## Copyright (C) 2012-2014 Olaf Till <i7tiol@t-online.de>
##
## 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/>.

## -*- texinfo -*-
## @deftypefn {Function File} {[@var{p}, @var{objf}, @var{cvg}, @var{outp}] =} nonlin_min (@var{f}, @var{pin})
## @deftypefnx {Function File} {[@var{p}, @var{objf}, @var{cvg}, @var{outp}] =} nonlin_min (@var{f}, @var{pin}, @var{settings})
## Frontend for nonlinear minimization of a scalar objective function.
##
## The functions supplied by the user have a minimal interface; any
## additionally needed constants can be supplied by wrapping the user
## functions into anonymous functions.
##
## The following description applies to usage with vector-based
## parameter handling. Differences in usage for structure-based
## parameter handling will be explained separately.
##
## @var{f}: objective function. It gets a column vector of real
## parameters as argument. In gradient determination, this function may
## be called with an informational second argument, whose content
## depends on the function for gradient determination.
##
## @var{pin}: real column vector of initial parameters.
##
## @var{settings}: structure whose fields stand for optional settings
## referred to below. The fields can be set by @code{optimset()}.
##
## The returned values are the column vector of final parameters
## @var{p}, the final value of the objective function @var{objf}, an
## integer @var{cvg} indicating if and how optimization succeeded or
## failed, and a structure @var{outp} with additional information,
## curently with possible fields: @code{niter}, the number of
## iterations, @code{nobjf}, the number of objective function calls
## (indirect calls by gradient function not counted), @code{lambda}, the
## lambda of constraints at the result, and @code{user_interaction},
## information on user stops (see settings). The backend may define
## additional fields. @var{cvg} is greater than zero for success and
## less than or equal to zero for failure; its possible values depend on
## the used backend and currently can be @code{0} (maximum number of
## iterations exceeded), @code{1} (success without further specification
## of criteria), @code{2} (parameter change less than specified
## precision in two consecutive iterations), @code{3} (improvement in
## objective function less than specified), @code{-1} (algorithm aborted
## by a user function), or @code{-4} (algorithm got stuck).
##
## @c The following block will be cut out in the package info file.
## @c BEGIN_CUT_TEXINFO
##
## For settings, type @code{optim_doc ("nonlin_min")}.
##
## For desription of structure-based parameter handling, type
## @code{optim_doc ("parameter structures")}.
##
## For description of individual backends (currently only one), type
## @code{optim_doc ("scalar optimization")} and choose the backend in
## the menu.
##
## @c END_CUT_TEXINFO
##
## @end deftypefn

## PKG_ADD: __all_opts__ ("nonlin_min");

function [p, objf, cvg, outp] = nonlin_min (f, pin, settings)

  ## some scalar defaults; some defaults are backend specific, so
  ## lacking elements in respective constructed vectors will be set to
  ## NA here in the frontend
  diffp_default = .001;
  stol_default = .0001;
  cstep_default = 1e-20;

  if (nargin == 1 && ischar (f) && strcmp (f, "defaults"))
    p = optimset ("param_config", [], ...
		  "param_order", [], ...
		  "param_dims", [], ...
		  "f_inequc_pstruct", false, ...
		  "f_equc_pstruct", false, ...
		  "objf_pstruct", false, ...
		  "df_inequc_pstruct", false, ...
		  "df_equc_pstruct", false, ...
		  "grad_objf_pstruct", false, ...
		  "hessian_objf_pstruct", false, ...
		  "lbound", [], ...
		  "ubound", [], ...
		  "objf_grad", [], ...
		  "objf_hessian", [], ...
                  "inverse_hessian", false, ...
		  "cpiv", @ cpiv_bard, ...
		  "max_fract_change", [], ...
		  "fract_prec", [], ... # vector, TolX is a scalar
		  "diffp", [], ...
		  "diff_onesided", [], ...
		  "complex_step_derivative_objf", false, ...
		  "complex_step_derivative_inequc", false, ...
		  "complex_step_derivative_equc", false, ...
		  "cstep", cstep_default, ...
		  "fixed", [], ...
		  "inequc", [], ...
		  "equc", [], ...
                  "f_inequc_idx", false, ...
                  "df_inequc_idx", false, ...
                  "f_equc_idx", false, ...
                  "df_equc_idx", false, ...
		  "TolFun", stol_default, ...
                  "TolX", [], ...
		  "MaxIter", [], ...
		  "Display", "off", ...
		  "Algorithm", "lm_feasible", ...
                  "parallel_local", false, ... # Matlabs UseParallel
                                # works differently
                  "user_interaction", {}, ...
		  "T_init", .01, ...
		  "T_min", 1.0e-5, ...
		  "mu_T", 1.005, ...
		  "iters_fixed_T", 10, ...
		  "max_rand_step", [], ...
		  "stoch_regain_constr", false, ...
                  "trace_steps", false, ...
                  "siman_log", false, ...
		  "debug", false, ...
                  "FunValCheck", "off", ...
                  "save_state", "", ...
                  "recover_state", "", ...
                  "octave_sqp_tolerance", []);
    return;
  endif

  if (nargin < 2 || nargin > 3)
    print_usage ();
  endif

  if (nargin == 2)
    settings = struct ();
  endif

  if (ischar (f))
    f = str2func (f);
  endif

  if (! (pin_struct = isstruct (pin)))
    if (! isvector (pin) || columns (pin) > 1)
      error ("initial parameters must be either a structure or a column vector");
    endif
  endif

