Beispiel #1
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    def clean(self,
              scenario_id=None,
              calibration_id=None,
              delete_scenario=False,
              delete_spatial_gfs=False):
        """Clean model outputs in OUTPUT<ScenarioID>-<CalibrationID> directory and/or
        GridFS files in OUTPUT collection.

        Examples:
            model.SetMongoClient()
            model.clean()
            model.UnsetMongoClient()
        """
        rmtree(self.OutputDirectory, ignore_errors=True)
        self.ConnectMongoDB()
        read_model = ReadModelData(self.mongoclient, self.db_name)
        if scenario_id is None:
            scenario_id = self.scenario_id
        if calibration_id is None:
            calibration_id = self.calibration_id
        read_model.CleanOutputGridFs(scenario_id, calibration_id)
        if delete_scenario:
            read_model.CleanScenariosConfiguration(scenario_id)
            if delete_spatial_gfs:
                read_model.CleanSpatialGridFs(scenario_id)
Beispiel #2
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 def OutputItems(self):
     # type: (...) -> Dict[AnyStr, Optional[List[AnyStr]]]
     """Read output items from database."""
     if self.output_items:
         return self.output_items
     read_model = ReadModelData(self.host, self.port, self.db_name)
     self.output_ids, self.output_items = read_model.OutputItems()
     return self.output_items
Beispiel #3
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    def ReadOutletObservations(self, vars_list):
        # type: (List[AnyStr]) -> (List[AnyStr], Dict[datetime, List[float]])
        """

        Examples:
            model.SetMongoClient()
            model.ReadOutletObservations()
            model.UnsetMongoClient()
        """
        self.ConnectMongoDB()
        self.ReadMongoDBData()
        read_model = ReadModelData(self.mongoclient, self.db_name)
        self.obs_vars, self.obs_value = read_model.Observation(
            self.outlet_id, vars_list, self.start_time, self.end_time)
        return self.obs_vars, self.obs_value
Beispiel #4
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 def ResetOutputsPeriod(
     self,
     output_ids,  # type: Union[AnyStr, List[AnyStr]]
     stime,  # type: Union[datetime, List[datetime]]
     etime  # type: Union[datetime, List[datetime]]
 ):
     # type: (...) -> None
     """Reset the STARTTIME and ENDTIME of OUTPUTID(s)."""
     if not isinstance(output_ids, list):
         output_ids = [output_ids]
     if not isinstance(stime, list):
         stime = [stime]
     if not isinstance(etime, list):
         etime = [etime]
     read_model = ReadModelData(self.host, self.port, self.db_name)
     for idx, outputid in enumerate(output_ids):
         cur_stime = stime[0]
         if idx < len(stime):
             cur_stime = stime[idx]
         cur_etime = etime[0]
         if idx < len(etime):
             cur_etime = etime[idx]
         cur_stime_str = cur_stime.strftime('%Y-%m-%d %H:%M:%S')
         cur_etime_str = cur_etime.strftime('%Y-%m-%d %H:%M:%S')
         db = read_model.maindb
         db[DBTableNames.main_fileout].find_one_and_update(
             {'OUTPUTID': outputid}, {
                 '$set': {
                     'STARTTIME': cur_stime_str,
                     'ENDTIME': cur_etime_str
                 }
             })
Beispiel #5
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 def clean(self,
           scenario_id=None,
           calibration_id=None,
           delete_scenario=False):
     """Clean model outputs in OUTPUT<ScenarioID>-<CalibrationID> directory and/or
     GridFS files in OUTPUT collection.
     """
     rmtree(self.OutputDirectory, ignore_errors=True)
     read_model = ReadModelData(self.host, self.port, self.db_name)
     if scenario_id is None:
         scenario_id = self.scenario_id
     if calibration_id is None:
         calibration_id = self.calibration_id
     read_model.CleanOutputGridFs(scenario_id, calibration_id)
     if delete_scenario:
         read_model.CleanScenariosConfiguration(scenario_id)
Beispiel #6
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    def ReadMongoDBData(self):
        """
        Examples:
            model.SetMongoClient()
            model.ReadMongoDBData()
            model.UnsetMongoClient()
        """
        if self.outlet_id >= 0:
            return

        self.ConnectMongoDB()
        read_model = ReadModelData(self.mongoclient, self.db_name)

