Complete general functions
This commit is contained in:
znetsixe
297
helper/nrmse/errorMetric.test.js
Normal file
297
helper/nrmse/errorMetric.test.js
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@@ -0,0 +1,297 @@
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const ErrorMetrics = require('./errorMetrics');
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// Dummy logger for tests
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const logger = {
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error: console.error,
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debug: console.log,
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info: console.log
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};
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const config = {
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thresholds: {
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NRMSE_LOW: 0.05,
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NRMSE_MEDIUM: 0.10,
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NRMSE_HIGH: 0.15,
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LONG_TERM_LOW: 0.02,
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LONG_TERM_MEDIUM: 0.04,
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LONG_TERM_HIGH: 0.06
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}
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};
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class ErrorMetricsTester {
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constructor() {
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this.totalTests = 0;
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this.passedTests = 0;
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this.failedTests = 0;
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this.errorMetrics = new ErrorMetrics(config, logger);
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}
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assert(condition, message) {
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this.totalTests++;
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if (condition) {
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console.log(`✓ PASS: ${message}`);
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this.passedTests++;
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} else {
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console.log(`✗ FAIL: ${message}`);
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this.failedTests++;
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}
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}
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testMeanSquaredError() {
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console.log("\nTesting Mean Squared Error...");
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const predicted = [1, 2, 3];
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const measured = [1, 3, 5];
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const mse = this.errorMetrics.meanSquaredError(predicted, measured);
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this.assert(Math.abs(mse - 1.67) < 0.1, "MSE correctly calculated");
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}
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testRootMeanSquaredError() {
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console.log("\nTesting Root Mean Squared Error...");
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const predicted = [1, 2, 3];
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const measured = [1, 3, 5];
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const rmse = this.errorMetrics.rootMeanSquaredError(predicted, measured);
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this.assert(Math.abs(rmse - 1.29) < 0.1, "RMSE correctly calculated");
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}
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testNormalizedRMSE() {
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console.log("\nTesting Normalized RMSE...");
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const predicted = [100, 102, 104];
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const measured = [98, 103, 107];
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const processMin = 90, processMax = 110;
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const nrmse = this.errorMetrics.normalizedRootMeanSquaredError(predicted, measured, processMin, processMax);
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this.assert(typeof nrmse === 'number' && nrmse > 0, "Normalized RMSE calculated correctly");
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}
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testNormalizeUsingRealtime() {
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console.log("\nTesting Normalize Using Realtime...");
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const predicted = [100, 102, 104];
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const measured = [98, 103, 107];
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try {
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const nrmse = this.errorMetrics.normalizeUsingRealtime(predicted, measured);
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this.assert(typeof nrmse === 'number' && nrmse > 0, "Normalize using realtime calculated correctly");
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} catch (error) {
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this.assert(false, `Normalize using realtime failed: ${error.message}`);
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}
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// Test with identical values to check error handling
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const sameValues = [100, 100, 100];
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try {
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this.errorMetrics.normalizeUsingRealtime(sameValues, sameValues);
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this.assert(false, "Should throw error with identical values");
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} catch (error) {
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this.assert(true, "Correctly throws error when min/max are the same");
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}
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}
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testLongTermNRMSD() {
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console.log("\nTesting Long Term NRMSD Accumulation...");
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// Reset the accumulation values
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this.errorMetrics.cumNRMSD = 0;
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this.errorMetrics.cumCount = 0;
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let lastValue = 0;
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for (let i = 0; i < 100; i++) {
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lastValue = this.errorMetrics.longTermNRMSD(0.1 + i * 0.001);
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}
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this.assert(
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this.errorMetrics.cumCount === 100 &&
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this.errorMetrics.cumNRMSD !== 0 &&
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lastValue !== 0,
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"Long term NRMSD accumulates over 100 iterations"
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);
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// Test that values are returned only after accumulating 100 samples
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this.errorMetrics.cumNRMSD = 0;
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this.errorMetrics.cumCount = 0;
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for (let i = 0; i < 99; i++) {
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const result = this.errorMetrics.longTermNRMSD(0.1);
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this.assert(result === 0, "No longTermNRMSD returned before 100 samples");
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}
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// Use a different value for the 100th sample to ensure a non-zero result
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const result = this.errorMetrics.longTermNRMSD(0.2);
