mirror of
https://github.com/gristlabs/grist-core.git
synced 2024-10-27 20:44:07 +00:00
8f531ef622
Summary: Previously, ref/reflist columns were formatted entirely based on their visible column, since they received values from the visible or display columns rather than the actual row IDs. This creates `ReferenceFormatter` and `ReferenceListFormatter` which still delegate most of the formatting work to a visible column formatter but fix a few issues: - ReferenceList columns now actually use the options (e.g. date format) of the visible column to format their elements. Previously they were formatted generically because the visible column formatter wasn't expecting a list. - Invalid references aren't formatted with an `#Invalid Ref` prefix. - When the ref column displays the Row ID, it doesn't have a visible or display column. Previously this led to the references being formatted as just numbers in most cases, with special code in the widget to display them like `Table1[2]`. Now they are consistently formatted in that style throughout. Test Plan: Updated existing tests. Reviewers: jarek Reviewed By: jarek Subscribers: dsagal Differential Revision: https://phab.getgrist.com/D3212
1079 lines
39 KiB
TypeScript
1079 lines
39 KiB
TypeScript
import * as BaseView from 'app/client/components/BaseView';
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import {GristDoc} from 'app/client/components/GristDoc';
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import {consolidateValues, formatPercent, sortByXValues, splitValuesByIndex,
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uniqXValues} from 'app/client/lib/chartUtil';
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import {Delay} from 'app/client/lib/Delay';
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import {Disposable} from 'app/client/lib/dispose';
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import {fromKoSave} from 'app/client/lib/fromKoSave';
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import {loadPlotly, PlotlyType} from 'app/client/lib/imports';
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import * as DataTableModel from 'app/client/models/DataTableModel';
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import {ViewFieldRec, ViewSectionRec} from 'app/client/models/DocModel';
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import {reportError} from 'app/client/models/errors';
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import {KoSaveableObservable, ObjObservable} from 'app/client/models/modelUtil';
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import {SortedRowSet} from 'app/client/models/rowset';
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import {cssLabel, cssRow, cssSeparator} from 'app/client/ui/RightPanel';
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import {cssFieldEntry, cssFieldLabel, IField, VisibleFieldsConfig } from 'app/client/ui/VisibleFieldsConfig';
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import {squareCheckbox} from 'app/client/ui2018/checkbox';
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import {colors, vars} from 'app/client/ui2018/cssVars';
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import {cssDragger} from 'app/client/ui2018/draggableList';
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import {icon} from 'app/client/ui2018/icons';
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import {linkSelect, menu, menuItem, select} from 'app/client/ui2018/menus';
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import {nativeCompare} from 'app/common/gutil';
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import {BaseFormatter} from 'app/common/ValueFormatter';
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import {decodeObject} from 'app/plugin/objtypes';
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import {Events as BackboneEvents} from 'backbone';
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import {Computed, dom, DomContents, DomElementArg, fromKo, Disposable as GrainJSDisposable, IOption,
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makeTestId, Observable, styled} from 'grainjs';
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import * as ko from 'knockout';
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import clamp = require('lodash/clamp');
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import debounce = require('lodash/debounce');
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import defaults = require('lodash/defaults');
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import defaultsDeep = require('lodash/defaultsDeep');
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import isNumber = require('lodash/isNumber');
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import sum = require('lodash/sum');
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import {Annotations, Config, Data, Datum, ErrorBar, Layout, LayoutAxis, Margin} from 'plotly.js';
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let Plotly: PlotlyType;
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// When charting multiple series based on user data, limit the number of series given to plotly.
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const MAX_SERIES_IN_CHART = 100;
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const DONUT_DEFAULT_HOLE_SIZE = 0.75;
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const DONUT_DEFAULT_TEXT_SIZE = 24;
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const testId = makeTestId('test-chart-');
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function isPieLike(chartType: string) {
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return ['pie', 'donut'].includes(chartType);
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}
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interface ChartOptions {
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multiseries?: boolean;
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lineConnectGaps?: boolean;
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lineMarkers?: boolean;
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invertYAxis?: boolean;
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logYAxis?: boolean;
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// If "symmetric", one series after each Y series gives the length of the error bars around it. If
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// "separate", two series after each Y series give the length of the error bars above and below it.