        self.outlet_id = read_model.OutletID
        self.subbasin_count = read_model.SubbasinCount
        self.scenario_dbname = read_model.ScenarioDBName
        self.start_time, self.end_time = read_model.SimulationPeriod
        self.output_ids, self.output_items = read_model.OutputItems()
Beispiel #7
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 def ResetSimulationPeriod(self):
     """Update simulation time range in MongoDB [FILE_IN]."""
     read_model = ReadModelData(self.host, self.port, self.db_name)
     if self.simu_stime and self.simu_etime:
         stime_str = self.simu_stime.strftime('%Y-%m-%d %H:%M:%S')
         etime_str = self.simu_etime.strftime('%Y-%m-%d %H:%M:%S')
         db = read_model.maindb
         db[DBTableNames.main_filein].find_one_and_update(
             {'TAG': 'STARTTIME'}, {'$set': {
                 'VALUE': stime_str
             }})
         db[DBTableNames.main_filein].find_one_and_update(
             {'TAG': 'ENDTIME'}, {'$set': {
                 'VALUE': etime_str
             }})
     self.start_time, self.end_time = read_model.SimulationPeriod
Beispiel #8
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    def ResetSimulationPeriod(self):
        """Update simulation time range in MongoDB [FILE_IN].

        Examples:
            model.SetMongoClient()
            model.ResetSimulationPeriod()
            model.UnsetMongoClient()
        """
        self.ConnectMongoDB()
        read_model = ReadModelData(self.mongoclient, self.db_name)
        if self.simu_stime and self.simu_etime:
            stime_str = self.simu_stime.strftime('%Y-%m-%d %H:%M:%S')
            etime_str = self.simu_etime.strftime('%Y-%m-%d %H:%M:%S')
            db = read_model.maindb
            db[DBTableNames.main_filein].find_one_and_update(
                {'TAG': 'STARTTIME'}, {'$set': {
                    'VALUE': stime_str
                }})
            db[DBTableNames.main_filein].find_one_and_update(
                {'TAG': 'ENDTIME'}, {'$set': {
                    'VALUE': etime_str
                }})
        self.start_time, self.end_time = read_model.SimulationPeriod
Beispiel #9
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    def __init__(self, cfg):
        # type: (PostConfig) -> None
        """Constructor"""
        self.model = MainSEIMS(args_dict=cfg.model_cfg.ConfigDict)
        self.ws = self.model.OutputDirectory
        if not FileClass.is_dir_exists(self.ws):
            raise ValueError('The output directory %s is not existed!' %
                             self.ws)
        self.plot_vars = cfg.plot_vars
        self.plot_cfg = cfg.plot_cfg  # type: PlotConfig
        # UTCTIME, calibration period
        self.stime = cfg.cali_stime
        self.etime = cfg.cali_etime
        self.subbsnID = cfg.plt_subbsnid
        # validation period
        self.vali_stime = cfg.vali_stime
        self.vali_etime = cfg.vali_etime

        # Read model data from MongoDB, the time period of simulation is read from FILE_IN.
        mongoclient = ConnectMongoDB(self.model.host,
                                     self.model.port).get_conn()
        self.readData = ReadModelData(mongoclient, self.model.db_name)
        self.mode = self.readData.Mode
        self.interval = self.readData.Interval
        # check start and end time of calibration
        st, et = self.readData.SimulationPeriod
        self.plot_validation = True
        if st > self.stime:
            self.stime = st
        if et < self.etime:
            self.etime = et
        if st > self.etime > self.stime:
            self.stime = st
            self.etime = et
            # in this circumstance, no validation should be calculated.
            self.vali_stime = None
            self.vali_etime = None
            self.plot_validation = False
        # check validation time period
        if self.vali_stime and self.vali_etime:
            if self.vali_stime >= self.vali_etime or st > self.vali_etime > self.vali_stime \
                or self.vali_stime >= et:
                self.vali_stime = None
                self.vali_etime = None
                self.plot_validation = False
            elif st > self.vali_stime:
                self.vali_stime = st
            elif et < self.vali_etime:
                self.vali_etime = et
        else:
            self.plot_validation = False
        # Set start time and end time of both calibration and validation periods
        start = self.stime
        end = self.etime
        if self.plot_validation:
            start = self.stime if self.stime < self.vali_stime else self.vali_stime
            end = self.etime if self.etime > self.vali_etime else self.vali_etime
        self.outletid = self.readData.OutletID
        # read precipitation
        self.pcp_date_value = self.readData.Precipitation(
            self.subbsnID, start, end)
        # read simulated data and update the available variables
        self.plot_vars, self.sim_data_dict = read_simulation_from_txt(
            self.ws, self.plot_vars, self.outletid, start, end)
        self.sim_data_value = list(
        )  # type: List[List[Union[datetime, float]]]
        for d, vs in self.sim_data_dict.items():
            self.sim_data_value.append([d] + vs[:])
        # reset start time and end time
        if len(self.sim_data_value) == 0:
            raise RuntimeError(
                'No available simulate data, please check the start and end time!'
            )
        # read observation data from MongoDB
        self.obs_vars, self.obs_data_dict = self.readData.Observation(
            self.subbsnID, self.plot_vars, start, end)

