mirror of
https://github.com/gristlabs/grist-core.git
synced 2024-10-27 20:44:07 +00:00
b80e56a4e1
Summary: Exposing new API in CustomSectionAPI for column mapping. The custom widget can call configure method (or use a ready method) with additional parameter "columns". This parameter is a list of column names that should be mapped by the user. Mapping configuration is exposed through an additional method in the CustomSectionAPI "mappings". It is also available through the onRecord(s) event. This DIFF is connected with PR for grist-widgets repository https://github.com/gristlabs/grist-widget/pull/15 Design document and discussion: https://grist.quip.com/Y2waA8h8Zuzu/Custom-Widget-field-mapping Test Plan: browser tests Reviewers: paulfitz Reviewed By: paulfitz Differential Revision: https://phab.getgrist.com/D3241
1136 lines
42 KiB
TypeScript
1136 lines
42 KiB
TypeScript
import * as BaseView from 'app/client/components/BaseView';
|
|
import {GristDoc} from 'app/client/components/GristDoc';
|
|
import {consolidateValues, formatPercent, 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 {ColumnRec, 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, menuText, select} from 'app/client/ui2018/menus';
|
|
import {nativeCompare, unwrap} from 'app/common/gutil';
|
|
import {BaseFormatter} from 'app/common/ValueFormatter';
|
|
import {decodeObject} from 'app/plugin/objtypes';
|
|
import {Events as BackboneEvents} from 'backbone';
|
|
import {Computed, dom, DomContents, DomElementArg, fromKo, Disposable as GrainJSDisposable,
|
|
IDisposable, IOption, makeTestId, Observable, styled, UseCB} from 'grainjs';
|
|
import * as ko from 'knockout';
|
|
import clamp = require('lodash/clamp');
|
|
import debounce = require('lodash/debounce');
|
|
import defaults = require('lodash/defaults');
|
|
import defaultsDeep = require('lodash/defaultsDeep');
|
|
import isNumber = require('lodash/isNumber');
|
|
import sum = require('lodash/sum');
|
|
import {Annotations, 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 DONUT_DEFAULT_HOLE_SIZE = 0.75;
|
|
const DONUT_DEFAULT_TEXT_SIZE = 24;
|
|
|
|
const testId = makeTestId('test-chart-');
|
|
|
|
function isPieLike(chartType: string) {
|
|
return ['pie', 'donut'].includes(chartType);
|
|
}
|
|
|
|
export function isNumericOnly(chartType: string) {
|
|
return ['bar', 'pie', 'donut', 'kaplan_meier', 'line', 'area', 'scatter'].includes(chartType);
|
|
}
|
|
|
|
// Returns the type of the visibleCol if col is of type `Ref`, otherwise returns the type of col.
|
|
function visibleColType(col: ColumnRec, use: UseCB = unwrap) {
|
|
const colType = use(col.pureType);
|
|
const isRef = colType === 'Ref';
|
|
return isRef ? use(use(col.visibleColModel).type) : colType;
|
|
}
|
|
|
|
// Returns true if col is one of 'Numeric', 'Int', 'Any'.
|
|
export function isNumericLike(col: ColumnRec, use: UseCB = unwrap) {
|
|
const colType = visibleColType(col, use);
|
|
return ['Numeric', 'Int', 'Any'].includes(colType);
|
|
}
|
|
|
|
|
|
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';
|
|
donutHoleSize?: number;
|
|
showTotal?: boolean;
|
|
textSize?: number;
|
|
}
|
|
|
|
// 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 === undefined) {
|
|
return series.label;
|
|
}
|
|
|
|
// Let's show [Blank] instead of leaving the name empty for that series. There is a possibility
|
|
// to confuse user between a blank cell and a cell holding the `[Blank]` value. But that is rare
|
|
// enough, and confusion can easily be removed by the chart creator by editing blank cells
|
|
// directly in the the table to put something more meaningful instead.
|
|
const groupName = series.group === '' ? '[Blank]' : series.group;
|
|
if (haveMultiple) {
|
|
return `${groupName} \u2022 ${series.label}`; // the unicode character is "black circle"
|
|
} else {
|
|
return String(groupName);
|
|
}
|
|
}
|
|
|
|
|
|
// 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<Layout>;
|
|
config?: Partial<Config>;
|
|
}
|
|
|
|
// Data options to pass to chart functions.
|
|
interface DataOptions extends Data {
|
|
|
|
// Allows to set the pie sort option (see: https://plotly.com/javascript/reference/pie/#pie-sort).
|
|
// Supports pie charts only.
|
|
sort?: boolean;
|
|
|
|
// Formatter to be used for the total inside donut charts.
|
|
totalFormatter?: BaseFormatter;
|
|
}
|
|
|
|
// Convert a list of Series into a set of Plotly traces.
|
|
type ChartFunc = (series: Series[], options: ChartOptions, dataOptions?: DataOptions) => 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;
|
|
protected gristDoc: GristDoc;
|
|
|
|
private _chartType: ko.Observable<string>;
|
|
private _options: ObjObservable<any>;
|
|
private _chartDom: HTMLElement;
|
|
private _update: () => void;
|
|
private _resize: () => void;
|
|
|
|
private _formatterComp: ko.Computed<BaseFormatter|undefined>;
|
|
|
|
// peek section's sort spec
|
|
private get _sortSpec() { return this.viewSection.activeSortSpec.peek(); }
|
|
|
|
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;
|
|
|
|
// Computed that returns the formatter of the first series. This is useful to format the total
|
|
// within a donut chart.