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this.assert(result !== 0, "longTermNRMSD returned after 100 samples");
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}
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testDetectImmediateDrift() {
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console.log("\nTesting Immediate Drift Detection...");
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// Test high drift
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let drift = this.errorMetrics.detectImmediateDrift(config.thresholds.NRMSE_HIGH + 0.01);
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this.assert(drift.level === 3, "Detects high immediate drift correctly");
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// Test medium drift
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drift = this.errorMetrics.detectImmediateDrift(config.thresholds.NRMSE_MEDIUM + 0.01);
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this.assert(drift.level === 2, "Detects medium immediate drift correctly");
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// Test low drift
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drift = this.errorMetrics.detectImmediateDrift(config.thresholds.NRMSE_LOW + 0.01);
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this.assert(drift.level === 1, "Detects low immediate drift correctly");
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// Test no drift
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drift = this.errorMetrics.detectImmediateDrift(config.thresholds.NRMSE_LOW - 0.01);
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this.assert(drift.level === 0, "Detects no immediate drift correctly");
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}
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testDetectLongTermDrift() {
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console.log("\nTesting Long Term Drift Detection...");
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// Test high drift
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let drift = this.errorMetrics.detectLongTermDrift(config.thresholds.LONG_TERM_HIGH + 0.01);
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this.assert(drift.level === 3, "Detects high long-term drift correctly");
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// Test medium drift
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drift = this.errorMetrics.detectLongTermDrift(config.thresholds.LONG_TERM_MEDIUM + 0.01);
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this.assert(drift.level === 2, "Detects medium long-term drift correctly");
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// Test low drift
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drift = this.errorMetrics.detectLongTermDrift(config.thresholds.LONG_TERM_LOW + 0.01);
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this.assert(drift.level === 1, "Detects low long-term drift correctly");
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// Test no drift
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drift = this.errorMetrics.detectLongTermDrift(config.thresholds.LONG_TERM_LOW - 0.01);
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this.assert(drift.level === 0, "Detects no long-term drift correctly");
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// Test negative drift values
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drift = this.errorMetrics.detectLongTermDrift(-config.thresholds.LONG_TERM_HIGH - 0.01);
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this.assert(drift.level === 3, "Detects negative high long-term drift correctly");
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}
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testDriftDetection() {
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console.log("\nTesting Combined Drift Detection...");
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let nrmseHigh = config.thresholds.NRMSE_HIGH + 0.01;
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let ltNRMSD = 0;
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let result = this.errorMetrics.detectDrift(nrmseHigh, ltNRMSD);
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this.assert(
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result !== null &&
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result.ImmDrift &&
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result.ImmDrift.level === 3 &&
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result.LongTermDrift.level === 0,
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"Detects high immediate drift with no long-term drift"
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);
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nrmseHigh = config.thresholds.NRMSE_LOW - 0.01;
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ltNRMSD = config.thresholds.LONG_TERM_MEDIUM + 0.01;
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result = this.errorMetrics.detectDrift(nrmseHigh, ltNRMSD);
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this.assert(
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result !== null &&
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result.ImmDrift.level === 0 &&
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result.LongTermDrift &&
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result.LongTermDrift.level === 2,
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"Detects medium long-term drift with no immediate drift"
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);
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nrmseHigh = config.thresholds.NRMSE_MEDIUM + 0.01;
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ltNRMSD = config.thresholds.LONG_TERM_MEDIUM + 0.01;
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result = this.errorMetrics.detectDrift(nrmseHigh, ltNRMSD);
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this.assert(
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result.ImmDrift.level === 2 &&
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result.LongTermDrift.level === 2,
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"Detects both medium immediate and medium long-term drift"
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);
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nrmseHigh = config.thresholds.NRMSE_LOW - 0.01;
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ltNRMSD = config.thresholds.LONG_TERM_LOW - 0.01;
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result = this.errorMetrics.detectDrift(nrmseHigh, ltNRMSD);
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this.assert(
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result.ImmDrift.level === 0 &&
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result.LongTermDrift.level === 0,
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"No significant drift detected when under thresholds"
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);
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}
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testAssessDrift() {
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console.log("\nTesting assessDrift function...");
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// Reset accumulation for testing
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this.errorMetrics.cumNRMSD = 0;
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this.errorMetrics.cumCount = 0;
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const predicted = [100, 101, 102, 103];
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const measured = [90, 91, 92, 93];
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const processMin = 90, processMax = 110;
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let result = this.errorMetrics.assessDrift(predicted, measured, processMin, processMax);
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this.assert(
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result !== null &&
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typeof result.nrmse === 'number' &&
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typeof result.longTermNRMSD === 'number' &&
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typeof result.immediateLevel === 'number' &&
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typeof result.immediateFeedback === 'string' &&
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typeof result.longTermLevel === 'number' &&
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typeof result.longTermFeedback === 'string',
