idp_pool

class EgonHeatTimeseries(**kwargs)

Bases: sqlalchemy.orm.decl_api.Base

building_id

selected_idp_profiles

zensus_population_id

annual_demand_generator(scenario)

Description: Create dataframe with annual demand and household count for each zensus cell

Returns

demand_count (pandas.DataFrame) – Annual demand of all zensus cell with MFH and SFH count and respective associated Station

create()

Description: Create dataframe with all temprature classes, 24hr. profiles and household stock

Returns

idp_df (pandas.DataFrame) – All IDP pool as classified as per household stock and temperature class

idp_pool_generator()

Create List of Dataframes for each temperature class for each household stock

Returns

list – List of dataframes with each element representing a dataframe for every combination of household stock and temperature class

select()

Random assignment of intray-day profiles to each day based on their temeprature class and household stock count

Returns

None.

temperature_classes()