import numpy as np
from pybullet_envs.deep_mimic.env.env import Env


class Path(object):

  def __init__(self):
    self.clear()
    return

  def pathlength(self):
    return len(self.actions)

  def is_valid(self):
    valid = True
    l = self.pathlength()
    valid &= len(self.states) == l + 1
    valid &= len(self.goals) == l + 1
    valid &= len(self.actions) == l
    valid &= len(self.logps) == l
    valid &= len(self.rewards) == l
    valid &= len(self.flags) == l

    return valid

  def check_vals(self):
    for vals in [self.states, self.goals, self.actions, self.logps, self.rewards]:
      for v in vals:
        if not np.isfinite(v).all():
          return False
    return True

  def clear(self):
    self.states = []
    self.goals = []
    self.actions = []
    self.logps = []
    self.rewards = []
    self.flags = []
    self.terminate = Env.Terminate.Null
    return

  def get_pathlen(self):
    return len(self.rewards)

  def calc_return(self):
    return sum(self.rewards)