        # Calibration period
        self.sim_obs_dict = match_simulation_observation(self.plot_vars,
                                                         self.sim_data_dict,
                                                         self.obs_vars,
                                                         self.obs_data_dict,
                                                         start_time=self.stime,
                                                         end_time=self.etime)
        calculate_statistics(self.sim_obs_dict)
        # Validation period if existed
        self.vali_sim_obs_dict = dict()
        if self.plot_validation:
            self.vali_sim_obs_dict = match_simulation_observation(
                self.plot_vars,
                self.sim_data_dict,
                self.obs_vars,
                self.obs_data_dict,
                start_time=self.vali_stime,
                end_time=self.vali_etime)
            calculate_statistics(self.vali_sim_obs_dict)
Beispiel #10
0
class TimeSeriesPlots(object):
    """Plot time series data, e.g., flow charge, sediment charge, etc.
    """
    def __init__(self, cfg):
        # type: (PostConfig) -> None
        """Constructor"""
        self.model = MainSEIMS(args_dict=cfg.model_cfg.ConfigDict)
        self.ws = self.model.OutputDirectory
        if not FileClass.is_dir_exists(self.ws):
            raise ValueError('The output directory %s is not existed!' %
                             self.ws)
        self.plot_vars = cfg.plot_vars
        self.plot_cfg = cfg.plot_cfg  # type: PlotConfig
        # UTCTIME, calibration period
        self.stime = cfg.cali_stime
        self.etime = cfg.cali_etime
        self.subbsnID = cfg.plt_subbsnid
        # validation period
        self.vali_stime = cfg.vali_stime
        self.vali_etime = cfg.vali_etime

        # Read model data from MongoDB, the time period of simulation is read from FILE_IN.
        mongoclient = ConnectMongoDB(self.model.host,
                                     self.model.port).get_conn()
        self.readData = ReadModelData(mongoclient, self.model.db_name)
        self.mode = self.readData.Mode
        self.interval = self.readData.Interval
        # check start and end time of calibration
        st, et = self.readData.SimulationPeriod
        self.plot_validation = True
        if st > self.stime:
            self.stime = st
        if et < self.etime:
            self.etime = et
        if st > self.etime > self.stime:
            self.stime = st
            self.etime = et
            # in this circumstance, no validation should be calculated.
            self.vali_stime = None
            self.vali_etime = None
            self.plot_validation = False
        # check validation time period
        if self.vali_stime and self.vali_etime:
            if self.vali_stime >= self.vali_etime or st > self.vali_etime > self.vali_stime \
                or self.vali_stime >= et:
                self.vali_stime = None
                self.vali_etime = None
                self.plot_validation = False
            elif st > self.vali_stime:
                self.vali_stime = st
            elif et < self.vali_etime:
                self.vali_etime = et
        else:
            self.plot_validation = False
        # Set start time and end time of both calibration and validation periods
        start = self.stime
        end = self.etime
        if self.plot_validation:
            start = self.stime if self.stime < self.vali_stime else self.vali_stime
            end = self.etime if self.etime > self.vali_etime else self.vali_etime
        self.outletid = self.readData.OutletID
        # read precipitation
        self.pcp_date_value = self.readData.Precipitation(
            self.subbsnID, start, end)
        # read simulated data and update the available variables
        self.plot_vars, self.sim_data_dict = read_simulation_from_txt(
            self.ws, self.plot_vars, self.outletid, start, end)
        self.sim_data_value = list(
        )  # type: List[List[Union[datetime, float]]]
        for d, vs in self.sim_data_dict.items():
            self.sim_data_value.append([d] + vs[:])
        # reset start time and end time
        if len(self.sim_data_value) == 0:
            raise RuntimeError(
                'No available simulate data, please check the start and end time!'
            )
        # read observation data from MongoDB
        self.obs_vars, self.obs_data_dict = self.readData.Observation(
            self.subbsnID, self.plot_vars, start, end)

