| Multivariate Pattern Analysis in Python

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This content refers to the previous stable release of PyMVPA. Please visit www.pymvpa.org for the most recent version of PyMVPA and its documentation.

# misc.io.eepbin

## Module: `misc.io.eepbin`

Inheritance diagram for `mvpa.misc.io.eepbin`:

Reader for binary EEP files.

## `EEPBin`

class `mvpa.misc.io.eepbin.``EEPBin`(source)

  Bases: `mvpa.misc.io.base.DataReader`

  Read-access to binary EEP files.

  EEP files are used by eeprobe a software for analysing even-related potentials (ERP), which was developed at the Max-Planck Institute for Cognitive Neuroscience in Leipzig, Germany.

  > http://www.ant-neuro.com/products/eeprobe

  EEP files consist of a plain text header and a binary data block in a single file. The header starts with a line of the form

  ‘;%d %d %d %g %g’ % (Nchannels, Nsamples, Ntrials, t0, dt)

  where Nchannels, Nsamples, Ntrials are the numbers of channels, samples per trial and trials respectively. t0 is the time of the first sample of a trial relative to the stimulus onset and dt is the sampling interval.

  The binary data block consists of single precision floats arranged in the following way:

      <trial1,channel1,sample1>,<trial1,channel1,sample2>,...
      <trial1,channel2,sample1>,<trial1,channel2,sample2>,...
      .
      <trial2,channel1,sample1>,<trial2,channel1,sample2>,...
      <trial2,channel2,sample1>,<trial2,channel2,sample2>,...

  Read EEP file and store header and data.

  Parameters: | source (str) – Filename.

  `channels`

    List of channel names

  `dt`

    Time difference between two adjacent samples

  `nchannels`

    Number of channels

  `nsamples`

    Number of trials/samples

  `ntimepoints`

    Number of data timepoints

  `t0`

    Relative start time of sampling interval

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