import * as BaseView from 'app/client/components/BaseView'; import {GristDoc} from 'app/client/components/GristDoc'; import {sortByXValues, splitValuesByIndex, uniqXValues} from 'app/client/lib/chartUtil'; import {Delay} from 'app/client/lib/Delay'; import {Disposable} from 'app/client/lib/dispose'; import {fromKoSave} from 'app/client/lib/fromKoSave'; import {loadPlotly, PlotlyType} from 'app/client/lib/imports'; import * as DataTableModel from 'app/client/models/DataTableModel'; import {ViewFieldRec, ViewSectionRec} from 'app/client/models/DocModel'; import {reportError} from 'app/client/models/errors'; import {KoSaveableObservable, ObjObservable} from 'app/client/models/modelUtil'; import {SortedRowSet} from 'app/client/models/rowset'; import {cssLabel, cssRow, cssSeparator} from 'app/client/ui/RightPanel'; import {cssFieldEntry, cssFieldLabel, IField, VisibleFieldsConfig } from 'app/client/ui/VisibleFieldsConfig'; import {squareCheckbox} from 'app/client/ui2018/checkbox'; import {colors, vars} from 'app/client/ui2018/cssVars'; import {cssDragger} from 'app/client/ui2018/draggableList'; import {icon} from 'app/client/ui2018/icons'; import {linkSelect, menu, menuItem, select} from 'app/client/ui2018/menus'; import {nativeCompare} from 'app/common/gutil'; import {decodeObject} from 'app/plugin/objtypes'; import {Events as BackboneEvents} from 'backbone'; import {Computed, dom, DomElementArg, fromKo, Disposable as GrainJSDisposable, IOption, makeTestId, Observable, styled} from 'grainjs'; import * as ko from 'knockout'; import debounce = require('lodash/debounce'); import defaults = require('lodash/defaults'); import defaultsDeep = require('lodash/defaultsDeep'); import {Config, Data, Datum, ErrorBar, Layout, LayoutAxis, Margin} from 'plotly.js'; let Plotly: PlotlyType; // When charting multiple series based on user data, limit the number of series given to plotly. const MAX_SERIES_IN_CHART = 100; const testId = makeTestId('test-chart-'); interface ChartOptions { multiseries?: boolean; lineConnectGaps?: boolean; lineMarkers?: boolean; invertYAxis?: boolean; logYAxis?: boolean; // If "symmetric", one series after each Y series gives the length of the error bars around it. If // "separate", two series after each Y series give the length of the error bars above and below it. errorBars?: 'symmetric' | 'separate'; } // tslint:disable:no-console // We use plotly's Datum to describe the type of values in cells. Cells may not match this // perfectly, but it's helpful for type-checking anyway. type RowPropGetter = (rowId: number) => Datum; // We convert Grist data to a list of Series first, from which we then construct Plotly traces. interface Series { label: string; // Corresponds to the column name. group?: Datum; // The group value, when grouped. values: Datum[]; } function getSeriesName(series: Series, haveMultiple: boolean) { if (!series.group) { return series.label; } else if (haveMultiple) { return `${series.group} \u2022 ${series.label}`; // the unicode character is "black circle" } else { return String(series.group); } } // The output of a ChartFunc. Normally it just returns one or more Data[] series, but sometimes it // includes layout information: e.g. a "Scatter Plot" returns a Layout with axis labels. interface PlotData { data: Data[]; layout?: Partial; config?: Partial; } // Convert a list of Series into a set of Plotly traces. type ChartFunc = (series: Series[], options: ChartOptions) => PlotData; // Helper for converting numeric Date/DateTime values (seconds since Epoch) to JS Date objects for // use with plotly. function dateGetter(getter: RowPropGetter): RowPropGetter { return (r: number) => { // 0's will turn into nulls, and non-numbers will turn into NaNs and then nulls. This prevents // Plotly from including 1970-01-01 onto X axis, which usually makes the plot useless. const val = (getter(r) as number) * 1000; // Plotly recommends using strings for dates rather than Date objects or timestamps. They are // interpreted more consistently. See https://github.com/plotly/plotly.js/issues/1532#issuecomment-290420534. return val ? new Date(val).toISOString() : null; }; } // List of column types whose values are encoded has list, ie: ['L', 'foo', ...]