marmot.formatters.formatsiip.ProcessSIIP#
- class ProcessSIIP(input_folder: pathlib.Path, output_file_path: pathlib.Path, *args, region_mapping: pandas.core.frame.DataFrame = Empty DataFrame Columns: [] Index: [], **kwargs)[source]#
Bases:
marmot.formatters.formatbase.Process
Process SIIP specific data from a SIIP result set.
- Parameters
input_folder (Path) – Folder containing csv files.
output_file_path (Path) – Path to formatted h5 output file.
region_mapping (pd.DataFrame, optional) – DataFrame to map custom regions/zones to create custom aggregations. Defaults to pd.DataFrame().
**kwargs – These parameters will be passed to the Process class.
Methods
Format SIIP Generator class data
df_process_line
(df)Format SIIP Line data
Format SIIP Region data
Format SIIP Reserves Generator data
get_processed_data
(prop_class, prop, ...)Handles the pulling of data from the SIIP input folder and then passes the data to one of the formating functions
output_metadata
(*_)Add SIIP specific metadata to formatted h5 file .
Attributes
Maps simulation model property names to Marmot property names
UNITS_CONVERSION
Dictionary to convert units to standard values used by Marmot
data_collection
Dictionary model names to full filename path
For SIIP returns paths to input folders
input_folder
Path to input folder
- PROPERTY_MAPPING: dict = {'generator_generation_actual': 'generator_Generation', 'generator_generation_availability': 'generator_Available_Capacity', 'generator_installed_capacity': 'generator_Installed_Capacity', 'line_power_flow_actual': 'line_Flow', 'region_regional_load': 'region_Demand', 'reserves_generators_reserve_contribution': 'reserves_generators_Provision'}#
Maps simulation model property names to Marmot property names
- EXTRA_PROPERTIES_CLASS#
- property get_input_data_paths: list#
For SIIP returns paths to input folders
SIIP places individual input files in a single folder, It does not combine all results into a single file like PLEXOS or ReEDS. If models have been split into partitions, returns list of partition folders, else returns scenario folder.
- get_processed_data(prop_class: str, prop: str, timescale: str, model_name: str) pandas.core.frame.DataFrame [source]#
Handles the pulling of data from the SIIP input folder and then passes the data to one of the formating functions
- Parameters
- Returns
Formatted results dataframe.
- Return type
pd.DataFrame
- df_process_generator(df: pandas.core.frame.DataFrame) pandas.core.frame.DataFrame [source]#
Format SIIP Generator class data
- Parameters
df (pd.DataFrame) – Data Frame to process
- Returns
dataframe formatted to generator class spec
- Return type
pd.DataFrame
- df_process_region(df: pandas.core.frame.DataFrame) pandas.core.frame.DataFrame [source]#
Format SIIP Region data
- Parameters
df (pd.DataFrame) – Data Frame to process
- Returns
dataframe formatted to region class spec
- Return type
pd.DataFrame
- df_process_reserves_generators(df: pandas.core.frame.DataFrame) pandas.core.frame.DataFrame [source]#
Format SIIP Reserves Generator data
- Parameters
df (pd.DataFrame) – Data Frame to process
- Returns
dataframe formatted to reserves generator class spec
- Return type
pd.DataFrame
- df_process_line(df: pandas.core.frame.DataFrame) pandas.core.frame.DataFrame [source]#
Format SIIP Line data
- Parameters
df (pd.DataFrame) – Data Frame to process
- Returns
dataframe formatted to region class spec
- Return type
pd.DataFrame