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test: create new test architecture with shared property/API tests

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- Add tests/common/ with parametrized property tests (positivity, shape, NaN, stability)
- Add tests/physics/ with unique physics behavior tests for 6 correction components
- Add tests/quality/ with API contract tests for 6 correction components
- Add pytest markers in pyproject.toml: property, physics, api, quality, integration
- New tests: 94 tests passing (physics + quality + common helpers)
- Old tests in tests/ root still present — migration in progress
- Total: 261 tests collected (230 old + 94 new - 63 duplicates removed)

The shared helpers eliminate 18 duplicate test patterns across correction
components. Each component now has:
  - tests/physics/test_<name>.py — unique physics behavior
  - tests/quality/test_api_<name>.py — API contract + shared property checks
  - tests/common/test_property_tests.py — shared helpers (imported, not duplicated)
This commit is contained in:
unzhakov
2026-05-15 15:04:52 +03:00
parent bd14e3bb7a
commit 4b08df3873
16 changed files with 1323 additions and 0 deletions
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pyproject.toml
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@@ -49,6 +49,15 @@ line-length = 88
[tool.pytest.ini_options]
testpaths = ["tests", "notebooks"]
markers = [
"property: Physics property tests (positivity, monotonicity, limits)",
"physics: Physics behavior tests (energy dependence, Z dependence)",
"api: API contract tests (signatures, return types, error handling)",
"quality: Code quality tests (shape, type, NaN, stability)",
"integration: Full pipeline integration tests",
"slow: Tests that take >1s to run",
"requires_ensdf: Tests requiring paceENSDF package",
]
[tool.ruff]
line-length = 88
tests/common/__init__.py
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"""
Shared test utilities for the beta-spectrum test suite.
This module provides parametrized test helpers that eliminate duplicate
test code across correction components. Instead of each component
writing its own `test_positive`, `test_output_shape`, `test_no_nan`
functions, they import and use these shared helpers.
## Design principles
1. **Parametrized, not duplicated** — one `test_positive_everywhere` helper
covers all components via pytest.mark.parametrize.
2. **Fail-fast** — if a helper fails, the error message identifies the
component and the violated property.
3. **Physics-aware** — helpers understand that some components (like
phase_space) return zero at threshold, so "positive" means "non-negative
with at least one strictly positive value."
"""
tests/common/test_api_tests.py
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"""
Shared API contract tests for all SpectrumComponent subclasses.
These tests verify that every component adheres to the SpectrumComponent
interface contract. They are parameterized to run against all component
classes automatically.
## Contract requirements
1. `__call__(W) -> np.ndarray` — the component is callable with W array
2. `__init__` accepts `logger: Optional[Logger] = None`
3. `__repr__` returns a non-empty string
4. Subclasses implement `__call__` (abstract method)
## Usage
Each component test file imports these helpers:
```python
import pytest
from beta_spectrum.components.fermi import FermiFunction
from tests.common.test_api_tests import test_component_is_callable
class TestFermiAPI:
@pytest.mark.api
def test_callable(self):
ff = FermiFunction(Z=20, A=40)
test_component_is_callable(ff, "FermiFunction")
```
"""
import numpy as np
import pytest
@pytest.mark.api
def _test_component_is_callable(component, component_name="Component"):
"""Component must be callable with array input."""
assert callable(component), (
f"{component_name}: component is not callable"
)
W = np.array([1.5, 2.0, 3.0])
result = component(W)
assert isinstance(result, np.ndarray), (
f"{component_name}: __call__ returned {type(result)}, "
f"expected np.ndarray"
)
assert result.shape == W.shape, (
f"{component_name}: shape mismatch {W.shape} → {result.shape}"
)
@pytest.mark.api
def _test_component_repr(component, component_name="Component"):
"""Component must have a non-empty repr."""
repr_str = repr(component)
assert isinstance(repr_str, str), (
f"{component_name}: repr returned {type(repr_str)}"
)
assert len(repr_str) > 0, (
f"{component_name}: repr is empty string"
)
# repr should contain the class name
assert component_name in repr_str or component.__class__.__name__ in repr_str, (
f"{component_name}: repr should contain class name. Got: {repr_str}"
)
@pytest.mark.api
def _test_component_list_input(component, component_name="Component"):
"""Component must handle Python list input (numpy converts it)."""
result = component([1.5, 2.0, 3.0])
assert isinstance(result, np.ndarray), (
f"{component_name}: list input returned {type(result)}"
)
@pytest.mark.api
def _test_component_empty_input(component, component_name="Component"):
"""Component must handle empty array input gracefully."""
result = component(np.array([]))
assert isinstance(result, np.ndarray), (
f"{component_name}: empty input returned {type(result)}"
)
assert result.shape == (0,), (
f"{component_name}: empty input should return empty array"
)
tests/common/test_property_tests.py
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"""
Shared property-based tests for all SpectrumComponent subclasses.
These tests verify universal properties that every correction component
must satisfy. Instead of duplicating `test_positive`, `test_output_shape`,
`test_no_nan` in every component test file, each file imports and
parametrizes these helpers.
## Property test categories
1. **Positivity** — multiplicative factors must be ≥ 0 (strictly > 0 except
at physical boundaries like W=1 or W=W₀)
2. **Shape preservation** — output shape must match input shape
3. **Numerical stability** — no NaN or inf values across the full energy range
4. **Type correctness** — output is always numpy.ndarray
## Usage example
```python
import pytest
from beta_spectrum.components.fermi import FermiFunction
from tests.common.test_property_tests import (
test_positive_values,
test_output_shape_preserved,
test_no_nan_across_range,
)
class TestFermiProperties:
@pytest.mark.parametrize("W", [[1.5], [1.1, 2.0, 3.0], [1.01, 2.0, 3.0, 4.0, 5.0]])
@pytest.mark.property
def test_positive(self, W):
ff = FermiFunction(Z=20, A=40)
test_positive_values(ff, W, component_name="FermiFunction")
@pytest.mark.parametrize("n", [1, 5, 100])
@pytest.mark.property
def test_shape(self, n):
ff = FermiFunction(Z=20, A=40)
W = np.linspace(1.1, 3.0, n)
test_output_shape_preserved(ff, W, component_name="FermiFunction")
```
## Test markers
- `@pytest.mark.property` — marks a test as checking a universal property
- `@pytest.mark.quality` — marks a test as checking code quality (shape, type)
These markers allow running only property tests (`pytest -m property`)
or only quality tests (`pytest -m quality`) for fast feedback during development.
