annotate m-toolbox/classes/@ao/timeaverage.m @ 3:960fe1aa1c10 database-connection-manager

Add LTPDADatabaseConnectionManager implementation. Java code
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 % TIMEAVERAGE Averages time series intervals
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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3 %
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4 % DESCRIPTION: Averages time series intervals and return a reduced time
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5 % series where each point represents the average of a stretch of data.
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6 % Despite the name this method can perform some different operations on the
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7 % data stretches or apply a user supplied function. Different functions can
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8 % be applied to X and Y data.
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9 %
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10 % CALL: BS = timeaverage(A1, A2, A3, ..., PL)
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11 %
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12 % INPUTS: AN - time series AOs
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13 % PL - parameters list
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14 %
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15 % OUTPUTS: BS - array of AOs
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16 %
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17 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'timeaverage')">Parameters Description</a>
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18 %
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19 % EXAMPLES:
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20 %
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21 % >> times = [ 0 100 200 300 400 500 ]
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22 % >> timeaverage(a, plist('times', times))
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23 % >> timeaverage(a, plist('start', 0, 'duration', 100, 'decay', 10, 'repetitions', 3))
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24 % >> timeaverage(a, plist('times', times, 'function', 'center'))
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25 % >> timeaverage(a, plist('times', times, 'function', @mean))
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26 % >> timeaverage(a, plist('times', times, 'xfunction', @min, 'yfunction', @mean))
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27 %
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28 % NOTES: The intervals are defined as ti <= x < te where ti is the start
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29 % time and te is the end time of each interval. If not specified the TIMES
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30 % vector is constructed from other parameters using the following schema
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31 % repeated accordingly a number of times specified with the REPETITIONS
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32 % parameter.
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33 %
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34 % settling duration decay settling duration
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35 % |------------|##############|---------|------------|##############|---
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36 % START
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37 %
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38 %
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39 % VERSION: $Id: timeaverage.m,v 1.10 2011/05/16 09:31:35 mauro Exp $
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40 %
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41 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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42
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43 function varargout = timeaverage(varargin)
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44
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45 % check if this is a call for parameters
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46 if utils.helper.isinfocall(varargin{:})
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47 varargout{1} = getInfo(varargin{3});
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48 return
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49 end
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50
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51 import utils.const.*
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52 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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53
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54 % collect input variable names
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55 in_names = cell(size(varargin));
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56 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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57
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58 % collect all AOs and plists
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59 [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
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60 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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61
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62 % decide on a deep copy or a modify
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63 bs = copy(as, nargout);
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64
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65 % accept spaces dashes or underscores
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66 pl = fixpnames(pl);
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67
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68 % combine plists
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69 pl = combine(pl, getDefaultPlist());
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70
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71 % splitting by time takes the precedence
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72 times = find(pl, 'times');
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73
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74 % otherwise construct a times vector based on other parameters
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75 if isempty(times)
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76 start = find(pl, 'start', find(pl, 'start time'));
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77 repeat = find(pl, 'repetitions');
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78 duration = find(pl, 'duration');
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79 settling = find(pl, 'settling', find(pl, 'settling time'));
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80 decay = find(pl, 'decay', find(pl, 'decay time'));
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81
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82 times = zeros(repeat*2, 1);
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83 for kk = 1:repeat
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84 times(2*kk-1) = start + settling*kk + duration*(kk-1) + decay*(kk-1);
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85 times(2*kk) = start + settling*kk + duration*kk + decay*(kk-1);
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86 end
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87 end
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88
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89 % check that the times vector as the right dimensions
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90 if mod(numel(times), 2)
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91 error('### times defines times intervals with an even number of points');
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92 end
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93
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94 % select which functions to apply to the data stretches
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95 method = lower(find(pl, 'method'));
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96 funct = find(pl, 'function');
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97 if isempty(funct)
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98 funct = method;
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99 end
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100 xfunct = find(pl, 'xfunction', funct);
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101 yfunct = find(pl, 'yfunction', funct);
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102 if isempty(xfunct)
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103 xfunct = funct;
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104 end
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105 if isempty(yfunct)
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106 yfunct = funct;
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107 end
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108
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109 % loop over input AOs
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110 for jj = 1:numel(bs)
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111
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112 % check input data
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113 if ~isa(bs(jj).data, 'tsdata')
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114 warning('LTPDA:isNotTsdata', '!!! %s is not a tsdata AO and will be ingnored', bs(jj).name);
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115 continue;
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116 end
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117
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118 [xmean, ymean, dy] = split_and_apply(bs(jj).x, bs(jj).y, times, xfunct, yfunct);
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119
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120 % assign values
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121 bs(jj).setXY(xmean, ymean);
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122 bs(jj).setDy(dy);
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123
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124 % set name
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125 bs(jj).name = sprintf('%s(%s)', mfilename, ao_invars{jj});
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126 % add history
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127 bs(jj).addHistory(getInfo('None'), pl, ao_invars(jj), bs(jj).hist);
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128
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129 end % loop over analysis objects
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130
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131 % set output
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132 if nargout == numel(bs)
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133 % list of outputs
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134 for ii = 1:numel(bs)
