96 lines
3.8 KiB
Python
96 lines
3.8 KiB
Python
import pytest
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import numpy as np
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import time
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from unittest.mock import Mock, patch
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from src.core.phase_sanitizer import PhaseSanitizer, PhaseSanitizationError
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_SANITIZER_CONFIG = {
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"unwrapping_method": "numpy",
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"outlier_threshold": 3.0,
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"smoothing_window": 5,
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"enable_outlier_removal": True,
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"enable_smoothing": True,
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"enable_noise_filtering": True,
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"noise_threshold": 0.1,
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}
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class TestPhaseSanitizer:
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"""Test suite for Phase Sanitizer following London School TDD principles"""
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@pytest.fixture
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def mock_phase_data(self):
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"""Generate synthetic phase data strictly within valid [-π, π] range"""
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return np.array([
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[0.1, 0.2, 0.4, 0.3, 0.5],
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[-1.0, -0.1, 0.0, 0.1, 0.2],
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[0.0, 0.1, 0.2, 0.3, 0.4],
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])
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@pytest.fixture
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def phase_sanitizer(self):
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"""Create Phase Sanitizer instance for testing"""
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return PhaseSanitizer(config=_SANITIZER_CONFIG)
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def test_unwrap_phase_removes_discontinuities(self, phase_sanitizer):
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"""Test that phase unwrapping removes 2π discontinuities"""
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# Create data with explicit 2π jump
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jumpy = np.array([[0.1, 0.2, 0.2 + 2 * np.pi, 0.4, 0.5]])
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result = phase_sanitizer.unwrap_phase(jumpy)
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assert result is not None
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assert isinstance(result, np.ndarray)
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assert result.shape == jumpy.shape
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phase_diffs = np.abs(np.diff(result[0]))
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assert np.all(phase_diffs < np.pi) # No jumps larger than π
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def test_remove_outliers_returns_same_shape(self, phase_sanitizer, mock_phase_data):
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"""Test that outlier removal preserves array shape"""
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result = phase_sanitizer.remove_outliers(mock_phase_data)
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assert result is not None
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assert isinstance(result, np.ndarray)
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assert result.shape == mock_phase_data.shape
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def test_smooth_phase_reduces_noise(self, phase_sanitizer, mock_phase_data):
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"""Test that phase smoothing reduces noise while preserving trends"""
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rng = np.random.default_rng(42)
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noisy_data = mock_phase_data + rng.normal(0, 0.05, mock_phase_data.shape)
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# Clip to valid range after adding noise
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noisy_data = np.clip(noisy_data, -np.pi, np.pi)
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result = phase_sanitizer.smooth_phase(noisy_data)
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assert result is not None
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assert isinstance(result, np.ndarray)
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assert result.shape == noisy_data.shape
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assert np.var(result) <= np.var(noisy_data)
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def test_sanitize_raises_for_1d_input(self, phase_sanitizer):
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"""Sanitizer should raise PhaseSanitizationError on 1D input"""
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with pytest.raises(PhaseSanitizationError, match="Phase data must be 2D array"):
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phase_sanitizer.sanitize_phase(np.array([0.1, 0.2, 0.3]))
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def test_sanitize_raises_for_empty_2d_input(self, phase_sanitizer):
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"""Sanitizer should raise PhaseSanitizationError on empty 2D input"""
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with pytest.raises(PhaseSanitizationError, match="Phase data cannot be empty"):
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phase_sanitizer.sanitize_phase(np.empty((0, 5)))
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def test_sanitize_full_pipeline_integration(self, phase_sanitizer, mock_phase_data):
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"""Test that full sanitization pipeline works correctly"""
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result = phase_sanitizer.sanitize_phase(mock_phase_data)
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assert result is not None
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assert isinstance(result, np.ndarray)
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assert result.shape == mock_phase_data.shape
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assert np.all(np.isfinite(result))
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def test_sanitize_performance_requirement(self, phase_sanitizer, mock_phase_data):
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"""Test that phase sanitization meets performance requirements (<5ms)"""
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start_time = time.perf_counter()
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phase_sanitizer.sanitize_phase(mock_phase_data)
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processing_time = time.perf_counter() - start_time
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assert processing_time < 0.005 # < 5 ms
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