from __future__ import annotations

from typing import Optional

import numpy as np


MODE_TO_ROW = {"11": 0, "22": 3, "12": 6}
LATERAL_ROW = {"11": 1, "22": 4, "12": None}
EPS33_ROW = {"11": 2, "22": 5, "12": None}


def evaluate_cubic_no_intercept(coeffs: np.ndarray, x: np.ndarray) -> np.ndarray:
    coeffs = np.asarray(coeffs, dtype=np.float32).reshape(-1)
    x = np.asarray(x, dtype=np.float32)
    coeffs_with_zero = np.append(coeffs, 0.0)
    return np.polyval(coeffs_with_zero, x).astype(np.float32)


def fit_cubic_no_intercept(x: np.ndarray, y: np.ndarray, degree: int = 3) -> Optional[np.ndarray]:
    x = np.asarray(x, dtype=np.float32).reshape(-1)
    y = np.asarray(y, dtype=np.float32).reshape(-1)
    if x.size < 2 or y.size < 2 or x.size != y.size:
        return None
    degree = int(max(1, min(int(degree), max(1, x.size - 1))))
    A = np.vstack([x**p for p in range(degree, 0, -1)]).T
    try:
        coeffs, *_ = np.linalg.lstsq(A, y, rcond=None)
        return coeffs.astype(np.float32)
    except Exception:
        return None


def default_x_for_mode(mode: str) -> np.ndarray:
    x_max = 0.1
    return np.linspace(0.0, x_max, 250, dtype=np.float32)