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errorBars?: 'symmetric' | 'separate';
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donutHoleSize?: number;
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showTotal?: boolean;
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textSize?: number;
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}
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// tslint:disable:no-console
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// We use plotly's Datum to describe the type of values in cells. Cells may not match this
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// perfectly, but it's helpful for type-checking anyway.
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type RowPropGetter = (rowId: number) => Datum;
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// We convert Grist data to a list of Series first, from which we then construct Plotly traces.
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interface Series {
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label: string; // Corresponds to the column name.
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group?: Datum; // The group value, when grouped.
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values: Datum[];
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}
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function getSeriesName(series: Series, haveMultiple: boolean) {
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if (series.group === undefined) {
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return series.label;
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}
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// Let's show [Blank] instead of leaving the name empty for that series. There is a possibility
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// to confuse user between a blank cell and a cell holding the `[Blank]` value. But that is rare
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// enough, and confusion can easily be removed by the chart creator by editing blank cells
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// directly in the the table to put something more meaningful instead.
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const groupName = series.group === '' ? '[Blank]' : series.group;
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if (haveMultiple) {
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return `${groupName} \u2022 ${series.label}`; // the unicode character is "black circle"
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} else {
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return String(groupName);
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}
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}
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// The output of a ChartFunc. Normally it just returns one or more Data[] series, but sometimes it
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// includes layout information: e.g. a "Scatter Plot" returns a Layout with axis labels.
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interface PlotData {
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data: Data[];
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layout?: Partial<Layout>;
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config?: Partial<Config>;
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}
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// Data options to pass to chart functions.
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interface DataOptions extends Data {
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// Allows to set the pie sort option (see: https://plotly.com/javascript/reference/pie/#pie-sort).
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// Supports pie charts only.
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sort?: boolean;
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// Formatter to be used for the total inside donut charts.
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totalFormatter?: BaseFormatter;
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}
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// Convert a list of Series into a set of Plotly traces.
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type ChartFunc = (series: Series[], options: ChartOptions, dataOptions?: DataOptions) => PlotData;
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// Helper for converting numeric Date/DateTime values (seconds since Epoch) to JS Date objects for
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// use with plotly.
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function dateGetter(getter: RowPropGetter): RowPropGetter {
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return (r: number) => {
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// 0's will turn into nulls, and non-numbers will turn into NaNs and then nulls. This prevents
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// Plotly from including 1970-01-01 onto X axis, which usually makes the plot useless.
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const val = (getter(r) as number) * 1000;
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// Plotly recommends using strings for dates rather than Date objects or timestamps. They are
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// interpreted more consistently. See https://github.com/plotly/plotly.js/issues/1532#issuecomment-290420534.
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return val ? new Date(val).toISOString() : null;
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};
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}
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// List of column types whose values are encoded has list, ie: ['L', 'foo', ...]. Such values
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// require special treatment to show correctly in charts.
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const LIST_TYPES = ['ChoiceList', 'RefList'];
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/**
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* ChartView component displays created charts.
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*/
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export class ChartView extends Disposable {
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public viewPane: Element;
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// These elements are defined in BaseView, from which we inherit with some hackery.
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protected viewSection: ViewSectionRec;
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protected sortedRows: SortedRowSet;
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protected tableModel: DataTableModel;
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protected gristDoc: GristDoc;
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private _chartType: ko.Observable<string>;
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private _options: ObjObservable<any>;
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private _chartDom: HTMLElement;
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private _update: () => void;
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private _resize: () => void;
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private _formatterComp: ko.Computed<BaseFormatter|undefined>;
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// peek section's sort spec
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private get _sortSpec() { return this.viewSection.activeSortSpec.peek(); }
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public create(gristDoc: GristDoc, viewSectionModel: ViewSectionRec) {
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BaseView.call(this as any, gristDoc, viewSectionModel);
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this._chartDom = this.autoDispose(this.buildDom());
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this._resize = this.autoDispose(Delay.untilAnimationFrame(this._resizeChart, this));
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// Note that .viewPane is used by ViewLayout to insert the actual DOM into the document.
