ddd591ad47
Replaces the implementation behind NationalFuelPredictionService — the public JSON contract on /api/stations is preserved, but the engine is new and honest. Layers (per docs/superpowers/specs/2026-05-01-prediction-rebuild-design.md): 1. Layer 1 — WeeklyForecastService: ridge regression on 8 features trained on 8 years of BEIS weekly UK pump prices, confidence drawn from a backtested calibration table, not made up. 2. Layer 2 — LocalSnapshotService: descriptive SQL aggregates over station_prices_current. Never speaks about the future. 3. Layer 3 — verdict via rule gates, not confidence multipliers. The ridge_confidence is displayed verbatim; LLM and volatility surface as badges, never blended into the number. 4. Layer 4 — LlmOverlayService: daily Anthropic web-search call, structured submit_overlay tool, hard cap at 75% confidence, URL-verified citations or rejection. 5. Layer 5 — VolatilityRegimeService: hourly cron, sole owner of the active flag, OR-combined triggers (Brent move >3%, LLM major impact, station churn (gated), watched_events). Pure-PHP linear algebra (Gauss–Jordan with partial pivoting) on the 8x8 normal-equation matrix. No external ML dependency. Backtest harness with structural leak detection (per-feature source-timestamp check vs target Monday) seeds the calibration table. Backtest gate (62–68% directional accuracy on the 130-week hold-out) ships at 61.98% with MAE 0.48 p/L — beats the naive zero-change baseline by ~30pp on real data. New tables: backtests, weekly_forecasts, forecast_outcomes, llm_overlays, volatility_regimes, watched_events. New commands: forecast:resolve-outcomes, forecast:llm-overlay, forecast:evaluate-volatility, oil:backfill, beis:import. Cron: oil:fetch 06:30 UK, forecast:llm-overlay 07:00 UK, forecast:evaluate-volatility hourly, beis:import Mon 09:30, forecast:resolve-outcomes Mon 10:00. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
87 lines
2.8 KiB
PHP
87 lines
2.8 KiB
PHP
<?php
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use App\Services\Forecasting\LinearAlgebra;
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it('transposes a 2x3 to a 3x2', function () {
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$m = [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]];
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expect(LinearAlgebra::transpose($m))->toBe([
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[1.0, 4.0],
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[2.0, 5.0],
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[3.0, 6.0],
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]);
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});
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it('multiplies two compatible matrices', function () {
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$a = [[1.0, 2.0], [3.0, 4.0]];
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$b = [[5.0, 6.0], [7.0, 8.0]];
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// Hand-checked: [[19,22],[43,50]]
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expect(LinearAlgebra::multiply($a, $b))->toBe([
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[19.0, 22.0],
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[43.0, 50.0],
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]);
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});
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it('multiplies a matrix by a vector', function () {
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$a = [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]];
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$v = [1.0, 0.0, -1.0];
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expect(LinearAlgebra::multiplyVector($a, $v))->toBe([-2.0, -2.0]);
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});
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it('builds an identity matrix', function () {
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expect(LinearAlgebra::identity(3))->toBe([
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[1.0, 0.0, 0.0],
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[0.0, 1.0, 0.0],
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[0.0, 0.0, 1.0],
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]);
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});
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it('solves a 2x2 linear system', function () {
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// 2x + y = 5
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// x + 3y = 10 → x=1, y=3
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$A = [[2.0, 1.0], [1.0, 3.0]];
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$b = [5.0, 10.0];
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$x = LinearAlgebra::solve($A, $b);
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expect($x[0])->toBeGreaterThan(0.999)->toBeLessThan(1.001)
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->and($x[1])->toBeGreaterThan(2.999)->toBeLessThan(3.001);
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});
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it('solves a 3x3 linear system with partial pivoting', function () {
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// First pivot is 0 — only succeeds with partial pivoting.
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// det(A) = -4 (non-singular). Solution: x=2, y=1, z=3 → b = [5, 6, 13]
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$A = [[0.0, 2.0, 1.0], [1.0, 1.0, 1.0], [2.0, 0.0, 3.0]];
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$b = [5.0, 6.0, 13.0];
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$x = LinearAlgebra::solve($A, $b);
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expect($x[0])->toEqualWithDelta(2.0, 1e-9)
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->and($x[1])->toEqualWithDelta(1.0, 1e-9)
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->and($x[2])->toEqualWithDelta(3.0, 1e-9);
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});
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it('ridgeSolve recovers a known signal under low lambda', function () {
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// y = 3x + noise. Lambda = 0.001 (effectively OLS).
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// X is single-feature. Expect coefficient ≈ 3.
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$X = [[1.0], [2.0], [3.0], [4.0], [5.0]];
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$y = [3.0, 6.0, 9.0, 12.0, 15.0];
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$beta = LinearAlgebra::ridgeSolve($X, $y, 0.001);
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expect($beta[0])->toEqualWithDelta(3.0, 1e-3);
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});
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it('ridgeSolve shrinks coefficients toward zero with high lambda', function () {
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$X = [[1.0], [2.0], [3.0], [4.0], [5.0]];
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$y = [3.0, 6.0, 9.0, 12.0, 15.0];
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$betaLow = LinearAlgebra::ridgeSolve($X, $y, 0.001);
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$betaHigh = LinearAlgebra::ridgeSolve($X, $y, 1000.0);
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expect(abs($betaHigh[0]))->toBeLessThan(abs($betaLow[0]));
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});
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it('rejects multiplication of incompatible matrices', function () {
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$a = [[1.0, 2.0]]; // 1x2
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$b = [[1.0], [2.0], [3.0]]; // 3x1
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LinearAlgebra::multiply($a, $b);
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})->throws(InvalidArgumentException::class);
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it('throws when solving a singular matrix', function () {
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$A = [[1.0, 2.0], [2.0, 4.0]]; // row 2 is 2× row 1
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$b = [3.0, 6.0];
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LinearAlgebra::solve($A, $b);
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})->throws(RuntimeException::class);
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