wavelet_scaleogram¶

wavelet_scaleogram(inst: BaseEpochs, f_low: float = 2, f_high: float = 1000, k0: int = 6, n_jobs: int = 1, decim: int = 1, verbose=10) → EpochsTFRArray[source][source]¶

Compute the wavelet scaleogram.

Parameters:

inst (instance of Raw, Epochs, or Evoked) – The instance to compute the wavelet scaleogram for.
f_low (float) – The lowest frequency to compute the scaleogram for.
f_high (float) – The highest frequency to compute the scaleogram for.
k0 (int) – The wavelet parameter.
n_jobs (int) – The number of jobs to run in parallel.
decim (int) – The decimation factor.
verbose (int) – The verbosity level.

Returns:

scaleogram – The wavelet scaleogram.

Return type:

instance of EpochsTFR

Notes

Examples

>>> import mne
>>> from ieeg.io import raw_from_layout
>>> from ieeg.navigate import trial_ieeg
>>> from bids import BIDSLayout
>>> bids_root = mne.datasets.epilepsy_ecog.data_path()
>>> layout = BIDSLayout(bids_root)
>>> raw = raw_from_layout(layout, subject="pt1", preload=True,
... extension=".vhdr", verbose=False)
Reading 0 ... 269079  =      0.000 ...   269.079 secs...
>>> epochs = trial_ieeg(raw, ['AST1,3', 'G16'], (-1, 2), verbose=False)
>>> wavelet_scaleogram(epochs, n_jobs=1, decim=10)
Using data from preloaded Raw for 2 events and 3001 original time points...
    Getting epoch for 85800-88801
    Getting epoch for 90760-93761
0 bad epochs dropped
Data is self data: False
<TFR from Epochs, unknown method | 2 epochs × 98 channels × 46 freqs × ...

Examples using `ieeg.timefreq.utils.wavelet_scaleogram`¶

Time and Frequency Permutation Cluster Statistics

Morlet Wavelet spectrogram plot

wavelet_scaleogram¶

Examples using ieeg.timefreq.utils.wavelet_scaleogram¶

Examples using `ieeg.timefreq.utils.wavelet_scaleogram`¶