model_output_schemas

TemperatureResultSchema

Bases: DataFrameModel

Schema for temperature result DataFrame with MultiIndex columns.

Structure: - Index: datetime (time series) - Columns: MultiIndex with 3 levels: - Level 0: circuit_name (str) - Level 1: cable_position (CablePosition enum values) - Level 2: cable_layer (CableLayer enum values) - Values: temperature in degrees Celsius (float)

check_datetime_index classmethod

check_datetime_index(df: DataFrame)

Ensure index is datetime-like.

Source code in cable_thermal_model/model/schemas/model_output_schemas.py

@pa.dataframe_check(error="Temperature result index must be datetime-like.")
@classmethod
def check_datetime_index(cls, df: pd.DataFrame):
    """Ensure index is datetime-like."""
    return pd.api.types.is_datetime64_any_dtype(df.index) or pd.api.types.is_timedelta64_dtype(df.index)

check_multiindex_columns classmethod

check_multiindex_columns(df: DataFrame)

Ensure columns are a MultiIndex with 3 levels.

Source code in cable_thermal_model/model/schemas/model_output_schemas.py

@pa.dataframe_check(
    error="Temperature result columns must be a 3-level MultiIndex: (circuit_name, cable_position, cable_layer)."
)
@classmethod
def check_multiindex_columns(cls, df: pd.DataFrame):
    """Ensure columns are a MultiIndex with 3 levels."""
    expected_nlevels = 3
    return isinstance(df.columns, pd.MultiIndex) and df.columns.nlevels == expected_nlevels

check_circuit_names classmethod

check_circuit_names(df: DataFrame) -> bool

Ensure level-0 names are valid circuit names or the measurement-point prefix.

Source code in cable_thermal_model/model/schemas/model_output_schemas.py

@pa.dataframe_check
@classmethod
def check_circuit_names(cls, df: pd.DataFrame) -> bool:
    """Ensure level-0 names are valid circuit names or the measurement-point prefix."""
    circuit_names = df.columns.get_level_values(0).unique()
    for name in circuit_names:
        if name == MEASUREMENT_POINT_KEY_PREFIX:
            continue  # Skip validation for measurement-point columns
        if not isinstance(name, str) or len(name) == 0:
            raise ValueError(f"Circuit name '{name}' is not a valid non-empty string.")
    return True

check_cable_positions classmethod

check_cable_positions(df: DataFrame) -> bool

Validate level-1 and level-2 values by column type.

• For cable result columns: level 1 must be a valid CablePosition. Level 2 must be a valid CableLayer.
• For measurement-point columns: level 1 must be a string starting with 'x='. Level 2 must be a string starting with 'y='.

Source code in cable_thermal_model/model/schemas/model_output_schemas.py

@pa.dataframe_check
@classmethod
def check_cable_positions(cls, df: pd.DataFrame) -> bool:
    """Validate level-1 and level-2 values by column type.

    - For cable result columns: level 1 must be a valid CablePosition. Level 2 must be a valid CableLayer.
    - For measurement-point columns: level 1 must be a string starting with 'x='. Level 2 must be a string
        starting with 'y='.
    """
    level0_values = df.columns.get_level_values(0)
    level1_values = df.columns.get_level_values(1)
    level2_values = df.columns.get_level_values(2)

    for level0, level1, level2 in zip(level0_values, level1_values, level2_values, strict=True):
        if level0 == MEASUREMENT_POINT_KEY_PREFIX:
            if not isinstance(level1, str) or not level1.startswith("x="):
                raise ValueError("Measurement-point columns must have level 1 as a string starting with 'x='.")
            if not isinstance(level2, str) or not level2.startswith("y="):
                raise ValueError("Measurement-point columns must have level 2 as a string starting with 'y='.")
        else:
            CablePosition(level1)
            CableLayer(level2)

    return True

check_temperature_values classmethod

check_temperature_values(df: DataFrame) -> bool

Ensure temperature values are floats.

Source code in cable_thermal_model/model/schemas/model_output_schemas.py

@pa.dataframe_check
@classmethod
def check_temperature_values(cls, df: pd.DataFrame) -> bool:
    """Ensure temperature values are floats."""
    for dtype in df.dtypes:
        if not pd.api.types.is_float_dtype(dtype):
            raise ValueError("All temperature values must be of float type.")
    return True

ModelOutputSchema

Bases: BaseModel, Generic[StateT]

Schema for the output of the thermal cable model, containing the temperature results and the final state.