[SciPy-User] optimize.fmin_l_bfgs_b wrong number of arguments

ilan barak ibarak2000@yahoo....
Sun Jul 22 11:22:47 CDT 2012


Hello,
I apologize for the long description, this is the best I can do...

I have two functions defined as:

def hypothesis(params):
    # build a series of length params[0], with starting gap
    params[1] , repitition params[2] with sclae params[3]
    # using tt as the basic shape
    result=np.zeros(params[0])
    for index in
    np.arange(params[1],params[0]-tt.shape[0],params[2]):
        result[int(round(index)):int(round(index))+tt.shape[0]]=tt
    return params[3]*result

def Cost(params,sig): #  starting gap params[0] , repitition
    params[1] with sclae params[2]
    # sig is signa;s to compare to
    # calculate error cost
    result=np.linalg.norm(sig-hypothesis([sig.shape[0]]+params))
    return result

The Cost function requires a 3 parameter list and a signal that is a
    800 long ndarray
Running the Cost with:
params=([start,gap,0.04])
Cost(params,mysig5) , where mysig 5 is length 800 ndarray works
    fine.
However:
p0 = np.array([10.,20.,0.01]) # Initial guess for the parameters
    start,gap,scale
mybounds = [(0,20), (10,25), (0.001,0.1)]
x, f, d= optimize.fmin_l_bfgs_b(Cost, p0[:],fprime=None,
    args=mysig5, bounds=mybounds, approx_grad=True)

complains:

Traceback               
    <module>   
    C:\Users\ilan\Documents\python\opt_detection_danny1.py    130       
    fmin_l_bfgs_b   
    C:\Python27\lib\site-packages\scipy\optimize\lbfgsb.py    199       
    func_and_grad   
    C:\Python27\lib\site-packages\scipy\optimize\lbfgsb.py    145       
TypeError: Cost() takes exactly 2 arguments (801 given)             
     

Where am I wrong

thanks

Ilan 


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