"""Trading cost models for portfolio execution simulation."""

from __future__ import annotations

from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Mapping

import numpy as np


class CostModel(ABC):
    """Interface for per-name execution cost models."""

    @abstractmethod
    def compute(
        self,
        traded_shares: np.ndarray,
        execution_price: np.ndarray,
        side: np.ndarray,
        date,
        metadata: Mapping[str, object] | None = None,
    ) -> np.ndarray:
        """Return per-name trading cost in yuan."""


@dataclass(frozen=True)
class SimpleProportionalCostModel(CostModel):
    """Simplified open-execution proportional cost model.

    Slippage is represented as an additional cash cost. The execution price is
    not adjusted by slippage, which avoids double-counting.
    """

    cost_bps: float = 0.0
    slippage_bps: float = 0.0

    def compute(
        self,
        traded_shares: np.ndarray,
        execution_price: np.ndarray,
        side: np.ndarray,
        date,
        metadata: Mapping[str, object] | None = None,
    ) -> np.ndarray:
        shares = np.asarray(traded_shares, dtype=np.float64)
        price = np.asarray(execution_price, dtype=np.float64)
        open_price = np.where(np.isfinite(price), price, 0.0)
        trade_value = np.abs(shares * open_price)
        return trade_value * (self.cost_bps + self.slippage_bps) / 1e4