import ReactDOM from 'react-dom';
import React from 'react';
import PropTypes from 'prop-types';
import d3 from 'd3';
import Mustache from 'mustache';
import { Table, Thead, Th, Tr, Td } from 'reactable';
import MetricOption from '../../components/MetricOption';
import { formatDateThunk } from '../../modules/dates';
import { d3format } from '../../modules/utils';
import InfoTooltipWithTrigger from '../../components/InfoTooltipWithTrigger';
import FormattedNumber from './FormattedNumber';
import SparklineCell from './SparklineCell';
import './TimeTable.css';
const ACCESSIBLE_COLOR_BOUNDS = ['#ca0020', '#0571b0'];
function colorFromBounds(value, bounds, colorBounds = ACCESSIBLE_COLOR_BOUNDS) {
if (bounds) {
const [min, max] = bounds;
const [minColor, maxColor] = colorBounds;
if (min !== null && max !== null) {
const colorScale = d3.scale.linear()
.domain([min, (max + min) / 2, max])
.range([minColor, 'grey', maxColor]);
return colorScale(value);
} else if (min !== null) {
return value >= min ? maxColor : minColor;
} else if (max !== null) {
return value < max ? maxColor : minColor;
}
}
return null;
}
const propTypes = {
className: PropTypes.string,
height: PropTypes.number,
// Example
// {'2018-04-14 00:00:00': { 'SUM(metric_value)': 80031779.40047 }}
data: PropTypes.objectOf(PropTypes.objectOf(PropTypes.number)).isRequired,
columnConfigs: PropTypes.arrayOf(PropTypes.shape({
colType: PropTypes.string,
comparisonType: PropTypes.string,
d3format: PropTypes.string,
key: PropTypes.string,
label: PropTypes.string,
timeLag: PropTypes.number,
})).isRequired,
rows: PropTypes.arrayOf(PropTypes.oneOfType([
PropTypes.shape({
label: PropTypes.string,
}),
PropTypes.shape({
metric_name: PropTypes.string,
}),
])).isRequired,
rowType: PropTypes.oneOf(['column', 'metric']).isRequired,
url: PropTypes.string,
};
const defaultProps = {
className: '',
height: undefined,
url: '',
};
class TimeTable extends React.PureComponent {
renderLeftCell(row) {
const { rowType, url } = this.props;
const context = { metric: row };
const fullUrl = url ? Mustache.render(url, context) : null;
if (rowType === 'column') {
const column = row;
if (fullUrl) {
return (
{column.label}
);
}
return column.label;
}
const metric = row;
return (
);
}
renderSparklineCell(valueField, column, entries) {
let sparkData;
if (column.timeRatio) {
// Period ratio sparkline
sparkData = [];
for (let i = column.timeRatio; i < entries.length; i++) {
const prevData = entries[i - column.timeRatio][valueField];
if (prevData && prevData !== 0) {
sparkData.push(entries[i][valueField] / prevData);
} else {
sparkData.push(null);
}
}
} else {
sparkData = entries.map(d => d[valueField]);
}
const formatDate = formatDateThunk(column.dateFormat);
return (
(
{d3format(column.d3Format, sparkData[index])}
{formatDate(entries[index].time)}
)}
/>
|
);
}
renderValueCell(valueField, column, reversedEntries) {
const recent = reversedEntries[0][valueField];
let v;
let errorMsg;
if (column.colType === 'time') {
// Time lag ratio
const { timeLag } = column;
const totalLag = Object.keys(reversedEntries).length;
if (timeLag > totalLag) {
errorMsg = `The time lag set at ${timeLag} exceeds the length of data at ${reversedEntries.length}. No data available.`;
} else {
v = reversedEntries[timeLag][valueField];
}
if (column.comparisonType === 'diff') {
v = recent - v;
} else if (column.comparisonType === 'perc') {
v = recent / v;
} else if (column.comparisonType === 'perc_change') {
v = (recent / v) - 1;
}
v = v || 0;
} else if (column.colType === 'contrib') {
// contribution to column total
v = recent / Object.keys(reversedEntries[0])
.map(k => k !== 'time' ? reversedEntries[0][k] : null)
.reduce((a, b) => a + b);
} else if (column.colType === 'avg') {
// Average over the last {timeLag}
v = reversedEntries
.map((k, i) => i < column.timeLag ? k[valueField] : 0)
.reduce((a, b) => a + b) / column.timeLag;
}
const color = colorFromBounds(v, column.bounds);
return (
{errorMsg
? ( {errorMsg} )
: (
)}
|
);
}
renderRow(row, entries, reversedEntries) {
const { columnConfigs } = this.props;
const valueField = row.label || row.metric_name;
const leftCell = this.renderLeftCell(row);
return (
|
{leftCell}
|
{columnConfigs.map(c => c.colType === 'spark'
? this.renderSparklineCell(valueField, c, entries)
: this.renderValueCell(valueField, c, reversedEntries))}
);
}
render() {
const {
className,
height,
data,
columnConfigs,
rowType,
rows,
} = this.props;
const entries = Object.keys(data)
.sort()
.map(time => ({ ...data[time], time }));
const reversedEntries = entries.concat().reverse();
const defaultSort = rowType === 'column' ? {
column: columnConfigs[0].key,
direction: 'desc',
} : false;
return (
c.key)}
>
| Metric |
{columnConfigs.map((c, i) => (
{c.label} {c.tooltip && (
)}
| ))}
{rows.map(row => this.renderRow(row, entries, reversedEntries))}
);
}
}
TimeTable.propTypes = propTypes;
TimeTable.defaultProps = defaultProps;
function adaptor(slice, payload) {
const { containerId, formData, datasource } = slice;
const {
column_collection: columnConfigs,
groupby,
metrics,
url,
} = formData;
const { records, columns } = payload.data;
const isGroupBy = groupby.length > 0;
// When there is a "group by",
// each row in the table is a database column
// Otherwise,
// each row in the table is a metric
let rows;
if (isGroupBy) {
rows = columns.map(column => (typeof column === 'object')
? column
: { label: column });
} else {
const metricMap = datasource.metrics
.reduce((acc, current) => {
const map = acc;
map[current.metric_name] = current;
return map;
}, {});
rows = metrics.map(metric => (typeof metric === 'object')
? metric
: metricMap[metric]);
}
// TODO: Better parse this from controls instead of mutative value here.
columnConfigs.forEach((column) => {
const c = column;
if (c.timeLag !== undefined && c.timeLag !== null && c.timeLag !== '') {
c.timeLag = parseInt(c.timeLag, 10);
}
});
ReactDOM.render(
,
document.getElementById(containerId),
);
}
export default adaptor;