# Demo entry 4722481

**HTML**

Submitted by **anonymous**
on May 10, 2016 at 16:32

Language: Python. Code size: 727 Bytes.

import numpy as np from numpy import linalg as LA def steepest_descent(f, gradients, initialguess, approximationlevel, maxiterations): n=len(initialguess) xk=initialguess for iterations in range(maxiterations): Vf=np.zeros(n) for i in range(0,n): Vf[i]= gradients[i](xk) pk = -Vf print 'pk',pk a=1 c1=0.0001 ared=1 pred=0 while ared>pred: ared = f(xk+a*pk) pred = f(xk)-a*c1*LA.norm(Vf)**2 print 'ared',ared print 'pred',pred print a a=a-0.005 xk=xk+a*pk print initialguess,a,pk,xk,f(xk) print f(initialguess)

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