  #### processing of settings and consistency checks

  backend = optimget (settings, "Algorithm", "lm_feasible");
  backend = map_matlab_algorithm_names (backend);
  [backend, path_bounds] = map_backend (backend);
  pconf = optimget (settings, "param_config");
  pord = optimget (settings, "param_order");
  pdims = optimget (settings, "param_dims");
  f_inequc_pstruct = optimget (settings, "f_inequc_pstruct", false);
  f_equc_pstruct = optimget (settings, "f_equc_pstruct", false);
  f_pstruct = optimget (settings, "objf_pstruct", false);
  dfdp_pstruct = optimget (settings, "grad_objf_pstruct", f_pstruct);
  hessian_pstruct = optimget (settings, "hessian_objf_pstruct", f_pstruct);
  df_inequc_pstruct = optimget (settings, "df_inequc_pstruct", ...
				f_inequc_pstruct);
  df_equc_pstruct = optimget (settings, "df_equc_pstruct", ...
			      f_equc_pstruct);
  lbound = optimget (settings, "lbound");
  ubound = optimget (settings, "ubound");
  dfdp = optimget (settings, "objf_grad");
  if (ischar (dfdp)) dfdp = str2func (dfdp); endif
  hessian = optimget (settings, "objf_hessian");
  max_fract_change = optimget (settings, "max_fract_change");
  fract_prec = optimget (settings, "fract_prec");
  diffp = optimget (settings, "diffp");
  diff_onesided = optimget (settings, "diff_onesided");
  fixed = optimget (settings, "fixed");
  do_cstep = optimget (settings, "complex_step_derivative_objf", false);
  cstep = optimget (settings, "cstep", cstep_default);
  if (do_cstep && ! isempty (dfdp))
    error ("both 'complex_step_derivative_objf' and 'objf_grad' are set");
  endif
  do_cstep_inequc = ...
      optimget (settings, "complex_step_derivative_inequc", false);
  do_cstep_equc = optimget (settings, "complex_step_derivative_equc", ...
			    false);
  if (! iscell (user_interaction = ...
                optimget (settings, "user_interaction", {})))
    user_interaction = {user_interaction};
  endif
  max_rand_step = optimget (settings, "max_rand_step");

  any_vector_conf = ! (isempty (lbound) && isempty (ubound) && ...
		       isempty (max_fract_change) && ...
		       isempty (fract_prec) && isempty (diffp) && ...
		       isempty (diff_onesided) && isempty (fixed) && ...
		       isempty (max_rand_step));

  ## collect constraints
  [mc, vc, f_genicstr, df_gencstr, user_df_gencstr] = ...
      __collect_constraints__ (optimget (settings, "inequc"), ...
			       do_cstep_inequc, "inequality constraints");
  [emc, evc, f_genecstr, df_genecstr, user_df_genecstr] = ...
      __collect_constraints__ (optimget (settings, "equc"), ...
			       do_cstep_equc, "equality constraints");
  mc_struct = isstruct (mc);
  emc_struct = isstruct (emc);

  ## correct "_pstruct" settings if functions are not supplied, handle
  ## constraint functions not honoring indices
  if (isempty (dfdp)) dfdp_pstruct = false; endif
  if (isempty (hessian)) hessian_pstruct = false; endif
  if (isempty (f_genicstr))
    f_inequc_pstruct = false;
  elseif (! optimget (settings, "f_inequc_idx", false))
    f_genicstr = @ (p, varargin) apply_idx_if_given ...
        (f_genicstr (p, varargin{:}), varargin{:});
  endif
  if (isempty (f_genecstr))
    f_equc_pstruct = false;
  elseif (! optimget (settings, "f_equc_idx", false))
    f_genecstr = @ (p, varargin) apply_idx_if_given ...
        (f_genecstr (p, varargin{:}), varargin{:});
  endif
  if (user_df_gencstr)
    if (! optimget (settings, "df_inequc_idx", false))
      df_gencstr = @ (varargin) df_gencstr (varargin{:})(varargin{2}, :);
    endif
  else
    df_inequc_pstruct = false;
  endif
  if (user_df_genecstr)
    if (! optimget (settings, "df_equc_idx", false))
      df_genecstr = @ (varargin) df_genecstr (varargin{:})(varargin{2}, :);
    endif
  else
    df_equc_pstruct = false;
  endif

  ## some settings require a parameter order
  if (pin_struct || ! isempty (pconf) || f_inequc_pstruct || ...
      f_equc_pstruct || f_pstruct || dfdp_pstruct || ...
      hessian_pstruct || df_inequc_pstruct || df_equc_pstruct || ...
      mc_struct || emc_struct)
    if (isempty (pord))
      if (pin_struct)
	if (any_vector_conf || ...
	    ! (f_pstruct && ...
	       (f_inequc_pstruct || isempty (f_genicstr)) && ...
	       (f_equc_pstruct || isempty (f_genecstr)) && ...
	       (dfdp_pstruct || isempty (dfdp)) && ...
	       (hessian_pstruct || isempty (hessian)) && ...
	       (df_inequc_pstruct || ! user_df_gencstr) && ...
	       (df_equc_pstruct || ! user_df_genecstr) && ...
	       (mc_struct || isempty (mc)) && ...
	       (emc_struct || isempty (emc))))
	  error ("no parameter order specified and constructing a parameter order from the structure of initial parameters can not be done since not all configuration or given functions are structure based");
	else
	  pord = fieldnames (pin);
	endif
      else
	error ("given settings require specification of parameter order or initial parameters in the form of a structure");
      endif
    endif
    pord = pord(:);
    if (pin_struct && ! all (isfield (pin, pord)))
      error ("some initial parameters lacking");
    endif
    if ((nnames = rows (unique (pord))) < rows (pord))
      error ("duplicate parameter names in 'param_order'");
    endif
    if (isempty (pdims))
      if (pin_struct)
	pdims = cellfun ...
	    (@ size, fields2cell (pin, pord), "UniformOutput", false);
      else
	pdims = num2cell (ones (nnames, 2), 2);
      endif
    else
      pdims = pdims(:);
      if (pin_struct && ...
	  ! all (cellfun (@ (x, y) prod (size (x)) == prod (y), ...
			  struct2cell (pin), pdims)))
	error ("given param_dims and dimensions of initial parameters do not match");
      endif
    endif
    if (nnames != rows (pdims))
      error ("lengths of 'param_order' and 'param_dims' not equal");
    endif
    pnel = cellfun (@ prod, pdims);
    ppartidx = pnel;
    if (any (pnel > 1))
      pnonscalar = true;
      cpnel = num2cell (pnel);
      prepidx = cat (1, cellfun ...
		     (@ (x, n) x(ones (1, n), 1), ...
		      num2cell ((1:nnames).'), cpnel, ...
		      "UniformOutput", false){:});
      epord = pord(prepidx, 1);
      psubidx = cat (1, cellfun ...
		     (@ (n) (1:n).', cpnel, ...
		      "UniformOutput", false){:});
    else
      pnonscalar = false; # some less expensive interfaces later
      prepidx = (1:nnames).';
      epord = pord;
      psubidx = ones (nnames, 1);
    endif
  else
    pord = []; # spares checks for given but not needed
  endif

