# -*- coding: utf-8 -*-
"""Evaluation helpers for cycle sensitivity analysis."""

from .cycles import BraytonCycle


RC_FIXED_KEYS = ("T_low", "T_high", "p_low", "p_high", "ploss")
RC_PARAM_KEYS = (
    "x",
    "compressor_eff",
    "recompressor_eff",
    "turbine_eff",
    "recuperator_eff",
    "highT_recuperator_eff",
)


def _require_keys(data, required_keys, data_name):
    missing = [key for key in required_keys if key not in data]
    if missing:
        missing_text = ", ".join(missing)
        raise ValueError(f"{data_name} missing required keys: {missing_text}")


def evaluate_rc_efficiency(fixed_params, params, refprop_path=None):
    """Return the recompression Brayton cycle thermal efficiency.

    The returned efficiency is a decimal value, for example 0.45 means 45%.
    A new cycle instance is created for each evaluation so repeated sensitivity
    runs do not reuse component state from previous cases.
    """
    fixed = dict(fixed_params)
    cycle_params = dict(params)

    _require_keys(fixed, RC_FIXED_KEYS, "fixed_params")
    _require_keys(cycle_params, RC_PARAM_KEYS, "params")

    cycle_kwargs = {"name": "rc efficiency evaluation"}
    if refprop_path is not None:
        cycle_kwargs["refprop_path"] = refprop_path

    cycle = BraytonCycle(**cycle_kwargs)
    return cycle.RC(
        T_low=fixed["T_low"],
        T_high=fixed["T_high"],
        p_low=fixed["p_low"],
        p_high=fixed["p_high"],
        ploss=fixed["ploss"],
        param=cycle_params,
    )