CODEWITHSUNDEEP
pythonoptimizationscipylevenberg-marquardt
Quini
Quini

Reputation: 11

Python: Scipy.optimize Levenberg-marquardt method

I have a question about how to use the Levenberg-Marquardt optimize method in Python. In the library SCIPY there are many optimization methods.

I tried two methods (Nelder-Mead and Basin-hopping) and both work well with the follow command:

# Nelder-Mead
res0_10 = optimize.minimize(f0_10, x0, method='Nelder-Mead', options={'disp': True, 'maxiter': 2000})

# Basin-hopping
res0_10 = optimize.basinhopping(f0_10, x0, niter=100, disp=True)

The problem emerge when I use the Levenberg-Marquardt (I copy only the part of error, because the program is long)

def f0_10(x):
    m, u, z, s = x 
    for i in range(alt_max):
         if i==alt_min: suma=0
         if i > alt_min:
         suma = suma + (B(x, i)-b0_10(x, i))**2
    return np.sqrt(suma/alt_max)

x0 = np.array([40., 0., 500., 50.])

res0_10 = root(f0_10, x0, jac=True, method='lm')

I only change the last sentence (res0_10 = root...). The program compile well, but when I execute the program:

Exception in Tkinter callback

Traceback (most recent call last):

File "C:\Users\Quini SB\AppData\Local\Enthought\Canopy\App\appdata\canopy-1.7.4.3348.win-x86_64\lib\lib-tk\Tkinter.py", line 1536, in __call__
return self.func(*args)

File "C:\Users\Quini SB\Desktop\tfg\Steyn - levmar.py", line 384, in askopenfilename
res0_10 = root(f0_10, x0, jac=True, method='lm')

File "C:\Users\Quini SB\AppData\Local\Enthought\Canopy\User\lib\site-packages\scipy\optimize\_root.py", line 188, in root
sol = _root_leastsq(fun, x0, args=args, jac=jac, **options)

File "C:\Users\Quini SB\AppData\Local\Enthought\Canopy\User\lib\site-packages\scipy\optimize\_root.py", line 251, in _root_leastsq
factor=factor, diag=diag)

File "C:\Users\Quini SB\AppData\Local\Enthought\Canopy\User\lib\site-packages\scipy\optimize\minpack.py", line 377, in leastsq
shape, dtype = _check_func('leastsq', 'func', func, x0, args, n)

File "C:\Users\Quini SB\AppData\Local\Enthought\Canopy\User\lib\site-packages\scipy\optimize\minpack.py", line 26, in _check_func
res = atleast_1d(thefunc(*((x0[:numinputs],) + args)))

File "C:\Users\Quini SB\AppData\Local\Enthought\Canopy\User\lib\site-packages\scipy\optimize\optimize.py", line 64, in __call__
self.jac = fg[1]

IndexError: invalid index to scalar variable.

Why does this error happen?

Upvotes: 1

Views: 7203

Answers (1)

valentin
valentin

Reputation: 3608

From documentation:

jac : bool or callable, optional

    If jac is a Boolean and is True, fun is assumed to return the value
    of Jacobian along with the objective function. If False, the 
    Jacobian will be estimated numerically. jac can also be a callable 
    returning the Jacobian of fun. In this case, it must accept the
    same arguments as fun.

So, your function 'f0_10' needs to return two values, because you set jac to True

Upvotes: 1

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