def __init__(self, id, supply_node_id, sql_id_table, sql_data_table, primary_key, data_id_key, reference=False, scenario=None): self.id = id self.input_type = 'total' self.supply_node_id = supply_node_id self.sql_id_table = sql_id_table self.sql_data_table = sql_data_table self.scenario = scenario self.mapped = False if reference: for col, att in util.object_att_from_table(self.sql_id_table, self.supply_node_id, primary_key): setattr(self, col, att) DataMapFunctions.__init__(self, data_id_key) self.read_timeseries_data(supply_node_id=self.supply_node_id) self.raw_values = util.remove_df_levels(self.raw_values, 'supply_technology') else: # measure specific sales does not require technology filtering Abstract.__init__(self, self.id, primary_key=primary_key, data_id_key=data_id_key)
def __init__(self, id, subsector_id, sql_id_table, sql_data_table, primary_key, data_id_key, reference=False, scenario=None): self.id = id self.subsector_id = subsector_id self.sql_id_table = sql_id_table self.sql_data_table = sql_data_table self.scenario = scenario self.mapped = False if reference: for col, att in util.object_att_from_table(self.sql_id_table, self.subsector_id, primary_key): if att is not None: setattr(self, col, att) DataMapFunctions.__init__(self, data_id_key) self.read_timeseries_data(subsector_id=self.subsector_id) self.raw_values = util.remove_df_levels(self.raw_values, 'technology') else: self.replaced_demand_tech_id = None # measure specific sales share does not require technology filtering Abstract.__init__(self, self.id, primary_key=primary_key, data_id_key=data_id_key)
def __init__(self, id, supply_node_id, sql_id_table, sql_data_table, reference=False): self.id = id self.supply_node_id = supply_node_id self.sql_id_table = sql_id_table self.sql_data_table = sql_data_table self.mapped = False self.input_type = 'intensity' if reference: for col, att in util.object_att_from_table(self.sql_id_table, self.supply_node_id, 'supply_node_id'): if att is not None: setattr(self, col, att) DataMapFunctions.__init__(self, 'supply_technology') self.read_timeseries_data() self.raw_values = util.remove_df_levels( self.raw_values, ['supply_node', 'supply_technology']) else: # measure specific sales share does not require technology filtering Abstract.__init__(self, self.id)
def __init__(self, id, drivers, sql_id_table, sql_data_table, primary_key, technology_id=None, **kwargs): self.id = id self.drivers = drivers self.technology_id = technology_id self.sql_id_table = sql_id_table self.sql_data_table = sql_data_table self.primary_key = primary_key for col, att in util.object_att_from_table(self.sql_id_table, self.id, 'subsector_id'): setattr(self, col, att) self.in_use_drivers() DataMapFunctions.__init__(self, self.primary_key) self.read_timeseries_data() self.projected = False
def __init__(self, id, drivers, sql_id_table, sql_data_table, demand_technology_id=None, **kwargs): self.id = id self.drivers = drivers self.demand_technology_id = demand_technology_id self.sql_id_table = sql_id_table self.sql_data_table = sql_data_table self.primary_key = 'subsector_id' self.data_id_key = 'subsector_id' for col, att in util.object_att_from_table(self.sql_id_table, self.id, 'subsector_id'): setattr(self, col, att) self.in_use_drivers() DataMapFunctions.__init__(self, self.data_id_key) self.read_timeseries_data() self.projected = False
def __init__(self, id, drivers, sql_id_table, sql_data_table, scenario=None, demand_technology_id=None): self.id = id self.drivers = drivers self.demand_technology_id = demand_technology_id self.sql_id_table = sql_id_table self.sql_data_table = sql_data_table if scenario: self.scenario = scenario self.primary_key = 'subsector_id' self.data_id_key = 'subsector_id' for col, att in util.object_att_from_table(self.sql_id_table, self.id, 'subsector_id'): setattr(self, col, att) self.in_use_drivers() DataMapFunctions.__init__(self, self.data_id_key) self.read_timeseries_data() self.projected = False
def __init__(self, id, supply_node_id, sql_id_table, sql_data_table, primary_key, data_id_key, reference=False): self.id = id self.input_type = 'total' self.supply_node_id = supply_node_id self.sql_id_table = sql_id_table self.sql_data_table = sql_data_table self.mapped = False if reference: for col, att in util.object_att_from_table(self.sql_id_table, self.supply_node_id, primary_key): setattr(self, col, att) DataMapFunctions.__init__(self, data_id_key) self.read_timeseries_data(supply_node_id=self.supply_node_id) self.raw_values = util.remove_df_levels(self.raw_values, 'supply_technology') else: # measure specific sales does not require technology filtering Abstract.__init__(self, self.id, primary_key=primary_key, data_id_key=data_id_key)
def __init__(self, id, subsector_id, sql_id_table, sql_data_table, primary_key, data_id_key, reference=False): self.id = id self.subsector_id = subsector_id self.sql_id_table = sql_id_table self.sql_data_table = sql_data_table self.mapped = False if reference: for col, att in util.object_att_from_table(self.sql_id_table, self.subsector_id, primary_key): if att is not None: setattr(self, col, att) DataMapFunctions.__init__(self, data_id_key) self.read_timeseries_data(subsector_id=self.subsector_id) self.raw_values = util.remove_df_levels(self.raw_values, 'technology') else: self.replaced_demand_tech_id = None # measure specific sales share does not require technology filtering Abstract.__init__(self, self.id, primary_key=primary_key, data_id_key=data_id_key)
def __init__(self, id, supply_node_id, sql_id_table, sql_data_table, reference=False): self.id = id self.supply_node_id = supply_node_id self.sql_id_table = sql_id_table self.sql_data_table = sql_data_table self.mapped = False self.input_type = 'intensity' if reference: for col, att in util.object_att_from_table(self.sql_id_table, self.supply_node_id, 'supply_node_id'): if att is not None: setattr(self, col, att) DataMapFunctions.__init__(self, 'supply_technology') self.read_timeseries_data() self.raw_values = util.remove_df_levels(self.raw_values, ['supply_node','supply_technology']) else: # measure specific sales share does not require technology filtering Abstract.__init__(self, self.id)