Test rep metric variation detection

tests/test_rep_analysis_variation.py

@@ -0,0 +1,196 @@
+from __future__ import annotations
+
+from pathlib import Path
+import math
+import sys
+import unittest
+
+sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "src"))
+
+from pozify.contracts import (
+    ExerciseClassification,
+    PoseFrame,
+    PoseSequence,
+    Rep,
+    Reps,
+    UserProfile,
+)
+from pozify.steps import rep_analysis, variation_detector
+
+
+def _frame(frame_index: int, landmarks: dict[str, dict[str, float]]) -> PoseFrame:
+    return PoseFrame(
+        frame_index=frame_index,
+        timestamp_sec=round(frame_index / 30.0, 3),
+        landmarks=landmarks,
+        world_landmarks={},
+        pose_quality={"mean_visibility": 0.95, "normalized": True},
+    )
+
+
+def _wave(frame_index: int, cycle_frames: int) -> float:
+    return (1.0 - math.cos(2.0 * math.pi * (frame_index / cycle_frames))) / 2.0
+
+
+def _push_up_landmarks(depth: float, *, hand_ratio: float = 1.7) -> dict[str, dict[str, float]]:
+    shoulder_y = 0.38 + depth * 0.16
+    hip_y = 0.46 + depth * 0.16
+    ankle_y = 0.54 + depth * 0.16
+    elbow_y = 0.46 + depth * 0.1
+    wrist_y = 0.5 + depth * 0.04
+    shoulder_width = 0.4
+    hand_width = shoulder_width * hand_ratio
+    return {
+        "left_shoulder": {"x": 0.3, "y": shoulder_y},
+        "right_shoulder": {"x": 0.7, "y": shoulder_y},
+        "left_elbow": {"x": 0.36 + depth * 0.02, "y": elbow_y},
+        "right_elbow": {"x": 0.64 - depth * 0.02, "y": elbow_y},
+        "left_wrist": {"x": 0.5 - hand_width / 2, "y": wrist_y},
+        "right_wrist": {"x": 0.5 + hand_width / 2, "y": wrist_y},
+        "left_hip": {"x": 0.42, "y": hip_y},
+        "right_hip": {"x": 0.58, "y": hip_y},
+        "left_ankle": {"x": 0.44, "y": ankle_y},
+        "right_ankle": {"x": 0.56, "y": ankle_y},
+    }
+
+
+def _squat_landmarks(depth: float, *, stance_ratio: float = 1.5) -> dict[str, dict[str, float]]:
+    shoulder_width = 0.2
+    stance_width = shoulder_width * stance_ratio
+    hip_y = 0.52 + depth * 0.22
+    shoulder_y = 0.28 + depth * 0.06
+    knee_y = 0.7
+    return {
+        "left_shoulder": {"x": 0.4, "y": shoulder_y},
+        "right_shoulder": {"x": 0.6, "y": shoulder_y},
+        "left_hip": {"x": 0.43, "y": hip_y},
+        "right_hip": {"x": 0.57, "y": hip_y},
+        "left_knee": {"x": 0.43 + depth * 0.05, "y": knee_y},
+        "right_knee": {"x": 0.57 - depth * 0.05, "y": knee_y},
+        "left_ankle": {"x": 0.5 - stance_width / 2, "y": 0.92},
+        "right_ankle": {"x": 0.5 + stance_width / 2, "y": 0.92},
+    }
+
+
+def _shoulder_press_landmarks(lift: float, *, partial: bool = True) -> dict[str, dict[str, float]]:
+    wrist_top = 0.56 if partial else 0.42
+    wrist_y = 0.76 - lift * (0.76 - wrist_top)
+    elbow_y = 0.6 - lift * 0.06
+    return {
+        "left_shoulder": {"x": 0.42, "y": 0.42},
+        "right_shoulder": {"x": 0.58, "y": 0.42},
+        "left_elbow": {"x": 0.4 - lift * 0.02, "y": elbow_y},
+        "right_elbow": {"x": 0.6 + lift * 0.02, "y": elbow_y},
+        "left_wrist": {"x": 0.4, "y": wrist_y},
+        "right_wrist": {"x": 0.6, "y": wrist_y},
+        "left_hip": {"x": 0.44, "y": 0.74},
+        "right_hip": {"x": 0.56, "y": 0.74},
+    }
+
+
+def _sequence(exercise: str) -> PoseSequence:
+    frames = []
+    for frame_index in range(25):
+        wave = _wave(frame_index, 24)
+        if exercise == "push_up":
+            landmarks = _push_up_landmarks(wave)
+        elif exercise == "shoulder_press":
+            landmarks = _shoulder_press_landmarks(wave)
+        else:
+            landmarks = _squat_landmarks(wave)
