sd.py

# sd.py
import numpy as np
from strong_wolfe import strong_wolfe

floatX = np.longdouble

def sd(fhandle, x0, max_iter=200000, ftol=1e-8, step_tol=1e-8,gtol=1e-8):
    x = np.asarray(x0, dtype=floatX).ravel().copy()
    f_prev = fhandle(x, 'f')
    for k in range(1, max_iter + 1):
        g = fhandle(x, 'grad')
        alpha = strong_wolfe(fhandle, x, -g)
        x_new = x + alpha * (-g)
        f_new = fhandle(x_new, 'f')
        if (abs(f_new - f_prev) < ftol and
                np.linalg.norm(x_new - x) < step_tol and
                np.linalg.norm(g) <= gtol):
            return x_new, f_new, k
        x, f_prev = x_new, f_new
    return x, fhandle(x, 'f'), max_iter