meeg_utils.steps.Resample#

class meeg_utils.steps.Resample(sfreq, *, npad='auto', window='auto', method='fft', n_jobs=None)[source]#

Resample the data.

Thin wrapper of mne.io.Raw.resample(), which applies its own anti-aliasing filter; annotations and events keep their timing.

Parameters:

  • sfreq (float) – New sampling frequency in Hz.

  • npad (int | str) – Padding.

  • window (str) – Frequency-domain window.

  • method ({"fft", "polyphase"}) – Resampling method.

  • n_jobs (int | str | None) – Parallel jobs, or "cuda".

qc_#

sfreq_before and sfreq_after.

Type:

dict

__init__(sfreq, *, npad='auto', window='auto', method='fft', n_jobs=None)[source]#

Methods

__init__(sfreq, *[, npad, window, method, ...])

fit(inst[, y, system])

Learn the step's state from the data.

fit_transform(inst[, y, system, copy])

Fit the step on the data and transform the same data.

get_metadata_routing()

Get metadata routing of this object.

get_params([deep])

Get parameters for this estimator.

plot([kind, inst])

Draw quality-control figures.

set_fit_request(*[, inst, system])

Configure whether metadata should be requested to be passed to the fit method.

set_params(**params)

Set the parameters of this estimator.

set_transform_request(*[, copy, inst])

Configure whether metadata should be requested to be passed to the transform method.

transform(inst, *[, copy])

Apply the fitted step to the data.

Attributes

accepts

Data types the step accepts.

adds_annotations

Whether the step may add BAD_ annotations (existing ones are kept).

changes_channels

Whether the step may add, drop or reorder channels.

changes_times

Whether the step may change the time axis (e.g. resampling, cropping).

drops_epochs

Whether the step may drop epochs (e.g. artifact rejection).

plot_kinds

kind -> whether it needs data (inst).

returns

Data type the step returns; None means the same type as its input.

systems

Acquisition systems the step applies to; None means all systems.
accepts: ClassVar[tuple[type, ...]] = (<class 'mne.io.base.BaseRaw'>, <class 'mne.epochs.BaseEpochs'>, <class 'mne.evoked.Evoked'>)#

Data types the step accepts.

changes_times: ClassVar[bool] = True#

Whether the step may change the time axis (e.g. resampling, cropping).