Package mvpa :: Package misc :: Package io :: Module eepbin :: Class EEPBin
[hide private]
[frames] | no frames]

Class EEPBin

source code


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>,...
Instance Methods [hide private]
 
__init__(self, source)
Read EEP file and store header and data.
source code
Class Variables [hide private]
  nchannels = property(fget= lambda self: self._props ['nchannel...
  ntimepoints = property(fget= lambda self: self._props ['ntimep...
  nsamples = property(fget= lambda self: self._data.shape [0], d...
  t0 = property(fget= lambda self: self._props ['t0'], doc= "Rel...
  dt = property(fget= lambda self: self._props ['dt'], doc= "Tim...
  channels = property(fget= lambda self: self._props ['channels'...
Class Variable Details [hide private]

nchannels

Value:
property(fget= lambda self: self._props ['nchannels'], doc= "Number of\
 channels")

ntimepoints

Value:
property(fget= lambda self: self._props ['ntimepoints'], doc= "Number \
of data timepoints")

nsamples

Value:
property(fget= lambda self: self._data.shape [0], doc= "Number of tria\
ls/samples")

t0

Value:
property(fget= lambda self: self._props ['t0'], doc= "Relative start t\
ime of sampling interval")

dt

Value:
property(fget= lambda self: self._props ['dt'], doc= "Time difference \
between two adjacent samples")

channels

Value:
property(fget= lambda self: self._props ['channels'], doc= "List of ch\
annel names")