bookmark - Refactor

tests/test_criteria/test_chest_femur_tibia.py

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+"""Tests for chest deflection, femur load, tibia index, 3ms clip, viscous criterion."""
+
+import numpy as np
+import pytest
+
+from impakt.criteria import chest_deflection, clip_3ms, femur_load, tibia_index, viscous_criterion
+
+
+class TestChestDeflection:
+    def test_basic(self, chest_deflection_channel):
+        result = chest_deflection(channel=chest_deflection_channel)
+        assert result.criterion == "Chest Deflection"
+        assert result.unit == "mm"
+        assert 30.0 < result.value < 40.0  # ~35mm in fixture
+
+    def test_peak_time(self, chest_deflection_channel):
+        result = chest_deflection(channel=chest_deflection_channel)
+        assert result.time_of_peak is not None
+        assert 0.0 < result.time_of_peak < 0.1
+
+
+class TestClip3ms:
+    def test_basic(self, head_accel_x):
+        result = clip_3ms(head_accel_x)
+        assert result.criterion == "3ms Clip"
+        assert result.value > 0
+
+    def test_body_region(self, head_accel_x):
+        result = clip_3ms(head_accel_x)
+        assert result.body_region == "Chest"
+
+
+class TestFemurLoad:
+    def test_single_channel(self, femur_left_channel):
+        result = femur_load(channel=femur_left_channel, side="left")
+        assert result.criterion == "Femur Load Left"
+        assert result.unit == "kN"
+        assert result.value > 0
+
+    def test_peak_time(self, femur_left_channel):
+        result = femur_load(channel=femur_left_channel, side="left")
+        assert result.time_of_peak is not None
+
+
+class TestTibiaIndex:
+    def test_with_all_components(self, time_array, sample_rate):
+        from impakt.channel.code import ChannelCode
+        from impakt.channel.model import Channel
+
+        t = time_array
+        fz = np.zeros_like(t)
+        mx = np.zeros_like(t)
+        my = np.zeros_like(t)
+        mask = (t >= 0.02) & (t <= 0.08)
+        fz[mask] = -5000 * np.sin(np.pi * (t[mask] - 0.02) / 0.06)
+        mx[mask] = 50 * np.sin(np.pi * (t[mask] - 0.02) / 0.06)
+        my[mask] = 80 * np.sin(np.pi * (t[mask] - 0.02) / 0.06)
+
+        fz_ch = Channel(
+            name="TIBFZ",
+            code=ChannelCode.parse("TIBFZ"),
+            data=fz,
+            time=t,
+            unit="N",
+            sample_rate=sample_rate,
+        )
+        mx_ch = Channel(
+            name="TIBMX",
+            code=ChannelCode.parse("TIBMX"),
+            data=mx,
+            time=t,
+            unit="N·m",
+            sample_rate=sample_rate,
+        )
+        my_ch = Channel(
+            name="TIBMY",
+            code=ChannelCode.parse("TIBMY"),
+            data=my,
+            time=t,
+            unit="N·m",
+            sample_rate=sample_rate,
+        )
+
+        result = tibia_index(fz_channel=fz_ch, mx_channel=mx_ch, my_channel=my_ch)
+        assert result.value > 0
+
+
+class TestViscousCriterion:
+    def test_basic(self, chest_deflection_channel):
+        result = viscous_criterion(channel=chest_deflection_channel)
+        assert result.criterion == "Viscous Criterion"
+        assert result.unit == "m/s"
+        assert result.value >= 0