fletcher_reeves(func=None,
dfunc=None,
args=( ) ,
x0=None,
min_options=None,
func_tol=1e-25,
grad_tol=None,
maxiter=1000000.0,
a0=1.0,
mu=0.0001,
eta=0.1,
full_output=0,
print_flag=0,
print_prefix='
' )
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Fletcher-Reeves conjugate gradient algorithm.
Page 120 from 'Numerical Optimization' by Jorge Nocedal and Stephen J.
Wright, 1999, 2nd ed. The algorithm is:
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Given x0
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Evaluate f0 = f(x0), g0 = g(x0)
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Set p0 = -g0, k = 0
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while g0 != 0:
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Compute ak and set xk+1 = xk + ak.pk
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Evaluate gk+1
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bk+1 = dot(gk+1, gk+1) / dot(gk, gk)
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pk+1 = -gk+1 + bk+1.pk
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k = k + 1
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