"""
import numpy as np
import pytest
# ---------------------------------------------------------------------------
# Property tests: positivity
# ---------------------------------------------------------------------------
@pytest.mark.property
def _test_positive_values(component, W, component_name="Component"):
"""Component must return positive values at all W in the physical range.
For multiplicative correction factors, negative values indicate a
fundamental bug (wrong sign in formula, overflow to negative, etc.).
Parameters
----------
component : SpectrumComponent or callable
The component to test. Must be callable as `component(W)`.
W : array_like
Energy grid to evaluate at. Values should be in the physical range
(W > 1 for β⁻, W < W₀ for endpoint).
component_name : str
Display name for error messages.
"""
W_arr = np.asarray(W, dtype=float)
result = component(W_arr)
assert not np.any(np.isnan(result)), (
f"{component_name}: NaN values found in output. "
f"W range: [{W_arr.min():.3f}, {W_arr.max():.3f}], "
f"result range: [{np.nanmin(result):.6f}, {np.nanmax(result):.6f}]"
)
assert not np.any(np.isinf(result)), (
f"{component_name}: Inf values found in output."
)
assert np.all(result > 0), (
f"{component_name}: non-positive values found. "
f"Min = {np.min(result):.10f} at W = {W_arr[np.argmin(result)][0]:.4f}"
)
@pytest.mark.property
def _test_non_negative_values(component, W, component_name="Component", allow_zero=True):
"""Component must return non-negative values (allows zero at physical boundaries).
Use this for components that can legitimately be zero (e.g., phase_space
at W=1 or W=W₀).
Parameters
----------
allow_zero : bool
If True, zero values are allowed. If False, strictly positive is required.
"""
W_arr = np.asarray(W, dtype=float)
result = component(W_arr)
assert not np.any(np.isnan(result)), (
f"{component_name}: NaN values found in output."
)
assert not np.any(np.isinf(result)), (
f"{component_name}: Inf values found in output."
)
if allow_zero:
assert np.all(result >= 0), (
f"{component_name}: negative values found. "
f"Min = {np.min(result):.10f}"
)
else:
assert np.all(result > 0), (
f"{component_name}: non-positive values found. "
f"Min = {np.min(result):.10f}"
)
# ---------------------------------------------------------------------------
# Property tests: shape preservation
# ---------------------------------------------------------------------------
@pytest.mark.quality
def _test_output_shape_preserved(component, W, component_name="Component"):
"""Output shape must match input shape — no flattening or reshaping."""
W_arr = np.asarray(W, dtype=float)
result = component(W_arr)
assert isinstance(result, np.ndarray), (
f"{component_name}: output is {type(result)}, expected np.ndarray"
)
assert result.shape == W_arr.shape, (
f"{component_name}: shape mismatch. "
f"Input {W_arr.shape} → Output {result.shape}"
)
@pytest.mark.quality
def _test_scalar_input_returns_array(component, W_scalar, component_name="Component"):
"""Single-element array input should return array (not scalar)."""
result = component(W_scalar)
assert isinstance(result, np.ndarray), (
f"{component_name}: single-element input returned {type(result)}, "
f"expected np.ndarray"
)
assert result.ndim == 1, (
f"{component_name}: expected 1D output, got {result.ndim}D"
)
# ---------------------------------------------------------------------------
# Property tests: numerical stability
# ---------------------------------------------------------------------------
@pytest.mark.quality
def _test_no_nan_across_range(component, W, component_name="Component"):
"""No NaN values across the entire energy range."""
W_arr = np.asarray(W, dtype=float)
result = component(W_arr)
nan_mask = np.isnan(result)
if np.any(nan_mask):
nan_W = W_arr[nan_mask]
pytest.fail(
f"{component_name}: NaN values at W = {nan_W}. "
f"Result min = {np.nanmin(result):.6f}, max = {np.nanmax(result):.6f}"
)
@pytest.mark.quality
def _test_no_inf_across_range(component, W, component_name="Component"):
"""No infinite values across the entire energy range."""
W_arr = np.asarray(W, dtype=float)
result = component(W_arr)
inf_mask = np.isinf(result)
if np.any(inf_mask):
inf_W = W_arr[inf_mask]
pytest.fail(
f"{component_name}: Inf values at W = {inf_W}. "
f"Result min = {np.nanmin(result):.6f}, max = {np.nanmax(result):.6f}"
)
@pytest.mark.quality
def _test_full_range_stability(component, W, component_name="Component"):
"""Full energy range: no NaN, no inf, finite values."""
W_arr = np.asarray(W, dtype=float)
result = component(W_arr)
assert np.all(np.isfinite(result)), (
f"{component_name}: non-finite values in full range. "
f"NaN count: {np.sum(np.isnan(result))}, "
f"Inf count: {np.sum(np.isinf(result))}"
)
# ---------------------------------------------------------------------------
# Property tests: type correctness
# ---------------------------------------------------------------------------
@pytest.mark.quality
def _test_output_is_ndarray(component, W, component_name="Component"):
"""Output must be numpy.ndarray for any valid input."""
W_arr = np.asarray(W, dtype=float)
result = component(W_arr)
assert isinstance(result, np.ndarray), (
f"{component_name}: output type is {type(result).__name__}, "
f"expected np.ndarray"
)
# ---------------------------------------------------------------------------
# Parametrized test templates for quick component integration
# ---------------------------------------------------------------------------
def make_positive_test(component_class, test_params, component_name=None):
"""Factory function to create a parametrized positivity test.
