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6.3.7.2. supy.util.diagnose#
- supy.util.diagnose(df_output: DataFrame, variable: Literal['T2', 'q2', 'U10'] = 'T2', **kwargs) AttributionResult[source]#
Generic diagnostic function for near-surface variables.
Automatically identifies anomalous values and attributes the causes.
- Parameters:
df_output (pd.DataFrame) – SUEWS output DataFrame
variable (str, optional) – Variable to diagnose: ‘T2’ (temperature), ‘q2’ (humidity), or ‘U10’ (10m wind speed). Default ‘T2’.
**kwargs – Additional keyword arguments passed to the specific function. - method: ‘anomaly’, ‘extreme’, or ‘diurnal’ - threshold: float for anomaly detection - df_forcing: forcing DataFrame (T2, q2 only) - hierarchical: bool (T2 only) - z_ref: float (U10 only)
- Returns:
Attribution decomposition with diagnostic interpretation.
- Return type:
Examples
>>> result = diagnose(df_output, variable="T2", method="anomaly") >>> print(result)
>>> result = diagnose(df_output, variable="q2", method="diurnal") >>> print(result)
>>> result = diagnose(df_output, variable="U10", method="extreme") >>> print(result)