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import { ComparisonLineConfig } from "../scatterCharts/ComparisonLine"
import { observable, computed, action } from "mobx"
import {
intersection,
without,
uniq,
last,
excludeUndefined,
flatten,
isEmpty,
isNumber,
domainExtent,
lowerCaseFirstLetterUnlessAbbreviation,
relativeMinAndMax,
exposeInstanceOnWindow,
groupBy,
sampleFrom,
intersectionOfSets,
} from "../../clientUtils/Util"
import { observer } from "mobx-react"
import { Bounds, DEFAULT_BOUNDS } from "../../clientUtils/Bounds"
import { NoDataModal } from "../noDataModal/NoDataModal"
import {
BASE_FONT_SIZE,
ScaleType,
EntitySelectionMode,
ScatterPointLabelStrategy,
SeriesName,
} from "../core/GrapherConstants"
import { Color } from "../../coreTable/CoreTableConstants"
import {
ConnectedScatterLegend,
ConnectedScatterLegendManager,
} from "./ConnectedScatterLegend"
import {
VerticalColorLegend,
VerticalColorLegendManager,
} from "../verticalColorLegend/VerticalColorLegend"
import { DualAxisComponent } from "../axis/AxisViews"
import { DualAxis, HorizontalAxis, VerticalAxis } from "../axis/Axis"
import { ComparisonLine } from "./ComparisonLine"
import { ColorScale, ColorScaleManager } from "../color/ColorScale"
import { AxisConfig } from "../axis/AxisConfig"
import { ChartInterface } from "../chart/ChartInterface"
import {
ScatterPlotManager,
ScatterSeries,
SeriesPoint,
} from "./ScatterPlotChartConstants"
import { ScatterTooltip } from "./ScatterTooltip"
import { ScatterPointsWithLabels } from "./ScatterPointsWithLabels"
import {
EntityName,
OwidRow,
OwidTableSlugs,
} from "../../coreTable/OwidTableConstants"
import { OwidTable } from "../../coreTable/OwidTable"
import { autoDetectYColumnSlugs, makeSelectionArray } from "../chart/ChartUtils"
import { ColorSchemeName } from "../color/ColorConstants"
import {
defaultIfErrorValue,
isNotErrorValue,
} from "../../coreTable/ErrorValues"
import {
ColorScaleConfig,
ColorScaleConfigDefaults,
} from "../color/ColorScaleConfig"
import { SelectionArray } from "../selection/SelectionArray"
import { CoreColumn } from "../../coreTable/CoreTableColumns"
import { ColorScaleBin } from "../color/ColorScaleBin"
@observer
export class ScatterPlotChart
extends React.Component<{
bounds?: Bounds
manager: ScatterPlotManager
}>
implements
ConnectedScatterLegendManager,
ChartInterface,
VerticalColorLegendManager,
ColorScaleManager
{
// currently hovered individual series key
@observable private hoveredSeries?: SeriesName
// currently hovered legend color
@observable private hoverColor?: Color
transformTable(table: OwidTable): OwidTable {
const { backgroundSeriesLimit, excludedEntities, addCountryMode } =
this.manager
if (
addCountryMode === EntitySelectionMode.Disabled ||
addCountryMode === EntitySelectionMode.SingleEntity
) {
table = table.filterByEntityNames(
this.selectionArray.selectedEntityNames
)
}
if (excludedEntities) {
const excludedEntityIdsSet = new Set(excludedEntities)
table = table.columnFilter(
OwidTableSlugs.entityId,
(entityId) => !excludedEntityIdsSet.has(entityId as number),
`Excluded entity ids specified by author: ${excludedEntities.join(
", "
)}`
)
}
// Allow authors to limit the # of background entities to get better perf and clearer charts.
if (backgroundSeriesLimit) {
const selectedSeriesNames = new Set<SeriesName>(
this.selectionArray.selectedEntityNames
)
// Todo: implement a better strategy for picking the entities to show for context. Maybe a couple per decile?
