128dbbe25c3232f1423337b2c37fb743d26df3c8,pgmpy/models/MarkovChain.py,MarkovChain,sample,#MarkovChain#,214

Before Change

        for i in range(size - 1):
            for j, (var, st) in enumerate(self.state):
                next_st = sample_discrete(list(self.transition_models[var][st].keys()),
                                          list(self.transition_models[var][st].values()))[0]
                self.state[j] = State(var, next_st)
            sampled.loc[i + 1] = [st for var, st in self.state]

        return sampled

After Change

        var_states = defaultdict(dict)
        var_values = defaultdict(dict)
        samples = defaultdict(dict)
        for var in self.transition_models.keys():
            for st in self.transition_models[var]:
                var_states[var][st] = list(self.transition_models[var][st].keys())
                var_values[var][st] = list(self.transition_models[var][st].values())
                samples[var][st] = sample_discrete(var_states[var][st], var_values[var][st])[0]

        for i in range(size - 1):
            for j, (var, st) in enumerate(self.state):
                next_st = samples[var][st]
                self.state[j] = State(var, next_st)

Instances