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Update ao_model_retrieve_in_timespan
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
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1 <!-- $Id: ao_convert_content.html,v 1.3 2008/03/03 09:08:10 hewitson Exp $ -->
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2 <p>
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3 In some cases it is desirable to build AOs 'by hand' from existing data files. If the data file
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4 doesn't conform to one of the existing AO constructors, then a conversion script can easily be
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5 written to create AOs from your data files.
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6 </p>
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7 <p>The following example shows how to convert an ASCII data file into Analysis Objects. The data file
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8 has 4 columns representing 4 different data channels. All 4 channels are sampled at the same rate of
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9 10Hz. The conversion function returns 4 AOs.</p>
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10
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11 <div class="fragment"><pre> <span class="code"> function b = myConverter(filename, fs)</span>
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12
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13 <span class="comment">% MYCONVERTER converts a multi-column ASCII data file into multiple AOs.</span>
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14 <span class="comment">%</span>
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15 <span class="comment">% usage: b = myConverter(filename, fs)</span>
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16 <span class="comment">%</span>
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17 <span class="comment">% Inputs:</span>
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18 <span class="comment">% filename - name of input data file</span>
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19 <span class="comment">% fs - sample rate of input data</span>
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20 <span class="comment">%</span>
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21 <span class="comment">% Outputs:</span>
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22 <span class="comment">% b - vector of AOs</span>
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23 <span class="comment">%</span>
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24 <span class="comment">%</span>
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25
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26 <span class="comment">% Load the data from text file</span>
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27 data_in = load(filename);
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28 ncols = size(data_in, 2);
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29
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30 <span class="comment">% Create AOs</span>
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31 b = [];
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32 <span class="keyword">for</span> j=1:ncols
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33
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34 <span class="comment">% Get this column of data</span>
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35 d = data_in(:,j);
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36
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37 <span class="comment">% name for this data</span>
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38 dataName = [<span class="string">'column'</span> num2str(j)];
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39
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40 <span class="comment">% Make tsdata object</span>
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41 ts = tsdata(d, fs);
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42 <span class="comment">% set name of data object</span>
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43 ts = set(ts, <span class="string">'name'</span>, dataName);
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44 <span class="comment">% set xunits to seconds</span>
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45 ts = set(ts, <span class="string">'xunits'</span>, <span class="string">'s'</span>);
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46 <span class="comment">% set xunits to Volts</span>
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47 ts = set(ts, <span class="string">'yunits'</span>, <span class="string">'V'</span>);
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48
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49 <span class="comment">% make history object</span>
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50 h = history(<span class="string">'myConverter'</span>, <span class="string">'0.1'</span>, plist(param(<span class="string">'filename'</span>, filename)));
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51
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52 <span class="comment">% make AO</span>
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53 a = ao(ts, h);
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54
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55 <span class="comment">% set AO name</span>
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56 a = set(a, <span class="string">'name'</span>, dataName);
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57
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58 <span class="comment">% add to output vector</span>
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59 b = [b a];
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60
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61 <span class="keyword">end</span></pre></div>
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62
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63 <br>
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64 <p>
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65 The script works by loading the four columns of data from the ASCII file into a matrix. The
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66 script then loops over the number of columns and creates an AO for each column.
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67 </p>
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68 <p>First a time-series (<tt>tsdata</tt>) object is made from the data in a column and given the
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69 input sample rate of the data. The 'name', 'xunits', and 'yunits' fields of the time-series data
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70 object are then set using calls to the <tt>set</tt> method of the <tt>tsdata</tt> class.
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71 </p>
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72 <p>
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73 Next a history object is made with its 'name' set to 'myConverter', the version set to '0.1',
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74 and the input filename is recorded in a parameter list attached to the history object.
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75 </p>
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76 <p>
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77 Following the creation of the data object and the history object, we can then create an
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78 Analysis Object. The name of the AO is then set and the object is added to a vector that is
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79 output by the function.
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80 </p>