main.py

import sys

import click

from constants import RECURSION_LIMIT
from mv import scripts as mv_utils
from sv import scripts as sv_utils

sys.setrecursionlimit(RECURSION_LIMIT)

allowed_methods = ["sec", "newt", "fib", "GS", "DS", "lagin", "ls", "CG"]


@click.command()
@click.argument("type", nargs=1)
@click.option("--func", "-f", type=str, help="Function to be optimized")
@click.option("--first", "-x1", type=float, default=None, help="First value of x")
@click.option("--second", "-x2", type=float, default=None, help="Second value of x")
@click.option("--third", "-x3", type=float, default=None, help="Third value of x")
@click.option("--iter", "-i", type=int, default=None, help="Number of iterations")
@click.option("--epsilon", "-e", type=float, default=10**-3, help="Epsilon")
def optimization(type, func, first, second, third, iter, epsilon):
    if type not in allowed_methods:
        print("Invalid method")
        return
    if not func:
        print("Function is required")
        return
    if type == "sec":
        if first is None or second is None:
            print("Missing arguments")
            return
        result = sv_utils.secant_primary(func, first, second, epsilon)
        print(result)
    elif type == "newt":
        if not first or not iter:
            print("Missing arguments")
            return
        result = sv_utils.newton_primary(func, first, iter, epsilon)
        print(result)
    elif type == "fib":
        if not first or not second or not iter:
            print("Missing arguments")
            return
        result = sv_utils.fibonacci_primary(func, first, second, iter, epsilon)
        print(result)
    elif type == "GS":
        if not first or not second or not iter:
            print("Missing arguments")
            return
        result = sv_utils.golden_section_primary(func, first, second, iter, epsilon)
        print(result)
    elif type == "DS":
        if not first or not second:
            print("Missing arguments")
            return
        result = mv_utils.downhill_simplex_primary(func, first, second)
        print(result)
    elif type == "lagin":
        if not first or not second:
            print("Missing arguments")
            return
        x = [first, second, third] if third else [first, second]
        result = mv_utils.lagrange_interpolation_primary(func, x)
        print(result)
    elif type == "ls":
        if not first or not second:
            print("Missing arguments")
            return
        result = mv_utils.least_squares_primary(func, first, second)
        print(result["x"])
    elif type == "CG":
        if not first or not second or not iter:
            print("Missing arguments")
            return
        result = mv_utils.cauchy_gradient_primary(func, first, second, iter)
        print(result)


if __name__ == "__main__":
    optimization()