text: """
  Copyright (c) 2018, Comma.ai, Inc.
  
  Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
  
  The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
  
  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
  
  """
  import os
  import math
  from common.realtime import sec_since_boot
  from selfdrive.swaglog import cloudlog
  from selfdrive.controls.lib.lateral_mpc import libmpc_py
  from selfdrive.controls.lib.drive_helpers import MPC_COST_LAT
  from selfdrive.controls.lib.lane_planner import LanePlanner
  import selfdrive.messaging as messaging
  
  LOG_MPC = os.environ.get('LOG_MPC', False)
  
  
  def calc_states_after_delay(states, v_ego, steer_angle, curvature_factor, steer_ratio, delay):
    states[0].x = v_ego * delay
    states[0].psi = v_ego * curvature_factor * math.radians(steer_angle) / steer_ratio * delay
    return states
  
  
  class PathPlanner():
    def __init__(self, CP):
      self.LP = LanePlanner()
  
      self.last_cloudlog_t = 0
  
      self.setup_mpc(CP.steerRateCost)
      self.solution_invalid_cnt = 0
      self.path_offset_i = 0.0
  
    def setup_mpc(self, steer_rate_cost):
      self.libmpc = libmpc_py.libmpc
      self.libmpc.init(MPC_COST_LAT.PATH, MPC_COST_LAT.LANE, MPC_COST_LAT.HEADING, steer_rate_cost)
  
      self.mpc_solution = libmpc_py.ffi.new("log_t *")
      self.cur_state = libmpc_py.ffi.new("state_t *")
      self.cur_state[0].x = 0.0
      self.cur_state[0].y = 0.0
      self.cur_state[0].psi = 0.0
      self.cur_state[0].delta = 0.0
  
      self.angle_steers_des = 0.0
      self.angle_steers_des_mpc = 0.0
      self.angle_steers_des_prev = 0.0
      self.angle_steers_des_time = 0.0
  
    def update_poly(self, CP, VM, v_ego, angle_steers, model):
      #v_ego = sm['carState'].vEgo
      #angle_steers = sm['carState'].steeringAngle
      active = True #sm['controlsState'].active
  
      angle_offset = 0 #sm['liveParameters'].angleOffset
  
      self.LP.update(v_ego, model)
  
      # Run MPC
      self.angle_steers_des_prev = self.angle_steers_des_mpc
      #VM.update_params(sm['liveParameters'].stiffnessFactor, sm['liveParameters'].steerRatio)
      curvature_factor = VM.curvature_factor(v_ego)
  
      # TODO: Check for active, override, and saturation
      # if active:
      #   self.path_offset_i += self.LP.d_poly[3] / (60.0 * 20.0)
      #   self.path_offset_i = clip(self.path_offset_i, -0.5,  0.5)
      #   self.LP.d_poly[3] += self.path_offset_i
      # else:
      #   self.path_offset_i = 0.0
  
      # account for actuation delay
      self.cur_state = calc_states_after_delay(self.cur_state, v_ego, angle_steers - angle_offset, curvature_factor, VM.sR, CP.steerActuatorDelay)
  
      v_ego_mpc = max(v_ego, 5.0)  # avoid mpc roughness due to low speed
      self.libmpc.run_mpc(self.cur_state, self.mpc_solution,
                          list(self.LP.l_poly), list(self.LP.r_poly), list(self.LP.d_poly),
                          self.LP.l_prob, self.LP.r_prob, curvature_factor, v_ego_mpc, self.LP.lane_width)
  
      # reset to current steer angle if not active or overriding
      if active:
        delta_desired = self.mpc_solution[0].delta[1]
        rate_desired = math.degrees(self.mpc_solution[0].rate[0] * VM.sR)
      else:
        delta_desired = math.radians(angle_steers - angle_offset) / VM.sR
        rate_desired = 0.0
  
      self.cur_state[0].delta = delta_desired
  
      self.angle_steers_des_mpc = float(math.degrees(delta_desired * VM.sR) + angle_offset)
  
      #  Check for infeasable MPC solution
      mpc_nans = any(math.isnan(x) for x in self.mpc_solution[0].delta)
      t = sec_since_boot()
      if mpc_nans:
        self.libmpc.init(MPC_COST_LAT.PATH, MPC_COST_LAT.LANE, MPC_COST_LAT.HEADING, CP.steerRateCost)
        self.cur_state[0].delta = math.radians(angle_steers - angle_offset) / VM.sR
  
        if t > self.last_cloudlog_t + 5.0:
          self.last_cloudlog_t = t
          cloudlog.warning("Lateral mpc - nan: True")
  
      if self.mpc_solution[0].cost > 20000. or mpc_nans:   # TODO: find a better way to detect when MPC did not converge
        self.solution_invalid_cnt += 1
      else:
        self.solution_invalid_cnt = 0
  
    def update(self, sm, pm, CP, VM):
      v_ego = sm['carState'].vEgo
      angle_steers = sm['carState'].steeringAngle
      active = sm['controlsState'].active
  
      angle_offset = sm['liveParameters'].angleOffset
  
      self.LP.update(v_ego, sm['model'])
  