. Such values // require special treatment to show correctly in charts. const LIST_TYPES = ['ChoiceList', 'RefList']; /** * ChartView component displays created charts. */ export class ChartView extends Disposable { public viewPane: Element; // These elements are defined in BaseView, from which we inherit with some hackery. protected viewSection: ViewSectionRec; protected sortedRows: SortedRowSet; protected tableModel: DataTableModel; private _chartType: ko.Observable; private _options: ObjObservable; private _chartDom: HTMLElement; private _update: () => void; private _resize: () => void; public create(gristDoc: GristDoc, viewSectionModel: ViewSectionRec) { BaseView.call(this as any, gristDoc, viewSectionModel); this._chartDom = this.autoDispose(this.buildDom()); this._resize = this.autoDispose(Delay.untilAnimationFrame(this._resizeChart, this)); // Note that .viewPane is used by ViewLayout to insert the actual DOM into the document. this.viewPane = this._chartDom; this._chartType = this.viewSection.chartTypeDef; this._options = this.viewSection.optionsObj; this._update = debounce(() => this._updateView(), 0); this.autoDispose(this._chartType.subscribe(this._update)); this.autoDispose(this._options.subscribe(this._update)); this.autoDispose(this.viewSection.viewFields().subscribe(this._update)); this.listenTo(this.sortedRows, 'rowNotify', this._update); this.autoDispose(this.sortedRows.getKoArray().subscribe(this._update)); } public prepareToPrint(onOff: boolean) { Plotly.relayout(this._chartDom, {}).catch(reportError); } protected onTableLoaded() { (BaseView.prototype as any).onTableLoaded.call(this); this._update(); } protected onResize() { this._resize(); } protected buildDom() { return dom('div.chart_container', testId('container')); } private listenTo(...args: any[]): void { /* replaced by Backbone */ } private async _updateView() { if (this.isDisposed()) { return; } const chartFunc = chartTypes[this._chartType()]; if (typeof chartFunc !== 'function') { console.warn("Unknown trace type %s", this._chartType()); return; } const fields: ViewFieldRec[] = this.viewSection.viewFields().all(); const rowIds: number[] = this.sortedRows.getKoArray().peek() as number[]; let series: Series[] = fields.map((field) => { // Use the colId of the displayCol, which may be different in case of Reference columns. const colId: string = field.displayColModel.peek().colId.peek(); const getter = this.tableModel.tableData.getRowPropFunc(colId) as RowPropGetter; const pureType = field.displayColModel().pureType(); const fullGetter = (pureType === 'Date' || pureType === 'DateTime') ? dateGetter(getter) : getter; return { label: field.label(), values: rowIds.map(fullGetter), }; }); const startIndexForYAxis = this._options.prop('multiseries') ? 2 : 1; for (let i = 0; i < series.length; ++i) { if (i < fields.length && LIST_TYPES.includes(fields[i].column.peek().pureType.peek())) { if (i < startIndexForYAxis) { // For x-axis and group column data, split series we should split records. series = splitValuesByIndex(series, i); } else { // For all y-axis, it's not sure what would be a sensible representation for choice list, // simply stringify choice list values seems reasonable. series[i].values = series[i].values.map((v) => String(decodeObject(v as any))); } } } const options: ChartOptions = this._options.peek() || {}; let plotData: PlotData = {data: []}; if (!options.multiseries) { plotData = chartFunc(series, options); } else if (series.length > 1) { // We need to group all series by the first column. const nseries = groupSeries(series[0].values, series.slice(1)); // This will be in the order in which nseries Map was created; concat() flattens