').remove();\n    }\n  }\n\n  drawCrosshair(position: number) {\n    if (this.heatmap) {\n      this.heatmap.selectAll('.heatmap-crosshair').remove();\n\n      let posX = position;\n      posX = Math.max(posX, this.yAxisWidth);\n      posX = Math.min(posX, this.chartWidth + this.yAxisWidth);\n\n      this.heatmap\n        .append('g')\n        .attr('class', 'heatmap-crosshair')\n        .attr('transform', 'translate(' + posX + ',0)')\n        .append('line')\n        .attr('x1', 1)\n        .attr('y1', this.chartTop)\n        .attr('x2', 1)\n        .attr('y2', this.chartBottom)\n        .attr('stroke-width', 1);\n    }\n  }\n\n  drawSharedCrosshair(pos: { x: any }) {\n    if (this.heatmap && this.ctrl.dashboard.graphTooltip !== 0) {\n      const posX = this.xScale(pos.x) + this.yAxisWidth;\n      this.drawCrosshair(posX);\n    }\n  }\n\n  clearCrosshair() {\n    if (this.heatmap) {\n      this.heatmap.selectAll('.heatmap-crosshair').remove();\n    }\n  }\n\n  render() {\n    this.data = this.ctrl.data;\n    this.panel = this.ctrl.panel;\n    this.timeRange = this.ctrl.range;\n\n    if (!this.setElementHeight() || !this.data) {\n      return;\n    }\n\n    // Draw default axes and return if no data\n    if (isEmpty(this.data.buckets)) {\n      this.addHeatmapCanvas();\n      this.addAxes();\n      return;\n    }\n\n    this.addHeatmap();\n    this.scope.yAxisWidth = this.yAxisWidth;\n    this.scope.xAxisHeight = this.xAxisHeight;\n    this.scope.chartHeight = this.chartHeight;\n    this.scope.chartWidth = this.chartWidth;\n    this.scope.chartTop = this.chartTop;\n  }\n\n  private getPanelYAxisWidth(): number | null {\n    if (!this.panel.yAxis.width) {\n      return null;\n    }\n\n    return isNaN(this.panel.yAxis.width) ? null : parseInt(this.panel.yAxis.width, 10);\n  }\n}\n","import { auto } from 'angular';\nimport { defaultsDeep, includes, keys, map, reduce, min as _min, max as _max } from 'lodash';\n\nimport { LegacyResponseData, PanelEvents, DataFrame, rangeUtil } from '@grafana/data';\nimport appEvents from 'app/core/app_events';\nimport TimeSeries from 'app/core/time_series2';\nimport kbn from 'app/core/utils/kbn';\nimport { TimeSrv } from 'app/features/dashboard/services/TimeSrv';\nimport { getProcessedDataFrames } from 'app/features/query/state/runRequest';\nimport { TemplateSrv } from 'app/features/templating/template_srv';\nimport { MetricsPanelCtrl } from 'app/plugins/sdk';\nimport { ZoomOutEvent } from 'app/types/events';\n\nimport { DataProcessor } from '../graph/data_processor';\n\nimport { axesEditor } from './axes_editor';\nimport { heatmapDisplayEditor } from './display_editor';\nimport {\n  convertToHeatMap,\n  convertToCards,\n  histogramToHeatmap,\n  calculateBucketSize,\n  sortSeriesByLabel,\n} from './heatmap_data_converter';\nimport rendering from './rendering';\n\nconst X_BUCKET_NUMBER_DEFAULT = 30;\nconst Y_BUCKET_NUMBER_DEFAULT = 10;\n\nconst panelDefaults: any = {\n  heatmap: {},\n  cards: {\n    cardPadding: null,\n    cardRound: null,\n  },\n  color: {\n    mode: 'spectrum',\n    cardColor: '#b4ff00',\n    colorScale: 'sqrt',\n    exponent: 0.5,\n    colorScheme: 'interpolateOranges',\n  },\n  legend: {\n    show: false,\n  },\n  dataFormat: 'timeseries',\n  yBucketBound: 'auto',\n  reverseYBuckets: