annotate m-toolbox/classes/@ao/mcmc_td.m @ 25:79dc7091dbbc database-connection-manager

Update tests
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 % MCMC_TD estimates paramters using a Monte Carlo Markov Chain.
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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: MCMC estimate the parameters of a given model given
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % inputs, outputs and noise using a Metropolis algorithm.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 %
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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: b = mcmc(out,pl)
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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 % INPUTS:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % out - analysis objects with measured outputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % pl - parameter list
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % OUTPUTS: b - pest object contatining estimate information
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'mcmc_td')">Parameters Description</a>
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17 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 % VERSION: $Id: mcmc_td.m,v 1.6 2011/04/08 08:56:12 hewitson Exp $
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19 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 % References: "Catching supermassive black holes binaries without a net"
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 % N.J. Cornish, E.K. Porter, Phys.Rev.D 75, 021301, 2007
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 % TODO: multiple chain option not implemented yet
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 % metropolis/hastings not implemented
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 % empty initial values not implemented
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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28
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 function varargout = mcmc_td(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 % Method can not be used as a modifier
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41 if nargout == 0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 error('### metropolis2D cannot be used as a modifier. Please give an output variable.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 % Collect all AOs smodels and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 % Decide on a deep copy or a modify
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 bs = copy(as, nargout);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 out = bs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57
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58
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 % Combine plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 pl = parse(pl, getDefaultPlist);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 % Get parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 N = find(pl, 'N');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 Tc = find(pl,'Tc');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 xi = find(pl,'heat');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 cvar = find(pl, 'cov');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 rng = find(pl,'range');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 search = find(pl,'search');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 simplex = find(pl,'simplex');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 x0 = find(pl,'x0');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 mdl = find(pl,'model');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 %nse = find(pl,'noise');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 jumps = find(pl,'jumps');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 parplot = find(pl,'plot');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 debug = find(pl,'debug');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 in = find(pl,'Input');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 inNames = find(pl,'inNames');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 outNames = find(pl,'outNames');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 Noise = find(pl,'Noise');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 parnames = find(pl,'parnames');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 cutbefore = find(pl,'cutbefore');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 cutafter = find(pl,'cutafter');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 % Check input parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 if isempty(rng)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 error('### Please define a search range ''range''');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 if isempty(parnames)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 error('### Please define the parameters ''parnames''');
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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 nparam = numel(parnames);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 % Get range for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 for i = 1:nparam
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 range(:,i) = rng{i};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 % do simplex
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105 if simplex
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Daniele Nicolodi <nicolodi@science.unitn.it>
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106 if isempty(x0)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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107 error('### Simplex needs a starting guess. Please input a ''x0''.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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108 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 switch class(mdl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110 case 'smodel'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111 %xo = fminsearch(@(x) utils.math.loglikehood(x,in,out,nse,mdl,param),xo,optimset('Display','iter'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112 case 'ssm'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 x0 = fminsearch(@(x)utils.math.loglikehood_ssm_td(x,in,out,parnames,mdl,inNames,outNames,Noise,'cutbefore',cutbefore,'cutafter',cutafter),x0,optimset('Display','iter'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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114 otherwise
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 error('### Model must be either from the ''smodel'' or the ''ssm'' class. Please check the inputs')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 for i = 1:numel(parnames)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 fprintf('### Simplex estimate: %s = %d \n',parnames{i},x0(i))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 %save('parameters_simplex.txt','x0','-ASCII')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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121 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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122 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125 % sample distribution
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126 smpl = utils.math.mhsample_td(mdl,in,out,cvar,N,range,parnames,Tc,xi,x0,search,jumps,parplot,debug,inNames,outNames,Noise,cutbefore,cutafter);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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127
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Daniele Nicolodi <nicolodi@science.unitn.it>
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128 % statistics of the chain
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Daniele Nicolodi <nicolodi@science.unitn.it>
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129 if isempty(Tc)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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130 initial =1;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132 initial = Tc(2)+1;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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133 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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134
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Daniele Nicolodi <nicolodi@science.unitn.it>
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135 mn = mean(smpl(initial:end,:));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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136 cv = cov(smpl(initial:end,:));
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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 cr = utils.math.cov2corr(cv);
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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 % compute pdf
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Daniele Nicolodi <nicolodi@science.unitn.it>
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141 for i = 1:nparam
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Daniele Nicolodi <nicolodi@science.unitn.it>
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142 [count,bin] = hist(smpl(initial:end,i));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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143 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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144
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Daniele Nicolodi <nicolodi@science.unitn.it>
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145 % create pest output
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Daniele Nicolodi <nicolodi@science.unitn.it>
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146 p = pest(mn);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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147 p.setName('metropolis2D');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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148 p.setNames(parnames{:});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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149 % add statistical info
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Daniele Nicolodi <nicolodi@science.unitn.it>
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150 p.setCov(cv);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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151 p.setCorr(cr);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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152 p.setDy(sqrt(diag(cv))); % need to change if non-gaussian
