server.ts を更新
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385
server.ts
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385
server.ts
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// package.json dependencies needed:
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// npm install express mathjs lodash
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// npm install -D @types/express @types/node @types/lodash typescript ts-node
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import express from 'express';
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import * as math from 'mathjs';
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import * as _ from 'lodash';
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const app = express();
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app.use(express.json());
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// Types for our data structures
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interface DataSeries {
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values: number[];
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labels?: string[];
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}
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interface Condition {
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field: string;
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operator: '>' | '<' | '=' | '>=' | '<=' | '!=';
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value: number | string;
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}
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interface ApiResponse<T> {
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success: boolean;
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data?: T;
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error?: string;
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}
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// Helper function for error handling
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const handleError = (error: unknown): string => {
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return error instanceof Error ? error.message : 'Unknown error';
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};
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// Core statistical functions
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class AnalyticsEngine {
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// Apply conditions to filter data
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private applyConditions(series: DataSeries, conditions: Condition[] = []): number[] {
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if (conditions.length === 0) return series.values;
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// For now, just return all values - you'd implement condition logic here
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// This would involve checking conditions against associated metadata
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return series.values;
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}
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// Remove duplicates from series
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unique(series: DataSeries): number[] {
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return _.uniq(series.values);
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}
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// Calculate mean with optional conditions
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mean(series: DataSeries, conditions: Condition[] = []): number {
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const filteredValues = this.applyConditions(series, conditions);
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if (filteredValues.length === 0) throw new Error('No data points match conditions');
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return Number(math.mean(filteredValues));
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}
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// Count values with optional conditions
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count(series: DataSeries, conditions: Condition[] = []): number {
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const filteredValues = this.applyConditions(series, conditions);
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return filteredValues.length;
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}
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// Calculate variance
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variance(series: DataSeries, conditions: Condition[] = []): number {
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const filteredValues = this.applyConditions(series, conditions);
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if (filteredValues.length === 0) throw new Error('No data points match conditions');
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return Number(math.variance(filteredValues));
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}
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// Calculate standard deviation
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standardDeviation(series: DataSeries, conditions: Condition[] = []): number {
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const filteredValues = this.applyConditions(series, conditions);
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if (filteredValues.length === 0) throw new Error('No data points match conditions');
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return Number(math.std(filteredValues));
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}
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// Calculate percentile/quantile
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percentile(
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series: DataSeries,
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percent: number,
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ascending: boolean = true,
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conditions: Condition[] = []
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): number {
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const filteredValues = this.applyConditions(series, conditions);
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if (filteredValues.length === 0) throw new Error('No data points match conditions');
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const sorted = ascending ?
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_.sortBy(filteredValues) :
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_.sortBy(filteredValues).reverse();
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const index = (percent / 100) * (sorted.length - 1);
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const lower = Math.floor(index);
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const upper = Math.ceil(index);
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const weight = index % 1;
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return sorted[lower] * (1 - weight) + sorted[upper] * weight;
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}
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// Calculate median (50th percentile)
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median(series: DataSeries, conditions: Condition[] = []): number {
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return this.percentile(series, 50, true, conditions);
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}
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// Calculate mode (most frequent value)
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mode(series: DataSeries, conditions: Condition[] = []): number[] {
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const filteredValues = this.applyConditions(series, conditions);
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const frequency = _.countBy(filteredValues);
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const maxFreq = Math.max(...Object.values(frequency));
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return Object.keys(frequency)
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.filter(key => frequency[key] === maxFreq)
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.map(Number);
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}
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// Rank values and get top N
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topN(
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series: DataSeries,
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n: number,
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ascending: boolean = false,
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conditions: Condition[] = []
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): number[] {
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const filteredValues = this.applyConditions(series, conditions);
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const sorted = ascending ?