false,\n  xAxis: {\n    show: true,\n  },\n  yAxis: {\n    show: true,\n    format: 'short',\n    decimals: null,\n    logBase: 1,\n    splitFactor: null,\n    min: null,\n    max: null,\n  },\n  xBucketSize: null,\n  xBucketNumber: null,\n  yBucketSize: null,\n  yBucketNumber: null,\n  tooltip: {\n    show: true,\n    showHistogram: false,\n  },\n  highlightCards: true,\n  hideZeroBuckets: false,\n};\n\nconst colorModes = ['opacity', 'spectrum'];\nconst opacityScales = ['linear', 'sqrt'];\n\n// Schemes from d3-scale-chromatic\n// https://github.com/d3/d3-scale-chromatic\nconst colorSchemes = [\n  // Diverging\n  { name: 'Spectral', value: 'interpolateSpectral', invert: 'always' },\n  { name: 'RdYlGn', value: 'interpolateRdYlGn', invert: 'always' },\n\n  // Sequential (Single Hue)\n  { name: 'Blues', value: 'interpolateBlues', invert: 'dark' },\n  { name: 'Greens', value: 'interpolateGreens', invert: 'dark' },\n  { name: 'Greys', value: 'interpolateGreys', invert: 'dark' },\n  { name: 'Oranges', value: 'interpolateOranges', invert: 'dark' },\n  { name: 'Purples', value: 'interpolatePurples', invert: 'dark' },\n  { name: 'Reds', value: 'interpolateReds', invert: 'dark' },\n\n  // Sequential (Multi-Hue)\n  { name: 'Turbo', value: 'interpolateTurbo', invert: 'light' },\n  { name: 'Cividis', value: 'interpolateCividis', invert: 'light' },\n  { name: 'Viridis', value: 'interpolateViridis', invert: 'light' },\n  { name: 'Magma', value: 'interpolateMagma', invert: 'light' },\n  { name: 'Inferno', value: 'interpolateInferno', invert: 'light' },\n  { name: 'Plasma', value: 'interpolatePlasma', invert: 'light' },\n  { name: 'Warm', value: 'interpolateWarm', invert: 'light' },\n  { name: 'Cool', value: 'interpolateCool', invert: 'light' },\n  { name: 'Cubehelix', value: 'interpolateCubehelixDefault', invert: 'light' },\n  { name: 'BuGn', value: 'interpolateBuGn', invert: 'dark' },\n  { name: 'BuPu', value: 'interpolateBuPu', invert: 'dark' },\n  { name: 'GnBu', value: 'interpolateGnBu', invert: 'dark' },\n  { name: 'OrRd', value: 'interpolateOrRd', invert: 'dark' },\n  { name: 'PuBuGn', value: 'interpolatePuBuGn', invert: 'dark' },\n  { name: 'PuBu', value: 'interpolatePuBu', invert: 'dark' },\n  { name: 'PuRd', value: 'interpolatePuRd', invert: 'dark' },\n  { name: 'RdPu', value: 'interpolateRdPu', invert: 'dark' },\n  { name: 'YlGnBu', value: 'interpolateYlGnBu', invert: 'dark' },\n  { name: 'YlGn', value: 'interpolateYlGn', invert: 'dark' },\n  { name: 'YlOrBr', value: 'interpolateYlOrBr', invert: 'dark' },\n  { name: 'YlOrRd', value: 'interpolateYlOrRd', invert: 'dark' },\n];\n\nconst dsSupportHistogramSort = ['elasticsearch'];\n\nexport class HeatmapCtrl extends MetricsPanelCtrl {\n  static templateUrl = 'module.html';\n\n  opacityScales: any = [];\n  colorModes: any = [];\n  colorSchemes: any = [];\n  selectionActivated: boolean;\n  unitFormats: any;\n  data: any;\n  series: TimeSeries[] = [];\n  dataWarning: any;\n  decimals = 0;\n  scaledDecimals = 0;\n\n  processor: DataProcessor; // Shared with graph panel\n\n  /** @ngInject */\n  constructor($scope: any, $injector: auto.IInjectorService, templateSrv: TemplateSrv, timeSrv: TimeSrv) {\n    super($scope, $injector);\n\n    this.selectionActivated = false;\n\n    defaultsDeep(this.panel, panelDefaults);\n    