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PyMVPA: Python MultiVariate Pattern Analysis
Package mvpa :: Package datasets :: Module channel :: Class ChannelDataset
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Class ChannelDataset

source code

Dataset handling data structured into channels.

Channels are assumes to contain several timepoints, thus this Dataset stores some additional properties (reference time t0, temporal distance of two timepoints dt and channelids (names)).

Instance Methods [hide private]
 
__init__(self, samples=None, dsattr=None, t0=None, dt=None, channelids=None, **kwargs)
Initialize ChannelDataset.		 source code
 
substractBaseline(self, t=None)
Substract mean baseline signal from the each timepoint.		 source code
 
resample(self, nt=None, sr=None, dt=None, window='ham', inplace=True, **kwargs)
Convenience method to resample data sample channel-wise.		 source code

Inherited from mapped.MappedDataset: mapForward, mapReverse, mapSelfReverse, selectFeatures

Class Variables [hide private]
  __doc__ = enhancedDocString('ChannelDataset', locals(), Mapped...
  channelids = property(fget= lambda self: self._dsattr ['ch_ids...
  t0 = property(fget= lambda self: self._dsattr ['ch_t0'], doc= ...
  dt = property(fget= lambda self: self._dsattr ['ch_dt'], doc= ...
  samplingrate = property(fget= lambda self: 1.0/ self._dsattr [...

Inherited from mapped.MappedDataset: O, mapper, samples_original

Method Details [hide private]

__init__(self, samples=None, dsattr=None, t0=None, dt=None, channelids=None, **kwargs)
(Constructor)

source code 
Initialize ChannelDataset.
Parameters:
  • samples, ndarray - Three-dimensional array: (samples x channels x timepoints).
  • 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.
Overrides: mapped.MappedDataset.__init__

substractBaseline(self, t=None)

source code 

Substract mean baseline signal from the each timepoint.

The baseline is determined by computing the mean over all timepoints specified by t.

The samples of the dataset are modified in-place and nothing is returned.

resample(self, nt=None, sr=None, dt=None, window='ham', inplace=True, **kwargs)

source code 

Convenience method to resample data sample channel-wise.

Resampling target can be specified by number of timepoint or temporal distance or sampling rate.

Please note that this method only operates on ChannelDataset and always returns such.

Returns:
ChannelDataset

Parameters:

nt: int
Number of timepoints to resample to.
dt: float
Temporal distance of samples after resampling.
sr: float
Target sampling rate.
inplace : bool
If inplace=False, it would create and return a new dataset with new samples
**kwargs:
All additional arguments are passed to resample() from scipy.signal


Class Variable Details [hide private]

__doc__

Value:
enhancedDocString('ChannelDataset', locals(), MappedDataset)

channelids

Value:
property(fget= lambda self: self._dsattr ['ch_ids'], doc= 'List of cha\
nnel IDs')

t0

Value:
property(fget= lambda self: self._dsattr ['ch_t0'], doc= 'Temporal pos\
ition of first sample in the ' 'timeseries (in seconds) -- possibly re\
lative ' 'to stimulus onset.')

dt

Value:
property(fget= lambda self: self._dsattr ['ch_dt'], doc= 'Time differe\
nce between two samples ' '(in seconds).')

samplingrate

Value:
property(fget= lambda self: 1.0/ self._dsattr ['ch_dt'], doc= 'Yeah, s\
ampling rate.')

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PyMVPA: Python MultiVariate Pattern Analysis
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