        # Calibration period
        self.sim_obs_dict = match_simulation_observation(self.plot_vars,
                                                         self.sim_data_dict,
                                                         self.obs_vars,
                                                         self.obs_data_dict,
                                                         start_time=self.stime,
                                                         end_time=self.etime)
        calculate_statistics(self.sim_obs_dict)
        # Validation period if existed
        self.vali_sim_obs_dict = dict()
        if self.plot_validation:
            self.vali_sim_obs_dict = match_simulation_observation(
                self.plot_vars,
                self.sim_data_dict,
                self.obs_vars,
                self.obs_data_dict,
                start_time=self.vali_stime,
                end_time=self.vali_etime)
            calculate_statistics(self.vali_sim_obs_dict)

    def generate_plots(self):
        """Generate hydrographs of discharge, sediment, nutrient (amount or concentrate), etc."""
        # set ticks direction, in or out
        plt.rcParams['xtick.direction'] = 'out'
        plt.rcParams['ytick.direction'] = 'out'
        plt.rcParams['font.family'] = self.plot_cfg.font_name
        plt.rcParams['mathtext.fontset'] = 'custom'
        plt.rcParams['mathtext.it'] = 'STIXGeneral:italic'
        plt.rcParams['mathtext.bf'] = 'STIXGeneral:italic:bold'

        obs_str = 'Observation'
        sim_str = 'Simulation'
        cali_str = 'Calibration'
        vali_str = 'Validation'
        pcp_str = 'Precipitation'
        pcpaxis_str = 'Precipitation (mm)'
        xaxis_str = 'Date time'
        if self.plot_cfg.plot_cn:
            plt.rcParams['axes.unicode_minus'] = False
            obs_str = u'观测值'
            sim_str = u'模拟值'
            cali_str = u'率定期'
            vali_str = u'验证期'
            pcp_str = u'降水'
            pcpaxis_str = u'降水 (mm)'
            xaxis_str = u'时间'

        sim_date = list(self.sim_data_dict.keys())
        for i, param in enumerate(self.plot_vars):
            # plt.figure(i)
            fig, ax = plt.subplots(figsize=(12, 4))
            ylabel_str = param
            if param in ['Q', 'QI', 'QG', 'QS']:
                ylabel_str += ' (m$^3$/s)'
            elif 'CONC' in param.upper():  # Concentrate
                if 'SED' in param.upper():
                    ylabel_str += ' (g/L)'
                else:
                    ylabel_str += ' (mg/L)'
            elif 'SED' in param.upper():  # amount
                ylabel_str += ' (kg)'

            obs_dates = None  # type: List[datetime]
            obs_values = None  # type: List[float]
            if self.sim_obs_dict and param in self.sim_obs_dict:
                obs_dates = self.sim_obs_dict[param][DataValueFields.utc]
                obs_values = self.sim_obs_dict[param]['Obs']
            # append validation data
            if self.vali_sim_obs_dict and param in self.vali_sim_obs_dict:
                obs_dates += self.vali_sim_obs_dict[param][DataValueFields.utc]
                obs_values += self.vali_sim_obs_dict[param]['Obs']
            if obs_values is not None:
                # TODO: if the observed data is continuous with datetime, plot line, otherwise, bar.
                # bar graph
                p1 = ax.bar(obs_dates,
                            obs_values,
                            label=obs_str,
                            color='none',
                            edgecolor='black',
                            linewidth=0.5,
                            align='center',
                            hatch='//')
                # # line graph
                # p1, = ax.plot(obs_dates, obs_values, label=obs_str, color='black', marker='+',
                #              markersize=2, linewidth=1)
            sim_list = [v[i + 1] for v in self.sim_data_value]
            p2, = ax.plot(sim_date,
                          sim_list,
                          label=sim_str,
                          color='red',
                          marker='+',
                          markersize=2,
                          linewidth=0.8)
            plt.xlabel(xaxis_str,
                       fontdict={'size': self.plot_cfg.axislabel_fsize})
            # format the ticks date axis
            date_fmt = mdates.DateFormatter('%m-%d-%y')
            # autodates = mdates.AutoDateLocator()
            # days = mdates.DayLocator(bymonthday=range(1, 32), interval=4)
            # months = mdates.MonthLocator()
            # ax.xaxis.set_major_locator(months)
            ax.xaxis.set_major_formatter(date_fmt)
            # ax.xaxis.set_minor_locator(days)
            ax.tick_params('both',
                           length=5,
                           width=2,
                           which='major',
                           labelsize=self.plot_cfg.tick_fsize)
            ax.tick_params('both',
                           length=3,
                           width=1,
                           which='minor',
                           labelsize=self.plot_cfg.tick_fsize)
            ax.set_xlim(left=self.sim_data_value[0][0],
                        right=self.sim_data_value[-1][0])
            fig.autofmt_xdate(rotation=0, ha='center')

