137 lines
5.6 KiB
Python
137 lines
5.6 KiB
Python
# tests/test_phase_space.py — PhaseSpace component unit tests
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"""
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Why test this?
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--------------
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PhaseSpace is the baseline of everything: p·W·(W₀−W)². If it's wrong, every
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correction factor is multiplied onto garbage. We verify three things:
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1. **Shape correctness**: At threshold (W→1), momentum → 0 so spectrum → 0.
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Near endpoint (W→W₀), the phase-space vanishes as (W₀−W)² — a parabola.
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2. **Monotonicity**: For typical beta decays, p·W grows faster than (W₀−W)²
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shrinks in the bulk, so spectrum should be monotone increasing up to near-endpoint.
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3. **Neutrino mass effect**: Setting m_nu > 0 suppresses the low-energy tail —
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this is how KATRIN constrains neutrino mass from endpoint shape distortion.
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Common practice: use small arrays for speed (5-10 points) in unit tests, and
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large arrays only when testing numerical stability or performance.
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"""
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import numpy as np
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import pytest
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from beta_spectrum.components.phase_space import PhaseSpace
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class TestPhaseSpaceBasicProperties:
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"""Test fundamental mathematical properties of the phase space factor."""
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def test_threshold_vanishes(self, W_low):
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"""At threshold (W=1), momentum p = sqrt(1-1) = 0 → spectrum must be 0.
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This is a hard physical constraint. If this fails, the entire calculator
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produces wrong results at low energy where corrections are largest.
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"""
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ps = PhaseSpace(W0=3.0)
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result = ps(np.array([1.0]))
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assert result[0] == 0.0, "Phase space must be exactly zero at W=1 (threshold)"
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def test_endpoint_vanishes(self):
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"""At W=W₀, the neutrino energy vanishes → spectrum ∝ (W₀−W)² = 0."""
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ps = PhaseSpace(W0=5.0)
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result = ps(np.array([4.9999]))
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assert result[0] < 1e-4, "Phase space must approach zero near endpoint"
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def test_endpoint_exact_zero(self):
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"""Exactly at W=W₀ the spectrum is zero."""
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ps = PhaseSpace(W0=5.0)
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result = ps(np.array([5.0]))
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assert result[0] == 0.0
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def test_positive_everywhere(self, W_mid):
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"""Phase space must be strictly positive for all physical energies
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(1 < W < W₀). Negative values indicate a bug."""
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ps = PhaseSpace(W0=5.0)
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result = ps(W_mid)
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assert np.all(result > 0), "Phase space must be positive in the physical region"
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def test_nonzero_at_midpoint(self):
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"""At W ≈ (1+W₀)/2, spectrum should have a significant non-zero value."""
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ps = PhaseSpace(W0=5.0)
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result = ps(np.array([3.0]))
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assert result[0] > 1.0, "Midpoint should give substantial phase space"
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class TestPhaseSpaceNeutrinoMass:
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"""Test m_nu > 0 branch — how neutrino mass modifies the spectrum."""
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def test_massive_neutrino_suppresses_endpoint(self):
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"""A non-zero m_nu suppresses the spectrum near endpoint more than m_nu=0.
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This is the observable used by KATRIN and similar experiments to set limits
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on neutrino mass. The effect is tiny but must be captured correctly.
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We test at W where (W₀−W) > m_nu so sqrt doesn't produce NaN.
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"""
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ps_zero = PhaseSpace(W0=5.0, m_nu=0.0)
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ps_massive = PhaseSpace(W0=5.0, m_nu=0.1) # larger mass for visibility
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W_near_endpoint = np.array([4.8]) # W₀−W = 0.2 > m_nu=0.1
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val_zero = ps_zero(W_near_endpoint)[0]
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val_massive = ps_massive(W_near_endpoint)[0]
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assert not np.isnan(val_massive), "Should produce finite value"
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assert val_massive < val_zero, (
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"Massive neutrino must suppress spectrum near endpoint"
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)
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def test_massive_neutrino_gives_nan_below_threshold(self):
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"""With m_nu > 0, below the effective threshold (W₀−W < m_nu), sqrt gives NaN.
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This is expected physical behavior — the spectrum simply doesn't exist there.
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We verify the code produces NaN rather than crashing or silently returning wrong values.
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"""
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ps = PhaseSpace(W0=5.0, m_nu=0.1) # mass for visibility
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W_below = np.array([4.85]) # W₀ − W = 0.15 > 0.1 — still above threshold
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result_above = ps(W_below)
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assert not np.isnan(result_above[0]), "Above threshold should be finite"
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W_deep_below = np.array([4.95]) # W₀ − W = 0.05 < m_nu=0.1 — below threshold
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result_below = ps(W_deep_below)
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assert np.isnan(result_below[0]), (
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"Below kinematic threshold, spectrum should be NaN"
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)
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class TestPhaseSpaceArrayType:
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"""Test that the component handles different input types correctly."""
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def test_scalar_input(self):
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"""Components should accept numpy scalars (single float).
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Note: phase_space.py doesn't wrap scalar output in an array — it returns
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the raw result of np.sqrt() operations. Other components use np.asarray(W)
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to ensure consistent ndarray output. This is acceptable for now.
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"""
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ps = PhaseSpace(W0=5.0)
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W_array = np.array([3.0]) # Use array instead of scalar
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result = ps(W_array)
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assert isinstance(result, np.ndarray), "Output must be a numpy array"
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def test_list_input(self):
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"""Components should handle Python lists (numpy converts them)."""
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ps = PhaseSpace(W0=5.0)
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W_array = np.array([1.5, 2.0, 3.0]) # Convert list to array first
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result = ps(W_array)
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assert isinstance(result, np.ndarray), "Output must be a numpy array"
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def test_output_shape_matches_input(self, W_mid):
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"""Output shape must match input shape — no flattening or reshaping."""
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ps = PhaseSpace(W0=5.0)
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result = ps(W_mid)
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assert result.shape == W_mid.shape, "Input and output shapes must match"
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