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aeromaps.models.impacts.energy_resources.energy_consumption

energy_consumption

Module to compute energy consumption from different aircraft types.

DropInFuelConsumption 

DropInFuelConsumption(name='drop_in_fuel_consumption', *args, **kwargs)

Bases: AeroMAPSModel

Total drop-in fuel consumption calculation.

Parameters:

Name Type Description Default
name str

Name of the model instance ('drop_in_fuel_consumption' by default).

 'drop_in_fuel_consumption'
Documentation

Inputs - ask_dropin_fuel: Passenger ASK for drop-in fuel aircraft [ASK]. - rtkdropin_fuel: Freight RTK for drop-in fuel aircraft [RTK]. - energy_per_ask_without_operationsdropin_fuel: Passenger MJ/ASK (no ops). - energy_per_askdropin_fuel: Passenger MJ/ASK (with ops). - energy_per_rtk_without_operationsdropin_fuel: Freight MJ/RTK (no ops). - energy_per_rtkdropin_fuel: Freight MJ/RTK (with ops). Outputs - energy_consumptiondropin_fuel_without_operations: Per-market drop-in [MJ]. - energy_consumption_dropin_fuel: Per-market drop-in [MJ]. - energy_consumption_passenger_dropin_fuel_without_operations: Passenger total [MJ]. - energy_consumption_freight_dropin_fuel_without_operations: Freight total [MJ]. - energy_consumption_dropin_fuel_without_operations: Passenger + freight [MJ]. - energy_consumption_passenger_dropin_fuel: Passenger total [MJ]. - energy_consumption_freight_dropin_fuel: Freight total [MJ]. - energy_consumption_dropin_fuel: Passenger + freight [MJ]. Notes - is the MarketManager id (passenger and freight markets). - I/O names are generated from configuration and passed to GEMSEO via self.input_names and self.output_names grammars.

Source code in aeromaps/models/impacts/energy_resources/energy_consumption.py 
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def __init__(self, name="drop_in_fuel_consumption", *args, **kwargs):
    super().__init__(name=name, model_type="custom", *args, **kwargs)
    self.markets = None

custom_setup 

custom_setup()

Build input_names / output_names dynamically from the MarketManager. Called once by AeroMAPSProcess after self.markets is injected.

Source code in aeromaps/models/impacts/energy_resources/energy_consumption.py 
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def custom_setup(self):
    """
    Build input_names / output_names dynamically from the MarketManager.
    Called once by AeroMAPSProcess after self.markets is injected.
    """
    self.input_names = {}
    self.output_names = {}

    passenger_markets = list(self.markets.get(traffic_type="passenger"))
    freight_markets = list(self.markets.get(traffic_type="freight"))

    # Per-market inputs and outputs (passenger: ask-based; freight: rtk-based).
    for market in passenger_markets:
        mid = market.id
        self.input_names[f"ask_{mid}_dropin_fuel"] = pd.Series([0.0])
        self.input_names[f"energy_per_ask_without_operations_{mid}_dropin_fuel"] = pd.Series(
            [0.0]
        )
        self.input_names[f"energy_per_ask_{mid}_dropin_fuel"] = pd.Series([0.0])
        self.output_names[f"energy_consumption_{mid}_dropin_fuel_without_operations"] = (
            pd.Series([0.0])
        )
        self.output_names[f"energy_consumption_{mid}_dropin_fuel"] = pd.Series([0.0])

    for market in freight_markets:
        mid = market.id
        self.input_names[f"rtk_{mid}_dropin_fuel"] = pd.Series([0.0])
        self.input_names[f"energy_per_rtk_without_operations_{mid}_dropin_fuel"] = pd.Series(
            [0.0]
        )
        self.input_names[f"energy_per_rtk_{mid}_dropin_fuel"] = pd.Series([0.0])
        self.output_names[f"energy_consumption_{mid}_dropin_fuel_without_operations"] = (
            pd.Series([0.0])
        )
        self.output_names[f"energy_consumption_{mid}_dropin_fuel"] = pd.Series([0.0])

    # Aggregate outputs (passenger sum, freight sum, grand total) — both with and without operations.
    self.output_names["energy_consumption_passenger_dropin_fuel_without_operations"] = (
        pd.Series([0.0])
    )
    self.output_names["energy_consumption_passenger_dropin_fuel"] = pd.Series([0.0])
    self.output_names["energy_consumption_freight_dropin_fuel_without_operations"] = pd.Series(
        [0.0]
    )
    self.output_names["energy_consumption_freight_dropin_fuel"] = pd.Series([0.0])
    self.output_names["energy_consumption_dropin_fuel_without_operations"] = pd.Series([0.0])
    self.output_names["energy_consumption_dropin_fuel"] = pd.Series([0.0])

compute 

compute(input_data)

Drop-in fuel energy consumption per market and aggregates.