  if (pin_struct)
    np = sum (pnel);
  else
    np = length (pin);
    if (! isempty (pord) && np != sum (pnel))
      error ("number of initial parameters not correct");
    endif
  endif

  plabels = num2cell (num2cell ((1:np).'));
  if (! isempty (pord))
    plabels = cat (2, plabels, num2cell (epord), ...
		   num2cell (num2cell (psubidx)));
  endif

  ## some useful vectors
  zerosvec = zeros (np, 1);
  NAvec = NA (np, 1);
  Infvec = Inf (np, 1);
  falsevec = false (np, 1);
  sizevec = [np, 1];

  ## collect parameter-related configuration
  if (! isempty (pconf))
    ## use supplied configuration structure

    ## parameter-related configuration is either allowed by a structure
    ## or by vectors
    if (any_vector_conf)
      error ("if param_config is given, its potential items must not \
	  be configured in another way");
    endif

    ## supplement parameter names lacking in param_config
    nidx = ! isfield (pconf, pord);
    pconf = cell2fields ({struct()}(ones (1, sum (nidx))), ...
			 pord(nidx), 2, pconf);

    pconf = structcat (1, fields2cell (pconf, pord){:});

    ## in the following, use reshape with explicit dimensions (instead
    ## of x(:)) so that errors are thrown if a configuration item has
    ## incorrect number of elements

    lbound = - Infvec;
    if (isfield (pconf, "lbound"))
      idx = ! fieldempty (pconf, "lbound");
      if (pnonscalar)
	lbound (idx(prepidx), 1) = ...
	    cat (1, cellfun (@ (x, n) reshape (x, n, 1), ...
			     {pconf(idx).lbound}.', ...
			     cpnel(idx), "UniformOutput", false){:});
      else
	lbound(idx, 1) = cat (1, pconf.lbound);
      endif
    endif

    ubound = Infvec;
    if (isfield (pconf, "ubound"))
      idx = ! fieldempty (pconf, "ubound");
      if (pnonscalar)
	ubound (idx(prepidx), 1) = ...
	    cat (1, cellfun (@ (x, n) reshape (x, n, 1), ...
			     {pconf(idx).ubound}.', ...
			     cpnel(idx), "UniformOutput", false){:});
      else
	ubound(idx, 1) = cat (1, pconf.ubound);
      endif
    endif

    max_fract_change = fract_prec = NAvec;

    if (isfield (pconf, "max_fract_change"))
      idx = ! fieldempty (pconf, "max_fract_change");
      if (pnonscalar)
	max_fract_change(idx(prepidx)) = ...
	    cat (1, cellfun (@ (x, n) reshape (x, n, 1), ...
			     {pconf(idx).max_fract_change}.', ...
			     cpnel(idx), ...
			     "UniformOutput", false){:});
      else
	max_fract_change(idx) = [pconf.max_fract_change];
      endif
    endif

    if (isfield (pconf, "fract_prec"))
      idx = ! fieldempty (pconf, "fract_prec");
      if (pnonscalar)
	fract_prec(idx(prepidx)) = ...
	    cat (1, cellfun (@ (x, n) reshape (x, n, 1), ...
			     {pconf(idx).fract_prec}.', cpnel(idx), ...
			     "UniformOutput", false){:});
      else
	fract_prec(idx) = [pconf.fract_prec];
      endif
    endif

    diffp = zerosvec;
    diffp(:) = diffp_default;
    if (isfield (pconf, "diffp"))
      idx = ! fieldempty (pconf, "diffp");
      if (pnonscalar)
	diffp(idx(prepidx)) = ...
	    cat (1, cellfun (@ (x, n) reshape (x, n, 1), ...
			     {pconf(idx).diffp}.', cpnel(idx), ...
			     "UniformOutput", false){:});
      else
	diffp(idx) = [pconf.diffp];
      endif
    endif

    diff_onesided = fixed = falsevec;

    if (isfield (pconf, "diff_onesided"))
      idx = ! fieldempty (pconf, "diff_onesided");
      if (pnonscalar)
	diff_onesided(idx(prepidx)) = ...
	    logical ...
	    (cat (1, cellfun (@ (x, n) reshape (x, n, 1), ...
			      {pconf(idx).diff_onesided}.', cpnel(idx), ...
			     "UniformOutput", false){:}));
      else
	diff_onesided(idx) = logical ([pconf.diff_onesided]);
      endif
    endif

