/usr/share/octave/packages/optim-1.3.0/minimize.m is in octave-optim 1.3.0-1.
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##
## This program is free software; you can redistribute it and/or modify it under
## the terms of the GNU General Public License as published by the Free Software
## Foundation; either version 3 of the License, or (at your option) any later
## version.
##
## This program is distributed in the hope that it will be useful, but WITHOUT
## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
## details.
##
## You should have received a copy of the GNU General Public License along with
## this program; if not, see <http://www.gnu.org/licenses/>.
## [x,v,nev,...] = minimize (f,args,...) - Minimize f
##
## ARGUMENTS
## f : string : Name of function. Must return a real value
## args : list or : List of arguments to f (by default, minimize the first)
## matrix : f's only argument
##
## RETURNED VALUES
## x : matrix : Local minimum of f. Let's suppose x is M-by-N.
## v : real : Value of f in x0
## nev : integer : Number of function evaluations
## or 1 x 2 : Number of function and derivative evaluations (if
## derivatives are used)
##
##
## Extra arguments are either a succession of option-value pairs or a single
## list or struct of option-value pairs (for unary options, the value in the
## struct is ignored).
##
## OPTIONS : DERIVATIVES Derivatives may be used if one of these options
## --------------------- uesd. Otherwise, the Nelder-Mean (see
## nelder_mead_min) method is used.
##
## 'd2f', d2f : Name of a function that returns the value of f, of its
## 1st and 2nd derivatives : [fx,dfx,d2fx] = feval (d2f, x)
## where fx is a real number, dfx is 1x(M*N) and d2fx is
## (M*N)x(M*N). A Newton-like method (d2_min) will be used.
##
## 'hess' : Use [fx,dfx,d2fx] = leval (f, args) to compute 1st and
## 2nd derivatives, and use a Newton-like method (d2_min).
##
## 'd2i', d2i : Name of a function that returns the value of f, of its
## 1st and pseudo-inverse of second derivatives :
## [fx,dfx,id2fx] = feval (d2i, x) where fx is a real
## number, dfx is 1x(M*N) and d2ix is (M*N)x(M*N).
## A Newton-like method will be used (see d2_min).
##
## 'ihess' : Use [fx,dfx,id2fx] = leval (f, args) to compute 1st
## derivative and the pseudo-inverse of 2nd derivatives,
## and use a Newton-like method (d2_min).
##
## NOTE : df, d2f or d2i take the same arguments as f.
##
## 'order', n : Use derivatives of order n. If the n'th order derivative
## is not specified by 'df', 'd2f' or 'd2i', it will be
## computed numerically. Currently, only order 1 works.
##
## 'ndiff' : Use a variable metric method (bfgs) using numerical
## differentiation.
##
## OPTIONS : STOPPING CRITERIA Default is to use 'tol'
## ---------------------------
## 'ftol', ftol : Stop search when value doesn't improve, as tested by
##
## ftol > Deltaf/max(|f(x)|,1)
##
## where Deltaf is the decrease in f observed in the last
## iteration. Default=10*eps
##
## 'utol', utol : Stop search when updates are small, as tested by
##
## tol > max { dx(i)/max(|x(i)|,1) | i in 1..N }
##
## where dx is the change in the x that occured in the last
## iteration.
##
## 'dtol',dtol : Stop search when derivatives are small, as tested by
##
## dtol > max { df(i)*max(|x(i)|,1)/max(v,1) | i in 1..N }
##
## where x is the current minimum, v is func(x) and df is
## the derivative of f in x. This option is ignored if
## derivatives are not used in optimization.
##
## MISC. OPTIONS
## -------------
## 'maxev', m : Maximum number of function evaluations <inf>
##
## 'narg' , narg : Position of the minimized argument in args <1>
## 'isz' , step : Initial step size (only for 0 and 1st order method) <1>
## Should correspond to expected distance to minimum
## 'verbose' : Display messages during execution
##
## 'backend' : Instead of performing the minimization itself, return
## [backend, control], the name and control argument of the
## backend used by minimize(). Minimimzation can then be
## obtained without the overhead of minimize by calling, if
## a 0 or 1st order method is used :
##
## [x,v,nev] = feval (backend, args, control)
##
## or, if a 2nd order method is used :
##
## [x,v,nev] = feval (backend, control.d2f, args, control)
function [x,v,nev,varargout] = minimize (f,args,varargin)
## Oldies
##
## 'df' , df : Name of a function that returns the derivatives of f
## in x : dfx = feval (df, x) where dfx is 1x(M*N). A
## variable metric method (see bfgs) will be used.
##
## 'jac' : Use [fx, dfx] = leval(f, args) to compute derivatives
## and use a variable metric method (bfgs).
##
# ####################################################################
# Read the options ###################################################
# ####################################################################
# Options with a value
op1 = "ftol utol dtol df d2f d2i order narg maxev isz";
# Boolean options
op0 = "verbose backend jac hess ihess ndiff" ;
default = struct ("backend",0,"verbose",0,...
"df","", "df", "","d2f","","d2i","", ...
"hess", 0, "ihess", 0, "jac", 0,"ndiff", 0, ...
"ftol" ,nan, "utol",nan, "dtol", nan,...
"order",nan, "narg",nan, "maxev",nan,...
