### documentation steepest descent

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 ... @@ -28,7 +28,7 @@ class ConjugateGradient(Loggable, object): ... @@ -28,7 +28,7 @@ class ConjugateGradient(Loggable, object): It is an iterative method for solving a linear system of equations: It is an iterative method for solving a linear system of equations: Ax = b Ax = b SUGESTED LITERATURE: SUGGESTED LITERATURE: Thomas V. Mikosch et al., "Numerical Optimization", Second Edition, Thomas V. Mikosch et al., "Numerical Optimization", Second Edition, 2006, Springer-Verlag New York 2006, Springer-Verlag New York ... @@ -46,7 +46,7 @@ class ConjugateGradient(Loggable, object): ... @@ -46,7 +46,7 @@ class ConjugateGradient(Loggable, object): conjugated directions. (default: None) conjugated directions. (default: None) preconditioner : function *optional* preconditioner : function *optional* The user can provide a function which transforms the variables of the The user can provide a function which transforms the variables of the system to make the convarge more favorable.(default: None) system to make the converge more favorable.(default: None) callback : function, *optional* callback : function, *optional* Function f(energy, iteration_number) specified by the user to print Function f(energy, iteration_number) specified by the user to print iteration number and energy value at every iteration step. It accepts iteration number and energy value at every iteration step. It accepts ... @@ -65,7 +65,7 @@ class ConjugateGradient(Loggable, object): ... @@ -65,7 +65,7 @@ class ConjugateGradient(Loggable, object): conjugated directions. conjugated directions. preconditioner : function preconditioner : function The user can provide a function which transforms the variables of the The user can provide a function which transforms the variables of the system to make the convarge more favorable. system to make the converge more favorable. callback : function callback : function Function f(energy, iteration_number) specified by the user to print Function f(energy, iteration_number) specified by the user to print iteration number and energy value at every iteration step. It accepts iteration number and energy value at every iteration step. It accepts ... ...
 ... @@ -29,7 +29,10 @@ class RelaxedNewton(QuasiNewtonMinimizer): ... @@ -29,7 +29,10 @@ class RelaxedNewton(QuasiNewtonMinimizer): --------- --------- line_searcher : LineSearch, line_searcher : LineSearch, An implementation of a line-search algorithm. An implementation of a line-search algorithm. callback : callback : function, *optional* Function f(energy, iteration_number) specified by the user to print iteration number and energy value at every iteration step. It accepts an Energy object(energy) and integer(iteration_number). (default: None) convergence_tolerance : float, convergence_tolerance : float, Specifies the required accuracy for convergence. (default : 10e-4) Specifies the required accuracy for convergence. (default : 10e-4) convergence_level : integer convergence_level : integer ... ...
 ... @@ -20,6 +20,22 @@ from .quasi_newton_minimizer import QuasiNewtonMinimizer ... @@ -20,6 +20,22 @@ from .quasi_newton_minimizer import QuasiNewtonMinimizer class SteepestDescent(QuasiNewtonMinimizer): class SteepestDescent(QuasiNewtonMinimizer): """Implementation of the steepest descent minimization scheme. It uses the gradient of the minimized function to get to the minimum. Parameters ---------- energy : Energy object The energy object providing implementations of the to be minimized function and gradient. Returns ------- descend_direction : Field Returns the descent direction. """ def _get_descend_direction(self, energy): def _get_descend_direction(self, energy): descend_direction = energy.gradient descend_direction = energy.gradient norm = descend_direction.norm() norm = descend_direction.norm() ... ...
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