title: SAX time series representation in R using the jmotif package
body: <p>I am trying to represent a number of time series plots using SAX so that I can mine them for similarities. I am using the jmotif package in R:</p>
  
  <pre><code>#Create an example dataframe
  example1 &lt;- data.frame(flow=c(1.1,2.2,3.3,4.4,5.5,6.6),
                     weight1=c(7.1,7.2,7.3,7.4,7.5,7.6), 
                     weight2=c(8.1,8.2,8.3,8.4,8.5,8.6)) 
  # Create a timeseries object
  examplets1 &lt;- ts(example1, start = 1, end = 6)
  
  #Analysis
  library(jmotif)
  #Normalise the data using Znorm
  examplezn &lt;- znorm(examplets1, threshold = 0.01)
  #Perform piecewise aggregate approximation
  examplepaa &lt;- paa(examplezn, 3)
  #Represent time series as SAX
  sax_via_window(examplepaa, 3, 3, 10, "mindist", 0.1)
  
  #This produces the result
  &gt; sax_via_window(examplepaa, 3, 3, 10, "mindist", 0.1)
  $`0`
  [1] "bgh"
  </code></pre>
  
  <p>I am having trouble interpreting these results. What I would expect is a symbolic representation that I could associate with each column eg.  Flow: acc, weight1: bgh and so on. The real datset would have about 100 columns of ts data!</p>
  
  <p>Am I incorrectly applying the method?</p>
  
  <p>Any help is greatly appreciated</p>