this.opacityScales = opacityScales;\n    this.colorModes = colorModes;\n    this.colorSchemes = colorSchemes;\n\n    // Use DataFrames\n    this.useDataFrames = true;\n    this.processor = new DataProcessor({\n      xaxis: { mode: 'custom' }, // NOT: 'histogram' :)\n      aliasColors: {}, // avoids null reference\n    });\n\n    // Bind grafana panel events\n    this.events.on(PanelEvents.render, this.onRender.bind(this));\n    this.events.on(PanelEvents.dataFramesReceived, this.onDataFramesReceived.bind(this));\n    this.events.on(PanelEvents.dataSnapshotLoad, this.onSnapshotLoad.bind(this));\n    this.events.on(PanelEvents.editModeInitialized, this.onInitEditMode.bind(this));\n\n    this.onCardColorChange = this.onCardColorChange.bind(this);\n  }\n\n  onInitEditMode() {\n    this.addEditorTab('Axes', axesEditor, 2);\n    this.addEditorTab('Display', heatmapDisplayEditor, 3);\n    this.unitFormats = kbn.getUnitFormats();\n  }\n\n  zoomOut(evt: any) {\n    appEvents.publish(new ZoomOutEvent({ scale: 2 }));\n  }\n\n  onRender() {\n    if (this.panel.dataFormat === 'tsbuckets') {\n      this.convertHistogramToHeatmapData();\n    } else {\n      this.convertTimeSeriesToHeatmapData();\n    }\n  }\n\n  convertTimeSeriesToHeatmapData() {\n    if (!this.range || !this.series) {\n      return;\n    }\n\n    let xBucketSize, yBucketSize, bucketsData, heatmapStats;\n    const logBase = this.panel.yAxis.logBase;\n\n    const xBucketNumber = this.panel.xBucketNumber || X_BUCKET_NUMBER_DEFAULT;\n    const xBucketSizeByNumber = Math.floor((this.range.to.valueOf() - this.range.from.valueOf()) / xBucketNumber);\n\n    // Parse X bucket size (number or interval)\n    const isIntervalString = kbn.intervalRegex.test(this.panel.xBucketSize);\n    if (isIntervalString) {\n      xBucketSize = rangeUtil.intervalToMs(this.panel.xBucketSize);\n    } else if (\n      isNaN(Number(this.panel.xBucketSize)) ||\n      this.panel.xBucketSize === '' ||\n      this.panel.xBucketSize === null\n    ) {\n      xBucketSize = xBucketSizeByNumber;\n    } else {\n      xBucketSize = Number(this.panel.xBucketSize);\n    }\n\n    // Calculate Y bucket size\n    heatmapStats = this.parseSeries(this.series);\n    const yBucketNumber = this.panel.yBucketNumber || Y_BUCKET_NUMBER_DEFAULT;\n    if (logBase !== 1) {\n      yBucketSize = this.panel.yAxis.splitFactor;\n    } else {\n      if (heatmapStats.max === heatmapStats.min) {\n        if (heatmapStats.max) {\n          yBucketSize = heatmapStats.max / Y_BUCKET_NUMBER_DEFAULT;\n        } else {\n          yBucketSize = 1;\n        }\n      } else {\n        yBucketSize = (heatmapStats.max - heatmapStats.min) / yBucketNumber;\n      }\n      yBucketSize = this.panel.yBucketSize || yBucketSize;\n    }\n\n    bucketsData = convertToHeatMap(this.series, yBucketSize, xBucketSize, logBase);\n\n    // Set default Y range if no data\n    if (!heatmapStats.min && !heatmapStats.max) {\n      heatmapStats = { min: -1, max: 1, minLog: 1 };\n      yBucketSize = 1;\n    }\n\n    const { cards, cardStats } = convertToCards(bucketsData, this.panel.hideZeroBuckets);\n\n    this.data = {\n      buckets: bucketsData,\n      heatmapStats: heatmapStats,\n      xBucketSize: xBucketSize,\n      yBucketSize: yBucketSize,\n      cards: cards,\n      cardStats: cardStats,\n    };\n  }\n\n  convertHistogramToHeatmapData() {\n    if (!this.range || !this.series) {\n      return;\n    }\n\n    const panelDatasource = this.getPanelDataSourceType();\n    let xBucketSize, yBucketSize, bucketsData, tsBuckets;\n\n    // Try to sort series by bucket bound, if datasource doesn't do it.