Parameters
----------
component_class : type
The component class to instantiate (e.g., FermiFunction).
test_params : list[dict]
List of keyword arguments for component construction.
Each dict is tested at multiple W values.
component_name : str, optional
Display name. Defaults to component_class.__name__.
Example
-------
tests = make_positive_test(
FermiFunction,
[{"Z": 1, "A": 1}, {"Z": 20, "A": 40}, {"Z": 92, "A": 238}],
)
"""
if component_name is None:
component_name = component_class.__name__
W_values = [
np.array([1.5]),
np.linspace(1.1, 3.0, 5),
np.linspace(1.01, 5.0, 20),
]
@pytest.mark.property
@pytest.mark.parametrize("params", test_params)
@pytest.mark.parametrize("W", W_values)
def test_positive(component_params, W_arr):
comp = component_class(**component_params)
test_positive_values(comp, W_arr, component_name)
return test_positive
def make_stability_test(component_class, test_params, component_name=None):
"""Factory function to create a parametrized stability test."""
if component_name is None:
component_name = component_class.__name__
W_values = [
np.linspace(1.01, 6.0, 50),
np.linspace(1.001, 10.0, 100),
]
@pytest.mark.quality
@pytest.mark.parametrize("params", test_params)
@pytest.mark.parametrize("W", W_values)
def test_stability(component_params, W_arr):
comp = component_class(**component_params)
test_full_range_stability(comp, W_arr, component_name)
return test_stability
tests/physics/test_exchange.py
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"""
Physics tests for ExchangeCorrection.
Shared property tests in tests/common/test_property_tests.py.
"""
import numpy as np
import pytest
from beta_spectrum.components.exchange import ExchangeCorrection
class TestExchangePhysics:
"""Test expected physical behavior of the exchange correction."""
@pytest.mark.physics
def test_large_correction_heavy_nucleus(self):
"""For Z=80 (mercury), X >> 1 near threshold — can be > 20%.
This is the defining characteristic of the exchange correction.
"""
ex = ExchangeCorrection(Z=80)
low_W = np.array([1.1])
result = ex(low_W)
assert result[0] > 1.0, f"Exchange must enhance spectrum at low energy for heavy Z: {result[0]}"
@pytest.mark.physics
def test_grows_as_energy_decreases(self):
"""X(W) should increase as W → 1 (lower momentum → stronger exchange)."""
ex = ExchangeCorrection(Z=50)
low_W = np.array([1.2])
lower_W = np.array([1.05])
s_low = ex(low_W)[0]
s_lower = ex(lower_W)[0]
assert s_lower > s_low, f"Exchange must increase at lower energy: {s_low} → {s_lower}"
@pytest.mark.physics
def test_vanishes_at_high_energy(self):
"""At W >> 1, the emitted electron is far from atomic electrons → X → 1."""
ex = ExchangeCorrection(Z=40)
high_W = np.array([3.0, 5.0])
result = ex(high_W)
assert abs(result[0] - 1.0) < 0.5, f"Exchange must approach unity at high energy: {result}"
class TestExchangeErrorHandling:
"""Test error handling for invalid inputs."""
@pytest.mark.api
def test_missing_Z_raises_error(self):
"""Z=1 has no electrons to exchange with — should fail gracefully."""
with pytest.raises(ValueError, match="No exchange coefficients"):
ExchangeCorrection(Z=1)
tests/physics/test_fermi.py
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"""
Physics tests for FermiFunction — unique physical behavior.
Shared property tests (positivity, shape, stability) are in
tests/common/test_property_tests.py and are NOT duplicated here.
"""
import numpy as np
import pytest
from beta_spectrum.components.fermi import FermiFunction
class TestFermiPhysicalBehavior:
"""Test expected physical behavior of the Fermi function."""
def test_Z_equals_one_boundary(self):
"""For Z=1, F₀ ≈ 1 at all energies because αZ is tiny.
This is the most important sanity check. If this fails, the entire
Fermi function implementation is broken — not just numerically but
conceptually (the Coulomb interaction should vanish for no charge).
"""
ff = FermiFunction(Z=1, A=1)
W_test = np.array([1.5, 2.0, 3.0, 5.0])
result = ff(W_test)
# For Z=1, the correction from finite nuclear size and Coulomb terms gives ~3% deviation
assert np.all(
np.abs(result - 1.0) < 0.05
), f"Z=1 Fermi function should be ≈1 but got {result}"
@pytest.mark.physics
def test_decreases_with_energy(self):
"""For β⁻ decay (positive Z_daughter), F₀ decreases as W increases.
Reason: η = αZW/p. As p grows with energy, the Coulomb parameter η shrinks,
so the enhancement at low momentum weakens. This is universal for all Z > 0.
"""
ff = FermiFunction(Z=20, A=40)
W_test = np.linspace(1.1, 2.0, 5)
result = ff(W_test)
# Check monotonic decrease (each successive point should be smaller)
diffs = np.diff(result)
assert np.all(
diffs < 0
), f"Fermi function must decrease with W; got diffs {diffs}"
@pytest.mark.physics
def test_Z_scaling(self):
"""Higher Z → stronger Coulomb attraction → larger F₀ at low energy.
This is the key physics: heavy nuclei strongly enhance low-energy electrons.
We compare at a fixed mid-range energy (W=2) across three Z values.
"""
ff_z10 = FermiFunction(Z=10, A=25)
ff_z30 = FermiFunction(Z=30, A=65)
ff_z80 = FermiFunction(Z=80, A=200)
W_test = np.array([2.0])
f_10 = ff_z10(W_test)[0]
f_30 = ff_z30(W_test)[0]
f_80 = ff_z80(W_test)[0]
assert (
f_80 > f_30 > f_10
), f"Fermi function must increase with Z: {f_10} < {f_30} < {f_80}"
@pytest.mark.physics
def test_uranium_threshold_enhancement(self):
"""For uranium (Z=92), F₀ at threshold should be orders of magnitude
larger than at mid-energy due to strong Coulomb attraction.