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"assessDrift returns complete result structure"
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);
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this.assert(
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result.immediateLevel > 0,
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"assessDrift detects immediate drift with significant difference"
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);
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// Test with identical values
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result = this.errorMetrics.assessDrift(predicted, predicted, processMin, processMax);
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this.assert(
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result.nrmse === 0 &&
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result.immediateLevel === 0,
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"assessDrift indicates no immediate drift when predicted equals measured"
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);
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// Test with slight drift
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const measuredSlight = [100, 100.5, 101, 101.5];
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result = this.errorMetrics.assessDrift(predicted, measuredSlight, processMin, processMax);
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this.assert(
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result !== null &&
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result.nrmse < 0.05 &&
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(result.immediateLevel < 2),
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"assessDrift returns appropriate levels for slight drift"
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);
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// Test long-term drift accumulation
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for (let i = 0; i < 100; i++) {
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this.errorMetrics.assessDrift(
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predicted,
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measured.map(m => m + (Math.random() * 2 - 1)), // Add small random fluctuation
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processMin,
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processMax
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);
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}
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result = this.errorMetrics.assessDrift(predicted, measured, processMin, processMax);
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this.assert(
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result.longTermNRMSD !== 0,
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"Long-term drift accumulates over multiple assessments"
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);
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}
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async runAllTests() {
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console.log("\nStarting Error Metrics Tests...\n");
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this.testMeanSquaredError();
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this.testRootMeanSquaredError();
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this.testNormalizedRMSE();
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this.testNormalizeUsingRealtime();
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this.testLongTermNRMSD();
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this.testDetectImmediateDrift();
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this.testDetectLongTermDrift();
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this.testDriftDetection();
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this.testAssessDrift();
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console.log("\nTest Summary:");
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console.log(`Total Tests: ${this.totalTests}`);
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console.log(`Passed: ${this.passedTests}`);
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console.log(`Failed: ${this.failedTests}`);
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process.exit(this.failedTests > 0 ? 1 : 0);
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}
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}
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// Run all tests
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const tester = new ErrorMetricsTester();
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tester.runAllTests().catch(console.error);
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154
helper/nrmse/errorMetrics.js
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154
helper/nrmse/errorMetrics.js
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@@ -0,0 +1,154 @@
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//load local dependencies
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const EventEmitter = require('events');
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//load all config modules
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const defaultConfig = require('./nrmseConfig.json');
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const ConfigUtils = require('../configUtils');
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class ErrorMetrics {
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constructor(config = {}, logger) {
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this.emitter = new EventEmitter(); // Own EventEmitter
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this.configUtils = new ConfigUtils(defaultConfig);
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this.config = this.configUtils.initConfig(config);
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// Init after config is set
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this.logger = logger;
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// For long-term NRMSD accumulation
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this.cumNRMSD = 0;
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this.cumCount = 0;
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}
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//INCLUDE timestamps in the next update OLIFANT
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meanSquaredError(predicted, measured) {
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if (predicted.length !== measured.length) {
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this.logger.error("Comparing MSE Arrays must have the same length.");
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return 0;
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}
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let sumSqError = 0;
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for (let i = 0; i < predicted.length; i++) {
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const err = predicted[i] - measured[i];
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sumSqError += err * err;
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}
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return sumSqError / predicted.length;
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}
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rootMeanSquaredError(predicted, measured) {
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return Math.sqrt(this.meanSquaredError(predicted, measured));
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}
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normalizedRootMeanSquaredError(predicted, measured, processMin, processMax) {
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const range = processMax - processMin;
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if (range <= 0) {
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this.logger.error("Invalid process range: processMax must be greater than processMin.");
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}
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const rmse = this.rootMeanSquaredError(predicted, measured);
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return rmse / range;
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}
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longTermNRMSD(input) {
