data module

data.generate_new_case_study(casestudy: str, config: dict)

Generates a new case study folder with default files and default values.

Parameters:

• casestudy (str) -- name of the case study to be created

• config (dict) -- configuration dictionary

data.generate_new_scenario(casestudy: str, scenario_dir: str, config: dict)

Generates a new scenario folder with default files and default values.

Parameters:

• casestudy (str) -- name of the case study

• scenario_dir (str) -- name of the scenario directory to be created

• config (dict) -- configuration dictionary

data.load_config() → dict

loads the configuration file

Returns:

configuration dictionary

Return type:

dict

data.load_cost_parameter(casestudy: str, scenario: str, config: dict) → dict

loads the cost and parameters for tje scenario from disk.

Parameters:

• casestudy (str) -- name of the case study

• scenario (str) -- name of the scenario

• config (dict) -- configuration dictionary

Returns:

dictionary containing the costs and parameters

Return type:

dict

data.load_data_from_disk(casestudy: str, scenario: str, config: dict) → dict

loads the data required for the optimization model from disk.

Parameters:

• casestudy (str) -- name of the case study

• scenario (str) -- name of the scenario

• config (dict) -- configuration dictionary

Returns:

dictionary containing the dataframes and geodataframes for the optimization model

Return type:

dict

data.load_model_data(scenario_path: str) → dict

Loads the model input data from the scenario path. - not used anymore, use load_data_from_disk instead

Parameters:

scenario_path (str) -- path to the correct scenario folder

Returns:

dictionary containing the dataframes and geodataframes for the optimization model

Return type:

dict

data.load_solar_gain_data(scenario: str, config: dict) → DataFrame

Loads the solar gain data for the scenario from disk.

Solar gain data here referes to the solar irradiation in W/m2 data that is used to calculate the solar gain for the buildings.

Parameters:

• scenario (str) -- name of the scenario

• config (dict) -- configuration dictionary

Returns:

dataframe containing the solar gain data and the time index

Return type:

pd.DataFrame

data.load_temp_data(scenario: str, config: dict) → DataFrame

Loads the outside temperature data for the scenario from disk.

Parameters:

• scenario (str) -- name of the scenario

• config (dict) -- configuration dictionary

Returns:

dataframe containing the outside temperature data and the time index

Return type:

pd.DataFrame

data.prepare_parameter_file(case_study_name: str, scenario_name: str, config: dict)

Prepares the parameter file for the scenario by loading the parameter xlsx file and saving it as a json file.

Parameters:

• case_study_name (str) -- name of the case study

• scenario_name (str) -- name of the scenario

• config (dict) -- configuration dictionary

data.read_output_from_disk(case_study_name: str, model_name: str, config: dict) → dict

Reads the output data of the optimisation model from the disk for the given case study and model name.

Parameters:

• case_study_name (str) -- name of the case study

• model_name (str) -- name of the scenario

• config (dict) -- configuration dictionary

Returns:

dictionary containing the output dataframes from the optimization model

Return type:

dict