import zmq
import math
import numpy as np

from common.realtime import sec_since_boot
from selfdrive.services import service_list
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.model_parser import ModelParser
import selfdrive.messaging as messaging


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(object):
  def __init__(self, CP):
    self.MP = ModelParser()

    self.last_cloudlog_t = 0

    context = zmq.Context()
    self.plan = messaging.pub_sock(context, service_list['pathPlan'].port)
    self.livempc = messaging.pub_sock(context, service_list['liveMpc'].port)

    self.setup_mpc(CP.steerRateCost)
    self.invalid_counter = 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(self, CP, VM, CS, md, live100, live_parameters):
    v_ego = CS.carState.vEgo
    angle_steers = CS.carState.steeringAngle
    active = live100.live100.active

    angle_offset_bias = live100.live100.angleModelBias + live_parameters.liveParameters.angleOffsetAverage

    self.MP.update(v_ego, md)

    # Run MPC
    self.angle_steers_des_prev = self.angle_steers_des_mpc
    VM.update_params(live_parameters.liveParameters.stiffnessFactor, live_parameters.liveParameters.steerRatio)
    curvature_factor = VM.curvature_factor(v_ego)

    l_poly = libmpc_py.ffi.new("double[4]", list(self.MP.l_poly))
    r_poly = libmpc_py.ffi.new("double[4]", list(self.MP.r_poly))
    p_poly = libmpc_py.ffi.new("double[4]", list(self.MP.p_poly))

    # account for actuation delay
    self.cur_state = calc_states_after_delay(self.cur_state, v_ego, angle_steers, 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,
                        l_poly, r_poly, p_poly,
                        self.MP.l_prob, self.MP.r_prob, self.MP.p_prob, curvature_factor, v_ego_mpc, self.MP.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_bias) / 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_bias)


    #  Check for infeasable MPC solution
    mpc_nans = np.any(np.isnan(list(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) / 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.invalid_counter += 1
    else:
      self.invalid_counter = 0

    plan_valid = self.invalid_counter < 2

    plan_send = messaging.new_message()
    plan_send.init('pathPlan')
    plan_send.pathPlan.laneWidth = float(self.MP.lane_width)
    plan_send.pathPlan.dPoly = map(float, self.MP.d_poly)
    plan_send.pathPlan.cPoly = map(float, self.MP.c_poly)
    plan_send.pathPlan.cProb = float(self.MP.c_prob)
    plan_send.pathPlan.lPoly = map(float, l_poly)
    plan_send.pathPlan.lProb = float(self.MP.l_prob)
    plan_send.pathPlan.rPoly = map(float, r_poly)
    plan_send.pathPlan.rProb = float(self.MP.r_prob)
    plan_send.pathPlan.angleSteers = float(self.angle_steers_des_mpc)
    plan_send.pathPlan.rateSteers = float(rate_desired)
    plan_send.pathPlan.angleOffset = float(live_parameters.liveParameters.angleOffsetAverage)
    plan_send.pathPlan.valid = bool(plan_valid)
    plan_send.pathPlan.paramsValid = bool(live_parameters.liveParameters.valid)

    self.plan.send(plan_send.to_bytes())

    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
    self.livempc.send(dat.to_bytes())