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Unit tests for core functionality.
"""
import numpy as np
import pytest
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
from src.features.engineering import (
compute_effective_pulses,
compute_peak_fluence,
compute_pulse_energy,
compute_spatial_overlap,
)
class TestFeatureEngineering:
"""Test physics-informed feature computations."""
def test_pulse_energy(self):
"""E = P / f: 100 mW / 100 kHz = 1 µJ"""
result = compute_pulse_energy(
np.array([100.0]), np.array([100.0])
)
np.testing.assert_allclose(result, [1.0], rtol=1e-5)
def test_pulse_energy_vectorized(self):
"""Test vectorized computation."""
powers = np.array([100, 200, 500])
rates = np.array([100, 100, 1000])
expected = np.array([1.0, 2.0, 0.5])
result = compute_pulse_energy(powers, rates)
np.testing.assert_allclose(result, expected, rtol=1e-5)
def test_peak_fluence_gaussian(self):
"""Test Gaussian beam fluence formula: F = 2E/(π*r²)"""
# 1 µJ pulse, 10 µm diameter (5 µm radius = 5e-4 cm)
result = compute_peak_fluence(np.array([1.0]), np.array([10.0]))
# Expected: 2 * 1e-6 / (π * (5e-4)²) = 2.546 J/cm²
expected = 2 * 1e-6 / (np.pi * (5e-4) ** 2)
np.testing.assert_allclose(result, [expected], rtol=1e-3)
def test_effective_pulses(self):
"""N_eff = f_rep * d_spot / v_scan"""
# 100 kHz, 10 µm spot, 1 mm/s
result = compute_effective_pulses(
np.array([100.0]), # kHz
np.array([10.0]), # µm
np.array([1.0]), # mm/s
)
# Expected: 100*1000 Hz * 10e-3 mm / 1 mm/s = 1000
np.testing.assert_allclose(result, [1000.0], rtol=1e-5)
def test_overlap_high_speed(self):
"""High speed → low overlap."""
result = compute_spatial_overlap(
np.array([10.0]), # mm/s (fast)
np.array([100.0]), # kHz
np.array([10.0]), # µm
)
# pitch = 10 / (100*1000) * 1000 = 0.1 µm → overlap ≈ 99%
assert result[0] > 90
def test_overlap_bounds(self):
"""Overlap should be clipped to [0, 99.9%]."""
result = compute_spatial_overlap(
np.array([1000.0]), # Very fast
np.array([1.0]), # Low rep rate
np.array([1.0]), # Small spot
)
assert result[0] >= 0
assert result[0] <= 100
class TestDataIntegrity:
"""Test data loading and preprocessing."""
def test_no_negative_targets(self):
"""Physical targets should be non-negative."""
# Generate dummy data matching expected format
n = 100
targets = np.random.exponential(5, size=(n, 5))
assert np.all(targets >= 0)
def test_feature_target_dimensions(self):
"""Feature and target arrays should have correct shapes."""
n_samples, n_features, n_targets = 100, 21, 5
X = np.random.randn(n_samples, n_features).astype(np.float32)
y = np.random.randn(n_samples, n_targets).astype(np.float32)
assert X.shape == (n_samples, n_features)
assert y.shape == (n_samples, n_targets)
if __name__ == "__main__":
pytest.main([__file__, "-v"])
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