\n    if (!includes(dsSupportHistogramSort, panelDatasource)) {\n      this.series.sort(sortSeriesByLabel);\n    }\n\n    if (this.panel.reverseYBuckets) {\n      this.series.reverse();\n    }\n\n    // Convert histogram to heatmap. Each histogram bucket represented by the series which name is\n    // a top (or bottom, depends of datasource) bucket bound. Further, these values will be used as Y axis labels.\n    bucketsData = histogramToHeatmap(this.series);\n\n    tsBuckets = map(this.series, 'label');\n    const yBucketBound = this.panel.yBucketBound;\n    if (\n      (panelDatasource === 'prometheus' && yBucketBound !== 'lower' && yBucketBound !== 'middle') ||\n      yBucketBound === 'upper'\n    ) {\n      // Prometheus labels are upper inclusive bounds, so add empty bottom bucket label.\n      tsBuckets = [''].concat(tsBuckets);\n    } else {\n      // Elasticsearch uses labels as lower bucket bounds, so add empty top bucket label.\n      // Use this as a default mode as well.\n      tsBuckets.push('');\n    }\n\n    // Calculate bucket size based on heatmap data\n    const xBucketBoundSet = map(keys(bucketsData), (key) => Number(key));\n    xBucketSize = calculateBucketSize(xBucketBoundSet);\n    // Always let yBucketSize=1 in 'tsbuckets' mode\n    yBucketSize = 1;\n\n    const { cards, cardStats } = convertToCards(bucketsData, this.panel.hideZeroBuckets);\n\n    this.data = {\n      buckets: bucketsData,\n      xBucketSize: xBucketSize,\n      yBucketSize: yBucketSize,\n      tsBuckets: tsBuckets,\n      cards: cards,\n      cardStats: cardStats,\n    };\n  }\n\n  getPanelDataSourceType() {\n    if (this.datasource && this.datasource.meta && this.datasource.meta.id) {\n      return this.datasource.meta.id;\n    } else {\n      return 'unknown';\n    }\n  }\n\n  // This should only be called from the snapshot callback\n  onSnapshotLoad(dataList: LegacyResponseData[]) {\n    this.onDataFramesReceived(getProcessedDataFrames(dataList));\n  }\n\n  // Directly support DataFrame\n  onDataFramesReceived(data: DataFrame[]) {\n    this.series = this.processor.getSeriesList({ dataList: data, range: this.range }).map((ts) => {\n      ts.color = undefined; // remove whatever the processor set\n      ts.flotpairs = ts.getFlotPairs(this.panel.nullPointMode);\n      return ts;\n    });\n\n    this.dataWarning = null;\n    const datapointsCount = reduce(\n      this.series,\n      (sum, series) => {\n        return sum + series.datapoints.length;\n      },\n      0\n    );\n\n    if (datapointsCount === 0) {\n      this.dataWarning = {\n        title: 'No data points',\n        tip: 'No datapoints returned from data query',\n      };\n    } else {\n      for (const series of this.series) {\n        if (series.isOutsideRange) {\n          this.dataWarning = {\n            title: 'Data points outside time range',\n            tip: 'Can be caused by timezone mismatch or missing time filter in query',\n          };\n          break;\n        }\n      }\n    }\n\n    this.render();\n  }\n\n  onDataError() {\n    this.series = [];\n    this.render();\n  }\n\n  onCardColorChange(newColor: any) {\n    this.panel.color.cardColor = newColor;\n    this.render();\n  }\n\n  parseSeries(series: TimeSeries[]) {\n    const min = _min(map(series, (s) => s.stats.min));\n    const minLog = _min(map(series, (s) => s.stats.logmin));\n    const max = _max(map(series, (s) => s.stats.max));\n\n    return {\n      max,\n      min,\n      minLog,\n    };\n  }\n\n  parseHistogramSeries(series: TimeSeries[]) {\n    const bounds = map(series, (s) => Number(s.alias));\n    const min = _min(bounds);\n    const minLog = _min(bounds);\n    const max = _max(bounds);\n\n    return {\n      max: max,\n      min: min,\n      minLog: minLog,\n    };\n  }\n\n  link(scope: any, elem: any, attrs: any, ctrl: any) {\n    rendering(scope, elem, attrs, ctrl);\n  }\n}\n","import { makeClassES5Compatible } from '@grafana/data';\nimport { loadPluginCss } from '@grafana/runtime';\nimport { MetricsPanelCtrl as MetricsPanelCtrlES6 } from 'app/angular/panel/metrics_panel_ctrl';\nimport { PanelCtrl as PanelCtrlES6 } from 'app/angular/panel/panel_ctrl';\nimport { QueryCtrl as QueryCtrlES6 } from 'app/angular/panel/query_ctrl';\n\nconst PanelCtrl = makeClassES5Compatible(PanelCtrlES6);\nconst MetricsPanelCtrl = makeClassES5Compatible(MetricsPanelCtrlES6);\nconst QueryCtrl = makeClassES5Compatible(QueryCtrlES6);\n\nexport { PanelCtrl, MetricsPanelCtrl, QueryCtrl, loadPluginCss };\n"],"names":["QueryCtrl","constructor","$scope","$injector","this","panelCtrl","ctrl","target","datasource","panel","isLastQuery","indexOf","targets","length","refresh","getColorScale","colorScheme","lightTheme","maxValue","minValue","colorInterpolator","d3ScaleChromatic","value","colorScaleInverted","invert","start","end","d3","scaleSequential","domain","getOpacityScale","options","legendOpacityScale","colorScale","scaleLinear","range","scalePow","exponent","drawLegendValues","elem","rangeFrom","rangeTo","legendWidth","valuesRange","legendElem","$","find","legendDomElement","get","legend","select","childNodes","legendValueScale","ticks","tickStepSize","tickStep","ticksNum","Math","ceil","firstTick","step","floor","getFirstCloseTick","i","current","isValueCloseTo","push","sortBy","uniq","buildLegendTicks","xAxis","axisBottom","tickValues","tickSize","colorRect","posY","svgElem","height","baseVal","getSvgElemHeight","posX","x","getSvgElemX","append","attr","call","remove","clearLegend","empty","val","valueTo","abs","coreModule","restrict","template","link","scope","attrs","render","outerWidth","color","mode","colorSchemes","contextSrv","legendHeight","valuesNumber","rangeStep","selectAll","data","enter","d","drawSimpleColorLegend","colorOptions","config","cardColor","style","drawSimpleOpacityLegend","events","on","PanelEvents","isEmpty","cards","cardStats","isNil","min","max","widthFactor","round","drawColorLegend","opacityScale","drawOpacityLegend","AxesEditorCtrl","uiSegmentSrv","unit","yAxis","format","editor","logScales","linear","dataFormats","yBucketBoundModes","Auto","Upper","Lower","Middle","axesEditor","templateUrl","controller","HeatmapDisplayEditorCtrl","heatmapDisplayEditor","sortSeriesByLabel","s1","s2","label1","