    if (isfield (pconf, "fixed"))
      idx = ! fieldempty (pconf, "fixed");
      if (pnonscalar)
	fixed(idx(prepidx)) = ...
	    logical ...
	    (cat (1, cellfun (@ (x, n) reshape (x, n, 1), ...
			      {pconf(idx).fixed}.', cpnel(idx), ...
			     "UniformOutput", false){:}));
      else
	fixed(idx) = logical ([pconf.fixed]);
      endif
    endif

    max_rand_step = NAvec;

    if (isfield (pconf, "max_rand_step"))
      idx = ! fieldempty (pconf, "max_rand_step");
      if (pnonscalar)
	max_rand_step(idx(prepidx)) = ...
	    logical ...
	    (cat (1, cellfun (@ (x, n) reshape (x, n, 1), ...
			      {pconf(idx).max_rand_step}.',
			      cpnel(idx), ...
			      "UniformOutput", false){:}));
      else
	max_rand_step(idx) = logical ([pconf.max_rand_step]);
      endif
    endif

  else
    ## use supplied configuration vectors

    if (isempty (lbound))
      lbound = - Infvec;
    elseif (any (size (lbound) != sizevec))
      error ("bounds: wrong dimensions");
    endif

    if (isempty (ubound))
      ubound = Infvec;
    elseif (any (size (ubound) != sizevec))
      error ("bounds: wrong dimensions");
    endif

    if (isempty (max_fract_change))
      max_fract_change = NAvec;
    elseif (any (size (max_fract_change) != sizevec))
      error ("max_fract_change: wrong dimensions");
    endif

    if (isempty (fract_prec))
      fract_prec = NAvec;
    elseif (any (size (fract_prec) != sizevec))
      error ("fract_prec: wrong dimensions");
    endif

    if (isempty (diffp))
      diffp = zerosvec;
      diffp(:) = diffp_default;
    else
      if (any (size (diffp) != sizevec))
	error ("diffp: wrong dimensions");
      endif
      diffp(isna (diffp)) = diffp_default;
    endif

    if (isempty (diff_onesided))
      diff_onesided = falsevec;
    else
      if (any (size (diff_onesided) != sizevec))
	error ("diff_onesided: wrong dimensions")
      endif
      diff_onesided(isna (diff_onesided)) = false;
      diff_onesided = logical (diff_onesided);
    endif

    if (isempty (fixed))
      fixed = falsevec;
    else
      if (any (size (fixed) != sizevec))
	error ("fixed: wrong dimensions");
      endif
      fixed(isna (fixed)) = false;
      fixed = logical (fixed);
    endif

    if (isempty (max_rand_step))
      max_rand_step = NAvec;
    elseif (any (size (max_rand_step) != sizevec))
      error ("max_rand_step: wrong dimensions");
    endif

  endif

  ## guaranty all (lbound <= ubound)
  if (any (lbound > ubound))
    error ("some lower bounds larger than upper bounds");
  endif

  ## pass bounds only if the backend respects bounds even during the
  ## course of optimization
  if (path_bounds)
    jac_lbound = lbound;
    jac_ubound = ubound;
  else
    jac_lbound = - Infvec;
    jac_ubound = Infvec;
  endif


  #### consider whether initial parameters and functions are based on
  #### parameter structures or parameter vectors; wrappers for call to
  #### default function for jacobians

  ## initial parameters
  if (pin_struct)
    if (pnonscalar)
      pin = cat (1, cellfun (@ (x, n) reshape (x, n, 1), ...
			     fields2cell (pin, pord), cpnel, ...
			     "UniformOutput", false){:});
    else
      pin = cat (1, fields2cell (pin, pord){:});
    endif
  endif

  ## objective function
  if (f_pstruct)
    if (pnonscalar)
      f = @ (p, varargin) ...
	  f (cell2struct ...
	     (cellfun (@ reshape, mat2cell (p, ppartidx), ...
		       pdims, "UniformOutput", false), ...
	      pord, 1), varargin{:});
    else
      f = @ (p, varargin) ...
	  f (cell2struct (num2cell (p), pord, 1), varargin{:});
    endif
  endif

  ## gradient of objective function
  if (isempty (dfdp))
    if (do_cstep)
      dfdp = @ (p, hook) jacobs (p, f, hook);
    else
      dfdp = @ (p, hook) __dfdp__ (p, f, hook);
    endif
  endif
  if (dfdp_pstruct)
    if (pnonscalar)
      dfdp = @ (p, hook) ...
	  cat (2, ...
	       fields2cell ...
	       (dfdp (cell2struct ...
		      (cellfun (@ reshape, mat2cell (p, ppartidx), ...
				pdims, "UniformOutput", false), ...
		       pord, 1), hook), ...
		pord){:});
    else
      dfdp = @ (p, hook) ...
	  cat (2, ...
	       fields2cell ...
	       (dfdp (cell2struct (num2cell (p), pord, 1), hook), ...
		pord){:});
    endif
  endif

  ## hessian of objective function
  if (hessian_pstruct)
    if (pnonscalar)
      hessian = @ (p) ...
	  hessian_struct2mat ...
	  (hessian (cell2struct ...
		    (cellfun (@ reshape, mat2cell (p, ppartidx), ...
			      pdims, "UniformOutput", false), ...
		     pord, 1)), pord);
    else
      hessian = @ (p) ...
	  hessian_struct2mat ...
	  (hessian (cell2struct (num2cell (p), pord, 1)), pord);
    endif
  endif

