109 lines
3.7 KiB
Python
109 lines
3.7 KiB
Python
"""
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Property-based tests using Hypothesis for edge case discovery.
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While the parametrized property tests in test_property_tests.py cover
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common cases, Hypothesis generates thousands of random inputs to find
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edge cases that human-written tests might miss.
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These tests are marked @pytest.mark.slow because they can take several
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seconds to complete. They are intended for CI/full test runs, not for
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fast feedback during development.
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"""
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import numpy as np
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from hypothesis import given, settings, strategies as st
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from beta_spectrum.components.fermi import FermiFunction
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from beta_spectrum.components.phase_space import PhaseSpace
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# ---------------------------------------------------------------------------
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# Fermi function: random Z, A, W combinations
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# ---------------------------------------------------------------------------
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@given(
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Z=st.integers(min_value=1, max_value=92),
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A=st.integers(min_value=1, max_value=300),
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W=st.floats(min_value=1.01, max_value=10.0, allow_infinity=False, allow_nan=False),
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)
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@settings(max_examples=200, deadline=None)
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def test_fermi_stable_for_random_params(Z: int, A: int, W: float):
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"""Fermi function must not crash or produce NaN for any valid (Z, A, W)."""
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ff = FermiFunction(Z=Z, A=A)
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result = ff(np.array([W]))
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assert not np.isnan(result[0]), f"NaN for Z={Z}, A={A}, W={W}"
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assert not np.isinf(result[0]), f"Inf for Z={Z}, A={A}, W={W}"
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assert result[0] > 0, f"Non-positive for Z={Z}, A={A}, W={W}: {result[0]}"
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@given(
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Z=st.integers(min_value=10, max_value=92),
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)
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@settings(max_examples=200, deadline=None)
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def test_fermi_monotonic_for_fixed_Z(Z: int):
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"""For high Z, Fermi function should be monotonically decreasing with W.
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For Z=1 the finite-size correction can cause slight non-monotonicity,
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so we test high-Z cases where Coulomb dominates.
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"""
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ff = FermiFunction(Z=Z, A=Z * 2 + 10)
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W_arr = np.linspace(1.05, 4.0, 10)
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result = ff(W_arr)
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diffs = np.diff(result)
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assert np.all(diffs <= 0), (
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f"Fermi function not monotonically decreasing for Z={Z}: " f"diffs = {diffs}"
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)
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# ---------------------------------------------------------------------------
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# Phase space: random W0, W combinations
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# ---------------------------------------------------------------------------
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@given(
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W0=st.floats(min_value=2.0, max_value=10.0, allow_infinity=False, allow_nan=False),
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W=st.floats(min_value=1.01, max_value=5.0, allow_infinity=False, allow_nan=False),
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)
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@settings(max_examples=200, deadline=None)
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def test_phase_space_valid_for_random_params(W0: float, W: float):
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"""Phase space must not crash for any valid (W0, W) with W < W0."""
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# Ensure W is always less than W0
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W = min(W, W0 - 0.02)
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ps = PhaseSpace(W0=W0)
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result = ps(np.array([W]))
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assert not np.isnan(result[0]), f"NaN for W0={W0:.2f}, W={W:.2f}"
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# Phase space should be non-negative for W < W0
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assert result[0] >= 0, f"Negative for W0={W0:.2f}, W={W:.2f}: {result[0]}"
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@given(
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W0=st.floats(min_value=2.0, max_value=10.0, allow_infinity=False, allow_nan=False),
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)
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@settings(max_examples=100, deadline=None)
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def test_phase_space_threshold_at_W1(W0: float):
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"""Phase space must be exactly zero at W=1."""
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ps = PhaseSpace(W0=W0)
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result = ps(np.array([1.0]))
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assert (
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result[0] == 0.0
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), f"Phase space should be 0 at W=1 for W0={W0:.2f}, got {result[0]}"
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@given(
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W0=st.floats(min_value=2.0, max_value=10.0, allow_infinity=False, allow_nan=False),
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)
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@settings(max_examples=100, deadline=None)
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def test_phase_space_endpoint_at_W0(W0: float):
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"""Phase space must be exactly zero at W=W0."""
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ps = PhaseSpace(W0=W0)
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result = ps(np.array([W0]))
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assert (
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result[0] == 0.0
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), f"Phase space should be 0 at W=W0={W0:.2f}, got {result[0]}"
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