annotate m-toolbox/classes/@ao/resample.m @ 24:056f8e1e995e database-connection-manager

Properly record history in fromRepository constructors
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % RESAMPLE overloads resample function for AOs.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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3 %
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4 % DESCRIPTION: RESAMPLE overloads resample function for AOs.
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5 %
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6 % CALL: bs = resample(a1,a2,a3,...,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % bs = resample(as,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 % bs = as.resample(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % INPUTS: aN - input analysis objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % as - input analysis objects array
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12 % pl - input parameter list
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13 %
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14 % OUTPUTS: bs - array of analysis objects, one for each input
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15 %
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16 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'resample')">Parameters Description</a>
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17 %
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18 % VERSION: $Id: resample.m,v 1.50 2011/07/14 05:33:18 mauro Exp $
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19 %
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20 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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21
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 function varargout = resample(varargin)
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23
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24 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 return
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28 end
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29
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30 import utils.const.*
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31 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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32
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33 % Collect input variable names
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34 in_names = cell(size(varargin));
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35 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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36
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 % Collect all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
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39 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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40
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41 % Decide on a deep copy or a modify
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 bs = copy(as, nargout);
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43
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44 % Combine plists
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45 pl = parse(pl, getDefaultPlist);
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46
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47 if isempty(pl)
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48 error('### Please give a plist with a parameter ''fsout''.');
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49 end
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50
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51 % Get output sample rate
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52 fsout = find(pl, 'fsout');
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53 if isempty(fsout)
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54 error('### Please give a plist with a parameter ''fsout''.');
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55 end
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56
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 % Get a filter if specified
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 filt = find(pl, 'filter');
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59 if ~isempty(filt) && ~isa(filt, 'mfir')
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60 error('The filter specified must be an mfir filter object (FIR filter).');
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61 end
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62
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63 % Loop over AOs
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64 for jj = 1:numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 if ~isa(bs(jj).data, 'tsdata')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 warning('!!! Skipping non-tsdata AO: %s', ao_invars{jj});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 % Compute the resampling factors
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 [P,Q] = utils.math.intfact(fsout,bs(jj).data.fs);
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70 utils.helper.msg(msg.PROC1, 'resampling by %g/%g', P, Q);
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71
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72 % Check we have an evenly sampled data series
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 if ~bs(jj).data.evenly()
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 error('### The AO %s is unevenly sampled. It can not be resampled this way.', ao_invars{jj});
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75 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 % resample y
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77 if isempty(filt)
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78 bs(jj).data.setY(resample(bs(jj).data.getY, P, Q));
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79 else
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80 [p,q] = rat( fsout/bs(jj).fs, 1e-12 );
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81 b = p*filt.a;
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82 bs(jj).data.setY(resample(bs(jj).data.getY, P, Q, b));
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83 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 % Set new sample rate
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 bs(jj).data.setFs(fsout);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 % Set output AO name
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87 bs(jj).name = sprintf('resample(%s)', ao_invars{jj});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 % Add history
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 bs(jj).addHistory(getInfo('None'), pl, ao_invars(jj), bs(jj).hist);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 % clear errors
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91 bs(jj).clearErrors;
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92 end
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93 end
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94
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 % Set output
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96 varargout = utils.helper.setoutputs(nargout, bs);
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97 end
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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 % Get Info Object
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101 %--------------------------------------------------------------------------
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102 function ii = getInfo(varargin)
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103 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 sets = {};
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105 pl = [];
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106 else
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107 sets = {'Default'};
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108 pl = getDefaultPlist;
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109 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: resample.m,v 1.50 2011/07/14 05:33:18 mauro Exp $', sets, pl);
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112 end
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113
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114 %--------------------------------------------------------------------------
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115 % Get Default Plist
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116 %--------------------------------------------------------------------------
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117 function plout = getDefaultPlist()
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118 persistent pl;
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119 if ~exist('pl', 'var') || isempty(pl)
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120 pl = buildplist();
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121 end
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122 plout = pl;
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123 end
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124
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125 function pl = buildplist()
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126
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127 pl = plist();
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128
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129 % Type
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130 p = param({'fsout',['The desired output frequency<br>'...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131 '(must be positive and integer).']}, paramValue.EMPTY_DOUBLE);
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132 pl.append(p);
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133
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134 p = param({'filter', 'The filter to apply in the resampling process.'}, paramValue.EMPTY_STRING);
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135 pl.append(p);
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136
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137 end
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138 % END
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139