findVectorIndices

  findVectorIndices converts time to the indices into a waveform vector

  Example:
  [n1 n2 epoch]=findVectorIndices(channel, start, stop)
  matrix=findVectorIndices(channel, start, stop)

  where:
    channel is a sigTOOL channel object
    start is the time of the first sample and must fall within a valid
            data epoch for the channel or an error will result
    stop is valid the time to search to for valid data

  n1 and n2 are the indices into the vector (epoch) corresponding to the
  times:
                        start <= t < stop
  for continuous waveforms or
                        start <= t <= stop
  for episodic waveforms and will be limited to (n1 >= 1) and
  (n2<=epoch length). 


  start and stop may be vectors, in which case n1, n2 and epoch will be
  vectors with one entry for each of the specified data periods.

  If only one output is requested, this will be a 3-column matrix
  containing n1, n2 and epoch in each row.

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  Continuous waveforms
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  If channel contains a continuous waveform (i.e. a single vector of adc
  data), n1 and n2 are simply linear indices into the the vector and epoch
  will always be equal to 1.
  n1 and n2 will always be aligned on subchannel of multiplexed data.

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  Episodic sampled waveforms
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  Epoch and n1, n2 can be used for subscripted indexing into the adc field.
  n1 and n2 give the rows and epoch the columns. Thus, n1 and n2 are the
  indices into the column vector of data representing the epoch e.g.
               [n1 n2 epoch]=findVectorIndices(channels{1}, 0.2, 0.3)
  The relevant adc data may be extracted with:
               data=channels{1}.adc(n1:n2, epoch)

  The exact sample times may be retrieved using convIndex2Time e.g
               t1=convIndex2Time(channels{1}, n1, epoch)
  With episodically sampled multiplexed data, n1 will always be aligned on
  subchannel 1. n2 will be aligned on subchannel 1 unless stop exceeds the
  epoch time in which case n2 will be aligned on the highest numbered
  subchannel and will be limited to the length of the data. This makes data
  extraction simpler, e.g. to extract subchannel 2 of 4:
           [n1 n2 epochs]=findVectorIndices(channels{1}, 0.2, 0.3);
           data=channels{1}.adc(n1+1:4:n2, epochs)

  See also convIndex2Time, ind2sub, sub2ind

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  Author: Malcolm Lidierth 09/06
  Copyright © King’s College London 2006-8
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  Acknowledgements:
  Revisions: