mne.decoding.
FilterEstimator
(info, l_freq, h_freq, picks=None, filter_length='auto', l_trans_bandwidth='auto', h_trans_bandwidth='auto', n_jobs=1, method='fir', iir_params=None, fir_design='firwin', verbose=None)[source]¶Estimator to filter RtEpochs.
Applies a zero-phase low-pass, high-pass, band-pass, or band-stop filter to the channels selected by “picks”.
l_freq and h_freq are the frequencies below which and above which, respectively, to filter out of the data. Thus the uses are:
- l_freq < h_freq: band-pass filter
- l_freq > h_freq: band-stop filter
- l_freq is not None, h_freq is None: low-pass filter
- l_freq is None, h_freq is not None: high-pass filter
If n_jobs > 1, more memory is required as “len(picks) * n_times” additional time points need to be temporarily stored in memory.
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See also
Notes
This is primarily meant for use in conjunction with
mne.realtime.RtEpochs
. In general it is not recommended in a
normal processing pipeline as it may result in edge artifacts. Use with
caution.
Methods
__hash__ ($self, /) |
Return hash(self). |
fit (epochs_data, y) |
Filter data. |
fit_transform (X[, y]) |
Fit to data, then transform it. |
transform (epochs_data) |
Filter data. |
__hash__
($self, /)¶Return hash(self).
fit
(epochs_data, y)[source]¶Filter data.
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fit_transform
(X, y=None, **fit_params)[source]¶Fit to data, then transform it.
Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.
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