      # Run MPC
      self.angle_steers_des_prev = self.angle_steers_des_mpc
      VM.update_params(sm['liveParameters'].stiffnessFactor, sm['liveParameters'].steerRatio)
      curvature_factor = VM.curvature_factor(v_ego)
  
      # TODO: Check for active, override, and saturation
      # if active:
      #   self.path_offset_i += self.LP.d_poly[3] / (60.0 * 20.0)
      #   self.path_offset_i = clip(self.path_offset_i, -0.5,  0.5)
      #   self.LP.d_poly[3] += self.path_offset_i
      # else:
      #   self.path_offset_i = 0.0
  
      # account for actuation delay
      self.cur_state = calc_states_after_delay(self.cur_state, v_ego, angle_steers - angle_offset, curvature_factor, VM.sR, CP.steerActuatorDelay)
  
      v_ego_mpc = max(v_ego, 5.0)  # avoid mpc roughness due to low speed
      self.libmpc.run_mpc(self.cur_state, self.mpc_solution,
                          list(self.LP.l_poly), list(self.LP.r_poly), list(self.LP.d_poly),
                          self.LP.l_prob, self.LP.r_prob, curvature_factor, v_ego_mpc, self.LP.lane_width)
  
      # reset to current steer angle if not active or overriding
      if active:
        delta_desired = self.mpc_solution[0].delta[1]
        rate_desired = math.degrees(self.mpc_solution[0].rate[0] * VM.sR)
      else:
        delta_desired = math.radians(angle_steers - angle_offset) / VM.sR
        rate_desired = 0.0
  
      self.cur_state[0].delta = delta_desired
  
      self.angle_steers_des_mpc = float(math.degrees(delta_desired * VM.sR) + angle_offset)
  
      #  Check for infeasable MPC solution
      mpc_nans = any(math.isnan(x) for x in self.mpc_solution[0].delta)
      t = sec_since_boot()
      if mpc_nans:
        self.libmpc.init(MPC_COST_LAT.PATH, MPC_COST_LAT.LANE, MPC_COST_LAT.HEADING, CP.steerRateCost)
        self.cur_state[0].delta = math.radians(angle_steers - angle_offset) / VM.sR
  
        if t > self.last_cloudlog_t + 5.0:
          self.last_cloudlog_t = t
          cloudlog.warning("Lateral mpc - nan: True")
  
      if self.mpc_solution[0].cost > 20000. or mpc_nans:   # TODO: find a better way to detect when MPC did not converge
        self.solution_invalid_cnt += 1
      else:
        self.solution_invalid_cnt = 0
      plan_solution_valid = self.solution_invalid_cnt < 2
  
      plan_send = messaging.new_message()
      plan_send.init('pathPlan')
      plan_send.valid = sm.all_alive_and_valid(service_list=['carState', 'controlsState', 'liveParameters', 'model'])
      plan_send.pathPlan.laneWidth = float(self.LP.lane_width)
      plan_send.pathPlan.dPoly = [float(x) for x in self.LP.d_poly]
      plan_send.pathPlan.lPoly = [float(x) for x in self.LP.l_poly]
      plan_send.pathPlan.lProb = float(self.LP.l_prob)
      plan_send.pathPlan.rPoly = [float(x) for x in self.LP.r_poly]
      plan_send.pathPlan.rProb = float(self.LP.r_prob)
  
      plan_send.pathPlan.angleSteers = float(self.angle_steers_des_mpc)
      plan_send.pathPlan.rateSteers = float(rate_desired)
      plan_send.pathPlan.angleOffset = float(sm['liveParameters'].angleOffsetAverage)
      plan_send.pathPlan.mpcSolutionValid = bool(plan_solution_valid)
      plan_send.pathPlan.paramsValid = bool(sm['liveParameters'].valid)
      plan_send.pathPlan.sensorValid = bool(sm['liveParameters'].sensorValid)
      plan_send.pathPlan.posenetValid = bool(sm['liveParameters'].posenetValid)
  
      pm.send('pathPlan', plan_send)
  
      if LOG_MPC:
        dat = messaging.new_message()
        dat.init('liveMpc')
        dat.liveMpc.x = list(self.mpc_solution[0].x)
        dat.liveMpc.y = list(self.mpc_solution[0].y)
        dat.liveMpc.psi = list(self.mpc_solution[0].psi)
        dat.liveMpc.delta = list(self.mpc_solution[0].delta)
        dat.liveMpc.cost = self.mpc_solution[0].cost
        pm.send('liveMpc', dat)
  