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135 varargout{ii} = bs(ii);
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136 end
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137 else
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138 % single output
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139 varargout{1} = bs;
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140 end
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141 end
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142
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143
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144 function ii = getInfo(varargin)
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145 if nargin == 1 && strcmpi(varargin{1}, 'None')
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146 sets = {};
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147 pl = [];
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148 else
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149 sets = {'Default'};
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150 pl = getDefaultPlist;
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151 end
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152 % build info object
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153 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: timeaverage.m,v 1.10 2011/05/16 09:31:35 mauro Exp $', sets, pl);
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154 % set the default property of the method as modifier or not
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155 ii.setModifier(true);
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156 % set the minumum number of inputs and outputs for the block
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157 ii.setArgsmin(1);
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158 ii.setOutmin(1);
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159 end
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160
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161
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162 function plout = getDefaultPlist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
163 persistent pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
164 if exist('pl', 'var')==0 || isempty(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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165 pl = buildplist();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
166 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
167 plout = pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
168 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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169
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
170 function pl = buildplist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
171 pl = plist;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
172
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
173 % method
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
174 p = param({'method','Reduction method to apply to data stretches.'}, ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
175 {1, {'MEAN', 'MEDIAN', 'MAX', 'MIN', 'RMS', 'CENTER'}, paramValue.SINGLE});
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
176 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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177
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
178 % function
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
179 p = param({'function', ['Function to apply to data stretches. It can be' ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
180 ' a function name or a function handle to a function that accepts'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
181 ' a vector and returns a scalar.']}, paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
182 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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183
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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184 % x function
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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185 p = param({'xfunction', ['Function to apply to X data stretches. It can be' ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
186 ' a function name or a function handle to a function that accepts'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
187 ' a vector and returns a scalar.']}, paramValue.EMPTY_DOUBLE);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
188 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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189
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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190 % y function
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
191 p = param({'yfunction', ['Function to apply to Y data stretches. It can be' ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
192 ' a function name or a function handle to a function that accepts'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
193 ' a vector and returns a scalar.']}, paramValue.EMPTY_DOUBLE);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
194 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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195
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
196 % times
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
197 p = param({'times', 'An array of start-stop times to split by.'}, paramValue.DOUBLE_VALUE([]));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
198 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
199
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
200 % start time
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
201 p = param({'start time', 'Start time of the measurement.'}, paramValue.DOUBLE_VALUE(0));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
202 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
203
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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204 % duration
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
205 p = param({'duration', 'Duration of each cicle.'}, paramValue.DOUBLE_VALUE(0));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
206 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
207
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
208 % repetitions
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
209 p = param({'repetitions', 'Number of cycles.'}, paramValue.DOUBLE_VALUE(1));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
210 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
211
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
212 % settling time
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
213 p = param({'settling time', 'Settling time in each cicle.'}, paramValue.DOUBLE_VALUE(0));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
214 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
215
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
216 % decay time
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
217 p = param({'decay time', 'Decay time in each cicle.'}, paramValue.DOUBLE_VALUE(0));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
218 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
219
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
220 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
221
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
222
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
223 function pl = fixpnames(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
224 % replace underscores and dashes in parameters names with spaces
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
225 if isa(pl, 'plist')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
226 for ii = 1:pl.nparams
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
227 pl.params(ii).setKey(strrep(strrep(pl.params(ii).key, '_', ' '), '-', ' '));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
228 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
229 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
230 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
231
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
232
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
233 function xmean = center(x) %#ok<DEFNU>
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
234 % computes the center of an interval defined by
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
235 % the minimum and maximum values in an array
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
236 xmean = mean([min(x) max(x)]);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
237 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
238
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
239
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
240 function [xmean, ymean, dy] = split_and_apply(x, y, times, xfunct, yfunct)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
241
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
242 % number of intervals
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
243 nint = numel(times) / 2;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
244
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
245 xmean = zeros(nint, 1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
246 ymean = zeros(nint, 1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
247
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
248 % for the mean we are able to compute uncertainty too
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
249 if ischar(yfunct) && strcmp(yfunct, 'mean')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
250 dy = zeros(nint, 1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
251 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
252 dy = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
253 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
254
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
255 % loop over the intervals
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
256 for kk = 1:nint
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
257
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
258 % create index of the interval
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
259 is = times(2*kk-1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
260 ie = times(2*kk);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
261 idx = x >= is & x < ie;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
262
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
263 % apply functions to interval
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
264 xmean(kk) = feval(xfunct, x(idx));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
265 ymean(kk) = feval(yfunct, y(idx));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
266
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
267 if ~isempty(dy)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
268 % compute uncertainty as the standard deviation of the mean
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
269 dy(kk) = std(y(idx)) / sqrt(length(x(idx)));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
270 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
271
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
272 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
273 end