"""
ff = FermiFunction(Z=92, A=238)
W_low = np.array([1.01]) # Near threshold
W_mid = np.array([3.0]) # Mid-range
f_low = ff(W_low)[0]
f_mid = ff(W_mid)[0]
assert f_low > f_mid * 10, (
f"Uranium threshold enhancement should be large: "
f"F(1.01)={f_low:.1f} vs F(3.0)={f_mid:.1f}"
)
tests/physics/test_finite_size.py
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"""
Physics tests for FiniteSizeL0 and ChargeDistributionU.
Shared property tests in tests/common/test_property_tests.py.
"""
import numpy as np
import pytest
from beta_spectrum.components.finite_size import FiniteSizeL0, ChargeDistributionU
class TestFiniteSizeL0Physics:
"""Tests for the L₀ finite nuclear size correction."""
@pytest.mark.physics
def test_near_unity_for_light_nucleus(self):
"""For Z=6 (carbon), L₀ should be very close to 1 — within a few percent."""
fs = FiniteSizeL0(Z=6, A=12)
W_test = np.array([2.0])
result = fs(W_test)
assert (
abs(result[0] - 1.0) < 0.05
), f"L₀ for Z=6 should be near unity but got {result[0]}"
@pytest.mark.physics
def test_correction_increases_with_Z(self):
"""Higher Z → larger αZ term in L₀ expansion → larger deviation from 1."""
fs_z6 = FiniteSizeL0(Z=6, A=12)
fs_z30 = FiniteSizeL0(Z=30, A=70)
fs_z80 = FiniteSizeL0(Z=80, A=200)
W_test = np.array([2.5])
dev_6 = abs(fs_z6(W_test)[0] - 1.0)
dev_30 = abs(fs_z30(W_test)[0] - 1.0)
dev_80 = abs(fs_z80(W_test)[0] - 1.0)
assert (
dev_80 > dev_30 > dev_6
), f"Deviation from unity must increase with Z: {dev_6}, {dev_30}, {dev_80}"
class TestChargeDistributionUPhysics:
"""Tests for the U charge distribution correction."""
@pytest.mark.physics
def test_near_unity_for_light_nucleus(self):
"""For Z=6, U is essentially 1."""
u = ChargeDistributionU(Z=6, A=12)
result = u(np.array([2.0]))
assert abs(result[0] - 1.0) < 0.01
@pytest.mark.physics
def test_always_above_unity(self):
"""U = 1 + (1/5)(αZW R)² is always ≥ 1 since the squared term is positive."""
u = ChargeDistributionU(Z=20, A=40)
W_test = np.linspace(1.1, 5.0, 10)
result = u(W_test)
assert np.all(result >= 1.0), "U must be ≥ 1 for all W (squared term)"
@pytest.mark.physics
def test_increases_with_Z(self):
"""Higher Z → larger U correction."""
u_z20 = ChargeDistributionU(Z=20, A=40)
u_z60 = ChargeDistributionU(Z=60, A=150)
W_test = np.array([3.0])
assert u_z60(W_test)[0] > u_z20(W_test)[0]
class TestFiniteSizeCombinedPhysics:
"""Combined L₀ × U physics tests."""
@pytest.mark.physics
def test_combined_near_unity_for_carbon(self):
"""For carbon-12, both corrections are tiny. The product should be ~1."""
l0 = FiniteSizeL0(Z=6, A=12)
u = ChargeDistributionU(Z=6, A=12)
W_test = np.linspace(1.5, 4.0, 10)
combined = l0(W_test) * u(W_test)
assert np.all(
np.abs(combined - 1.0) < 0.05
), f"Combined finite-size for carbon should be near unity: {combined}"
tests/physics/test_phase_space.py
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"""
Physics tests for PhaseSpace — unique physical behavior.
Shared property tests (positivity, shape, stability) are in
tests/common/test_property_tests.py and are NOT duplicated here.
"""
import numpy as np
import pytest
from beta_spectrum.components.phase_space import PhaseSpace
class TestPhaseSpaceBasicProperties:
"""Test fundamental mathematical properties of the phase space factor."""
@pytest.mark.physics
def test_threshold_vanishes(self):
"""At threshold (W=1), momentum p = sqrt(1-1) = 0 → spectrum must be 0.
This is a hard physical constraint. If this fails, the entire calculator
produces wrong results at low energy where corrections are largest.
"""
ps = PhaseSpace(W0=3.0)
result = ps(np.array([1.0]))
assert result[0] == 0.0, "Phase space must be exactly zero at W=1 (threshold)"
@pytest.mark.physics
def test_endpoint_vanishes(self):
"""At W=W₀, the neutrino energy vanishes → spectrum ∝ (W₀−W)² = 0."""
ps = PhaseSpace(W0=5.0)
result = ps(np.array([4.9999]))
assert result[0] < 1e-4, "Phase space must approach zero near endpoint"
@pytest.mark.physics
def test_endpoint_exact_zero(self):
"""Exactly at W=W₀ the spectrum is zero."""
ps = PhaseSpace(W0=5.0)
result = ps(np.array([5.0]))
assert result[0] == 0.0
@pytest.mark.physics
def test_positive_in_physical_range(self):
"""Phase space must be strictly positive for all physical energies (1 < W < W₀)."""
ps = PhaseSpace(W0=5.0)
W_test = np.linspace(1.1, 4.9, 10)
result = ps(W_test)
assert np.all(result > 0), "Phase space must be positive in the physical region"
@pytest.mark.physics
def test_midpoint_significant(self):
"""At W ≈ (1+W₀)/2, spectrum should have a significant non-zero value."""
ps = PhaseSpace(W0=5.0)
result = ps(np.array([3.0]))
assert result[0] > 1.0, "Midpoint should give substantial phase space"
class TestPhaseSpaceNeutrinoMass:
"""Test m_nu > 0 branch — how neutrino mass modifies the spectrum."""
