annotate m-toolbox/classes/@pest/computePdf.m @ 38:3aef676a1b20 database-connection-manager

Keep backtrace on error
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % computes Probability Density Function from a pest object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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3 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 % DESCRIPTION: computes Probability Density Function from a pest object.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % CALL: p = computePdf(p,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % p.computePdf(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % INPUTS: p - pest object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % pl - parameter list (BurnIn,nbins)
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11 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % OUTPUTs: p - pest object with the computed normilized pdf
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13 %
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14 % <a href="matlab:utils.helper.displayMethodInfo('pest', 'computePdf')">Parameters Description</a>
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15 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % VERSION: $Id: computePdf.m,v 1.2 2011/06/06 14:02:12 nikos Exp $
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17 %
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18 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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19
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 function varargout = computePdf(varargin)
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21
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 %%% Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 end
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27
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 import utils.const.*
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29 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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30
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31 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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34
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35 % Collect all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 [pests, pest_invars] = utils.helper.collect_objects(varargin(:), 'pest', in_names);
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37 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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38
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 % Decide on a deep copy or a modify
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 p = copy(pests, nargout);
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41
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42 % combine plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43 pl = parse(pl, getDefaultPlist());
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 BurnIn = find(pl, 'BurnIn');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 nbins = find(pl, 'nbins');
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46
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 if ~all(isa(pests, 'pest'))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 error('### computePdf must be only applied to pest objects.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 end
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50
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51 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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52
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 N = numel(p);
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54
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55 for ii=1:N
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 a=p(ii).chain;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 D=size(a);
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58 [n(1,:),xout(1,:)]=hist(a(BurnIn:D(1),1),nbins);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 sumbins = sum(n(1,:));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 PDF = [xout(1,:) ; n(1,:)/sumbins]';
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61
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62 for jj=2:D(2)
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63 % creating histograms
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64 [n(jj,:),xout(jj,:)]=hist(a(BurnIn:D(1),jj),nbins);
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65 sumbins = sum(n(jj,:));
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66 PDF = [PDF xout(jj,:)' (n(jj,:)')/sumbins];
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67 end
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68 PDFn(:,:,ii)= PDF;
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69 end
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70
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71 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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72
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 % Output pest/pdf
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 if nargout == 1
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75 for ii=1:N
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76 p(ii).setPdf(PDFn(:,:,ii));
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77 end
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78 out = p;
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79 elseif nargout == 0
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80 for ii=1:N
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81 p(ii).setPdf(PDFn(:,:,ii));
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82 end
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83 out = p;
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84 out.addHistory(getInfo('None'), pl, pest_invars(:), [pests(:).hist]);
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85 else
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86 error('### The number of output arguments must be a one or zero');
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87 end
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88
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89 name = p(1).name;
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90 if N>1
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91 for ii=2:N
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92 name = [name ',' p(ii).name];
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93 end
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94 end
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95
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 % Set outputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 if nargout > 0
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98 varargout{1} = out;
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99 end
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100
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101 end
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102
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103
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104 %--------------------------------------------------------------------------
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105 % Get Info Object
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106 %--------------------------------------------------------------------------
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107 function ii = getInfo(varargin)
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108 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 sets = {};
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110 pl = [];
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111 else
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112 sets = {'Default'};
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113 pl = getDefaultPlist;
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114 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 % Build info object
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116 ii = minfo(mfilename, 'pest', 'ltpda', utils.const.categories.helper, '$Id: computePdf.m,v 1.2 2011/06/06 14:02:12 nikos Exp $', sets, pl);
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117 end
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118
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119
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120 %--------------------------------------------------------------------------
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121 % Get Default Plist
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122 %--------------------------------------------------------------------------
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123 function plout = getDefaultPlist()
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124 persistent pl;
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125 if exist('pl', 'var')==0 || isempty(pl)
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126 pl = buildplist();
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127 end
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128 plout = pl;
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129 end
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130
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131 function pl = buildplist()
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132 pl = plist();
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133
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134 p = param({'BurnIn','Number of samples (of the chains) to be discarded'}, paramValue.DOUBLE_VALUE(1));
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135 pl.append(p);
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136
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Daniele Nicolodi <nicolodi@science.unitn.it>
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137 p = param({'nbins','Number of bins of the pdf histogram computed for every parameter'}, paramValue.DOUBLE_VALUE(10));
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138 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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139
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140 end
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141