#!/usr/bin/env python3
from cereal import car
from selfdrive.car.subaru.values import CAR, PREGLOBAL_CARS
from selfdrive.car import STD_CARGO_KG, scale_rot_inertia, scale_tire_stiffness, gen_empty_fingerprint
from selfdrive.car.interfaces import CarInterfaceBase

class CarInterface(CarInterfaceBase):

  @staticmethod
  def compute_gb(accel, speed):
    return float(accel) / 4.0

  @staticmethod
  def get_params(candidate, fingerprint=gen_empty_fingerprint(), car_fw=None):
    ret = CarInterfaceBase.get_std_params(candidate, fingerprint)

    ret.carName = "subaru"
    ret.radarOffCan = True

    if candidate in PREGLOBAL_CARS:
      ret.safetyModel = car.CarParams.SafetyModel.subaruLegacy
    else:
      ret.safetyModel = car.CarParams.SafetyModel.subaru

    # Subaru port is a community feature, since we don't own one to test
    ret.communityFeature = True
    ret.dashcamOnly = candidate in PREGLOBAL_CARS

    ret.enableCamera = True

    ret.steerRateCost = 0.7
    ret.steerLimitTimer = 0.4

    if candidate == CAR.ASCENT:
      ret.mass = 2031. + STD_CARGO_KG
      ret.wheelbase = 2.89
      ret.centerToFront = ret.wheelbase * 0.5
      ret.steerRatio = 13.5
      ret.steerActuatorDelay = 0.3   # end-to-end angle controller
      ret.lateralTuning.pid.kf = 0.00003
      ret.lateralTuning.pid.kiBP, ret.lateralTuning.pid.kpBP = [[0., 20.], [0., 20.]]
      ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.0025, 0.1], [0.00025, 0.01]]

    if candidate == CAR.IMPREZA:
      ret.mass = 1568. + STD_CARGO_KG
      ret.wheelbase = 2.67
      ret.centerToFront = ret.wheelbase * 0.5
      ret.steerRatio = 15
      ret.steerActuatorDelay = 0.4   # end-to-end angle controller
      ret.lateralTuning.pid.kf = 0.00005
      ret.lateralTuning.pid.kiBP, ret.lateralTuning.pid.kpBP = [[0., 20.], [0., 20.]]
      ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.2, 0.3], [0.02, 0.03]]

    if candidate == CAR.FORESTER:
      ret.mass = 1568. + STD_CARGO_KG
      ret.wheelbase = 2.67
      ret.centerToFront = ret.wheelbase * 0.5
      ret.steerRatio = 17           # learned, 14 stock
      ret.steerActuatorDelay = 0.1
      ret.lateralTuning.pid.kf = 0.000038
      ret.lateralTuning.pid.kiBP, ret.lateralTuning.pid.kpBP = [[0., 14., 23.], [0., 14., 23.]]
      ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.01, 0.065, 0.2], [0.001, 0.015, 0.025]]

    if candidate in [CAR.FORESTER_PREGLOBAL, CAR.OUTBACK_PREGLOBAL_2018]:
      ret.safetyParam = 1  # Outback 2018-2019 and Forester have reversed driver torque signal
      ret.mass = 1568 + STD_CARGO_KG
      ret.wheelbase = 2.67
      ret.centerToFront = ret.wheelbase * 0.5
      ret.steerRatio = 20           # learned, 14 stock
      ret.steerActuatorDelay = 0.1
      ret.lateralTuning.pid.kf = 0.000039
      ret.lateralTuning.pid.kiBP, ret.lateralTuning.pid.kpBP = [[0., 10., 20.], [0., 10., 20.]]
      ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.01, 0.05, 0.2], [0.003, 0.018, 0.025]]

    if candidate == CAR.LEGACY_PREGLOBAL:
      ret.mass = 1568 + STD_CARGO_KG
      ret.wheelbase = 2.67
      ret.centerToFront = ret.wheelbase * 0.5
      ret.steerRatio = 12.5   # 14.5 stock
      ret.steerActuatorDelay = 0.15
      ret.lateralTuning.pid.kf = 0.00005
      ret.lateralTuning.pid.kiBP, ret.lateralTuning.pid.kpBP = [[0., 20.], [0., 20.]]
      ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.1, 0.2], [0.01, 0.02]]

    if candidate == CAR.OUTBACK_PREGLOBAL:
      ret.mass = 1568 + STD_CARGO_KG
      ret.wheelbase = 2.67
      ret.centerToFront = ret.wheelbase * 0.5
      ret.steerRatio = 20           # learned, 14 stock
      ret.steerActuatorDelay = 0.1
      ret.lateralTuning.pid.kf = 0.000039
      ret.lateralTuning.pid.kiBP, ret.lateralTuning.pid.kpBP = [[0., 10., 20.], [0., 10., 20.]]
      ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.01, 0.05, 0.2], [0.003, 0.018, 0.025]]

    # TODO: get actual value, for now starting with reasonable value for
    # civic and scaling by mass and wheelbase
    ret.rotationalInertia = scale_rot_inertia(ret.mass, ret.wheelbase)

    # TODO: start from empirically derived lateral slip stiffness for the civic and scale by
    # mass and CG position, so all cars will have approximately similar dyn behaviors
    ret.tireStiffnessFront, ret.tireStiffnessRear = scale_tire_stiffness(ret.mass, ret.wheelbase, ret.centerToFront)

    return ret

  # returns a car.CarState
  def update(self, c, can_strings):
    self.cp.update_strings(can_strings)
    self.cp_cam.update_strings(can_strings)

    ret = self.CS.update(self.cp, self.cp_cam)

    ret.canValid = self.cp.can_valid and self.cp_cam.can_valid
    ret.steeringRateLimited = self.CC.steer_rate_limited if self.CC is not None else False

    ret.events = self.create_common_events(ret).to_msg()

    self.CS.out = ret.as_reader()
    return self.CS.out

  def apply(self, c):
    can_sends = self.CC.update(c.enabled, self.CS, self.frame, c.actuators,
                               c.cruiseControl.cancel, c.hudControl.visualAlert,
                               c.hudControl.leftLaneVisible, c.hudControl.rightLaneVisible)
    self.frame += 1
    return can_sends
