pybispectra.general.Threenorm#

class pybispectra.general.Threenorm(data: ndarray, freqs: ndarray, sampling_freq: int | float, times: ndarray | None = None, verbose: bool = True)[source]#

Class for computing the threenorm.

Parameters:

datandarray, shape of [epochs, channels, frequencies (, times)]: Fourier coefficients.
freqsndarray, shape of [frequencies]: Frequencies (in Hz) in data. Frequencies are expected to be evenly spaced.
sampling_freqint | float: Sampling frequency (in Hz) of the data from which data was derived.
timesndarray, shape of [times] | None: Timepoints (in seconds) in data. If data has a times dimension and times = None, the time of the first sample in data is assumed to be 0 seconds.

Added in version 1.3.
verbosebool (default True): Whether or not to report the progress of the processing.

Attributes:

resultsResultsGeneral: Threenorm results.
datandarray of float, shape of [epochs, channels, frequencies (, times)]: Fourier coefficients.
freqsndarray of float, shape of [frequencies]: Frequencies (in Hz) in data.
sampling_freqint | float: Sampling frequency (in Hz) of the data from which data was derived.
timesndarray, shape of [times] | None: Timepoints (in seconds) in data.
verbosebool: Whether or not to report the progress of the processing.

Methods

`compute`([indices, f1s, f2s, times, n_jobs])	Compute the threenorm, averaged over epochs.
`copy`()	Return a copy of the object.

Notes

Added in version 1.2.

Compute the threenorm, averaged over epochs.

Parameters:

indicestuple of tuple of int, length of 3 | None (default None): Indices of the channels \(k\), \(m\), and \(n\), respectively, to compute the threenorm for. If None, the threenorm for all channel combinations is computed.
f1stuple of int or float, length of 2 | None (default None): Start and end lower frequencies to compute the threenorm for, respectively. If None, all frequencies are used.
f2stuple of int or float, length of 2 | None (default None): Start and end higher frequencies to compute the threenorm for, respectively. If None, all frequencies are used.
timestuple of int or float, length of 2 | None (default None): Start and end times (in seconds) to compute the threenorm for, respectively. If None, all timepoints are used.

Added in version 1.3.
n_jobsint (default 1): The number of jobs to run in parallel. If -1, all available CPUs are used.

Notes

The threenorm, \(\textbf{N}\), [1] has the general form

\(\textbf{N}_{kmn}(f_1,f_2)=(<|\textbf{k}(f_1)|^3><|\textbf{m} (f_2)|^3> <|\textbf{n}(f_2+f_1)|^3>)^{\frac{1}{3}}\) ,

where \(kmn\) is a combination of signals with Fourier coefficients \(\textbf{k}\), \(\textbf{m}\), and \(\textbf{n}\), respectively; \(f_1\) and \(f_2\) correspond to a lower and higher frequency, respectively; and \(<>\) represents the average value over epochs.

The threenorm is computed between all values of f1s and f2s.

Warning

For values of f1s higher than f2s or where f2s + f1s exceeds the Nyquist frequency, a numpy.nan value is returned.

References

copy()[source]#: Return a copy of the object.