const backgroundSeriesNames = new Set<SeriesName>(
sampleFrom(
table.availableEntityNames.filter(
(name) => !selectedSeriesNames.has(name)
),
backgroundSeriesLimit,
123
)
)
table = table.columnFilter(
table.entityNameSlug,
(name) =>
selectedSeriesNames.has(name as string) ||
backgroundSeriesNames.has(name as string),
`Capped background series at ${backgroundSeriesLimit}`
)
}
if (this.xScaleType === ScaleType.log && this.xColumnSlug)
table = table.replaceNonPositiveCellsForLogScale([this.xColumnSlug])
if (this.yScaleType === ScaleType.log && this.yColumnSlug)
table = table.replaceNonPositiveCellsForLogScale([this.yColumnSlug])
if (this.sizeColumnSlug) {
// The tolerance on the size column is ignored. If we want to change this in the future
// we need to check all charts for regressions.
table = table.interpolateColumnWithTolerance(
this.sizeColumnSlug,
Infinity
)
}
if (this.colorColumnSlug) {
const tolerance =
table.get(this.colorColumnSlug)?.display?.tolerance ?? Infinity
table = table.interpolateColumnWithTolerance(
this.colorColumnSlug,
tolerance
)
if (this.manager.matchingEntitiesOnly) {
table = table.dropRowsWithErrorValuesForColumn(
this.colorColumnSlug
)
}
}
// We want to "chop off" any rows outside the time domain for X and Y to avoid creating
// leading and trailing timeline times that don't really exist in the dataset.
const [timeDomainStart, timeDomainEnd] = table.timeDomainFor([
this.xColumnSlug,
this.yColumnSlug,
])
table = table.filterByTimeRange(
timeDomainStart ?? -Infinity,
timeDomainEnd ?? Infinity
)
if (this.xOverrideTime !== undefined) {
table = table.interpolateColumnWithTolerance(this.yColumnSlug)
} else {
table = table.interpolateColumnsByClosestTimeMatch(
this.xColumnSlug,
this.yColumnSlug
)
}
// Drop any rows which have non-number values for X or Y.
// This needs to be done after the tolerance, because the tolerance may fill in some gaps.
table = table
.columnFilter(
this.xColumnSlug,
isNumber,
"Drop rows with non-number values in X column"
)
.columnFilter(
this.yColumnSlug,
isNumber,
"Drop rows with non-number values in Y column"
)
// The tolerance application might lead to some data being dropped for some years.
// For example, if X times are [2000, 2005, 2010], and Y times are [2005], then for all 3
// rows we have the same match [[2005, 2005], [2005, 2005], [2005, 2005]].
// This means we can drop 2000 and 2010 from the timeline.
// It might not make a huge difference here, but it makes a difference when there are more
// entities covering different time periods.
const [originalTimeDomainStart, originalTimeDomainEnd] =
table.originalTimeDomainFor([this.xColumnSlug, this.yColumnSlug])
table = table.filterByTimeRange(
originalTimeDomainStart ?? -Infinity,
originalTimeDomainEnd ?? Infinity
)
return table
}
@computed get inputTable(): OwidTable {
return this.manager.table
}
@computed private get transformedTableFromGrapher(): OwidTable {
return (
this.manager.transformedTable ??
this.transformTable(this.inputTable)
)
}
// TODO chunk this up into multiple computeds for better performance?
@computed get transformedTable(): OwidTable {
let table = this.transformedTableFromGrapher
if (
this.manager.hideLinesOutsideTolerance &&
this.manager.startTime !== undefined &&
this.manager.endTime !== undefined
) {
const entityNames = Array.from(
intersectionOfSets(
[this.manager.startTime, this.manager.endTime].map(
(targetTime) =>
table.filterByTargetTimes([targetTime], 0)
.availableEntityNameSet
)
)
)
table = table.filterByEntityNames(entityNames)
}
// We don't want to apply this transform when relative mode is also enabled, it has a
// sligthly different endpoints logic that drops initial zeroes to avoid DivideByZero error.
