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comparison m-toolbox/classes/@ao/interp.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 % INTERP interpolate the values in the input AO(s) at new values.
2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3 %
4 % DESCRIPTION: INTERP interpolate the values in the input AO(s) at new values
5 % specified by the input parameter list.
6 %
7 % CALL: b = interp(a, pl)
8 %
9 % INPUTS: a - input array of AOs
10 % pl - parameter list with the keys 'vertices' and 'method'
11 %
12 % OUTPUTS: b - output array of AOs
13 %
14 % REMARKs: 1) Matrix cdata objects are not supported.
15 % 2) If a time-series object is interpolated, the sample rate
16 % is adjusted to the best fit of the new data.
17 %
18 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'interp')">Parameters Description</a>
19 %
20 % VERSION: $Id: interp.m,v 1.43 2011/08/23 13:49:41 hewitson Exp $
21 %
22 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
23
24 function varargout = interp(varargin)
25
26 % Check if this is a call for parameters
27 if utils.helper.isinfocall(varargin{:})
28 varargout{1} = getInfo(varargin{3});
29 return
30 end
31
32 import utils.const.*
33 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
34
35 % Collect input variable names
36 in_names = cell(size(varargin));
37 for ii = 1:nargin,in_names{ii} = inputname(ii);end
38
39 % Collect all AOs and plists
40 [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
41 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
42
43 % Decide on a deep copy or a modify
44 bs = copy(as, nargout);
45
46 % Combine plists
47 pl = parse(pl, getDefaultPlist);
48
49 % Get parameters
50 vertices = find(pl, 'vertices');
51 method = find(pl, 'method');
52
53 utils.helper.msg(msg.PROC1, 'using %s interpolation', method);
54
55 %-----------------------
56 % Loop over input AOs
57 for jj = 1:numel(bs)
58 %----------------------------
59 % Interpolate this vector
60 if ~isa(bs(jj).data, 'cdata')
61 x = bs(jj).x;
62 y = bs(jj).y;
63 dy = bs(jj).dy;
64 % for tsdata, fsdata and xydata objects
65 bs(jj).data.setXY(vertices, interp1(x,y,vertices, method, 'extrap'));
66 if isa(bs(jj).data, 'tsdata')
67 % here we have to set the toffset to 0 because that information is
68 % stored in the x-values until it is collapsed below. Otherwise we
69 % end up with double the toffset.
70 bs(jj).data.setToffset(0);
71 end
72 if ~isempty(dy) && numel(dy) > 1
73 bs(jj).data.setDy(interp1(x, dy, vertices, method, 'extrap'));
74 end
75 if isprop(bs(jj).data, 'enbw')
76 if ~isempty(bs(jj).data.enbw) && numel(bs(jj).data.enbw) > 1
77 bs(jj).data.setEnbw(interp1(x, bs(jj).data.enbw, vertices, method, 'extrap'));
78 end
79 end
80 else
81 % for cdata object
82 bs(jj).data.setY(interp1(bs(jj).data.y,vertices, method, 'extrap'));
83 if ~isempty(bs(jj).dy) && numel(bs(jj).dy) > 1
84 bs(jj).data.setDy(interp1(bs(jj).dy, vertices, method, 'extrap'));
85 end
86 end
87
88 % Adjust sample rate for tsdata
89 if isa(bs(jj).data, 'tsdata')
90 utils.helper.msg(msg.PROC1, 'adjusting sample rate of new data to best fit');
91 [fs, t0, fitted] = tsdata.fitfs(bs(jj).data.getX);
92 utils.helper.msg(msg.PROC2, 'got new sample rate of %g Hz', fs);
93 utils.helper.msg(msg.PROC2, 'got new t0 %g', t0);
94 bs(jj).data.setFs(fs);
95 if ~fitted
96 bs(jj).data.collapseX;
97 end
98 end
99 % set name
100 bs(jj).name = sprintf('%s(%s)', method, ao_invars{jj});
101 % Add history
102 bs(jj).addHistory(getInfo('None'), pl, ao_invars, bs(jj).hist);
103 end
104
105 % Set output
106 if nargout == numel(bs)
107 % List of outputs
108 for ii = 1:numel(bs)
109 varargout{ii} = bs(ii);
110 end
111 else
112 % Single output
113 varargout{1} = bs;
114 end
115 end
116
117 %--------------------------------------------------------------------------
118 % Get Info Object
119 %--------------------------------------------------------------------------
120 function ii = getInfo(varargin)
121 if nargin == 1 && strcmpi(varargin{1}, 'None')
122 sets = {};
123 pl = [];
124 else
125 sets = {'Default'};
126 pl = getDefaultPlist;
127 end
128 % Build info object
129 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: interp.m,v 1.43 2011/08/23 13:49:41 hewitson Exp $', sets, pl);
130 end
131
132 %--------------------------------------------------------------------------
133 % Get Default Plist
134 %--------------------------------------------------------------------------
135 function plout = getDefaultPlist()
136 persistent pl;
137 if exist('pl', 'var')==0 || isempty(pl)
138 pl = buildplist();
139 end
140 plout = pl;
141 end
142
143 function pl = buildplist()
144
145 pl = plist();
146
147 % Vertices
148 p = param({'vertices', 'A new set of vertices to interpolate on.'}, paramValue.EMPTY_DOUBLE);
149 pl.append(p);
150
151 % Method
152 p = param({'method', 'Specify the interpolation method.'},{3, {'nearest', 'linear', 'spline', 'cubic'}, paramValue.SINGLE});
153 pl.append(p);
154
155 end