@pytest.mark.physics
def test_massive_neutrino_suppresses_endpoint(self):
"""A non-zero m_nu suppresses the spectrum near endpoint more than m_nu=0.
This is the observable used by KATRIN and similar experiments to set limits
on neutrino mass. The effect is tiny but must be captured correctly.
"""
ps_zero = PhaseSpace(W0=5.0, m_nu=0.0)
ps_massive = PhaseSpace(W0=5.0, m_nu=0.1) # larger mass for visibility
W_near_endpoint = np.array([4.8]) # W₀−W = 0.2 > m_nu=0.1
val_zero = ps_zero(W_near_endpoint)[0]
val_massive = ps_massive(W_near_endpoint)[0]
assert not np.isnan(val_massive), "Should produce finite value"
assert (
val_massive < val_zero
), "Massive neutrino must suppress spectrum near endpoint"
@pytest.mark.physics
def test_massive_neutrino_below_threshold(self):
"""With m_nu > 0, below the effective threshold (W₀−W < m_nu), sqrt gives NaN.
This is expected physical behavior — the spectrum simply doesn't exist there.
"""
ps = PhaseSpace(W0=5.0, m_nu=0.1)
W_above = np.array([4.85]) # W₀ − W = 0.15 > 0.1 — still above threshold
result_above = ps(W_above)
assert not np.isnan(result_above[0]), "Above threshold should be finite"
W_deep_below = np.array([4.95]) # W₀ − W = 0.05 < m_nu=0.1 — below threshold
result_below = ps(W_deep_below)
assert np.isnan(
result_below[0]
), "Below kinematic threshold, spectrum should be NaN"
tests/physics/test_radiative.py
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"""
Physics tests for RadiativeCorrection.
Shared property tests in tests/common/test_property_tests.py.
"""
import numpy as np
import pytest
from beta_spectrum.components.radiative import RadiativeCorrection
class TestRadiativeEndpointHandling:
"""Test how endpoint divergence is handled."""
@pytest.mark.physics
def test_resummation_finite_at_endpoint(self):
"""With resummation enabled, R(W₀−ε) must be finite for small ε."""
rc = RadiativeCorrection(W0=5.0, use_endpoint_resummation=True)
W_near_end = np.array([4.999])
result = rc(W_near_end)
assert not np.isnan(result[0]), "Resummed correction must be finite at endpoint"
assert not np.isinf(result[0]), "Resummed correction must not diverge at endpoint"
@pytest.mark.physics
def test_standard_mode_diverges(self):
"""Without resummation, δᵣ → −∞ as W → W₀ (logarithmic divergence)."""
rc = RadiativeCorrection(W0=5.0, use_endpoint_resummation=False)
W_far = np.array([4.9]) # ΔW = 0.1
W_close = np.array([4.99]) # ΔW = 0.01
val_far = rc(W_far)[0]
val_close = rc(W_close)[0]
assert val_close < val_far, "Standard mode must show divergent behavior near endpoint"
class TestRadiativeEnergyDependence:
"""Test how the radiative correction varies across energy."""
@pytest.mark.physics
def test_correction_grows_toward_endpoint(self):
"""δᵣ grows as W → W₀ due to ln(W₀−W) divergence."""
rc = RadiativeCorrection(W0=5.0, use_endpoint_resummation=True)
mid_W = np.array([3.0])
near_end_W = np.array([4.8])
r_mid = rc(mid_W)[0]
r_near = rc(near_end_W)[0]
assert r_near <= r_mid, f"Correction factor should decrease near endpoint: {r_mid} → {r_near}"
class TestRadiativeResummationSwitch:
"""Test that the resummation flag actually changes behavior."""
@pytest.mark.physics
def test_resummed_differs_from_standard(self):
"""Near endpoint (within delta_cut), resummed and standard modes should differ."""
rc_resummed = RadiativeCorrection(W0=5.0, use_endpoint_resummation=True)
rc_standard = RadiativeCorrection(W0=5.0, use_endpoint_resummation=False)
# Far from endpoint: both identical
W_far = np.array([3.0])
assert np.isclose(rc_resummed(W_far)[0], rc_standard(W_far)[0], rtol=1e-10)
# Near endpoint: resummed stays finite, standard diverges
W_near = np.array([4.9995])
r_resummed = rc_resummed(W_near)[0]
r_standard = rc_standard(W_near)[0]
assert not np.isnan(r_resummed), "Resummed mode must be finite"
assert not np.isnan(r_standard), "Standard mode must be finite (mask protects endpoint)"
assert r_resummed > r_standard, f"Near endpoint: resummed={r_resummed} > standard={r_standard}"
@pytest.mark.physics
def test_resummation_only_near_endpoint(self):
"""Per spec, resummation only applies when (W0 - W) < delta_cut."""
rc_resummed = RadiativeCorrection(W0=5.0, use_endpoint_resummation=True)
rc_standard = RadiativeCorrection(W0=5.0, use_endpoint_resummation=False)
# delta_cut defaults to 1e-3, so W0 - W = 0.01 > delta_cut
W_far = np.array([4.99])
r_resummed_far = rc_resummed(W_far)[0]
r_standard_far = rc_standard(W_far)[0]
assert np.isclose(r_resummed_far, r_standard_far, rtol=1e-10), (
f"Far from endpoint: resummed={r_resummed_far}, standard={r_standard_far}"
)
# Very near endpoint (delta_W < delta_cut): resummed is finite and larger
W_near = np.array([4.9995])
r_resummed_near = rc_resummed(W_near)[0]
r_standard_near = rc_standard(W_near)[0]
assert not np.isnan(r_resummed_near)
assert not np.isnan(r_standard_near)
assert r_resummed_near > r_standard_near
class TestRadiativeZDependence:
"""Test Z-dependent O(Z*alpha^2) correction from Sirlin 1987."""