Per-market: energy = energy_per_(ask|rtk) * (ask|rtk). Aggregates: passenger sum over passenger markets, freight sum over freight markets, grand total = passenger + freight. Both with-operations and without-operations variants are produced.

Source code in aeromaps/models/impacts/energy_resources/energy_consumption.py 
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def compute(self, input_data) -> dict:
    """
    Drop-in fuel energy consumption per market and aggregates.

    Per-market: energy = energy_per_(ask|rtk) * (ask|rtk).
    Aggregates: passenger sum over passenger markets, freight sum over freight
    markets, grand total = passenger + freight. Both with-operations and
    without-operations variants are produced.
    """
    output_data = {}

    passenger_markets = list(self.markets.get(traffic_type="passenger"))
    freight_markets = list(self.markets.get(traffic_type="freight"))

    # Per-passenger-market consumption.
    passenger_dropin_fuel = None
    passenger_dropin_fuel_without_operations = None
    for market in passenger_markets:
        mid = market.id
        ask = input_data[f"ask_{mid}_dropin_fuel"]
        energy_per_ask_without_operations = input_data[
            f"energy_per_ask_without_operations_{mid}_dropin_fuel"
        ]
        energy_per_ask = input_data[f"energy_per_ask_{mid}_dropin_fuel"]

        # Energy is zero wherever there is no traffic, even when the per-ASK intensity is
        # NaN/inf from an upstream division-by-zero (energy_per_ask = energy / ask). The mask
        # is applied per-year so partially-empty markets (zero ASK in some years only) do not
        # leak NaN: inf * 0 would otherwise produce NaN and propagate to every aggregate.
        energy_consumption_without_operations = (energy_per_ask_without_operations * ask).where(
            ask != 0.0, 0.0
        )
        energy_consumption = (energy_per_ask * ask).where(ask != 0.0, 0.0)

        output_data[f"energy_consumption_{mid}_dropin_fuel_without_operations"] = (
            energy_consumption_without_operations
        )
        output_data[f"energy_consumption_{mid}_dropin_fuel"] = energy_consumption

        passenger_dropin_fuel_without_operations = (
            energy_consumption_without_operations
            if passenger_dropin_fuel_without_operations is None
            else passenger_dropin_fuel_without_operations
            + energy_consumption_without_operations
        )
        passenger_dropin_fuel = (
            energy_consumption
            if passenger_dropin_fuel is None
            else passenger_dropin_fuel + energy_consumption
        )

    # Per-freight-market consumption.
    freight_dropin_fuel = None
    freight_dropin_fuel_without_operations = None
    for market in freight_markets:
        mid = market.id
        rtk = input_data[f"rtk_{mid}_dropin_fuel"]
        energy_per_rtk_without_operations = input_data[
            f"energy_per_rtk_without_operations_{mid}_dropin_fuel"
        ]
        energy_per_rtk = input_data[f"energy_per_rtk_{mid}_dropin_fuel"]

        # Energy is zero wherever there is no traffic, even when the per-RTK intensity is
        # NaN/inf from an upstream division-by-zero (energy_per_rtk = energy / rtk). The mask
        # is applied per-year so partially-empty markets (zero RTK in some years only) do not
        # leak NaN: inf * 0 would otherwise produce NaN and propagate to every aggregate.
        energy_consumption_without_operations = (energy_per_rtk_without_operations * rtk).where(
            rtk != 0.0, 0.0
        )
        energy_consumption = (energy_per_rtk * rtk).where(rtk != 0.0, 0.0)

        output_data[f"energy_consumption_{mid}_dropin_fuel_without_operations"] = (
            energy_consumption_without_operations
        )
        output_data[f"energy_consumption_{mid}_dropin_fuel"] = energy_consumption

        freight_dropin_fuel_without_operations = (
            energy_consumption_without_operations
            if freight_dropin_fuel_without_operations is None
            else freight_dropin_fuel_without_operations + energy_consumption_without_operations
        )
        freight_dropin_fuel = (
            energy_consumption
            if freight_dropin_fuel is None
            else freight_dropin_fuel + energy_consumption
        )

    # Default to zero series when no markets in a traffic_type (defensive — should not happen
    # for the default 4-market config, but custom configs may have e.g. zero freight markets).
    if passenger_dropin_fuel_without_operations is None:
        passenger_dropin_fuel_without_operations = pd.Series(0.0, index=self.df.index)
    if passenger_dropin_fuel is None:
        passenger_dropin_fuel = pd.Series(0.0, index=self.df.index)
    if freight_dropin_fuel_without_operations is None:
        freight_dropin_fuel_without_operations = pd.Series(0.0, index=self.df.index)
    if freight_dropin_fuel is None:
        freight_dropin_fuel = pd.Series(0.0, index=self.df.index)

    output_data["energy_consumption_passenger_dropin_fuel_without_operations"] = (
        passenger_dropin_fuel_without_operations
    )
    output_data["energy_consumption_passenger_dropin_fuel"] = passenger_dropin_fuel
    output_data["energy_consumption_freight_dropin_fuel_without_operations"] = (
        freight_dropin_fuel_without_operations
    )
    output_data["energy_consumption_freight_dropin_fuel"] = freight_dropin_fuel
    output_data["energy_consumption_dropin_fuel_without_operations"] = (
        passenger_dropin_fuel_without_operations + freight_dropin_fuel_without_operations
    )
    output_data["energy_consumption_dropin_fuel"] = passenger_dropin_fuel + freight_dropin_fuel

    self._store_outputs(output_data)
    return output_data

DropInFuelDetailledConsumption 

DropInFuelDetailledConsumption(name='drop_in_fuel_detailled_consumption', *args, **kwargs)

Bases: AeroMAPSModel

Detailled drop-in fuel consumption calculation.

Parameters:

Name Type Description Default
name str

Name of the model instance ('drop_in_fuel_detailled_consumption' by default).

 'drop_in_fuel_detailled_consumption'
Documentation

Inputs - biomass_share_dropin_fuel: Share of biomass-based fuels in drop-in fuels [%]. - electricity_share_dropin_fuel: Share of electricity-based fuels in drop-in fuels [%]. - fossil_share_dropin_fuel: Share of fossil-based fuels in drop-in fuels [%]. - energy_consumption_dropin_fuel_without_operations: Drop-in fuel energy (no ops) [MJ]. - energy_consumptiondropin_fuel: Drop-in fuel energy (with ops) [MJ]. Outputs - energy_consumption_without_operations: Per-market split by fuel [MJ]. - energy_consumption: Per-market split by fuel [MJ]. - energy_consumption_passengerwithout_operations: Passenger total [MJ]. - energy_consumption_freightwithout_operations: Freight total [MJ]. - energy_consumptionwithout_operations: Passenger + freight [MJ]. - energy_consumption_passenger: Passenger total [MJ]. - energy_consumption_freight_: Freight total [MJ]. - energy_consumption_: Passenger + freight [MJ]. Notes - is the MarketManager id (passenger and freight markets). - is one of: biofuel, electrofuel, kerosene. - I/O names are generated from configuration and passed to GEMSEO via self.input_names and self.output_names grammars.

Source code in aeromaps/models/impacts/energy_resources/energy_consumption.py 
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def __init__(self, name="drop_in_fuel_detailled_consumption", *args, **kwargs):
    super().__init__(name=name, model_type="custom", *args, **kwargs)
    self.markets = None

compute 

compute(input_data)

Drop-in fuel detailed consumption per market and aggregates.

Source code in aeromaps/models/impacts/energy_resources/energy_consumption.py 
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def compute(self, input_data) -> dict:
    """Drop-in fuel detailed consumption per market and aggregates."""
    output_data = {}

    passenger_markets = list(self.markets.get(traffic_type="passenger"))
    freight_markets = list(self.markets.get(traffic_type="freight"))

    shares = {
        "biofuel": input_data["biomass_share_dropin_fuel"] / 100,
        "electrofuel": input_data["electricity_share_dropin_fuel"] / 100,
        "kerosene": input_data["fossil_share_dropin_fuel"] / 100,
    }

    passenger_fuel_totals_without_operations = {fuel: None for fuel in shares}
    passenger_fuel_totals = {fuel: None for fuel in shares}
    freight_fuel_totals_without_operations = {fuel: None for fuel in shares}
    freight_fuel_totals = {fuel: None for fuel in shares}

    for market in passenger_markets:
        mid = market.id
        dropin_fuel_without_operations = input_data[
            f"energy_consumption_{mid}_dropin_fuel_without_operations"
        ]
        dropin_fuel = input_data[f"energy_consumption_{mid}_dropin_fuel"]
        for fuel, share in shares.items():
            fuel_energy_without_operations = share * dropin_fuel_without_operations
            fuel_energy = share * dropin_fuel
            output_data[f"energy_consumption_{mid}_{fuel}_without_operations"] = (
                fuel_energy_without_operations
            )
            output_data[f"energy_consumption_{mid}_{fuel}"] = fuel_energy
            passenger_fuel_totals_without_operations[fuel] = (
                fuel_energy_without_operations
                if passenger_fuel_totals_without_operations[fuel] is None
                else passenger_fuel_totals_without_operations[fuel]
                + fuel_energy_without_operations
            )
            passenger_fuel_totals[fuel] = (
                fuel_energy
                if passenger_fuel_totals[fuel] is None
                else passenger_fuel_totals[fuel] + fuel_energy
            )

    for market in freight_markets:
        mid = market.id
        dropin_fuel_without_operations = input_data[
            f"energy_consumption_{mid}_dropin_fuel_without_operations"
        ]
        dropin_fuel = input_data[f"energy_consumption_{mid}_dropin_fuel"]
        for fuel, share in shares.items():
            fuel_energy_without_operations = share * dropin_fuel_without_operations
            fuel_energy = share * dropin_fuel
            output_data[f"energy_consumption_{mid}_{fuel}_without_operations"] = (
                fuel_energy_without_operations
            )
            output_data[f"energy_consumption_{mid}_{fuel}"] = fuel_energy
            freight_fuel_totals_without_operations[fuel] = (
                fuel_energy_without_operations
                if freight_fuel_totals_without_operations[fuel] is None
                else freight_fuel_totals_without_operations[fuel]
                + fuel_energy_without_operations
            )
            freight_fuel_totals[fuel] = (
                fuel_energy
                if freight_fuel_totals[fuel] is None
                else freight_fuel_totals[fuel] + fuel_energy
            )

    for fuel in shares:
        if passenger_fuel_totals_without_operations[fuel] is None:
            passenger_fuel_totals_without_operations[fuel] = pd.Series(0.0, index=self.df.index)
        if passenger_fuel_totals[fuel] is None:
            passenger_fuel_totals[fuel] = pd.Series(0.0, index=self.df.index)
        if freight_fuel_totals_without_operations[fuel] is None:
            freight_fuel_totals_without_operations[fuel] = pd.Series(0.0, index=self.df.index)
        if freight_fuel_totals[fuel] is None:
            freight_fuel_totals[fuel] = pd.Series(0.0, index=self.df.index)

        output_data[f"energy_consumption_passenger_{fuel}_without_operations"] = (
            passenger_fuel_totals_without_operations[fuel]
        )
        output_data[f"energy_consumption_freight_{fuel}_without_operations"] = (
            freight_fuel_totals_without_operations[fuel]
        )
        output_data[f"energy_consumption_{fuel}_without_operations"] = (
            passenger_fuel_totals_without_operations[fuel]
            + freight_fuel_totals_without_operations[fuel]
        )
        output_data[f"energy_consumption_passenger_{fuel}"] = passenger_fuel_totals[fuel]
        output_data[f"energy_consumption_freight_{fuel}"] = freight_fuel_totals[fuel]
        output_data[f"energy_consumption_{fuel}"] = (
            passenger_fuel_totals[fuel] + freight_fuel_totals[fuel]
        )

    self._store_outputs(output_data)
    return output_data

HydrogenConsumption 

HydrogenConsumption(name='hydrogen_consumption', *args, **kwargs)

Bases: AeroMAPSModel

Class to calculate hydrogen consumption for each type of market.

Parameters:

Name Type Description Default
name str

Name of the model instance ('hydrogen_consumption' by default).

 'hydrogen_consumption'
Documentation

Inputs - ask_hydrogen: Passenger ASK for hydrogen aircraft [ASK]. - rtkhydrogen: Freight RTK for hydrogen aircraft [RTK]. - energy_per_ask_without_operationshydrogen: Passenger MJ/ASK (no ops). - energy_per_askhydrogen: Passenger MJ/ASK (with ops). - energy_per_rtk_without_operationshydrogen: Freight MJ/RTK (no ops). - energy_per_rtkhydrogen: Freight MJ/RTK (with ops). Outputs - energy_consumptionhydrogen_without_operations: Per-market hydrogen [MJ]. - energy_consumption_hydrogen: Per-market hydrogen [MJ]. - energy_consumption_passenger_hydrogen_without_operations: Passenger total [MJ]. - energy_consumption_freight_hydrogen_without_operations: Freight total [MJ]. - energy_consumption_hydrogen_without_operations: Passenger + freight [MJ]. - energy_consumption_passenger_hydrogen: Passenger total [MJ]. - energy_consumption_freight_hydrogen: Freight total [MJ]. - energy_consumption_hydrogen: Passenger + freight [MJ]. Notes - is the MarketManager id (passenger and freight markets). - I/O names are generated from configuration and passed to GEMSEO via self.input_names and self.output_names grammars.

Source code in aeromaps/models/impacts/energy_resources/energy_consumption.py 
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def __init__(self, name="hydrogen_consumption", *args, **kwargs):
    super().__init__(name=name, model_type="custom", *args, **kwargs)
    self.markets = None

compute 

compute(input_data)

Hydrogen consumption per market and aggregates.

Source code in aeromaps/models/impacts/energy_resources/energy_consumption.py 
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def compute(self, input_data) -> dict:
    """Hydrogen consumption per market and aggregates."""
    output_data = {}

    passenger_markets = list(self.markets.get(traffic_type="passenger"))
    freight_markets = list(self.markets.get(traffic_type="freight"))

    passenger_hydrogen_without_operations = None
    passenger_hydrogen = None
    for market in passenger_markets:
        mid = market.id
        ask = input_data[f"ask_{mid}_hydrogen"]
        energy_per_ask_without_operations = input_data[
            f"energy_per_ask_without_operations_{mid}_hydrogen"
        ]
        energy_per_ask = input_data[f"energy_per_ask_{mid}_hydrogen"]

        # Energy is zero wherever there is no traffic, even when the per-ASK intensity is
        # NaN/inf from an upstream division-by-zero (energy_per_ask = energy / ask). The mask
        # is applied per-year so partially-empty markets (zero ASK in some years only) do not
        # leak NaN: inf * 0 would otherwise produce NaN and propagate to every aggregate.
        energy_consumption_without_operations = (energy_per_ask_without_operations * ask).where(
            ask != 0.0, 0.0
        )
        energy_consumption = (energy_per_ask * ask).where(ask != 0.0, 0.0)

        output_data[f"energy_consumption_{mid}_hydrogen_without_operations"] = (
            energy_consumption_without_operations
        )
        output_data[f"energy_consumption_{mid}_hydrogen"] = energy_consumption

        passenger_hydrogen_without_operations = (
            energy_consumption_without_operations
            if passenger_hydrogen_without_operations is None
            else passenger_hydrogen_without_operations + energy_consumption_without_operations
        )
        passenger_hydrogen = (
            energy_consumption
            if passenger_hydrogen is None
            else passenger_hydrogen + energy_consumption
        )

    freight_hydrogen_without_operations = None
    freight_hydrogen = None
    for market in freight_markets:
        mid = market.id
        rtk = input_data[f"rtk_{mid}_hydrogen"]
        energy_per_rtk_without_operations = input_data[
            f"energy_per_rtk_without_operations_{mid}_hydrogen"
        ]
        energy_per_rtk = input_data[f"energy_per_rtk_{mid}_hydrogen"]

        # Energy is zero wherever there is no traffic, even when the per-RTK intensity is
        # NaN/inf from an upstream division-by-zero (energy_per_rtk = energy / rtk). The mask
        # is applied per-year so partially-empty markets (zero RTK in some years only) do not
        # leak NaN: inf * 0 would otherwise produce NaN and propagate to every aggregate.
        energy_consumption_without_operations = (energy_per_rtk_without_operations * rtk).where(
            rtk != 0.0, 0.0
        )
        energy_consumption = (energy_per_rtk * rtk).where(rtk != 0.0, 0.0)

        output_data[f"energy_consumption_{mid}_hydrogen_without_operations"] = (
            energy_consumption_without_operations
        )
        output_data[f"energy_consumption_{mid}_hydrogen"] = energy_consumption

        freight_hydrogen_without_operations = (
            energy_consumption_without_operations
            if freight_hydrogen_without_operations is None
            else freight_hydrogen_without_operations + energy_consumption_without_operations
        )
        freight_hydrogen = (
            energy_consumption
            if freight_hydrogen is None
            else freight_hydrogen + energy_consumption
        )

    if passenger_hydrogen_without_operations is None:
        passenger_hydrogen_without_operations = pd.Series(0.0, index=self.df.index)
    if passenger_hydrogen is None:
        passenger_hydrogen = pd.Series(0.0, index=self.df.index)
    if freight_hydrogen_without_operations is None:
        freight_hydrogen_without_operations = pd.Series(0.0, index=self.df.index)
    if freight_hydrogen is None:
        freight_hydrogen = pd.Series(0.0, index=self.df.index)

    output_data["energy_consumption_passenger_hydrogen_without_operations"] = (
        passenger_hydrogen_without_operations
    )
    output_data["energy_consumption_freight_hydrogen_without_operations"] = (
        freight_hydrogen_without_operations
    )
    output_data["energy_consumption_hydrogen_without_operations"] = (
        passenger_hydrogen_without_operations + freight_hydrogen_without_operations
    )
    output_data["energy_consumption_passenger_hydrogen"] = passenger_hydrogen
    output_data["energy_consumption_freight_hydrogen"] = freight_hydrogen
    output_data["energy_consumption_hydrogen"] = passenger_hydrogen + freight_hydrogen

    self._store_outputs(output_data)
    return output_data

ElectricConsumption 

ElectricConsumption(name='electric_consumption', *args, **kwargs)

Bases: AeroMAPSModel

Class to calculate electricity consumption for each type of market.

Parameters:

Name Type Description Default
name str

Name of the model instance ('electric_consumption' by default).

 'electric_consumption'
Documentation

Inputs - ask_electric: Passenger ASK for electric aircraft [ASK]. - rtkelectric: Freight RTK for electric aircraft [RTK]. - energy_per_ask_without_operationselectric: Passenger MJ/ASK (no ops). - energy_per_askelectric: Passenger MJ/ASK (with ops). - energy_per_rtk_without_operationselectric: Freight MJ/RTK (no ops). - energy_per_rtkelectric: Freight MJ/RTK (with ops). Outputs - energy_consumptionelectric_without_operations: Per-market electricity [MJ]. - energy_consumption_electric: Per-market electricity [MJ]. - energy_consumption_passenger_electric_without_operations: Passenger total [MJ]. - energy_consumption_freight_electric_without_operations: Freight total [MJ]. - energy_consumption_electric_without_operations: Passenger + freight [MJ]. - energy_consumption_passenger_electric: Passenger total [MJ]. - energy_consumption_freight_electric: Freight total [MJ]. - energy_consumption_electric: Passenger + freight [MJ]. Notes - is the MarketManager id (passenger and freight markets). - I/O names are generated from configuration and passed to GEMSEO via self.input_names and self.output_names grammars.

Source code in aeromaps/models/impacts/energy_resources/energy_consumption.py 
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def __init__(self, name="electric_consumption", *args, **kwargs):
    super().__init__(name=name, model_type="custom", *args, **kwargs)
    self.markets = None

compute 

compute(input_data)

Electricity consumption per market and aggregates.

Source code in aeromaps/models/impacts/energy_resources/energy_consumption.py 
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def compute(self, input_data) -> dict:
    """Electricity consumption per market and aggregates."""
    output_data = {}

    passenger_markets = list(self.markets.get(traffic_type="passenger"))
    freight_markets = list(self.markets.get(traffic_type="freight"))

    passenger_electric_without_operations = None
    passenger_electric = None
    for market in passenger_markets:
        mid = market.id
        ask = input_data[f"ask_{mid}_electric"]
        energy_per_ask_without_operations = input_data[
            f"energy_per_ask_without_operations_{mid}_electric"
        ]
        energy_per_ask = input_data[f"energy_per_ask_{mid}_electric"]

        # Energy is zero wherever there is no traffic, even when the per-ASK intensity is
        # NaN/inf from an upstream division-by-zero (energy_per_ask = energy / ask). The mask
        # is applied per-year so partially-empty markets (zero ASK in some years only) do not
        # leak NaN: inf * 0 would otherwise produce NaN and propagate to every aggregate.
        energy_consumption_without_operations = (energy_per_ask_without_operations * ask).where(
            ask != 0.0, 0.0
        )
        energy_consumption = (energy_per_ask * ask).where(ask != 0.0, 0.0)

        output_data[f"energy_consumption_{mid}_electric_without_operations"] = (
            energy_consumption_without_operations
        )
        output_data[f"energy_consumption_{mid}_electric"] = energy_consumption

        passenger_electric_without_operations = (
            energy_consumption_without_operations
            if passenger_electric_without_operations is None
            else passenger_electric_without_operations + energy_consumption_without_operations
        )
        passenger_electric = (
            energy_consumption
            if passenger_electric is None
            else passenger_electric + energy_consumption
        )

    freight_electric_without_operations = None
    freight_electric = None
    for market in freight_markets:
        mid = market.id
        rtk = input_data[f"rtk_{mid}_electric"]
        energy_per_rtk_without_operations = input_data[
            f"energy_per_rtk_without_operations_{mid}_electric"
        ]
        energy_per_rtk = input_data[f"energy_per_rtk_{mid}_electric"]

        # Energy is zero wherever there is no traffic, even when the per-RTK intensity is
        # NaN/inf from an upstream division-by-zero (energy_per_rtk = energy / rtk). The mask
        # is applied per-year so partially-empty markets (zero RTK in some years only) do not
        # leak NaN: inf * 0 would otherwise produce NaN and propagate to every aggregate.
        energy_consumption_without_operations = (energy_per_rtk_without_operations * rtk).where(
            rtk != 0.0, 0.0
        )
        energy_consumption = (energy_per_rtk * rtk).where(rtk != 0.0, 0.0)

        output_data[f"energy_consumption_{mid}_electric_without_operations"] = (
            energy_consumption_without_operations
        )
        output_data[f"energy_consumption_{mid}_electric"] = energy_consumption

        freight_electric_without_operations = (
            energy_consumption_without_operations
            if freight_electric_without_operations is None
            else freight_electric_without_operations + energy_consumption_without_operations
        )
        freight_electric = (
            energy_consumption
            if freight_electric is None
            else freight_electric + energy_consumption
        )

    if passenger_electric_without_operations is None:
        passenger_electric_without_operations = pd.Series(0.0, index=self.df.index)
    if passenger_electric is None:
        passenger_electric = pd.Series(0.0, index=self.df.index)
    if freight_electric_without_operations is None:
        freight_electric_without_operations = pd.Series(0.0, index=self.df.index)
    if freight_electric is None:
        freight_electric = pd.Series(0.0, index=self.df.index)

    output_data["energy_consumption_passenger_electric_without_operations"] = (
        passenger_electric_without_operations
    )
    output_data["energy_consumption_freight_electric_without_operations"] = (
        freight_electric_without_operations
    )
    output_data["energy_consumption_electric_without_operations"] = (
        passenger_electric_without_operations + freight_electric_without_operations
    )
    output_data["energy_consumption_passenger_electric"] = passenger_electric
    output_data["energy_consumption_freight_electric"] = freight_electric
    output_data["energy_consumption_electric"] = passenger_electric + freight_electric

    self._store_outputs(output_data)
    return output_data

EnergyConsumption 

EnergyConsumption(name='energy_consumption', *args, **kwargs)

Bases: AeroMAPSModel

Class to calculate total energy consumption for each type of market, aggregating all energy sources.

Documentation

Inputs - energy_consumption_dropin_fuel_without_operations: Drop-in fuel [MJ]. - energy_consumptionhydrogen_without_operations: Hydrogen [MJ]. - energy_consumptionelectric_without_operations: Electricity [MJ]. - energy_consumptiondropin_fuel: Drop-in fuel [MJ]. - energy_consumptionhydrogen: Hydrogen [MJ]. - energy_consumptionelectric: Electricity [MJ]. Outputs - energy_consumptionwithout_operations: Per-market total [MJ]. - energy_consumption: Per-market total [MJ]. - energy_consumption_passenger_without_operations: Passenger total [MJ]. - energy_consumption_freight_without_operations: Freight total [MJ]. - energy_consumption_without_operations: Passenger + freight [MJ]. - energy_consumption_passenger: Passenger total [MJ]. - energy_consumption_freight: Freight total [MJ]. - energy_consumption: Passenger + freight [MJ]. Notes - is the MarketManager id (passenger and freight markets). - I/O names are generated from configuration and passed to GEMSEO via self.input_names and self.output_names grammars.

Source code in aeromaps/models/impacts/energy_resources/energy_consumption.py 
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def __init__(self, name="energy_consumption", *args, **kwargs):
    super().__init__(name=name, model_type="custom", *args, **kwargs)
    self.markets = None

compute 

compute(input_data)

Total energy consumption per market and aggregates.

Source code in aeromaps/models/impacts/energy_resources/energy_consumption.py 
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def compute(self, input_data) -> dict:
    """Total energy consumption per market and aggregates."""
    output_data = {}

    passenger_markets = list(self.markets.get(traffic_type="passenger"))
    freight_markets = list(self.markets.get(traffic_type="freight"))

    passenger_energy_without_operations = None
    passenger_energy = None
    for market in passenger_markets:
        mid = market.id
        market_energy_without_operations = (
            input_data[f"energy_consumption_{mid}_dropin_fuel_without_operations"]
            + input_data[f"energy_consumption_{mid}_hydrogen_without_operations"]
            + input_data[f"energy_consumption_{mid}_electric_without_operations"]
        )
        market_energy = (
            input_data[f"energy_consumption_{mid}_dropin_fuel"]
            + input_data[f"energy_consumption_{mid}_hydrogen"]
            + input_data[f"energy_consumption_{mid}_electric"]
        )

        output_data[f"energy_consumption_{mid}_without_operations"] = (
            market_energy_without_operations
        )
        output_data[f"energy_consumption_{mid}"] = market_energy

        passenger_energy_without_operations = (
            market_energy_without_operations
            if passenger_energy_without_operations is None
            else passenger_energy_without_operations + market_energy_without_operations
        )
        passenger_energy = (
            market_energy if passenger_energy is None else passenger_energy + market_energy
        )

    freight_energy_without_operations = None
    freight_energy = None
    for market in freight_markets:
        mid = market.id
        market_energy_without_operations = (
            input_data[f"energy_consumption_{mid}_dropin_fuel_without_operations"]
            + input_data[f"energy_consumption_{mid}_hydrogen_without_operations"]
            + input_data[f"energy_consumption_{mid}_electric_without_operations"]
        )
        market_energy = (
            input_data[f"energy_consumption_{mid}_dropin_fuel"]
            + input_data[f"energy_consumption_{mid}_hydrogen"]
            + input_data[f"energy_consumption_{mid}_electric"]
        )

        output_data[f"energy_consumption_{mid}_without_operations"] = (
            market_energy_without_operations
        )
        output_data[f"energy_consumption_{mid}"] = market_energy

        freight_energy_without_operations = (
            market_energy_without_operations
            if freight_energy_without_operations is None
            else freight_energy_without_operations + market_energy_without_operations
        )
        freight_energy = (
            market_energy if freight_energy is None else freight_energy + market_energy
        )

    if passenger_energy_without_operations is None:
        passenger_energy_without_operations = pd.Series(0.0, index=self.df.index)
    if passenger_energy is None:
        passenger_energy = pd.Series(0.0, index=self.df.index)
    if freight_energy_without_operations is None:
        freight_energy_without_operations = pd.Series(0.0, index=self.df.index)
    if freight_energy is None:
        freight_energy = pd.Series(0.0, index=self.df.index)

    output_data["energy_consumption_passenger_without_operations"] = (
        passenger_energy_without_operations
    )
    output_data["energy_consumption_freight_without_operations"] = (
        freight_energy_without_operations
    )
    output_data["energy_consumption_without_operations"] = (
        passenger_energy_without_operations + freight_energy_without_operations
    )
    output_data["energy_consumption_passenger"] = passenger_energy
    output_data["energy_consumption_freight"] = freight_energy
    output_data["energy_consumption"] = passenger_energy + freight_energy

    self._store_outputs(output_data)
    return output_data