This documentation is for development version 0.18.dev0.

mne.viz.plot_raw_psd

mne.viz.plot_raw_psd(raw, tmin=0.0, tmax=inf, fmin=0, fmax=inf, proj=False, n_fft=None, picks=None, ax=None, color='black', area_mode='std', area_alpha=0.33, n_overlap=0, dB=True, estimate='auto', average=False, show=True, n_jobs=1, line_alpha=None, spatial_colors=None, xscale='linear', reject_by_annotation=True, verbose=None)[source]

Plot the power spectral density across channels.

Different channel types are drawn in sub-plots. When the data has been processed with a bandpass, lowpass or highpass filter, dashed lines indicate the boundaries of the filter (–). The line noise frequency is also indicated with a dashed line (-.).

Parameters:
raw : instance of Raw

The raw instance to use.

tmin : float

Start time for calculations.

tmax : float

End time for calculations.

fmin : float

Start frequency to consider.

fmax : float

End frequency to consider.

proj : bool

Apply projection.

n_fft : int | None

Number of points to use in Welch FFT calculations. Default is None, which uses the minimum of 2048 and the number of time points.

picks : str | list | slice | None

Channels to include. Slices and lists of integers will be interpreted as channel indices. In lists, channel type strings (e.g., ['meg', 'eeg']) will pick channels of those types, channel name strings (e.g., ['MEG0111', 'MEG2623'] will pick the given channels. Can also be the string values “all” to pick all channels, or “data” to pick data channels. None (default) will pick good data channels. Cannot be None if ax is supplied. If both picks and ax are None, separate subplots will be created for each standard channel type (mag, grad, and eeg).

ax : instance of matplotlib Axes | None

Axes to plot into. If None, axes will be created.

color : str | tuple

A matplotlib-compatible color to use. Has no effect when spatial_colors=True.

area_mode : str | None

Mode for plotting area. If ‘std’, the mean +/- 1 STD (across channels) will be plotted. If ‘range’, the min and max (across channels) will be plotted. Bad channels will be excluded from these calculations. If None, no area will be plotted. If average=False, no area is plotted.

area_alpha : float

Alpha for the area.

n_overlap : int

The number of points of overlap between blocks. The default value is 0 (no overlap).

dB : bool

Plot Power Spectral Density (PSD), in units (amplitude**2/Hz (dB)) if dB=True, and estimate='power' or estimate='auto'. Plot PSD in units (amplitude**2/Hz) if dB=False and, estimate='power'. Plot Amplitude Spectral Density (ASD), in units (amplitude/sqrt(Hz)), if dB=False and estimate='amplitude' or estimate='auto'. Plot ASD, in units (amplitude/sqrt(Hz) (db)), if dB=True and estimate='amplitude'.

estimate : str, {‘auto’, ‘power’, ‘amplitude’}

Can be “power” for power spectral density (PSD), “amplitude” for amplitude spectrum density (ASD), or “auto” (default), which uses “power” when dB is True and “amplitude” otherwise.

average : bool

If False (default), the PSDs of all channels is displayed. No averaging is done and parameters area_mode and area_alpha are ignored. When False, it is possible to paint an area (hold left mouse button and drag) to plot a topomap.

show : bool

Show figure if True.

n_jobs : int

Number of jobs to run in parallel.

line_alpha : float | None

Alpha for the PSD line. Can be None (default) to use 1.0 when average=True and 0.1 when average=False.

spatial_colors : bool

Whether to use spatial colors. Only used when average=False.

xscale : str

Can be ‘linear’ (default) or ‘log’.

reject_by_annotation : bool

Whether to omit bad segments from the data while computing the PSD. If True, annotated segments with a description that starts with ‘bad’ are omitted. Has no effect if inst is an Epochs or Evoked object. Defaults to True.

New in version 0.15.0.

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

Returns:
fig : instance of Figure

Figure with frequency spectra of the data channels.