feat: train forecasts on trade outcomes
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from pathlib import Path
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def test_retrain_runner_passes_training_horizon_to_calibrator() -> None:
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runner = (
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Path(__file__).resolve().parents[1] / "tools" / "run_torch_retrain.ps1"
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).read_text(encoding="utf-8")
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calibration_start = runner.index("$calibrationBaseArgs = @(")
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calibration_end = runner.index("\n )", calibration_start)
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calibration_args = runner[calibration_start:calibration_end]
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assert '"--horizon", $Horizon.ToString()' in calibration_args
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def test_retrain_runner_uses_a_regime_sized_validation_window() -> None:
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runner = (
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Path(__file__).resolve().parents[1] / "tools" / "run_torch_retrain.ps1"
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).read_text(encoding="utf-8")
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assert "[int]$ValidationWindow = 0" in runner
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assert "else { 720 }" in runner
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assert '"--validation-window", $ValidationWindow.ToString()' in runner
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