  ## function for general inequality constraints
  if (f_inequc_pstruct)
    if (pnonscalar)
      f_genicstr = @ (p, varargin) ...
	  f_genicstr (cell2struct ...
		      (cellfun (@ reshape, mat2cell (p, ppartidx), ...
				pdims, "UniformOutput", false), ...
		       pord, 1), varargin{:});
    else
      f_genicstr = @ (p, varargin) ...
	  f_genicstr ...
	  (cell2struct (num2cell (p), pord, 1), varargin{:});
    endif
  endif

  ## note this stage
  possibly_pstruct_f_genicstr = f_genicstr;

  ## jacobian of general inequality constraints
  if (df_inequc_pstruct)
    if (pnonscalar)
      df_gencstr = @ (p, func, idx, hook) ...
	  cat (2, ...
	       fields2cell ...
	       (df_gencstr ...
		(cell2struct ...
		 (cellfun (@ reshape, mat2cell (p, ppartidx), ...
			   pdims, "UniformOutput", false), pord, 1), ...
		 func, idx, hook), ...
		pord){:});
    else
      df_gencstr = @ (p, func, idx, hook) ...
	  cat (2, ...
	       fields2cell ...
	       (df_gencstr (cell2struct (num2cell (p), pord, 1), ...
			    func, idx, hook), ...
		pord){:});
    endif
  endif

  ## function for general equality constraints
  if (f_equc_pstruct)
    if (pnonscalar)
      f_genecstr = @ (p, varargin) ...
	  f_genecstr (cell2struct ...
		      (cellfun (@ reshape, mat2cell (p, ppartidx), ...
				pdims, "UniformOutput", false), ...
		       pord, 1), varargin{:});
    else
      f_genecstr = @ (p, varargin) ...
	  f_genecstr ...
	  (cell2struct (num2cell (p), pord, 1), varargin{:});
    endif
  endif

  ## note this stage
  possibly_pstruct_f_genecstr = f_genecstr;

  ## jacobian of general equality constraints
  if (df_equc_pstruct)
    if (pnonscalar)
      df_genecstr = @ (p, func, idx, hook) ...
	  cat (2, ...
	       fields2cell ...
	       (df_genecstr ...
		(cell2struct ...
		 (cellfun (@ reshape, mat2cell (p, ppartidx), ...
			   pdims, "UniformOutput", false), pord, 1), ...
		 func, idx, hook), ...
		pord){:});
    else
      df_genecstr = @ (p, func, idx, hook) ...
	  cat (2, ...
	       fields2cell ...
	       (df_genecstr (cell2struct (num2cell (p), pord, 1), ...
			     func, idx, hook), ...
		pord){:});
    endif
  endif

  ## linear inequality constraints
  if (mc_struct)
    idx = isfield (mc, pord);
    if (rows (fieldnames (mc)) > sum (idx))
      error ("unknown fields in structure of linear inequality constraints");
    endif
    smc = mc;
    mc = zeros (np, rows (vc));
    mc(idx(prepidx), :) = cat (1, fields2cell (smc, pord(idx)){:});
  endif

  ## linear equality constraints
  if (emc_struct)
    idx = isfield (emc, pord);
    if (rows (fieldnames (emc)) > sum (idx))
      error ("unknown fields in structure of linear equality constraints");
    endif
    semc = emc;
    emc = zeros (np, rows (evc));
    emc(idx(prepidx), :) = cat (1, fields2cell (semc, pord(idx)){:});
  endif

  ## parameter-related configuration for jacobian functions
  if (dfdp_pstruct || df_inequc_pstruct || df_equc_pstruct)
    if(pnonscalar)
      s_diffp = cell2struct ...
	  (cellfun (@ reshape, mat2cell (diffp, ppartidx), ...
		    pdims, "UniformOutput", false), pord, 1);
      s_diff_onesided = cell2struct ...
	  (cellfun (@ reshape, mat2cell (diff_onesided, ppartidx), ...
		    pdims, "UniformOutput", false), pord, 1);
      s_jac_lbound = cell2struct ...
	  (cellfun (@ reshape, mat2cell (jac_lbound, ppartidx), ...
		    pdims, "UniformOutput", false), pord, 1);
      s_jac_ubound = cell2struct ...
	  (cellfun (@ reshape, mat2cell (jac_ubound, ppartidx), ...
		    pdims, "UniformOutput", false), pord, 1);
      s_plabels = cell2struct ...
	  (num2cell ...
	   (cat (2, cellfun ...
		 (@ (x) cellfun ...
		  (@ reshape, mat2cell (cat (1, x{:}), ppartidx), ...
		   pdims, "UniformOutput", false), ...
		  num2cell (plabels, 1), "UniformOutput", false){:}), ...
	    2), ...
	   pord, 1);
      s_orig_fixed = cell2struct ...
	  (cellfun (@ reshape, mat2cell (fixed, ppartidx), ...
		    pdims, "UniformOutput", false), pord, 1);
    else
      s_diffp = cell2struct (num2cell (diffp), pord, 1);
      s_diff_onesided = cell2struct (num2cell (diff_onesided), pord, 1);
      s_jac_lbound = cell2struct (num2cell (jac_lbound), pord, 1);
      s_jac_ubound = cell2struct (num2cell (jac_ubound), pord, 1);
      s_plabels = cell2struct (num2cell (plabels, 2), pord, 1);
      s_orig_fixed = cell2struct (num2cell (fixed), pord, 1);
    endif
  endif

