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)
