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datasets.channel

Module: datasets.channel

Inheritance diagram for mvpa.datasets.channel:

Dataset handling data structured in channels.

ChannelDataset

class mvpa.datasets.channel.ChannelDataset(samples=None, dsattr=None, t0=None, dt=None, channelids=None, **kwargs)

Bases: mvpa.datasets.mapped.MappedDataset

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)).

See also

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

MappedDataset

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.
• 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.

channelids

List of channel IDs

dt

Time difference between two samples (in seconds).

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

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.

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

Return :

ChannelDataset

samplingrate

Yeah, sampling rate.

substractBaseline(t=None)

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.

Parameters:t (int | float | None) – If an integer, t denotes the number of timepoints in the from the start of each sample to be used to compute the baseline signal. If a floating point value, t is the duration of the baseline window from the start of each sample in whatever unit corresponding to the datasets samplingrate. Finally, if None the t0 property of the dataset is used to determine t as it would have been specified as duration.

t0

Temporal position of first sample in the timeseries (in seconds) – possibly relative to stimulus onset.