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this.viewPane = this._chartDom;
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this._chartType = this.viewSection.chartTypeDef;
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this._options = this.viewSection.optionsObj;
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// Computed that returns the formatter of the first series. This is useful to format the total
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// within a donut chart.
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this._formatterComp = this.autoDispose(ko.computed(() => {
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const field = this.viewSection.viewFields().at(1);
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return field?.visibleColFormatter();
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}));
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this._update = debounce(() => this._updateView(), 0);
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this.autoDispose(this._chartType.subscribe(this._update));
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this.autoDispose(this._options.subscribe(this._update));
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this.autoDispose(this.viewSection.viewFields().subscribe(this._update));
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this.listenTo(this.sortedRows, 'rowNotify', this._update);
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this.autoDispose(this.sortedRows.getKoArray().subscribe(this._update));
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this.autoDispose(this._formatterComp.subscribe(this._update));
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}
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public prepareToPrint(onOff: boolean) {
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Plotly.relayout(this._chartDom, {}).catch(reportError);
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}
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protected onTableLoaded() {
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(BaseView.prototype as any).onTableLoaded.call(this);
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this._update();
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}
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protected onResize() {
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this._resize();
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}
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protected buildDom() {
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return dom('div.chart_container', testId('container'));
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}
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private listenTo(...args: any[]): void { /* replaced by Backbone */ }
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private async _updateView() {
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if (this.isDisposed()) { return; }
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const chartFunc = chartTypes[this._chartType()];
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if (typeof chartFunc !== 'function') {
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console.warn("Unknown trace type %s", this._chartType());
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return;
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}
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const fields: ViewFieldRec[] = this.viewSection.viewFields().all();
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const rowIds: number[] = this.sortedRows.getKoArray().peek() as number[];
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let series: Series[] = fields.map((field) => {
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// Use the colId of the displayCol, which may be different in case of Reference columns.
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const colId: string = field.displayColModel.peek().colId.peek();
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const getter = this.tableModel.tableData.getRowPropFunc(colId) as RowPropGetter;
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const pureType = field.displayColModel().pureType();
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const fullGetter = (pureType === 'Date' || pureType === 'DateTime') ? dateGetter(getter) : getter;
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return {
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label: field.label(),
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values: rowIds.map(fullGetter),
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};
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});
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const startIndexForYAxis = this._options.prop('multiseries').peek() ? 2 : 1;
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for (let i = 0; i < series.length; ++i) {
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if (i < fields.length && LIST_TYPES.includes(fields[i].column.peek().pureType.peek())) {
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if (i < startIndexForYAxis) {
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// For x-axis and group column data, split series we should split records.
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series = splitValuesByIndex(series, i);
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} else {
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// For all y-axis, it's not sure what would be a sensible representation for choice list,
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// simply stringify choice list values seems reasonable.
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series[i].values = series[i].values.map((v) => String(decodeObject(v as any)));
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}
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}
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}
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const dataOptions: DataOptions = {};
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const options: ChartOptions = this._options.peek() || {};
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let plotData: PlotData = {data: []};
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if (isPieLike(this._chartType.peek())) {
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// Plotly's pie charts have a sort option that is enabled by default. Let's turn it off.
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dataOptions.sort = false;
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// This line is for labels to stay in order when value changes, which can happen when using
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// charts with linked list.
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sortByXValues(series);
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}
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if (this._chartType.peek() === 'donut') {
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dataOptions.totalFormatter = this._formatterComp.peek();
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}
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if (!options.multiseries) {
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plotData = chartFunc(series, options, dataOptions);
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} else if (series.length > 1) {
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// We need to group all series by the first column.
