ebm.cmd.result_handler module

transform_model_to_horizontal(model, value_column='m2')

transform_to_sorted_heating_systems(df: DataFrame, holiday_homes: DataFrame, building_column: str = 'building_category') → DataFrame

transform_heating_systems_to_horizontal(model: DataFrame)

write_result(output_file, csv_delimiter, output, sheet_name='area forecast')

append_result(output_file: Path, df: DataFrame, sheet_name='Sheet 1')

Write df to output_file using sheet_name. If output_file already exists the sheet will be added tp ouput_file rather than replacing the entire content.

Parameters

output_file : df : sheet_name :

Returns

class EbmDefaultHandler

Bases: object

extract_model(year_range: YearRange, building_categories: list[BuildingCategory] | None, database_manager: DatabaseManager, step_choice: str = 'energy-use') → DataFrame

Extract dataframe for a certain step in the ebm model.

Possible steps are energy_use (default), heating-systems, energy-use, area-forecast

Parameters

year_range : ebm.model.dataclasses.YearRange building_categories : list[BuildingCategory] database_manager : ebm.model.database_manager.DatabaseManager step_choice : str, optional

Returns

pd.DataFrame

static extract_energy_requirements(building_categories, database_manager: DatabaseManager, area_forecast: DataFrame, period: YearRange) → DataFrame

Extracts energy needs for building_categories and period

Parameters

building_categories : list[BuildingCategory] database_manager : ebm.model.database_manager.DatabaseManager area_forecast : pd.DataFrame period :ebm.model.dataclasses.YearRange

Returns

pd.DataFrame

static extract_area_forecast(building_categories, database_manager: DatabaseManager, period: YearRange) → DataFrame

static write_tqdm_result(output_file: Path, output: DataFrame, csv_delimiter: str = ',', reset_index=True)