|
|
this._formatterComp = this.autoDispose(ko.computed(() => {
|
|
const field = this.viewSection.viewFields().at(1);
|
|
return field?.visibleColFormatter();
|
|
}));
|
|
|
|
this._update = debounce(() => this._updateView(), 0);
|
|
|
|
let subs: IDisposable[] = [];
|
|
this.autoDispose(this._chartType.subscribe(this._update));
|
|
this.autoDispose(this._options.subscribe(this._update));
|
|
this.autoDispose(this.viewSection.viewFields().subscribe((viewFields: ViewFieldRec[]) => {
|
|
this._update();
|
|
subs.forEach((sub) => sub.dispose());
|
|
subs = [
|
|
...viewFields.map((field) => field.displayColModel.peek().type.subscribe(this._update)),
|
|
...viewFields.map((field) => field.visibleColModel.peek().type.subscribe(this._update)),
|
|
];
|
|
}));
|
|
this.listenTo(this.sortedRows, 'rowNotify', this._update);
|
|
this.autoDispose(this.sortedRows.getKoArray().subscribe(this._update));
|
|
this.autoDispose(this._formatterComp.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[];
|
|
const startIndexForYAxis = this._options.prop('multiseries').peek() ? 2 : 1;
|
|
let series: Series[] = fields
|
|
.filter((field, i) => i < startIndexForYAxis || this._isCompatibleSeries(field.column.peek()))
|
|
.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),
|
|
};
|
|
});
|
|
|
|
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 dataOptions: DataOptions = {};
|
|
const options: ChartOptions = this._options.peek() || {};
|
|
let plotData: PlotData = {data: []};
|
|
|
|
if (isPieLike(this._chartType.peek())) {
|
|
|
|
// Plotly's pie charts have a sort option that is enabled by default. Let's turn it off.
|
|
dataOptions.sort = false;
|
|
|
|
// This line is for labels to stay in order when value changes, which can happen when using
|
|
// charts with linked list.
|
|
sortByXValues(series);
|
|
}
|
|
|
|
if (this._chartType.peek() === 'donut') {
|
|
dataOptions.totalFormatter = this._formatterComp.peek();
|
|
}
|
|
|
|
if (!options.multiseries) {
|
|
plotData = chartFunc(series, options, dataOptions);
|
|
} 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.
|
|
const xvalues = Array.from(new Set(series[1].values));
|
|
for (const gSeries of nseries.values()) {
|
|
|
|
// All series have partial list of values, ie: if some may have Q1, Q2, Q3, Q4 as x values
|
|
// some others might only have Q1. This causes inconsistent result in regard of the order
|
|
// bars will be displayed by plotly (for bar charts). This eventually result in bars not
|
|
// following the sorting order. This line fixes that issue by consolidating all series to
|
|
// have at least on entry of each x values.
|
|
if (this._chartType.peek() === 'bar') {
|
|
if (this._sortSpec?.length) { consolidateValues(gSeries, xvalues); }
|
|
}
|
|
|
|
const part = chartFunc(gSeries, options, dataOptions);
|
|
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<Layout> = defaultsDeep(plotData.layout, getPlotlyLayout(options));
|
|
const config: Partial<Config> = {...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);
|
|
}
|
|
|
|
private _isCompatibleSeries(col: ColumnRec) {
|
|
return isNumericOnly(this._chartType.peek()) ? isNumericLike(col) : true;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* 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<T extends Datum>(groupColumn: T[], valueSeries: Series[]): Map<T, Series[]> {
|
|
const nseries = new Map<T, Series[]>();
|
|
|
|
// 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<Series, ErrorBar> {
|
|
const result = new Map<Series, ErrorBar>();
|
|
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<Layout> {
|
|
// 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<LayoutAxis> = {};
|
|
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);
|
|
|
|
// 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 or there are no viewFields,
|
|
// for example during section removal.
|
|
private _groupDataColId: Computed<number> = Computed.create(this, (use) => {
|
|
const multiseries = use(this._optionsObj.prop('multiseries'));
|
|
const viewFields = use(use(this._section.viewFields).getObservable());
|
|
if (!multiseries || viewFields.length === 0) { 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<number> = 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<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(() => {
|
|
const hiddenColumns = this._section.hiddenColumns.peek();
|
|
const filterFunc = this._isCompatibleSeries.bind(this);
|
|
const nonNumericCount = hiddenColumns.filter((col) => !filterFunc(col)).length;
|
|
return [
|
|
...hiddenColumns
|
|
.filter((col) => filterFunc(col))
|
|
.map((col) => menuItem(
|
|
() => this._configFieldsHelper.addField(col),
|
|
col.label.peek(),
|
|
)),
|
|
nonNumericCount ? menuText(
|
|
`${nonNumericCount} ` + (
|
|
nonNumericCount > 1 ?
|
|
`non-numeric columns are not shown` :
|
|
`non-numeric column is not shown`
|
|
),
|
|
testId('yseries-picker-message'),
|
|
) : null,
|
|
];
|
|
}),
|
|
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(): DomContents {
|
|
|
|
// 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 dom.domComputed((use) => {
|
|
const filterFunc = (field: ViewFieldRec) => this._isCompatibleSeries(use(field.column), use);
|
|
return this._configFieldsHelper.buildVisibleFieldsConfigHelper({
|
|
itemCreateFunc: (field) => this._buildField(field),
|
|
draggableOptions: {
|
|
removeButton: false,
|
|
drag_indicator: cssDragger,
|
|
}, skipFirst, freeze: this._freezeYAxis, filterFunc
|
|
});
|
|
});
|
|
}
|
|
|
|
private _isCompatibleSeries(col: ColumnRec, use: UseCB = unwrap) {
|
|
return isNumericOnly(use(this._chartType)) ? isNumericLike(col, use) : true;
|
|
}
|
|
|
|
}
|
|
|
|
// 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;
|
|
}
|
|
`);
|