aboutsummaryrefslogtreecommitdiff
path: root/modules/test/test-predictor-accuracy.js
diff options
context:
space:
mode:
Diffstat (limited to 'modules/test/test-predictor-accuracy.js')
-rw-r--r--modules/test/test-predictor-accuracy.js44
1 files changed, 43 insertions, 1 deletions
diff --git a/modules/test/test-predictor-accuracy.js b/modules/test/test-predictor-accuracy.js
index 1a79167..3688b03 100644
--- a/modules/test/test-predictor-accuracy.js
+++ b/modules/test/test-predictor-accuracy.js
@@ -149,7 +149,7 @@ function ok(name, cond, detail) {
p.notePrediction('read the logs', 'test');
p.recordResult(p._extractFeatures('read the logs'), 0.5, 1, true, { task: 'read the logs' });
const rec = p._dataPoints[p._dataPoints.length - 1];
- ok('K1 errorPct capped at 500%', rec.errorPct <= 5, 'errorPct=' + rec.errorPct);
+ ok('K1 errorPct is stored raw', rec.errorPct > 5, 'errorPct=' + rec.errorPct);
}
// L. a tool/loop prediction is never consumed by the similarity fallback
@@ -205,5 +205,47 @@ function ok(name, cond, detail) {
'total=' + p._accuracy.total + ' pending=' + p._pending.length);
}
+
+// Q. an aborted 0.079 s run must not drive the next prediction to zero (§5 point 1→2)
+{
+ const { p } = mk();
+ const task = 'paste a 2158 char status report';
+ p.notePrediction(task, 'loop');
+ p.recordResult(p._extractFeatures(task), 0.079, 1, true, { task });
+ const next = p.notePrediction(task, 'loop');
+ ok('Q1 prediction is never 0 s', next.predictedDuration >= 1, 'pred=' + next.predictedDuration);
+ ok('Q2 the aborted run is marked unusable', p._dataPoints[0].usable === false);
+ ok('Q3 it never trains _findSimilar', p._findSimilar(p._extractFeatures(task)).length === 0);
+}
+
+// R. the persisted field is a SUM and the display divides by the paired count
+{
+ const { p, out, term } = mk(true);
+ for (let i = 0; i < 2; i++) {
+ const task = 'read the logs';
+ p.notePrediction(task, 'loop');
+ p.recordResult(p._extractFeatures(task), 20, 2, true, { task }); // 15 s predicted vs 20 s observed
+ }
+ p._saveNow();
+ const blob = JSON.parse(term.fs.readFile('/system/metrics/predictor.json'));
+ ok('R1 stored accumulator is a sum and is named errorSum', typeof blob.errorSum === 'number' && !('mape' in blob),
+ JSON.stringify(Object.keys(blob)));
+ out.length = 0; p.showStatus();
+ const line = out.find(l => l.includes('Accuracy')) || '';
+ ok('R2 display shows the mean with its sample count', /Accuracy: \d+% \(2\/2 paired\) · mean error \d+%/.test(line), line.trim());
+}
+
+// S. a floored prediction is consumed but not scored as error (§5 defect C)
+{
+ const { p } = mk();
+ const pred = p.notePrediction('read the logs', 'test');
+ p._pending[0].floored = true;
+ p._pending[0].predictedDuration = 1;
+ p.recordResult(p._extractFeatures('read the logs'), 54.7, 2, true, { task: 'read the logs' });
+ ok('S1 floored prediction does not enter accuracy', p._accuracy.total === 0, 'total=' + p._accuracy.total);
+ ok('S2 it is still recorded and marked unscored', p._dataPoints[0].scored === false);
+ ok('S3 pending consumed', p._pending.length === 0);
+}
+
console.log(passes + '/' + (passes + fails) + ' PASS');
process.exit(fails ? 1 : 0);