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annotate m-toolbox/classes/@ao/polyfit.m @ 1:2014ba5b353a database-connection-manager

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Remove old code
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Sat, 03 Dec 2011 18:13:55 +0100
parents f0afece42f48
children
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0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % POLYFIT overloads polyfit() function of MATLAB for Analysis Objects.
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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: POLYFIT overloads polyfit() function of MATLAB for Analysis
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % Objects. It finds the coefficients of a polynomial P(X) of
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % degree N that fits the data Y best in a least-squares sense:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % P(1)*X^N + P(2)*X^(N-1) +...+ P(N)*X + P(N+1)
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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 % CALL: bs = polyfit(a1, a2, a3, ..., pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % bs = polyfit(as,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % bs = as.polyfit(pl)
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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 % INPUTS: aN - input analysis objects with data to be fitted.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % X will be a.x
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 % Y will be a.y
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % as - input analysis objects array
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 % pl - input parameter list
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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 % OUTPUTs: bs - An array of pest objects, each with the N+1 fitting coefficients P(j)
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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 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'polyfit')">Parameters Description</a>
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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 % VERSION: $Id: polyfit.m,v 1.48 2011/05/12 03:37:08 mauro Exp $
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 % EXAMPLES:
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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 % %% Make fake AO from polyval
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 % nsecs = 100;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 % fs = 10;
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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 % u = unit('fm s^-2');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 % pl = plist('nsecs', nsecs, 'fs', fs, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 % 'tsfcn', 'polyval([3 2 1 ], t) + 1000*randn(size(t))', ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 % 'xunits', 's', 'yunits', u);
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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 % a1 = ao(pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 % %% Fit a polynomial
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 % N = 3;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41 % p1 = polyfit(a1, plist('N', N));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 % p2 = polyfit(a1, plist('N', N, 'rescale', true));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 % %% Compute fit: evaluating pest
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 % %% Here we need to specify that we want to use the 'x' field of
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 % %% the AO a to build the output AO
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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 % b1 = p1.eval(plist('type', 'tsdata', 'XData', a1, 'Xfield', 'x'));
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49 % b2 = p2.eval(a1, plist('type', 'tsdata', 'Xfield', 'x'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 % %% Plot fit
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 % iplot(a1, b1, plist('LineStyles', {'', '--'}));
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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 % %% Remove polynomial
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 % c = a1-b1;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 % iplot(c)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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59
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 function varargout = polyfit(varargin)
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61
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 end
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67
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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70
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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74
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 % Collect all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 [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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77 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 if nargout == 0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 error('### polyfit can not be used as a modifier method. Please give at least one output');
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81 end
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82
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 % Combine plists
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84 use_pl = parse(pl, getDefaultPlist);
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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 % Degree of polynomial to fit
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 N = find(use_pl, 'N');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 % Center and rescale the data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 rescale = utils.prog.yes2true(find(use_pl, 'rescale'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 % Loop over input AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 for jj = 1 : numel(as)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 if isa(as(jj).data, 'cdata')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 warning('!!! Can''t fit to cdata objects. Skipping AO %s', ao_invars{jj});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 bs = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 % Fit polynomial
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 mu = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 if rescale
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 [p,s,mu] = polyfit(as(jj).x, as(jj).y, N);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 [p,s] = polyfit(as(jj).x, as(jj).y, N);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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106
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Daniele Nicolodi <nicolodi@science.unitn.it>
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107 % prepare models, units, names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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108 model = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 for kk = 1:N+1
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110 names{kk} = ['P' num2str(kk)];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111 units{kk} = as(jj).yunits ./ ((as(jj).xunits).^(N-kk+1));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112 if kk == 1
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 model = [model 'P' num2str(kk) '*X.^' num2str(N-kk+1)];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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114 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 model = [model ' + P' num2str(kk) '*X.^' num2str(N-kk+1)];
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116 end
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117 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 model = smodel(plist('expression', model, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 'params', names, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 'values', p, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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121 'xvar', 'X', ...
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122 'xunits', as(jj).xunits, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123 'yunits', as(jj).yunits ...
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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
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126 % Build new pest objects from these N+1 coefficients
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Daniele Nicolodi <nicolodi@science.unitn.it>
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127 bs(jj) = pest;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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128 bs(jj).setY(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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129 bs(jj).setDof(s.df);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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130 bs(jj).setNames(names{:});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131 bs(jj).setYunits(units);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132 bs(jj).setModels(model);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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133 bs(jj).name = sprintf('polyfit(%s)', ao_invars{jj});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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134 bs(jj).addHistory(getInfo('None'), use_pl, ao_invars(jj), as(jj).hist);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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135 % Set procinfo object with some data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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136 bs(jj).procinfo = plist('S', s, 'mu', mu);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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137
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138 end
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139
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140 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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141
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Daniele Nicolodi <nicolodi@science.unitn.it>
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142 % Set output
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Daniele Nicolodi <nicolodi@science.unitn.it>
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143 varargout = utils.helper.setoutputs(nargout, bs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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144
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145 end
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146
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Daniele Nicolodi <nicolodi@science.unitn.it>
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147 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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148 % Get Info Object
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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>
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150 function ii = getInfo(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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151 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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152 sets = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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153 pl = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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154 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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155 sets = {'Default'};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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156 pl = getDefaultPlist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
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157 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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158 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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159 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: polyfit.m,v 1.48 2011/05/12 03:37:08 mauro Exp $', sets, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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160 ii.setModifier(false);
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161 ii.setArgsmin(1);
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162 end
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163
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164 %--------------------------------------------------------------------------
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165 % Get Default Plist
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166 %--------------------------------------------------------------------------
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167 function plout = getDefaultPlist()
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168 persistent pl;
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169 if ~exist('pl', 'var') || isempty(pl)
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170 pl = buildplist();
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171 end
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172 plout = pl;
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173 end
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174
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175 function pl = buildplist()
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176 pl = plist();
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177
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178 % N
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179 p = param({'N','Degree of polynomial to fit.'}, {2, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9}, paramValue.SINGLE});
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180 pl.append(p);
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181
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182 % Rescale
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183 p = param({'rescale',['set to ''true'' or ''false'' to center and ', ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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184 'rescale the data before fitting.<br>', ...
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185 'See "help polyfit" for further details.']}, paramValue.FALSE_TRUE);
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186 pl.append(p);
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187
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188 end
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189
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190 % END
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191