if (this.compareEndPointsOnly && !this.manager.isRelativeMode) {
table = table.keepMinTimeAndMaxTimeForEachEntityOnly()
}
if (this.manager.isRelativeMode) {
table = table.toAverageAnnualChangeForEachEntity([
this.xColumnSlug,
this.yColumnSlug,
])
}
return table
}
@computed private get manager(): ScatterPlotManager {
return this.props.manager
}
@computed.struct private get bounds(): Bounds {
return this.props.bounds ?? DEFAULT_BOUNDS
}
@computed private get canAddCountry(): boolean {
const { addCountryMode } = this.manager
return (addCountryMode &&
addCountryMode !== EntitySelectionMode.Disabled) as boolean
}
@computed private get selectionArray(): SelectionArray {
return makeSelectionArray(this.manager)
}
@action.bound private onSelectEntity(entityName: SeriesName): void {
if (this.canAddCountry) this.selectionArray.toggleSelection(entityName)
}
// Returns the colors that are used by all points, *across the whole timeline*.
// This is why we need the table before the timeline filter is applied.
@computed private get colorsInUse(): Color[] {
const allValues =
this.manager.tableAfterAuthorTimelineAndActiveChartTransformAndPopulationFilter?.get(
this.colorColumnSlug
)?.valuesIncludingErrorValues ?? []
// Need to convert InvalidCell to undefined for color scale to assign correct color
const colorValues = uniq(
allValues.map((value) =>
isNotErrorValue(value) ? value : undefined
)
) as (string | number)[]
return excludeUndefined(
colorValues.map((colorValue) =>
this.colorScale.getColor(colorValue)
)
)
}
@computed get fontSize(): number {
return this.manager.baseFontSize ?? BASE_FONT_SIZE
}
@action.bound onLegendMouseOver(color: string): void {
this.hoverColor = color
}
@action.bound onLegendMouseLeave(): void {
this.hoverColor = undefined
}
// When the color legend is clicked, toggle selection fo all associated keys
@action.bound onLegendClick(): void {
const { hoverColor, selectionArray } = this
if (!this.canAddCountry || hoverColor === undefined) return
const keysToToggle = this.series
.filter((g) => g.color === hoverColor)
.map((g) => g.seriesName)
const allKeysActive =
intersection(keysToToggle, this.selectedEntityNames).length ===
keysToToggle.length
if (allKeysActive)
selectionArray.setSelectedEntities(
without(this.selectedEntityNames, ...keysToToggle)
)
else
selectionArray.setSelectedEntities(
uniq(this.selectedEntityNames.concat(keysToToggle))
)
}
// Colors on the legend for which every matching series is focused
@computed get focusColors(): string[] {
const { colorsInUse } = this
return colorsInUse.filter((color) => {
const matchingKeys = this.series
.filter((g) => g.color === color)
.map((g) => g.seriesName)
return (
intersection(matchingKeys, this.selectedEntityNames).length ===
matchingKeys.length
)
})
}
// All currently hovered series keys, combining the legend and the main UI
@computed private get hoveredSeriesNames(): string[] {
const { hoverColor, hoveredSeries } = this
const hoveredSeriesNames =
hoverColor === undefined
? []
: uniq(
this.series
.filter((g) => g.color === hoverColor)
.map((g) => g.seriesName)
)
if (hoveredSeries !== undefined) hoveredSeriesNames.push(hoveredSeries)
return hoveredSeriesNames
}
@computed private get focusedEntityNames(): string[] {
return this.selectedEntityNames
}
@computed private get selectedEntityNames(): string[] {
return this.selectionArray.selectedEntityNames
}
@computed get displayStartTime(): string {
return this.transformedTable.timeColumnFormatFunction(
this.transformedTable.minTime ?? 1900
)
}
@computed get displayEndTime(): string {
return this.transformedTable.timeColumnFormatFunction(
this.transformedTable.maxTime ?? 2000
)
}
@computed private get arrowLegend(): ConnectedScatterLegend | undefined {
