Source Code for Module mvpa.misc.io.eepbin

  1  # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- 
  2  # vi: set ft=python sts=4 ts=4 sw=4 et: 
  3  ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ## 
  4  # 
  5  #   See COPYING file distributed along with the PyMVPA package for the 
  6  #   copyright and license terms. 
  7  # 
  8  #   Derived from the EEP binary reader of the pybsig toolbox 
  9  #   (C) by Ingo Fruend 
 10  # 
 11  ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ## 
 12  """Reader for binary EEP files.""" 
 13   
 14  __docformat__ = 'restructuredtext' 
 15   
 16  import numpy as N 
 17  from mvpa.misc.io import DataReader 
 18   
 19   
 20 -class EEPBin(DataReader): 
 21      """Read-access to binary EEP files. 
 22   
 23      EEP files are used by *eeprobe* a software for analysing even-related 
 24      potentials (ERP), which was developed at the Max-Planck Institute for 
 25      Cognitive Neuroscience in Leipzig, Germany. 
 26   
 27        http://www.ant-neuro.com/products/eeprobe 
 28   
 29      EEP files consist of a plain text header and a binary data block in a 
 30      single file. The header starts with a line of the form 
 31   
 32      ';%d %d %d %g %g' % (Nchannels, Nsamples, Ntrials, t0, dt) 
 33   
 34      where Nchannels, Nsamples, Ntrials are the numbers of channels, samples 
 35      per trial and trials respectively. t0 is the time of the first sample 
 36      of a trial relative to the stimulus onset and dt is the sampling interval. 
 37   
 38      The binary data block consists of single precision floats arranged in the 
 39      following way:: 
 40   
 41          <trial1,channel1,sample1>,<trial1,channel1,sample2>,... 
 42          <trial1,channel2,sample1>,<trial1,channel2,sample2>,... 
 43          . 
 44          <trial2,channel1,sample1>,<trial2,channel1,sample2>,... 
 45          <trial2,channel2,sample1>,<trial2,channel2,sample2>,... 
 46      """ 
 47 -    def __init__(self, source): 
 48          """Read EEP file and store header and data. 
 49   
 50          :Parameter: 
 51            source : str 
 52              Filename. 
 53          """ 
 54          # init base class 
 55          DataReader.__init__(self) 
 56          # temp storage of number of samples 
 57          nsamples = None 
 58          # non-critical header components stored in temp dict 
 59          hdr = {} 
 60   
 61          infile = open(source, "r") 
 62   
 63          # read file the end of header of EOF 
 64          while True: 
 65              # one line at a time 
 66              line = infile.readline() 
 67   
 68              # stop if EOH or EOF 
 69              if not line or line.startswith(';EOH;'): 
 70                  break 
 71   
 72              # no crap! 
 73              line = line.strip() 
 74   
 75              # all but first line as colon 
 76              if not line.count(':'): 
 77                  # top header 
 78                  l = line.split() 
 79                  # extract critical information 
 80                  self._props['nchannels'] = int(l[0][1:]) 
 81                  self._props['ntimepoints'] = int(l[1]) 
 82                  self._props['t0'] = float(l[3]) 
 83                  self._props['dt'] = float(l[4]) 
 84                  nsamples = int(l[2]) 
 85              else: 
 86                  # simply store non-critical extras 
 87                  l = line.split(':') 
 88                  key = l[0].lstrip(';') 
 89                  value = ':'.join(l[1:]) 
 90                  hdr[key] = value 
 91   
 92          # post process channel name info -> list 
 93          if hdr.has_key('channels'): 
 94              self._props['channels'] = hdr['channels'].split() 
 95   
 96          self._data = \ 
 97              N.reshape(N.fromfile(infile, dtype='f'), \ 
 98                  (nsamples, 
 99                   self._props['nchannels'], 
100                   self._props['ntimepoints'])) 
101   
102          # cleanup 
103          infile.close() 
104   
105   
106      nchannels = property(fget=lambda self: self._props['nchannels'], 
107                           doc="Number of channels") 
108      ntimepoints  = property(fget=lambda self: self._props['ntimepoints'], 
109                           doc="Number of data timepoints") 
110      nsamples   = property(fget=lambda self: self._data.shape[0], 
111                           doc="Number of trials/samples") 
112      t0        = property(fget=lambda self: self._props['t0'], 
113                           doc="Relative start time of sampling interval") 
114      dt        = property(fget=lambda self: self._props['dt'], 
115                           doc="Time difference between two adjacent samples") 
116      channels  = property(fget=lambda self: self._props['channels'], 
117                           doc="List of channel names") 
118