1

import matplotlib.pyplot as plt
import numpy as np


def f(x):
    return (x - 3) / (x ** 2 + 5) ** 0.5


def search_method(a, b, e=0.01):
    d = (b - a) / 4
    x0 = a
    while True:
        x1 = x0 + d
        if f(x0) > f(x1):
            x0 = x1
            if a <= x0 <= b:
                continue
            else:
                if abs(d) <= e:
                    return x0
                else:
                    x0 = x1
                    d = -d / 4
        else:
            if abs(d) <= e:
                return x0
            else:
                x0 = x1
                d = -d / 4


f_min = search_method(-3, -1)
print('Метод поразрядного поиска')
print('x =', f_min)
print('f(x) =', f(f_min))
print()


def dichotomy_method(a, b, e=0.01):
    c = 0.002
    while True:
        x1 = (b + a - c) / 2
        x2 = (b + a + c) / 2
        if f(x1) <= f(x2):
            b = x2
        else:
            a = x1
        e_n = (b - a) / 2
        if e_n > e:
            continue
        else:
            return (a + b) / 2

f_min = dichotomy_method(-3, -1)
print('Метод дихотомии')
print('x =', f_min)
print('f(x) =', f(f_min))
print()


def golden_section_method(a, b, e=0.01):
    while True:
        c = a + (3 - 5**0.5) / 2 * (b - a)
        d = a + (5**0.5 - 1) / 2 * (b - a)
        if f(d) > f(c):
            b = d
        else:
            a = c
        if (b - a) > e:
            continue
        else:
            return min(d, c)


f_min = golden_section_method(-3, -1)
print('Метод золотого сечения')
print('x =', f_min)
print('f(x) =', f(f_min))
print()

x = np.arange(-3, -1, 0.01)
y = list(map(f, x))

plt.plot(x, y)
plt.show()