99 lines
3.4 KiB
Python
99 lines
3.4 KiB
Python
"""Tests for fitter.model."""
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import numpy as np
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import pytest
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from beta_spectrum import BetaSpectrum, SpectrumConfig
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from fitter.model import SpectrumModel
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class TestSpectrumModel:
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"""Test SpectrumModel."""
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def _make_model(self) -> tuple[SpectrumModel, SpectrumConfig]:
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"""Create a test SpectrumModel (no detector response)."""
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config = SpectrumConfig(
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Z_parent=43,
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Z_daughter=44,
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A_number=99,
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endpoint_MeV=0.294,
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)
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spectrum = BetaSpectrum.from_config(config)
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model = SpectrumModel(spectrum)
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return model, config
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def test_evaluate_unconvolved(self) -> None:
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model, config = self._make_model()
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energies_keV = np.linspace(0.01, 0.29, 50)
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values = model.evaluate_unconvolved(energies_keV)
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assert len(values) == 50
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assert np.all(np.isfinite(values))
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assert np.all(values >= 0)
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def test_evaluate_no_detector(self) -> None:
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model, config = self._make_model()
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energies_keV = np.linspace(0.01, 0.29, 50)
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values = model.evaluate(energies_keV, normalization=1.0, background=0.0)
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assert len(values) == 50
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assert np.all(np.isfinite(values))
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def test_evaluate_with_normalization(self) -> None:
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model, config = self._make_model()
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energies_keV = np.linspace(0.01, 0.29, 50)
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values1 = model.evaluate(energies_keV, normalization=1.0, background=0.0)
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values2 = model.evaluate(energies_keV, normalization=2.0, background=0.0)
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np.testing.assert_allclose(values2, values1 * 2.0)
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def test_evaluate_with_background(self) -> None:
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model, config = self._make_model()
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energies_keV = np.linspace(0.01, 0.29, 50)
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values1 = model.evaluate(energies_keV, normalization=1.0, background=0.0)
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values2 = model.evaluate(energies_keV, normalization=1.0, background=5.0)
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np.testing.assert_allclose(values2, values1 + 5.0)
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def test_convolve_requires_detector(self) -> None:
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model, _ = self._make_model()
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energies_keV = np.linspace(0.01, 0.29, 50)
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with pytest.raises(RuntimeError):
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model.convolve(energies_keV)
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def test_default_params(self) -> None:
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from exp_data.spectrum import ExpSpectrum
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energies = np.linspace(0, 100, 200)
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counts = 50 * np.exp(-0.5 * ((energies - 50) / 5) ** 2) + 10
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exp_spec = ExpSpectrum(energies=energies, counts=counts)
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norm, bg = SpectrumModel.default_params(exp_spec)
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assert norm > 0
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assert bg >= 0
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def test_default_bounds(self) -> None:
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lower, upper = SpectrumModel.default_bounds(100)
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assert len(lower) == 2
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assert len(upper) == 2
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assert lower[0] < upper[0]
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assert lower[1] < upper[1]
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class TestSpectrumModelKeVToW:
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"""Test energy unit conversion in SpectrumModel."""
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def test_keV_to_W(self) -> None:
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config = SpectrumConfig(
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Z_parent=43, Z_daughter=44, A_number=99, endpoint_MeV=0.294
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)
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model = SpectrumModel(BetaSpectrum.from_config(config))
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# 0 keV → W = 1.0
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W = model._keV_to_W(np.array([0.0]))
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assert np.isclose(W[0], 1.0)
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# 511 keV → W = 2.0
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W = model._keV_to_W(np.array([510.998950]))
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assert np.isclose(W[0], 2.0)
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# 294 keV → W ≈ 1.575
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W = model._keV_to_W(np.array([294.0]))
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assert np.isclose(W[0], 294.0 / 510.998950 + 1.0)
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