if (
this.displayStartTime === this.displayEndTime ||
this.manager.isRelativeMode
)
return undefined
return new ConnectedScatterLegend(this)
}
@action.bound private onScatterMouseOver(series: ScatterSeries): void {
this.hoveredSeries = series.seriesName
}
@action.bound private onScatterMouseLeave(): void {
this.hoveredSeries = undefined
}
@action.bound private onScatterClick(): void {
if (this.hoveredSeries) this.onSelectEntity(this.hoveredSeries)
}
@computed private get tooltipSeries(): ScatterSeries | undefined {
const { hoveredSeries, focusedEntityNames } = this
if (hoveredSeries !== undefined)
return this.series.find((g) => g.seriesName === hoveredSeries)
if (focusedEntityNames && focusedEntityNames.length === 1)
return this.series.find(
(g) => g.seriesName === focusedEntityNames[0]
)
return undefined
}
@computed private get legendDimensions(): VerticalColorLegend {
return new VerticalColorLegend({ manager: this })
}
@computed get maxLegendWidth(): number {
return this.sidebarMaxWidth
}
@computed private get sidebarMinWidth(): number {
return Math.max(this.bounds.width * 0.1, 60)
}
@computed private get sidebarMaxWidth(): number {
return Math.max(this.bounds.width * 0.2, this.sidebarMinWidth)
}
@computed.struct get sidebarWidth(): number {
const { legendDimensions, sidebarMinWidth, sidebarMaxWidth } = this
return Math.max(
Math.min(legendDimensions.width, sidebarMaxWidth),
sidebarMinWidth
)
}
// todo: Refactor
@computed get dualAxis(): DualAxis {
const { horizontalAxisPart, verticalAxisPart } = this
return new DualAxis({
bounds: this.bounds.padRight(this.sidebarWidth + 20),
horizontalAxis: horizontalAxisPart,
verticalAxis: verticalAxisPart,
})
}
@computed get yAxis(): VerticalAxis {
return this.dualAxis.verticalAxis
}
@computed get xAxis(): HorizontalAxis {
return this.dualAxis.horizontalAxis
}
@computed private get comparisonLines():
| ComparisonLineConfig[]
| undefined {
return this.manager.comparisonLines
}
@action.bound private onToggleEndpoints(): void {
this.manager.compareEndPointsOnly =
!this.compareEndPointsOnly || undefined
}
// Colors currently on the chart and not greyed out
@computed get activeColors(): string[] {
const { hoveredSeriesNames, focusedEntityNames } = this
const activeKeys = hoveredSeriesNames.concat(focusedEntityNames)
let series = this.series
if (activeKeys.length)
series = series.filter((g) => activeKeys.includes(g.seriesName))
const colorValues = uniq(
flatten(series.map((s) => s.points.map((p) => p.color)))
)
return excludeUndefined(
colorValues.map((color) => this.colorScale.getColor(color))
)
}
@computed private get hideConnectedScatterLines(): boolean {
return !!this.manager.hideConnectedScatterLines
}
@computed private get points(): JSX.Element {
const {
dualAxis,
focusedEntityNames,
hoveredSeriesNames,
hideConnectedScatterLines,
manager,
series,
sizeDomain,
colorScale,
colorColumn,
} = this
return (
<ScatterPointsWithLabels
noDataModalManager={manager}
hideConnectedScatterLines={hideConnectedScatterLines}
seriesArray={series}
dualAxis={dualAxis}
colorScale={!colorColumn.isMissing ? colorScale : undefined}
sizeDomain={sizeDomain}
focusedSeriesNames={focusedEntityNames}
hoveredSeriesNames={hoveredSeriesNames}
onMouseOver={this.onScatterMouseOver}
onMouseLeave={this.onScatterMouseLeave}
onClick={this.onScatterClick}
/>
)
}
@computed private get colorColumnSlug(): string | undefined {
return this.manager.colorColumnSlug
}
@computed private get colorColumn(): CoreColumn {
return this.transformedTable.get(this.colorColumnSlug)
}
@computed get legendItems(): ColorScaleBin[] {
return this.colorScale.legendBins.filter((bin) =>
this.colorsInUse.includes(bin.color)
)
}
@computed get title(): string | undefined {
