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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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  <title>Constructing AOs from data files (LTPDA Toolbox)</title>
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  <h1 class="title"><a name="f3-12899" id="f3-12899"></a>Constructing AOs from data files</h1>
  <hr>
  
  <p>
	<p>
  You can build AOs from existing ASCII data files. Various formats are supported,
  for example, multiple columns, files containing comments.
</p>
<br>
<h2>Install the data pack</h2>
<br>
<p>
  The data-pack for this training session should be downloaded from the <a href="http://www.lisa.aei-hannover.de/ltpda/training_sessions/training_session_1/training_session_1.html">LTPDA web-site</a>.
  The zip file will expand to a top-level directory. This should contain sub-directories
  for each topic of the training session.
</p>
<p>
  The rest of the tutorial will assume that you have changed directories in MATLAB
  to the data-pack directory so that filenames are relative to that directory. To
  change the working directory of MATLAB, either use the MATLAB interface
  or type
</p>
<div class="fragment"><pre>
  cd /path/to/my/data/pack
</pre></div>
<br>
<h2>Create an AO from a simple ASCII file</h2>
<br>
<p>
  The data-pack contains a simple two-column text file which represents a time-series
  sampled at 10Hz. The first column contains the time-stamps, the second column the amplitude values.
</p>
<p>
  To convert this data file to an AO, use the following command:
</p>
<div class="fragment"><pre>
>> pl = plist(<span class="string">'filename'</span>, <span class="string">'topic1/simpleASCII.txt'</span>, ...
              <span class="string">'columns'</span>, [1 2], ...
              <span class="string">'type'</span>, <span class="string">'tsdata'</span>);
>> a = ao(pl)
M:     constructing from plist
M:     load file: simpleASCII.txt
M:     constructing from filename and/or plist
M:     constructing from data object tsdata
----------- ao 01: simpleASCII.txt_01_02 -----------

       name: simpleASCII.txt_01_02
       data: (0,1.13549060238654) (0.1,2.37202031808076) (0.2,-0.531181753855465) (0.3,1.25684477541224) (0.4,1.30895517480354) ...
             -------- tsdata 01 ------------

                 fs:  10
                  x:  [1000 1], double
                  y:  [1000 1], double
                 dx:  [0 0], double
                 dy:  [0 0], double
             xunits:  []
             yunits:  []
              nsecs:  100
                 t0:  1970-01-01 00:00:00.000
             -------------------------------

       hist: ao / ao / SId: fromDatafile.m,v 1.39 2011/04/18 16:55:26 ingo Exp S-->SId: ao.m,v 1.346 2011/05/07 06:56:17 mauro Exp S
description:
       UUID: bde61c39-2c7e-4e77-9c15-6e6a4cc29e12
----------------------------------------------------
</pre></div>
<p>
  From the output on the screen you can see that
  <ol>
    <li>the name of the AO has automatically been set based on the filename and
    the columns of data loaded</li>
    <li>the sample rate of the data is 10Hz, as expected</li>
    <li>the length of the data is 100s</li>
  </ol>
</p>
<p>
  You can plot this data and see that it is just a randon noise time-series.
</p>
<br>
<h2>Create an AO from a multi-column ASCII file</h2>
<br>
<p>
  The data-pack contains a data file which contains multiple columns of data. Here
  we will load only selected columns from the file and produce multiple AOs, one
  for each column loaded. Column 1 of the file contains the time-stamps; columns
  2-6 contain sine waves at frequencies 1-5Hz.
</p>
<p>
  Let's load the 2Hz and 4Hz sine waves from the file. At the same time, we'll
  give the AOs names, Y units, and descriptions.
</p>
<div class="fragment"><pre>
sigs = ao(plist(<span class="string">'filename'</span>, <span class="string">'topic1/multicolumnASCII.txt'</span>, ...
                <span class="string">'type'</span>, <span class="string">'tsdata'</span>, ...
                <span class="string">'columns'</span>, [1 3 1 5], ...
                <span class="string">'name'</span>, {<span class="string">'sin2'</span>, <span class="string">'sin4'</span>}, ...
                <span class="string">'yunits'</span>, {<span class="string">'m'</span>, <span class="string">'m'</span>}, ...
                <span class="string">'description'</span>, {<span class="string">'sine wave at 2Hz'</span>, <span class="string">'sine wave at 4Hz'</span>}))
</pre></div>
<p>
  You can plot the results and focus on the first 2 seconds of data
</p>
<div class="fragment"><pre>
    sigs.iplot(plist(<span class="string">'XRanges'</span>, [0 2]))
</pre></div>







  </p>

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  <br>
  <table class="nav" summary="Navigation aid" border="0" width=
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    <tr valign="top">
      <td align="left" width="20"><a href="ltpda_training_topic_1_5.html"><img src=
      "b_prev.gif" border="0" align="bottom" alt=
      "Saving and loading AOs"></a>&nbsp;</td>

      <td align="left">Saving and loading AOs</td>

      <td>&nbsp;</td>

      <td align="right">Writing LTPDA scripts</td>

      <td align="right" width="20"><a href=
      "ltpda_training_topic_1_7.html"><img src="b_next.gif" border="0" align=
      "bottom" alt="Writing LTPDA scripts"></a></td>
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