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test: adapt existing suites to unconditional core, drop dead detector tests

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unzhakov
2026-09-30 03:08:13 +03:00
parent 7dc2ec79d1
commit 8172ba2541
6 changed files with 103 additions and 320 deletions
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tests/fitter/test_model.py
+15 -36
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@@ -10,8 +10,8 @@ from fitter.model import SpectrumModel
class TestSpectrumModel:
"""Test SpectrumModel."""
def _make_model(self, with_detector: bool = False):
"""Create a test SpectrumModel."""
def _make_model(self) -> tuple[SpectrumModel, SpectrumConfig]:
"""Create a test SpectrumModel (no detector response)."""
config = SpectrumConfig(
Z_parent=43,
Z_daughter=44,
@@ -20,24 +20,10 @@ class TestSpectrumModel:
)
spectrum = BetaSpectrum.from_config(config)
detector = None
if with_detector:
detector = BetaSpectrum.create_detector_from_config(
SpectrumConfig(
Z_parent=43,
Z_daughter=44,
A_number=99,
endpoint_MeV=0.294,
detector_model="gaussian",
detector_sigma_a_keV=1.0,
detector_n_channels=100,
)
)
model = SpectrumModel(spectrum, detector)
model = SpectrumModel(spectrum)
return model, config
def test_evaluate_unconvolved(self):
def test_evaluate_unconvolved(self) -> None:
model, config = self._make_model()
energies_keV = np.linspace(0.01, 0.29, 50)
values = model.evaluate_unconvolved(energies_keV)
@@ -45,44 +31,34 @@ class TestSpectrumModel:
assert np.all(np.isfinite(values))
assert np.all(values >= 0)
def test_evaluate_no_detector(self):
def test_evaluate_no_detector(self) -> None:
model, config = self._make_model()
energies_keV = np.linspace(0.01, 0.29, 50)
values = model.evaluate(energies_keV, normalization=1.0, background=0.0)
assert len(values) == 50
assert np.all(np.isfinite(values))
def test_evaluate_with_normalization(self):
def test_evaluate_with_normalization(self) -> None:
model, config = self._make_model()
energies_keV = np.linspace(0.01, 0.29, 50)
values1 = model.evaluate(energies_keV, normalization=1.0, background=0.0)
values2 = model.evaluate(energies_keV, normalization=2.0, background=0.0)
np.testing.assert_allclose(values2, values1 * 2.0)
def test_evaluate_with_background(self):
def test_evaluate_with_background(self) -> None:
model, config = self._make_model()
energies_keV = np.linspace(0.01, 0.29, 50)
values1 = model.evaluate(energies_keV, normalization=1.0, background=0.0)
values2 = model.evaluate(energies_keV, normalization=1.0, background=5.0)
np.testing.assert_allclose(values2, values1 + 5.0)
def test_convolve_requires_detector(self):
def test_convolve_requires_detector(self) -> None:
model, _ = self._make_model()
energies_keV = np.linspace(0.01, 0.29, 50)
with pytest.raises(RuntimeError):
model.convolve(energies_keV)
def test_convolve_with_detector(self):
model, _ = self._make_model(with_detector=True)
energies_keV = model.detector_response.channel_energies
values = model.convolve(energies_keV)
assert len(values) == model.detector_response.n_channels
assert np.all(np.isfinite(values))
# Convolution can produce small negative values due to numerical effects
# — check that most values are non-negative
assert np.sum(values >= 0) > len(values) * 0.9
def test_default_params(self):
def test_default_params(self) -> None:
from exp_data.spectrum import ExpSpectrum
energies = np.linspace(0, 100, 200)
@@ -93,7 +69,7 @@ class TestSpectrumModel:
assert norm > 0
assert bg >= 0
def test_default_bounds(self):
def test_default_bounds(self) -> None:
lower, upper = SpectrumModel.default_bounds(100)
assert len(lower) == 2
assert len(upper) == 2
@@ -104,8 +80,11 @@ class TestSpectrumModel:
class TestSpectrumModelKeVToW:
"""Test energy unit conversion in SpectrumModel."""
def test_keV_to_W(self):
model = SpectrumModel(None) # type: ignore
def test_keV_to_W(self) -> None:
config = SpectrumConfig(
Z_parent=43, Z_daughter=44, A_number=99, endpoint_MeV=0.294
)
model = SpectrumModel(BetaSpectrum.from_config(config))
# 0 keV → W = 1.0
W = model._keV_to_W(np.array([0.0]))
assert np.isclose(W[0], 1.0)