"isz", nan);
if nargin == 3 # Accomodation to struct and list optional
tmp = varargin{1};
if isstruct (tmp)
opls = {};
for [v,k] = tmp # Treat separately unary and binary opts
if findstr ([" ",k," "],op0)
opls (end+1) = {k}; # append k
else
opls (end+[1:2]) = {k, v}; # append k and v
end
end
elseif iscell (tmp)
opls = tmp;
else
opls = {tmp};
end
else
opls = varargin;
end
ops = read_options (opls,...
"op0",op0, "op1",op1, "default",default);
backend=ops.backend; verbose=ops.verbose;
df=ops.df; d2f=ops.d2f; d2i=ops.d2i;
hess=ops.hess; ihess=ops.ihess; jac=ops.jac;
ftol=ops.ftol; utol=ops.utol; dtol=ops.dtol;
order=ops.order; narg=ops.narg; maxev=ops.maxev;
isz=ops.isz; ndiff=ops.ndiff;
if length (df), error ("Option 'df' doesn't exist any more. Sorry.\n");end
if jac, error ("Option 'jac' doesn't exist any more. Sorry.\n");end
# Basic coherence checks #############
ws = ""; # Warning string
es = ""; # Error string
# Warn if more than 1 differential is given
if !!length (df) + !!length (d2f) + !!length (d2i) + jac + hess + ihess + ...
ndiff > 1
# Order of preference of
if length (d2i), ws = [ws,"d2i='",d2i,"', "]; end
if length (d2f), ws = [ws,"d2f='",d2f,"', "]; end
if length (df), ws = [ws,"df='",df,"', "]; end
if hess , ws = [ws,"hess, "]; end
if ihess , ws = [ws,"ihess, "]; end
if jac , ws = [ws,"jac, "]; end
if ndiff , ws = [ws,"ndiff, "]; end
ws = ws(1:length(ws)-2);
ws = ["Options ",ws," were passed. Only one will be used\n"]
end
# Check that enough args are passed to call
# f(), unless backend is specified, in which
# case I don't need to call f()
if ! isnan (narg) && ! backend
if narg > 1
es = [es,sprintf("narg=%i, but a single argument was passed\n",narg)];
end
end
if length (ws), warn (ws); end
if length (es), error (es); end # EOF Basic coherence checks #########
op = 0; # Set if any option is passed and should be
# passed to backend
if ! isnan (ftol) , ctls.ftol = ftol; op = 1; end
if ! isnan (utol) , ctls.utol = utol; op = 1; end
if ! isnan (dtol) , ctls.dtol = dtol; op = 1; end
if ! isnan (maxev) , ctls.maxev = maxev; op = 1; end
if ! isnan (narg) , ctls.narg = narg; op = 1; end
if ! isnan (isz) , ctls.isz = isz; op = 1; end
if verbose , ctls.verbose = 1; op = 1; end
# defaults That are used in this function :
if isnan (narg), narg = 1; end
# ##########################################
# Choose one optimization method ###########
# Choose according to available derivatives
if ihess, d2f = f; ctls.id2f = 1; op = 1;
elseif hess, d2f = f;
end
if length (d2i), method = "d2_min"; ctls.id2f = 1; op = 1; d2f = d2i;
elseif length (d2f), method = "d2_min";
### elseif length (df) , method = "bfgsmin"; ctls.df = df; op = 1;
### elseif jac , method = "bfgsmin"; ctls.jac = 1 ; op = 1;
## else method = "nelder_mead_min";
## end
# Choose method because ndiff is passed ####
elseif ndiff , method = "bfgsmin";
# Choose method by specifying order ########
elseif ! isnan (order)
if order == 0, method = "nelder_mead_min";
elseif order == 1
method = "bfgsmin";
elseif order == 2
if ! (length (d2f) || length (d2i))
error ("minimize(): 'order' is 2, but 2nd differential is missing\n");
end
else
error ("minimize(): 'order' option only implemented for order<=2\n");
end
else # Default is nelder_mead_min
method = "nelder_mead_min";
end # EOF choose method ########################
if verbose
printf ("minimize(): Using '%s' as back-end\n",method);
end
# More checks ##############################
ws = "";
if !isnan (isz) && strcmp (method,"d2_min")
ws = [ws,"option 'isz' is passed to method that doesn't use it"];
end
if length (ws), warn (ws); end
# EOF More checks ##########################
if strcmp (method, "d2_min"), all_args = {f, d2f, args};
elseif strcmp (method, "bfgsmin"),all_args = {f, args};
else all_args = {f, args};
end
# Eventually add ctls to argument list
if op, all_args{end+1} = ctls; end
if ! backend # Call the backend ###################
if strcmp (method, "d2_min"),
[x,v,nev,h] = d2_min(all_args{:});
# Eventually return inverse of Hessian
if nargout > 3, varargout{1} = h; vr_val_cnt=2; end
elseif strcmp (method, "bfgsmin")
nev = nan;
if !iscell(args), args = {args}; end
if isnan (ftol), ftol = 1e-12; end # Use bfgsmin's defaults
if isnan (utol), utol = 1e-6; end
if isnan (dtol), dtol = 1e-5; end
if isnan (maxev), maxev = inf; end
[x, v, okcv] = bfgsmin (f, args, {maxev,verbose,1,narg,0,ftol,utol,dtol});
else
[x,v,nev] = feval (method, all_args{:});
end
else # Don't call backend, just return its name
# and arguments.
x = method;
if op, v = ctls; else v = []; end
end
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