Mercurial > hg > ltpda

annotate m-toolbox/classes/@ao/interp.m @ 22:b11e88004fca database-connection-manager

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