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annotate m-toolbox/html_help/help/ug/interp_content.html @ 51:9d5c88356247 database-connection-manager

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Make unit tests database connection parameters configurable
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 07 Dec 2011 17:24:37 +0100
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 <h2>Description</h2>
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2 <p>
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3 Interpolation of data can be done in the LTPDA Toolbox by means of
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4 <a href="matlab:doc('ao/interp')"><tt>interp</tt></a>.
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5 This function interpolates the values in the input AO(s) at new values specified by the
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6 input parameter list.
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7 </p>
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8 <p>
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9 <a href="matlab:doc('ao/interp')"><tt>Interp</tt></a> overloads <tt>interp1</tt> function of
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10 Matlab Signal Processing Toolbox for AOs.
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11 </p>
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12 <br>
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13 <br>
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14 <h2>Syntax</h2>
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15 </p>
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16 <div class="fragment"><pre>
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17 <br>
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18 b = interpolate(a, pl)
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19 </pre>
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20 </div>
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21 <h2>Parameters</h2>
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22 <p>
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23 The following parameters can be set in the method:
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24 <ul>
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25 <li> <tt>vertices</tt> - specify the new vertices to interpolate on </li>
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26 <li> <tt>method</tt> - four methods are available for interpolating data</li>
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27 <ul>
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28 <li> 'nearest'- nearest neighbor interpolation </li>
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29 <li> 'linear' - linear interpolation </li>
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30 <li> 'spline' - spline interpolation (default option) </li>
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31 <li> 'cubic' - shape-preserving piecewise cubic interpolation </li>
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32 </ul>
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33 </ul>
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34 For details see <tt>interp1</tt> help of Matlab.
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35 </p>
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36 <p>
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37 <h2>Examples</h2>
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38 </p>
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39 <p>
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40 1. Interpolation of a sequence of random data at original sampling rate of 1 Hz
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41 by a factor of 10 with no initial phase.
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42 </p>
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43 <div class="fragment"><pre>
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44 <br>
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45 <span class="comment">% Signal generation</span>
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46 pl = plist(<span class="string">'tsfcn'</span>,<span class="string">'sin(2*pi*1.733*t)'</span>,...
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47 <span class="string">'fs'</span>,1,<span class="string">'nsecs'</span>,10,...
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48 <span class="string">'yunits'</span>,<span class="string">'V'</span>);
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49 x = ao(pl);
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50 <span class="comment">% Interpolate on a new time vector</span>
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51 t = linspace(0, x.data.nsecs - 1/x.data.fs, 2*len(x));
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52 pl_spline = plist(<span class="string">'vertices'</span>,t);
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53 pl_nearest = plist(<span class="string">'vertices'</span>,t,<span class="string">'method'</span>,<span class="string">'nearest'</span>);
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54 x_spline = interp(x,pl_spline);
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55 x_nearest = interp(x,pl_nearest);
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56 iplot([x x_spline x_nearest], plist(<span class="string">'Markers'</span>, {<span class="string">'x'</span>, <span class="string">'o'</span>, <span class="string">'+'</span>}, ...
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57 <span class="string">'LineColors'</span>, {<span class="string">'k'</span>, <span class="string">'r'</span>}));
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58 </pre>
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59 </div>
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60 <br>
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61 <br>
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62 <img src="images/interp.png" alt="Interpolate" border="0">