  #### some further values and checks

  if (any (fixed & (pin < lbound | pin > ubound)))
    warning ("some fixed parameters outside bounds");
  endif

  if (any (diffp <= 0))
    error ("some elements of 'diffp' non-positive");
  endif

  if (cstep <= 0)
    error ("'cstep' non-positive");
  endif

  if ((hook.TolFun = optimget (settings, "TolFun", stol_default)) < 0)
    error ("'TolFun' negative");
  endif

  if (any (fract_prec < 0))
    error ("some elements of 'fract_prec' negative");
  endif

  if (any (max_fract_change < 0))
    error ("some elements of 'max_fract_change' negative");
  endif

  ## dimensions of linear constraints
  if (isempty (mc))
    mc = zeros (np, 0);
    vc = zeros (0, 1);
  endif
  if (isempty (emc))
    emc = zeros (np, 0);
    evc = zeros (0, 1);
  endif
  [rm, cm] = size (mc);
  [rv, cv] = size (vc);
  if (rm != np || cm != rv || cv != 1)
    error ("linear inequality constraints: wrong dimensions");
  endif
  [erm, ecm] = size (emc);
  [erv, ecv] = size (evc);
  if (erm != np || ecm != erv || ecv != 1)
    error ("linear equality constraints: wrong dimensions");
  endif

  ## note initial values of linear constraits
  pin_cstr.inequ.lin_except_bounds = mc.' * pin + vc;
  pin_cstr.equ.lin = emc.' * pin + evc;

  ## note number and initial values of general constraints
  if (isempty (f_genicstr))
    pin_cstr.inequ.gen = [];
    n_genicstr = 0;
  else
    n_genicstr = length (pin_cstr.inequ.gen = f_genicstr (pin));
  endif
  if (isempty (f_genecstr))
    pin_cstr.equ.gen = [];
    n_genecstr = 0;
  else
    n_genecstr = length (pin_cstr.equ.gen = f_genecstr (pin));
  endif

  #### collect remaining settings
  parallel_local = hook.parallel_local = ...
      __optimget_parallel_local__ (settings, false);
  hook.MaxIter = optimget (settings, "MaxIter");
  if (ischar (hook.cpiv = optimget (settings, "cpiv", @ cpiv_bard)))
    hook.cpiv = str2func (hook.cpiv);
  endif
  hook.Display = optimget (settings, "Display", "off");
  hook.testing = optimget (settings, "debug", false);
  hook.siman.T_init = optimget (settings, "T_init", .01);
  hook.siman.T_min = optimget (settings, "T_min", 1.0e-5);
  hook.siman.mu_T = optimget (settings, "mu_T", 1.005);
  hook.siman.iters_fixed_T = optimget (settings, "iters_fixed_T", 10);
  hook.stoch_regain_constr = ...
      optimget (settings, "stoch_regain_constr", false);
  hook.trace_steps = ...
      optimget (settings, "trace_steps", false);
  hook.siman_log = ...
      optimget (settings, "siman_log", false);
  hook.save_state = optimget (settings, "save_state", "");
  hook.recover_state = optimget (settings, "recover_state", "");
  hook.octave_sqp_tolerance = ...
      optimget (settings, "octave_sqp_tolerance", []);
  hook.inverse_hessian = optimget (settings, "inverse_hessian", false);
  hook.TolX = optimget (settings, "TolX", []);
  hook.FunValCheck = optimget (settings, "FunValCheck", "off");

  #### handle fixing of parameters
  orig_fixed = fixed;
  if (all (fixed))
    error ("no free parameters");
  endif

  nonfixed = ! fixed;
  if (any (fixed))
    ## backend (returned values and initial parameters)
    backend = @ (f, pin, hook) ...
	backend_wrapper (backend, fixed, f, pin, hook);

    ## objective function
    f = @ (p, varargin) f (assign (pin, nonfixed, p), varargin{:});

    ## gradient of objective function
    dfdp = @ (p, hook) ...
	dfdp (assign (pin, nonfixed, p), hook)(nonfixed);

    ## hessian of objective function
    if (! isempty (hessian))
      hessian = @ (p) ...
	  hessian (assign (pin, nonfixed, p))(nonfixed, nonfixed);
    endif
    
    ## function for general inequality constraints
    f_genicstr = @ (p, varargin) ...
	f_genicstr (assign (pin, nonfixed, p), varargin{:});
    
    ## jacobian of general inequality constraints
    df_gencstr = @ (p, func, idx, hook) ...
	df_gencstr (assign (pin, nonfixed, p), func, idx, hook) ...
	(:, nonfixed);

    ## function for general equality constraints
    f_genecstr = @ (p, varargin) ...
	f_genecstr (assign (pin, nonfixed, p), varargin{:});

    ## jacobian of general equality constraints
    df_genecstr = @ (p, func, idx, hook) ...
	df_genecstr (assign (pin, nonfixed, p), func, idx, hook) ...
	(:, nonfixed);

    ## linear inequality constraints
    vc += mc(fixed, :).' * (tp = pin(fixed));
    mc = mc(nonfixed, :);

    ## linear equality constraints
    evc += emc(fixed, :).' * tp;
    emc = emc(nonfixed, :);

    ## _last_ of all, vectors of parameter-related configuration,
    ## including "fixed" itself
    lbound = lbound(nonfixed, :);
    ubound = ubound(nonfixed, :);
    max_fract_change = max_fract_change(nonfixed);
    fract_prec = fract_prec(nonfixed);
    max_rand_step = max_rand_step(nonfixed);
    fixed = fixed(nonfixed);
  endif