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Daniele Nicolodi <nicolodi@science.unitn.it>
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153 p.setPdf([reshape(bin, 1, []), reshape(count, 1, [])]); % not yet able to store bins
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Daniele Nicolodi <nicolodi@science.unitn.it>
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154 p.setChain(smpl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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155 p.setModels(mdl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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156 % set history
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Daniele Nicolodi <nicolodi@science.unitn.it>
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157 p.addHistory(getInfo('None'), pl, [ao_invars(:)], [bs(:).hist mdl(:).hist]);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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158
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Daniele Nicolodi <nicolodi@science.unitn.it>
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159 % Set output
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Daniele Nicolodi <nicolodi@science.unitn.it>
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160 varargout{1} = p;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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161
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Daniele Nicolodi <nicolodi@science.unitn.it>
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162 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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163
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Daniele Nicolodi <nicolodi@science.unitn.it>
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164
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
165
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
166 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
167 % Get Info Object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
168 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
169 function ii = getInfo(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
170 if nargin == 1 && strcmpi(varargin{1}, 'None')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
171 sets = {};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
172 pl = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
173 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
174 sets = {'Default'};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
175 pl = getDefaultPlist;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
176 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
177 % Build info object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
178 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: mcmc_td.m,v 1.6 2011/04/08 08:56:12 hewitson Exp $', sets, pl);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
179 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
180
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
181 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
182 % Get Default Plist
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
183 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
184 function plout = getDefaultPlist()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
185 persistent pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
186 if exist('pl', 'var')==0 || isempty(pl)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
187 pl = buildplist();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
188 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
189 plout = pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
190 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
191
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
192 function pl = buildplist()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
193 pl = plist();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
194
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
195 % N
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
196 p = param({'N','number of samples of the chain.'}, paramValue.DOUBLE_VALUE(1000));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
197 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
198
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
199 % Sigma
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
200 p = param({'cov','covariance of the gaussian jumping distribution.'}, paramValue.DOUBLE_VALUE(1e-4));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
201 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
202
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
203 % Param
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
204 p = param({'parnames','A cell array of evaluated parameters.'}, paramValue.EMPTY_CELL);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
205 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
206
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
207
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
208 % Model
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
209 p = param({'model','The model for the system, at the moment only ssm is supported'}, paramValue.EMPTY_STRING);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
210 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
211
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
212 % Search
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
213 p = param({'search','Set to true to use bigger jumps in parameter space during annealing and cool down.'}, paramValue.TRUE_FALSE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
214 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
215
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
216 % Simplex
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
217 p = param({'simplex','Set to true to perform a simplex search to find the starting parameters of the MCMC chain.'}, paramValue.TRUE_FALSE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
218 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
219
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
220 % heat
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
221 p = param({'heat','The heat index flattening likelihood surface during annealing.'}, paramValue.DOUBLE_VALUE(1));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
222 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
223
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
224 % Tc
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
225 p = param({'Tc','An array of two values setting the initial and final value for the cooling down.'}, paramValue.EMPTY_STRING);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
226 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
227
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
228 % x0
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
229 p = param({'x0','The proposed initial values.'}, paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
230 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
231
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
232 % jumps
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
233 p = param({'jumps','An array of four numbers setting the rescaling of the covariance matrix during the search phase.',...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
234 'The first value is the one applied by default, the following thhree apply just when the chain sample is',...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
235 'mod(10), mod(25) and mod(100) respectively.'}, paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
236 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
237
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
238 % plot
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
239 p = param({'plot','Select indexes of the parameters to be plotted.'}, paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
240 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
241
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
242 % debug
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
243 p = param({'debug','Set to true to get debug information of the MCMC process.'}, paramValue.FALSE_TRUE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
244 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
245
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
246 % Input
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
247 p = param({'Input','An array of analysis object containing the input signals'},paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
248 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
249
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
250 % inNames
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
251 p = param({'inNames','Cell array of input port names'}, paramValue.EMPTY_CELL);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
252 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
253
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
254 % outNames
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
255 p = param({'outNames','Cell array of output port names'}, paramValue.EMPTY_CELL);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
256 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
257
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
258
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
259 % Noise
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
260 p = param({'Noise','An array of analysis objects containg noise series'}, paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
261 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
262
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
263 % cutbefore
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
264 p = param({'cutbefore','the data samples to cut at the starting of the series'}, paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
265 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
266
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
267 % cutafter
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
268 p = param({'cutafter','the data samples to cut at the ending of the series'}, paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
269 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
270
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
271
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
272 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
273
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
274
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
275