def test_from_mdp_lst_biased(self):
    mdp_lst = [OvercookedGridworld.from_layout_name(name) for name in self.layout_name_short_lst]
    ae = AgentEvaluator.from_mdp_lst(mdp_lst=mdp_lst, env_params={'horizon': 400}, sampling_freq=self.biased)
    counts = {}
    for _ in range(self.num_reset):
        ae.env.reset(regen_mdp=True)
        if (ae.env.mdp.layout_name in counts):
            counts[ae.env.mdp.layout_name] += 1
        else:
            counts[ae.env.mdp.layout_name] = 1
    gt = {self.layout_name_short_lst[i]: self.biased[i] for i in range(len(self.layout_name_short_lst))}
    for (k, v) in counts.items():
        self.assertAlmostEqual(gt[k], (v / self.num_reset), 2, ('more than 2 places off for ' + k))
def test_from_mdp_lst_biased(self):
    mdp_lst = [OvercookedGridworld.from_layout_name(name) for name in self.layout_name_short_lst]
    ae = AgentEvaluator.from_mdp_lst(mdp_lst=mdp_lst, env_params={'horizon': 400}, sampling_freq=self.biased)
    counts = {}
    for _ in range(self.num_reset):
        ae.env.reset(regen_mdp=True)
        if (ae.env.mdp.layout_name in counts):
            counts[ae.env.mdp.layout_name] += 1
        else:
            counts[ae.env.mdp.layout_name] = 1
    gt = {self.layout_name_short_lst[i]: self.biased[i] for i in range(len(self.layout_name_short_lst))}
    for (k, v) in counts.items():
        self.assertAlmostEqual(gt[k], (v / self.num_reset), 2, ('more than 2 places off for ' + k))