annotate m-toolbox/classes/@ao/bilinfit.m @ 10:75007001cbfe database-connection-manager

Check for binary only objects
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 % BILINFIT is a linear fitting tool
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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: BILINFIT linear fitting tool based on MATLAB's lscov
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % function. It solves an equation in the form
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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 % Y = X(1) * P(1) + X(2) * P(2) + ... + 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 % for the fit parameters P. It handles an arbitrary number of input vectors
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % and uncertainties on the dependent vector Y and input vectors X(1..N).
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % The output is a pest object where the fields are containing:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % Quantity % Field
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % Fit coefficients y
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % Uncertainties on the fit parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 % (given as standard deviations) dy
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % The reduced CHI2 of the fit chi2
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 % The covariance matrix cov
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 % The degrees of freedom of the fit dof
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 % CALL: P = bilinfit(X1, X2, .., XN, Y, PL)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 % INPUTS: Y - dependent variable
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 % X(1..N) - input variables
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 % PL - parameter list
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 % OUTPUT: P - a pest object with the N+1 elements
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 % PARAMETERS:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 % 'dy' - uncertainty on the dependent variable
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 % 'dx' - uncertainties on the input variables
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 % 'p0' - initial guess on the fit parameters to propagate uncertainities
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 % in the input variables X(1..N) to the dependent variable Y
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'bilinfit')">Parameters Description</a>
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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 % VERSION: $Id: bilinfit.m,v 1.20 2011/04/08 08:56:11 hewitson Exp $
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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 % EXAMPLES:
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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 % % 1) Determine the coefficients of a linear combination of noises:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43 % % Make some data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 % fs = 10;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 % nsecs = 10;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 % x1 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 % x2 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 % n = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 % c = [ao(1,plist('yunits','m/m')) ao(2,plist('yunits','m/m'))];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 % y = c(1)*x1 + c(2)*x2 + n;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 % y.simplifyYunits;
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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 % % Get a fit for the c coefficients and a constant term
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 % p = bilinfit(x1, x2, y)
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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 % % Do linear combination: using eval
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 % pl_split = plist('times', [1 5]);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 % yfit = eval(p, split(x1, pl_split), split(x2, pl_split));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 % % Plot (compare data with fit)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 % iplot(y, yfit, plist('Linestyles', {'-','--'}))
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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 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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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 function varargout = bilinfit(varargin)
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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 % check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 % tell the system we are runing
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 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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76
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 % collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 for ii = 1:nargin,in_names{ii} = inputname(ii);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 % collect all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 [aos, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 if nargout == 0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 error('### bilinfit can not be used as a modifier method. Please give at least one output');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 end
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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 if numel(aos) < 2
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 error('### bilinfit needs at least 2 inputs AOs');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 % combine plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 pl = parse(pl, getDefaultPlist());
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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 % extract parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 dy = find(pl, 'dy');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 dx = find(pl, 'dx');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 p0 = find(pl, 'p0');
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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 % collect inputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 Y = aos(end);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 X = aos(1:end-1);
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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 % collect inputs names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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106 argsname = aos(1).name;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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107 for jj = 2:numel(aos)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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108 argsname = [argsname ',' aos(jj).name];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111 % get data from AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112 x = X(:).y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 y = Y.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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114
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 % vectors length
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 N = length(y);
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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 % uncertainty on Y
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 if isempty(dy)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 dy = 1;
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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 if isa(dy, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123 % check units
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124 if Y.yunits ~= dy.yunits
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125 error('### Y and DY units are not compatible - %s %s', char(Y.yunits), char(dy.yunits));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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127 % extract values from AO
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Daniele Nicolodi <nicolodi@science.unitn.it>
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128 dy = dy.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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129 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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130 if isscalar(dy)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131 % given a single value construct a vector
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132 dy = ones(N, 1) * dy;
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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 % squares
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Daniele Nicolodi <nicolodi@science.unitn.it>
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136 sigma2 = dy.^2;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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137 sigma2y_rms = sqrt(sum(sigma2)/N);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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138
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Daniele Nicolodi <nicolodi@science.unitn.it>
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139 % extract values for initial guess
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Daniele Nicolodi <nicolodi@science.unitn.it>
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140 if (isa(p0, 'ao') || isa(p0, 'pest'))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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141 p0 = p0.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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142 end
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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 % uncertainty on X
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Daniele Nicolodi <nicolodi@science.unitn.it>
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145 if ~isempty(dx)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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146
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Daniele Nicolodi <nicolodi@science.unitn.it>
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147 for k = 1:length(dx)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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148 dxi = dx(k);