+        frames.append(_frame(frame_index, landmarks))
+    return PoseSequence(
+        frames=frames,
+        normalized=True,
+        smoothing_method="none",
+        pose_valid_ratio=1.0,
+    )
+
+
+def _classification(exercise: str) -> ExerciseClassification:
+    return ExerciseClassification(
+        exercise=exercise,
+        confidence=0.95,
+        window_predictions=[],
+        fallback_required=False,
+    )
+
+
+def _reps(exercise: str) -> Reps:
+    return Reps(
+        exercise=exercise,
+        reps=[Rep(1, 0, 12, 24, 0.0, 0.4, 0.8)],
+        partial_reps=[],
+    )
+
+
+def _profile() -> UserProfile:
+    return UserProfile(
+        goal="beginner_practice",
+        experience_level="beginner",
+        intended_exercise="auto",
+        intended_variation=None,
+        known_limitations=[],
+        equipment="bodyweight",
+    )
+
+
+class RepAnalysisVariationTests(unittest.TestCase):
+    def test_push_up_metrics_detect_wide_grip_variation(self) -> None:
+        analysis = rep_analysis.run(
+            _classification("push_up"),
+            _reps("push_up"),
+            _sequence("push_up"),
+        )
+        variation = variation_detector.run(_classification("push_up"), analysis, _profile())
+
+        self.assertEqual(variation.detected_variation, "wide_grip_push_up")
+        self.assertIn("wide_hand_placement", variation.not_issues)
+        self.assertGreater(analysis.items[0].metrics["hand_width_ratio"], 1.45)
+        self.assertIn("body_line_score", analysis.items[0].metrics)
+
+    def test_squat_metrics_detect_wide_stance_variation(self) -> None:
+        analysis = rep_analysis.run(_classification("squat"), _reps("squat"), _sequence("squat"))
+        variation = variation_detector.run(_classification("squat"), analysis, _profile())
+
+        self.assertEqual(variation.detected_variation, "wide_squat_stance")
+        self.assertIn("wide_stance", variation.not_issues)
+        self.assertGreater(analysis.items[0].metrics["stance_width_ratio"], 1.35)
+        self.assertIn("min_knee_angle_deg", analysis.items[0].metrics)
+
+    def test_shoulder_press_metrics_detect_partial_press_variation(self) -> None:
+        analysis = rep_analysis.run(
+            _classification("shoulder_press"),
+            _reps("shoulder_press"),
+            _sequence("shoulder_press"),
+        )
+        variation = variation_detector.run(_classification("shoulder_press"), analysis, _profile())
+
+        self.assertEqual(variation.detected_variation, "partial_press")
+        self.assertIn("partial_range_of_motion", variation.not_issues)
+        self.assertIn("lockout_quality", analysis.items[0].metrics)
+        self.assertLess(analysis.aggregate_metrics["avg_wrist_travel"], 0.24)
+
+    def test_profile_intended_variation_overrides_metric_rule(self) -> None:
+        profile = UserProfile(
+            goal="beginner_practice",
+            experience_level="beginner",
+            intended_exercise="push_up",
+            intended_variation="close_grip_push_up",
+            known_limitations=[],
+            equipment="bodyweight",
+        )
+        analysis = rep_analysis.run(
+            _classification("push_up"),
+            _reps("push_up"),
+            _sequence("push_up"),
+        )
+        variation = variation_detector.run(_classification("push_up"), analysis, profile)
+
+        self.assertEqual(variation.detected_variation, "close_grip_push_up")
+        self.assertEqual(variation.variation_confidence, 0.95)
+        self.assertIn("close_hand_placement", variation.not_issues)
+
+
+if __name__ == "__main__":
+    unittest.main()