title: Combination Operators on Sensors Arrays Data
body: <p>Is there any standardized operators over data from arrays of sensors?</p>
  
  <p>I am normally dealing with sensors data in the form of <code>time + channels</code>. The time is a timestamp, and the channels are the available data for these timestamps. All these fields are numeric, no strings involved.</p>
  
  <p>Normally I have to mix those data objects in different ways. Let's suppose <code>M1</code> is size <code>m1xn1</code> and <code>M2</code> is size <code>m2xn2</code>:</p>
  
  <ul>
  <li>Combine rows of data from the same channels and different timestamps (i.e. <code>n1 == n2</code>). This leads to a vertical concatenation <code>[M1; M2]</code>.</li>
  <li>Combine columns of data from the same timestamps and different channels, (i.e. <code>m1 == m2</code>). This leads to a horizontal concatenation <code>[M1 M2]</code>.</li>
  </ul>
  
  <p>These operators are trivial and well defined.</p>
  
  <p>When I have slight differences, for example, a few additional samples in <code>M1</code> or <code>M2</code>, everything turns complicated and I have to think in weird schemes to perform such operations, such as these:</p>
  
  <ul>
  <li>Cleaning the exceeding samples on <code>M1</code> or <code>M2</code>, for matching the dimensions.</li>
  <li>Calculate an aggregated timestamp, obtaining a <code>unique(sort())</code> on the timestamps, and then apply a union like in a SQL <code>JOIN</code> sentence.</li>
  <li>Aggregate the data on <code>M1</code> or <code>M2</code>, this is, reducing <code>m1</code> or <code>m2</code> to a smaller figure, resampling the timescale, and then apply an aggregation like in a SQL <code>GROUP</code> sentence.</li>
  </ul>
  
  <p>I cannot think of a unique and definite function to combine this sort of data. How can I do this?</p>