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July 7, 2012 16:53
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L-BFGS example in Scipy
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import numpy as np | |
from scipy.optimize import fmin_bfgs | |
def rosen(x): | |
return sum(100.0*(x[1:]-x[:-1]**2.0)**2.0 + (1-x[:1])**2.0) | |
def rosen_der(x): | |
xm = x[1:-1] | |
xm_m1 = x[:-2] | |
xm_p1 = x[2:] | |
der = np.zeros_like(x) | |
der[1:-1] = 200*(xm-xm_m1**2) - 400*(xm_p1 - xm**2)*xm - 2*(1-xm) | |
der[0] = -400*x[0]*(x[1]-x[0]**2) - 2*(1-x[0]) | |
der[-1] = 200*(x[-1]-x[-2]**2) | |
return der | |
x0 = np.array([1.3, 0.7, 0.8, 1.9, 1.2]) | |
res = fmin_bfgs(rosen, x0, fprime=rosen_der) | |
print res |
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any explanation?