initial commit

tests/test_transform/test_align.py

@@ -0,0 +1,49 @@
+"""Tests for alignment transforms."""
+
+import numpy as np
+import pytest
+
+from impakt.transform.align import XAlign, YAlign, x_align, y_align
+
+
+class TestXAlign:
+    def test_manual_shift(self, head_accel_x):
+        shifted = x_align(head_accel_x, method="manual", reference_time=0.01)
+        # Time should be shifted by -0.01s
+        assert np.isclose(shifted.time[0], head_accel_x.time[0] - 0.01, atol=1e-10)
+
+    def test_threshold_shift(self, head_accel_x):
+        shifted = XAlign(
+            method="threshold",
+            threshold_value=5.0,
+            threshold_direction="abs",
+        ).apply(head_accel_x)
+        # Time should be shifted so the first crossing of 5g is at t=0
+        # The first crossing should be very close to t=0 in the shifted signal
+        assert shifted.time[0] < 0  # Pre-trigger still negative
+
+    def test_trigger_noop(self, head_accel_x):
+        shifted = x_align(head_accel_x, method="trigger")
+        assert np.array_equal(shifted.time, head_accel_x.time)
+
+
+class TestYAlign:
+    def test_default_baseline(self, head_accel_x):
+        aligned = y_align(head_accel_x)
+        # Pre-trigger region should be very close to zero
+        pre_mask = aligned.time < 0
+        if np.any(pre_mask):
+            pre_mean = np.mean(aligned.data[pre_mask])
+            assert abs(pre_mean) < 0.1  # Should be near zero
+
+    def test_explicit_window(self, head_accel_x):
+        aligned = y_align(head_accel_x, window=(-0.01, 0.0))
+        # Mean over the window should be approximately zero
+        mask = (aligned.time >= -0.01) & (aligned.time <= 0.0)
+        window_mean = np.mean(aligned.data[mask])
+        assert abs(window_mean) < 0.1
+
+    def test_original_unchanged(self, head_accel_x):
+        original = head_accel_x.data.copy()
+        _ = y_align(head_accel_x)
+        assert np.array_equal(head_accel_x.data, original)

tests/test_transform/test_cfc.py

@@ -0,0 +1,53 @@
+"""Tests for CFC filtering."""
+
+import numpy as np
+import pytest
+
+from impakt.transform.cfc import CFCFilter, cfc_filter
+
+
+class TestCFCFilter:
+    def test_cfc60(self, head_accel_x):
+        filtered = cfc_filter(head_accel_x, 60)
+        assert filtered.cfc_class == 60
+        assert len(filtered.data) == len(head_accel_x.data)
+        # Filtered signal should be smoother (lower peak)
+        assert filtered.peak <= head_accel_x.peak
+        # But still retain the general shape
+        assert filtered.peak > 20.0  # Not completely killed
+
+    def test_cfc180(self, head_accel_x):
+        filtered = cfc_filter(head_accel_x, 180)
+        assert filtered.cfc_class == 180
+
+    def test_cfc600(self, head_accel_x):
+        filtered = cfc_filter(head_accel_x, 600)
+        assert filtered.cfc_class == 600
+
+    def test_cfc1000(self, head_accel_x):
+        filtered = cfc_filter(head_accel_x, 1000)
+        assert filtered.cfc_class == 1000
+        # CFC 1000 removes very little — peak should be close to original
+        assert abs(filtered.peak - head_accel_x.peak) < 5.0
+
+    def test_invalid_cfc_class(self):
+        with pytest.raises(ValueError, match="Invalid CFC class"):
+            CFCFilter(cfc_class=42)
+
+    def test_transform_history(self, head_accel_x):
+        filtered = cfc_filter(head_accel_x, 180)
+        assert len(filtered.transform_history) == 1
+        assert "CFC 180" in filtered.transform_history[0]
+
+    def test_original_unchanged(self, head_accel_x):
+        original_data = head_accel_x.data.copy()
+        _ = cfc_filter(head_accel_x, 180)
+        assert np.array_equal(head_accel_x.data, original_data)
+
+    def test_progressive_filtering(self, head_accel_x):
+        """Lower CFC classes should produce smoother (lower peak) output."""
+        peak_1000 = cfc_filter(head_accel_x, 1000).peak
+        peak_600 = cfc_filter(head_accel_x, 600).peak
+        peak_180 = cfc_filter(head_accel_x, 180).peak
+        peak_60 = cfc_filter(head_accel_x, 60).peak
+        assert peak_1000 >= peak_600 >= peak_180 >= peak_60