return this.colorScale.legendDescription
}
componentDidMount(): void {
exposeInstanceOnWindow(this)
}
render(): JSX.Element {
if (this.failMessage)
return (
<NoDataModal
manager={this.manager}
bounds={this.bounds}
message={this.failMessage}
/>
)
const {
bounds,
dualAxis,
arrowLegend,
sidebarWidth,
tooltipSeries,
comparisonLines,
legendDimensions,
} = this
return (
<g className="ScatterPlot">
<DualAxisComponent dualAxis={dualAxis} showTickMarks={false} />
{comparisonLines &&
comparisonLines.map((line, i) => (
<ComparisonLine
key={i}
dualAxis={dualAxis}
comparisonLine={line}
/>
))}
{this.points}
<VerticalColorLegend manager={this} />
{(arrowLegend || tooltipSeries) && (
<line
x1={bounds.right - sidebarWidth}
y1={bounds.top + legendDimensions.height + 2}
x2={bounds.right - 5}
y2={bounds.top + legendDimensions.height + 2}
stroke="#ccc"
/>
)}
{arrowLegend && (
<g className="clickable" onClick={this.onToggleEndpoints}>
{arrowLegend.render(
bounds.right - sidebarWidth,
bounds.top + legendDimensions.height + 11
)}
</g>
)}
{tooltipSeries && (
<ScatterTooltip
yColumn={this.yColumn!}
xColumn={this.xColumn!}
series={tooltipSeries}
maxWidth={sidebarWidth}
fontSize={this.fontSize}
x={bounds.right - sidebarWidth}
y={
bounds.top +
legendDimensions.height +
11 +
(arrowLegend ? arrowLegend.height + 10 : 0)
}
/>
)}
</g>
)
}
@computed get legendY(): number {
return this.bounds.top
}
@computed get legendX(): number {
return this.bounds.right - this.sidebarWidth
}
colorScale = new ColorScale(this)
@computed get colorScaleColumn(): CoreColumn {
// We need to use inputTable in order to get consistent coloring for a variable across
// charts, e.g. each continent being assigned to the same color.
// inputTable is unfiltered, so it contains every value that exists in the variable.
return this.inputTable.get(this.colorColumnSlug)
}
@computed get colorScaleConfig(): ColorScaleConfigDefaults | undefined {
return (
ColorScaleConfig.fromDSL(this.colorColumn.def) ??
this.manager.colorScale
)
}
defaultBaseColorScheme = ColorSchemeName.continents
defaultNoDataColor = "#959595"
@computed get hasNoDataBin(): boolean {
if (this.colorColumn.isMissing) return false
return this.colorColumn.valuesIncludingErrorValues.some(
(value) => !isNotErrorValue(value)
)
}
@computed private get yAxisConfig(): AxisConfig {
return new AxisConfig(this.manager.yAxisConfig, this)
}
@computed private get xAxisConfig(): AxisConfig {
return new AxisConfig(this.manager.xAxisConfig, this)
}
@computed private get yColumnSlug(): string {
return autoDetectYColumnSlugs(this.manager)[0]
}
@computed private get yColumn(): CoreColumn {
return this.transformedTable.get(this.yColumnSlug)
}
@computed private get xColumnSlug(): string {
const { xColumnSlug } = this.manager
return xColumnSlug ?? this.manager.table.timeColumn.slug
}
@computed private get xColumn(): CoreColumn {
return this.transformedTable.get(this.xColumnSlug)
}
@computed private get sizeColumnSlug(): string | undefined {
return this.manager.sizeColumnSlug
}
@computed private get sizeColumn(): CoreColumn {
return this.transformedTable.get(this.sizeColumnSlug)
}
@computed get failMessage(): string {
if (this.yColumn.isMissing) return "Missing Y axis variable"
if (this.yColumn.isMissing) return "Missing X axis variable"
if (isEmpty(this.allEntityNamesWithXAndY)) {
if (
this.manager.isRelativeMode &&
this.manager.hasTimeline &&
this.manager.startTime === this.manager.endTime
) {
return "Please select a start and end point on the timeline below"
}
return "No entities with data for both X and Y"
}
if (isEmpty(this.series)) return "No matching data"
return ""
}
// todo: remove this. Should be done as a simple column transform at the data level.
