577 lines
22 KiB
Python
577 lines
22 KiB
Python
"""
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Integration tests for end-to-end pose estimation pipeline.
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Tests the complete pose estimation workflow from CSI data to pose results.
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"""
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import pytest
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import asyncio
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import numpy as np
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from datetime import datetime, timedelta
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from typing import Dict, Any, List, Optional
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from unittest.mock import AsyncMock, MagicMock, patch
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import json
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from dataclasses import dataclass
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@dataclass
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class CSIData:
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"""CSI data structure for testing."""
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timestamp: datetime
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router_id: str
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amplitude: np.ndarray
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phase: np.ndarray
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frequency: float
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bandwidth: float
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antenna_count: int
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subcarrier_count: int
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@dataclass
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class PoseResult:
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"""Pose estimation result structure."""
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timestamp: datetime
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frame_id: str
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persons: List[Dict[str, Any]]
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zone_summary: Dict[str, int]
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processing_time_ms: float
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confidence_scores: List[float]
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metadata: Dict[str, Any]
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class MockCSIProcessor:
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"""Mock CSI data processor."""
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def __init__(self):
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self.is_initialized = False
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self.processing_enabled = True
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async def initialize(self):
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"""Initialize the processor."""
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self.is_initialized = True
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async def process_csi_data(self, csi_data: CSIData) -> Dict[str, Any]:
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"""Process CSI data into features."""
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if not self.is_initialized:
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raise RuntimeError("Processor not initialized")
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if not self.processing_enabled:
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raise RuntimeError("Processing disabled")
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# Simulate processing
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await asyncio.sleep(0.01) # Simulate processing time
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return {
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"features": np.random.rand(64, 32).tolist(), # Mock feature matrix
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"quality_score": 0.85,
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"signal_strength": -45.2,
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"noise_level": -78.1,
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"processed_at": datetime.utcnow().isoformat()
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}
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def set_processing_enabled(self, enabled: bool):
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"""Enable/disable processing."""
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self.processing_enabled = enabled
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class MockPoseEstimator:
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"""Mock pose estimation model."""
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def __init__(self):
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self.is_loaded = False
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self.model_version = "1.0.0"
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self.confidence_threshold = 0.5
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async def load_model(self):
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"""Load the pose estimation model."""
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await asyncio.sleep(0.1) # Simulate model loading
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self.is_loaded = True
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async def estimate_poses(self, features: np.ndarray) -> Dict[str, Any]:
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"""Estimate poses from features."""
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if not self.is_loaded:
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raise RuntimeError("Model not loaded")
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# Simulate pose estimation
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await asyncio.sleep(0.05) # Simulate inference time
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# Generate mock pose data
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num_persons = np.random.randint(0, 4) # 0-3 persons
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persons = []
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for i in range(num_persons):
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confidence = np.random.uniform(0.3, 0.95)
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if confidence >= self.confidence_threshold:
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persons.append({
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"person_id": f"person_{i}",
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"confidence": confidence,
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"bounding_box": {
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"x": np.random.uniform(0, 800),
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"y": np.random.uniform(0, 600),
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"width": np.random.uniform(50, 200),
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"height": np.random.uniform(100, 400)
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},
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"keypoints": [
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{
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"name": "head",
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"x": np.random.uniform(0, 800),
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"y": np.random.uniform(0, 200),
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"confidence": np.random.uniform(0.5, 0.95)
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},
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{
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"name": "torso",
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"x": np.random.uniform(0, 800),
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"y": np.random.uniform(200, 400),
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"confidence": np.random.uniform(0.5, 0.95)
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}
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],
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"activity": "standing" if np.random.random() > 0.2 else "sitting"
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})
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return {
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"persons": persons,
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"processing_time_ms": np.random.uniform(20, 80),
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"model_version": self.model_version,
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"confidence_threshold": self.confidence_threshold
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}
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def set_confidence_threshold(self, threshold: float):
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"""Set confidence threshold."""
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self.confidence_threshold = threshold
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class MockZoneManager:
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"""Mock zone management system."""
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def __init__(self):
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self.zones = {
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"zone1": {"id": "zone1", "name": "Zone 1", "bounds": [0, 0, 400, 600]},
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"zone2": {"id": "zone2", "name": "Zone 2", "bounds": [400, 0, 800, 600]},
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"zone3": {"id": "zone3", "name": "Zone 3", "bounds": [0, 300, 800, 600]}
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}
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def assign_persons_to_zones(self, persons: List[Dict[str, Any]]) -> Dict[str, Any]:
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"""Assign detected persons to zones."""
