Bdcamethods¶
- BDCA(mapp, x0, options)[source]¶
BDCA is a derivative-free algorithm for solving systems of nonlinear equations \(f(x) = 0\), x in \(R^m\) using the nonlinear unconstrained minimization \(\textrm{min}\ \psi(x) = 1/2 ||f(x)||^2\) s.t. x in \(R^m\).
- USAGE
[x_best,psi_best,out] = BDCA (mapp, x0, options)
- INPUTS
mapp – function handle provides f(x) and gradient f(x)
x0 – initial point
options – structure including the parameteres of scheme
.MaxNumIter - maximum number of iterations
.MaxNumMapEval - maximum number of function evaluations
.TimeLimit - maximum running time
.epsilon - accuracy parameter
.x_opt - optimizer
.psi_opt - optimum
.alpha - constant for the line searche
.beta - backtarcking constant
.lambda_bar - starting step-size for the line search
.rho - strong convexity parameter
.kin - kinetic parameter in R^(2n)
.flag_line_search - “Armijo” or “Quadratic_interpolation”
.flag_x_error - 1: saves \(x_{error}\), 0: do not saves \(x_{error}\) (default)
.flag_psi_error - 1:saves \(\psi_{error}\), 0: do not saves \(\psi_{error}\) (default)
.flag_time - 1: saves \(\psi_{error}\), 0: do not saves \(\psi_{error}\) (default)
.Stopping_Crit - stopping criterion:
stop if \(||nfxk|| \leq \epsilon\)
stop if MaxNumIter is reached
stop if MaxNumMapEval is reached
stop if TimeLimit is reached
stop if (default) \(||hxk|| \leq \epsilon\) or MaxNumIter is reached
- OUTPUTS
x_best – the best approximation of the optimizer
psi_best – the best approximation of the optimum
out – structure including more output information
.T - running time
.Niter - total number of iterations
.Nmap - total number of mapping evaluations
.merit_func - array including all merit function values
.x_error - relative error \(\textrm{norm}(x_k(:)-x_{opt}(:))/\textrm{norm}(x_{opt})\)
.psi_error - relative error \((\psi_k-\psi_{opt})/(\psi_0-\psi_{opt}))\)
.Status - reason of termination
- DCA(mapp, x0, options)[source]¶
DCA is a derivative-free algorithm for solving systems of nonlinear equations \(f(x) = 0\), x in \(R^m\) using the nonlinear unconstrained minimization \(min psi(x) = 1/2 ||f(x)||^2\) s.t. x in \(R^m\).
- USAGE
[x_best,psi_best,out] = DCA (mapp, x0, options)
- INPUTS
mapp – function handle provides f(x) and gradient f(x)
x0 – initial point
options – structure including the parameteres of scheme
.MaxNumIter - maximum number of iterations
.MaxNumMapEval - maximum number of function evaluations
.TimeLimit - maximum running time
.epsilon - accuracy parameter
.x_opt - optimizer
.psi_opt - optimum
.alpha - constant for the line searche
.beta - backtarcking constant
.lambda_bar - starting step-size for the line search
.rho - strong convexity parameter
.kin - kinetic parameter in \(R^{2n}\)
.flag_line_search - “Armijo” or “Quadratic_interpolation”
.flag_x_error - 1: saves \(x_{error}\), 0: do not saves \(x_{error}\) (default)
.flag_psi_error - 1:saves \(\psi_{error}\), 0: do not saves \(\psi_{error}\) (default)
.flag_time - 1: saves \(\psi_{error}\), 0: do not saves \(psi_{error}\) (default)
.Stopping_Crit - stopping criterion:
stop if \(||nfxk|| \leq \epsilon\)
stop if MaxNumIter is reached
stop if MaxNumMapEval is reached
stop if TimeLimit is reached
stop if (default) \(||hxk|| \leq \epsilon\) or MaxNumIter is reached
- OUTPUTS
x_best – the best approximation of the optimizer
psi_best – the best approximation of the optimum
out – structure including more output information
.T - running time
.Niter - total number of iterations
.Nmap - total number of mapping evaluations
.merit_func - array including all merit function values
.x_error - relative error \(\textrm{norm}(x_k(:)-x_{opt}(:))/\textrm{norm}(x_{opt})\)
.psi_error - relative error \((\psi_k-\psi_{opt})/(\psi_0-\psi_{opt}))\)
.Status - reason of termination
- FuncGradHessSub(x, y, F, R, kin, rho)[source]¶
SubGradHess provides the function value, the gradient, and the Hessian of the subproblem of DCA and BDCA to be used in fminunc.