// Possible to override the x axis dimension to target a special year
// In case you want to graph say, education in the past and democracy today https://ourworldindata.org/grapher/correlation-between-education-and-democracy
@computed get xOverrideTime(): number | undefined {
return this.manager.xOverrideTime
}
// Unlike other charts, the scatterplot shows all available data by default, and the selection
// is just for emphasis. But this behavior can be disabled.
@computed private get hideBackgroundEntities(): boolean {
return this.manager.addCountryMode === EntitySelectionMode.Disabled
}
@computed private get allEntityNamesWithXAndY(): EntityName[] {
return intersection(
this.yColumn.uniqEntityNames,
this.xColumn.uniqEntityNames
)
}
// todo: remove. do this at table filter level
getSeriesNamesToShow(
filterBackgroundEntities = this.hideBackgroundEntities
): Set<SeriesName> {
const seriesNames = filterBackgroundEntities
? this.selectionArray.selectedEntityNames
: this.allEntityNamesWithXAndY
if (this.manager.matchingEntitiesOnly && !this.colorColumn.isMissing)
return new Set(
intersection(seriesNames, this.colorColumn.uniqEntityNames)
)
return new Set(seriesNames)
}
@computed get compareEndPointsOnly(): boolean {
return !!this.manager.compareEndPointsOnly
}
@computed get allPoints(): SeriesPoint[] {
return flatten(this.series.map((series) => series.points))
}
// domains across the entire timeline
private domainDefault(property: "x" | "y"): [number, number] {
const scaleType = property === "x" ? this.xScaleType : this.yScaleType
if (!this.manager.useTimelineDomains) {
return domainExtent(
this.pointsForAxisDomains.map((point) => point[property]),
scaleType,
this.manager.zoomToSelection && this.selectedPoints.length
? 1.1
: 1
)
}
if (this.manager.isRelativeMode)
return relativeMinAndMax(this.allPoints, property)
return domainExtent(
this.allPoints.map((v) => v[property]),
scaleType
)
}
@computed private get xDomainDefault(): [number, number] {
return this.domainDefault("x")
}
@computed private get selectedPoints(): SeriesPoint[] {
const seriesNamesSet = this.getSeriesNamesToShow(true)
return this.allPoints.filter(
(point) => point.entityName && seriesNamesSet.has(point.entityName)
)
}
@computed private get pointsForAxisDomains(): SeriesPoint[] {
if (
!this.selectionArray.numSelectedEntities ||
!this.manager.zoomToSelection
)
return this.allPoints
return this.selectedPoints.length ? this.selectedPoints : this.allPoints
}
@computed private get sizeDomain(): [number, number] {
if (this.sizeColumn.isMissing) return [1, 100]
const sizeValues = this.transformedTable
.get(this.sizeColumn.slug)
.values.filter(isNumber)
return domainExtent(sizeValues, ScaleType.linear)
}
@computed private get yScaleType(): ScaleType {
return this.manager.isRelativeMode
? ScaleType.linear
: this.yAxisConfig.scaleType || ScaleType.linear
}
@computed private get yDomainDefault(): [number, number] {
return this.domainDefault("y")
}
@computed private get verticalAxisPart(): VerticalAxis {
const { manager, yDomainDefault } = this
const axisConfig = this.yAxisConfig
const axis = axisConfig.toVerticalAxis()
axis.formatColumn = this.yColumn
const label = axisConfig.label || this.yColumn?.displayName || ""
axis.scaleType = this.yScaleType
if (manager.isRelativeMode) {
axis.domain = yDomainDefault // Overwrite user's min/max
if (label && label.length > 1) {
axis.label = `Average annual change in ${lowerCaseFirstLetterUnlessAbbreviation(
label
)}`
}
} else {
axis.updateDomainPreservingUserSettings(yDomainDefault)
axis.label = label
}
return axis
}
@computed private get xScaleType(): ScaleType {
