mne.time_frequency.CrossSpectralDensity#

class mne.time_frequency.CrossSpectralDensity(data, ch_names, frequencies, n_fft, tmin=None, tmax=None, projs=None)[source]#

Cross-spectral density.

Given a list of time series, the CSD matrix denotes for each pair of time series, the cross-spectral density. This matrix is symmetric and internally stored as a vector.

This object can store multiple CSD matrices: one for each frequency. Use .get_data(freq) to obtain an CSD matrix as an ndarray.

Parameters:

datandarray, shape ((n_channels**2 + n_channels) // 2, n_frequencies): For each frequency, the cross-spectral density matrix in vector format.
ch_nameslist of str: List of string names for each channel.
frequenciesfloat | list of float | list of list of float: Frequency or frequencies for which the CSD matrix was calculated. When averaging across frequencies (see the CrossSpectralDensity.mean() function), this will be a list of lists that contains for each frequency bin, the frequencies that were averaged. Frequencies should always be sorted.
n_fftint: The number of FFT points or samples that have been used in the computation of this CSD.
tminfloat | None: Start of the time window for which CSD was calculated in seconds. Can be None (the default) to indicate no timing information is available.
tmaxfloat | None: End of the time window for which CSD was calculated in seconds. Can be None (the default) to indicate no timing information is available.
projslist of Projection | None: List of projectors to apply to timeseries data when using this CSD object to compute a DICS beamformer. Defaults to None, which means no projectors will be applied.

Attributes:

n_channels: Number of time series defined in this CSD object.

Methods

`__getitem__`(sel)	Subselect frequencies.
`__len__`()	Return number of frequencies.
`copy`()	Return copy of the CrossSpectralDensity object.
`get_data`([frequency, index, as_cov])	Get the CSD matrix for a given frequency as NumPy array.
`mean`([fmin, fmax])	Calculate the mean CSD in the given frequency range(s).
`pick_channels`(ch_names[, ordered])	Pick channels from this cross-spectral density matrix.
`pick_frequency`([freq, index])	Get a CrossSpectralDensity object with only the given frequency.
`plot`([info, mode, colorbar, cmap, n_cols, show])	Plot CSD matrices.
`save`(fname, *[, overwrite, verbose])	Save the CSD to an HDF5 file.
`sum`([fmin, fmax])	Calculate the sum CSD in the given frequency range(s).

See also

csd_fourier
csd_multitaper
csd_morlet
csd_array_fourier
csd_array_multitaper
csd_array_morlet

__getitem__(sel)[source]#

Subselect frequencies.

Parameters:

selndarray: Array of frequency indices to subselect.

Returns:

csdinstance of CrossSpectralDensity: A new CSD instance with the subset of frequencies.

__len__()[source]#

Return number of frequencies.

Returns:

n_freqsint: The number of frequencies.

copy()[source]#

Return copy of the CrossSpectralDensity object.

Returns:

copyinstance of CrossSpectralDensity: A copy of the object.

get_data(frequency=None, index=None, as_cov=False)[source]#

Get the CSD matrix for a given frequency as NumPy array.

If there is only one matrix defined in the CSD object, calling this method without any parameters will return it. If multiple matrices are defined, use either the frequency or index parameter to select one.

Parameters:

frequencyfloat | None: Return the CSD matrix for a specific frequency. Only available when no averaging across frequencies has been done.
indexint | None: Return the CSD matrix for the frequency or frequency-bin with the given index.
as_covbool: Whether to return the data as a numpy array (False, the default), or pack it in a mne.Covariance object (True).

New in v0.20.

Returns:

csdndarray, shape (n_channels, n_channels) | instance of Covariance: The CSD matrix corresponding to the requested frequency.

See also

pick_frequency

mean(fmin=None, fmax=None)[source]#

Calculate the mean CSD in the given frequency range(s).

Parameters:

fminfloat | list of float | None: Lower bound of the frequency range in Hertz. Defaults to the lowest frequency available. When a list of frequencies is given, these are used as the lower bounds (inclusive) of frequency bins and the mean is taken for each bin.
fmaxfloat | list of float | None: Upper bound of the frequency range in Hertz. Defaults to the highest frequency available. When a list of frequencies is given, these are used as the upper bounds (inclusive) of frequency bins and the mean is taken for each bin.

Returns:

csdinstance of CrossSpectralDensity: The CSD matrix, averaged across the given frequency range(s).

Examples using mean:

Compute a cross-spectral density (CSD) matrix

Compute source power using DICS beamformer

property n_channels#: Number of time series defined in this CSD object.

pick_channels(ch_names, ordered=False)[source]#

Pick channels from this cross-spectral density matrix.

Parameters:

ch_nameslist of str: List of channels to keep. All other channels are dropped.
orderedbool: If True (default False), ensure that the order of the channels matches the order of ch_names.

Returns:

csdinstance of CrossSpectralDensity.: The modified cross-spectral density object.

Notes

Operates in-place.

New in v0.20.0.

pick_frequency(freq=None, index=None)[source]#

Get a CrossSpectralDensity object with only the given frequency.

Parameters:

freqfloat | None: Return the CSD matrix for a specific frequency. Only available when no averaging across frequencies has been done.
indexint | None: Return the CSD matrix for the frequency or frequency-bin with the given index.

Returns:

csdinstance of CrossSpectralDensity: A CSD object containing a single CSD matrix that corresponds to the requested frequency or frequency-bin.

See also

get_data

plot(info=None, mode='csd', colorbar=True, cmap='viridis', n_cols=None, show=True)[source]#

Plot CSD matrices.

A sub-plot is created for each frequency. If an info object is passed to the function, different channel types are plotted in different figures.

Parameters:

infomne.Info | None: The mne.Info object with information about the sensors and methods of measurement. Used to split the figure by channel-type, if provided. By default, the CSD matrix is plotted as a whole.
mode‘csd’ | ‘coh’: Whether to plot the cross-spectral density (‘csd’, the default), or the coherence (‘coh’) between the channels.
colorbarbool: Whether to show a colorbar. Defaults to True.
cmapstr | None: The matplotlib colormap to use. Defaults to None, which means the colormap will default to matplotlib’s default.
n_colsint | None: CSD matrices are plotted in a grid. This parameter controls how many matrix to plot side by side before starting a new row. By default, a number will be chosen to make the grid as square as possible.
showbool: Whether to show the figure. Defaults to True.

Returns:

figlist of Figure: The figures created by this function.

save(fname, *, overwrite=False, verbose=None)[source]#

Save the CSD to an HDF5 file.

Parameters:

fnamepath-like: The name of the file to save the CSD to. The extension '.h5' will be appended if the given filename doesn’t have it already.
overwritebool: If True (default False), overwrite the destination file if it exists.

New in v1.0.
verbosebool | str | int | None: Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

New in v1.0.

See also

read_csd: For reading CSD objects from a file.

sum(fmin=None, fmax=None)[source]#

Calculate the sum CSD in the given frequency range(s).

If the exact given frequencies are not available, the nearest frequencies will be chosen.

Parameters:

fminfloat | list of float | None: Lower bound of the frequency range in Hertz. Defaults to the lowest frequency available. When a list of frequencies is given, these are used as the lower bounds (inclusive) of frequency bins and the sum is taken for each bin.
fmaxfloat | list of float | None: Upper bound of the frequency range in Hertz. Defaults to the highest frequency available. When a list of frequencies is given, these are used as the upper bounds (inclusive) of frequency bins and the sum is taken for each bin.

Returns: