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Demands

Demand

Bases: BaseModel

Source code in passengersim/config/demands.py 
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class Demand(BaseModel, extra="forbid"):
    orig: str
    """Origin location for this demand.

    This is commonly a three letter airport code, but it need not be limited
    to airports.  It can be any location that is relevant to the simulation.

    If using 'places' for locations, this should match the 'name' field of
    a Place object."""

    dest: str
    """Destination location for this demand.

    This is commonly a three letter airport code, but it need not be limited
    to airports.  It can be any location that is relevant to the simulation.

    If using 'places' for locations, this should match the 'name' field of
    a Place object."""

    segment: str
    """Customer segment that this demand belongs to.

    For many applications, segments include 'business' and 'leisure', but
    they are not limited to these two categories."""

    @property
    def identifier(self):
        """Unique identifier for this demand."""
        return f"{self.orig}~{self.dest}@{self.segment}"

    base_demand: float
    reference_fare: float
    distance: float | None = 0.0
    choice_model: str | None = None
    """The name of the choice model that is applied for this demand."""

    dwm_tolerance: float | None = 0.0
    """The Decision Window is the shortest elapsed time, plus the tolerance (random draw)."""

    todd_curve: str | None = None
    """Time Of Day curve to be used in the choice model.  These
       can vary by length of haul, day of week, E-W directionality, etc.
       If specified here, it will override the curve in the ChoiceModel"""

    curve: str | None = None
    """The name of the booking curve that is applied for this demand.

    Each demand is attached to a booking curve that describes the temporal
    distribution of customer arrivals."""

    group_sizes: list[float] | None = None
    """Probability of each group size.
    i.e. [0.5, 0.3, 0.2] will give 50% one pax, 30% 2 pax, etc"""

    prob_saturday_night: float = False
    """Probability that the customer has a R/T itinerary with a Saturday night stay.
       Using this for choice modeling and CP experiments"""

    prob_num_days: list[float] = []
    """Probability of durations.
       [0.1, 0.3, 0.4, 0.2] will have durations of 1, 2, 3, 4 days
       and probability of each is specified explicitly
       Using this for choice modeling and CP experiments"""

    deterministic: bool = False
    """Whether the total amount of demand generated in each sample should be constant.

    If this is true, there will be no variance in the total demand generated,
    Which will be equal to the base demand modified by any market multipliers.
    There still can be some randomness in the timeframe arrival distribution of
    this demand, but the total demand generated in each sample will be the same.
    """

    overrides: list[DemandOverride] = []
    """Used for some specialized tests.
       Each dictionary should have 'carrier', 'discount_pct' and 'pref_adj'"""

    @property
    def choice_model_(self):
        """Choice model, falling back to segment name if not set explicitly."""
        return self.choice_model or self.segment

    @field_validator("curve", mode="before")
    def curve_integer_name(cls, v):
        """Booking curves can have integer names, treat as string."""
        if isinstance(v, int):
            v = str(v)
        return v

base_demand instance-attribute 

base_demand: float

choice_model class-attribute instance-attribute 

choice_model: str | None = None

The name of the choice model that is applied for this demand.

choice_model_ property 

choice_model_

Choice model, falling back to segment name if not set explicitly.

curve class-attribute instance-attribute 

curve: str | None = None

The name of the booking curve that is applied for this demand.

Each demand is attached to a booking curve that describes the temporal distribution of customer arrivals.

dest instance-attribute 

dest: str

Destination location for this demand.

This is commonly a three letter airport code, but it need not be limited to airports. It can be any location that is relevant to the simulation.

If using 'places' for locations, this should match the 'name' field of a Place object.

deterministic class-attribute instance-attribute 

deterministic: bool = False

Whether the total amount of demand generated in each sample should be constant.

If this is true, there will be no variance in the total demand generated, Which will be equal to the base demand modified by any market multipliers. There still can be some randomness in the timeframe arrival distribution of this demand, but the total demand generated in each sample will be the same.

distance class-attribute instance-attribute 

distance: float | None = 0.0

dwm_tolerance class-attribute instance-attribute 

dwm_tolerance: float | None = 0.0

The Decision Window is the shortest elapsed time, plus the tolerance (random draw).

group_sizes class-attribute instance-attribute 

group_sizes: list[float] | None = None

Probability of each group size. i.e. [0.5, 0.3, 0.2] will give 50% one pax, 30% 2 pax, etc

identifier property 

identifier

Unique identifier for this demand.

orig instance-attribute 

orig: str

Origin location for this demand.

This is commonly a three letter airport code, but it need not be limited to airports. It can be any location that is relevant to the simulation.

If using 'places' for locations, this should match the 'name' field of a Place object.

overrides class-attribute instance-attribute 

overrides: list[DemandOverride] = []

Used for some specialized tests. Each dictionary should have 'carrier', 'discount_pct' and 'pref_adj'

prob_num_days class-attribute instance-attribute 

prob_num_days: list[float] = []

Probability of durations. [0.1, 0.3, 0.4, 0.2] will have durations of 1, 2, 3, 4 days and probability of each is specified explicitly Using this for choice modeling and CP experiments

prob_saturday_night class-attribute instance-attribute 

prob_saturday_night: float = False

Probability that the customer has a R/T itinerary with a Saturday night stay. Using this for choice modeling and CP experiments

reference_fare instance-attribute 

reference_fare: float

segment instance-attribute 

segment: str

Customer segment that this demand belongs to.

For many applications, segments include 'business' and 'leisure', but they are not limited to these two categories.

todd_curve class-attribute instance-attribute 

todd_curve: str | None = None

Time Of Day curve to be used in the choice model. These can vary by length of haul, day of week, E-W directionality, etc. If specified here, it will override the curve in the ChoiceModel

curve_integer_name 

curve_integer_name(v)

Booking curves can have integer names, treat as string.

Source code in passengersim/config/demands.py 
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@field_validator("curve", mode="before")
def curve_integer_name(cls, v):
    """Booking curves can have integer names, treat as string."""
    if isinstance(v, int):
        v = str(v)
    return v

DemandOverride

Bases: BaseModel

Source code in passengersim/config/demands.py 
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class DemandOverride(BaseModel, extra="forbid"):
    carrier: str
    """Carrier code for the override."""

    discount_pct: float = 0.0
    """Discount percentage to apply for this override."""

    pref_adj: float = 0.0
    """Preference adjustment to apply for this override."""

carrier instance-attribute 

carrier: str

Carrier code for the override.

discount_pct class-attribute instance-attribute 

discount_pct: float = 0.0

Discount percentage to apply for this override.

pref_adj class-attribute instance-attribute 

pref_adj: float = 0.0

Preference adjustment to apply for this override.