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"""Test the resample module."""
import numpy as np
import pytest
from transivent.resample import average_downsample, downsample_to_interval
def test_average_downsample_basic():
"""Test basic downsampling functionality."""
# Create test data
t = np.linspace(0, 1, 1000)
x = np.ones(1000)
# Downsample by factor of 10
t_down, x_down = average_downsample(t, x, q=10)
assert len(t_down) == 100
assert len(x_down) == 100
assert np.allclose(x_down, 1.0) # Mean should be preserved
assert np.allclose(t_down[1] - t_down[0], t[10] - t[0]) # Check time step
def test_average_downsample_q1():
"""Test that q=1 returns unchanged data."""
t = np.linspace(0, 1, 100)
x = np.random.randn(100)
t_out, x_out = average_downsample(t, x, q=1)
np.testing.assert_array_equal(t_out, t)
np.testing.assert_array_equal(x_out, x)
def test_average_downsample_invalid_q():
"""Test error handling for invalid downsample factor."""
t = np.linspace(0, 1, 100)
x = np.random.randn(100)
with pytest.raises(ValueError, match="q must be >= 1"):
average_downsample(t, x, q=0)
with pytest.raises(ValueError, match="q must be >= 1"):
average_downsample(t, x, q=-1)
def test_average_downsample_short_array():
"""Test downsampling when array is shorter than factor."""
t = np.linspace(0, 1, 5)
x = np.ones(5)
with pytest.raises(ValueError, match="Input length .* is less than downsample factor"):
average_downsample(t, x, q=10)
def test_downsample_to_interval():
"""Test interval-based downsampling."""
# 10 kHz data (exact interval)
t = np.arange(10000) * 1e-4
x = np.random.randn(10000)
# Downsample to 1 kHz
t_down, x_down = downsample_to_interval(t, x, target_interval=1e-3)
# Should downsample by factor of 10
assert len(t_down) == 1000
assert len(x_down) == 1000
# Original dt was 1e-4, new dt should be 1e-3
assert np.allclose(t_down[1] - t_down[0], 1e-3)
def test_downsample_to_interval_upsampling():
"""Test error for upsampling (not supported)."""
t = np.linspace(0, 1, 1000) # dt = 0.001
x = np.random.randn(1000)
with pytest.raises(ValueError, match="Upsampling not supported"):
downsample_to_interval(t, x, target_interval=5e-4) # Smaller interval
def test_average_downsample_preserves_amplitude():
"""Test that amplitude is preserved through averaging."""
t = np.linspace(0, 1, 1000)
# Create a step function
x = np.concatenate([np.ones(500), 2 * np.ones(500)])
# Downsample by factor of 10
t_down, x_down = average_downsample(t, x, q=10)
# Check the transition is at the right place
transition_idx = 50 # 500 / 10
# First part should be ~1, second part should be ~2
assert np.allclose(x_down[:transition_idx], 1.0)
assert np.allclose(x_down[transition_idx:], 2.0)
if __name__ == "__main__":
pytest.main([__file__, "-v"])
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