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const nseries = groupSeries(series[0].values, series.slice(1));
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// This will be in the order in which nseries Map was created; concat() flattens the arrays.
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const xvalues = Array.from(new Set(series[1].values));
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for (const gSeries of nseries.values()) {
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// All series have partial list of values, ie: if some may have Q1, Q2, Q3, Q4 as x values
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// some others might only have Q1. This causes inconsistent result in regard of the order
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// bars will be displayed by plotly (for bar charts). This eventually result in bars not
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// following the sorting order. This line fixes that issue by consolidating all series to
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// have at least on entry of each x values.
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if (this._chartType.peek() === 'bar') {
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if (this._sortSpec?.length) { consolidateValues(gSeries, xvalues); }
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}
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const part = chartFunc(gSeries, options, dataOptions);
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part.data = plotData.data.concat(part.data);
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plotData = part;
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}
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}
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Plotly = Plotly || await loadPlotly();
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// Loading plotly is asynchronous and it may happen that the chart view had been disposed in the
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// meantime and cause error later. So let's check again.
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if (this.isDisposed()) { return; }
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const layout: Partial<Layout> = defaultsDeep(plotData.layout, getPlotlyLayout(options));
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const config: Partial<Config> = {...plotData.config, displayModeBar: false};
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// react() can be used in place of newPlot(), and is faster when updating an existing plot.
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await Plotly.react(this._chartDom, plotData.data, layout, config);
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this._resizeChart();
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}
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private _resizeChart() {
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if (this.isDisposed() || !Plotly || !this._chartDom.parentNode) { return; }
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Plotly.Plots.resize(this._chartDom);
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}
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}
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/**
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* Group the given array of series by a column of group values. The groupColumn and each of the
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* series should be arrays of the same length.
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*
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* For example, if groupColumn has CompanyID, and valueSeries contains [Date, Employees, Revenues]
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* (each an array of values), then returns a map mapping each CompanyID to the array [Date,
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* Employees, Revenue], each value of which is itself an array of values for that CompanyID.
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*/
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function groupSeries<T extends Datum>(groupColumn: T[], valueSeries: Series[]): Map<T, Series[]> {
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const nseries = new Map<T, Series[]>();
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// Limit the number if group values so as to limit the total number of series we pass into
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// Plotly. Too many series are impossible to make sense of anyway, and can hang the browser.
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// TODO: When not all data is shown, we should probably show some indicator, similar to when
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// OnDemand data is truncated.
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const maxGroups = Math.floor(MAX_SERIES_IN_CHART / valueSeries.length);
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const groupValues: T[] = [...new Set(groupColumn)].sort().slice(0, maxGroups);
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// Set up empty lists for each group.
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for (const group of groupValues) {
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nseries.set(group, valueSeries.map((s: Series) => ({
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label: s.label,
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group,
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values: []
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})));
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}
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// Now fill up the lists.
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for (let row = 0; row < groupColumn.length; row++) {
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const group = groupColumn[row];
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const series: Series[]|undefined = nseries.get(group);
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if (series) {
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for (let i = 0; i < valueSeries.length; i++) {
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series[i].values.push(valueSeries[i].values[row]);
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}
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}
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}
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return nseries;
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}
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// If errorBars are requested, removes error bar series from the 'series' list, adding instead a
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// mapping from each main Y series to the corresponding plotly ErrorBar object.
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function extractErrorBars(series: Series[], options: ChartOptions): Map<Series, ErrorBar> {
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const result = new Map<Series, ErrorBar>();
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if (options.errorBars) {
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// We assume that series is of the form [X, Y1, Y1-bar, Y2, Y2-bar, ...] (if "symmetric") or
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// [X, Y1, Y1-below, Y1-above, Y2, Y2-below, Y2-above, ...] (if "separate").