label2","parseHistogramLabel","label","err","console","error","message","Infinity","Number","isNaN","Error","convertToCards","buckets","hideZero","forEach","xBucket","yBucket","card","y","yBounds","bounds","values","count","pushToXBuckets","point","bucketNum","seriesName","pointExt","concat","points","pushToYBuckets","parseInt","getValueBucketBound","yBucketSize","logBase","getBucketBound","yBucketSplitFactor","getLogScaleBucketBounds","bottom","getLogScaleBucketBound","getBucketBounds","bucketSize","top","convertToValueBuckets","index","valueLog","logp","pow","powTop","additionalBucketSize","additionalLog","convertToLogScaleValueBuckets","base","log","getDistance","a","b","HISTOGRAM_WIDTH","HeatmapTooltip","dashboard","heatmapPanel","mouseOverBucket","originalFillColor","onMouseLeave","bind","destroy","onMouseMove","e","tooltip","show","move","add","pos","panelRelY","xBucketIndex","yBucketIndex","getBucketIndexes","boundBottom","boundTop","xData","yData","bucket","bucketIndex","toString","time","formatDate","countValueFormatter","bucketBoundFormatter","isNumber","tooltipDecimals","tickValueFormatter","decimals","scaledDecimals","tooltipHtml","tsBuckets","tickFormatter","valIndex","tsBucketsFormatted","yBucketBound","showHistogram","html","addHistogram","getXBucketIndex","getYBucketIndex","xBucketSize","getSharedTooltipPos","pageX","offset","left","xScale","pageY","chartHeight","histogramData","map","undefined","filter","histXScale","yScale","copy","barWidth","barNumberFactor","histogramDomain","reduce","sum","histYScale","node","tooltipWidth","clientWidth","tooltipHeight","clientHeight","window","innerWidth","pageYOffset","innerHeight","fmt","getValueFormat","formattedValueToString","HeatmapRenderer","$heatmap","selection","active","x1","x2","padding","right","margin","dataRangeWidingFactor","onRender","LegacyGraphHoverEvent","onGraphHover","LegacyGraphHoverClearEvent","onGraphHoverClear","onMouseDown","hoverEvent","clearCrosshair","event","drawSharedCrosshair","renderingCompleted","setElementHeight","row","isString","replace","css","getYAxisWidth","panelYAxisWidth","getPanelYAxisWidth","axisText","nodes","text","getBBox","width","getXAxisHeight","axisLinePosition","parseFloat","addXAxis","timeRange","from","to","chartWidth","graphTimeFormat","valueOf","timeZone","getTimezone","tickFormat","date","dateTimeFormat","tickPadding","yAxisWidth","heatmap","addYAxis","tickInterval","ticksUtils","heatmapStats","yMin","yMax","wideYAxisRange","decimalsAuto","flotTickSize","tickSizeInner","tickSizeOuter","yWiding","addLogYAxis","adjustLogRange","minLog","adjustLogMin","adjustLogMax","logScaleTickValues","addYAxisFromBuckets","valueFormatted","toNumber","scale","trimmed","substring","v","tickShift","domainMin","domainMax","tickValue","fixYAxisTickSize","addAxes","chartTop","chartBottom","dataFormat","xAxisHeight","addHeatmapCanvas","heatmapElem","cardPadding","cardRound","addHeatmap","yBuckets","emptyBucket","nullBucket","minBucket","newBucket","mergeZeroBuckets","cardsData","maxValueAuto","minValueAuto","setCardSize","getCardX","getCardWidth","getCardY","getCardHeight","getCardColor","getCardOpacity","highlightCard","resetCardHighLight","highlightColor","darker","strokeColor","brighter","curre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