НПтаМ_ПР№4_Мірошниченко

from __future__ import annotations

from pathlib import Path

import matplotlib.pyplot as plt
import numpy as np


def build_curves() -> tuple[np.ndarray, dict[str, np.ndarray]]:
    T_over_Q = 2.0
    Q_over_T = 1.0 / T_over_Q
    l0 = 2.0
    a = 2.0
    D = 2.0

    beta = 1.0 / (1.0 + Q_over_T)
    gamma = T_over_Q * (D - 1.0)

    x = np.logspace(np.log10(5.0), np.log10(500.0), 500)

    curves = {
        "Дебаївська експонента": np.exp(-x),
        "Закон Колерауша": np.exp(-(x ** beta)),
        r"$\exp\!\left(-\left[(T/Q)\ln x\right]^{1/a}\right)$": np.exp(-((T_over_Q * np.log(x)) ** (1.0 / a))),
        r"$[(T/Q)\ln x]^{-1/l_0}$": (T_over_Q * np.log(x)) ** (-1.0 / l0),
        r"$x^{-\gamma}$": x ** (-gamma),
        r"$[(T/Q)\ln x]^{-D/a}$": (T_over_Q * np.log(x)) ** (-D / a),
        r"$[\ln((T/Q)\ln x)]^{-D}$": np.log(T_over_Q * np.log(x)) ** (-D),
    }

    return x, curves


def make_plot(output_path: str | Path = "pr4_asymptotics_from_python.png", show: bool = True) -> Path:
    x, curves = build_curves()
    output_path = Path(output_path)

    plt.figure(figsize=(8.4, 5.2))
    for label, y in curves.items():
        plt.plot(x, y, label=label)

    plt.xscale("log")
    plt.xlabel(r"$x=t/\tau_0$")
    plt.ylabel("S(x)")
    plt.title("Порівняння часових асимптотик структурного фактора")
    plt.grid(True, which="both", alpha=0.25)
    plt.legend()
    plt.tight_layout()
    plt.savefig(output_path, dpi=200)

    if show:
        plt.show()
    else:
        plt.close()

    return output_path


if __name__ == "__main__":
    saved_to = make_plot()
    print(f"Графік збережено у файл: {saved_to.resolve()}")