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for (let i = 1; i < series.length; i++) {
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result.set(series[i], {
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type: 'data',
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symmetric: (options.errorBars === 'symmetric'),
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array: series[i + 1] && series[i + 1].values,
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arrayminus: (options.errorBars === 'separate' ? series[i + 2] && series[i + 2].values : undefined),
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thickness: 1,
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width: 3,
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});
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series.splice(i + 1, (options.errorBars === 'symmetric' ? 1 : 2));
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}
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}
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return result;
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}
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// Getting an ES6 class to work with old-style multiple base classes takes a little hacking.
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defaults(ChartView.prototype, BaseView.prototype);
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Object.assign(ChartView.prototype, BackboneEvents);
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function getPlotlyLayout(options: ChartOptions): Partial<Layout> {
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// Note that each call to getPlotlyLayout() creates a new layout object. We are intentionally
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// avoiding reuse because Plotly caches too many layout calculations when the object is reused.
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const yaxis: Partial<LayoutAxis> = {};
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if (options.logYAxis) { yaxis.type = 'log'; }
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if (options.invertYAxis) { yaxis.autorange = 'reversed'; }
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return {
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// Margins include labels, titles, legend, and may get auto-expanded beyond this.
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margin: {
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l: 50,
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r: 50,
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b: 40, // Space below chart which includes x-axis labels
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t: 30, // Space above the chart (doesn't include any text)
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pad: 4
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} as Margin,
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legend: {
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// Translucent background, so chart data is still visible if legend overlaps it.
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bgcolor: "#FFFFFF80",
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},
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yaxis,
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};
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}
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/**
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* The grainjs component for side-pane configuration options for a Chart section.
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*/
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export class ChartConfig extends GrainJSDisposable {
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// helper to build the draggable field list
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private _configFieldsHelper = VisibleFieldsConfig.create(this, this._gristDoc, this._section, true);
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// The index for the x-axis in the list visible fields. Could be eigther 0 or 1 depending on
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// whether multiseries is set.
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private _xAxisFieldIndex = Computed.create(
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this, fromKo(this._optionsObj.prop('multiseries')), (_use, multiseries) => (
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multiseries ? 1 : 0
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)
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);
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// The column id of the grouping column, or -1 if multiseries is disabled or there are no viewFields,
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// for example during section removal.
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private _groupDataColId: Computed<number> = Computed.create(this, (use) => {
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const multiseries = use(this._optionsObj.prop('multiseries'));
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const viewFields = use(use(this._section.viewFields).getObservable());
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if (!multiseries || viewFields.length === 0) { return -1; }
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return use(viewFields[0].column).getRowId();
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})
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.onWrite((colId) => this._setGroupDataColumn(colId));
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// Updating the group data column involves several changes of the list of view fields which could
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// leave the x-axis field index momentarily point to the wrong column. The freeze x axis
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// observable is part of a hack to fix this issue.
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private _freezeXAxis = Observable.create(this, false);
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private _freezeYAxis = Observable.create(this, false);
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// The column is of the x-axis.
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private _xAxis: Computed<number> = Computed.create(
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this, this._xAxisFieldIndex, this._freezeXAxis, (use, i, freeze) => {
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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<Array<IOption<number>>>(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) => isPieLike(chartType) ? '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 (isPieLike(val)) {
|
|
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(): DomContents {
|
|
|
|
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: 'donut', label: 'Donut Chart', icon: 'ChartDonut' },
|
|
{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) => !isPieLike(use(this._section.chartTypeDef)), () => [
|
|
// 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.maybeOwned((use) => use(this._section.chartTypeDef) === 'donut', (owner) => [
|
|
cssSlideRow(
|
|
'Hole Size',
|
|
Computed.create(owner, (use) => use(this._optionsObj.prop('donutHoleSize')) ?? DONUT_DEFAULT_HOLE_SIZE),
|
|
(val: number) => this._optionsObj.prop('donutHoleSize').saveOnly(val),
|
|
testId('option')
|
|
),
|
|
cssCheckboxRow('Show Total', this._optionsObj.prop('showTotal')),
|
|
dom.maybe(this._optionsObj.prop('showTotal'), () => (
|
|
cssNumberWithSpinnerRow(
|
|
'Text Size',
|
|
Computed.create(owner, (use) => use(this._optionsObj.prop('textSize')) ?? DONUT_DEFAULT_TEXT_SIZE),
|
|
(val: number) => this._optionsObj.prop('textSize').saveOnly(val),
|
|
testId('option')
|
|
)
|
|
))
|
|
]),
|
|
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(): Element {
|
|
|
|
// 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
|
|
});
|
|
}
|
|
}
|
|
|
|
// Row for a numeric option. User can change value using spinners or directly using keyboard. In
|
|
// case of invalid values, the field reverts to the saved one.