            plt.ylabel(ylabel_str,
                       fontdict={'size': self.plot_cfg.axislabel_fsize})
            # plt.legend(bbox_to_anchor = (0.03, 0.85), loc = 2, shadow = True)
            if obs_values is not None:
                ymax = max(max(sim_list), max(obs_values)) * 1.6
                ymin = min(min(sim_list), min(obs_values)) * 0.8
            else:
                ymax = max(sim_list) * 1.8
                ymin = min(sim_list) * 0.8
            ax.set_ylim(float(ymin), float(ymax))
            ax2 = ax.twinx()
            ax.tick_params(axis='x',
                           which='both',
                           bottom=True,
                           top=False,
                           labelsize=self.plot_cfg.tick_fsize)
            ax2.tick_params(axis='y',
                            length=5,
                            width=2,
                            which='major',
                            labelsize=self.plot_cfg.tick_fsize)
            ax2.set_ylabel(pcpaxis_str,
                           fontdict={'size': self.plot_cfg.axislabel_fsize})

            pcp_date = [v[0] for v in self.pcp_date_value]
            preci = [v[1] for v in self.pcp_date_value]
            p3 = ax2.bar(pcp_date,
                         preci,
                         label=pcp_str,
                         color='blue',
                         linewidth=0,
                         align='center')
            ax2.set_ylim(float(max(preci)) * 1.8, float(min(preci)) * 0.8)
            # draw a dash line to separate calibration and validation period
            delta_dt = (self.sim_data_value[-1][0] -
                        self.sim_data_value[0][0]) // 9
            delta_dt2 = (self.sim_data_value[-1][0] -
                         self.sim_data_value[0][0]) // 35
            # by default, separate time line is the end of calibration period
            sep_time = self.etime
            time_pos = [sep_time - delta_dt]
            ymax, ymin = ax2.get_ylim()
            yc = abs(ymax - ymin) / 4.
            order = 1  # By default, calibration period is before validation period
            if self.plot_validation:
                sep_time = self.vali_stime if self.vali_stime >= self.etime else self.stime
                cali_vali_labels = [cali_str, vali_str]
                if self.vali_stime < self.stime:
                    order = 0
                    cali_vali_labels = [vali_str, cali_str]
                time_pos = [sep_time - delta_dt, sep_time + delta_dt2]
                ax.axvline(sep_time,
                           color='black',
                           linestyle='dashed',
                           linewidth=2)
                plt.text(time_pos[0],
                         yc,
                         cali_vali_labels[0],
                         fontdict={
                             'style': 'italic',
                             'weight': 'bold',
                             'size': self.plot_cfg.label_fsize
                         },
                         color='black')
                plt.text(time_pos[1],
                         yc,
                         cali_vali_labels[1],
                         fontdict={
                             'style': 'italic',
                             'weight': 'bold',
                             'size': self.plot_cfg.label_fsize
                         },
                         color='black')
            # set legend and labels
            if obs_values is None or len(obs_values) < 2:
                leg = ax.legend([p3, p2], [pcp_str, sim_str],
                                ncol=2,
                                bbox_to_anchor=(0., 1.02, 1., 0.102),
                                borderaxespad=0.2,
                                loc='lower left',
                                fancybox=True,
                                fontsize=self.plot_cfg.legend_fsize)
            else:
                leg = ax.legend([p3, p1, p2], [pcp_str, obs_str, sim_str],
                                bbox_to_anchor=(0., 1.02, 1., 0.102),
                                borderaxespad=0.,
                                ncol=3,
                                loc='lower left',