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const storedNRMSD = this.cumNRMSD;
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const storedCount = this.cumCount;
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const newCount = storedCount + 1;
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// Update cumulative values
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this.cumCount = newCount;
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// Calculate new running average
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if (storedCount === 0) {
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this.cumNRMSD = input; // First value
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} else {
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// Running average formula: newAvg = oldAvg + (newValue - oldAvg) / newCount
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this.cumNRMSD = storedNRMSD + (input - storedNRMSD) / newCount;
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}
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if(newCount >= 100) {
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// Return the current NRMSD value, not just the contribution from this sample
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return this.cumNRMSD;
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}
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return 0;
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}
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normalizeUsingRealtime(predicted, measured) {
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const realtimeMin = Math.min(Math.min(...predicted), Math.min(...measured));
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const realtimeMax = Math.max(Math.max(...predicted), Math.max(...measured));
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const range = realtimeMax - realtimeMin;
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if (range <= 0) {
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throw new Error("Invalid process range: processMax must be greater than processMin.");
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}
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const rmse = this.rootMeanSquaredError(predicted, measured);
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return rmse / range;
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}
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detectImmediateDrift(nrmse) {
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let ImmDrift = {};
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this.logger.debug(`checking immediate drift with thresholds : ${this.config.thresholds.NRMSE_HIGH} ${this.config.thresholds.NRMSE_MEDIUM} ${this.config.thresholds.NRMSE_LOW}`);
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switch (true) {
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case( nrmse > this.config.thresholds.NRMSE_HIGH ) :
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ImmDrift = {level : 3 , feedback : "High immediate drift detected"};
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break;
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case( nrmse > this.config.thresholds.NRMSE_MEDIUM ) :
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ImmDrift = {level : 2 , feedback : "Medium immediate drift detected"};
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break;
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case(nrmse > this.config.thresholds.NRMSE_LOW ):
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ImmDrift = {level : 1 , feedback : "Low immediate drift detected"};
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break;
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default:
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ImmDrift = {level : 0 , feedback : "No drift detected"};
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}
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return ImmDrift;
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}
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detectLongTermDrift(longTermNRMSD) {
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let LongTermDrift = {};
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this.logger.debug(`checking longterm drift with thresholds : ${this.config.thresholds.LONG_TERM_HIGH} ${this.config.thresholds.LONG_TERM_MEDIUM} ${this.config.thresholds.LONG_TERM_LOW}`);
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switch (true) {
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case(Math.abs(longTermNRMSD) > this.config.thresholds.LONG_TERM_HIGH) :
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LongTermDrift = {level : 3 , feedback : "High long-term drift detected"};
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break;
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case (Math.abs(longTermNRMSD) > this.config.thresholds.LONG_TERM_MEDIUM) :
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LongTermDrift = {level : 2 , feedback : "Medium long-term drift detected"};
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break;
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case ( Math.abs(longTermNRMSD) > this.config.thresholds.LONG_TERM_LOW ) :
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LongTermDrift = {level : 1 , feedback : "Low long-term drift detected"};
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break;
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default:
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LongTermDrift = {level : 0 , feedback : "No drift detected"};
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}
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return LongTermDrift;
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}
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detectDrift(nrmse, longTermNRMSD) {
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const ImmDrift = this.detectImmediateDrift(nrmse);
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const LongTermDrift = this.detectLongTermDrift(longTermNRMSD);
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return { ImmDrift, LongTermDrift };
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}
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// asses the drift
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assessDrift(predicted, measured, processMin, processMax) {
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// Compute NRMSE and check for immediate drift
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const nrmse = this.normalizedRootMeanSquaredError(predicted, measured, processMin, processMax);
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this.logger.debug(`NRMSE: ${nrmse}`);
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// cmopute long-term NRMSD and add result to cumalitve NRMSD
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const longTermNRMSD = this.longTermNRMSD(nrmse);
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// return the drift
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// Return the drift assessment object
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const driftAssessment = this.detectDrift(nrmse, longTermNRMSD);
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return {
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nrmse,
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longTermNRMSD,
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immediateLevel: driftAssessment.ImmDrift.level,
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immediateFeedback: driftAssessment.ImmDrift.feedback,
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longTermLevel: driftAssessment.LongTermDrift.level,
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longTermFeedback: driftAssessment.LongTermDrift.feedback
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};
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}
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}
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module.exports = ErrorMetrics;
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138
helper/nrmse/nrmseConfig.json
Normal file
138
helper/nrmse/nrmseConfig.json
Normal file
@@ -0,0 +1,138 @@
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{
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"general": {
|
||||
"name": {
|
||||
"default": "ErrorMetrics",
|
||||
"rules": {
|
||||
"type": "string",
|
||||
"description": "A human-readable name for the configuration."
