output_parser¶

output_parser ¶

PyAERMOD Output File Parser

Parses AERMOD output files (.out) and converts results to pandas DataFrames. Based on AERMOD version 24142 output format specifications.

ModelRunInfo `dataclass` ¶

Metadata about the AERMOD run

SourceSummary `dataclass` ¶

Summary information for a source

ReceptorInfo `dataclass` ¶

Information about a receptor

ConcentrationResult `dataclass` ¶

Concentration results for a specific averaging period

AERMODOutputParser ¶

Parser for AERMOD output files

Extracts run information, source data, receptor data, and concentration results.

parse ¶

parse() -> AERMODResults

Parse the output file and return results object

Returns: AERMODResults object with all parsed data

AERMODResults `dataclass` ¶

Complete AERMOD results

Contains all parsed information from an AERMOD output file.

from_file `classmethod` ¶

from_file(output_file: Union[str, Path]) -> AERMODResults

Parse AERMOD output file

Args: output_file: Path to AERMOD .out file

Returns: AERMODResults object

get_concentrations ¶

get_concentrations(averaging_period: str = 'ANNUAL') -> Optional[pd.DataFrame]

Get concentration DataFrame for specific averaging period

Args: averaging_period: Averaging period (e.g., 'ANNUAL', '24HR', '1HR')

Returns: DataFrame with x, y, concentration columns, or None if period not found.

get_max_concentration ¶

get_max_concentration(averaging_period: str = 'ANNUAL') -> Optional[Dict]

Get maximum concentration and its location

Args: averaging_period: Averaging period

Returns: Dictionary with 'value', 'x', 'y', 'units', or None if period not found.

get_concentration_at_point ¶

get_concentration_at_point(x: float, y: float, averaging_period: str = 'ANNUAL', tolerance: float = 1.0) -> Optional[float]

Get concentration at specific point (within tolerance)

Args: x: X coordinate y: Y coordinate averaging_period: Averaging period tolerance: Distance tolerance for matching receptors

Returns: Concentration value or None if no receptor found

get_sources_dataframe ¶

get_sources_dataframe() -> pd.DataFrame

Get sources as DataFrame

get_receptors_dataframe ¶

get_receptors_dataframe() -> pd.DataFrame

Get receptors as DataFrame

summary ¶

summary() -> str

Generate a text summary of results

export_to_csv ¶

export_to_csv(output_dir: Union[str, Path], prefix: str = 'aermod')

Export all results to CSV files

Args: output_dir: Directory for output files prefix: Prefix for filenames

parse_aermod_output ¶

parse_aermod_output(output_file: Union[str, Path]) -> AERMODResults

Parse an AERMOD output file

Args: output_file: Path to .out file