open source driving agent
				
			 
			
		 
		
		
		
		
		
		
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								#!/usr/bin/env python3
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								import numpy as np
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								import time
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								from tqdm import tqdm
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								from cereal import car
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								from openpilot.selfdrive.car.tests.routes import CarTestRoute
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								from openpilot.selfdrive.car.tests.test_models import TestCarModelBase
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								from openpilot.tools.plotjuggler.juggle import DEMO_ROUTE
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								N_RUNS = 10
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								class CarModelTestCase(TestCarModelBase):
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								  test_route = CarTestRoute(DEMO_ROUTE, None)
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								  ci = False
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								if __name__ == '__main__':
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								  # Get CAN messages and parsers
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								  tm = CarModelTestCase()
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								  tm.setUpClass()
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								  tm.setUp()
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								  CC = car.CarControl.new_message()
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								  ets = []
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								  for _ in tqdm(range(N_RUNS)):
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								    start_t = time.process_time_ns()
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								    for msg in tm.can_msgs:
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								      for cp in tm.CI.can_parsers:
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								        if cp is not None:
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								          cp.update_strings((msg.as_builder().to_bytes(),))
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								    ets.append((time.process_time_ns() - start_t) * 1e-6)
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								  print(f'{len(tm.can_msgs)} CAN packets, {N_RUNS} runs')
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								  print(f'{np.mean(ets):.2f} mean ms, {max(ets):.2f} max ms, {min(ets):.2f} min ms, {np.std(ets):.2f} std ms')
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								  print(f'{np.mean(ets) / len(tm.can_msgs):.4f} mean ms / CAN packet')
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