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zone_summary = {zone_id: 0 for zone_id in self.zones.keys()}
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for person in persons:
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bbox = person["bounding_box"]
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person_center_x = bbox["x"] + bbox["width"] / 2
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person_center_y = bbox["y"] + bbox["height"] / 2
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# Check which zone the person is in
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for zone_id, zone in self.zones.items():
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x1, y1, x2, y2 = zone["bounds"]
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if x1 <= person_center_x <= x2 and y1 <= person_center_y <= y2:
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zone_summary[zone_id] += 1
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person["zone_id"] = zone_id
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break
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else:
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person["zone_id"] = None
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return zone_summary
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class TestPosePipelineIntegration:
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"""Integration tests for the complete pose estimation pipeline."""
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@pytest.fixture
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def csi_processor(self):
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"""Create CSI processor."""
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return MockCSIProcessor()
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@pytest.fixture
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def pose_estimator(self):
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"""Create pose estimator."""
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return MockPoseEstimator()
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@pytest.fixture
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def zone_manager(self):
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"""Create zone manager."""
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return MockZoneManager()
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@pytest.fixture
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def sample_csi_data(self):
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"""Create sample CSI data."""
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return CSIData(
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timestamp=datetime.utcnow(),
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router_id="router_001",
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amplitude=np.random.rand(64, 32),
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phase=np.random.rand(64, 32),
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frequency=5.8e9, # 5.8 GHz
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bandwidth=80e6, # 80 MHz
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antenna_count=4,
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subcarrier_count=64
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)
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@pytest.fixture
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async def pose_pipeline(self, csi_processor, pose_estimator, zone_manager):
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"""Create complete pose pipeline."""
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class PosePipeline:
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def __init__(self, csi_processor, pose_estimator, zone_manager):
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self.csi_processor = csi_processor
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self.pose_estimator = pose_estimator
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self.zone_manager = zone_manager
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self.is_initialized = False
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async def initialize(self):
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"""Initialize the pipeline."""
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await self.csi_processor.initialize()
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await self.pose_estimator.load_model()
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self.is_initialized = True
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async def process_frame(self, csi_data: CSIData) -> PoseResult:
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"""Process a single frame through the pipeline."""
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if not self.is_initialized:
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raise RuntimeError("Pipeline not initialized")
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start_time = datetime.utcnow()
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# Step 1: Process CSI data
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processed_data = await self.csi_processor.process_csi_data(csi_data)
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# Step 2: Extract features
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features = np.array(processed_data["features"])
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# Step 3: Estimate poses
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pose_data = await self.pose_estimator.estimate_poses(features)
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# Step 4: Assign to zones
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zone_summary = self.zone_manager.assign_persons_to_zones(pose_data["persons"])
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# Calculate processing time
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end_time = datetime.utcnow()
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processing_time = (end_time - start_time).total_seconds() * 1000
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return PoseResult(
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timestamp=start_time,
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frame_id=f"frame_{int(start_time.timestamp() * 1000)}",
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persons=pose_data["persons"],
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zone_summary=zone_summary,
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processing_time_ms=processing_time,
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confidence_scores=[p["confidence"] for p in pose_data["persons"]],
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metadata={
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"csi_quality": processed_data["quality_score"],
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"signal_strength": processed_data["signal_strength"],
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"model_version": pose_data["model_version"],
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"router_id": csi_data.router_id
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}
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)
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pipeline = PosePipeline(csi_processor, pose_estimator, zone_manager)
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await pipeline.initialize()
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return pipeline
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@pytest.mark.asyncio
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async def test_pipeline_initialization_should_fail_initially(self, csi_processor, pose_estimator, zone_manager):
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"""Test pipeline initialization - should fail initially."""
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class PosePipeline:
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def __init__(self, csi_processor, pose_estimator, zone_manager):
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self.csi_processor = csi_processor
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self.pose_estimator = pose_estimator
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self.zone_manager = zone_manager
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self.is_initialized = False
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async def initialize(self):
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await self.csi_processor.initialize()
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await self.pose_estimator.load_model()
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self.is_initialized = True
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pipeline = PosePipeline(csi_processor, pose_estimator, zone_manager)
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# Initially not initialized
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assert not pipeline.is_initialized
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assert not csi_processor.is_initialized
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assert not pose_estimator.is_loaded
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# Initialize pipeline
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await pipeline.initialize()
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# This will fail initially
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assert pipeline.is_initialized
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assert csi_processor.is_initialized
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assert pose_estimator.is_loaded
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@pytest.mark.asyncio
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async def test_end_to_end_pose_estimation_should_fail_initially(self, pose_pipeline, sample_csi_data):
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"""Test end-to-end pose estimation - should fail initially."""