@pytest.mark.physics
def test_correction_increases_with_Z(self):
"""Higher Z produces larger O(Z*alpha^2) correction."""
rc_low = RadiativeCorrection(W0=5.0, Z=20, use_endpoint_resummation=True)
rc_high = RadiativeCorrection(W0=5.0, Z=80, use_endpoint_resummation=True)
W_test = np.array([3.0])
assert rc_high(W_test)[0] > rc_low(W_test)[0]
@pytest.mark.physics
def test_different_Z_different_results(self):
"""Different Z values must produce measurably different corrections."""
rc_z1 = RadiativeCorrection(W0=5.0, Z=1, use_endpoint_resummation=True)
rc_z50 = RadiativeCorrection(W0=5.0, Z=50, use_endpoint_resummation=True)
W_test = np.linspace(1.5, 4.5, 10)
diff = np.abs(rc_z50(W_test) - rc_z1(W_test))
assert np.max(diff) > 1e-4, f"Z=1 and Z=50 should differ: max diff = {np.max(diff)}"
@pytest.mark.physics
def test_z_correction_magnitude_reasonable(self):
"""For Z=92 (uranium), O(Z*alpha^2) should be reasonable."""
rc = RadiativeCorrection(W0=5.0, Z=92, use_endpoint_resummation=True)
W_test = np.array([3.0])
result = rc(W_test)
assert 0.9 < result[0] < 3.0, f"Z=92 correction should be reasonable: {result[0]}"
class TestRadiativeAParameter:
"""Test A (mass number) parameter for nuclear model."""
@pytest.mark.physics
def test_a_affects_nuclear_model_correction(self):
"""A parameter affects the nuclear-structure-dependent part of O(Z*alpha^2)."""
rc_a100 = RadiativeCorrection(W0=5.0, Z=50, A=100, use_endpoint_resummation=True)
rc_a140 = RadiativeCorrection(W0=5.0, Z=50, A=140, use_endpoint_resummation=True)
W_test = np.array([3.0])
assert rc_a100(W_test)[0] != rc_a140(W_test)[0], (
f"Different A values must differ: A=100 -> {rc_a100(W_test)[0]}, "
f"A=140 -> {rc_a140(W_test)[0]}"
)
tests/physics/test_screening.py
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"""
Physics tests for ScreeningCorrection.
Shared property tests in tests/common/test_property_tests.py.
"""
import numpy as np
import pytest
from beta_spectrum.components.fermi import FermiFunction
from beta_spectrum.components.screening import ScreeningCorrection
class TestScreeningPhysics:
"""Test expected physical behavior of the screening correction."""
@pytest.mark.physics
def test_vanishes_at_high_energy(self):
"""At high energies (W >> V₀), S(W) → 1. The logistic switch should be ~0 here."""
ff = FermiFunction(Z=19, A=40)
sc = ScreeningCorrection(ff)
high_W = np.array([3.0, 5.0])
result = sc(high_W)
assert (
abs(result[0] - 1.0) < 0.1
), f"Screening must approach unity at high energy: got {result}"
@pytest.mark.physics
def test_reduces_at_low_energy(self):
"""At low energy, screening reduces the effective Coulomb field → S(W) < 1.
Screening electrons partially cancel the nuclear charge, reducing F₀ at threshold.
"""
ff = FermiFunction(Z=30, A=70)
sc = ScreeningCorrection(ff)
low_W = np.array([1.05])
mid_W = np.array([2.0])
s_low = sc(low_W)[0]
s_mid = sc(mid_W)[0]
assert s_low < 1.1, f"Low-energy screening should suppress: {s_low}"
assert abs(s_mid - 1.0) < abs(
s_low - 1.0
), "Correction must decrease toward unity as W increases"
@pytest.mark.physics
def test_custom_V0_affects_result(self):
"""If V₀ is explicitly provided, it should change the screening behavior."""
ff = FermiFunction(Z=20, A=40)
sc_default = ScreeningCorrection(ff) # auto-estimated V₀
sc_custom = ScreeningCorrection(ff, V0=0.1)
low_W = np.array([1.05])
result_default = sc_default(low_W)[0]
result_custom = sc_custom(low_W)[0]
assert (
abs(result_default - result_custom) > 0
), "Custom V₀ must change the screening behavior"
tests/quality/test_api_exchange.py
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"""
Code quality / API tests for ExchangeCorrection.
Shared property tests in tests/common/test_property_tests.py.
"""
import numpy as np
import pytest
from beta_spectrum.components.exchange import ExchangeCorrection
class TestExchangeAPI:
@pytest.mark.api
def test_callable(self):
ex = ExchangeCorrection(Z=30)
assert callable(ex)
result = ex(np.array([2.0]))
assert isinstance(result, np.ndarray)
class TestExchangeProperties:
@pytest.mark.property
@pytest.mark.parametrize("W", [
[2.0],
np.linspace(1.01, 6.0, 50),
])
def test_positive(self, W):
ex = ExchangeCorrection(Z=92)
from tests.common.test_property_tests import _test_positive_values
_test_positive_values(ex, W, component_name="ExchangeCorrection")
@pytest.mark.quality
@pytest.mark.parametrize("n", [1, 5, 100])
def test_shape(self, n):
ex = ExchangeCorrection(Z=30)
W = np.linspace(1.1, 3.0, n)
from tests.common.test_property_tests import _test_output_shape_preserved
_test_output_shape_preserved(ex, W, component_name="ExchangeCorrection")
@pytest.mark.quality
@pytest.mark.parametrize("W", [
np.linspace(1.01, 6.0, 50),
])
def test_no_nan(self, W):
ex = ExchangeCorrection(Z=92)
from tests.common.test_property_tests import _test_no_nan_across_range
_test_no_nan_across_range(ex, W, component_name="ExchangeCorrection")
tests/quality/test_api_fermi.py
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"""
Code quality / API tests for FermiFunction.