the arrays. for (const gSeries of nseries.values()) { const part = chartFunc(gSeries, options); part.data = plotData.data.concat(part.data); plotData = part; } } Plotly = Plotly || await loadPlotly(); // Loading plotly is asynchronous and it may happen that the chart view had been disposed in the // meantime and cause error later. So let's check again. if (this.isDisposed()) { return; } const layout: Partial = defaultsDeep(plotData.layout, getPlotlyLayout(options)); const config: Partial = {...plotData.config, displayModeBar: false}; // react() can be used in place of newPlot(), and is faster when updating an existing plot. await Plotly.react(this._chartDom, plotData.data, layout, config); this._resizeChart(); } private _resizeChart() { if (this.isDisposed() || !Plotly || !this._chartDom.parentNode) { return; } Plotly.Plots.resize(this._chartDom); } } /** * Group the given array of series by a column of group values. The groupColumn and each of the * series should be arrays of the same length. * * For example, if groupColumn has CompanyID, and valueSeries contains [Date, Employees, Revenues] * (each an array of values), then returns a map mapping each CompanyID to the array [Date, * Employees, Revenue], each value of which is itself an array of values for that CompanyID. */ function groupSeries(groupColumn: T[], valueSeries: Series[]): Map { const nseries = new Map(); // Limit the number if group values so as to limit the total number of series we pass into // Plotly. Too many series are impossible to make sense of anyway, and can hang the browser. // TODO: When not all data is shown, we should probably show some indicator, similar to when // OnDemand data is truncated. const maxGroups = Math.floor(MAX_SERIES_IN_CHART / valueSeries.length); const groupValues: T[] = [...new Set(groupColumn)].sort().slice(0, maxGroups); // Set up empty lists for each group. for (const group of groupValues) { nseries.set(group, valueSeries.map((s: Series) => ({ label: s.label, group, values: [] }))); } // Now fill up the lists. for (let row = 0; row < groupColumn.length; row++) { const group = groupColumn[row]; const series: Series[]|undefined = nseries.get(group); if (series) { for (let i = 0; i < valueSeries.length; i++) { series[i].values.push(valueSeries[i].values[row]); } } } return nseries; } // If errorBars are requested, removes error bar series from the 'series' list, adding instead a // mapping from each main Y series to the corresponding plotly ErrorBar object. function extractErrorBars(series: Series[], options: ChartOptions): Map { const result = new Map(); if (options.errorBars) { // We assume that series is of the form [X, Y1, Y1-bar, Y2, Y2-bar, ...] (if "symmetric") or // [X, Y1, Y1-below, Y1-above, Y2, Y2-below, Y2-above, ...] (if "separate"). for (let i = 1; i < series.length; i++) { result.set(series[i], { type: 'data', symmetric: (options.errorBars === 'symmetric'), array: series[i + 1] && series[i + 1].values, arrayminus: (options.errorBars === 'separate' ? series[i + 2] && series[i + 2].values : undefined), thickness: 1, width: 3, }); series.splice(i + 1, (options.errorBars === 'symmetric' ? 1 : 2)); } } return result; } // Getting an ES6 class to work with old-style multiple base classes takes a little hacking. defaults(ChartView.prototype, BaseView.prototype); Object.assign(ChartView.prototype, BackboneEvents); function getPlotlyLayout(options: ChartOptions): Partial { // Note that each call to getPlotlyLayout() creates a new layout object. We are intentionally // avoiding reuse because Plotly caches too many layout calculations when the object is reused. const yaxis: Partial = {}; if (options.logYAxis) { yaxis.type = 'log'; } if (options.invertYAxis) { yaxis.autorange = 'reversed'; } return { // Margins include labels, titles, legend, and may get auto-expanded beyond this. margin: { l: 50, r: 50, b: 40, // Space below chart which includes x-axis labels t: 30, // Space above