Mercurial > hg > ltpda

annotate m-toolbox/classes/@pest/mcmcPlot.m @ 20:d58813ab1b92 database-connection-manager

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Update ltpda_uo.submit
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
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0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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1
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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: simple tool that plots mcmc pest objects
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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: mcmcPlot(pest_obj,pl)
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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 % Parameters: - pest_obj: pest object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % - pl: plist
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % example: - mcmcPlot(p,plist('plotmatrix',true,'burnin',5000,'pdfs',true,'chain',[1 2 3 4 5 6]))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 %<a href="matlab:utils.helper.displayMethodInfo('pest', 'mcmcPlot')">ParametersDescription</a>
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14 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 % Nikos Oct 2011
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 function varargout = mcmcPlot(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 %%% Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 end
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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 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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29
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 % Collect all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 [pests, pest_invars] = utils.helper.collect_objects(varargin(:), 'pest', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 % Decide on a deep copy or a modify
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 p = copy(pests, nargout);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41 % combine plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 pl = parse(pl, getDefaultPlist());
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43 BurnIn = find(pl, 'burnin');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 nbins = find(pl, 'nbins');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 paramarray = find(pl, 'chain');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 %colorm = find(pl, 'colormap');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 if ~all(isa(pests, 'pest'))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 error('### mcmcPlot must be only applied to pest objects.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51
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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
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 outfigs = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 N = numel(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 if (BurnIn == 1 && ((find(pl, 'plotmatrix'))))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 utils.helper.msg(msg.IMPORTANT, sprintf(['The burn-in field is left empty or equal to one. For '...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 'better and more accurate display the burn-in section of the chains should be discarded.']));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 elseif (BurnIn == 1 && ((find(pl, 'pdfs'))))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 utils.helper.msg(msg.IMPORTANT, sprintf(['The burn-in field is left empty or equal to one. For '...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 'better and more accurate display the burn-in section of the chains should be discarded.']));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 for numpest=1:N
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 % compute PDF
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 chain=p(numpest).chain(:,2:size(p(numpest).chain,2));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 p(numpest).computePdf(plist('BurnIn',BurnIn,'nbins',nbins));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 if isempty(paramarray)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 % plot chain field (skip 1st column where the Loglikelihood is stored)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 outfigs = [outfigs ; figure];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 data = plot(chain);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 ch = p(numpest).chain(:,paramarray);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 outfigs = [outfigs ; figure];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 data = plot(ch);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 if (find(pl, 'plotmatrix'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 chn = p(numpest).chain(BurnIn:size(chain,1),2:size(p(numpest).chain,2));
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83 outfigs = [outfigs ; figure];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 plotmatrix(chn);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 if (find(pl, 'results'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 chainn = chain(BurnIn:size(chain,1),:);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 utils.helper.msg(msg.IMPORTANT, sprintf('Results:'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 for ii = 1:(size(chainn,2))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 mu = mean(chainn(:,ii));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 sigma = std(chainn(:,ii));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 res = [mu sigma];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 utils.helper.msg(msg.IMPORTANT, sprintf(' %d \t',res));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 if (find(pl, 'pdfs'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 outfigs = [outfigs ; figure];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 if ~(find(pl, 'plotmatrix'))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 chn = p.chain(BurnIn:size(p.chain(:,:),1),:);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105 a=p(numpest).pdf;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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106 a(:,1) = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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107 a(:,1) = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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108
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 for kk =1:size(chn,2)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110 subplot(2,4,kk)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111 x = linspace(min(a(:,2*kk-1)),max(a(:,2*kk-1)),10);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112 h = bar(a(:,2*kk-1),a(:,2*kk));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 hold on;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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114 y=normpdf(x,mean(chn(:,kk)),std(chn(:,kk)));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 s=sum(y);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 y=y/s;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117 plot(x,y,'r-','LineWidth',2);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 hold off;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 shading interp % Needed to graduate colors
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Daniele Nicolodi <nicolodi@science.unitn.it>
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121
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Daniele Nicolodi <nicolodi@science.unitn.it>
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122 ch = get(h,'Children');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123 fvd = get(ch,'Faces');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124 fvcd = get(ch,'FaceVertexCData');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125 n = 10;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126 [zs, izs] = sortrows(a(:,2*kk),1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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127 k = 128; % Number of colors in color table
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Daniele Nicolodi <nicolodi@science.unitn.it>
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128 colormap(summer(k)); % Expand the previous colormap
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Daniele Nicolodi <nicolodi@science.unitn.it>
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129 shading interp % Needed to graduate colors
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Daniele Nicolodi <nicolodi@science.unitn.it>
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130 for i = 1:n
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131 color = floor(k*i/n); % Interpolate a color index
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132 row = izs(i); % Look up actual row # in data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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133 fvcd(fvd(row,1)) = 1; % Color base vertices 1st index
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Daniele Nicolodi <nicolodi@science.unitn.it>
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134 fvcd(fvd(row,4)) = 1;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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135 fvcd(fvd(row,2)) = color; % Assign top vertices color
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Daniele Nicolodi <nicolodi@science.unitn.it>
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136 fvcd(fvd(row,3)) = color;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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137 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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138 set(ch,'FaceVertexCData', fvcd); % Apply the vertex coloring
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Daniele Nicolodi <nicolodi@science.unitn.it>
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139 set(ch,'EdgeColor','k') % Give bars black borders
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Daniele Nicolodi <nicolodi@science.unitn.it>
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140 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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141
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Daniele Nicolodi <nicolodi@science.unitn.it>
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142
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Daniele Nicolodi <nicolodi@science.unitn.it>
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143