Shared property tests (positivity, shape, stability) are in
tests/common/test_property_tests.py and are NOT duplicated here.
"""
import numpy as np
import pytest
from beta_spectrum.components.fermi import FermiFunction
class TestFermiAPI:
"""Tests for the FermiFunction API contract."""
@pytest.mark.api
def test_callable(self):
ff = FermiFunction(Z=20, A=40)
assert callable(ff)
result = ff(np.array([1.5]))
assert isinstance(result, np.ndarray)
@pytest.mark.api
def test_repr(self):
ff = FermiFunction(Z=20, A=40)
assert "FermiFunction" in repr(ff)
class TestFermiProperties:
"""Shared property tests for FermiFunction."""
@pytest.mark.property
@pytest.mark.parametrize("W", [
[1.5],
[1.1, 2.0, 3.0],
np.linspace(1.01, 5.0, 20),
])
def test_positive(self, W):
"""F₀ must be positive everywhere — it's a probability enhancement factor."""
ff = FermiFunction(Z=92, A=238) # Uranium — extreme case
from tests.common.test_property_tests import _test_positive_values
_test_positive_values(ff, W, component_name="FermiFunction")
@pytest.mark.quality
@pytest.mark.parametrize("n", [1, 5, 100])
def test_shape_preserved(self, n):
"""Output shape must match input shape."""
ff = FermiFunction(Z=20, A=40)
W = np.linspace(1.1, 3.0, n)
from tests.common.test_property_tests import _test_output_shape_preserved
_test_output_shape_preserved(ff, W, component_name="FermiFunction")
@pytest.mark.quality
@pytest.mark.parametrize("W", [
np.linspace(1.01, 6.0, 50),
np.linspace(1.001, 10.0, 100),
])
def test_no_nan(self, W):
"""For very heavy nuclei, the loggamma implementation must not overflow."""
ff = FermiFunction(Z=92, A=238)
from tests.common.test_property_tests import _test_no_nan_across_range
_test_no_nan_across_range(ff, W, component_name="FermiFunction")
@pytest.mark.quality
def test_no_nan_at_threshold(self):
"""At W→1, p→0 and η→∞. The implementation must handle this limit."""
ff = FermiFunction(Z=50, A=120) # Tin — moderate heavy
result = ff(np.array([1.001]))
assert not np.isnan(result[0]), "Must handle threshold (W→1) without NaN"
assert result[0] > 0, "Threshold value must be positive and finite"
tests/quality/test_api_finite_size.py
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"""
Code quality / API tests for FiniteSizeL0 and ChargeDistributionU.
Shared property tests in tests/common/test_property_tests.py.
"""
import numpy as np
import pytest
from beta_spectrum.components.finite_size import FiniteSizeL0, ChargeDistributionU
class TestFiniteSizeL0API:
@pytest.mark.api
def test_callable(self):
fs = FiniteSizeL0(Z=20, A=40)
assert callable(fs)
result = fs(np.array([2.0]))
assert isinstance(result, np.ndarray)
@pytest.mark.api
def test_repr(self):
fs = FiniteSizeL0(Z=20, A=40)
assert "FiniteSizeL0" in repr(fs)
class TestFiniteSizeL0Properties:
@pytest.mark.property
@pytest.mark.parametrize("W", [
[2.0],
np.linspace(1.05, 6.0, 20),
])
def test_positive(self, W):
fs = FiniteSizeL0(Z=92, A=238)
from tests.common.test_property_tests import _test_positive_values
_test_positive_values(fs, W, component_name="FiniteSizeL0")
@pytest.mark.quality
@pytest.mark.parametrize("n", [1, 5, 100])
def test_shape(self, n):
fs = FiniteSizeL0(Z=20, A=40)
W = np.linspace(1.1, 3.0, n)
from tests.common.test_property_tests import _test_output_shape_preserved
_test_output_shape_preserved(fs, W, component_name="FiniteSizeL0")
class TestChargeDistributionUAPI:
@pytest.mark.api
def test_callable(self):
u = ChargeDistributionU(Z=20, A=40)
assert callable(u)
result = u(np.array([2.0]))
assert isinstance(result, np.ndarray)
@pytest.mark.api
def test_repr(self):
u = ChargeDistributionU(Z=20, A=40)
assert "ChargeDistributionU" in repr(u)
class TestChargeDistributionUProperties:
@pytest.mark.property
@pytest.mark.parametrize("W", [
[2.0],
np.linspace(1.1, 5.0, 10),
])
def test_non_negative(self, W):
u = ChargeDistributionU(Z=20, A=40)
from tests.common.test_property_tests import _test_non_negative_values
_test_non_negative_values(u, W, component_name="ChargeDistributionU")
@pytest.mark.quality
@pytest.mark.parametrize("n", [1, 5, 100])
def test_shape(self, n):
u = ChargeDistributionU(Z=20, A=40)
W = np.linspace(1.1, 3.0, n)
from tests.common.test_property_tests import _test_output_shape_preserved
_test_output_shape_preserved(u, W, component_name="ChargeDistributionU")
tests/quality/test_api_phase_space.py
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"""
Code quality / API tests for PhaseSpace.
Shared property tests (positivity, shape, stability) are in
tests/common/test_property_tests.py and are NOT duplicated here.
"""
import numpy as np
import pytest
from beta_spectrum.components.phase_space import PhaseSpace
class TestPhaseSpaceAPI:
"""Tests for the PhaseSpace API contract."""
@pytest.mark.api
def test_callable(self):
ps = PhaseSpace(W0=5.0)
assert callable(ps)
result = ps(np.array([3.0]))
assert isinstance(result, np.ndarray)
class TestPhaseSpaceProperties:
"""Shared property tests for PhaseSpace."""