|
||||
}
|
||||
},
|
||||
"id": {
|
||||
"default": null,
|
||||
"rules": {
|
||||
"type": "string",
|
||||
"nullable": true,
|
||||
"description": "A unique identifier for this configuration, assigned dynamically when needed."
|
||||
}
|
||||
},
|
||||
"unit": {
|
||||
"default": "unitless",
|
||||
"rules": {
|
||||
"type": "string",
|
||||
"description": "The unit used for the state values (e.g., 'meters', 'seconds', 'unitless')."
|
||||
}
|
||||
},
|
||||
"logging": {
|
||||
"logLevel": {
|
||||
"default": "info",
|
||||
"rules": {
|
||||
"type": "enum",
|
||||
"values": [
|
||||
{
|
||||
"value": "debug",
|
||||
"description": "Log messages are printed for debugging purposes."
|
||||
},
|
||||
{
|
||||
"value": "info",
|
||||
"description": "Informational messages are printed."
|
||||
},
|
||||
{
|
||||
"value": "warn",
|
||||
"description": "Warning messages are printed."
|
||||
},
|
||||
{
|
||||
"value": "error",
|
||||
"description": "Error messages are printed."
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"enabled": {
|
||||
"default": true,
|
||||
"rules": {
|
||||
"type": "boolean",
|
||||
"description": "Indicates whether logging is active. If true, log messages will be generated."
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"functionality": {
|
||||
"softwareType": {
|
||||
"default": "errorMetrics",
|
||||
"rules": {
|
||||
"type": "string",
|
||||
"description": "Logical name identifying the software type."
|
||||
}
|
||||
},
|
||||
"role": {
|
||||
"default": "error calculation",
|
||||
"rules": {
|
||||
"type": "string",
|
||||
"description": "Functional role within the system."
|
||||
}
|
||||
}
|
||||
},
|
||||
"mode": {
|
||||
"current": {
|
||||
"default": "active",
|
||||
"rules": {
|
||||
"type": "enum",
|
||||
"values": [
|
||||
{
|
||||
"value": "active",
|
||||
"description": "The error metrics calculation is active."
|
||||
},
|
||||
{
|
||||
"value": "inactive",
|
||||
"description": "The error metrics calculation is inactive."
|
||||
}
|
||||
],
|
||||
"description": "The operational mode of the error metrics calculation."
|
||||
}
|
||||
}
|
||||
},
|
||||
"thresholds": {
|
||||
"NRMSE_LOW": {
|
||||
"default": 0.05,
|
||||
"rules": {
|
||||
"type": "number",
|
||||
"description": "Low threshold for normalized root mean squared error."
|
||||
}
|
||||
},
|
||||
"NRMSE_MEDIUM": {
|
||||
"default": 0.10,
|
||||
"rules": {
|
||||
"type": "number",
|
||||
"description": "Medium threshold for normalized root mean squared error."
|
||||
}
|
||||
},
|
||||
"NRMSE_HIGH": {
|
||||
"default": 0.15,
|
||||
"rules": {
|
||||
"type": "number",
|
||||
"description": "High threshold for normalized root mean squared error."
|
||||
}
|
||||
},
|
||||
"LONG_TERM_LOW": {
|
||||
"default": 0.02,
|
||||
"rules": {
|
||||
"type": "number",
|
||||
"description": "Low threshold for long-term normalized root mean squared deviation."
|
||||
}
|
||||
},
|
||||
"LONG_TERM_MEDIUM": {
|
||||
"default": 0.04,
|
||||
"rules": {
|
||||
"type": "number",
|
||||
"description": "Medium threshold for long-term normalized root mean squared deviation."
|
||||
}
|
||||
},
|
||||
"LONG_TERM_HIGH": {
|
||||
"default": 0.06,
|
||||
"rules": {
|
||||
"type": "number",
|
||||
"description": "High threshold for long-term normalized root mean squared deviation."
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user