annotate m-toolbox/classes/@matrix/linearize.m @ 40:977eb37f31cb database-connection-manager

User friendlier errors from utils.mysql.connect
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 18:04:03 +0100
parents f0afece42f48
children
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % LINEARIZE output the derivatives of the model relative to the parameters.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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3 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 % DESCRIPTION: LINEARIZE output the derivatives of the model relative to
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % the parameters. Output is a collection of models corresponding to the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % derivative of input model for each parameter
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 % CALL: dmod = linearize(imod)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % <a href="matlab:utils.helper.displayMethodInfo('matrix', 'linearize')">Parameters Description</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % VERSION: $Id: linearize.m,v 1.14 2011/04/08 08:56:31 hewitson Exp $
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13 %
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14 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 function varargout = linearize(varargin)
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16
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17 % utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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18
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 end
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24
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 for ii = 1:nargin
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28 in_names{ii} = inputname(ii);
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29 end
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30
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 % Collect all smodels and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 [as, matrix_invars, rest] = utils.helper.collect_objects(varargin(:), 'matrix', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 [pl, pl_invars, rest] = utils.helper.collect_objects(rest(:), 'plist', in_names);
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34
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35 % Merge with default plist
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 pl = parse(pl, getDefaultPlist);
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37
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 % get parameters and make sure we are working with a cell array
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 pnames = find(pl,'Params');
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40 if isa(pnames, 'char')
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41 pnames = {pnames};
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42 end
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43
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 % decide if sorting
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 sorting = find(pl,'Sorting');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 if sorting
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 pnames = sort(pnames);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 end
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49
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 % loop over input matrices
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 dmod(numel(as),1)=collection;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 for ww=1:numel(as)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 imod=as(ww);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 if strcmpi(class(imod.objs(1)),'smodel')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 % a matrix of smodels is assumed
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 % join params
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57
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 if isempty(pnames) % linearize with respect to all model parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 % store a common set of parameters for mod, it is needed for
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 % the derivative
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 [rw,cl] = size(imod.objs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 % loop over dimensions
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 mpars = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 mvals = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 for aa = 1:rw
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 for bb = 1:cl
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 obj = imod.objs(aa,bb);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 [mpars,id1,id2] = union(mpars,obj.params);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 nom1 = mvals(id1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 nom2 = obj.values(id2);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 mvals = [nom1 nom2];
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72 end
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73 end
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74 for ff = 1:numel(imod.objs)
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75 imod.objs(ff).setParams(mpars,mvals);
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76 end
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77
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78 % it is assumed a common set of parameters for the matrix object
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79 pnames = imod.objs(1).params;
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80 end %isempty(pnames)
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81
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 % get matrix dimension
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 [rw,cl] = size(imod.objs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 % start linearization
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 for ii = 1:numel(pnames)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 tmod = copy(imod,1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 for jj = 1:rw
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 for kk = 1:cl
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 tmod.objs(jj,kk) = diff(imod.objs(jj,kk),pnames{ii}); % do symbolic derivative for smodel
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 tmod.objs(jj,kk).setName(sprintf('d{%s}/d{%s}',imod.objs(jj,kk).name,pnames{ii}));
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92 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 % set the name of the parameter to the matrix, this is important to
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 % identify automatically to what derivatives we are referring
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 tmod.setName(pnames{ii});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 % dmod.addObjects(tmod);
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98 dmod(ww).addObjects(tmod);
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99 end
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100 dmod(ww).setName(sprintf('linearize(%s)',imod.name));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 error('Only matrix of smodels supported at the moment')
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103 end %strcmpi(class(imod.objs(1)),'smodel')
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104
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105 end
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106
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Daniele Nicolodi <nicolodi@science.unitn.it>
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107 if nargout == 1
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Daniele Nicolodi <nicolodi@science.unitn.it>
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108 varargout{1} = dmod;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 elseif nargout == numel(as)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110 % List of outputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111 for ii = 1:numel(as)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112 varargout{ii} = dmod.index(ii);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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114 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 error('Set at least one output value')
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116 end
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117
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118 end
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119
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120 %--------------------------------------------------------------------------
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121 % Get Info Object
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122 %--------------------------------------------------------------------------
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123 function ii = getInfo(varargin)
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124
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126 sets = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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127 pls = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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128 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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129 sets = {'Default'};
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130 pls = getDefaultPlist;
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131 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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133 ii = minfo(mfilename, 'matrix', 'ltpda', utils.const.categories.op, '$Id: linearize.m,v 1.14 2011/04/08 08:56:31 hewitson Exp $', sets, pls);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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134 ii.setModifier(false);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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135 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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136
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Daniele Nicolodi <nicolodi@science.unitn.it>
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137 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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138 % Get Default Plist
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Daniele Nicolodi <nicolodi@science.unitn.it>
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139 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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140 function plout = getDefaultPlist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
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141 persistent pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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142 if exist('pl', 'var')==0 || isempty(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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143 pl = buildplist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
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144 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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145 plout = pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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146 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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147
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Daniele Nicolodi <nicolodi@science.unitn.it>
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148 function pl = buildplist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
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149 pl = plist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
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150
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Daniele Nicolodi <nicolodi@science.unitn.it>
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151 p = param({'Params', ['Cell array with parameters names with respect to linearize. <br>' ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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152 'Leave it empty to linearize with respect to all model parameters']}, paramValue.EMPTY_DOUBLE);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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153 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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154
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Daniele Nicolodi <nicolodi@science.unitn.it>
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155 p = param({'Sorting', ' Decide to sort the lits of input parameters'}, paramValue.TRUE_FALSE);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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156 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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157
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Daniele Nicolodi <nicolodi@science.unitn.it>
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158 end