  #### supplement constants to jacobian functions

  ## gradient of objective function
  if (dfdp_pstruct)
    dfdp = @ (p, hook) ...
	dfdp (p, cell2fields ...
	      ({s_diffp, s_diff_onesided, s_jac_lbound, ...
		s_jac_ubound, s_plabels, ...
		cell2fields(num2cell(hook.fixed), pord(nonfixed), ...
			    1, s_orig_fixed), ...
                cstep, parallel_local}, ...
	       {"diffp", "diff_onesided", "lbound", "ubound", ...
		"plabels", "fixed", "h", "parallel_local"}, ...
	       2, hook));
  else
    dfdp = @ (p, hook) ...
	dfdp (p, cell2fields ...
	      ({diffp, diff_onesided, jac_lbound, jac_ubound, ...
		plabels, assign(orig_fixed, nonfixed, hook.fixed), ...
		cstep, parallel_local}, ...
	       {"diffp", "diff_onesided", "lbound", "ubound", ...
		"plabels", "fixed", "h", "parallel_local"}, ...
	       2, hook));
  endif

  ## jacobian of general inequality constraints
  if (df_inequc_pstruct)
    df_gencstr = @ (p, func, idx, hook) ...
	df_gencstr (p, func, idx, cell2fields ...
		    ({s_diffp, s_diff_onesided, s_jac_lbound, ...
		      s_jac_ubound, s_plabels, ...
		      cell2fields(num2cell(hook.fixed), pord(nonfixed), ...
				  1, s_orig_fixed), ...
                      cstep, parallel_local}, ...
		     {"diffp", "diff_onesided", "lbound", "ubound", ...
		      "plabels", "fixed", "h", "parallel_local"}, ...
		     2, hook));
  else
    df_gencstr = @ (p, func, idx, hook) ...
	df_gencstr (p, func, idx, cell2fields ...
		    ({diffp, diff_onesided, jac_lbound, ...
		      jac_ubound, plabels, ...
		      assign(orig_fixed, nonfixed, hook.fixed), ...
                      cstep, parallel_local}, ...
		     {"diffp", "diff_onesided", "lbound", "ubound", ...
		      "plabels", "fixed", "h", "parallel_local"}, ...
		     2, hook));
  endif

  ## jacobian of general equality constraints
  if (df_equc_pstruct)
    df_genecstr = @ (p, func, idx, hook) ...
	df_genecstr (p, func, idx, cell2fields ...
		     ({s_diffp, s_diff_onesided, s_jac_lbound, ...
		       s_jac_ubound, s_plabels, ...
		       cell2fields(num2cell(hook.fixed), pord(nonfixed), ...
				   1, s_orig_fixed), ...
                       cstep, parallel_local}, ...
		      {"diffp", "diff_onesided", "lbound", "ubound", ...
		       "plabels", "fixed", "h", "parallel_local"}, ...
		      2, hook));
  else
    df_genecstr = @ (p, func, idx, hook) ...
	df_genecstr (p, func, idx, cell2fields ...
		     ({diffp, diff_onesided, jac_lbound, ...
		       jac_ubound, plabels, ...
		       assign(orig_fixed, nonfixed, hook.fixed), ...
                       cstep, parallel_local}, ...
		      {"diffp", "diff_onesided", "lbound", "ubound", ...
		       "plabels", "fixed", "h", "parallel_local"}, ...
		      2, hook));
  endif

  #### interfaces to constraints
  
  ## include bounds into linear inequality constraints
  tp = eye (sum (nonfixed));
  lidx = lbound != - Inf;
  uidx = ubound != Inf;
  mc = cat (2, tp(:, lidx), - tp(:, uidx), mc);
  vc = cat (1, - lbound(lidx, 1), ubound(uidx, 1), vc);

  ## concatenate linear inequality and equality constraints
  mc = cat (2, mc, emc);
  vc = cat (1, vc, evc);
  n_lincstr = rows (vc);

  ## concatenate general inequality and equality constraints
  if (n_genecstr > 0)
    if (n_genicstr > 0)
      nidxi = 1 : n_genicstr;
      nidxe = n_genicstr + 1 : n_genicstr + n_genecstr;
      f_gencstr = @ (p, idx, varargin) ...
	  cat (1, ...
	       f_genicstr (p, idx(nidxi), varargin{:}), ...
	       f_genecstr (p, idx(nidxe), varargin{:}));
      df_gencstr = @ (p, idx, hook) ...
	  cat (1, ...
	       df_gencstr (p, @ (p, varargin) ...
			   possibly_pstruct_f_genicstr ...
			   (p, idx(nidxi), varargin{:}), ...
			   idx(nidxi), ...
			   setfield (hook, "f", ...
				     hook.f(nidxi(idx(nidxi))))), ...
	       df_genecstr (p, @ (p, varargin) ...
			    possibly_pstruct_f_genecstr ...
			    (p, idx(nidxe), varargin{:}), ...
			    idx(nidxe), ...
			    setfield (hook, "f", ...
				      hook.f(nidxe(idx(nidxe))))));
    else
      f_gencstr = f_genecstr;
      df_gencstr = @ (p, idx, hook) ...
	  df_genecstr (p, ...
		       @ (p, varargin) ...
		       possibly_pstruct_f_genecstr ...
		       (p, idx, varargin{:}), ...
		       idx, ...
		       setfield (hook, "f", hook.f(idx)));
    endif
  else
    f_gencstr = f_genicstr;
    df_gencstr = @ (p, idx, hook) ...
	df_gencstr (p, ...
		    @ (p, varargin) ...
		    possibly_pstruct_f_genicstr (p, idx, varargin{:}), ...
		    idx, ...
		    setfield (hook, "f", hook.f(idx)));
  endif    
  n_gencstr = n_genicstr + n_genecstr;

