idp_pool

class EgonHeatTimeseries(**kwargs)[source]

Bases: sqlalchemy.ext.declarative.api.Base

building_id
selected_idp_profiles
zensus_population_id
annual_demand_generator()[source]

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()[source]

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()[source]

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

TYPE list
List of dataframes with each element representing a dataframe for every combination of household stock and temperature class
select()[source]

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

Returns:None.
temperature_classes()[source]