                                fancybox=True,
                                fontsize=self.plot_cfg.legend_fsize)
                try:
                    nse = self.sim_obs_dict[param]['NSE']  # type: float
                    r2 = self.sim_obs_dict[param]['R-square']  # type: float
                    pbias = self.sim_obs_dict[param]['PBIAS']  # type: float
                    rsr = self.sim_obs_dict[param]['RSR']  # type: float
                    cali_txt = '$\mathit{NSE}$: %.2f\n$\mathit{RSR}$: %.2f\n' \
                               '$\mathit{PBIAS}$: %.2f%%\n$\mathit{R^2}$: %.2f' % \
                               (nse, rsr, pbias, r2)
                    print_msg_header = 'Cali-%s-NSE,Cali-%s-RSR,' \
                                       'Cali-%s-PBIAS,Cali-%s-R2,' % (param, param, param, param)
                    print_msg = '%.3f,%.3f,%.3f,%.3f,' % (nse, rsr, pbias, r2)
                    cali_pos = time_pos[0] if order else time_pos[1]
                    plt.text(cali_pos,
                             yc * 2.5,
                             cali_txt,
                             color='red',
                             fontsize=self.plot_cfg.label_fsize - 1)
                    if self.plot_validation and self.vali_sim_obs_dict:
                        nse = self.vali_sim_obs_dict[param]['NSE']
                        r2 = self.vali_sim_obs_dict[param]['R-square']
                        pbias = self.vali_sim_obs_dict[param]['PBIAS']
                        rsr = self.vali_sim_obs_dict[param]['RSR']
                        vali_txt = '$\mathit{NSE}$: %.2f\n$\mathit{RSR}$: %.2f\n' \
                                   '$\mathit{PBIAS}$: %.2f%%\n$\mathit{R^2}$: %.2f' % \
                                   (nse, rsr, pbias, r2)
                        print_msg_header += 'Vali-%s-NSE,Vali-%s-RSR,' \
                                            'Vali-%s-PBIAS,' \
                                            'Vali-%s-R2' % (param, param, param, param)
                        print_msg += '%.3f,%.3f,%.3f,%.3f' % (nse, rsr, pbias,
                                                              r2)
                        vali_pos = time_pos[1] if order else time_pos[0]
                        plt.text(vali_pos,
                                 yc * 2.5,
                                 vali_txt,
                                 color='red',
                                 fontsize=self.plot_cfg.label_fsize - 1)
                    print('%s\n%s\n' % (print_msg_header, print_msg))

                except ValueError or Exception:
                    pass
            plt.tight_layout()
            leg.get_frame().set_alpha(0.5)
            timerange = '%s-%s' % (self.sim_data_value[0][0].strftime(
                '%Y-%m-%d'), self.sim_data_value[-1][0].strftime('%Y-%m-%d'))
            save_png_eps(plt, self.ws, param + '-' + timerange, self.plot_cfg)
Beispiel #11
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 def ReadOutletObservations(self, vars_list):
     # type: (List[AnyStr]) -> (List[AnyStr], Dict[datetime, List[float]])
     read_model = ReadModelData(self.host, self.port, self.db_name)
     self.obs_vars, self.obs_value = read_model.Observation(
         self.outlet_id, vars_list, self.start_time, self.end_time)
     return self.obs_vars, self.obs_value
Beispiel #12
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 def SimulatedPeriod(self):
     # type: (...) -> (datetime, datetime)
     read_model = ReadModelData(self.host, self.port, self.db_name)
     return read_model.SimulationPeriod
Beispiel #13
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 def ScenarioDBName(self):
     # type: (...) -> AnyStr
     read_model = ReadModelData(self.host, self.port, self.db_name)
     return read_model.ScenarioDBName
Beispiel #14
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 def SubbasinCount(self):
     # type: (...) -> int
     read_model = ReadModelData(self.host, self.port, self.db_name)
     return read_model.SubbasinCount
Beispiel #15
0
 def OutletID(self):
     # type: (...) -> int
     read_model = ReadModelData(self.host, self.port, self.db_name)
     return read_model.OutletID