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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 if ~isempty(dxi)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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151 if isa(dxi, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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152 % check units
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Daniele Nicolodi <nicolodi@science.unitn.it>
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153 if X(k).yunits ~= dxi.yunits
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Daniele Nicolodi <nicolodi@science.unitn.it>
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154 error('### X and DX units are not compatible - %s %s', char(X.yunits), char(dxi.yunits));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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155 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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156 % extract values from AO
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Daniele Nicolodi <nicolodi@science.unitn.it>
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157 dxi = dxi.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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158 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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159 if isscalar(dxi)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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160 % given a single value construct a vector
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Daniele Nicolodi <nicolodi@science.unitn.it>
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161 dxi = ones(N, 1) * dxi;
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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>
parents:
diff changeset
163
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
164 % squares
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
165 sigma2xi = dxi.^2;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
166
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
167 % if A0 guess are not given
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
168 if isempty(p0(k))
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
169 % set it to obtain equal error contribution to the Y error
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
170 sigma2xi_rms = sqrt(sum(sigma2xi)/N);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
171 p0(k) = sigma2y_rms/sigma2xi_rms;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
172 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
173
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
174 % add contribution to weights
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
175 sigma2 = sigma2 + sigma2xi * p0(k)^2;
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
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
178 end
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 % constant term
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
182 c = ones(N, 1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
183
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
184 % build matrix
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
185 m = [x c];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
186
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
187 % solve
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
188 [p, stdx, mse, s] = lscov(m, y, 1./sigma2);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
189
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
190 % scale errors and covariance matrix
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
191 stdp = stdx ./ sqrt(mse);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
192 s = s ./ mse;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
193
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
194 % compute chi2
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
195 dof = N - length(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
196 chi2 = sum((y - lincom(m, p)).^2 ./ sigma2) / dof;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
197
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
198 % prepare model, units, names
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
199 model = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
200 for kk = 1:length(p)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
201 switch kk
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
202 case 1
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
203 units(kk) = simplify(Y.yunits/X(kk).yunits);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
204 model = ['P' num2str(kk) '*X' num2str(kk)];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
205 xvar{kk} = ['X' num2str(kk)];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
206 xunits{kk} = X(kk).yunits;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
207 case length(p)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
208 units(kk) = Y.yunits;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
209 model = [model ' + P' num2str(kk)];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
210 otherwise
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
211 units(kk) = simplify(Y.yunits/X(kk).yunits);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
212 model = [model ' + P' num2str(kk) '*X' num2str(kk)];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
213 xvar{kk} = ['X' num2str(kk)];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
214 xunits{kk} = X(kk).yunits;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
215 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
216 names{kk} = ['P' num2str(kk)];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
217
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
218 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
219 model = smodel(plist('expression', model, ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
220 'params', names, ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
221 'values', p, ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
222 'xvar', xvar, ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
223 'xunits', xunits, ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
224 'yunits', Y.yunits));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
225
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
226
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
227 % build the output pest object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
228 out = pest;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
229 out.setY(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
230 out.setDy(stdp);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
231 out.setCov(s);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
232 out.setChi2(chi2);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
233 out.setDof(dof);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
234 out.setNames(names{:});
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
235 out.setYunits(units);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
236 out.setModels(model);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
237 out.name = sprintf('bilinfit(%s)', argsname);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
238 out.addHistory(getInfo('None'), pl, ao_invars, [aos(:).hist]);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
239 % set procinfo object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
240 out.procinfo = plist('MSE', mse);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
241
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
242 % set outputs
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
243 varargout{1} = out;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
244
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
245 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
246
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
247 % computes linear combination
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
248 function out = lincom(x, p)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
249 assert(size(x, 2) == length(p));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
250 out = zeros(size(x, 1), 1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
251 for k = 1:length(p)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
252 out = out + x(:,k) * p(k);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
253 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
254 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
255
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
256 % get info object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
257 function ii = getInfo(varargin)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
258 if nargin == 1 && strcmpi(varargin{1}, 'None')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
259 sets = {};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
260 pl = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
261 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
262 sets = {'Default'};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
263 pl = getDefaultPlist();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
264 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
265 % build info object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
266 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.op, '$Id: bilinfit.m,v 1.20 2011/04/08 08:56:11 hewitson Exp $', sets, pl);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
267 ii.setModifier(false);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
268 ii.setArgsmin(2);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
269 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
270
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
271 % get default plist
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
272
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
273 function plout = getDefaultPlist()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
274 persistent pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
275 if ~exist('pl', 'var') || isempty(pl)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
276 pl = buildplist();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
277 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
278 plout = pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
279 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
280
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
281 function pl = buildplist()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
282
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
283 % default plist for linear fitting
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
284 pl = plist.MULTILINEAR_FIT_PLIST;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
285
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
286 end