backtrack(func,
args,
x,
f,
g,
p,
a_init=1.0,
rho=0.5,
c=0.0001,
max_iter=500)
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Backtracking line search.
Procedure 3.1, page 41, from 'Numerical Optimization' by Jorge Nocedal and Stephen J. Wright,
1999, 2nd ed.
Requires the gradient vector at point xk.
Function options
~~~~~~~~~~~~~~~~
func - The function to minimise.
args - The tuple of arguments to supply to the functions func.
x - The parameter vector.
f - The function value at the point x.
g - The gradient vector at the point x.
p - The descent direction.
a_init - Initial step length.
rho - The step length scaling factor (should be between 0 and 1).
c - Constant between 0 and 1 determining the slope for the sufficient decrease condition.
Returned objects
~~~~~~~~~~~~~~~~
The parameter vector, minimised along the direction xk + ak.pk, to be used at k+1.
Internal variables
~~~~~~~~~~~~~~~~~~
ai - The step length at line search iteration i.
xai - The parameter vector at step length ai.
fai - The function value at step length ai.
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