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[SIP-5] Refactor Paired t-test (#5762)
* extract TTestTable into another file. * Move into directory. * update proptypes
This commit is contained in:
Krist Wongsuphasawat
committed by
Chris Williams
Chris Williams
parent
b284788fd8
commit
68e7794daf
244
superset/assets/src/visualizations/PairedTTest/TTestTable.jsx
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244
superset/assets/src/visualizations/PairedTTest/TTestTable.jsx
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import dist from 'distributions';
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import React from 'react';
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import { Table, Tr, Td, Thead, Th } from 'reactable';
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import PropTypes from 'prop-types';
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export const dataPropType = PropTypes.arrayOf(PropTypes.shape({
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group: PropTypes.arrayOf(PropTypes.string),
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values: PropTypes.arrayOf(PropTypes.shape({
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x: PropTypes.number,
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y: PropTypes.number,
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})),
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}));
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const propTypes = {
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metric: PropTypes.string.isRequired,
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groups: PropTypes.arrayOf(PropTypes.string).isRequired,
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data: dataPropType.isRequired,
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alpha: PropTypes.number,
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liftValPrec: PropTypes.number,
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pValPrec: PropTypes.number,
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};
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const defaultProps = {
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alpha: 0.05,
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liftValPrec: 4,
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pValPrec: 6,
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};
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class TTestTable extends React.Component {
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constructor(props) {
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super(props);
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this.state = {
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pValues: [],
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liftValues: [],
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control: 0,
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};
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}
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componentWillMount() {
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this.computeTTest(this.state.control); // initially populate table
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}
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getLiftStatus(row) {
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// Get a css class name for coloring
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if (row === this.state.control) {
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return 'control';
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}
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const liftVal = this.state.liftValues[row];
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if (Number.isNaN(liftVal) || !Number.isFinite(liftVal)) {
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return 'invalid'; // infinite or NaN values
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}
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return liftVal >= 0 ? 'true' : 'false'; // green on true, red on false
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}
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getPValueStatus(row) {
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if (row === this.state.control) {
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return 'control';
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}
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const pVal = this.state.pValues[row];
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if (Number.isNaN(pVal) || !Number.isFinite(pVal)) {
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return 'invalid';
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}
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return ''; // p-values won't normally be colored
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}
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getSignificance(row) {
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// Color significant as green, else red
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if (row === this.state.control) {
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return 'control';
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}
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// p-values significant below set threshold
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return this.state.pValues[row] <= this.props.alpha;
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}
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computeLift(values, control) {
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// Compute the lift value between two time series
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let sumValues = 0;
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let sumControl = 0;
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for (let i = 0; i < values.length; i++) {
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sumValues += values[i].y;
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sumControl += control[i].y;
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}
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return (((sumValues - sumControl) / sumControl) * 100)
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.toFixed(this.props.liftValPrec);
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}
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computePValue(values, control) {
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// Compute the p-value from Student's t-test
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// between two time series
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let diffSum = 0;
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let diffSqSum = 0;
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let finiteCount = 0;
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for (let i = 0; i < values.length; i++) {
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const diff = control[i].y - values[i].y;
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if (global.isFinite(diff)) {
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finiteCount++;
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diffSum += diff;
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diffSqSum += diff * diff;
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}
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}
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const tvalue = -Math.abs(diffSum *
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Math.sqrt((finiteCount - 1) /
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(finiteCount * diffSqSum - diffSum * diffSum)));
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try {
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return (2 * new dist.Studentt(finiteCount - 1).cdf(tvalue))
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.toFixed(this.props.pValPrec); // two-sided test
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} catch (err) {
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return NaN;
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}
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}
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computeTTest(control) {
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// Compute lift and p-values for each row
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// against the selected control
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const data = this.props.data;
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const pValues = [];
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const liftValues = [];
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if (!data) {
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return;
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}
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for (let i = 0; i < data.length; i++) {
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if (i === control) {
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pValues.push('control');
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liftValues.push('control');
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} else {
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pValues.push(this.computePValue(data[i].values, data[control].values));
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liftValues.push(this.computeLift(data[i].values, data[control].values));
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}
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}
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this.setState({ pValues, liftValues, control });
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}
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render() {
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const data = this.props.data;
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const metric = this.props.metric;
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const groups = this.props.groups;
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// Render column header for each group
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const columns = groups.map((group, i) => (
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<Th key={i} column={group}>{group}</Th>
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));
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const numGroups = groups.length;
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// Columns for p-value, lift-value, and significance (true/false)
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columns.push(<Th key={numGroups + 1} column="pValue">p-value</Th>);
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columns.push(<Th key={numGroups + 2} column="liftValue">Lift %</Th>);
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columns.push(<Th key={numGroups + 3} column="significant">Significant</Th>);
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const rows = data.map((entry, i) => {
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const values = groups.map((group, j) => ( // group names
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<Td key={j} column={group} data={entry.group[j]} />
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));
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values.push(
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<Td
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key={numGroups + 1}
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className={this.getPValueStatus(i)}
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column="pValue"
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data={this.state.pValues[i]}
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/>,
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);
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values.push(
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<Td
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key={numGroups + 2}
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className={this.getLiftStatus(i)}
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column="liftValue"
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data={this.state.liftValues[i]}
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/>,
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);
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values.push(
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<Td
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key={numGroups + 3}
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className={this.getSignificance(i)}
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column="significant"
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data={this.getSignificance(i)}
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/>,
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);
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return (
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<Tr
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key={i}
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onClick={this.computeTTest.bind(this, i)}
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className={i === this.state.control ? 'control' : ''}
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>
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{values}
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</Tr>
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);
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});
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// When sorted ascending, 'control' will always be at top
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const sortConfig = groups.concat([
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{
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column: 'pValue',
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sortFunction: (a, b) => {
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if (a === 'control') {
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return -1;
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}
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if (b === 'control') {
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return 1;
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}
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return a > b ? 1 : -1; // p-values ascending
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},
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},
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{
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column: 'liftValue',
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sortFunction: (a, b) => {
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if (a === 'control') {
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return -1;
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}
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if (b === 'control') {
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return 1;
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}
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return parseFloat(a) > parseFloat(b) ? -1 : 1; // lift values descending
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},
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},
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{
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column: 'significant',
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sortFunction: (a, b) => {
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if (a === 'control') {
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return -1;
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}
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if (b === 'control') {
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return 1;
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}
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return a > b ? -1 : 1; // significant values first
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},
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},
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]);
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return (
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<div>
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<h3>{metric}</h3>
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<Table
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className="table"
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id={`table_${metric}`}
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sortable={sortConfig}
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>
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<Thead>
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{columns}
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</Thead>
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{rows}
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</Table>
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</div>
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);
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}
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}
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TTestTable.propTypes = propTypes;
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TTestTable.defaultProps = defaultProps;
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export default TTestTable;
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