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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>
parents:
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145
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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146
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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147 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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148
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Daniele Nicolodi <nicolodi@science.unitn.it>
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149
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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150 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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151
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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152 if nargout == 0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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153 out = outfigs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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154 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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155 error('### mcmcPlot cannot be used as a modifier!');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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156 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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157
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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158 % Set outputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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159 if nargout > 0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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160 varargout{1} = out;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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161 end
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162
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Daniele Nicolodi <nicolodi@science.unitn.it>
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163 end
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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>
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165
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Daniele Nicolodi <nicolodi@science.unitn.it>
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166 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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167 % Get Info Object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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168 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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169 function ii = getInfo(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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170 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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171 sets = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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172 pl = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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173 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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174 sets = {'Default'};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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175 pl = getDefaultPlist;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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176 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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177 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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178 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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Daniele Nicolodi <nicolodi@science.unitn.it>
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179 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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180
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181
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Daniele Nicolodi <nicolodi@science.unitn.it>
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182 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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183 % Get Default Plist
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Daniele Nicolodi <nicolodi@science.unitn.it>
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184 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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185 function plout = getDefaultPlist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
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186 persistent pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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187 if exist('pl', 'var')==0 || isempty(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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188 pl = buildplist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
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189 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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190 plout = pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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191 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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192
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Daniele Nicolodi <nicolodi@science.unitn.it>
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193 function pl = buildplist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
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194 pl = plist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
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195
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Daniele Nicolodi <nicolodi@science.unitn.it>
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196 p = param({'chain',['Insert an array containing the parameters to plot. If left empty,'...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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197 'then by default will plot the chains of every parameter. (note: The loglikelihood is stored '...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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198 'in the first column)']}, paramValue.DOUBLE_VALUE([]));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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199 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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200
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Daniele Nicolodi <nicolodi@science.unitn.it>
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201 p = param({'BurnIn',['Number of samples (of the chains) to be discarded for the computation of the PDFs of the parameters. Also used'...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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202 'for producing the plotmatrix figure.']}, paramValue.DOUBLE_VALUE(1));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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203 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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204
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Daniele Nicolodi <nicolodi@science.unitn.it>
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205 p = param({'nbins','Number of bins of the pdf histogram computed for every parameter (used again for the computation of the PDFs of the parameters)'}, paramValue.DOUBLE_VALUE(10));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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206 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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207
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Daniele Nicolodi <nicolodi@science.unitn.it>
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208 p = param({'plotmatrix','Boolean to determine if a plotmatrix is desired'}, {1, {false,true}, paramValue.OPTIONAL});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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209 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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210
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Daniele Nicolodi <nicolodi@science.unitn.it>
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211 p = param({'pdfs','Boolean to determine if a plot of the PDFs of each parameter is desired'}, {1, {false,true}, paramValue.OPTIONAL});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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212 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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213
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Daniele Nicolodi <nicolodi@science.unitn.it>
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214 %p = param({'colormap','Choose a default matlab colormap for the parameter histogarms.'}, paramValue.DOUBLE_VALUE(summer));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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215 %pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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216
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Daniele Nicolodi <nicolodi@science.unitn.it>
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217 p = param({'results',['Set to "true" if a table of the results of the estimated parameters is desired.'...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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218 'The results are printed on screen in 2 columns: the 1st contains the mean value'....
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Daniele Nicolodi <nicolodi@science.unitn.it>
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219 'and the second the sigma. Burn-in field is requiered.']}, {1, {false,true}, paramValue.OPTIONAL});
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220 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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221
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Daniele Nicolodi <nicolodi@science.unitn.it>
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222 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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223