gasrank.py 文件源码

def plot_abilities_two_components(self, team_ids, component_id=0, **kwargs):
        import matplotlib.pyplot as plt
        import seaborn as sns

        figsize = kwargs.get('figsize',(15,5))

        if component_id == 0:
            name_strings = self.team_strings
            name_dict = self.team_dict
        else:
            name_strings = self.team_strings_2
            name_dict = self.team_dict_2

        if self.latent_variables.estimated is False:
            raise Exception("No latent variables estimated!")
        else:
            plt.figure(figsize=figsize)

            if type(team_ids) == type([]):
                if type(team_ids[0]) == str:
                    for team_id in team_ids:
                        plt.plot(np.trim_zeros(self._model_abilities(self.latent_variables.get_z_values())[component_id].T[name_dict[team_id]],
                            trim='b'), label=name_strings[name_dict[team_id]])
                else:
                    for team_id in team_ids:
                        plt.plot(np.trim_zeros(self._model_abilities(self.latent_variables.get_z_values())[component_id].T[team_id],
                            trim='b'), label=name_strings[team_id])
            else:
                if type(team_ids) == str:
                    plt.plot(np.trim_zeros(self._model_abilities(self.latent_variables.get_z_values())[component_id].T[name_dict[team_ids]],
                        trim='b'), label=name_strings[name_dict[team_ids]])
                else:
                    plt.plot(np.trim_zeros(self._model_abilities(self.latent_variables.get_z_values())[component_id].T[team_ids],
                        trim='b'), label=name_strings[team_ids])
            plt.legend()
            plt.ylabel("Power")
            plt.xlabel("Games")
            plt.show()