|
|
function cssNumberWithSpinnerRow(label: string, value: Computed<number>, save: (val: number) => Promise<void>,
|
|
...args: DomElementArg[]) {
|
|
const minValue = 1;
|
|
let input: HTMLInputElement;
|
|
|
|
// Set the input's value to the value that's saved on the server.
|
|
function reset() {
|
|
input.value = value.get() + "px";
|
|
}
|
|
|
|
async function onChange(val: string, func: (val: number) => number = (v) => v) {
|
|
let fvalue = parseFloat(val);
|
|
if (isFinite(fvalue)) {
|
|
fvalue = clamp(func(fvalue), minValue, Infinity);
|
|
await save(fvalue);
|
|
}
|
|
// Reset is needed if value were not a valid number.
|
|
reset();
|
|
}
|
|
|
|
return cssRow(
|
|
cssRowLabel(label),
|
|
cssNumberWithSpinner(
|
|
input = cssNumberInput(
|
|
{type: 'text'},
|
|
dom.prop('value', (use) => use(value) + "px"),
|
|
dom.on('change', (_ev, el) => onChange(el.value)),
|
|
dom.onKeyDown({
|
|
ArrowDown: (_ev, el) => onChange(el.value, (val) => val - 1),
|
|
ArrowUp: (_ev, el) => onChange(el.value, (val) => val + 1),
|
|
}),
|
|
),
|
|
|
|
// We add spinners as overlay in order to support showing the unit 'px' next to the value.
|
|
cssSpinners(
|
|
'input',
|
|
{type: 'number', step: '1', min: String(minValue)},
|
|
dom.prop('value', value),
|
|
dom.on('change', (_ev, el) => onChange(el.value)),
|
|
),
|
|
),
|
|
...args
|
|
);
|
|
}
|
|
|
|
// Row for a numeric option that leaves between 0 and 1. User can change value using a slider, or
|
|
// spinners or by directly using keyboard. Value is shown as percent. If user enter an invalid
|
|
// value, field reverts to the saved value.
|
|
function cssSlideRow(label: string, value: Computed<number>, save: (val: number) => Promise<void>,
|
|
...args: DomElementArg[]) {
|
|
let input: HTMLInputElement;
|
|
|
|
// Set the input's value to the value that's saved on the server.
|
|
function reset() {
|
|
input.value = formatPercent(value.get());
|
|
}
|
|
|
|
async function onChange(val: string, func: (val: number) => number = (v) => v) {
|
|
let fvalue = parseFloat(val);
|
|
if (isFinite(fvalue)) {
|
|
fvalue = clamp(func(fvalue), 0, 99) / 100;
|
|
await save(fvalue);
|
|
}
|
|
// Reset is needed if value were not a valid number.
|
|
reset();
|
|
}
|
|
|
|
return cssRow(
|
|
cssRowLabel(label),
|
|
cssRangeInput(
|
|
{type: 'range', min: "0", max: "1", step: "0.01"},
|
|
dom.prop('value', value),
|
|
dom.on('change', (_ev, el) => save(Number(el.value)))
|
|
),
|
|
cssNumberWithSpinner(
|
|
input = cssNumberInput(
|
|
{type: 'text'},
|
|
dom.prop('value', (use) => formatPercent(use(value))),
|
|
dom.on('change', (_ev, el) => onChange(el.value)),
|
|
dom.onKeyDown({
|
|
ArrowDown: (_ev, el) => onChange(el.value, (val) => val - 1),
|
|
ArrowUp: (_ev, el) => onChange(el.value, (val) => val + 1),
|
|
}),
|
|
),
|
|
|
|
// We add spinners as overlay in order to support showing the unit '%' next to the value.