return this.manager.isRelativeMode
? ScaleType.linear
: this.xAxisConfig.scaleType ?? ScaleType.linear
}
@computed private get xAxisLabelBase(): string {
const xDimName = this.xColumn?.displayName
if (this.xOverrideTime !== undefined)
return `${xDimName} in ${this.xOverrideTime}`
return xDimName
}
@computed private get horizontalAxisPart(): HorizontalAxis {
const { xDomainDefault, manager, xAxisLabelBase } = this
const { xAxisConfig } = this
const axis = xAxisConfig.toHorizontalAxis()
axis.formatColumn = this.xColumn
axis.scaleType = this.xScaleType
if (manager.isRelativeMode) {
axis.domain = xDomainDefault // Overwrite user's min/max
const label = xAxisConfig.label || xAxisLabelBase
if (label && label.length > 1) {
axis.label = `Average annual change in ${lowerCaseFirstLetterUnlessAbbreviation(
label
)}`
}
} else {
axis.updateDomainPreservingUserSettings(xDomainDefault)
const label = xAxisConfig.label || xAxisLabelBase
if (label) axis.label = label
}
return axis
}
getPointLabel(row: OwidRow): string | undefined {
const strat = this.manager.scatterPointLabelStrategy
let label
if (strat === ScatterPointLabelStrategy.y) {
label = this.yColumn?.formatValue(row[this.yColumnSlug])
} else if (strat === ScatterPointLabelStrategy.x) {
label = this.xColumn?.formatValue(row[this.xColumnSlug])
} else {
label = this.transformedTable.timeColumnFormatFunction(
row[this.transformedTable.timeColumn.slug]
)
}
return label
}
private removePointsOutsidePlane(points: SeriesPoint[]): SeriesPoint[] {
const { yAxisConfig, xAxisConfig } = this
if (
yAxisConfig.removePointsOutsideDomain ||
xAxisConfig.removePointsOutsideDomain
) {
return points.filter((point) => {
return (
!xAxisConfig.shouldRemovePoint(point.x) &&
!yAxisConfig.shouldRemovePoint(point.y)
)
})
}
return points
}
@computed private get allPointsBeforeEndpointsFilter(): SeriesPoint[] {
const { entityNameSlug, timeColumn } = this.transformedTable
// We are running this filter first because it only depends on author-specified config, not
// on any user interaction.
return this.removePointsOutsidePlane(
this.transformedTable.rows.map((row) => {
return {
x: row[this.xColumnSlug],
y: row[this.yColumnSlug],
size: defaultIfErrorValue(row[this.sizeColumn.slug], 0),
color: defaultIfErrorValue(
row[this.colorColumn.slug],
undefined
),
entityName: row[entityNameSlug],
label: this.getPointLabel(row) ?? "",
timeValue: row[timeColumn.slug],
time: {
x: row[this.xColumn!.originalTimeColumnSlug!],
y: row[this.yColumn!.originalTimeColumnSlug!],
},
}
})
)
}
@computed get series(): ScatterSeries[] {
return Object.entries(
groupBy(this.allPointsBeforeEndpointsFilter, (p) => p.entityName)
).map(([entityName, points]) => {
const series: ScatterSeries = {
seriesName: entityName,
label: entityName,
color: "#932834", // Default color, used when no color dimension is present
size: this.getSizeFromPoints(points),
points,
}
this.assignColorToSeries(entityName, series)
return series
})
}
private assignColorToSeries(
entityName: EntityName,
series: ScatterSeries
): void {
if (series.points.length) {
const keyColor =
this.transformedTable.getColorForEntityName(entityName)
if (keyColor !== undefined) series.color = keyColor
else if (!this.colorColumn.isMissing) {
const colorValue = last(
series.points.map((point) => point.color)
)
const color = this.colorScale.getColor(colorValue)
if (color !== undefined) {
series.color = color
series.isScaleColor = true
}
}
}
}
private getSizeFromPoints(points: SeriesPoint[]): number {
const size = last(points.map((v) => v.size).filter(isNumber))
return size ?? 0
}
}
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