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result = await pose_pipeline.process_frame(sample_csi_data)
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# This will fail initially
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assert isinstance(result, PoseResult)
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assert result.timestamp is not None
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assert result.frame_id.startswith("frame_")
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assert isinstance(result.persons, list)
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assert isinstance(result.zone_summary, dict)
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assert result.processing_time_ms > 0
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assert isinstance(result.confidence_scores, list)
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assert isinstance(result.metadata, dict)
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# Verify zone summary
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expected_zones = ["zone1", "zone2", "zone3"]
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for zone_id in expected_zones:
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assert zone_id in result.zone_summary
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assert isinstance(result.zone_summary[zone_id], int)
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assert result.zone_summary[zone_id] >= 0
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# Verify metadata
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assert "csi_quality" in result.metadata
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assert "signal_strength" in result.metadata
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assert "model_version" in result.metadata
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assert "router_id" in result.metadata
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assert result.metadata["router_id"] == sample_csi_data.router_id
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@pytest.mark.asyncio
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async def test_pipeline_with_multiple_frames_should_fail_initially(self, pose_pipeline):
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"""Test pipeline with multiple frames - should fail initially."""
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results = []
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# Process multiple frames
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for i in range(5):
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csi_data = CSIData(
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timestamp=datetime.utcnow(),
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router_id=f"router_{i % 2 + 1:03d}", # Alternate between router_001 and router_002
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amplitude=np.random.rand(64, 32),
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phase=np.random.rand(64, 32),
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frequency=5.8e9,
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bandwidth=80e6,
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antenna_count=4,
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subcarrier_count=64
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)
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result = await pose_pipeline.process_frame(csi_data)
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results.append(result)
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# This will fail initially
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assert len(results) == 5
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# Verify each result
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for i, result in enumerate(results):
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assert result.frame_id != results[0].frame_id if i > 0 else True
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assert result.metadata["router_id"] in ["router_001", "router_002"]
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assert result.processing_time_ms > 0
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@pytest.mark.asyncio
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async def test_pipeline_error_handling_should_fail_initially(self, csi_processor, pose_estimator, zone_manager, sample_csi_data):
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"""Test pipeline error handling - should fail initially."""
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class PosePipeline:
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def __init__(self, csi_processor, pose_estimator, zone_manager):
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self.csi_processor = csi_processor
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self.pose_estimator = pose_estimator
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self.zone_manager = zone_manager
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self.is_initialized = False
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async def initialize(self):
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await self.csi_processor.initialize()
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await self.pose_estimator.load_model()
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self.is_initialized = True
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async def process_frame(self, csi_data):
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if not self.is_initialized:
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raise RuntimeError("Pipeline not initialized")
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processed_data = await self.csi_processor.process_csi_data(csi_data)
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features = np.array(processed_data["features"])
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pose_data = await self.pose_estimator.estimate_poses(features)
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return pose_data
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pipeline = PosePipeline(csi_processor, pose_estimator, zone_manager)
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# Test uninitialized pipeline
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with pytest.raises(RuntimeError, match="Pipeline not initialized"):
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await pipeline.process_frame(sample_csi_data)
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# Initialize pipeline
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await pipeline.initialize()
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# Test with disabled CSI processor
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csi_processor.set_processing_enabled(False)
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with pytest.raises(RuntimeError, match="Processing disabled"):
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await pipeline.process_frame(sample_csi_data)
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# This assertion will fail initially
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assert True # Test completed successfully
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@pytest.mark.asyncio
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async def test_confidence_threshold_filtering_should_fail_initially(self, pose_pipeline, sample_csi_data):
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"""Test confidence threshold filtering - should fail initially."""
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# Set high confidence threshold
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pose_pipeline.pose_estimator.set_confidence_threshold(0.9)
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result = await pose_pipeline.process_frame(sample_csi_data)
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# This will fail initially
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# With high threshold, fewer persons should be detected
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high_confidence_count = len(result.persons)
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# Set low confidence threshold
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pose_pipeline.pose_estimator.set_confidence_threshold(0.1)
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result = await pose_pipeline.process_frame(sample_csi_data)
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low_confidence_count = len(result.persons)
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# Low threshold should detect same or more persons
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assert low_confidence_count >= high_confidence_count
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# All detected persons should meet the threshold
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for person in result.persons:
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assert person["confidence"] >= 0.1
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class TestPipelinePerformance:
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"""Test pose pipeline performance characteristics."""
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@pytest.mark.asyncio
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async def test_pipeline_throughput_should_fail_initially(self, pose_pipeline):
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"""Test pipeline throughput - should fail initially."""
