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Package API

pypsa_validation_processing

__all__ = ['Network_Processor'] module-attribute

Network_Processor

Processes a PyPSA NetworkCollection against IAMC variable definitions.

Reads variable definitions from a definitions folder, executes the corresponding statistics functions to extract values from a given PyPSA NetworkCollection, and returns the results as a pyam.IamDataFrame.

Outputs are converted to the units of common definitions, set in the definitions variable in definitions_path via :meth:pyam.IamDataFrame.convert_unit if convert_units is True in config.

calculate_variables_values() -> None

Calculate values for all defined variables.

Iterates over all variables in self.dsd, calls :meth:_execute_function_for_variable for each one, and assembles the results.

When self.aggregate_per_year is True (default), assembles a single :class:pyam.IamDataFrame with one column per investment year and stores it in self.dsd_with_values.

When self.aggregate_per_year is False, stores a list[tuple[int, pyam.IamDataFrame]] in self.dsd_with_values, one entry per investment year. Each :class:pyam.IamDataFrame contains the full time-series for that year.

Applies aggregation based on self.aggregation_level config.

read_definitions() -> nomenclature.DataStructureDefinition

Read IAMC variable definitions from the definitions folder.

Populates dsd with a :class:nomenclature.DataStructureDefinition built from self.definitions_path and returns it.

Returns:

Type Description
DataStructureDefinition

The loaded data structure definition.

structure_pyam_from_pandas(df: pd.DataFrame) -> pyam.IamDataFrame

Creates a pyam.IamDataFrame from a pandas DataFrame.

Parameters:

Name Type Description Default
df DataFrame

DataFrame with IAMC variables as columns and years as index.

 required

Returns:

Type Description
IamDataFrame

A pyam.IamDataFrame with IAMC variables as columns and years as index.
Notes

When aggregation_level="country", region labels are country codes by default. If map_country_codes_to_names is True in config, country codes are mapped to full names via :data:REGION_MAPPING. For country="all", the country column in df (populated by :meth:_aggregate_to_country) is used as the region dimension, one row per country. When aggregation_level="region", the location column in df is used directly.

write_output_to_xlsx() -> Path

Write the computed IAMC data to an Excel file (or files).

  • When aggregate_per_year=True: writes a single file <self.path_dsd_with_values>/PYPSA_{model}_{scenario}_{country}.xlsx.
  • When aggregate_per_year=False: creates a sub-folder <self.path_dsd_with_values>/PYPSA_timeseries_{model}_{scenario}_{country}/ and writes one file per investment year named PYPSA_{model}_{scenario}_{country}_{year}.xlsx.

Returns:

Type Description
Path

Path to the written file (aggregate_per_year=True) or to the folder containing all per-year files (aggregate_per_year=False).

Raises:

Type Description
RuntimeError

If :meth:calculate_variables_values has not been called yet.