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							120 lines
						
					
					
						
							3.4 KiB
						
					
					
				
			
		
		
	
	
							120 lines
						
					
					
						
							3.4 KiB
						
					
					
				{
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 "cells": [
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "segments = [\n",
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    "  \"d9df6f87e8feff94|2023-03-28--17-41-10/1:12\"\n",
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    "]\n",
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    "platform = \"SUBARU_OUTBACK\"\n"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "import copy\n",
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    "import numpy as np\n",
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    "\n",
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    "from opendbc.can.parser import CANParser\n",
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    "\n",
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    "from openpilot.selfdrive.car.subaru.values import DBC\n",
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    "from openpilot.tools.lib.logreader import LogReader\n",
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    "\n",
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    "\"\"\"\n",
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    "In this example, we plot the relationship between Cruise_Brake and Acceleration for stock eyesight.\n",
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    "\"\"\"\n",
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    "\n",
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    "for segment in segments:\n",
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    "  lr = LogReader(segment)\n",
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    "\n",
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    "  messages = [\n",
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    "    (\"ES_Distance\", 20),\n",
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    "    (\"ES_Brake\", 20),\n",
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    "    (\"ES_Status\", 20),\n",
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    "  ]\n",
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    "\n",
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    "  cp = CANParser(DBC[platform][\"pt\"], messages, 1)\n",
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    "\n",
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    "  es_distance_history = []\n",
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    "  es_status_history = []\n",
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    "  es_brake_history = []\n",
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    "  acceleration_history = []\n",
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    "\n",
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    "  last_acc = 0\n",
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    "\n",
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    "  for msg in lr:\n",
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    "    if msg.which() == \"can\":\n",
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    "      cp.update_strings([msg.as_builder().to_bytes()])\n",
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    "      es_distance_history.append(copy.copy(cp.vl[\"ES_Distance\"]))\n",
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    "      es_brake_history.append(copy.copy(cp.vl[\"ES_Brake\"]))\n",
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    "      es_status_history.append(copy.copy(cp.vl[\"ES_Status\"]))\n",
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    "\n",
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    "      acceleration_history.append(last_acc)\n",
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    "\n",
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    "    if msg.which() == \"carState\":\n",
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    "      last_acc = msg.carState.aEgo"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "def process(history, func):\n",
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    "  return np.array([func(h) for h in history])\n",
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    "\n",
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    "cruise_activated = process(es_status_history, lambda es_status: es_status[\"Cruise_Activated\"])\n",
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    "cruise_throttle = process(es_distance_history, lambda es_distance: es_distance[\"Cruise_Throttle\"])\n",
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    "cruise_rpm = process(es_status_history, lambda es_status: es_status[\"Cruise_RPM\"])\n",
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    "cruise_brake = process(es_brake_history, lambda es_brake: es_brake[\"Brake_Pressure\"])\n",
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    "acceleration = process(acceleration_history, lambda acc: acc)"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "import matplotlib.pyplot as plt\n",
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    "\n",
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    "valid_brake = (cruise_activated==1) & (cruise_brake>0) # only when cruise is activated and eyesight is braking\n",
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    "\n",
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    "ax = plt.figure().add_subplot()\n",
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    "\n",
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    "ax.set_title(\"Brake_Pressure vs Acceleration\")\n",
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    "ax.set_xlabel(\"Brake_Pessure\")\n",
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    "ax.set_ylabel(\"Acceleration\")\n",
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    "ax.scatter(cruise_brake[valid_brake], -acceleration[valid_brake])"
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   ]
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  }
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 ],
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