- USAGE
[func, grad, Hess] = FuncGradHessSub (x, y, F, R, kin, rho)
- INPUTS
x,y – points
F – Forward stoichiometric matrix
kin – kinetics parameter in \(R^{2n}\)
rho – strongly comvex modulus
- OUTPUTS
f – function value
grad – gradient
H – Hessian
- InitialBDCA(options)[source]¶
InitialBDCA is a function for initializing the parameters of BDCA and DCA. If some parameters specified by the user InitialDuplo uses these parameters. Otherwise, the default values will be used.
- INPUTS
options – structure including the parameteres of scheme
.MaxNumIter - maximum number of iterations
.MaxNumMapEval - maximum number of function evaluations
.TimeLimit - maximum running time
.epsilon - accuracy parameter
.x_opt - optimizer
.psi_opt - optimum
.alpha - constant for the line searche
.beta - backtarcking constant
.lambda_bar - starting step-size for the line search
.rho - strong convexity parameter
.kin - kinetic parameter in \(R^{2n}\)
.flag_line_search - “Armijo” or “Quadratic_interpolation”
.flag_x_error - 1: saves \(x_{error}\), 0: do not saves \(x_{error}\) (default)
.flag_psi_error - 1:saves \(\psi_{error}\), 0: do not saves \(\psi_{error}\) (default)
.flag_time - 1: saves \(\psi_{error}\), 0: do not saves \(\psi_{error}\) (default)
.Stopping_Crit - stopping criterion:
stop if \(||nfxk|| \leq \epsilon\)
stop if MaxNumIter is reached
stop if MaxNumMapEval is reached
stop if TimeLimit is reached
stop if (default) \(||hxk|| \leq \epsilon\) or MaxNumIter is reached
- OUTPUTS
MaxNumIter – maximum number of iterations
MaxNumMapEval – maximum number of function evaluations
TimeLimit – maximum running time
epsilon – accuracy parameter
x_opt – optimizer
psi_opt – optimum
alpha – constant for the line search
beta – backtracking constant
lambda_bar – starting step-size for the line search
flag_x_error – 1: saves \(x_{error}\), 0: do not saves \(x_{error}\) (default)
flag_psi_error – 1: saves \(\psi_{error}\), 0: do not saves \(\psi_{error}\) (default)
flag_time – 1: saves \(\psi_{error}\), 0: do not saves \(\psi_{error}\) (default)
Stopping_Crit – stopping criterion
- Rate_function(opt, varargin)[source]¶
- USAGE
fxk = Rate_function (opt, varargin)
- INPUTS
xk – current point;
opt – structure includes required parameters:
.FR - concatenation of forward and reverse stoichiometric matrix
.A - Reduced forward stoichiometric matrix
.B - Reduced reverse stoichiometric matrix
.k - initial kinetic
- OUTPUT
fxk
- StopCritBDCA(nfxk, Niter, Nmap, T, MaxNumIter, MaxNumMapEval, TimeLimit, epsilon, Stopping_Crit)[source]¶
Function checking that one of the stopping criteria holds to terminate LLM and GLM. It perepare the status determining why the algorithm is stopped.
- USAGE
[StopFlag, Status] = StopCritBDCA (nfxk, Niter, Nmap, T, MaxNumIter, MaxNumMapEval, TimeLimit, epsilon, Stopping_Crit)
- INPUTS
nhxk – the norm 2 of h(xk)
Niter – the number of iterations
Nmap – the number of mapping calls
T – the running time
MaxNumIter – maximum number of iterations
MaxNumMapEval – maximum number of function evaluations
TimeLimit – maximum running time
epsilon – accuracy parameter
Stopping_Crit – stopping criterion:
stop if \(||nfxk|| \leq \epsilon\)
stop if MaxNumIter is reached
stop if MaxNumMapEval is reached
stop if TimeLimit is reached
stop if (default) \(||hxk|| \leq \epsilon\) or MaxNumIter is reached
- OUTPUTS
StopFlag – 1: if one of the stopping criteria holds, 0: if none of the stopping criteria holds
Status – the reason of the scheme termination