How to use the numdifftools.multicomplex.bicomplex function in numdifftools

def _multicomplex2(f, fx, x, h, *args, **kwds):
        z = bicomplex(x + 1j * h, h)
        return f(z, *args, **kwds).imag12

def _multicomplex2(f, fx, x, h, *args, **kwargs):
        '''Calculate Hessian with bicomplex-step derivative approximation
        '''
        n = len(x)
        ee = np.diag(h)
        hess = np.outer(h, h)
        for i in range(n):
            for j in range(i, n):
                zph = bicomplex(x + 1j * ee[i, :], ee[j, :])
                hess[i, j] = (f(zph, *args, **kwargs)).imag12 / hess[j, i]
                hess[j, i] = hess[i, j]
        return hess

def _multicomplex2(f, fx, x, h, *args, **kwds):
        n = len(x)
        increments = np.identity(n) * h
        partials = [f(bicomplex(x + 1j * hi, hi), *args, **kwds).imag12
                    for hi in increments]
        return np.array(partials)

def _multicomplex(f, fx, x, h, *args, **kwds):
        n = len(x)
        increments = np.identity(n) * 1j * h
        partials = [f(bicomplex(x + hi, 0), *args, **kwds).imag
                    for hi in increments]
        return np.array(partials).T

def _multicomplex(f, fx, x, h, *args, **kwds):
        z = bicomplex(x + 1j * h, 0)
        return f(z, *args, **kwds).imag