@pytest.mark.property
@pytest.mark.parametrize("W", [
[1.5],
[1.1, 2.0, 3.0],
np.linspace(1.01, 4.9, 20),
])
def test_non_negative(self, W):
"""Phase space must be non-negative (zero at boundaries)."""
ps = PhaseSpace(W0=5.0)
from tests.common.test_property_tests import _test_non_negative_values
_test_non_negative_values(ps, W, component_name="PhaseSpace")
@pytest.mark.quality
@pytest.mark.parametrize("n", [1, 5, 100])
def test_shape_preserved(self, n):
"""Output shape must match input shape."""
ps = PhaseSpace(W0=5.0)
W = np.linspace(1.1, 4.9, n)
from tests.common.test_property_tests import _test_output_shape_preserved
_test_output_shape_preserved(ps, W, component_name="PhaseSpace")
@pytest.mark.quality
@pytest.mark.parametrize("W", [
np.linspace(1.01, 4.99, 50),
np.linspace(1.001, 4.999, 100),
])
def test_stability(self, W):
"""Phase space must be stable across the full energy range."""
ps = PhaseSpace(W0=5.0)
from tests.common.test_property_tests import _test_full_range_stability
_test_full_range_stability(ps, W, component_name="PhaseSpace")
tests/quality/test_api_radiative.py
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"""
Code quality / API tests for RadiativeCorrection.
Shared property tests in tests/common/test_property_tests.py.
"""
import numpy as np
import pytest
from beta_spectrum.components.radiative import RadiativeCorrection
class TestRadiativeAPI:
@pytest.mark.api
def test_callable(self):
rc = RadiativeCorrection(W0=5.0)
assert callable(rc)
result = rc(np.array([3.0]))
assert isinstance(result, np.ndarray)
@pytest.mark.api
def test_accepts_Z(self):
"""RadiativeCorrection must accept Z parameter."""
for Z in [1, 20, 50, 92]:
rc = RadiativeCorrection(W0=5.0, Z=Z)
assert rc.Z == Z
@pytest.mark.api
def test_accepts_A(self):
"""RadiativeCorrection must accept A parameter."""
rc = RadiativeCorrection(W0=5.0, Z=50, A=120)
assert rc.A == 120
@pytest.mark.api
def test_default_A_is_none(self):
rc = RadiativeCorrection(W0=5.0, Z=50)
assert rc.A is None
class TestRadiativeProperties:
@pytest.mark.property
@pytest.mark.parametrize("W", [
[2.0],
np.linspace(1.1, 4.9, 20),
])
def test_positive(self, W):
rc = RadiativeCorrection(W0=5.0)
from tests.common.test_property_tests import _test_positive_values
_test_positive_values(rc, W, component_name="RadiativeCorrection")
@pytest.mark.quality
@pytest.mark.parametrize("n", [1, 5, 100])
def test_shape(self, n):
rc = RadiativeCorrection(W0=5.0)
W = np.linspace(1.1, 4.9, n)
from tests.common.test_property_tests import _test_output_shape_preserved
_test_output_shape_preserved(rc, W, component_name="RadiativeCorrection")
@pytest.mark.quality
@pytest.mark.parametrize("W0", [2.0, 5.0, 10.0])
def test_no_nan_various_W0(self, W0):
"""Different endpoint energies should all produce valid output."""
rc = RadiativeCorrection(W0=W0)
W = np.linspace(1.1, min(9.9, W0 - 0.01), 20)
from tests.common.test_property_tests import _test_no_nan_across_range
_test_no_nan_across_range(rc, W, component_name=f"RadiativeCorrection(W0={W0})")
@pytest.mark.quality
@pytest.mark.parametrize("W", [
np.linspace(1.0001, 4.9999, 200),
np.linspace(1.001, 9.99, 100),
])
def _test_full_range_stability(self, W):
"""Entire energy range from threshold to endpoint must be free of NaN/inf."""
rc = RadiativeCorrection(W0=5.0, Z=92, use_endpoint_resummation=True)
from tests.common.test_property_tests import _test_full_range_stability
_test_full_range_stability(rc, W, component_name="RadiativeCorrection(Z=92)")
@pytest.mark.quality
def test_ultra_low_energy_stable(self):
"""W = 1.00001 (beta ~ 0.014) — deep in small-beta regime."""
rc = RadiativeCorrection(W0=5.0, Z=92, use_endpoint_resummation=True)
W_ultra_low = np.array([1.00001])
result = rc(W_ultra_low)
assert not np.isnan(result[0])
assert not np.isinf(result[0])
tests/quality/test_api_screening.py
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"""
Code quality / API tests for ScreeningCorrection.
Shared property tests in tests/common/test_property_tests.py.
"""
import numpy as np
import pytest
from beta_spectrum.components.fermi import FermiFunction
from beta_spectrum.components.screening import ScreeningCorrection
class TestScreeningAPI:
@pytest.mark.api
def test_callable(self):
ff = FermiFunction(Z=20, A=40)
sc = ScreeningCorrection(ff)
assert callable(sc)
result = sc(np.array([2.0]))
assert isinstance(result, np.ndarray)
@pytest.mark.api
def test_repr(self):
ff = FermiFunction(Z=20, A=40)
sc = ScreeningCorrection(ff)
assert "Screening" in repr(sc)
class TestScreeningProperties:
@pytest.mark.property
@pytest.mark.parametrize("W", [
[2.0],
np.linspace(1.02, 3.0, 20),
])
def test_positive(self, W):
ff = FermiFunction(Z=40, A=95)
sc = ScreeningCorrection(ff)
from tests.common.test_property_tests import _test_positive_values
_test_positive_values(sc, W, component_name="ScreeningCorrection")
@pytest.mark.quality
@pytest.mark.parametrize("n", [1, 5, 100])
def test_shape(self, n):
ff = FermiFunction(Z=20, A=40)
sc = ScreeningCorrection(ff)
W = np.linspace(1.1, 3.0, n)
from tests.common.test_property_tests import _test_output_shape_preserved
_test_output_shape_preserved(sc, W, component_name="ScreeningCorrection")