babylon.engine.dialectics.trpf

TRPFDialectic — Tendency of the Rate of Profit to Fall (V3 Ch13-15).

Pole A holds the tendency (profit rate trajectory). Pole B holds the counter-tendency vector from economics.counter_tendencies.

See also

babylon.economics.counter_tendencies: Counter-tendency calculations.

Classes

ProfitRateState(**data)	Pole A for the TRPF dialectic.
TRPFDialectic(**data)	Tendency of the Rate of Profit to Fall ↔ Counteracting Tendencies.

class babylon.engine.dialectics.trpf.ProfitRateState(**data)

Bases: BaseModel

Pole A for the TRPF dialectic.

Parameters:

• profit_rate (float)

• profit_rate_trend (float)

• organic_composition (Annotated[float, Ge(ge=0)])

profit_rate

Current average rate of profit.

profit_rate_trend

Year-over-year change in profit rate.

organic_composition

c/v ratio (OCC).

model_config: ClassVar[ConfigDict] = {'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

profit_rate: float

profit_rate_trend: float

organic_composition: float

class babylon.engine.dialectics.trpf.TRPFDialectic(**data)

Bases: Dialectic[ProfitRateState, CounterTendencyStrength]

Tendency of the Rate of Profit to Fall ↔ Counteracting Tendencies.

Pole A holds the tendency (profit rate trajectory). Pole B holds the counter-tendency vector from economics.counter_tendencies.

Weight semantics:

< 0: TRPF dominating (profit rate falling, counter-tendencies weak). > 0: Counter-tendencies dominating (profit rate sustained).

Motion law:

Reads upstream OCC and exploitation rate changes, delegates to CounterTendencyStrength.net_counter_tendency for weight.

No sublation: TRPF is a structural tendency, not an event.

Parameters:

• id (UUID)

• type_tag (str)

• pole_a (ProfitRateState)

• pole_b (CounterTendencyStrength)

• weight (Annotated[float, Ge(ge=-1.0), Le(le=1.0)])

• parent_id (UUID | None)

• tick_created (int)

• tick_updated (int)

type_tag: str

step(inputs, world)

Motion law T for TRPF dynamics.

Parameters:

• inputs (TickInputs) – Upstream outputs. Looks for occ, exploitation_rate.

• world (WorldView) – Read-only world context.

Return type:

TRPFDialectic

Returns:

New TRPFDialectic with updated weight and poles.

observe()

Project TRPF state for downstream consumers.

Return type:

dict[str, Any]

Returns:

Observation dict with profit rate, OCC, net counter-tendency.

model_config: ClassVar[ConfigDict] = {'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

id: UUID

pole_a: A

pole_b: B

weight: float

parent_id: UUID | None

tick_created: int

tick_updated: int