the chart (doesn't include any text) pad: 4 } as Margin, legend: { // Translucent background, so chart data is still visible if legend overlaps it. bgcolor: "#FFFFFF80", }, yaxis, }; } /** * The grainjs component for side-pane configuration options for a Chart section. */ export class ChartConfig extends GrainJSDisposable { // helper to build the draggable field list private _configFieldsHelper = VisibleFieldsConfig.create(this, this._gristDoc, this._section, true); // The index for the x-axis in the list visible fields. Could be eigther 0 or 1 depending on // whether multiseries is set. private _xAxisFieldIndex = Computed.create( this, fromKo(this._optionsObj.prop('multiseries')), (_use, multiseries) => ( multiseries ? 1 : 0 ) ); // The column id of the grouping column, or -1 if multiseries is disabled. private _groupDataColId: Computed = Computed.create(this, (use) => { const multiseries = use(this._optionsObj.prop('multiseries')); const viewFields = use(use(this._section.viewFields).getObservable()); if (!multiseries) { return -1; } return use(viewFields[0].column).getRowId(); }) .onWrite((colId) => this._setGroupDataColumn(colId)); // Updating the group data column involves several changes of the list of view fields which could // leave the x-axis field index momentarily point to the wrong column. The freeze x axis // observable is part of a hack to fix this issue. private _freezeXAxis = Observable.create(this, false); private _freezeYAxis = Observable.create(this, false); // The column is of the x-axis. private _xAxis: Computed = Computed.create( this, this._xAxisFieldIndex, this._freezeXAxis, (use, i, freeze) => { if (freeze) { return this._xAxis.get(); } const viewFields = use(use(this._section.viewFields).getObservable()); if (i < viewFields.length) { return use(viewFields[i].column).getRowId(); } return -1; }) .onWrite((colId) => this._setXAxis(colId)); // The list of available columns for the group data picker. Picking the actual x-axis is not // permitted. private _groupDataOptions = Computed.create>>(this, (use) => [ {value: -1, label: 'Pick a column'}, ...this._section.table().columns().peek() // filter out hidden column (ie: manualsort ...) and the one selected for x axis .filter((col) => !col.isHiddenCol.peek() && (col.getRowId() !== use(this._xAxis))) .map((col) => ({ value: col.getRowId(), label: col.label.peek(), icon: 'FieldColumn', })) ]); // Force checking/unchecking of the group data checkbox option. private _groupDataForce = Observable.create(null, false); // State for the group data option checkbox. True, if a group data column is set or if the user // forced it. False otherwise. private _groupData = Computed.create( this, this._groupDataColId, this._groupDataForce, (_use, col, force) => { if (col > -1) { return true; } return force; }).onWrite((val) => { if (val === false) { this._groupDataColId.set(-1); } this._groupDataForce.set(val); }); // The label to show for the first field in the axis configurator. private _firstFieldLabel = Computed.create(this, fromKo(this._section.chartTypeDef), ( (_use, chartType) => chartType === 'pie' ? 'LABEL' : 'X-AXIS' )); // A computed that returns `this._section.chartTypeDef` and that takes care of removing the group // data option when type is switched to 'pie'. private _chartType = Computed.create(this, (use) => use(this._section.chartTypeDef)) .onWrite((val) => { return this._gristDoc.docData.bundleActions('switched chart type', async () => { await this._section.chartTypeDef.saveOnly(val); // When switching chart type to 'pie' makes sure to remove the group data option. if (val === 'pie') { await this._setGroupDataColumn(-1); this._groupDataForce.set(false); } }); }); constructor(private _gristDoc: GristDoc, private _section: ViewSectionRec) { super(); } private get _optionsObj() { return this._section.optionsObj; } public buildDom() { if (this._section.parentKey() !== 'chart') { return null; } return [ cssRow( select(this._chartType, [ {value: 'bar', label: 'Bar Chart', icon: 'ChartBar' }, {value: 'pie', label: 'Pie Chart', icon: 'ChartPie' }, {value: 'area', label: 'Area Chart', icon: 'ChartArea' }, {value: 'line', label: 'Line Chart', icon: 'ChartLine' }, {value: 'scatter', label: 'Scatter Plot', icon: 'ChartLine' }, {value: 'kaplan_meier', label: 'Kaplan-Meier Plot', icon: 'ChartKaplan'}, ]), testId("type"), ), dom.maybe((use) => use(this._section.chartTypeDef) !== 'pie', () => [ // These options don't make much sense for a pie chart. cssCheckboxRowObs('Group data', this._groupData), cssCheckboxRow('Invert Y-axis', this._optionsObj.prop('invertYAxis')), cssCheckboxRow('Log scale Y-axis', this._optionsObj.prop('logYAxis')), ]), dom.maybe((use) => use(this._section.chartTypeDef) === 'line', () => [ cssCheckboxRow('Connect gaps', this._optionsObj.prop('lineConnectGaps')), cssCheckboxRow('Show markers', this._optionsObj.prop('lineMarkers')), ]), dom.maybe((use) => ['line', 'bar'].includes(use(this._section.chartTypeDef)), () => [ cssRow( cssRowLabel('Error bars'), dom('div', linkSelect(fromKoSave(this._optionsObj.prop('errorBars')), [ {value: '', label: 'None'}, {value: 'symmetric', label: 'Symmetric'}, {value: 'separate', label: 'Above+Below'}, ], {defaultLabel: 'None'})), testId('error-bars'), ), dom.domComputed(this._optionsObj.prop('errorBars'), (value: ChartOptions["errorBars"]) => value === 'symmetric' ? cssRowHelp('Each Y series is followed by a series for the length of error bars.') : value === 'separate' ? cssRowHelp('Each Y series is followed by two series, for top and bottom error bars.') : null ), ]), cssSeparator(), dom.maybe(this._groupData, () => [ cssLabel('Group data'), cssRow( select(this._groupDataColId, this._groupDataOptions), testId('group-by-column'), ), cssHintRow('Create separate series for each value of the selected column.'), ]), // TODO: user should select x axis before widget reach page cssLabel(dom.text(this._firstFieldLabel), testId('first-field-label')), cssRow( select( this._xAxis, this._section.table().columns().peek() .filter((col) => !col.isHiddenCol.peek()) .map((col) => ({ value: col.getRowId(), label: col.label.peek(), icon: 'FieldColumn', })) ), testId('x-axis'), ), cssLabel('SERIES'), this._buildYAxis(), cssRow( cssAddYAxis( cssAddIcon('Plus'), 'Add Series', menu(() => this._section.hiddenColumns.peek().map((col) => ( menuItem(() => this._configFieldsHelper.addField(col), col.label.peek()) ))), testId('add-y-axis'), ) ), ]; } private async _setXAxis(colId: number) { const optionsObj = this._section.optionsObj; const col = this._gristDoc.docModel.columns.getRowModel(colId); const viewFields = this._section.viewFields.peek(); await this._gristDoc.docData.bundleActions('selected new x-axis', async () => { this._freezeYAxis.set(true); try { // first remove the current field if (this._xAxisFieldIndex.get() < viewFields.peek().length) { await this._configFieldsHelper.removeField(viewFields.peek()[this._xAxisFieldIndex.get()]); } // if new field was used to group by column series, disable multiseries const fieldIndex = viewFields.peek().findIndex((f) => f.column.peek().getRowId() === colId); if (fieldIndex === 0 && optionsObj.prop('multiseries').peek()) { await optionsObj.prop('multiseries').setAndSave(false); return; } // if new field is already visible, moves the fields to the first place else add the field to the first // place const xAxisField = viewFields.peek()[this._xAxisFieldIndex.get()]; if (fieldIndex > -1) { await this._configFieldsHelper.changeFieldPosition(viewFields.peek()[fieldIndex], xAxisField); } else { await this._configFieldsHelper.addField(col, xAxisField); } } finally { this._freezeYAxis.set(false); } }); } private async _setGroupDataColumn(colId: number) { const viewFields = this._section.viewFields.peek().peek(); await this._gristDoc.docData.bundleActions('selected new x-axis', async () => { this._freezeXAxis.set(true); this._freezeYAxis.set(true); try { // if grouping was already set, first remove the current field if (this._groupDataColId.get() > -1) { await this._configFieldsHelper.removeField(viewFields[0]); } if (colId > -1) { const col = this._gristDoc.docModel.columns.getRowModel(colId); const field = viewFields.find((f) => f.column.peek().getRowId() === colId); // if new field is already visible, moves the fields to the first place else add the field to the first // place if (field) { await this._configFieldsHelper.changeFieldPosition(field, viewFields[0]); } else { await this._configFieldsHelper.addField(col, viewFields[0]); } } await this._optionsObj.prop('multiseries').setAndSave(colId > -1); } finally { this._freezeXAxis.set(false); this._freezeYAxis.set(false); } }, {nestInActiveBundle: true}); } private _buildField(col: IField) { return cssFieldEntry( cssFieldLabel(dom.text(col.label)), cssRemoveIcon( 'Remove', dom.on('click', () => this._configFieldsHelper.removeField(col)), testId('ref-select-remove'), ), testId('y-axis'), ); } private _buildYAxis() { // The y-axis are all visible fields that comes after the x-axis and maybe the group data // column. Hence the draggable list of y-axis needs to skip either one or two visible fields. const skipFirst = Computed.create(this, fromKo(this._optionsObj.prop('multiseries')), (_use, multiseries) => ( multiseries ? 2 : 1 )); return this._configFieldsHelper.buildVisibleFieldsConfigHelper({ itemCreateFunc: (field) => this._buildField(field), draggableOptions: { removeButton: false, drag_indicator: cssDragger, }, skipFirst, freeze: this._freezeYAxis }); } } function cssCheckboxRow(label: string, value: KoSaveableObservable, ...args: DomElementArg[]) { return cssCheckboxRowObs(label, fromKoSave(value), ...args); } function cssCheckboxRowObs(label: string, value: Observable, ...args: DomElementArg[]) { return dom('label', cssRow.cls(''), cssRowLabel(label), squareCheckbox(value, ...args), ); } function basicPlot(series: Series[], options: ChartOptions, dataOptions: Partial): PlotData { trimNonNumericData(series); const errorBars = extractErrorBars(series, options); if (dataOptions.type === 'bar') { // Plotly has weirdness when redundant values shows up on the x-axis: the values that shows // up on hover is different than the value on the y-axis. It seems that one is the sum of all // values with same x-axis value, while the other is the last of them. To fix this, we force // unique values for the x-axis. series = uniqXValues(series); } return { data: series.slice(1).map((line: Series): Data => ({ name: getSeriesName(line, series.length > 2), x: series[0].values, y: line.values, error_y: errorBars.get(line), ...dataOptions, })), layout: { xaxis: series.length > 0 ? {title: series[0].label} : {}, // Include yaxis title for a single y-value series only (2 series total); // If there are fewer than 2 total series, there is no y-series to display. // If there are multiple y-series, a legend will be included instead, and the yaxis title // is less meaningful, so omit it. yaxis: series.length === 2 ? {title: series[1].label} : {}, }, }; } // Most chart types take a list of series and then use the first series for the X-axis, and each // subsequent series for their Y-axis values, allowing for multiple lines on the same plot. // Each series should have the form {label, values}. export const chartTypes: {[name: string]: ChartFunc} = { // TODO There is a lot of code duplication across chart types. Some refactoring is in order. bar(series: Series[], options: ChartOptions): PlotData { return basicPlot(series, options, {type: 'bar'}); }, line(series: Series[], options: ChartOptions): PlotData { sortByXValues(series); return basicPlot(series, options, { type: 'scatter', connectgaps: options.lineConnectGaps, mode: options.lineMarkers ? 