|
|
cssSpinners(
|
|
'input',
|
|
{type: 'number', step: '0.01', min: '0', max: '0.99'},
|
|
dom.prop('value', value),
|
|
dom.on('change', (_ev, el) => save(Number(el.value))),
|
|
)
|
|
),
|
|
...args
|
|
);
|
|
}
|
|
|
|
function cssCheckboxRow(label: string, value: KoSaveableObservable<unknown>, ...args: DomElementArg[]) {
|
|
return cssCheckboxRowObs(label, fromKoSave(value), ...args);
|
|
}
|
|
|
|
function cssCheckboxRowObs(label: string, value: Observable<boolean>, ...args: DomElementArg[]) {
|
|
return dom('label', cssRow.cls(''),
|
|
cssRowLabel(label),
|
|
squareCheckbox(value, ...args),
|
|
);
|
|
}
|
|
|
|
function basicPlot(series: Series[], options: ChartOptions, dataOptions: Data): 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.
|
|
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[], _options: ChartOptions, dataOptions: DataOptions = {}): 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,
|
|
...dataOptions,
|
|
}]
|
|
};
|
|
},
|
|
|
|
|
|
donut(series: Series[], options: ChartOptions, dataOptions: DataOptions = {}): PlotData {
|
|
const hole = isNumber(options.donutHoleSize) ? options.donutHoleSize : DONUT_DEFAULT_HOLE_SIZE;
|
|
const annotations: Array<Partial<Annotations>> = [];
|
|
const plotData: PlotData = chartTypes.pie(series, options, {...dataOptions, hole});
|
|
|
|
function format(val: number) {
|
|
if (dataOptions.totalFormatter) {
|
|
return dataOptions.totalFormatter.formatAny(val);
|
|
}
|
|
return String(val);
|
|
}
|
|
|
|
if (options.showTotal) {
|
|
annotations.push({
|
|
text: format(
|
|
series.length > 1 ?
|
|
sum(series[1].values.filter(isNumber)) :
|
|
plotData.data[0].labels!.length,
|
|
),
|
|
showarrow: false,
|
|
font: {
|
|
size: options.textSize ?? DONUT_DEFAULT_TEXT_SIZE,
|
|
}
|
|
} as any);
|
|
}
|
|
return defaultsDeep(
|
|
plotData,
|
|
{layout: {annotations}}
|
|
);
|
|
|
|
},
|
|
|
|
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<number, number>();
|
|
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: ${colors.slate};
|
|
`);
|
|
|
|
const cssRangeInput = styled('input', `
|
|
input& {
|
|
width: 82px;
|
|
margin-right: 4px;
|
|
}
|
|
`);
|
|
|
|
const cssNumberWithSpinner = styled('div', `
|
|
position: relative;
|
|
`);
|
|
|
|
const cssNumberInput = styled('input', `
|
|
width: 55px;
|
|
`);
|
|
|
|
|
|
const cssSpinners = styled('input', `
|
|
width: 19px;
|
|
position: absolute;
|
|
top: 2px;
|
|
right: 1px;
|
|
border: none;
|
|
outline: none;
|
|
appearance: none;
|
|
-moz-appearance: none;
|
|
visibility: hidden;
|
|
|
|
.${cssNumberWithSpinner.className}:hover & {
|
|
visibility: visible;
|
|
}
|
|
|
|
/* needed for chrome to show spinners, indeed the cursor could be outside of spinners' input
|
|
element */
|
|
&[type=number]::-webkit-inner-spin-button {
|
|
opacity: 1;
|
|
}
|
|
`);
|