from __future__ import annotations

import inspect
import os

import numpy as np


def make_grid(
    dt: float | None = None,
    period: float | None = None,
    t_num: float | None = None,
    wl_min: float | None = None,
):
    ...


class Root:
    dt: float = Param()
    period: float
    t_num: int

    fiber: Fiber
    pulses: PulseTrain

    def __init__(self, name: str):
        ...

    @dt.register
    def dt_from_lmin(wavelength_max: float, wavelength_pump: float):
        return 1 / 6e8 * 1 / (1 / wavelength_pump - 1 / wavelength_max)


class PulseTrain:
    pulse_width: float
    shape: str = "gaussian"
    peak_power: float
    quantum_noise: bool = True

    def load_noise_spectrum(self, path: os.PathLike):
        ...


class Fiber:
    beta2_arr: np.ndarray
    length: float


params = Root(dt=2e-15, t_num=1024)

pulses = params.pulse_train
pulses.pulse_width = 50e-15
pulses.shape = "sech"
pulses.load_noise_spectrum(dBm="./some_noise.csv", v_ref=3)

fiber = params.fiber
fiber.length = 0.2