| 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.

# datasets.eep

## Module: `datasets.eep`

Inheritance diagram for `mvpa.datasets.eep`:

Dataset that gets its samples from an EEP binary file

## `EEPDataset`

class `mvpa.datasets.eep.``EEPDataset`(samples=None, **kwargs)

  Bases: `mvpa.datasets.channel.ChannelDataset`

  Dataset using a EEP binary file as source.

  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

  See also

  Please refer to the documentation of the base class for more information:

  `ChannelDataset`

  Initialize EEPDataset.

  Parameters:

  - samples (Filename (string) of a EEP binary file or an EEPBin) – object
  - t0 (float) – Reference time of the first timepoint. Can be used to preserve information about the onset of some stimulation. Preferably in seconds.
  - dt (float) – Temporal distance between two timepoints. Has to be given in seconds. Otherwise samplingrate property will not return Hz.
  - channelids (list) – List of channel names.
  - mapper (Instance of Mapper) – This mapper will be embedded in the dataset and is used and updated, by all subsequent mapping or feature selection procedures.
  - data (dict) – Dictionary with an arbitrary number of entries. The value for each key in the dict has to be an ndarray with the same length as the number of rows in the samples array. A special entry in this dictionary is ‘samples’, a 2d array (samples x features). A shallow copy is stored in the object.
  - dsattr (dict) – Dictionary of dataset attributes. An arbitrary number of arbitrarily named and typed objects can be stored here. A shallow copy of the dictionary is stored in the object.
  - dtype (type | None) – If None – do not change data type if samples is an ndarray. Otherwise convert samples to dtype.

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