  ## concatenate linear and general constraints, defining the final
  ## function interfaces
  if (n_gencstr > 0)
    nidxl = 1:n_lincstr;
    nidxh = n_lincstr + 1 : n_lincstr + n_gencstr;
    f_cstr = @ (p, idx, varargin) ...
	cat (1, ...
	     mc(:, idx(nidxl)).' * p + vc(idx(nidxl), 1), ...
	     f_gencstr (p, idx(nidxh), varargin{:}));
    df_cstr = @ (p, idx, hook) ...
	cat (1, ...
	     mc(:, idx(nidxl)).', ...
	     df_gencstr (p, idx(nidxh), ...
			 setfield (hook, "f", ...
				   hook.f(nidxh))));
  else
    f_cstr = @ (p, idx, varargin) mc(:, idx).' * p + vc(idx, 1);
    df_cstr = @ (p, idx, hook) mc(:, idx).';
  endif

  ## define eq_idx (logical index of equality constraints within all
  ## concatenated constraints
  eq_idx = false (n_lincstr + n_gencstr, 1);
  eq_idx(n_lincstr + 1 - rows (evc) : n_lincstr) = true;
  n_cstr = n_lincstr + n_gencstr;
  eq_idx(n_cstr + 1 - n_genecstr : n_cstr) = true;

  #### prepare interface hook

  ## passed constraints
  hook.mc = mc;
  hook.vc = vc;
  hook.f_cstr = f_cstr;
  hook.df_cstr = df_cstr;
  hook.n_gencstr = n_gencstr;
  hook.eq_idx = eq_idx;
  hook.lbound = lbound;
  hook.ubound = ubound;

  ## passed values of constraints for initial parameters
  hook.pin_cstr = pin_cstr;

  ## passed function for gradient of objective function
  hook.dfdp = dfdp;

  ## passed function for hessian of objective function
  hook.hessian = hessian;

  ## passed function for complementary pivoting
  ## hook.cpiv = cpiv; # set before

  ## passed options
  hook.max_fract_change = max_fract_change;
  hook.fract_prec = fract_prec;
  ## hook.TolFun = ; # set before
  ## hook.MaxIter = ; # set before
  hook.fixed = fixed;
  hook.user_interaction = user_interaction;
  hook.max_rand_step = max_rand_step;

  #### call backend

  [p, objf, cvg, outp] = backend (f, pin, hook);

  if (pin_struct)
    if (pnonscalar)
      p = cell2struct ...
	  (cellfun (@ reshape, mat2cell (p, ppartidx), ...
		    pdims, "UniformOutput", false), ...
	   pord, 1);
    else
      p = cell2struct (num2cell (p), pord, 1);
    endif
  endif

endfunction

function backend = map_matlab_algorithm_names (backend)

  ## nothing done here at the moment

endfunction

function [backend, path_bounds] = map_backend (backend)

  switch (backend)
      ##    case "sqp_infeasible"
      ##      backend = "__sqp__";
      ##    case "sqp"
      ##      backend = "__sqp__";
    case "lm_feasible"
      backend = "__lm_feasible__";
      path_bounds = true;
    case "octave_sqp"
      backend = "__octave_sqp_wrapper__";
      path_bounds = false;
    case "siman"
      backend = "__siman__";
      path_bounds = true;
    case "d2_min"
      backend = "__d2_min__";
      path_bounds = false;
    otherwise
      error ("no backend implemented for algorithm '%s'", backend);
  endswitch

  backend = str2func (backend);

endfunction

function [p, resid, cvg, outp] = backend_wrapper (backend, fixed, f, p, hook)

  [tp, resid, cvg, outp] = backend (f, p(! fixed), hook);

  p(! fixed) = tp;

endfunction

function lval = assign (lval, lidx, rval)

  lval(lidx) = rval;

endfunction

function m = hessian_struct2mat (s, pord)

  m = cell2mat (fields2cell ...
		(structcat (1, NA, fields2cell (s, pord){:}), pord));

  idx = isna (m);

  m(idx) = (m.')(idx);

endfunction

function ret = apply_idx_if_given  (ret, varargin)

  if (nargin > 1)
    ret = ret(varargin{1});
  endif

endfunction

%!demo
%! ## Example for default optimization (Levenberg/Marquardt with
%! ## BFGS), one non-linear equality constraint. Constrained optimum is
%! ## at p = [0; 1].
%! objective_function = @ (p) p(1)^2 + p(2)^2;
%! pin = [-2; 5];
%! constraint_function = @ (p) p(1)^2 + 1 - p(2);
%! [p, objf, cvg, outp] = nonlin_min (objective_function, pin, optimset ("equc", {constraint_function}))

%!demo
%! ## Example for simulated annealing, two parameters, "trace_steps"
%! ## is true;
%! t_init = .2;
%! t_min = .002;
%! mu_t = 1.002;
%! iters_fixed_t = 10;
%! init_p = [2; 2];
%! max_rand_step = [.2; .2];
%! [p, objf, cvg, outp] = nonlin_min (@ (p) (p(1)/10)^2 + (p(2)/10)^2 + .1 * (-cos(4*p(1)) - cos(4*p(2))), init_p, optimset ("algorithm", "siman", "max_rand_step", max_rand_step, "t_init", t_init, "T_min", t_min, "mu_t", mu_t, "iters_fixed_T", iters_fixed_t, "trace_steps", true));
%! p
%! objf
%! x = (outp.trace(:, 1) - 1) * iters_fixed_t + outp.trace(:, 2);
%! x(1) = 0;
%! plot (x, cat (2, outp.trace(:, 3:end), t_init ./ (mu_t .^ outp.trace(:, 1))))
%! legend ({"objective function value", "p(1)", "p(2)", "Temperature"})
%! xlabel ("subiteration")