'lines+markers' : 'lines', }); }, area(series: Series[], options: ChartOptions): PlotData { sortByXValues(series); return basicPlot(series, options, { type: 'scatter', fill: 'tozeroy', line: {shape: 'spline'}, }); }, scatter(series: Series[], options: ChartOptions): PlotData { return basicPlot(series.slice(1), options, { type: 'scatter', mode: 'text+markers', text: series[0].values as string[], textposition: "bottom center", }); }, pie(series: Series[]): PlotData { let line: Series; if (series.length === 0) { return {data: []}; } if (series.length > 1) { trimNonNumericData(series); line = series[1]; } else { // When there is only one series of labels, simply count their occurrences. line = {label: 'Count', values: series[0].values.map(() => 1)}; } return { data: [{ type: 'pie', name: getSeriesName(line, false), // nulls cause JS errors when pie charts resize, so replace with blanks. // (a falsy value would cause plotly to show its index, like "2" which is more confusing). labels: series[0].values.map(v => (v == null || v === "") ? "-" : v), values: line.values, }] }; }, kaplan_meier(series: Series[]): PlotData { // For this plot, the first series names the category of each point, and the second the // survival time for that point. We turn that into as many series as there are categories. if (series.length < 2) { return {data: []}; } const newSeries = groupIntoSeries(series[0].values, series[1].values); return { data: newSeries.map((line: Series): Data => { const points = kaplanMeierPlot(line.values as number[]); return { type: 'scatter', mode: 'lines', line: {shape: 'hv'}, name: getSeriesName(line, false), x: points.map(p => p.x), y: points.map(p => p.y), } as Data; }) }; }, }; /** * Assumes a list of series of the form [xValues, yValues1, yValues2, ...]. Remove from all series * those points for which all of the y-values are non-numeric (e.g. null or a string). */ function trimNonNumericData(series: Series[]): void { const values = series.slice(1).map((s) => s.values); for (const s of series) { s.values = s.values.filter((_, i) => values.some(v => typeof v[i] === 'number')); } } // Given two parallel arrays, returns an array of series of the form // {label: category, values: array-of-values} function groupIntoSeries(categoryList: Datum[], valueList: Datum[]): Series[] { const groups = new Map(); for (const [i, cat] of categoryList.entries()) { if (!groups.has(cat)) { groups.set(cat, []); } groups.get(cat).push(valueList[i]); } return Array.from(groups, ([label, values]) => ({label, values})); } // Given a list of survivalValues, returns a list of {x, y} pairs for the kaplanMeier plot. function kaplanMeierPlot(survivalValues: number[]): Array<{x: number, y: number}> { // First get a distribution of survivalValue -> count. const dist = new Map(); for (const v of survivalValues) { dist.set(v, (dist.get(v) || 0) + 1); } // Sort the distinct values. const distinctValues = Array.from(dist.keys()); distinctValues.sort(nativeCompare); // Now generate plot values, with 'x' for survivalValue and 'y' the number of surviving points. let y = survivalValues.length; const points = [{x: 0, y}]; for (const x of distinctValues) { y -= dist.get(x)!; points.push({x, y}); } return points; } const cssRowLabel = styled('div', ` flex: 1 0 0px; margin-right: 8px; font-weight: initial; /* negate bootstrap */ color: ${colors.dark}; overflow: hidden; text-overflow: ellipsis; user-select: none; `); const cssRowHelp = styled(cssRow, ` font-size: ${vars.smallFontSize}; color: ${colors.slate}; `); const cssAddIcon = styled(icon, ` margin-right: 4px; `); const cssAddYAxis = styled('div', ` display: flex; cursor: pointer; color: ${colors.lightGreen}; --icon-color: ${colors.lightGreen}; &:not(:first-child) { margin-top: 8px; } &:hover, &:focus, &:active { color: ${colors.darkGreen}; --icon-color: ${colors.darkGreen}; } `); const cssRemoveIcon = styled(icon, ` display: none; cursor: pointer; flex: none; margin-left: 8px; .${cssFieldEntry.className}:hover & { display: block; } `); const cssHintRow = styled('div', ` margin: -4px 16px 8px 16px; color: ${colors.slate}; `);