from __future__ import annotations

from dataclasses import dataclass, field
from pathlib import Path


CORE_FEATURE_NAMES: tuple[str, ...] = (
    "frequency_hz",
    "frequency_squared",
    "x_rms",
    "theoretical_accel",
)


@dataclass
class DataConfig:
    project_root: Path = field(default_factory=lambda: Path(__file__).resolve().parents[1])
    data_dir: str = "downloads/Non_TMD"
    harmonic_pattern: str = "harmonic*.csv"

    code_column: str = "code"
    time_column: str = "time"
    base_sensor_code: str = "WSMS00012"
    base_axis: str = "value1"
    response_sensor_code: str = "WSMS00007"
    response_axis: str = "value3"

    middle_segment_start_ratio: float = 0.20
    middle_segment_end_ratio: float = 0.80
    min_segment_length: int = 512
    steady_window_ratio: float = 0.25
    steady_window_stride_ratio: float = 0.05
    stability_subwindow_count: int = 4
    interpolation_method: str = "linear"
    normalization_eps: float = 1e-6
    harmonic_amplitude_m: float = 0.005

    data_root: Path = field(init=False)

    def __post_init__(self) -> None:
        self.project_root = Path(self.project_root).resolve()
        self.data_root = (self.project_root / self.data_dir).resolve()


@dataclass
class ModelConfig:
    model_name: str = "knn_distance"
    n_neighbors: int = 4
    distance_power: int = 2


@dataclass
class TrainConfig:
    checkpoint_dir: str = "checkpoints_final"
    model_name: str = "task1_final_model.pkl"
    fit_csv_name: str = "task1_final_fit_all.csv"
    fit_figure_name: str = "task1_final_fit_curve.png"
    dense_curve_csv_name: str = "task1_final_dense_curve.csv"
    evaluation_dense_csv_name: str = "evaluation_dense_curve.csv"
    dense_curve_points: int = 400


@dataclass
class ExperimentConfig:
    data: DataConfig = field(default_factory=DataConfig)
    model: ModelConfig = field(default_factory=ModelConfig)
    train: TrainConfig = field(default_factory=TrainConfig)


def make_experiment_config() -> ExperimentConfig:
    return ExperimentConfig()


def checkpoint_dir(config: ExperimentConfig) -> Path:
    path = config.data.project_root / config.train.checkpoint_dir / "task1_final"
    path.mkdir(parents=True, exist_ok=True)
    return path


def evaluation_dir(config: ExperimentConfig) -> Path:
    path = config.data.project_root / "evaluation_outputs" / "task1_final"
    path.mkdir(parents=True, exist_ok=True)
    return path