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comparison m-toolbox/classes/@ao/polyfit.m @ 0:f0afece42f48

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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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1 % POLYFIT overloads polyfit() function of MATLAB for Analysis Objects.
2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3 %
4 % DESCRIPTION: POLYFIT overloads polyfit() function of MATLAB for Analysis
5 % Objects. It finds the coefficients of a polynomial P(X) of
6 % degree N that fits the data Y best in a least-squares sense:
7 % P(1)*X^N + P(2)*X^(N-1) +...+ P(N)*X + P(N+1)
8 %
9 % CALL: bs = polyfit(a1, a2, a3, ..., pl)
10 % bs = polyfit(as,pl)
11 % bs = as.polyfit(pl)
12 %
13 % INPUTS: aN - input analysis objects with data to be fitted.
14 % X will be a.x
15 % Y will be a.y
16 % as - input analysis objects array
17 % pl - input parameter list
18 %
19 % OUTPUTs: bs - An array of pest objects, each with the N+1 fitting coefficients P(j)
20 %
21 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'polyfit')">Parameters Description</a>
22 %
23 % VERSION: $Id: polyfit.m,v 1.48 2011/05/12 03:37:08 mauro Exp $
24 %
25 % EXAMPLES:
26 %
27 % %% Make fake AO from polyval
28 % nsecs = 100;
29 % fs = 10;
30 %
31 % u = unit('fm s^-2');
32 %
33 % pl = plist('nsecs', nsecs, 'fs', fs, ...
34 % 'tsfcn', 'polyval([3 2 1 ], t) + 1000*randn(size(t))', ...
35 % 'xunits', 's', 'yunits', u);
36 %
37 % a1 = ao(pl);
38 %
39 % %% Fit a polynomial
40 % N = 3;
41 % p1 = polyfit(a1, plist('N', N));
42 % p2 = polyfit(a1, plist('N', N, 'rescale', true));
43 %
44 % %% Compute fit: evaluating pest
45 % %% Here we need to specify that we want to use the 'x' field of
46 % %% the AO a to build the output AO
47 %
48 % b1 = p1.eval(plist('type', 'tsdata', 'XData', a1, 'Xfield', 'x'));
49 % b2 = p2.eval(a1, plist('type', 'tsdata', 'Xfield', 'x'));
50 %
51 % %% Plot fit
52 % iplot(a1, b1, plist('LineStyles', {'', '--'}));
53 %
54 % %% Remove polynomial
55 % c = a1-b1;
56 % iplot(c)
57 %
58 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
59
60 function varargout = polyfit(varargin)
61
62 % Check if this is a call for parameters
63 if utils.helper.isinfocall(varargin{:})
64 varargout{1} = getInfo(varargin{3});
65 return
66 end
67
68 import utils.const.*
69 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
70
71 % Collect input variable names
72 in_names = cell(size(varargin));
73 for ii = 1:nargin,in_names{ii} = inputname(ii);end
74
75 % Collect all AOs and plists
76 [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
77 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
78
79 if nargout == 0
80 error('### polyfit can not be used as a modifier method. Please give at least one output');
81 end
82
83 % Combine plists
84 use_pl = parse(pl, getDefaultPlist);
85
86 % Degree of polynomial to fit
87 N = find(use_pl, 'N');
88
89 % Center and rescale the data
90 rescale = utils.prog.yes2true(find(use_pl, 'rescale'));
91
92 % Loop over input AOs
93 for jj = 1 : numel(as)
94
95 if isa(as(jj).data, 'cdata')
96 warning('!!! Can''t fit to cdata objects. Skipping AO %s', ao_invars{jj});
97 bs = [];
98 else
99 % Fit polynomial
100 mu = [];
101 if rescale
102 [p,s,mu] = polyfit(as(jj).x, as(jj).y, N);
103 else
104 [p,s] = polyfit(as(jj).x, as(jj).y, N);
105 end
106
107 % prepare models, units, names
108 model = [];
109 for kk = 1:N+1
110 names{kk} = ['P' num2str(kk)];
111 units{kk} = as(jj).yunits ./ ((as(jj).xunits).^(N-kk+1));
112 if kk == 1
113 model = [model 'P' num2str(kk) '*X.^' num2str(N-kk+1)];
114 else
115 model = [model ' + P' num2str(kk) '*X.^' num2str(N-kk+1)];
116 end
117 end
118 model = smodel(plist('expression', model, ...
119 'params', names, ...
120 'values', p, ...
121 'xvar', 'X', ...
122 'xunits', as(jj).xunits, ...
123 'yunits', as(jj).yunits ...
124 ));
125
126 % Build new pest objects from these N+1 coefficients
127 bs(jj) = pest;
128 bs(jj).setY(p);
129 bs(jj).setDof(s.df);
130 bs(jj).setNames(names{:});
131 bs(jj).setYunits(units);
132 bs(jj).setModels(model);
133 bs(jj).name = sprintf('polyfit(%s)', ao_invars{jj});
134 bs(jj).addHistory(getInfo('None'), use_pl, ao_invars(jj), as(jj).hist);
135 % Set procinfo object with some data
136 bs(jj).procinfo = plist('S', s, 'mu', mu);
137
138 end
139
140 end
141
142 % Set output
143 varargout = utils.helper.setoutputs(nargout, bs);
144
145 end
146
147 %--------------------------------------------------------------------------
148 % Get Info Object
149 %--------------------------------------------------------------------------
150 function ii = getInfo(varargin)
151 if nargin == 1 && strcmpi(varargin{1}, 'None')
152 sets = {};
153 pl = [];
154 else
155 sets = {'Default'};
156 pl = getDefaultPlist();
157 end
158 % Build info object
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);
160 ii.setModifier(false);
161 ii.setArgsmin(1);
162 end
163
164 %--------------------------------------------------------------------------
165 % Get Default Plist
166 %--------------------------------------------------------------------------
167 function plout = getDefaultPlist()
168 persistent pl;
169 if ~exist('pl', 'var') || isempty(pl)
170 pl = buildplist();
171 end
172 plout = pl;
173 end
174
175 function pl = buildplist()
176 pl = plist();
177
178 % N
179 p = param({'N','Degree of polynomial to fit.'}, {2, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9}, paramValue.SINGLE});
180 pl.append(p);
181
182 % Rescale
183 p = param({'rescale',['set to ''true'' or ''false'' to center and ', ...
184 'rescale the data before fitting.<br>', ...
185 'See "help polyfit" for further details.']}, paramValue.FALSE_TRUE);
186 pl.append(p);
187
188 end
189
190 % END
191