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frame_count = 10
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start_time = datetime.utcnow()
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# Process multiple frames
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for i in range(frame_count):
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csi_data = CSIData(
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timestamp=datetime.utcnow(),
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router_id="router_001",
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amplitude=np.random.rand(64, 32),
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phase=np.random.rand(64, 32),
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frequency=5.8e9,
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bandwidth=80e6,
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antenna_count=4,
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subcarrier_count=64
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)
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await pose_pipeline.process_frame(csi_data)
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end_time = datetime.utcnow()
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total_time = (end_time - start_time).total_seconds()
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fps = frame_count / total_time
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# This will fail initially
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assert fps > 5.0 # Should process at least 5 FPS
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assert total_time < 5.0 # Should complete 10 frames in under 5 seconds
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@pytest.mark.asyncio
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async def test_concurrent_frame_processing_should_fail_initially(self, pose_pipeline):
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"""Test concurrent frame processing - should fail initially."""
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async def process_single_frame(frame_id: int):
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csi_data = CSIData(
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timestamp=datetime.utcnow(),
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router_id=f"router_{frame_id % 3 + 1:03d}",
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amplitude=np.random.rand(64, 32),
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phase=np.random.rand(64, 32),
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frequency=5.8e9,
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bandwidth=80e6,
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antenna_count=4,
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subcarrier_count=64
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)
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result = await pose_pipeline.process_frame(csi_data)
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return result.frame_id
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# Process frames concurrently
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tasks = [process_single_frame(i) for i in range(5)]
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results = await asyncio.gather(*tasks)
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# This will fail initially
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assert len(results) == 5
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assert len(set(results)) == 5 # All frame IDs should be unique
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@pytest.mark.asyncio
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async def test_memory_usage_stability_should_fail_initially(self, pose_pipeline):
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"""Test memory usage stability - should fail initially."""
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import psutil
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import os
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process = psutil.Process(os.getpid())
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initial_memory = process.memory_info().rss
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# Process many frames
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for i in range(50):
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csi_data = CSIData(
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timestamp=datetime.utcnow(),
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router_id="router_001",
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amplitude=np.random.rand(64, 32),
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phase=np.random.rand(64, 32),
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frequency=5.8e9,
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bandwidth=80e6,
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antenna_count=4,
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subcarrier_count=64
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)
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await pose_pipeline.process_frame(csi_data)
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# Periodic memory check
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if i % 10 == 0:
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current_memory = process.memory_info().rss
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memory_increase = current_memory - initial_memory
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# This will fail initially
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# Memory increase should be reasonable (less than 100MB)
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assert memory_increase < 100 * 1024 * 1024
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final_memory = process.memory_info().rss
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total_increase = final_memory - initial_memory
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# Total memory increase should be reasonable
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assert total_increase < 200 * 1024 * 1024 # Less than 200MB increase
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class TestPipelineDataFlow:
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"""Test data flow through the pipeline."""
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@pytest.mark.asyncio
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async def test_data_transformation_chain_should_fail_initially(self, csi_processor, pose_estimator, zone_manager, sample_csi_data):
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"""Test data transformation through the pipeline - should fail initially."""
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# Step 1: CSI processing
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await csi_processor.initialize()
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processed_data = await csi_processor.process_csi_data(sample_csi_data)
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# This will fail initially
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assert "features" in processed_data
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assert "quality_score" in processed_data
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assert isinstance(processed_data["features"], list)
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assert 0 <= processed_data["quality_score"] <= 1
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# Step 2: Pose estimation
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await pose_estimator.load_model()
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features = np.array(processed_data["features"])
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pose_data = await pose_estimator.estimate_poses(features)
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assert "persons" in pose_data
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assert "processing_time_ms" in pose_data
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assert isinstance(pose_data["persons"], list)
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# Step 3: Zone assignment
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zone_summary = zone_manager.assign_persons_to_zones(pose_data["persons"])
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assert isinstance(zone_summary, dict)
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assert all(isinstance(count, int) for count in zone_summary.values())
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# Verify person zone assignments
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for person in pose_data["persons"]:
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if "zone_id" in person and person["zone_id"]:
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assert person["zone_id"] in zone_summary
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@pytest.mark.asyncio
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async def test_pipeline_state_consistency_should_fail_initially(self, pose_pipeline, sample_csi_data):
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"""Test pipeline state consistency - should fail initially."""
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# Process the same frame multiple times
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results = []
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for _ in range(3):
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result = await pose_pipeline.process_frame(sample_csi_data)
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results.append(result)
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# This will fail initially
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# Results should be consistent (same input should produce similar output)
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assert len(results) == 3
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# All results should have the same router_id
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router_ids = [r.metadata["router_id"] for r in results]
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assert all(rid == router_ids[0] for rid in router_ids)
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# Processing times should be reasonable and similar
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processing_times = [r.processing_time_ms for r in results]
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assert all(10 <= pt <= 200 for pt in processing_times) # Between 10ms and 200ms |