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_.sortBy(filteredValues) :
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_.sortBy(filteredValues).reverse();
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return sorted.slice(0, n);
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}
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// Get maximum value
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max(series: DataSeries, conditions: Condition[] = []): number {
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const filteredValues = this.applyConditions(series, conditions);
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if (filteredValues.length === 0) throw new Error('No data points match conditions');
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return Math.max(...filteredValues);
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}
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// Get minimum value
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min(series: DataSeries, conditions: Condition[] = []): number {
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const filteredValues = this.applyConditions(series, conditions);
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if (filteredValues.length === 0) throw new Error('No data points match conditions');
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return Math.min(...filteredValues);
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}
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// Calculate percent change
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percentChange(series: DataSeries, step: number = 1): number[] {
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const values = series.values;
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const changes: number[] = [];
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for (let i = step; i < values.length; i++) {
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const change = ((values[i] - values[i - step]) / values[i - step]) * 100;
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changes.push(change);
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}
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return changes;
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}
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// Basic correlation between two series
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correlation(series1: DataSeries, series2: DataSeries): number {
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if (series1.values.length !== series2.values.length) {
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throw new Error('Series must have same length for correlation');
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}
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const x = series1.values;
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const y = series2.values;
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const n = x.length;
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const sumX = _.sum(x);
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const sumY = _.sum(y);
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const sumXY = _.sum(x.map((xi, i) => xi * y[i]));
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const sumX2 = _.sum(x.map(xi => xi * xi));
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const sumY2 = _.sum(y.map(yi => yi * yi));
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const numerator = n * sumXY - sumX * sumY;
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const denominator = Math.sqrt((n * sumX2 - sumX * sumX) * (n * sumY2 - sumY * sumY));
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return numerator / denominator;
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}
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}
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// Initialize analytics engine
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const analytics = new AnalyticsEngine();
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// API Routes
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app.get('/api/health', (req, res) => {
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res.json({ status: 'OK', timestamp: new Date().toISOString() });
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});
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// Unique values endpoint
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app.post('/api/unique', (req, res) => {
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try {
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const { series }: { series: DataSeries } = req.body;
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const result = analytics.unique(series);
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res.json({ success: true, data: result } as ApiResponse<number[]>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number[]>);
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}
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});
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// Mean calculation endpoint
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app.post('/api/mean', (req, res) => {
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try {
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const { series, conditions = [] }: { series: DataSeries; conditions?: Condition[] } = req.body;
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const result = analytics.mean(series, conditions);
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res.json({ success: true, data: result } as ApiResponse<number>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number>);
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}
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});
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// Count endpoint
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app.post('/api/count', (req, res) => {
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try {
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const { series, conditions = [] }: { series: DataSeries; conditions?: Condition[] } = req.body;
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const result = analytics.count(series, conditions);
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res.json({ success: true, data: result } as ApiResponse<number>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number>);
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}
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});
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// Variance endpoint
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app.post('/api/variance', (req, res) => {
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try {
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const { series, conditions = [] }: { series: DataSeries; conditions?: Condition[] } = req.body;
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const result = analytics.variance(series, conditions);
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res.json({ success: true, data: result } as ApiResponse<number>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number>);
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}
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});
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// Standard deviation endpoint
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app.post('/api/std', (req, res) => {
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try {
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const { series, conditions = [] }: { series: DataSeries; conditions?: Condition[] } = req.body;
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const result = analytics.standardDeviation(series, conditions);
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res.json({ success: true, data: result } as ApiResponse<number>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number>);
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}
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});
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// Percentile endpoint
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app.post('/api/percentile', (req, res) => {
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try {
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const {
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series,
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percent,
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ascending = true,
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conditions = []
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}: {
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series: DataSeries;
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percent: number;
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ascending?: boolean;
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conditions?: Condition[]
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} = req.body;
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const result = analytics.percentile(series, percent, ascending, conditions);
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res.json({ success: true, data: result } as ApiResponse<number>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number>);
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}
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});
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// Median endpoint
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app.post('/api/median', (req, res) => {
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try {
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const { series, conditions = [] }: { series: DataSeries; conditions?: Condition[] } = req.body;
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const result = analytics.median(series, conditions);
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res.json({ success: true, data: result } as ApiResponse<number>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number>);
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}
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});
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// Mode endpoint
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app.post('/api/mode', (req, res) => {
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try {
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const { series, conditions = [] }: { series: DataSeries; conditions?: Condition[] } = req.body;
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const result = analytics.mode(series, conditions);
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res.json({ success: true, data: result } as ApiResponse<number[]>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number[]>);
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}
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});
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// Top N endpoint
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app.post('/api/topn', (req, res) => {
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try {
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const {
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series,
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n,
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ascending = false,
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conditions = []
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}: {
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series: DataSeries;
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n: number;
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ascending?: boolean;
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conditions?: Condition[]
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} = req.body;
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const result = analytics.topN(series, n, ascending, conditions);
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res.json({ success: true, data: result } as ApiResponse<number[]>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number[]>);
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}
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});
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// Max/Min endpoints
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app.post('/api/max', (req, res) => {
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try {
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const { series, conditions = [] }: { series: DataSeries; conditions?: Condition[] } = req.body;
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const result = analytics.max(series, conditions);
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res.json({ success: true, data: result } as ApiResponse<number>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number>);
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}
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});
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app.post('/api/min', (req, res) => {
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try {
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const { series, conditions = [] }: { series: DataSeries; conditions?: Condition[] } = req.body;
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const result = analytics.min(series, conditions);
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res.json({ success: true, data: result } as ApiResponse<number>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number>);
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}
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});
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// Percent change endpoint
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app.post('/api/percent-change', (req, res) => {
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try {
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const { series, step = 1 }: { series: DataSeries; step?: number } = req.body;
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const result = analytics.percentChange(series, step);
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res.json({ success: true, data: result } as ApiResponse<number[]>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number[]>);
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}
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});
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// Correlation endpoint
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app.post('/api/correlation', (req, res) => {
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try {
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const { series1, series2 }: { series1: DataSeries; series2: DataSeries } = req.body;
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const result = analytics.correlation(series1, series2);
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res.json({ success: true, data: result } as ApiResponse<number>);
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} catch (error) {
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const errorMessage = handleError(error);
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res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number>);
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}
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});
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// Error handling middleware
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app.use((err: Error, req: express.Request, res: express.Response, next: express.NextFunction) => {
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console.error(err.stack);
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res.status(500).json({ success: false, error: 'Internal server error' } as ApiResponse<any>);
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});
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// Start server
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const PORT = process.env.PORT || 3000;
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app.listen(PORT, () => {
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console.log(`Analytics API server running on port ${PORT}`);
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console.log(`Health check: http://localhost:${PORT}/api/health`);
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});
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export default app;
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