Mercurial > hg > ltpda

annotate m-toolbox/classes/@pzmodel/tomfir.m @ 31:a26669b59d7e database-connection-manager

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Update LTPDAworkbench
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
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0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % TOMFIR approximates a pole/zero model with an FIR filter.
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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: TOMFIR approximates a pole/zero model with an FIR filter.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % The response of the pzmodel is computed using pzmodel/resp with
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % the additional input parameter of param('f1', 0). The final
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % frequency in the response is set automatically from the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 % pzmodel/resp function if not specified as an input. This upper
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % frequency is then taken as the Nyquist frequency and the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % sample rate of the corresponding fsdata AO is set accordingly.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % The function then calls mfir() with the new fsdata AO as input.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % The result is an FIR filter designed to have a magnitude response
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % equal to the magnitude response of the pole/zero model. The filter
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % has linear phase and the phase of the pzmodel is ignored.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % CALL: f = tomfir(pzm)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 % f = tomfir(pzm, plist)
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18 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 % <a href="matlab:utils.helper.displayMethodInfo('pzmodel', 'tomfir')">Parameters Description</a>
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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 % VERSION: $Id: tomfir.m,v 1.18 2011/04/08 08:56:32 hewitson Exp $
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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 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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24
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 function varargout = tomfir(varargin)
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26
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 %%% Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 end
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32
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33 % Check output arguments number
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34 if nargout == 0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 error('### pzmodel/tomfir cannot be used as a modifier. Please give an output variable.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 end
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37
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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41
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 % Collect all AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43 [pzms, pzm_invars] = utils.helper.collect_objects(varargin(:), 'pzmodel', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 pls = utils.helper.collect_objects(varargin(:), 'plist');
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45
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 % Store inhists to suppress intermediate history steps
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 inhists = [pzms(:).hist];
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48
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 % Get default parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 pl = parse(pls, getDefaultPlist);
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51
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 % Decide on a deep copy or a modify
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 pzms = copy(pzms, nargout);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 % check design parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 fs = find(pl, 'fs');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 f1 = find(pl, 'f1');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 f2 = find(pl, 'f2');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 nf = find(pl, 'nf');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 f2 = fs/2;
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61
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 r = resp(pzms, plist('f1', f1, 'f2', f2, 'nf', nf, 'scale', 'lin'));
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63
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 % Set fs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 r.setFs(fs);
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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 % compute filter
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 for kk = 1:numel(r)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 % throws a warning if the model has a delay
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 if(pzms(kk).delay~=0)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 disp('!!! PZmodel delay is not used in the discretization')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 % Compute mfir filter
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 f(kk) = mfir(r(kk));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 f(kk).addHistory(getInfo, pl, pzm_invars(kk), inhists(kk));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 end
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77
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 % Reshape the output to the shape of the input
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 f = reshape(f, size(r));
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80
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 % Set output
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 if nargout == numel(f)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 % List of outputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 for ii = 1:numel(f)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 varargout{ii} = f(ii);
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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 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 % Single output
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 varargout{1} = f;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 end
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91
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 end
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93
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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 % Local Functions %
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96 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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97
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98 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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99 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 % FUNCTION: getInfo
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 % DESCRIPTION: Get Info Object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 % HISTORY: 11-07-07 M Hewitson
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105 % Creation.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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106 %
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107 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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108
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 function ii = getInfo(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111 sets = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112 pl = [];
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113 else
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114 sets = {'Default'};
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115 pl = getDefaultPlist;
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116 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 ii = minfo(mfilename, 'pzmodel', 'ltpda', utils.const.categories.op, '$Id: tomfir.m,v 1.18 2011/04/08 08:56:32 hewitson Exp $', sets, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 ii.setModifier(false);
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120 end
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121
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Daniele Nicolodi <nicolodi@science.unitn.it>
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122 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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123 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124 % FUNCTION: getDefaultPlist
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125 %
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126 % DESCRIPTION: Get Default Plist
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127 %
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128 % HISTORY: 11-07-07 M Hewitson
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Daniele Nicolodi <nicolodi@science.unitn.it>
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129 % Creation.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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130 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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132
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Daniele Nicolodi <nicolodi@science.unitn.it>
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133 function plout = getDefaultPlist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
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134 persistent pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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135 if exist('pl', 'var')==0 || isempty(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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136 pl = buildplist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
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137 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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138 plout = pl;
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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
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Daniele Nicolodi <nicolodi@science.unitn.it>
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141 function plo = buildplist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
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142 fs = 10;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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143 f2 = fs/2;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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144
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Daniele Nicolodi <nicolodi@science.unitn.it>
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145 plo = plist();
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146
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Daniele Nicolodi <nicolodi@science.unitn.it>
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147 % FS
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148 p = param({'fs', 'Frequency of the fir filter.'}, paramValue.DOUBLE_VALUE(fs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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149 plo.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 % F1
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Daniele Nicolodi <nicolodi@science.unitn.it>
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152 p = param({'f1','Start frequency.'}, paramValue.DOUBLE_VALUE(0));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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153 plo.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 % F2
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Daniele Nicolodi <nicolodi@science.unitn.it>
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156 p = param({'f2','Stop frequency.'}, paramValue.DOUBLE_VALUE(f2));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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157 plo.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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158
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Daniele Nicolodi <nicolodi@science.unitn.it>
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159 % Nf
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Daniele Nicolodi <nicolodi@science.unitn.it>
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160 p = param({'nf','Number of evaluation frequencies.'}, paramValue.DOUBLE_VALUE(1000));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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161 plo.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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162
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Daniele Nicolodi <nicolodi@science.unitn.it>
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163 % Scale
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Daniele Nicolodi <nicolodi@science.unitn.it>
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164 p = param({'scale',['Spacing of frequencies:<ul>', ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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165 '<li>''lin'' - Linear scale.</li>', ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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166 '<li>''log'' - Logarithmic scale.</li></ul>']}, {1, {'lin', 'log'} paramValue.SINGLE});
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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167 plo.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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168
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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169 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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170